IJACSA Vol. 9 Issue 3 (2018)

1

Bitter Melon Crop Yield Prediction using Machine Learning Algorithm

Author 1: Marizel B. Villanueva Author 2: Ma. Louella M. Salenga

This research paper aimed to determine the crop bearing capability of bitter melon or bitter gourd more commonly called “Ampalaya” in the Filipino language. Images of bitter melon leaves were gathered from Ampalaya farms and these were used as main data of the research. The leaves were classified as good and bad through their description. The research used Machine Learning Algorithm through Convolutional Neural Network. Training of data was through the capabilities of Keras, Tensor Flow and Python worked together. In conclusion, increasing number of images could enable a machine to learn the difference between a good and a bad Ampalaya plant when presented an image for prediction.

Agriculture Artificial Intelligence Keras machine learning algorithm machine learning neural network convolutional neural network prediction Python tensor flow

Abstract doi.org/10.14569/IJACSA.2018.090301 PDF

2

Evaluating X-Ray based Medical Imaging Devices with Fuzzy Preference Ranking Organization Method for Enrichment Evaluations

Author 1: Dilber Uzun Ozsahin Author 2: Berna Uzun Author 3: Musa Sani Musa Author 4: Ilker Ozsahin

X-rays are ionizing radiation of very high energy, which are used in the medical imaging field to produce images of diagnostic importance. X-ray-based imaging devices are machines that send ionizing radiation to the patient’s body, and obtain an image which can be used to effectively diagnose the patient. These devices serve the same purpose, only that some are the advanced form of the others and are used for specialized radiological exams. These devices have image quality parameters which need to be assessed in order to portray the efficiency, potentiality and negativity of each. The parameters include sensitivity and specificity, radiation dose delivered to the patient, cost of treatment and machine. The parameters are important in that they affect the patient, the hospital management and the radiation worker. Therefore, this paper incorporates these parameters into fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) multi-criteria decision theory in order to help the decision makers to improve the efficiency of their decision processes, so that they will arrive at the best solution in due course.

X-ray-based imaging devices medical imaging fuzzy PROMETHEE

Abstract doi.org/10.14569/IJACSA.2018.090302 PDF

3

Challenges in Designing Ethical Rules for Infrastructures in Internet of Vehicles

Author 1: Razi Iqbal

Vehicular Ad-hoc Networks (VANETs) have seen significant advancements in technology. Innovation in connectivity and communication has brought substantial capabilities to various components of VANETs such as vehicles, infrastructures, passengers, drivers and affiliated environmental sensors. Internet of Things (IoT) has brought the notion of Internet of Vehicles (IoV) to VANETs where each component of VANET is connected directly or indirectly to the Internet. Vehicles and infrastructures are the key components of a VANET system that can greatly augment the overall experience of the network by integrating the competencies of Vehicle to Vehicle (V2V), Vehicle to Pedestrian (V2P), Vehicle to Sensor (V2S), Vehicle to Infrastructure (V2I) and Infrastructure to Infrastructure (I2I). Internet connectivity in Vehicles and Infrastructures has immensely expanded the potential of developing applications for VANETs under the broad spectrum of IoV. Advent in the use of technology in VANETs requires considerable efforts in scheming the ethical rules for autonomous systems. Currently, there is a gap in literature that focuses on the challenges involved in designing ethical rules or policies for infrastructures, sometimes referred to as Road Side Units (RSUs) for IoVs. This paper highlights the key challenges entailing the design of ethical rules for RSUs in IoV systems. Furthermore, the article also proposes major ethical principles for RSUs in IoV systems that would set foundation for modeling future IoV architectures.

Ethics road side units vehicular ad-hoc networks internet of vehicles intelligent transportation systems

Abstract doi.org/10.14569/IJACSA.2018.090303 PDF

4

Analysis of the Impact of Different Parameter Settings on Wireless Sensor Network Lifetime

Author 1: Muhammad Usman Younus

The importance of wireless sensors is increasing day by day due to their large demand. Sensor networks are facing some issues in which battery lifetime of sensor node is critical. It depends on the nature and application of the wireless sensor network and its different parameters (sampling frequency, transmission frequency, processing power and transmission power). In this paper, we propose a new and realistic model to show the effect of energy consumption on a lifetime of wireless sensor nodes. After analyzing the model behavior, we are able to find out the sensitive parameters that are highly effective for lifetime of sensor nodes.

Wireless sensor network energy consumption lifetime WSN parameters transmission frequency sampling frequency

Abstract doi.org/10.14569/IJACSA.2018.090304 PDF

5

Day-Ahead Load Forecasting using Support Vector Regression Machines

Author 1: Lemuel Clark P. Velasco Author 2: Daisy Lou L. Polestico Author 3: Dominique Michelle M. Abella Author 4: Genesis T. Alegata Author 5: Gabrielle C. Luna

Accurate day-ahead load prediction plays a significant role to electric companies because decisions on power system generations depend on future behavior of loads. This paper presents a strategy for short-term load forecasting that utilizes support vector regression machines. Proper data preparation, model implementation and model validation methods were introduced in this study. The SVRM model being implemented is composed of specific features, parameters, data architecture and kernel to achieve accurate pattern discovery. The developed model was implemented into an electric load forecasting system using the java open source library called LibSVM. To confirm the effectiveness of the proposed model, the performance of the developed model is evaluated through the validation set of the study and compared to other published models. The created SVRM model produced the lowest Mean Average Percentage Error (MAPE) of 1.48% and was found to be a viable forecasting technique for a day-ahead electric load forecasting system.

Support vector regression machines day-ahead load forecasting energy analytics

Abstract doi.org/10.14569/IJACSA.2018.090305 PDF

6

Online Estimation of Wind Turbine Tip Speed Ratio by Adaptive Neuro-Fuzzy Algorithm

Author 1: Aamer Bilal Asghar Author 2: Xiaodong Liu

The efficiency of a wind turbine highly depends on the value of tip speed ratio during its operation. The power coefficient of a wind turbine varies with tip speed ratio. For maximum power extraction, it is very important to hold the tip speed ratio at optimum value and operate the variable-speed wind turbine at its maximum power coefficient. In this paper, an intelligent learning based adaptive neuro-fuzzy inference system (ANFIS) is proposed for online estimation of tip speed ratio (TSR) as a function of wind speed and rotor speed. The system is developed by assigning fuzzy membership functions (MFs) to the input-output variables and artificial neural network (ANN) is applied to train the system using back propagation gradient descent algorithm and least square method. During the training process, the ANN adjusts the shape of MFs by analyzing training data set and automatically generates the decision making fuzzy rules. The simulations are done in MATLAB for standard offshore 5 MW baseline wind turbine developed by national renewable energy laboratory (NREL). The performance of proposed neuro-fuzzy algorithm is compared with conventional multilayer perceptron feed-forward neural network (MLPFFNN). The results show the effectiveness of proposed model. The proposed system is more reliable for accurate estimation of tip speed ratio.

Wind speed rotor speed power coefficient tip speed ratio ANFIS

Abstract doi.org/10.14569/IJACSA.2018.090306 PDF

7

Techniques for Improving the Labelling Process of Sentiment Analysis in the Saudi Stock Market

Author 1: Hamed AL-Rubaiee Author 2: Renxi Qiu Author 3: Khalid Alomar Author 4: Dayou Li

Sentiment analysis is utilised to assess users’ feedback and comments. Recently, researchers have shown an increased interest in this topic due to the spread and expansion of social networks. Users’ feedback and comments are written in unstructured formats, usually with informal language, which presents challenges for sentiment analysis. For the Arabic language, further challenges exist due to the complexity of the language and no sentiment lexicon is available. Therefore, labelling carried out by hand can lead to mislabelling and misclassification. Consequently, inaccurate classification creates the need to construct a relabelling process for Arabic documents to remove noise in labelling. The aim of this study is to improve the labelling process of the sentiment analysis. Two approaches were utilised. First, a neutral class was added to create a framework of reliable Twitter tweets with positive, negative, or neutral sentiments. The second approach was improving the labelling process by relabelling. In this study, the relabelling process applied to only seven random features (positive or negative): “earnings” (ارباح), “losses” (خسائر), “green colour” (باللون_الاخضر), “growing” (زياده), “distribution” (توزيع), “decrease” (انخفاض), “financial penalty” (غرامة), and “delay” (تاجيل). Of the 48 tweets documented and examined, 20 tweets were relabelled and the classification error was reduced by 1.34%.

Opinion mining association rule Arabic language sentiment analysis Twitter

Abstract doi.org/10.14569/IJACSA.2018.090307 PDF

8

Designing of Cell Coverage in Light Fidelity

Author 1: Rabia Riaz Author 2: Sanam Shahla Rizvi Author 3: Farina Riaz Author 4: Sana Shokat

The trend of communication has changed and the internet user demands to have higher data rate and secure communication link. Wireless-Fidelity (Wi-Fi) that uses radio waves for communication has been used as an internet access methodology for many years. Now a new concept of wireless communication is introduced that uses visible light for communication and is known as the Light-Fidelity (Li-Fi). Li-Fi attracted the researchers for its vast advantages over Wi-Fi. Wi-Fi is now an integral part of everyday life. In near future, due to scarcity of spectrum, it would be quite difficult to accommodate new users in limited spectrum of Wi-Fi. To overcome this, Li-Fi is a good option because of its infinite spectrum range, as it uses the visible range of the spectrum. Many researchers discussed that Li-Fi is secure when compared to Wi-Fi. But is it really secure enough? Can anybody access hotspot of Li-Fi? Or is there a need to develop a technique that is used to block the unauthorized access? In this research work, a cellular concept is introduced for the Li-Fi usage in order to increase the security. This research presents a flexible and adjustable cell structure that enhances the security of Li-Fi. The coverage area is shown by utilizing the geometrical structure of the cone and the area of the cone can be controlled. A mechanical system is also installed on the roof to control the coverage area of a Li-Fi by moving LED bulb slightly up and down. A mathematical expression for the proposed coverage area of the cell is provided, which is formed on the ground level by a beam of light originating from the source of light. The adjustable and controlled structure provides security benefits to the owner. Finally, the research is backed by its simulation in Matlab.

Light-Fidelity (Li-Fi) Wireless-Fidelity (Wi-Fi) communication technology light emitting diode (LED)

Abstract doi.org/10.14569/IJACSA.2018.090308 PDF

9

A Collective Neurodynamic Approach to Survivable Virtual Network Embedding

Author 1: Ashraf A. Shahin

Network virtualization has attracted significant amount of attention in the last few years as one of the key features of cloud computing. Network virtualization allows multiple virtual networks to share physical resources of single substrate network. However, sharing substrate network resources increases impact of single substrate resource failure. One of the commonly applied mechanisms to protect against such failures is provisioning redundant substrate resources for each virtual network to be used to recover affected virtual resources. However, redundant resources decreases cloud revenue by increasing virtual network embedding cost. In this paper, a collective neurodynamic approach has been proposed to reduce amount of provisioned redundant resources and reduce cost of embedding virtual networks. The proposed approach has been evaluated by using simulation and compared against some existing survivable virtual network embedding techniques.

Collective neurodynamics integer linear programming global optimization network virtualization survivable virtual network embedding

Abstract doi.org/10.14569/IJACSA.2018.090309 PDF

10

Breast Cancer Classification in Histopathological Images using Convolutional Neural Network

Author 1: Mohamad Mahmoud Al Rahhal

Computer based analysis is one of the suggested means that can assist oncologists in the detection and diagnosis of breast cancer. On the other hand, deep learning has been promoted as one of the hottest research directions very recently in the general imaging literature, thanks to its high capability in detection and recognition tasks. Yet, it has not been adequately suited to the problem of breast cancer so far. In this context, I propose in this paper an approach for breast cancer detection and classification in histopathological images. This approach relies on a deep convolutional neural networks (CNN), which is pretrained on an auxiliary domain with very large labelled images, and coupled with an additional network composed of fully connected layers. The network is trained separately with respect to various image magnifications (40x, 100x, 200x and 400x). The results presented in the patient level achieved promising scores compared to the state of the art methods.

Convolutional neural network (CNN) histopathological images imagenet classification

Abstract doi.org/10.14569/IJACSA.2018.090310 PDF

11

A Portable Natural Language Interface to Arabic Ontologies

Author 1: Aimad Hakkoum Author 2: Hamza Kharrazi Author 3: Said Raghay

With the growing expansion of the semantic web and its applications, providing natural language interfaces (NLI) to end-users becomes essential to querying RDF stores and ontologies, using simple questions expressed in natural language. Existing NLIs work mostly with the English language. There are very few attempts to develop systems supporting the Arabic language. In this paper, we propose a portable NLI to Arabic ontologies; it will transform the user’s query expressed in Arabic into formal language query. The proposed system starts by a preparation phase that creates a gazetteer from the given ontology. The issued query is then processed using natural language processing (NLP) techniques to extract keywords. These keywords are mapped to the ontology entities, then a valid SPARQL query is generated based on the ontology definition and the reasoning capabilities of the Web Ontology Language (OWL). To evaluate our tool we used two different Arabic ontologies: a Qur’anic ontology and an Arabic sample of Mooney Geography dataset. The proposed system achieved 64% recall and 76% precision.

Natural language interface ontology Semantic web Arabic natural language processing (NLP)

Abstract doi.org/10.14569/IJACSA.2018.090311 PDF

12

Online Incremental Rough Set Learning in Intelligent Traffic System

Author 1: Amal Bentaher Author 2: Yasser Fouad Author 3: Khaled Mahar

In the last few years, vehicle to vehicle communication (V2V) technology has been developed to improve the efficiency of traffic communication and road accident avoidance. In this paper, we have proposed a model for online rough sets learning vehicle to vehicle communication algorithm. This model is an incremental learning method, which can learn data object-by-object or class-by-class. This paper proposed a new rules generation for vehicle data classifying in collaborative environments. ROSETTA tool is applied to verify the reliability of the generated results. The experiments show that the online rough sets based algorithm for vehicle data classifying is suitable to be executed in the communication of traffic environments. The implementation of this model on the objectives’ (cars’) rules that define parameters for the determination of the value of communication, and for reducing the decision rules that leads to the estimation of their optimal value. The confusion matrix is used to assess the performance of the chosen model and classes (Yes or No). The experimental results show the overall accuracy (predicted and actual) of the proposed model. The results show the strength of the online learning model against offline models and demonstrate the importance of the accuracy and adaptability of the incremental learning in improving the prediction ability.

Vehicle to vehicle communication online learning rough sets theory intelligent traffic system

Abstract doi.org/10.14569/IJACSA.2018.090312 PDF

13

Permanent Relocation and Self-Route Recovery in Wireless Sensor and Actor Networks

Author 1: Khalid Mahmood Author 2: Muhammad Amir Khan Author 3: Mahmood ul Hassan Author 4: Ansar Munir Shah Author 5: Muhammad Kashif Saeed

Wireless sensor and actor network’s connectivity and coverage plays a significant role in mission-critical applications, whereas sensors and actors respond immediately to the detected events in an organized and coordinated way for an optimum restoration. When one or multiple actors fail, the network becomes disjoint by losing connectivity and coverage; therefore, self-healing algorithm is required to sustain the connectivity and coverage. In this paper two algorithms; Permanent Relocation Algorithm for Centralized Actor Recovery (PRACAR) and Self-Route Recovery Algorithm (SRRA) for sensors have been proposed for connectivity and coverage. The effectiveness of proposed technique has been proved by realistic simulation results which ensure that our proposed technique better handles the connectivity and coverage.

Wireless sensor and actor networks connectivity restoration node mobility route recovery node relocation

Abstract doi.org/10.14569/IJACSA.2018.090313 PDF

14

Optimization based Approach for Content Distribution in Hybrid Mobile Social Networks

Author 1: Rizwan Akhtar Author 2: Imran Memon Author 3: Zuhaib Ashfaq Khan Author 4: Changda Wang

This paper presents the new strategy for smooth content distribution in the mobile social network. We proposed a new method, hybrid mobile social network architecture scheme considered as one node of a social community called social super node with higher capacity provides the services of content distribution. We proposed methods and techniques that are introduced to set the criteria to select a social super node (SSN). The simulation results are carried out to measure the correctness of the network performance of the proposed method. These results indicate that the accessing of those content of nearby social super node instead of the content provider is used to improve overall network performance in terms of content end-to-end delays, delivery ratio, throughput, and cost.

Mobile social network social super node delays network performance end-to-end delays content delivery

Abstract doi.org/10.14569/IJACSA.2018.090314 PDF

15

Distributed Energy Efficient Node Relocation Algorithm (DEENR)

Author 1: Mahmood ul Hassan Author 2: Muhammad Amir Khan Author 3: Shahzad Ali Author 4: Khalid Mahmood Author 5: Ansar Munir Shah

Wireless Sensor Networks (WSNs) due to their inherent features are vulnerable to single or multiple sensor node failure. Node’s failure can result in partitioning of the networks resulting in loss of inter-node connectivity and eventually compromising the operation of the sensor network. The recovery from partitioning of network is crucial for inter-node connectivity. In literature, a number of approaches have been proposed for the restoration of inter-node connectivity. There is a need for a distributed approach that has an energy efficient operation as energy is a scarce resource. By keeping this in mind we propose a novel technique to restore the connectivity that is distributed and energy efficient. The effectiveness of the proposed technique is proven by extensive simulations. The simulation results show that the proposed technique is efficient and capable of restoring network connectivity by using the mechanisms for improving the coverage.

Wireless sensor network node failure network connectivity

Abstract doi.org/10.14569/IJACSA.2018.090315 PDF

16

Secure and Privacy Preserving Mail Servers using Modified Homomorphic Encryption (MHE) Scheme

Author 1: Lija Mohan Author 2: Sudheep Elayidon M

Electronic mail (Email) or the paperless mail is becoming the most acceptable, faster and cheapest way of formal and informal information sharing between users. Around 500 billion mails are sent each day and the count is expected to be increasing. Today, even the sensitive and private information are shared through emails, thus making it the primary target for attackers and hackers. Also, the companies having their own mail server, relies on cloud system for storing the mails at a lower cost and maintenance. This affected the privacy of users as the searching pattern is visible to the cloud. To rectify this, we need to have a secure architecture for storing the emails and retrieve them according to the user queries. Data as well as the queries and computations to retrieve the relevant mails should be hidden from the third party. This article proposes a modified homomorphic encryption (MHE) technique to secure the mails. Homomorphic encryption is made practical using MHE and by incorporating Map Reduce parallel programming model, the execution time is exponentially reduced. Well known techniques in information retrieval, like Vector Space model and Term Frequency – Inverse Document Frequency (TF-IDF) concepts are utilized for finding relevant mails to the query. The analysis done on the dataset proves that our method is efficient in terms of execution time and in ensuring the security of the data and the privacy of the users.

Big data encrypted data searching privacy preserving homomorphic encryption hadoop map reduce

Abstract doi.org/10.14569/IJACSA.2018.090316 PDF

17

Strategic Framework and Maturity Index for Measuring Knowledge Management Practices in Government Organizations

Author 1: Shilpa Vijaivargia Author 2: Hemant Kumar Garg

Knowledge is considered as an intellectual asset of any Organization through which performance of the Organization could be enhanced exponentially. Harnessing of the Organization’s Tacit and Explicit knowledge and its Management is a crucial task as Knowledge Management Practices adopted by Government Organizations are not standardized yet. They are depending on the structure and processes adopted by the organizations at their own level. This paper presents a Strategic Framework of Knowledge Management and defines Maturity Index at three levels for measuring Knowledge Management Practices adopted by an Organization. This paper defines Value of the Knowledge at all the three defined Maturity levels which is based on number of times the knowledge content is viewed, benefits gained against viewing such contents in terms of tangible asset and Socio-Economic Impact. Knowledge Management Practices adopted by Bharat Electronics Limited (BEL) studied and measured at the Maturity Level is defined in this paper.

Knowledge Explicit knowledge Tacit knowledge knowledge management knowledge architecture knowledge process framework knowledge audit maturity index knowledge audit

Abstract doi.org/10.14569/IJACSA.2018.090317 PDF

18

Smart Card ID: An Evolving and Viable Technology

Author 1: Praveen Kumar Singh Author 2: Neeraj Kumar Author 3: Bineet Kumar Gupta

In today’s world carrying a number of plastic smart cards to establish our identity has become an integral segment of our routine lives. Identity establishment necessitates a pre stored readily available data about self and to the administrator to authenticate it with claimer’s personal information. There is a distinct requirement of a technological solution for nationwide multipurpose identity for any citizen across the board. Number of options has been exercised by various countries and every option has its own pros and cons. However, it has been observed that in most of the cases Smart Card solution has been preferred by a user and administrator both. The use of Smart cards are so prevalent that be it any profession, without incorporating its application, identity of any individual is hardly considered complete. In this paper, the principle aim is to discuss the viability of Smart Card technology as an identity solution and its ability to perform various functions with strong access control that increases the reliability of Smart Cards over other technologies. It outlines the overview of smart card technology along with its key applications. Security concerns of smart card have been discussed through an algorithm with the help of a division integer proposition. Possibilities of upgrading it with evolving technology offer it as a universal acceptability of identification. Capability of storing desired amount of information by an administrator to compute multiple operations to authenticate a citizen dictates its widening acceptability and an endeavor has been made in this paper to explain it through a proposed system flow chart.

ISO IoT multipurpose authentication security smart card reader cryptography identification technology smart card application

Abstract doi.org/10.14569/IJACSA.2018.090318 PDF

19

A Smart Under-Frequency Load Shedding Scheme based on Takagi-Sugeno Fuzzy Inference System and Flexible Load Priority

Author 1: J. A. Laghari Author 2: Suhail Ahmed Almani Author 3: Jagdesh Kumar Author 4: Hazlie Mokhlis

This paper proposes a new smart under frequency load shedding (UFLS) scheme, based on Takagi-Sugeno (TS) fuzzy inference system and flexible load priority. The proposed scheme consists of two parts. First part consists of fuzzy load shed amount estimation module (FLSAEM) which uses TS-fuzzy to estimate the amount of load shed and sends its value to accurate load shedding module (ALSM) to perform accurate load shedding using flexible load priority. The performance of the proposed scheme is tested for intentional islanding case and increment of sudden load in the system. Moreover, the response of the proposed scheme is compared with adaptive UFLS scheme to highlight its advantages. The simulation results show that the proposed UFLS scheme provides the accurate load shedding due to advantage of flexible priority whereas adaptive UFLS scheme due to fixed load priority does not succeed to achieve accurate load shedding.

Distributed generation (DG) flexible load priority fuzzy load shed amount estimation module (FLSAEM) islanded distribution network under-frequency load shedding (UFLS)

Abstract doi.org/10.14569/IJACSA.2018.090319 PDF

20

Fuzzy Gains-Scheduling of an Integral Sliding Mode Controller for a Quadrotor Unmanned Aerial Vehicle

Author 1: Nour Ben Ammar Author 2: Soufiene Bouallègue Author 3: Joseph Haggège

This paper investigates an Adaptive Fuzzy Gains-Scheduling Integral Sliding Mode Controller (AFGS-ISMC) design approach to deal with the attitude and altitude stabilization problem of an Unmanned Aerial Vehicles (UAV) precisely of a quadrotor. The Integral Sliding Mode Control (ISMC) seems to be an adequate control tool to remedy this problem. The selection of the controller parameters is done most of the time using repetitive trials-errors based methods. This method is not completely reliable and becomes a time-consuming and difficult task. Here we propose the tuning and selection of all ISMC gains adaptively according to a fuzzy supervisor. The sliding surface and its differential are declared as Fuzzy Logic Supervisor (FLS) inputs and the integral sliding mode control gains as the FLS outputs. The proposed fuzzy-based supervision mechanisms modify all ISMC gains to be time-varying and further enhance the performance and robustness of the obtained adaptive nonlinear controllers against uncertainties and external disturbances. The proposed adaptive fuzzy technique increases the effectiveness of the ISMC structure compared to the classical SMC strategy and excludes the dull and repetitive trials-errors process for its design and tuning. Various simulations have been carried out and followed by comparison and discussion of the results in order to prove the superiority of the suggested fuzzy gains-scheduled ISMC approach for the quadrotor attitude and altitude flight stabilization.

Quadrotor UAV modeling flight dynamics stabilization integral sliding mode control fuzzy gains-scheduling adaptive control

Abstract doi.org/10.14569/IJACSA.2018.090320 PDF

21

Interactive Hypermedia Programs and its Impact on the Achievement of University Students Academically Defaulting in Computer Sciences

Author 1: Mohamed Desoky Rabeh

Traditional teaching practices through lecture series in a classroom have shown to have less universal efficacy in imparting knowledge to every student. Some students encounter problems in this traditional setting, especially in subjects that require applied instruction rather than verbal teaching. University students who have problems in understanding computer science have been hypothesized in this study to achieve better results on the application of interactive hypermedia programs in their curricula. The study has, thus, conducted a teaching survey through pretest-posttest control group design where computer science students of the Community College of Northern Border University were selected through non-probability sampling methodology and were made to undergo traditional teaching followed by interactive hypermedia sessions on the same subject. The evaluations of the change in performance provided results that showed that there existed a statistically significant difference in the mean scores of students after attending the interactive hypermedia program, providing evidence that hypermedia induced educational sessions were better to induce performance of students than those sessions that did not have any hypermedia exposure. However, the study also provided an understanding of limitations such as generalized quantitative experiments on computer science students of the Northern Border University, but the researcher believes that more widespread experimentation of the same kind can help establish the unbiased performance supremacy of hypermedia instruction in improving the academic performance of university students in different subjects.

Interactive hypermedia program traditional teaching university students computer sciences achievement impact

Abstract doi.org/10.14569/IJACSA.2018.090321 PDF

22

Mobile Phone Operations using Human Eyes Only and its Applications

Author 1: Kohei Arai

Mobile phone operations using human eyes only is proposed together with its applications for cooking with referring to recipes and manufacturing with referring to manuals, production procedure, so on. It is found that most of mobile phone operations can be done without touching the screen of the mobile phone. Also, mobile phone operation success rate based on the proposed method is evaluated for the environmental illumination conditions, visible or near infrared (NIR) cameras, the distance between user and mobile phone, as well as pupil size detection accuracy against the environmental illumination changes. Meanwhile, the functionality of two typical applications of the proposed method is confirmed successfully.

Mobile phone operations line of sight estimation gaze estimation wearable computing pupil detection

Abstract doi.org/10.14569/IJACSA.2018.090322 PDF

23

Computerized Steganographic Technique using Fuzzy Logic

Author 1: Abdulrahman Abdullah Alghamdi

Steganography is the method of providing Computer security in which hiding the required information is done by inserting messages within other messages, which is a string of characters containing the useful information, in a carrier image. Using this technique, the required information from the secret image is embedded into individual rows as well as columns present in the pixels of carrier image. In this paper, a novel fuzzy logic based technique is proposed to hide the secret message in individual rows and in individual columns of pixels of the carrier image and to extract the hidden message in the same carrier image. The fuzzification process transforms the image in to various bitplanes. Pixel number and Correlation Value is computed in the original image for hiding the secret information in to the original image. The pixel number and Correlation value is also used as the key for retrieving the embedded image from the receiver side. Pixel merging is done in the sender side by assigning a steganographic value of white and black pixels in original image based on the fuzzy rules by comparing the pixels present in the original and secret images. The information which is hided can be retrieved by using the same fuzzy rules. Experimental results show that the proposed method can hide and retrieve the secret and important messages in an image more effectively and accurately.

Computer security fuzzy logic carrier image secret image steganography fuzzification peak signal to noise ratio

Abstract doi.org/10.14569/IJACSA.2018.090323 PDF

24

An Efficient Algorithm for Load Balancing in Multiprocessor Systems

Author 1: Saleh A. Khawatreh

A multiprocessor system is a computer with two or more central processing units (CPUs) with each one sharing the common main memory as well as the peripherals. Multiprocessor system is either homogeneous or heterogeneous system. A homogeneous system is a cluster of processors joined to a high speed network for accomplishing the required task; also it is defined as parallel computing system. Homogeneous is a technique of parallel computing system. A heterogeneous system can be defined as the interconnection of a number of processors, having dissimilar computational speed. Load balance is a method of distributing work between the processors fairly in order to get optimal response time, resource utilization, and throughput. Load balancing is either static or dynamic. In static load balancing, work is distributed among all processors before the execution of the algorithm. In dynamic load balancing, work is distributed among all processors during execution of the algorithm. So problems arise when it cannot statistically divide the tasks among the processors. To use multiprocessor systems efficiently, several load balancing algorithms have been adopted widely. This paper proposes an efficient load balance algorithm which addresses common overheads that may decrease the efficiency of a multiprocessor system. Such overheads are synchronization, data communication, response time, and throughput.

Multiprocessor system homogeneous system heterogeneous system load balance static load balancing dynamic load balancing response time throughput

Abstract doi.org/10.14569/IJACSA.2018.090324 PDF

25

Performance Evaluation of a Deployed 4G LTE Network

Author 1: E.T. Tchao Author 2: J.D. Gadze Author 3: Jonathan Obeng Agyapong

In Ghana and many countries within Sub-Sahara Africa, Long Term Evolution (LTE) is being considered for use within the sectors of Governance, Energy distribution and transmission, Transport, Education and Health. Subscribers and Governments within the region have high expectations for these new networks and want to leverage the promised enhanced coverage and high data rates for development. Recent performance evaluations of deployed WiMAX networks in Ghana showed promising performance of a wireless broadband technology in supporting the capacity demands needed in the peculiar Sub-Saharan African terrain. The deployed WiMAX networks, however could not achieve the optimal quality of service required for providing a seamless wireless connectivity demands needed for emerging mobile applications. This paper evaluates the performance of some selected key network parameters of a newly deployed LTE network in the 2600 MHz band operating in the peculiar Sub-Saharan African terrain under varied MIMO Antenna Configurations. We adopted simulation and field measurement to aid us in our evaluation. Genex Unet has been used to simulate network coverage and throughput performance of 2X2, 4X4 and 8X8 MIMO configurations of the deployed networks. The average simulated throughput per sector of 4X4 MIMO configuration was seen to be better than the 2X2 configuration. However, the percentage coverage for users under the 2x2 MIMO simulation scenario was better than that of the adaptive 4x4 MIMO configuration with 2x2 MIMO achieving 60.41% of coverage area having throughput values between 1 - 40Mbps as against 55.87% achieved by the 4x4 MIMO configuration in the peculiar deployment terrain.

Long term evolution MIMO performance evaluation sub-Saharan African propagation environment

Abstract doi.org/10.14569/IJACSA.2018.090325 PDF

26

Automatic Detection Technique for Speech Recognition based on Neural Networks Inter-Disciplinary

Author 1: Mohamad A. A. Al- Rababah Author 2: Abdusamad Al-Marghilani Author 3: Akram Aref Hamarshi

Automatic speech recognition allows the machine to understand and process information provided orally by a human user. It consists of using matching techniques to compare a sound wave to a set of samples, usually composed of words but also of phonemes. This field uses the knowledge of several sciences: anatomy, phonetics, signal processing, linguistics, computer science, artificial intelligence and statistics. The latest acoustic modeling methods provide deep neural networks for speech recognition. In particular, recurrent neural networks (RNNs) have several characteristics that make them a model of choice for automatic speech processing. They can keep and take into account in their decisions past and future contextual information. This paper specifically studies the behavior of Long Short-Term Memory (LSTM)-based neural networks on a specific task of automatic speech processing: speech detection. LSTM model were compared to two neural models: Multi-Layer Perceptron (MLP) and Elman’s Recurrent Neural Network (RNN). Tests on five speech detection tasks show the efficiency of the Long Short-Term Memory (LSTM) model.

Speech recognition automatic detection recurrent neural network (RNN) LSTM

Abstract doi.org/10.14569/IJACSA.2018.090326 PDF

27

Image based Arabic Sign Language Recognition System

Author 1: Reema Alzohairi Author 2: Raghad Alghonaim Author 3: Waad Alshehri Author 4: Shahad Aloqeely

Through history, humans have used many ways of communication such as gesturing, sounds, drawing, writing, and speaking. However, deaf and speaking impaired people cannot use speaking to communicate with others, which may give them a sense of isolation within their societies. For those individuals, sign language is their principal way to communicate. However, most people (who can hear) do not know the sign language. In this paper, we aim to automatically recognize Arabic Sign Language (ArSL) alphabets using an image-based methodology. More specifically, various visual descriptors are investigated to build an accurate ArSL alphabet recognizer. The extracted visual descriptors are conveyed to One-Versus-All Support Vector Machine (SVM). The analysis of the results shows that Histograms of Oriented Gradients (HOG) descriptor outperforms the other considered descriptors. Thus, the ArSL gesture models that are learned by One-Versus-All SVM using HOG descriptors are deployed in the proposed system.

Component Arabic sign language image visual descriptor recognition

Abstract doi.org/10.14569/IJACSA.2018.090327 PDF

28

The Adoption of Software Process Improvement in Saudi Arabian Small and Medium Size Software Organizations: An Exploratory Study

Author 1: Mohammed Ateeq Alanezi

Quite a lot of attention has been paid in the literature on “how to adopt” software process improvement (SPI) in Small and Medium Size (SME) software organization in several countries. This has resulted in limited improvements to the software industry and impacted the Saudi’s economy. However, the SPI adoption is one of the major issues in the domain of small and medium size software organization, especially in developing countries. The objective of this study is to investigate the current state of SPI adoption in Saudi Arabia in comparison to those of the standard models used internationally which could help in improving the software quality and have an impact on Saudi Arabian economy. After examining a number of studies in the literature, we have designed a questionnaire to survey SME software organizations in Saudi Arabia. First, we conducted a pilot study with 24 senior managers to access the intended survey and further improve the process. Then, we sent out 480 questionnaires to the participants and received 291 responses. The most interesting part of this result is that the respondents highlighted the benefits of using SPI standard; whereby, when asked about the reason for not using SPI, 64% of the respondents agree that the usage of SPI standard is time consuming and 55% agree that there is a difficulty in understanding the SPI standard.

Software process improvement software organization software adoption small and medium enterprises (SME)

Abstract doi.org/10.14569/IJACSA.2018.090328 PDF

29

Ant Colony Optimization for a Plan Guide Course Registration Sequence

Author 1: Wael Waheed Al-Qassas Author 2: Mohammad Said El-Bashir Author 3: Rabah Al-Shboul Author 4: Anwar Ali Yahya

Students in universities do not follow the prescribed course plan guide, which affects the registration process. In this research, we present an approach to tackle the problem of guide for plan of course sequence (GPCS) since that sequence may not be suitable for all students due to various conditions. The Ant Colony Optimization (ACO) algorithm is anticipated to be a suitable approach to solving such problems. Data on sequence of the courses registered by students of the Computer Science Department at Al Al-Bayt University over four years were collected for this study. The fundamental task was to find the suitable pheromone evaporation rate in ACO that generates the optimal GPCS by conducting an Adaptive Ant Colony Optimization (AACO) on the model that used the collected data. We found that 17 courses out of 31 were placed in semesters differing from the semesters preset in the course plan.

Ant colony optimization guide plan university course registration

Abstract doi.org/10.14569/IJACSA.2018.090329 PDF

30

Continuous Path Planning of Kinematically Redundant Manipulator using Particle Swarm Optimization

Author 1: Affiani Machmudah Author 2: Setyamartana Parman Author 3: M.B. Baharom

This paper addresses a problem of a continuous path planning of a redundant manipulator where an end-effector needs to follow a desired path. Based on a geometrical analysis, feasible postures of a self-motion are mapped into an interval so that there will be an angle domain boundary and a redundancy resolution to track the desired path lies within this boundary. To choose a best solution among many possible solutions, meta-heuristic optimizations, namely, a Genetic Algorithm (GA), a Particle Swarm Optimization (PSO), and a Grey Wolf Optimizer (GWO) will be employed with an optimization objective to minimize a joint angle travelling distance. To achieve n-connectivity of sampling points, the angle domain trajectories are modelled using a sinusoidal function generated inside the angle domain boundary. A complex geometrical path obtained from Bezier and algebraic curves are used as the traced path that should be followed by a 3-Degree of Freedom (DOF) arm robot manipulator and a hyper-redundant manipulator. The path from the PSO yields better results than that of the GA and GWO.

Path planning redundant manipulator genetic algorithm particle swarm optimization grey wolf optimizer insert

Abstract doi.org/10.14569/IJACSA.2018.090330 PDF

31

On the Sampling and the Performance Comparison of Controlled LTI Systems

Author 1: Sirine FEKIH Author 2: Boutheina SFAIHI Author 3: Mohamed BENREJEB

In this paper, the impact of the discretization techniques and the sampling time, on the finite-time stabilization of sampled-data controlled Linear Time Invariant (LTI) systems, is investigated. To stabilize the process in finite time, a discrete-time feedback dead-beat controller is designed for the sampled-data system. Checkable conditions on the approximate discrete-time plant model and the associated controller that guarantee the finite-time stabilization of the exact model are developed. The trade-off between the discretization technique, the sampling time and the desired performances is illustrated and discussed. Results are presented through a case study.

Sampled-data systems discretization finite time stabilization dead-beat control

Abstract doi.org/10.14569/IJACSA.2018.090331 PDF

32

Arabic Text Categorization using Machine Learning Approaches

Author 1: Riyad Alshammari

Arabic Text categorization is considered one of the severe problems in classification using machine learning algorithms. Achieving high accuracy in Arabic text categorization depends on the preprocessing techniques used to prepare the data set. Thus, in this paper, an investigation of the impact of the preprocessing methods concerning the performance of three machine learning algorithms, namely, Na¨ıve Bayesian, DMNBtext and C4.5 is conducted. Results show that the DMNBtext learning algorithm achieved higher performance compared to other machine learning algorithms in categorizing Arabic text.

Arabic text categorization machine learning

Abstract doi.org/10.14569/IJACSA.2018.090332 PDF

33

2-D Object Recognition Approach using Wavelet Transform

Author 1: Kamelsh Kumar Author 2: Riaz Ahmed Shaikh Author 3: Rafaqat Hussain Arain Author 4: Safdar Ali Shah

Humans have supernatural ability to observe, analyze, and tell about the layout of the 3D world with the help of their natural visual system. But contrary to machine vision system, it remains a most difficult task to recognize various objects from images being captured by cameras. This paper presents 2-D image object recognition approach using Daubechies (Db10) wavelet transform. Firstly, an edge detection is carried out to delineate objects from the images. Secondly, shape moments have been used for object recognition. For testing purpose, different geometrical shapes such as rectangle, circle, triangle and pattern have been selected for image analysis. Simulation has been performed using MATLAB, and obtained results showed that it accurately identifies the objects. The research goal was to test 2-D images for object recognition.

Wavelet transforms db10 edge detection object recognition shape moments

Abstract doi.org/10.14569/IJACSA.2018.090333 PDF

34

Evaluation for Feature Driven Development Paradigm in Context of Architecture Design Augmentation and Perspective Implications

Author 1: Shahbaz Ahmed Khan Gahyyur Author 2: Abdul Razzaq Author 3: Syed Zeeshan Hasan Author 4: Salman Ahmed Author 5: Rafi Ullah

Agile is a light weight software development methodology that is useful for rapid application development which is the need of current software industry. Since the focus of agile software development is the customer but it does not provide the detailed information about the application’s architecture and documentation, so software architecture has its own benefits and use of it has many positive effects. The focus of this paper is to provide a systematic mapping of emerging issues in feature driven development that arises due to lack of architecture support in agile methodology and proposed solution’s model. Results of this mapping provides a guideline for researcher to improve the agile methodology by achieving the benefits employed by having an architecture in place that is aligned with agile values and principles. Following research addresses to implement the SEI architecture centric methods in FDD methodology in an adapted form, such that the burden of architecture doesn’t affect the agility of FDD. And the researcher found the de-motivators of agile which helps to understand the internal cycle and reduces the issues to implement the architecture. This study helps to understand the difference between architecture and FDD. This researcher mapping creates awareness about the process improvement with the combination of architecture and FDD.

Software architecture agile architecture and agile integration of architecture and agile agile architecting practices

Abstract doi.org/10.14569/IJACSA.2018.090334 PDF

35

A High Gain MIMO Antenna for Fixed Satellite and Radar Applications

Author 1: Ahsan Altaf Author 2: Khalid Mahmood Author 3: Mehre Munir Author 4: Saad Hassan Kiani

Patch antennas have emerged rapidly with advancement of communication technology. For antenna design purposes, Finite difference time domain (FDTD) method is a commonly used. This paper focuses on the interaction among elements of MIMO antenna also known as mutual coupling using FDTD method. An M shape is introduced and with placement of isolating structure, round about 12dB of isolation is increased without degradation of performance parameters. The proposed antenna design can be used for radar and satellite services applications.

Mutual coupling isolating structure multiple input multiple output radar application finite difference time domain

Abstract doi.org/10.14569/IJACSA.2018.090335 PDF

36

Circular Calibration of Depth Extraction in Stereo Configuration

Author 1: Zulfiqar Ibrahim Author 2: Zulfiqar Ali Bangash Author 3: Muhammad Zeeshan

Lens distortion is defined as departure from rectilinear projection of an imaging system which affects the accuracy of almost all vision applications. This work addresses the problem of distortion with investigating the effects of camera’s view angle and spherical nature of lens on image, and then derives a closed-form solution for the correction of distorted pixel's angle in image according to geometric shape of lens. We first propose technique that explores the linear relation between lens and charge-coupled device in intrinsic environment of camera, through analysis of pixel’s angle in field of view. Second technique for depth extraction through linear transformation in rectangular configuration is achieved by considering the camera’s background in field of view which provides optimal results in closed environment. As the object moves away from the center of image in image plane, depth accuracy starts to deteriorate due to radial distortion. To rectify this problem, we finally purpose circular calibration methodology which addresses this inaccuracy and accommodate radial distortion to achieve optimal results up to 98%, in great depth with very large baseline. Results show the improvement over established stereo imaging techniques in depth extraction where the presented considerations are not observed. This methodology ensures high accuracy of triangulated depth with very large base line.

Stereo imaging depth extraction triangulation radial distortion lenses rectilinear projection component

Abstract doi.org/10.14569/IJACSA.2018.090336 PDF

37

An Automatic Arabic Essay Grading System based on Text Similarity Algorithms

Author 1: Abdulaziz Shehab Author 2: Mahmoud Faroun Author 3: Magdi Rashad

Manual grading process has many problems such as time consuming, costly, enormous resources, lot of efforts and huge pressure on instructors. These problems place the educational community in a dire need to have auto-grading systems so as to address these problems associated with manual grading. Auto-grading systems are wide spread over the world because they play a critical role in educational technology. Additionally, the auto-grading system is introducing many advantages as it saves cost, effort and time in comparison to manual grading. This research compares the different algorithms used in automatic grading systems in Arabic languages using string and corpus algorithms separately. This process is a challenging task following the necessity of inclusive assessment to authenticate the answers precisely. Moreover, the challenge is heightened when working with the Arabic language characterized by complexities in morphology, semantics and syntax. The research applied multiple similarity measures and introduces Arabic data set that contains 210 students’ answers. The results obtained prove that an automatic grading system could provide the teacher with an effective solution for article grading systems.

Auto-grading systems string-based similarity corpus-based similarity N-Gram

Abstract doi.org/10.14569/IJACSA.2018.090337 PDF

38

An Effective Automatic Image Annotation Model Via Attention Model and Data Equilibrium

Author 1: Amir Vatani Author 2: Milad Taleby Ahvanooey Author 3: Mostafa Rahimi

Nowadays, a huge number of images are available. However, retrieving a required image for an ordinary user is a challenging task in computer vision systems. During the past two decades, many types of research have been introduced to improve the performance of the automatic annotation of images, which are traditionally focused on content-based image retrieval. Although, recent research demonstrates that there is a semantic gap between content-based image retrieval and image semantics understandable by humans. As a result, existing research in this area has caused to bridge the semantic gap between low-level image features and high-level semantics. The conventional method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, we propose a novel AIA model based on the deep learning feature extraction method. The proposed model has three phases, including a feature extractor, a tag generator, and an image annotator. First, the proposed model extracts automatically the high and low-level features based on dual tree continues wavelet transform (DT-CWT), singular value decomposition, distribution of color ton, and the deep neural network. Moreover, the tag generator balances the dictionary of the annotated keywords by a new log-entropy auto-encoder (LEAE) and then describes these keywords by word embedding. Finally, the annotator works based on the long-short-term memory (LSTM) network in order to obtain the importance degree of specific features of the image. The experiments conducted on two benchmark datasets confirm that the superiority of proposed model compared to the previous models in terms of performance criteria.

Automatic image annotation attention model skewed learning deep learning word embedding log-entropy auto encoder

Abstract doi.org/10.14569/IJACSA.2018.090338 PDF

39

A Systematic Literature Review of Success Factors and Barriers of Agile Software Development

Author 1: Shahbaz Ahmed Khan Ghayyur Author 2: Salman Ahmed Author 3: Mukhtar Ali Author 4: Adnan Naseem Author 5: Abdul Razzaq Author 6: Naveed Ahmed

Motivator and demotivator plays an important role in software industry. It encompasses software performance and productivity which are necessary for projects of Agile software development (ASD). Existing studies comprise of motivators and demotivators of ASD, which exist in dispersed form. That is why there is a need of a detailed systematic literature review to review the factors and sub-factors effecting motivators and demotivators in ASD. A comprehensive review is executed to gather the critical success factors of motivator and demotivator of Agile software development. Thus, the ongoing study classifies motivator and demotivator factors into four classes, i.e., people, organization, technical and process. However, sub-classification is also executed to clarify more of the motivators of agile. Along with this, motivator and demotivator of scrum process is also categorized to overview a clear vision.

Agile methods systematic literature review motivator demotivator success factors barriers scrum ASD

Abstract doi.org/10.14569/IJACSA.2018.090339 PDF

40

Standardization of Cloud Security using Mamdani Fuzzifier

Author 1: Shan e Zahra Author 2: Muhammad Adnan Khan Author 3: Muhammad Nadeem Ali Author 4: Sabir Abbas

Cloud health has consistently been a major issue in information technology. In the CC environment, it becomes particularly serious because the data is located in different places even in the entire globe. Associations are moving their information on to cloud as they feel their information is more secure and effectively evaluated. However, as a few associations are moving to the cloud, they feel shaky. As the present day world pushes ahead with innovation, one must know about the dangers that come along with cloud health. Cloud benefit institutionalization is important for cloud security administrations. There are a few confinements seeing cloud security as it is never a 100% secure. Instabilities will dependably exist in a cloud with regards to security. Cloud security administrations institutionalization will assume a noteworthy part in securing the cloud benefits and to assemble a trust to precede onward cloud. In the event that security is tight and the specialist organizations can guarantee that any interruption endeavor to their information can be observed, followed and confirmed. In this paper, we proposed ranking system using Mamdani fuzzifier. After performing different ranking conditions, like, if compliance is 14.3, Data Protection 28.2, Availability 19.7 and recovery is 14.7 then cloud health is 85% and system will respond in result of best cloud health services.

CC CS FIS FRBS MIE standards compliance data protection availability and recovery

Abstract doi.org/10.14569/IJACSA.2018.090340 PDF

41

Evolutionary Design of a Carbon Dioxide Emission Prediction Model using Genetic Programming

Author 1: Abdel Karim Baareh

Weather pollution is considered as one of the most important, dangerous problem that affects our life and the society security from the different sides. The global warming problem affecting the atmosphere is related to the carbon dioxide emission (CO2) from the different fossil fuels along with temperature. In this paper, this phenomenon is studied to find a solution for preventing and reducing the poison CO2 gas emerged from affecting the society and reducing the smoke pollution. The developed model consists of four input attributes: the global oil, natural gas, coal, and primary energy consumption and one output the CO2 gas. The stochastic search algorithm Genetic Programming (GP) was used as an effective and robust tool in building the forecasting model. The model data for both training and testing cases were taken from the years of 1982 to 2000 and 2003 to 2010, respectively. According to the results obtained from the different evaluation criteria, it is nearly obvious that the performance of the GP in carbon gas emission estimation was very good and efficient in solving and dealing with the climate pollution problems.

Fossil fuels carbon emission forecasting genetic programming

Abstract doi.org/10.14569/IJACSA.2018.090341 PDF

42

Understanding the Factors Affecting the Adoption of Green Computing in the Gulf Universities

Author 1: ARWA IBRAHIM AHMED

Many universities worldwide have adopted, or are intend to adopt green computing in their campuses to improve environmental sustainability and efficient-energy consumption. However, the factors affect the adoption of green computing are still not understood. The aim of this study is to investigate the key success factors affecting the adoption of green computing in developing countries’ universities, specifically in Gulf States universities. This study draws mainly on the TOE model suggested by Tornatzky and Fleischer [1] to understand the key areas for the success factors of green computing adoption. Data was collected based on survey research design to 118 Gulf universities. The findings revealed that the top five success factors affect the adoption of green computing in gulf universities are: awareness, relative advantage, top management support, adequate resources and government policy. Moreover, among the proposed three contexts the most important one is organizational, followed by environmental, and finally technology factors. This study contributes to the theory by providing taxonomy of the factors affecting the adoption of green computing. For practitioners, this study will assist the decision makers in gulf countries to benefit from the findings of this study to make well informed decisions by focusing on the key factor that have a greater impact on adopting green computing.

Success factors green computing TOE model and universities

Abstract doi.org/10.14569/IJACSA.2018.090342 PDF

43

The use of Harmonic Balance in Wave Concept Iterative Method for Nonlinear Radio Frequency Circuit Simulation

Author 1: Hicham MEGNAFI Author 2: Noureddine BOUKLI-HACENE Author 3: Nathalie RAVUE Author 4: Henri BAUDRAND

This paper presents the birth of the new hybrid method for the non-linear Radio frequency circuits’ simulation. This method is based on the combination of the wave concept iterative procedure (WCIP) and the harmonic balance (HB) for their advantages. It consists also the development of an application based on this method for the simulation of nonlinear planar radio frequency circuits. The simulation of the Radio frequency diode implemented in micro-strip line is done. The validations are obtained by the comparison of the results obtained by our new hybrid method and Harmonic Balance under Advanced Design System (ADS) software.

WCIP harmonic balance nonlinear circuits planar radio frequency circuits radio frequency diode

Abstract doi.org/10.14569/IJACSA.2018.090343 PDF

44

A Solution for the Uniform Integration of Field Devices in an Industrial Supervisory Control and Data Acquisition System

Author 1: Simona-Anda TCACIUC(GHERASIM)

Supervisory Control and Data Acquisition (SCADA) systems are increasingly used solutions for monitoring and controlling various industrial processes. The existence of a large number of communication protocols helps to deploy complex systems that enable users to access data from one or more processes at a certain distance, and even control those processes. This article presents a solution for the uniform integration of field devices in an industrial SCADA system. This uniform integration is based on the CANopen communication protocol and the EDS files containing detailed descriptions of devices in a CANopen network. Based on the information and structure of the EDS files, we have designed and developed a database aimed at storing these data in an organization that enables them to be safely and efficiently processed. This database is the basis of a website application that enables the user to learn the characteristics of the field devices connected to the local industrial networks in a SCADA system.

SCADA system uniform device integration EDS files communication protocols distributed database

Abstract doi.org/10.14569/IJACSA.2018.090344 PDF

45

An Efficient Mechanism Protocol for Wireless Sensor Networks by using Grids

Author 1: Emad Ibbini Author 2: Kweh Yeah Lun Author 3: Mohamed Othman Author 4: Zurina Mohd Hanapi

Multilevel short-distance clustering communication is an important scheme to reduce lost data packets over the path to the sink, particularly when nodes are deployed in a dense WSN (wireless sensor network). Our proposed protocol solves the problems of single hop paths in the TDTCGE (two-dimensional technique based on center of gravity and energy) method, which addresses only single-hop problems and does not minimize distances between nodes by using multi-hop nodes with multilevel clustering grids to avoid dropped packets and to guarantee reliable paths without failures. In multilevel clustering grids, transmitted data are aggregated from lower-level grids to upper-level grids. In this paper, the proposed protocol obtains the optimal path for data transmission between cluster heads and the sink for heterogeneous WSNs. The cluster head nodes play an important role in forwarding data originating from other normal nodes that aggregate data to upper clusterheads. This routing approach is more efficient than other routing approaches, and it provides a reliable protocol for avoidance of data loss. In addition, the proposed protocol produces sleep and wakeup signals to the nodes and cluster heads via an MD (mediation device), thereby reducing energy consumption. Simulation results demonstrate the efficiency of the proposed method in terms of fewer dropped packets and high energy efficiency. The network environment overcomes the drawbacks of failure paths and provides reliable transmission to the sink.

Multilevel WSN reliable heterogeneous routing

Abstract doi.org/10.14569/IJACSA.2018.090345 PDF

46

Double Authentication Model using Smartphones to Enhance Student on-Campus Network Access

Author 1: Zakaria Saleh Author 2: Ahmed Mashhour

Computers are widely used by all universities to provide network access to students. Therefore, the securities of these computers play a major role in protecting the network. In light of that, a strong access control is required to ensure that sensitive information will only be accessed through firm authentication mechanism. Smartphones are widely used by students, and can be employed to further enhance student authentication by storing partial access information on the Smartphone. And while students should not leave their computer systems unattended, some do. Therefore, daily network access requires that computer unit to be configured in a way that includes password authentication and an access code stored on a device (the smartphone) which needs to be presented by the user during the authentication process. It is a fact that software and hardware may fail to fully secure and protect systems, but user’s negligence to safeguard their systems by logging out of the computer unit before moving away is far more serious security issue. The system being developed in this research will lock the computer unit once the student moves away from that computer unit and loosing communication with the smartphone.

Bluetooth double authentication campus network computer unit security model design smartphone system design

Abstract doi.org/10.14569/IJACSA.2018.090346 PDF

47

A User-Based Trust Model for Cloud Computing Environment

Author 1: Othman Saeed Author 2: Riaz Ahmed Shaikh

There are many trust management models for the cloud environment. Selecting an appropriate trust model is not an easy job for a user. This work presents a new trust model called ARICA model which help a user to reduce the reliance on the trust value of provider and third-party feedback. Simultaneously, the ARICA model increases the dependence on the user trust value. Furthermore, the proposed model measured the trust based on five attributes: Availability, Reliability, Integrity, Confidentiality, and Authentication. This paper presents the comparison of the proposed ARICA trust model with two existing schemes. Results show that the proposed model provides better accurate results.

Trust management model trust value of provider feedback trust value of third-party feedback user trust value availability reliability integrity confidential authentication

Abstract doi.org/10.14569/IJACSA.2018.090347 PDF

48

Synthetic Loads Analysis of Directed Acyclic Graphs for Scheduling Tasks

Author 1: Apolinar Velarde Martinez

Graphs are structures used in different areas of scientific research, for the ease they have to represent different models of real life. There is a great variety of algorithms that build graphs with very dissimilar characteristics and types that model the relationships between the objects of the problem to solve. To model the relationships, characteristics such as depth, width and density of the graph are used in the directed acyclic graphs (DAGs) to find the solution to the objective problem. These characteristics are rarely analyzed and taken into account before being used in the approach of a solution. In this work, we present a set of methods for the random generation of DAGs. DAGs are produced with three of these methods representing three synthetic loads. Each of the three above characteristics is evaluated and analyzed in each of DAGs. The generation and evaluation of synthetic loads is with the objective of predicting the behavior of each DAG, based on its characteristics, in a scheduling algorithm and assignment of parallel tasks in a distributed heterogeneous computing system (DHCS).

Directed acyclic graph distributed heterogeneous computing system (DHCS) Algorithm for scheduling and allocation tasks in a DHCS parallel tasks

Abstract doi.org/10.14569/IJACSA.2018.090348 PDF

49

A Comprehensive IoT Attacks Survey based on a Building-blocked Reference Model

Author 1: Hezam Akram Abdul-Ghani Author 2: Dimitri Konstantas Author 3: Mohammed Mahyoub

Internet of Things (IoT) has not yet reached a distinctive definition. A generic understanding of IoT is that it offers numerous services in many domains, utilizing conventional internet infrastructure by enabling different communication patterns such as human-to-object, object-to-objects, and object-to-object. Integrating IoT objects into the standard Internet, however, has unlocked several security challenges, as most internet technologies and connectivity protocols have been specifically designed for unconstrained objects. Moreover, IoT objects have their own limitations in terms of computation power, memory and bandwidth. IoT vision, therefore, has suffered from unprecedented attacks targeting not only individuals but also enterprises, some examples of these attacks are loss of privacy, organized crime, mental suffering, and the probability of jeopardizing human lives. Hence, providing a comprehensive classification of IoT attacks and their available countermeasures is an indispensable requirement. In this paper, we propose a novel four-layered IoT reference model based on building blocks strategy, in which we develop a comprehensive IoT attack model composed of four key phases. First, we have proposed IoT asset-based attack surface, which consists of four main components: 1) physical objects, 2) protocols covering whole IoT stack, 3) data, and 4) software. Second, we describe a set of IoT security goals. Third, we identify IoT attack taxonomy for each asset. Finally, we show the relationship between each attack and its violated security goals, and identify a set of countermeasures to protect each asset as well. To the best of our knowledge, this is the first paper that attempts to provide a comprehensive IoT attacks model based on a building-blocked reference model.

Internet of Things (IoT) building block security and privacy reference model

Abstract doi.org/10.14569/IJACSA.2018.090349 PDF

50

Enhanced Detection and Elimination Mechanism from Cooperative Black Hole Threats in MANETs

Author 1: Samiullah Khan Author 2: Faqir Usman Author 3: Matiullah Author 4: Fahim Khan Khalil

Malicious node invasion as black hole attack is a burning issue in MANETs. Black hole attacks with a single malicious node is easy to detect and prevent. The collaborative attacks with multiple cooperative malicious node is a challenging issue in security of MANETs as it is difficult to figure out due to its complex and sophisticated mechanism. This study proposed a novel signature-based technique to detect and handle the cooperative black hole attack in MANETs. For this purpose, diverse type of simulation scenarios are used with increasing number of nodes. The parameters such as average throughput, average packet drop, average end to end delay, average processing time and malicious node detection rate are used to measure the impact of signature-based malicious node detection scheme. AODV is used as routing protocol in this study. This study revealed that the performance of MANETs degrades with an increase in a number of malicious nodes. The average throughput of MANETs decreases with increase in average end to end delay and average packet drop. Signature-based malicious nodes detection mechanism is used to counter the cooperative black hole attack. The signature-based technique has enhanced the detection and elimination of cooperative black hole attack in MANETs. This helps in comparatively an increase in average throughput and decrease in packet delay and packet drop.

Mobile Ad-hoc Networks (MANETs) black hole attack AODV malicious node cooperative attack

Abstract doi.org/10.14569/IJACSA.2018.090350 PDF

51

QTID: Quran Text Image Dataset

Author 1: Mahmoud Badry Author 2: Hesham Hassan Author 3: Hanaa Bayomi Author 4: Hussien Oakasha

Improving the accuracy of Arabic text recognition in imagery requires a big modern dataset as data is the fuel for many modern machine learning models. This paper proposes a new dataset, called QTID, for Quran Text Image Dataset, the first Arabic dataset that includes Arabic marks. It consists of 309,720 different 192x64 annotated Arabic word images that contain 2,494,428 characters in total, which were taken from the Holy Quran. These finely annotated images were randomly divided into 90%, 5%, 5% sets for training, validation, and testing, respectively. In order to analyze QTID, a different dataset statistics were shown. Experimental evaluation shows that current best Arabic text recognition engines like Tesseract and ABBYY FineReader cannot work well with word images from the proposed dataset.

HDF5 dataset Arabic script Holy Quran text image handwritten text recognition Arabic OCR text image datasets

Abstract doi.org/10.14569/IJACSA.2018.090351 PDF

52

Analysis of Biometric Technology Adaption and Acceptance in Canada

Author 1: Eesa Al Solami

This study aimed at analyzing the analysis biometric technology adoption and acceptance in Canada. From the introduction, the paper reveals that biometrics technology has been in existence for many decades despite rising to popularity in the last two decades. Canada has highly advanced in information technology. It is observed that the three sectors for the adoption and acceptance of biometric technologies are: financial services, immigration, and law enforcement. The study uses judgment for sampling and questionnaires for the collection of data. Given the high rate of adoption and acceptance of biometric technologies in Canada, the paper concludes that the adoption of these technologies is at the adaptation state. Age and experience also influence the rate at which individuals accept biometric technologies with the most experienced participants showing the highest rate of approval.

Adaption biometric technology organizational

Abstract doi.org/10.14569/IJACSA.2018.090352 PDF

53

Enhancing Quality of Lossy Compressed Images using Minimum Decreasing Technique

Author 1: Ahmed L. Alshami Author 2: Mohammed Otair

The acceleration in technology development came with the urgent need to use large amounts of information, and the way of storing or transferring the huge information via various digital networks became very important issues, particularly in terms of compressing size and quality preservation. The digital image usage has become widespread in many sectors; it become important to manipulate these images to use them in optimal form by maintaining the quality, especially during the compression process using the lossy techniques. This paper presents a new technique to enhance the quality of compressed images while preserving the compression ratio by adding some of pre-processing steps before implementing any existing lossy compression technique. The proposed technique depends on decreasing the minimum elements from the image pixels values in each: row, column, and 2 2 block, respectively. These steps minimize the required number of bits to represent each pixel in the compressed images. In order to prove the efficiency of the proposed technique, two lossy compression techniques (novel and classical) were implemented with the proposed. They implemented on wide range of well-known images with different dimensions, sizes, and types. The experimental results show that the quality of the decompressed images with the proposed technique were enhanced in terms of: MSE, MAE and PSNR as quality evaluation metrics.

Image compression lossy technique lossless technique image quality measurement RIFD and JPEG

Abstract doi.org/10.14569/IJACSA.2018.090353 PDF

54

The Impact of Quantum Computing on Present Cryptography

Author 1: Vasileios Mavroeidis Author 2: Kamer Vishi Author 3: Mateusz D. Zych Author 4: Audun Jøsang

The aim of this paper is to elucidate the implications of quantum computing in present cryptography and to introduce the reader to basic post-quantum algorithms. In particular the reader can delve into the following subjects: present cryptographic schemes (symmetric and asymmetric), differences between quantum and classical computing, challenges in quantum computing, quantum algorithms (Shor’s and Grover’s), public key encryption schemes affected, symmetric schemes affected, the impact on hash functions, and post quantum cryptography. Specifically, the section of Post-Quantum Cryptography deals with different quantum key distribution methods and mathematicalbased solutions, such as the BB84 protocol, lattice-based cryptography, multivariate-based cryptography, hash-based signatures and code-based cryptography.

Quantum computers post-quantum cryptography Shor’s algorithm Grover’s algorithm asymmetric cryptography symmetric cryptography

Abstract doi.org/10.14569/IJACSA.2018.090354 PDF

55

Media Content Access: Image-based Filtering

Author 1: Rehan Ullah Khan Author 2: Ali Alkhalifah

As the content on the internet contains sensitive adult material, filtering and blocking this content is essential for the social and ethical values of the many societies and organizations. In this paper, the content filtering is explored from still images perspectives. Thus, this article investigates and analyses the content based filtering which can help in the flagging of the images as adult nature or safe images. As the proposed approach is based on the Chroma (colour) based skin segmentation and detection for detecting the objectionable content in images, therefore, the approach proceeds in the direction of the classical Machine Learning approaches and uses the two well-known classifiers: The Random Forest and the Neural Network. Their fusion is also investigated. Skin colour is analyzed in the YCbCr colour space and in the form of blob analysis. With the “Adult vs Safe” classification, an Accuracy of 0.88 and the low RMSE of 0.313 is achieved, indicating the usefulness of the detection model.

Skin detection content based filtering content analysis machine learning random forest neural network

Abstract doi.org/10.14569/IJACSA.2018.090355 PDF

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Half Mode Substrate Integrated Waveguide Cavity based RFID Chipless Tag

Author 1: Soumaya Sakouhi Author 2: Hedi Ragad Author 3: Mohamed Latrach Author 4: Ali Gharsallah

This study presents the design of a compact Radio Frequency Identification chipless tag, with reduced size, important quality factor and improved results. The proposed prototype is based on Substrate Integrated Waveguide technology using the Half-Mode Substrate Integrated Waveguide technique to reduce the tag size by the half and preserve the same response. Further, the operating frequency band is from 5.5 to 8 GHz inside a compact surface of 1.3 × 5.7 cm². The frequency domain approach is adopted based on the frequency shift coding technique.

Radio frequency identification (RFID) chipless tag substrate integrated waveguide (SIW) ultra wide band (UWB)

Abstract doi.org/10.14569/IJACSA.2018.090356 PDF