Software Engineering and Information Systems
Hamidah Ibrahim; Fatimah Sidi; Nur Izura Udzir; Poh Kuang Teo
Volume 4, Issue 4 , November 2018, , Pages 255-266
Abstract
Policy evaluation is a process to determine whether a request submitted by a user satisfies the access control policies defined by an organization. Modality conflict is one of the main issues in policy evaluation. Existing modality conflict detection approaches do not consider complex condition attributes ...
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Policy evaluation is a process to determine whether a request submitted by a user satisfies the access control policies defined by an organization. Modality conflict is one of the main issues in policy evaluation. Existing modality conflict detection approaches do not consider complex condition attributes such as spatial and temporal constraints. An effective authorization propagation rule is needed to detect the modality conflicts that occur among the applicable policies. This work proposes a modality conflict detection model to identify the applicable policies during policy evaluation, which supports an authorization propagation rule to investigate the class-subclass relationships of a subject, resource, action, and location of a request and a policy. The comparison with previous work is conducted, and findings show the solution which considers the condition attribute (i.e. spatial and temporal constraints) can affect the decision as to whether the applicable policies should be retrieved or not which further affect the accuracy of the modality conflict detection process. Whereas the applicable policies which are retrieved for a request can influence the detection of modality conflict among the applicable policies. In conclusion, our proposed solution is more effective in identifying the applicable policies and detecting modality conflict than the previous work.
Pattern Analysis and Intelligent Systems
Forogh Ahmadi; Vafa Maihami
Volume 5, Issue 4 , November 2019, , Pages 255-265
Abstract
Automatic image annotation is a process in which computer systems automatically assign the textual tags related with visual content to a query image. In most cases, inappropriate tags generated by the users as well as the images without any tags among the challenges available in this field have a negative ...
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Automatic image annotation is a process in which computer systems automatically assign the textual tags related with visual content to a query image. In most cases, inappropriate tags generated by the users as well as the images without any tags among the challenges available in this field have a negative effect on the query's result. In this paper, a new method is presented for automatic image annotation with the aim at improving the obtained tags, as well as reducing the effect of unrelated tags. In the proposed method, first, the initial tags are determined by extracting the low-level features of the image and using neighbor voting method. Afterwards, each initial tag is assigned by a degree based on the neighbor image features of the query image. Finally, they will be ranked based on summing the degrees of each tag and the best tags will be selected by removing the unrelated tags. The experiments conducted on the proposed method using the NUS-WIDE dataset and the commonly used evaluation metrics demonstrate the effectiveness of the proposed system compared to the previous works.
Forouz Ghaffarizadeh; Ahmad Khademzadeh
Volume 1, Issue 1 , February 2015, , Pages 51-58
Abstract
Mobile ad hoc networks (MANET) are constructed by mobile nodes without access point. Since MANET has certain constraints, including power shortages, an unstable wireless environment and node mobility, more power-efficient and reliable routing protocols are needed. The OLSR protocol is an optimization ...
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Mobile ad hoc networks (MANET) are constructed by mobile nodes without access point. Since MANET has certain constraints, including power shortages, an unstable wireless environment and node mobility, more power-efficient and reliable routing protocols are needed. The OLSR protocol is an optimization of the classical link state algorithm. OLSR introduces an interesting concept, the multipoint relays (MPRs), to mitigate the message overhead during the flooding process. Although very efficient by many points, it suffers from the drawbacks of not taking into account QoS metrics such as delay or bandwidth. To overcome this pitfall, some QOLSR solutions have been designed. IN this paper, we introduce an algorithm for MPRs selection based on Battery Capacity and Link Stability. Simulation results show that our proposed protocol is able to enhance throughput and improve end-to-end delay.
Pejman Goudarzi
Volume 1, Issue 1 , February 2015, , Pages 59-64
Abstract
Rate allocation has become a demanding task in data networks as diversity in users and traffics proliferate. Most commonly used algorithm in end hosts is TCP. This is a loss based scheme therefore it exhibits oscillatory behavior which reduces network performance. Moreover, since the price for all sessions ...
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Rate allocation has become a demanding task in data networks as diversity in users and traffics proliferate. Most commonly used algorithm in end hosts is TCP. This is a loss based scheme therefore it exhibits oscillatory behavior which reduces network performance. Moreover, since the price for all sessions is based on the aggregate throughput, losses that are caused by TCP affect other sessions as well and aggressively reduce their throughput and also have a drastic effect on the overall good put of the system. In this paper a new differentiated pricing method is proposed that not only reduces the loss phenomenon in the network, it improves the overall performance of the network and allows other sessions such as Proportional or Minimum Potential Delay schemes achieve more fair rates. Stability property of the algorithm is investigated and some numerical analysis is presented to verify the claims.
Pattern Analysis and Intelligent Systems
Nita M Thakare
Volume 6, Issue 1 , February 2020, , Pages 1-8
Abstract
Despite of achieving good performance in controlled environment, the conventional 3D face recognition systems still encounter problems in handling the large variations in lighting conditions, facial expression and head pose The humans use the hybrid approach to recognize faces and therefore in this proposed ...
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Despite of achieving good performance in controlled environment, the conventional 3D face recognition systems still encounter problems in handling the large variations in lighting conditions, facial expression and head pose The humans use the hybrid approach to recognize faces and therefore in this proposed method the human face recognition ability is incorporated by combining global and local information to develop a robust face recognition system.In this papers it is proposed that hybridization of global and local facial features and combination of 2D and 3D modality helps in improving performance of face recognition system. The main issue of existing face recognition systems is the high false accept rate which is not desirable when security is the main concern. Most of the existing face recognition techniques overcome these problems with some constraints. However, the proposed methodology has achieved better results and handled all the three issues successfully. Also the use of 2.5D images (Depth Map) and dimensionality reduced data (Eigen faces) has shown that the system is computationally reasonable.
Computer Networks and Distributed Systems
Abbas Ali Khan; Dr. Mohammad Hanif Ali; Dr. A. K. M. Fazlul Haque; Chandan Debnath; DR. Md. Ismail Jabiullah
Volume 6, Issue 1 , February 2020, , Pages 9-18
Abstract
A Detailed Exploration of usability statistics and Application Rating on short-range Wireless protocols Bluetooth (IEEE 802.15.1), ZigBee (IEEE 802.15.4), Wi-Fi (IEEE 802.11) and NFC (ISO/IEC 14443) has been performed that being representing of those prominent wireless protocols evaluating their main ...
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A Detailed Exploration of usability statistics and Application Rating on short-range Wireless protocols Bluetooth (IEEE 802.15.1), ZigBee (IEEE 802.15.4), Wi-Fi (IEEE 802.11) and NFC (ISO/IEC 14443) has been performed that being representing of those prominent wireless protocols evaluating their main characteristics and performances in terms of some metric such as co-existence, data rate, security, power consumption, joining time are analyzed and presented. Furthermore, considering the file sharing, tag connection, payment method apply and security parameters, usability statistics, application rating and research output is also depicted so that one can easily identify the scope of the protocols, and can visualize the most trending and demandable wireless protocol. A deeply analyzed bar graph illustrates the most demandable wireless protocol . This can be applied in any user's work in the Wireless Network lab and also be implemented in any real-world applications for the appropriate components and devices among the protocols in proper fields.
Pattern Analysis and Intelligent Systems
Aref Safari; Danial Barazandeh; Seyed Ali Khalegh Pour
Volume 6, Issue 1 , February 2020, , Pages 19-24
Abstract
Accurate segmentation of brain tumor plays a key role in the diagnosis of brain tumor. Preset and precise diagnosis of Magnetic Resonance Imaging (MRI) brain tumor is enormously significant for medical analysis. During the last years many methods have been proposed. In this research, a novel fuzzy approach ...
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Accurate segmentation of brain tumor plays a key role in the diagnosis of brain tumor. Preset and precise diagnosis of Magnetic Resonance Imaging (MRI) brain tumor is enormously significant for medical analysis. During the last years many methods have been proposed. In this research, a novel fuzzy approach has been proposed to classify a given MRI brain image as normal or cancer label and the intensity of the disease. The applied method first employed feature selection algorithms to extract features from images, and then followed by applying a median filter to reduce the dimensions of features. The brain MRI offers a valuable method to perform pre-and-post surgical evaluations, which are keys to define procedures and to verify their effects. The reduced dimension was submitted to a diagnosis algorithm. We retrospectively investigated a total of 19 treatment plans, each of whom has CT simulation and MRI images acquired during pretreatment. The dose distributions of the same treatment plans were calculated on original CT simulation images as ground truth, as well as on pseudo CT images generated from MRI images. The simulation results demonstrate that the proposed algorithm is promising.
Computer Networks and Distributed Systems
Bello Kontagora Nuhu; Olayemi Olaniyi; Dauda Aji Idris; Chinedu Onyema
Volume 6, Issue 1 , February 2020, , Pages 25-32
Abstract
Carbon Monoxide (CO) is the most abundant air pollutant gas and accumulates rapidly to dangerous concentrations even in areas that seem to be well ventilated. Carbon monoxide detectors/alarm systems exist but people who are old, hearing impaired, partially sighted or heavy sleepers may not get the warning ...
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Carbon Monoxide (CO) is the most abundant air pollutant gas and accumulates rapidly to dangerous concentrations even in areas that seem to be well ventilated. Carbon monoxide detectors/alarm systems exist but people who are old, hearing impaired, partially sighted or heavy sleepers may not get the warning or find it difficult to wake up and get out in the event of dangerous concentration of CO in their homes. This paper presents the development of a smart CO monitoring and control system to control the ventilation in a room when carbon monoxide concentration is at a level dangerous to human health. The system is comprised of a microcontroller interfaced with CO sensor (MQ-7) and ultrasonic distance sensor (HC-SR04) for CO concentration sampling and window state determination respectively. A third component interfaced with the controller is a DC motor, which accordingly control the window when the concentration of CO is high. A mechanism was provided to ensure that the fan in the room is ON and the window is completely open whenever CO concentration is high to ensure quick restoration of the air quality. Results from the performance evaluation of the system showed that it achieved an average response time of 6 seconds and consumed 321.62mW and 652.82mW of power during sampling and control respectively. The obtained results showed that the system is capable of responding quickly to dangerous concentration of CO, thus a desired attribute of CO monitoring systems hence, can adequately replace the existing systems with less power consumption.
fatima ali habqa
Volume 6, Issue 1 , February 2020, , Pages 33-38
Abstract
ABSRACTThis study presents the kinematic analysis of a four-degree freedom medical robotic arm using the Matlab and the robotic-tool, the arm was designed using a solid work program, As well as details of the control of the real design of this arm using Arduino Mega 2560, The specialist enters the position ...
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ABSRACTThis study presents the kinematic analysis of a four-degree freedom medical robotic arm using the Matlab and the robotic-tool, the arm was designed using a solid work program, As well as details of the control of the real design of this arm using Arduino Mega 2560, The specialist enters the position to be reached by the automatic arm (injection position), Or moving the arm to any position by entering the values of the corners of the joints, In this search, we have moved the arm to the selected position Without injecting into the muscle which need another study and a medical sensor determines the amount of needle entry in the muscle, According to criteria determined by the specialist and can be added to the designed interface.Key words: Kinetic study, medical robot, four degrees freedom, Labview, Arduino Mega 2560.Key words: Kinetic study, medical robot, four degrees freedom, Labview, Arduino Mega 2560.
ZAHER AHMED BAMASOOD
Volume 6, Issue 1 , February 2020, , Pages 39-46
Abstract
In this paper we present Document analysis and classification system to segment and classify contents of Arabic document images. This system includes preprocessing, document segmentation, feature extraction and document classification. A document image is enhanced in the preprocessing by removing noise, ...
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In this paper we present Document analysis and classification system to segment and classify contents of Arabic document images. This system includes preprocessing, document segmentation, feature extraction and document classification. A document image is enhanced in the preprocessing by removing noise, binarization, and detecting and correcting image skew. In document segmentation, an algorithm is proposed to segment a document image into homogenous regions. In document classification, Neural Network (Multilayer Perceptron- Back propagation) classifier is applied to classify each region to text or non text based on a number of features extracted in feature extraction. These features are collected from different other researchers’ works. Experiments were conducted on 398 document images selected randomly from printed Arabic text database (PATDB) which was selected from various printing forms which are advertisements, book chapters, magazines, newspapers, letters and reports documents. As results, the proposed segmentation algorithm achieved only 0.814% as ratio of the overlapping areas of the merged zones to the total size of zones and 1.938% as the ratio of missed areas to total size of zones. The features, that show the best accuracy individually, are Background Vertical Run Length (RL) Mean, and Standard Deviation of foreground.
Swathi B H; Gururaj H L
Volume 6, Issue 2 , May 2020, , Pages 47-60
Abstract
A Wireless Sensor Network consists of several tiny devices which have the capability to sense and compute the environmental phenomenon. These sensor nodes are deployed in remote areas without any physical protections. A Wireless Sensor Network can have various types of anomalies due to some random deployment ...
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A Wireless Sensor Network consists of several tiny devices which have the capability to sense and compute the environmental phenomenon. These sensor nodes are deployed in remote areas without any physical protections. A Wireless Sensor Network can have various types of anomalies due to some random deployment of nodes, obstruction and physical destructions. These anomalies can diminish the sensing and communication functionalities of the network. Many kinds of holes can be formed in a sensor network that creates geographically correlated areas. These holes are also responsible for creating communication voids. These voids do not let the packets to reach the destination and minimises the expected network performance. Hence it ought to be resolved. In this paper we presented different kinds of holes that infect the sensor network, their characteristics and the effects on successful communication within the sensor network .Later we presented a detailed review on different routing hole handing techniques available in literature ,their possible strengths and short comes. At last we also presented a qualitative comparison of these routing hole handing techniques.
Computer Networks and Distributed Systems
Zahra Nafarieh
Volume 6, Issue 2 , May 2020, , Pages 61-70
Abstract
Abstract— Bot networks are a serious threat to cyber security, whose destructive behavior affects network performance directly. Detecting of infected HTTP communications is a big challenge because infected HTTP connections are clearly merged with other types of HTTP traffic. Cybercriminals prefer ...
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Abstract— Bot networks are a serious threat to cyber security, whose destructive behavior affects network performance directly. Detecting of infected HTTP communications is a big challenge because infected HTTP connections are clearly merged with other types of HTTP traffic. Cybercriminals prefer to use the web as a communication environment to launch application layer attacks and secretly engage in forbidden activities, while TLS (Transport Layer Security) protocols allow encrypted communication between client and server in the context of Internet provides. Methods of analyzing traffic behavior do not depend on payloads. This means that they can work with encrypted network communication protocols. Traffic behavior analysis methods do not depend on package shipments, which means they can work with encrypted network communication protocols. Hence, the analysis of TLS and HTTP traffic behavior has been considered for detecting malicious activities. Because of the exchange of information in the network context is very high and the volume of information is very large, storing and indexing of this massive data require a Big data platform.
Pattern Analysis and Intelligent Systems
Ali Ahmad Ali
Volume 6, Issue 2 , May 2020, , Pages 71-78
Abstract
Abstract— An educational platform is presented here for the beginner students in the Simulation and Artificial Intelligence sciences. It provides with a start point of building and simulation of the manipulators, especially of 2R planar Robot. It also displays a method to replace the inverse kinematic ...
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Abstract— An educational platform is presented here for the beginner students in the Simulation and Artificial Intelligence sciences. It provides with a start point of building and simulation of the manipulators, especially of 2R planar Robot. It also displays a method to replace the inverse kinematic model (IKM) of the Robot with a simpler one, by using a Multi-Layer Perceptron Neural Network (MLP-NN), to make the end-effector able to track a specific path, which has a rectangular shape (in this article), and allocated in the robot's workspace. The method is based on Back-Propagation Levenberg Marquardt algorithm. This paper also suggests a good strategy for the simulation of the robot's motion in Matlab to tell the beginners how the operation could be done quite closely to the built-in Matlab functions. The control part was ignored here for the simplicity. So we can classify this paper as a manual in the robotic world.
Pattern Analysis and Intelligent Systems
Farhad Soleimanian Gharehchopogh; Sevda Haggi
Volume 6, Issue 2 , May 2020, , Pages 79-90
Abstract
The detection and prevention of crime, in the past few decades, required several years of research and analysis. However, today, thanks to smart systems based on data mining techniques, it is possible to detect and prevent crime in a considerably less time. Classification and clustering-based smart techniques ...
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The detection and prevention of crime, in the past few decades, required several years of research and analysis. However, today, thanks to smart systems based on data mining techniques, it is possible to detect and prevent crime in a considerably less time. Classification and clustering-based smart techniques can classify and cluster the crime-related samples. The most important factor in the clustering technique is to find the centrality of the clusters and the distance between the samples of each cluster and the center of the cluster. The problem with clustering techniques, such as k-modes, is the failure to precisely detect the centrality of clusters. Therefore, in this paper, Elephant Herding Optimization (EHO) Algorithm and k-modes are used for clustering and detecting the crime by means of detecting the similarity of crime with each other. The proposed model consists of two basic steps: First, the cluster centrality should be detected for optimized clustering; in this regard, the EHO Algorithm is used. Second, k-modes are used to find the clusters of crimes with close similarity criteria based on distance. The proposed model was evaluated on the Community and Crime dataset consisting of 1994 samples with 128 characteristics. The results showed that purity accuracy of the proposed model is equal to 91.45% for 400 replicates.
Computer Networks and Distributed Systems
Maryam Amiri Kamalabad; farhad mardukhi; naser Nematbakhsh
Volume 6, Issue 2 , May 2020, , Pages 91-106
Abstract
In general, Policy-based approaches play an important role in the management of web services, for instance, in the choice of semantic web service and quality of services (QoS) in particular. The present research work illustrates a procedure for the web service selection among functionality similar web ...
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In general, Policy-based approaches play an important role in the management of web services, for instance, in the choice of semantic web service and quality of services (QoS) in particular. The present research work illustrates a procedure for the web service selection among functionality similar web services based on WS-Policy semantic matching. In this study, the procedure of WS-Policy publishing in the UDDI registry was also described. The approach, which is used to represent the policies, is thus represented as semantic trees, and in this representation, measurable quality attributes are considered; and the certain matching operations are used to identify the similarity match via match function or similarity distance function. The illustration of semantic concepts and rules during policy matching, which is not possible by using a mere semantic concept, leads to better web service matches. The proposed approach has been validated through various tests that can evaluate the similarity of large and arbitrary sets of measurable quality attributes. We also compared the proposed procedure with the other ones. The proposed procedure for web service choose, which uses WS-Policy semantic matching, can be more effective to solve different problems like selection, composition, and substitution of services.
Pattern Analysis and Intelligent Systems
Esther N Khakata; Vincent Oteke Omwenga; Simon S. Msanjila
Volume 6, Issue 2 , May 2020, , Pages 107-118
Abstract
This paper focuses on the prediction of student learning styles using data mining techniques within their institutions. This prediction was aimed at finding out how different learning styles are achieved within learning environments which are specifically influenced by already existing factors. These ...
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This paper focuses on the prediction of student learning styles using data mining techniques within their institutions. This prediction was aimed at finding out how different learning styles are achieved within learning environments which are specifically influenced by already existing factors. These learning styles, have been affected by different factors that are mainly engraved and found within the students learning environment. To obtain the learning styles, a data mining technique was used and this explicitly involved the use of pattern analysis in order to identify the underlying learning styles in the data collected from the learners. This paper highlights the five major learning styles that describe the patterns extracted from the collected data. Therefore, considering the changed learning ecosystem, it is clear that prediction of student learning styles can be done when the various factor inputs within the student environment are brought together and analyzed to focus on learning within internet-mediated environments.
Computer Networks and Distributed Systems
Behzad Seif; mohammad goodarzi
Volume 7, Issue 2 , May 2021, , Pages 93-102
Abstract
Today, the use of wireless sensor networks has become very popular in many applications. Due to the connection in wireless sensor networks, it is done wirelessly, so they are naturally insecure and prone to various types of attacks. In the past, various solutions were offered in this regard, each of ...
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Today, the use of wireless sensor networks has become very popular in many applications. Due to the connection in wireless sensor networks, it is done wirelessly, so they are naturally insecure and prone to various types of attacks. In the past, various solutions were offered in this regard, each of which had its problems. Therefore, in this proposed solution, an attempt was made to solve these problems. The proposed solution for securing sensor nodes uses authentication based on the ZKP protocol, which has been improved with Interlock, and game theory has also been used to more quickly identify intrusive nodes. One of the most important benefits of the proposed solution is to prevent attacks such as sleep deprivation. The proposed algorithm is able to detect quickly and is able to prevent network damage in the fastest possible time. The proposed solution was implemented and reviewed in MATLAB environment and the studies showed a very good performance of the proposed method.
Software Engineering and Information Systems
Amir Abbas Farahmand; Reza Radfar; Alireza Poorebrahimi; Mani Sharifi
Volume 7, Issue 2 , May 2021, , Pages 103-126
Abstract
IoT, a state-of-the-art technology, faces many challenges in its growth and development. One of the main concerns is the potential threats posed by the spread of such technology in the world. The widespread adoption and spread of such a technology can threaten us much more seriously than the Internet ...
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IoT, a state-of-the-art technology, faces many challenges in its growth and development. One of the main concerns is the potential threats posed by the spread of such technology in the world. The widespread adoption and spread of such a technology can threaten us much more seriously than the Internet currently available. The challenges we face in adopting such technology will include both the social and the technical aspects. Technical limitations include security considerations, privacy, as well as the resource, energy, and capacity issues for such a large amount of data and processing. Besides, socially, cultural infrastructure must first be provided for the diffusion of such technologies among the community. This study aimed to investigate the factors affecting the readiness level of the acceptance of IoT technologies. The relationships are examined as six main categories identified, namely the social aspect, the cultural aspect, the human aspect, the technological aspect, the financial aspect, the management aspect, government laws, and regulations. The opinions of senior ICT executives nationwide were collected. The statistical population of this study consists of experts and users of the financial sector, stock exchange, and financial institutions. Since the statistical population is infinite, 384 randomly available individuals are selected. SMART.PLS was used to validate the model and test the relationships between variables. The results indicate the impact of the identified categories on IoT adoption readiness.
Pattern Analysis and Intelligent Systems
Abdulbaghi Ghaderzadeh; sahar Hosseinpanahi; Sarkhel Taher kareem
Volume 7, Issue 2 , May 2021, , Pages 115-125
Abstract
Nowadays, spam is a major challenge regarding emails. Spam is a specific type of email that is sent to the network for malicious purposes. Spam plays an important role in stealing information and can include fake links to trick users. Machine learning and data mining techniques such as artificial neural ...
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Nowadays, spam is a major challenge regarding emails. Spam is a specific type of email that is sent to the network for malicious purposes. Spam plays an important role in stealing information and can include fake links to trick users. Machine learning and data mining techniques such as artificial neural networks are the most applicable methods to detect spam. The multi-layer artificial neural network needs to select the most important features as inputs to reduce the output error for accurate spam detection. In the proposed method, a smart method based on swarm intelligence algorithms is used for feature selection. In this study, a binary version of Emperor Penguin Optimizer (EPO) is used to select more appropriate features. The proposed method uses the selected features for learning and classification in the spam detection process. Experiments in the MATLAB environment on the Spambase dataset show that with the increase in population the error in spam detection in Emails will decrease about 14.61% and with the increase in feature space, it will decrease about 43.85% in the best situation. Experiments show that the proposed method has less error in detecting spam compare to other methods, multilayer artificial neural network, recursive neural network, support vector machine, Bayesian network, and whale optimization algorithm. Experiments show that the error of spam detection in the proposed approach is about 23.57% less than the whale optimization algorithm. Empirical results, obtained through simulations on the Spambase dataset, show our approach outperforms the other existing methods on precision value.
Computer Networks and Distributed Systems
Fatemeh Davami; Sahar Adabi; Ali Rezaee; Amir Masoud Rahamni
Volume 7, Issue 2 , May 2021, , Pages 126-136
Abstract
In the last ten years, the Cloud data centers have been manifested as the crucial computing architectures to enable extreme data workflows. Due to the complicatedness and diverse kinds of computational resources like Fog nodes and Cloud servers, workflow scheduling has been proposed to be the main challenge ...
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In the last ten years, the Cloud data centers have been manifested as the crucial computing architectures to enable extreme data workflows. Due to the complicatedness and diverse kinds of computational resources like Fog nodes and Cloud servers, workflow scheduling has been proposed to be the main challenge in Cloud and or Fog computing environments. For resolving this issue, the present study offers a scheduling algorithm according to the critical path extraction, referred to as the Critical Path Extraction Algorithm (CPEA). In fact, it is one of the new multi-criteria decision-making algorithms to extract the critical paths of multiple workflows because it is of high importance to find the critical path in the creation and control of the scheduling. Moreover, an extensive software simulation investigation has been performed to compare this new algorithm in the real work-loads and recent algorithm. We compare our algorithm with the GRP-HEFT algorithm. The experimental results confirm the proposed algorithm's superiority in fulfilling make-span and waiting time and that workflow scheduling based on CPEA further improves the workflow make-span and waiting time.
Computer Networks and Distributed Systems
Bharat Mahaur; Aishwarya Gupta
Volume 6, Issue 3 , August 2020, , Pages 133-144
Abstract
Vehicular Ad-Hoc Networks (VANETs) is a novel technology that has recently emerged and due to its swift changing topology and high mobility nature, it has become problematic to design an efficient routing protocol in VANETs’ amongst both moving and stationary units. Also, the existing routing algorithms ...
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Vehicular Ad-Hoc Networks (VANETs) is a novel technology that has recently emerged and due to its swift changing topology and high mobility nature, it has become problematic to design an efficient routing protocol in VANETs’ amongst both moving and stationary units. Also, the existing routing algorithms are not very effective to satisfy all requirements of VANETs. This paper explores the need of a reliable routing and proposes an approach that makes use of an extended restricted greedy forwarding mechanism to select the next forwarding vehicle on basis of its average relative velocity and neighborhood density with its own neighboring vehicles. We also use static PCR junction node which forwards the packet to correct road segment vehicle based upon the relative information. The objective of this paper is to increase route reliability by increasing throughput with considerable end to end delay. Simulation results show that the proposed approach IJDRP outperforms existing GPCR and E-GyTAR.
Pattern Analysis and Intelligent Systems
reza molaee fard
Volume 7, Issue 2 , May 2021, , Pages 137-146
Abstract
Recommending systems are systems that, by taking limited information from the user and features such as what the user has searched for in the past and what product they have rated, can correctly identify the user and the desired items Offer the user. The user's desired items are suggested to him through ...
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Recommending systems are systems that, by taking limited information from the user and features such as what the user has searched for in the past and what product they have rated, can correctly identify the user and the desired items Offer the user. The user's desired items are suggested to him through the user profile. In this research, a new method is presented to recommend the user's interests in the form of the user's personalized profile. The way to do this is to use other users' searched information in the form of a database to recommend to new users. The procedure is that we first collect a log file from the items searched by users, then we pre-process this log file to remove the data from the raw state and clean it. Then, using data weighting and using the score function, we extract the most searched items of users in the past and provide them to the user in the form of a recommendation system based on participatory filtering. Finally, we use our data using an algorithm. We optimize the cuckoo that this information can be of interest to the user. The results of this study showed 99% accuracy and 97% frequency, which can to a large extent correctly predict the user's favorite items and pages and start with the problem that is the problem of most recommender systems To confront.
Computer Networks and Distributed Systems
Derdus Kenga; Vincent Oteke Omwenga; Patrick Job Ogao
Volume 6, Issue 3 , August 2020, , Pages 145-154
Abstract
The ability to measure the energy consumed by cloud infrastructure is a crucial step towards the development of energy efficiency policies in the cloud infrastructure. There are hardware-based and software-based methods of measuring energy usage in cloud infrastructure. However, most hardware-based energy ...
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The ability to measure the energy consumed by cloud infrastructure is a crucial step towards the development of energy efficiency policies in the cloud infrastructure. There are hardware-based and software-based methods of measuring energy usage in cloud infrastructure. However, most hardware-based energy measurement methods measure the energy consumed system-wide - including the energy lost in transit. In an environment such as the cloud, where energy consumption can be a result of different components, it is important to isolate the energy, which is consumed as a result of executing application workloads. This information can be crucial in making decisions such as workload consolidation. In this paper, we propose an experimental approach of measuring power consumption as a result of executing application workloads in IaaS cloud. This approach is based on Intel’s Running Average Power Limit (RAPL) interface. Application workload is obtained from Phoronix Test Suite (PTS)’ 7zip and aio-stress. To demonstrate the feasibility of this approach, we have described an approach, which can be used to study the effect of workload consolidation on CPU and I/O's power performance by varying the number of Virtual Machines (VMs) . Power is measured in watts. Performance of CPU is measured in Million Instructions per Second (MIPS) and I/O performance (as a result of processing data intensive) is measured in MB/s. Our results on the effect of workload consolidation has been compared with previous research and was found to be consistent. This shows that the proposed method of measuring power consumption is accurate.
Pattern Analysis and Intelligent Systems
Razieh Asgarnezhad; Karrar Ali Mohsin Alhameedawi
Volume 7, Issue 2 , May 2021, , Pages 147-156
Abstract
Due to the importance of automatic identification of brain conditions, many researchers concentrate on Epilepsy disorder to aim to the detecting of eye states and classification systems. Eye state recognition has a vital role in biomedical informatics such as controlling smart home devices, driving detection, ...
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Due to the importance of automatic identification of brain conditions, many researchers concentrate on Epilepsy disorder to aim to the detecting of eye states and classification systems. Eye state recognition has a vital role in biomedical informatics such as controlling smart home devices, driving detection, etc. This issue is known as electroencephalogram signals. There are many works in this context in which traditional techniques and manually extracted features are used. The extraction of effective features and the selection of proper classifiers are challenging issues. In this study, a classification system named PEML-E was proposed in which a different pre-processing stage is used. The ensemble methods in the classification stage are compared to the base classifiers and the most important works in this context. To evaluate, a freely available public EEG eye state dataset from UCI is applied. The highest accuracy, precision, recall, F1, specificity, and sensitivity are obtained 95.88, 95.39, 96.25, 96.18, 96.25, and 95.44%, respectively.
Computer Networks and Distributed Systems
Hanieh Ghorashi; Meghdad Mirabi
Volume 6, Issue 3 , August 2020, , Pages 155-168
Abstract
Cloud computing is a model for convenient on-demand user’s access to changeable and configurable computing resources such as networks, servers, storage, applications, and services with minimal management of resources and service provider interaction. Task scheduling is regarded as a fundamental ...
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Cloud computing is a model for convenient on-demand user’s access to changeable and configurable computing resources such as networks, servers, storage, applications, and services with minimal management of resources and service provider interaction. Task scheduling is regarded as a fundamental issue in cloud computing which aims at distributing the load on the different resources of a distributed system in order to optimize resource utilization and response time. In this paper, an optimization-based method for task scheduling is presented in order to improve the efficiency of cloud computing. In the proposed approach, three criteria for scheduling, including the task execution time, the task transfer time, and the cost of task execution have been considered. Our method not only reduces the execution time of the overall tasks but also minimizes the maximum time required for task execution. We employ the Multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) for solving the scheduling problem. To evaluate the efficiency of the proposed method, a real cloud environment is simulated, and a similar method based on Multi-Objective Particle Swarm Optimization is applied. Experimental results show the superiority of our approach over the baseline technique.