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2020

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Articles 1261 - 1290 of 2675

Full-Text Articles in Computer Engineering

Tga: Team Game Algorithm, M.J. Mahmoodabadi Jun 2020

Tga: Team Game Algorithm, M.J. Mahmoodabadi

Future Computing and Informatics Journal

Lately, there is a growing interest in conducting research on optimization algorithms due to their wide range of engineering applications. One of the optimization algorithms' categories is evolutionary algorithms which are inspired from the natural behavior of animals and humans. Further, each of the evolutionary algorithms has its own advantages and disadvantages in convergence accuracy and computational time. In the present paper, a novel solution search algorithm taken from the team games is introduced. This evolutionary algorithm named Team Game Algorithm (TGA) involves passing a ball, making mistakes and substitution operators. Comparing the TGA's results to the outcomes of other …

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Hybrid Energy Aware Clustered Protocol For Iot Heterogeneous Network, Rowayda A. Sadek Jun 2020

Hybrid Energy Aware Clustered Protocol For Iot Heterogeneous Network, Rowayda A. Sadek

Future Computing and Informatics Journal

IoT diverse applications face many challenges. The main challenge is to have efficient energy aware communication protocols that utilize the diversity and heterogeneity of the connected things through Internet. Saving energy is a vital requirement in the limited battery energy nodes and also for the outsourced energy nodes for green computing. IoT milieu has many diverse devices that are heterogeneous in their energies, their Internet availability, etc. These devices are usually distributed into regions with different heterogeneity levels; ranging from homogeneous to near homogenous, till reaching to the high heterogeneous regions. Many existed protocols efficiently treated either the homogenous devices …

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A Fast Sift Based Method For Copy Move Forgery Detection, Hesham A. Alberry, Abdelfatah A. Hegazy, Gouda I. Salama Jun 2020

A Fast Sift Based Method For Copy Move Forgery Detection, Hesham A. Alberry, Abdelfatah A. Hegazy, Gouda I. Salama

Future Computing and Informatics Journal

Image forensics is an important area of research used to indicate if a particular image is original or subjected to any kind of tampering. Images are essential part of judgment in tribunals. For forensic analysis, image forgery-detection techniques used to identify the forged images. In this paper, an effective algorithm to indicate Copy Move Forgery in digital image presented. The Scale Invariant Feature Transform (SIFT) and Fuzzy C-means (FCM) for clustering are utilized in the proposed algorithm. A number of numerical experiments performed using the MICC-220 dataset. The authors created an additional dataset, which consisted of 353 color images. The …

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Withdrawn: Forecasting Of Nonlinear Time Series Using Artificial Neural Network, Amr Badr Jun 2020

Withdrawn: Forecasting Of Nonlinear Time Series Using Artificial Neural Network, Amr Badr

Future Computing and Informatics Journal

When forecasting time series, it is important to classify them according to linearity behavior; the linear time series remains at the forefront of academic and applied research. It has often been found that simple linear time series models usually leave certain aspects of economic and financial data unexplained. The dynamic behavior of most of the time series in our real life, with its autoregressive and inherited moving average terms, pose the challenge to forecast nonlinear times series that contain inherited moving average terms using computational intelligence methodologies such as neural networks. It is rare to find studies that concentrate on …

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Attribute Selection Using Fuzzy Roughset Based Customized Similarity Measure For Lung Can Cer Microarra Y Gene Expression Data, C. Arunkumar, S. Ramakrishnan Jun 2020

Attribute Selection Using Fuzzy Roughset Based Customized Similarity Measure For Lung Can Cer Microarra Y Gene Expression Data, C. Arunkumar, S. Ramakrishnan

Future Computing and Informatics Journal

Microarray gene expression data plays a prominent role in feature selection that helps in diagnosis and treatment of a wide variety of diseases. Microarray gene expression data contains redundant feature genes of high dimensionality and smaller training and testing samples. This paper proposes a customized similarity measure using fuzzy rough quick reduct algorithm for attribute selection. Information Gain based entropy is used to reduce the dimensionality in the first stage and the proposed fuzzy rough quick reduct method that defines a customized similarity measure for selecting the minimum number of informative genes and removing the redundant genes is employed at …

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Hcidl: Human-Computer Interface Description Language For Multi-Target, Multimodal, Plastic User Interfaces, Abdelkrim Benamar, Lamia Gaouar, Olivier Le Goaer, Frédérique Biennier Jun 2020

Hcidl: Human-Computer Interface Description Language For Multi-Target, Multimodal, Plastic User Interfaces, Abdelkrim Benamar, Lamia Gaouar, Olivier Le Goaer, Frédérique Biennier

Future Computing and Informatics Journal

From the human-computer interface perspectives, the challenges to befaced are related to the consideration of new, multiple interactions, and the diversity of devices. The large panel of interactions (touching, shaking, voice dictation, positioning …) and the diversification of interaction devices can be seen as a factor of flexibility albeit introducing incidental complexity. Our work is part of the field of user interface description languages. After an analysis of the scientific context of our work, this paper introduces HCIDL, a modelling language staged in a model-driven engineering approach. Among the properties related to human-computer interface, our proposition is intended for modelling …

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A Survey On Opinion Summarization Technique S For Social Media, Mohammed Elsaid Moussa, Ensaf Hussein Mohamed, Mohamed H. Haggag Jun 2020

A Survey On Opinion Summarization Technique S For Social Media, Mohammed Elsaid Moussa, Ensaf Hussein Mohamed, Mohamed H. Haggag

Future Computing and Informatics Journal

The volume of data on the social media is huge and even keeps increasing. The need for efficient processing of this extensive information resulted in increasing research interest in knowledge engineering tasks such as Opinion Summarization. This survey shows the current opinion summarization challenges for social media, then the necessary pre-summarization steps like preprocessing, features extraction, noise elimination, and handling of synonym features. Next, it covers the various approaches used in opinion summarization like Visualization, Abstractive, Aspect based, Query-focused, Real Time, Update Summarization, and highlight other Opinion Summarization approaches such as Contrastive, Concept-based, Community Detection, Domain Specific, Bilingual, Social Bookmarking, …

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Patient Symptoms Elicitation Process For Breast Cancer Medical Expert Systems: A Semantic Web And Natural Language Parsing Approach, O.N. Oyelade, A.A. Obiniyi, S.B. Junaidu, S.A. Adewuyi Jun 2020

Patient Symptoms Elicitation Process For Breast Cancer Medical Expert Systems: A Semantic Web And Natural Language Parsing Approach, O.N. Oyelade, A.A. Obiniyi, S.B. Junaidu, S.A. Adewuyi

Future Computing and Informatics Journal

Information gathering from patient by clinicians during diagnostic procedures may sometimes require some skills to adequately collect required information that will be sufficient for the procedure. A situation where this information gathering may proof difficult in when a diagnostic decision making support system (DDSS) will have to gather such information from patient before carrying out the diagnostic procedure. Research has proven that it is more challenging to ensure user or patient inputs, in their raw form, maps into the list of acceptable medical terms for diagnostic tasks. This paper therefore proposes a formalized input generating model that addresses this shortcoming …

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Classification Using Deep Learning Neural Networks For Brain Tumors, Heba Mohsen Jun 2020

Classification Using Deep Learning Neural Networks For Brain Tumors, Heba Mohsen

Future Computing and Informatics Journal

Deep Learning is a new machine learning field that gained a lot of interest over the past few years. It was widely applied to several applications and proven to be a powerful machine learning tool for many of the complex problems. In this paper we used Deep Neural Network classifier which is one of the DL architectures for classifying a dataset of 66 brain MRIs into 4 classes e.g. normal, glioblastoma, sarcoma and metastatic bronchogenic carcinoma tumors. The classifier was combined with the discrete wavelet transform (DWT) the powerful feature extraction tool and principal components analysis (PCA) and the evaluation …

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Depth-Based Human Activity Recognition: A Comparative Perspective Study On Feature Extraction, Heba Hamdy Ali, Hossam M. Moftah, Aliaa A.A. Youssif Jun 2020

Depth-Based Human Activity Recognition: A Comparative Perspective Study On Feature Extraction, Heba Hamdy Ali, Hossam M. Moftah, Aliaa A.A. Youssif

Future Computing and Informatics Journal

Depth Maps-based Human Activity Recognition is the process of categorizing depth sequences with a particular activity. In this problem, some applications represent robust solutions in domains such as surveillance system, computer vision applications, and video retrieval systems. The task is challenging due to variations inside one class and distinguishes between activities of various classes and video recording settings. In this study, we introduce a detailed study of current advances in the depth maps-based image representations and feature extraction process. Moreover, we discuss the state of art datasets and subsequent classification procedure. Also, a comparative study of some of the more …

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Privacy-Preserving Data Aggregation In Resource-Constrained Sensor Nodes In Internet Of Things: A Review, Inayat Ali Jun 2020

Privacy-Preserving Data Aggregation In Resource-Constrained Sensor Nodes In Internet Of Things: A Review, Inayat Ali

Future Computing and Informatics Journal

Privacy problems are lethal and getting more attention than any other issue with the notion of the Internet of Things (IoT). Since IoT has many application areas including smart home, smart grids, smart healthcare system, smart and intelligent transportation and many more. Most of these applications are fueled by the resource-constrained sensor network, such as Smart healthcare system is powered by Wireless Body Area Network (WBAN) and Smart home and weather monitoring systems are fueled by Wireless Sensor Networks (WSN). In the mentioned application areas sensor node life is a very important aspect of these technologies as it explicitly effects …

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Simultaneous Ranking And Selection Of Keystroke Dynamics Features Through A Novel Multi-Objective Binary Bat Algorithm, Taha M. Mohamed, Hossam M. Moftah Jun 2020

Simultaneous Ranking And Selection Of Keystroke Dynamics Features Through A Novel Multi-Objective Binary Bat Algorithm, Taha M. Mohamed, Hossam M. Moftah

Future Computing and Informatics Journal

In this paper, we propose a novel multi-objective binary bat algorithm for simultaneous ranking and selection of keystroke dynamics features. The proposed algorithm uses the V shaped binarization function. Simulation results show that, the proposed algorithm can efficiently identify the most important features of the data set. Of the three feature classes, the key down hold time features (H-features) are proofed to be the most dominant features. Using H-features only in classification decreases the mean square error (MSE) by 2% compared to choosing all features in classification. The UD features are the second ranked features. The worst features are the …

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Overcoming Business Process Reengineering Obstacles Using Ontology-Based Knowledge Map Methodology, Mahmoud Abdellatif, Marwa Salah Farhan, Naglaa Saeed Shehata Jun 2020

Overcoming Business Process Reengineering Obstacles Using Ontology-Based Knowledge Map Methodology, Mahmoud Abdellatif, Marwa Salah Farhan, Naglaa Saeed Shehata

Future Computing and Informatics Journal

Business process reengineering (BPR) is identified as one of the most important solutions for organizational improvements in all performance measures of business processes. However, high failure rates 70% is reported about using it the most important reason that caused the failure is the focus on the process itself; regardless of the surrounding environment, and the knowledge of the organization. The other reasons are due to the lack of tools to determine the causes of the inconsistencies and inefficiencies. This paper proposes Process Reengineering Ontology-based knowledge Map Methodology (PROM) to reduce the failure ratio, solve BPR problems, and overcome their difficulties. …

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Pulsar Selection Using Fuzzy Knn Classifier, Taha M. Mohamed Jun 2020

Pulsar Selection Using Fuzzy Knn Classifier, Taha M. Mohamed

Future Computing and Informatics Journal

Pulsars are rare type of stars that emit radio signals that could be detected from earth. Astronomy scientists give more attention to this type of stars for many reasons. In the near past, the problem of pulsar selection was carried out manually. Recently, neural network techniques are proposed to solve the problem. In this paper, we present a novel technique to efficiently selecting pulsars. The proposed algorithm is based on the fuzzy knn classifier. Results show that, the proposed algorithm outperforms five other classifiers, including neural network classifiers, using three evaluation metrics. The proposed algorithm is evaluated on the recent …

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A Robust 3d Mesh Watermarking Algorithm Utilizing Fuzzy C-Means Clustering, Ola M. El Zein, Lamiaa M. El Bakrawy, Neveen I. Ghali Prof. Jun 2020

A Robust 3d Mesh Watermarking Algorithm Utilizing Fuzzy C-Means Clustering, Ola M. El Zein, Lamiaa M. El Bakrawy, Neveen I. Ghali Prof.

Future Computing and Informatics Journal

A new robust 3D watermarking algorithm utilizing Fuzzy C-Means (FCM) clustering technique is presented. FCM clusters 3D mesh vertices into suitable and unsuitable choices to insert the watermark without occasioning visible deformation, and also it is tough for the attacker to determine places of the watermark insertion. Two watermarking processes are offered to insert the watermark into 3D mesh models. The first process utilizes topical statistical measurements like average and standard deviation in order to alter the values of vertices to secret watermark data into 3D mesh models, however, the second process utilizes a jumbled insertion planning to insert the …

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An Improved Rank Based Disease Prediction Using Web Navigation Patterns On Bio-Medical Databases, P. Dhanalakshmi, K. Ramani Jun 2020

An Improved Rank Based Disease Prediction Using Web Navigation Patterns On Bio-Medical Databases, P. Dhanalakshmi, K. Ramani

Future Computing and Informatics Journal

Applying machine learning techniques to on-line biomedical databases is a challenging task, as this data is collected from large number of sources and it is multi-dimensional. Also retrieval of relevant document from large repository such as gene document takes more processing time and an increased false positive rate. Generally, the extraction of biomedical document is based on the stream of prior observations of gene parameters taken at different time periods. Traditional web usage models such as Markov, Bayesian and Clustering models are sensitive to analyze the user navigation patterns and session identification in online biomedical database. Moreover, most of the …

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A Framework For Safer Driving In Mauritius, V Bassoo, V Hurbungs, V. Ramnarain Seetohul, T.P Fowdur, Y Beeharry Jun 2020

A Framework For Safer Driving In Mauritius, V Bassoo, V Hurbungs, V. Ramnarain Seetohul, T.P Fowdur, Y Beeharry

Future Computing and Informatics Journal

According to the National Transport Authority (NTA), there were 493,081 registered vehicles in Mauritius in April 2016, which represents a 1.4% annual increase compared to 2015. Despite the sensitization campaigns and the series of measures setup by the Minister of Public Infrastructure and Land Transport, the number of road accidents continues to rise. The three main elements that contribute to accidents are: road infrastructure, vehicle and driver. The driver has the highest contribution in collisions. If the driver is given the right information (e.g. driving behaviour, accident-prone areas and vehicle status) at the right time, he/she can make better driving …

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Feature Level Review Table Generation For E-Commerce Websites To Produce Qualitative Rating Of The Products, Kumar Raja, S Pushpa Jun 2020

Feature Level Review Table Generation For E-Commerce Websites To Produce Qualitative Rating Of The Products, Kumar Raja, S Pushpa

Future Computing and Informatics Journal

It is widely acknowledged today that E-Commerce business is growing rapidly. This is happened only because of people are completely depending on the ratings and reviews given by the customers who are already purchased and using the products. Online surveys, customer reviews on shopping sites are the key sources to understand customer requirements and feedback to help upgrade the product quality and achieve greater outcomes. Now the challenge is that whether those reviews came from product level or feature level will be the million dollar question. To overcome this problem we are proposing a new algorithm to give feature level …

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Pentagonal Fuzzy Number, Its Properties And Application In Fuzzy Equation, Sankar Mondal Jun 2020

Pentagonal Fuzzy Number, Its Properties And Application In Fuzzy Equation, Sankar Mondal

Future Computing and Informatics Journal

The paper presents an adaptation of pentagonal fuzzy number. Different type of pentagonal fuzzy number is formed. The arithmetic operation of a particular type of pentagonal fuzzy number is addressed here. The difference between two pentagonal valued functions is also addressed here. Demonstration of pentagonal fuzzy solutions of fuzzy equation is carried out with the said numbers. Additionally, an illustrative example is also taken with the useful graph and table for usefulness for attained to the proposed concept

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Informative Gene Selection Using Adaptive Analytic Hierarchy Process (A2hp), Abhishek Bhola, Shafa Mahajan Jun 2020

Informative Gene Selection Using Adaptive Analytic Hierarchy Process (A2hp), Abhishek Bhola, Shafa Mahajan

Future Computing and Informatics Journal

Gene expression dataset derived from microarray experiments are marked by large number of genes, which contains the gene expression values at different sample conditions/time-points. Selection of informative genes from these large datasets is an issue of major concern for various researchers and biologists. In this study, we propose a gene selection and dimensionality reduction method called Adaptive Analytic Hierarchy Process (A2HP). Traditional analytic hierarchy process is a multiple-criteria based decision analysis method whose result depends upon the expert knowledge or decision makers. It is mainly used to solve the decision problems in different fields. On the other hand, A2HP is …

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A New Method To Reduce The Effects Of Http-Get Flood Attack, Hamid Mirvaziri Jun 2020

A New Method To Reduce The Effects Of Http-Get Flood Attack, Hamid Mirvaziri

Future Computing and Informatics Journal

HTTP Get Flood attack is known as the most common DDOS attack on the application layer with a frequency of 21 percent in all attacks. Since a huge amount of requests is sent to the Web Server for receiving pages and also the volume of responses issued by the server is much more than the volume received by zombies in this kind of attack, hence it could be done by small botnets; in the other hand, because every zombie attempts to issue the request by the use of its real address, carries out all stages of the three-stage handshakes, and …

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Wavelet Based Transition Region Extraction For Image Segmentation, Priyadarsan Parida, Nilamani Bhoi Jun 2020

Wavelet Based Transition Region Extraction For Image Segmentation, Priyadarsan Parida, Nilamani Bhoi

Future Computing and Informatics Journal

Transition region based approaches are recent hybrid segmentation techniques well known for its simplicity and effectiveness. Here, the segmentation effectiveness depends on robust extraction of transition regions. So, we have proposed a transition region method which initially decomposes the gray image in wavelet domain. Two existing transition region approaches are applied on approximate coefficients to extract transition region feature matrix. Using this feature matrix the corresponding prominent wavelet coefficients of different bands are found. Inverse wavelet transform are then applied on the modified coefficients to get edge image with more than one pixel width. Otsu thresholding is applied on it …

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Enersave Api: Android-Based Power-Saving Framework For Mobile Devices, Y Beeharry, A.M Muharum, V Hurbungs, Vershley Joyejob Jun 2020

Enersave Api: Android-Based Power-Saving Framework For Mobile Devices, Y Beeharry, A.M Muharum, V Hurbungs, Vershley Joyejob

Future Computing and Informatics Journal

Power consumption is a major factor to be taken into consideration when using mobile devices in the IoT field. Good Power management requires proper understanding of the way in which it is being consumed by the end-devices. This paper is a continuation of the work in Ref. [1] and proposes an energy saving API for the Android Operating System in order to help developers turn their applications into energy-aware ones. The main features heavily used for building smart applications, greatly impact battery life of Android devices and which have been taken into consideration are: Screen brightness, Colour scheme, CPU frequency, …

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Forecasting Of Nonlinear Time Series Using Ann, Ahmed Tealab, Hesham Hefny, Amr Badr Jun 2020

Forecasting Of Nonlinear Time Series Using Ann, Ahmed Tealab, Hesham Hefny, Amr Badr

Future Computing and Informatics Journal

When forecasting time series, it is important to classify them according linearity behavior that the linear time series remains at the forefront of academic and applied research, it has often been found that simple linear time series models usually leave certain aspects of economic and financial data unexplained. The dynamic behavior of most of the time series in our real life with its autoregressive and inherited moving average terms issue the challenge to forecast nonlinear times series that contain inherited moving average terms using computational intelligence methodologies such as neural networks. It is rare to find studies that concentrate on …

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Designing Fuzzy Rule Base Using Spider Monkey Optimization Algorithm In Cooperative Framework, Joydip Dhar Jun 2020

Designing Fuzzy Rule Base Using Spider Monkey Optimization Algorithm In Cooperative Framework, Joydip Dhar

Future Computing and Informatics Journal

The paper focusses on the implementation of cooperative Spider Monkey Optimization Algorithm (SMO) to design and optimize the fuzzy rule base. Spider Monkey Optimization Algorithm is a fission-fusion based Swarm Intelligence algorithm. Cooperative Spider Monkey Algorithm is an off-line algorithm used to optimize all the free parameters in a fuzzy rule base. The Spider Monkeys are divided into various groups the solution from each group represents a fuzzy rule. These groups work in a cooperative way to design the whole fuzzy rule base. Simulation on fuzzy rules of two nonlinear controllers is done with a parametric study to verify the …

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Interesting Association Rule Mining With Consistent And Inconsistent Rule Detection From Big Sales Data In Distributed Environment, Dinesh J. Prajapati, Sanjay Garg, N.C. Chauhan Jun 2020

Interesting Association Rule Mining With Consistent And Inconsistent Rule Detection From Big Sales Data In Distributed Environment, Dinesh J. Prajapati, Sanjay Garg, N.C. Chauhan

Future Computing and Informatics Journal

Nowadays, there is an increasing demand in mining interesting patterns from the big data. The process of analyzing such a huge amount of data is really computationally complex task when using traditional methods. The overall purpose of this paper is in twofold. First, this paper presents a novel approach to identify consistent and inconsistent association rules from sales data located in distributed environment. Secondly, the paper also overcomes the main memory bottleneck and computing time overhead of single computing system by applying computations to multi node cluster. The proposed method initially extracts frequent itemsets for each zone using existing distributed …

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A Survey On Exploring Key Performance Indicators, Amira Idrees Jun 2020

A Survey On Exploring Key Performance Indicators, Amira Idrees

Future Computing and Informatics Journal

Key Performance Indicators (KPIs) allows gathering knowledge and exploring the best way to achieve organization goals. Many researchers have provided different ideas for determining KPI's either manually, and semi-automatic, or automatic which is applied in different fields. This work concentrates on providing a survey of different approaches for exploring and predicting key performance indicators (KPIs).

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A Survey Of Iot Cloud Platforms, Partha Pratim Ray Jun 2020

A Survey Of Iot Cloud Platforms, Partha Pratim Ray

Future Computing and Informatics Journal

Internet of Things (IoT) envisages overall merging of several “things” while utilizing internet as the backbone of the communication system to establish a smart interaction between people and surrounding objects. Cloud, being the crucial component of IoT, provides valuable application specific services in many application domains. A number of IoT cloud providers are currently emerging into the market to leverage suitable and specific IoT based services. In spite of huge possible involvement of these IoT clouds, no standard cum comparative analytical study has been found across the literature databases. This article surveys popular IoT cloud platforms in light of solving …

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A Cloud Interoperability Broker (Cib) For Data Migration In Saas, Hassan Ali, Ramdan Mowad, Amira Farouk Jun 2020

A Cloud Interoperability Broker (Cib) For Data Migration In Saas, Hassan Ali, Ramdan Mowad, Amira Farouk

Future Computing and Informatics Journal

Cloud computing is becoming increasingly popular. Information technology market leaders, e.g., Microsoft, Google, and Amazon, are extensively shifting toward cloud-based solutions. However, there is isolation in the cloud implementations provided by the cloud vendors. Limited interoperability can cause one user to adhere to a single cloud provider; thus, a required migration of an application or data from one cloud provider to another may necessitate a significant effort and/or full-cycle redevelopment to fit the new provider's standards and implementation. The ability to move from one cloud vendor to another would be a step toward advancing cloud computing interoperability and increasing customer …

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Fixing Rules For Data Cleaning Based On Conditional Functional Dependency, Asmaa Abdo Jun 2020

Fixing Rules For Data Cleaning Based On Conditional Functional Dependency, Asmaa Abdo

Future Computing and Informatics Journal

Most existing databases suffer from data inconsistencies. Enhancing data quality efforts are necessary to resolve this issue. In this paper, two techniques are proposed for mining accurate conditional functional dependencies rules from such databases to be employed for data cleaning. The idea of the proposed techniques is to mine firstly maximal closed frequent patterns, then mine the dependable conditional functional dependencies rules with the help of lift measure. Moreover, data repairing algorithm is proposed for fixing inconsistent tuples found in the database exploiting the generated rules. An extensive experimental is conducted study to confirm the effectiveness of the proposed techniques …

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