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2020

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Articles 4501 - 4530 of 10642

Full-Text Articles in Engineering

Constraint-Type Fictitious Time Integration Method For Solving Non-Linear Multi-Dimensional Elliptic Partial Differential Equations, Yung-Wei Chen, Chein-Shan Liu, Yen-Shen Chang, Jiang-Ren Chang Jun 2020

Constraint-Type Fictitious Time Integration Method For Solving Non-Linear Multi-Dimensional Elliptic Partial Differential Equations, Yung-Wei Chen, Chein-Shan Liu, Yen-Shen Chang, Jiang-Ren Chang

Journal of Marine Science and Technology–Taiwan

In this paper, we propose a constraint-type fictitious time integration method (FTIM) for solving multi-dimensional non-linear elliptic-type partial differential equations. Based on the variable transformation of FTIM, the original governing equation is transformed into a new parabolic equation of an evolution type by introducing a space-time variable, and a new time integration direction is obtained. However, the space-time variable depends on the governing equation, boundary condition and fictitious time variable, especially due to the nonlinear effect. Previous studies have not discussed the definition of these nonlinear parameter problems, which may result in severe numerical instability and inaccuracy. To completely overcome …

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Resistive Switching In Atomic Layer Deposited Hfo2/Zro2 Nanolayer Stacks, Lin Tang, Hiraku Maruyama, Taihao Han, Juan C. Nino, Yonghong Chen, Dou Zhang Jun 2020

Resistive Switching In Atomic Layer Deposited Hfo2/Zro2 Nanolayer Stacks, Lin Tang, Hiraku Maruyama, Taihao Han, Juan C. Nino, Yonghong Chen, Dou Zhang

Materials Science and Engineering Faculty Research & Creative Works

The resistive switching properties of HfO2/ZrO2 nanolayers with the total thickness of 16 nm prepared using atomic layer deposition (ALD) were investigated. Current-voltage behavior, pulse time mode measurement, retention and endurance tests were carried out to characterize the memristive (memory-resistive) properties. Resistive switching was observed in all nanolayer stacks, and the set voltage (Vset) decreased with increasing the number of layers (i.e., increasing number of hafnia-zirconia interfaces). Grazing incidence x-ray diffraction (GI-XRD) results demonstrate that the hafnia transforms from monoclinic to orthorhombic crystal structure during the post metallization annealing. Shifts in the binding energy of the x-ray …

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Numerical Analyses Of Pile Foundation For Support Structure Of Offshore Wind Turbine At Changhua Coast In Taiwan, Der-Guey Lin, Sheng-Hsien Wang, Jui-Ching Chou, Cheng-Yu Ku, Lien-Kwei Chien Jun 2020

Numerical Analyses Of Pile Foundation For Support Structure Of Offshore Wind Turbine At Changhua Coast In Taiwan, Der-Guey Lin, Sheng-Hsien Wang, Jui-Ching Chou, Cheng-Yu Ku, Lien-Kwei Chien

Journal of Marine Science and Technology–Taiwan

This study investigates the bearing capacities of group pile foundation (jacket foundation) installed on the seabed of offshore wind farm (OWF) at the Changhua coast of Western Taiwan for the jacket support structure of offshore wind turbine (OWT) using three-dimensional (3-D) finite element method (FEM). The jacket foundations are subjected to a combined Vertical-Horizontal-Moment (V-H-M) loading for the operational period. The responses of installed group pile foundations are investigated under the combined loading in marine silty sand-low plasticity silt & clay (SM-ML-CL) layers determined by 19 offshore boring logs. The validity of numerical procedures was verified by a large-scale lateral …

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Extraction Of Chitosan From Died Honey Bee Apis Mellifera, Gulnora Akmalovna Ixtiyarova, Dilshoda Azamovna Hazratova, Bobur Nosir O’G’Li Umarov, Oksana Muratbayevna Seytnazarova Jun 2020

Extraction Of Chitosan From Died Honey Bee Apis Mellifera, Gulnora Akmalovna Ixtiyarova, Dilshoda Azamovna Hazratova, Bobur Nosir O’G’Li Umarov, Oksana Muratbayevna Seytnazarova

Chemical Technology, Control and Management

This article presents the results of obtaining biopolymers of chitin and chitosan from a new promising source- died honey bee apis mellifera. To obtain chitin, at the first stage, the protein (deproteination) and mineral (demineralization) constituents of subpestilence, i.e. put them in soluble state and removed. Demineralization was carried out with 2 M hudrochloric acid for 5 hours at room temperature. The process of deproteination is carried out by processing the crushed raw materials with 1 N sodium hudroxide solution for 1 hour at a temperature of 800С. Each process was accompanied by washing the raw materials to …

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Using Of Parametric Nonlinear Lc-Circuits In Stabilized Transducers Of The Number Of Phases, Ivan Mikhaylovich Bedritsky, Kamila Komilovna Jurayeva, Laziz Kholboboyevich Bozorov Jun 2020

Using Of Parametric Nonlinear Lc-Circuits In Stabilized Transducers Of The Number Of Phases, Ivan Mikhaylovich Bedritsky, Kamila Komilovna Jurayeva, Laziz Kholboboyevich Bozorov

Chemical Technology, Control and Management

The use of nonlinear circuits of an autoparametric nature with inductive and capacitive elements for obtaining the necessary phase shifts in single-phase-three-phase converters is considered. The amplitude-phase relations between the stresses of windings located on different rods of a three-core core are obtained. The conditions under which it is possible to stabilize the stresses of the artificial phases of the Converter, as well as the phase shifts between them, are shown.

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Application Of A Convolutional Neural Networks For Images Recognition, Avazjon Rakhimovich Marakhimov, Lyudmila Petrovna Varlamova Jun 2020

Application Of A Convolutional Neural Networks For Images Recognition, Avazjon Rakhimovich Marakhimov, Lyudmila Petrovna Varlamova

Chemical Technology, Control and Management

In the problems of image recognition, various approaches used when the image is noisy and there is a small sample of observations. The paper discusses nonparametric recognition methods and methods based on deep neural networks. This neural network allows you to collapse images, to perform downsampling as many times as necessary. Moreover, the image recognition speed is quite high, and the data dimension is reduced by using convolutional layers. One of the most important elements of the application of convolutional neural networks is training. The article gives the results of work on the application of convolutional neural networks. The work …

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Development Of A Control Device And Algorithm For Autonomous-Moving Systems, Farhod Qosimov, Ru Jiang, Dong Zhang, Mirkhalil Ismailov Jun 2020

Development Of A Control Device And Algorithm For Autonomous-Moving Systems, Farhod Qosimov, Ru Jiang, Dong Zhang, Mirkhalil Ismailov

Chemical Technology, Control and Management

The article is devoted to improving the control and algorithm for Autonomous moving systems. The function of the controller is to provide communication between the control computer and the actuator. The ATmega2560 microcontroller is selected as the main processor. The electrical diagram of additional devices of the microcontroller is formed. Printed circuit boards consisting of separate blocks are made on the basis of the electrical circuit. To exchange information with external systems and process the received data, a special algorithm for the microcontroller has been created. The microcontroller is programmed based on this algorithm. The analysis of the functioning of …

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Smart Drugs:Improving Healthcare Using Smart Pill Box For Medicine Reminder And Monitoring System, Diaa Salama Abdul Minaam, Mohamed Abd-Elfattah Jun 2020

Smart Drugs:Improving Healthcare Using Smart Pill Box For Medicine Reminder And Monitoring System, Diaa Salama Abdul Minaam, Mohamed Abd-Elfattah

Future Computing and Informatics Journal

Many medical errors are due to the fact that people in charge of patient or elder's medication have to deal with sorting huge amounts of pills each day. This paper consists on the conception, design and creation of a pillbox prototype intended to solve this deficiency in the medical area as it has the ability of sorting out the pills by itself as well as many other advanced features, with this device being intended to be used by hospitals or retirement homes. This medication pill box is focused on patients who frequently take medications or vitamin supplements, or attendants who …

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Antlion Optimization And Boosting Classifier For Spam Email Detection, Amany A. Naem, Neveen I. Ghali Prof., Afaf A. Saleh Jun 2020

Antlion Optimization And Boosting Classifier For Spam Email Detection, Amany A. Naem, Neveen I. Ghali Prof., Afaf A. Saleh

Future Computing and Informatics Journal

Spam emails are not necessary, though they are harmful as they include viruses and spyware, so there is an emerging need for detecting spam emails. Several methods for detecting spam emails were suggested based on the methods of machine learning, which were submitted to reduce non relevant emails and get results of high precision for spam email classification. In this work, a new predictive method is submitted based on antlion optimization (ALO) and boosting termed as ALO-Boosting for solving spam emails problem. ALO is a computational model imitates the preying technicality of antlions to ants in the life cycle. Where …

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A New Online Scheduling Approach For Enhancing Qos In Cloud, Aida A. Nasr, Nirmeen A. El-Bahnasawy, Gamal Attiya, Ayman El-Sayed Jun 2020

A New Online Scheduling Approach For Enhancing Qos In Cloud, Aida A. Nasr, Nirmeen A. El-Bahnasawy, Gamal Attiya, Ayman El-Sayed

Future Computing and Informatics Journal

Quality-of-Services (QoS) is one of the most important requirements of cloud users. So, cloud providers continuously try to enhance cloud management tools to guarantee the required QoS and provide users the services with high quality. One of the most important management tools which play a vital role in enhancing QoS is scheduling. Scheduling is the process of assigning users’ tasks into available Virtual Machines (VMs). This paper presents a new task scheduling approach, called Online Potential Finish Time (OPFT), to enhance the cloud data-center broker, which is responsible for the scheduling process, and solve the QoS issue. The main idea …

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Automatic Labeling Of Hidden Web Data Using Multi-Heuristics Annotator, Umamageswari Baskaran, R. Kalpana Jun 2020

Automatic Labeling Of Hidden Web Data Using Multi-Heuristics Annotator, Umamageswari Baskaran, R. Kalpana

Future Computing and Informatics Journal

Hidden web contains huge amount of high quality data which are not indexed to search engines. Hidden web refers to web pages which are generated dynamically by embedding backend data matching the search keywords, in server-side templates. They are created for human consumption and makes automated processing cumbersome since structured data is embedded within unstructured HTML tags. In order to enable machine processing, structured data must be detected, extracted and annotated. Many heuristic based approaches DeLa [1], MSAA [2] are available in the literature to perform automatic annotation. Most of these techniques fail if data values didn't contain labels present …

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A Systematic Review For The Determination And Classification Of The Crm Critical Success Factors Supporting With Their Metrics, Mahmoud Abd Ellatif, Marwa Salah Farhan, Amira Hassan Abed Jun 2020

A Systematic Review For The Determination And Classification Of The Crm Critical Success Factors Supporting With Their Metrics, Mahmoud Abd Ellatif, Marwa Salah Farhan, Amira Hassan Abed

Future Computing and Informatics Journal

The successful implementation of customer relationship management (CRM) is not easy and seems to be a complex task. Almost about 70% of all CRM implementation projects fail to achieve their expected objectives. Therefore, most researchers and information systems developers concentrate on the critical success factors approach which can enhance the success of CRM implementation and turn the failure and drawbacks faced CRM into successful CRM systems adoption and implementation. In this paper, the number of the previous studies is reviewed to demonstrate the barriers behind this high failure rate. In addition, an extensive review is conducted in order to identify …

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Stage – Specific Predictive Models For Main Prognosis Measures Of Breast Cancer, Ahmed Attia Said, Laila A. Abd-Elmegid, Sherif Kholeif, Ayman Abdelsamie Gaber Jun 2020

Stage – Specific Predictive Models For Main Prognosis Measures Of Breast Cancer, Ahmed Attia Said, Laila A. Abd-Elmegid, Sherif Kholeif, Ayman Abdelsamie Gaber

Future Computing and Informatics Journal

Breast cancer is a malignant tumor that starts in the cells of the breast. A malignant tumor is a group of cancer cells that can grow into near tissues or invading the distant areas of the body. The disease occurs almost entirely in women, but men can get it, too. Survival rate, recurrence detection and disease-free survival rate (DFS) are the main patient's outcome and prognosis measures. Breast cancer outcomes are vary among different stages of the disease. There are five stages of breast cancer named as 0, 1, 2, 3, and 4. Prognosis helps doctors to save patients' lives …

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Applying Spatial Intelligence For Decision Support Systems, Amira Idrees, Mohamed H. Ibrahim Jun 2020

Applying Spatial Intelligence For Decision Support Systems, Amira Idrees, Mohamed H. Ibrahim

Future Computing and Informatics Journal

Data mining is one of the vital techniques that could be applied in different fields such as medical, educational and industrial fields. Extracting patterns from spatial data is very useful to be used for discovering the trends in the data. However, analyzing spatial data is exhaustive due to its details as it is related to locations with a special representation such as longitude and latitude. This paper aims at proposing an approach for applying data mining techniques over spatial data to find trends in the data for decision support. Basic information considering spatial data is presented with presenting the proposed …

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An Qos Based Multifaceted Matchmaking Framework For Web Services Discovery, G. Sambasivam Jun 2020

An Qos Based Multifaceted Matchmaking Framework For Web Services Discovery, G. Sambasivam

Future Computing and Informatics Journal

With the increasing demand, the web service has been the prominent technology for providing good solutions to the interoperability of different kind of systems. Web service supports mainly interoperability properties as it is the major usage of this promising technology. Although several technologies had been evolved before web service technology and this has more advantage of other technologies. This paper has concentrated mainly on the Multifaceted Matchmaking framework for Web Services Discovery using Quality of Services parameters. Traditionally web services have been discovered only with the functional properties like input, output, precondition and effect. Nowadays there is an increase in …

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Medical Image Retrieval Using Self-Organising Map On Texture Features, Shashwati Mishra Jun 2020

Medical Image Retrieval Using Self-Organising Map On Texture Features, Shashwati Mishra

Future Computing and Informatics Journal

The process of capturing, transfer and sharing of information in the form of digital images have become easier due to the use of advanced technologies. Retrieval of desired images from these huge collections of image databases is one of the popular research areas and has its applications in various fields. An image set consists of images containing objects of different colours, shapes, orientations and sizes. The surface texture of the object in an image may also vary from another object in a different image. These factors make the process of image retrieval a difficult one. In this paper, Self-Organising Map …

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Benign And Malignant Breast Cancer Segmentation Using Optimized Region Growing Technique, S. Punitha, A. Amuthan, K. Suresh Joseph Jun 2020

Benign And Malignant Breast Cancer Segmentation Using Optimized Region Growing Technique, S. Punitha, A. Amuthan, K. Suresh Joseph

Future Computing and Informatics Journal

Breast cancer is one of the dreadful diseases that affect women globally. The occurrences of breast masses in the breast region are the main cause for women to develop a breast cancer. Early detection of breast mass will increase the survival rate of women and hence developing an automated system for detection of the breast masses will support radiologists for accurate diagnosis. In the pre-processing step, the images are pre-processed using Gaussian filtering. An automated detection method of breast masses is proposed using an optimized region growing technique where the initial seed points and thresholds are optimally generated using a …

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A Genetic Algorithm For Service Flow Management With Budget Constraint In Heterogeneous Computing, Ahmed A. Abdulhamed, Medhat A. Tawfeek, Arabi E. Keshk Jun 2020

A Genetic Algorithm For Service Flow Management With Budget Constraint In Heterogeneous Computing, Ahmed A. Abdulhamed, Medhat A. Tawfeek, Arabi E. Keshk

Future Computing and Informatics Journal

Heterogeneous computing supply various and scalable resources for many applications requirements. Its structure is based on interconnecting machines with several processing capacity spread over networks. The scientific bioinformatics and many other applications demand service flow processing in which services have dependencies execution. The environments of this computing are suitable for huge computational needs that contains diverse groups of services. Managing and mapping services of service flow to the suitable candidates who provides the service is classified as NP-complete problem. The managing such interdependent services on heterogeneous environments also takes the Quality of Service (QoS) requirements from users into account. This …

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Time Series Forecasting Using Artificial Neural Networks Methodologies: A Systematic Review, Ahmed Tealab Jun 2020

Time Series Forecasting Using Artificial Neural Networks Methodologies: A Systematic Review, Ahmed Tealab

Future Computing and Informatics Journal

This paper studies the advances in time series forecasting models using artificial neural network methodologies in a systematic literature review. The systematic review has been done using a manual search of the published papers in the last 11 years (2006e2016) for the time series forecasting using new neural network models and the used methods are displayed. In the covered period in the study, the results obtained found 17 studies that meet all the requirements of the search criteria. Only three of the obtained proposals considered a process different to the autoregressive of a neural networks model. These results conclude that, …

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Fuzzy Clustering Based Transition Region Extraction For Image Segmentation, Priyadarsan Parida Jun 2020

Fuzzy Clustering Based Transition Region Extraction For Image Segmentation, Priyadarsan Parida

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 clustering approach based transition region extraction method for image segmentation. The proposed method initially uses the local variance of the input image to get the variance feature image. Fuzzy C-means clustering is applied to the variance feature image to separate the transitional features from the feature image. Further, Otsu thresholding is applied to the transitional feature image to extract the transition region. For extracting the exact edge image, morphological …

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A Low Cost Autonomous Unmanned Ground Vehicle, Leckraj Nagowah Jun 2020

A Low Cost Autonomous Unmanned Ground Vehicle, Leckraj Nagowah

Future Computing and Informatics Journal

The aim of this project is to design and implement a low cost Autonomous Unmanned Ground Vehicle (AUGV), a vehicle that can be controlled remotely without an onboard human presence. The AUGV is also able to move autonomously while automatically detecting and avoiding obstacles. The vehicle also reads directions from QR codes, calculates the shortest path to its destination and autonomous move towards its final destination. A Raspberry Pi 3 has been used as the brain of the vehicle together with other components such as DC and Servo motors, Ultrasonic and Infrared sensors, webcam, batteries, power bank, motor controller and …

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Distributed Processing Of Location Based Spatial Query Through Vantage Point Transformation, M. Priya, R. Kalpana Jun 2020

Distributed Processing Of Location Based Spatial Query Through Vantage Point Transformation, M. Priya, R. Kalpana

Future Computing and Informatics Journal

Location Based Services is the popular and geo sensitive service implicated over the smart phone by internet. Nowadays these system find its own enhancement, as they are using device‘s real time geographical information to provide information and entertainment. It allows the user to get the response to the query based on their current location there by location becomes the most basic context for the user. For example these services are used to check in restaurants, coffee shops to get the business reward from the nearest shop or to track the location of a person. The user of the smart phone …

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A Proposed Hybrid Model For Adopting Cloud Computing In E-Government, Kh. E. Ali, Sh. A. Mazen, E. E. Hassanein Jun 2020

A Proposed Hybrid Model For Adopting Cloud Computing In E-Government, Kh. E. Ali, Sh. A. Mazen, E. E. Hassanein

Future Computing and Informatics Journal

Many developing countries are now experiencing revolution in e-government to deliver fluent and simple services for their citizens. However, governmental sectors face many challenges in using its e-governments’ services and its infrastructure, improving current services or developing new services; as data and applications increasingly inflating, IT budget costs, software licensing and support and difficulties in migration, integration and management for software and hardware. These challenges may lead to failure of e-governments’ projects. Therefore, there is a need for a solution to overcome these challenges. Cloud Computing plays a vital role to solve these problems. This paper demonstrates egovernment's obstacles and …

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Non-Sequential Partitioning Approaches To Decision Tree Classifier, Shankru Guggari, Vijayakumar Kadappa, V. Umadevi Jun 2020

Non-Sequential Partitioning Approaches To Decision Tree Classifier, Shankru Guggari, Vijayakumar Kadappa, V. Umadevi

Future Computing and Informatics Journal

Decision tree is a well-known classifier which is widely used in real-world applications. It is easy to interpret, however it suffers from instability and lower classification performance for high-dimensionality datasets due to curse of dimensionality. Feature set partitioning is a novel concept to address the higher dimensionality problem by dividing the feature set into subsets (blocks). Many of the existing partitioning based decision tree approaches are sequential in nature, which lack logical relationships amongst the features. In this work, we propose novel non-sequential feature set partitioning methods by exploiting the ideas of Ferrer Diagram and Bell Triangle to create feature …

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Feature Based Transition Region Extraction For Image Segmentation: Application To Worm Separation From Leaves, Priyadarsan Parida, Nilamani Bhoi Jun 2020

Feature Based Transition Region Extraction For Image Segmentation: Application To Worm Separation From Leaves, 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 transition region extraction method for image segmentation. The proposed method initially decomposes the gray image in wavelet domain. Local standard deviation filtering and thresholding operation is used to extract transition region feature matrix. Using this feature matrix, the corresponding prominent wavelet coefficients of different bands are found. The inverse wavelet transform is then applied to the modified coefficients to get edge image with more than one-pixel width. Global thresholding …

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Partition Based Clustering Of Large Datasets Using Mapreduce Framework: An Analysis Of Recent Themes And Directions, Tanvir Habib Sardar, Zahid Ansari Jun 2020

Partition Based Clustering Of Large Datasets Using Mapreduce Framework: An Analysis Of Recent Themes And Directions, Tanvir Habib Sardar, Zahid Ansari

Future Computing and Informatics Journal

Data clustering is one of the fundamental techniques in scientific analysis and data mining, which describes a dataset according to similarities among its objects. Partition based clustering algorithms are the most popular and widely used clustering technique. In this information era, due to the digitization of every field, the huge volume of data is available to data analysts. The quick growth of such datasets makes decade old computing platforms, programming paradigms, and clustering algorithms become inadequate to obtain knowledge from these datasets. To cluster such large datasets, Hadoop distributed platform, MapReduce programming paradigm and modified clustering algorithms are being used …

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Bio-Inspired Computing: Algorithms Review, Deep Analysis, And The Scope Of Applications, Ashraf Darwish Prof. Jun 2020

Bio-Inspired Computing: Algorithms Review, Deep Analysis, And The Scope Of Applications, Ashraf Darwish Prof.

Future Computing and Informatics Journal

Bio-inspired computing represents the umbrella of different studies of computer science, mathematics, and biology in the last years. Bioinspired computing optimization algorithms is an emerging approach which is based on the principles and inspiration of the biological evolution of nature to develop new and robust competing techniques. In the last years, the bio-inspired optimization algorithms are recognized in machine learning to address the optimal solutions of complex problems in science and engineering. However, these problems are usually nonlinear and restricted to multiple nonlinear constraints which propose many problems such as time requirements and high dimensionality to find the optimal solution. …

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Task Schedul Ing For Cloud Computing Using Multi-Objective Hybrid Bacteria Foraging Algorithm, Sobhanayak Srichandan, Turuk Ashok Kumar, Sahoo Bibhudatta Jun 2020

Task Schedul Ing For Cloud Computing Using Multi-Objective Hybrid Bacteria Foraging Algorithm, Sobhanayak Srichandan, Turuk Ashok Kumar, Sahoo Bibhudatta

Future Computing and Informatics Journal

Cloud computing is the delivery of computing services over the internet. Cloud services allow individuals and other businesses organization to use data that are managed by third parties or another person at remote locations. Most Cloud providers support services under constraints of Service Level Agreement (SLA) definitions. The SLAs are composed of different quality of service (QoS) rules promised by the provider. A cloud environment can be classified into two types: computing clouds and data clouds. In computing cloud, task scheduling plays a vital role in maintaining the quality of service and SLA. Efficient task scheduling is one of the …

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An Analysis Of Mapreduce Efficiency In Document Clustering Using Parallel K-Means Algorithm, Tanvir Habib Sardar, Zahid Ansari Jun 2020

An Analysis Of Mapreduce Efficiency In Document Clustering Using Parallel K-Means Algorithm, Tanvir Habib Sardar, Zahid Ansari

Future Computing and Informatics Journal

One of the significant data mining techniques is clustering. Due to expansion and digitalization of each field, large datasets are being generated rapidly. Such large dataset clustering is a challenge for traditional sequential clustering algorithms due to huge processing time. Distributed parallel architectures and algorithms are thus helpful to achieve performance and scalability requirement of clustering large datasets. In this study, we design and experiment a parallel k-means algorithm using MapReduce programming model and compared the result with sequential k-means for clustering varying size of document dataset. The result demonstrates that proposed k-means obtains higher performance and outperformed sequential k-means …

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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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