Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Computer Engineering (65)
- Computer and Systems Architecture (7)
- Computational Engineering (5)
- Civil and Environmental Engineering (4)
- Electrical and Computer Engineering (4)
-
- Structural Engineering (4)
- Architecture (2)
- Education (2)
- Other Computer Engineering (2)
- Academic Advising (1)
- Analytical, Diagnostic and Therapeutic Techniques and Equipment (1)
- Automotive Engineering (1)
- Biomedical (1)
- Business (1)
- Business Analytics (1)
- Business Intelligence (1)
- Chemical Engineering (1)
- Civil Engineering (1)
- Community College Leadership (1)
- Construction Engineering and Management (1)
- Data Storage Systems (1)
- Digital Communications and Networking (1)
- Electrical and Electronics (1)
- Electronic Devices and Semiconductor Manufacturing (1)
- Engineering Education (1)
- Geography (1)
- Health and Medical Administration (1)
- Management Information Systems (1)
- Manufacturing (1)
- Keyword
-
- Forecasting; Nonlinear time series; Neural networks; Moving averages (3)
- Machine Learning (2)
- Activity recognition; Depth; Feature extraction; Video; Human body detection; Hand gesture (1)
- Algorithmic Composition Artificial Intelligence (1)
- Annotation; Semantic labeling; Deep web; Surface web (1)
-
- Antiques (1)
- Architectural design (1)
- Automatic Programming (1)
- Autonomous; Unmanned vehicle; Robots; Sensors (1)
- Biomedical documents; PubMed; Rank prediction; Web usage; User patterns; Server log (1)
- Boosting classifier; Antlion optimization; Feature selection; Spam email; Classification (1)
- Breast cancer; Survival rate (SR); Disease free survival (DFS); Recurrence detection; Prediction; Data mining (1)
- Business process reengineering; Knowledge map; Ontology; Analytic hierarchical processing (1)
- Bvlgari (1)
- Chinese Remainder Theorem (CRT). (1)
- Cloud ERP; SaaS ERP; SLR; Cloud ERP benefits; Cloud ERP challenges (1)
- Cloud computing models; E-government; E-government's challenges; Governmental cloud (1)
- Cloud computing; Interoperability; SaaS broker (1)
- Cloud computing; Resource allocation; Pareto solutions; Bacteria foraging; Genetic algorithms (1)
- Cloud computing; Task scheduling; QOS; Load balancing (1)
- Cloud-based Healthcare systems (1)
- Cold-formed Steel frames Finite Element Modeling Moment-rotation (1)
- Colorectal Cancer Deep Learning Algorithms (1)
- Complaint Handling System (1)
- Complaint Management System (1)
- Computational Intelligence (1)
- Computer Music (1)
- Concept Map (1)
- Continuous requirements prioritization. (1)
- Controller (1)
Articles 31 - 60 of 78
Full-Text Articles in Engineering
A Low Cost Autonomous Unmanned Ground Vehicle, Leckraj Nagowah
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 …
Distributed Processing Of Location Based Spatial Query Through Vantage Point Transformation, M. Priya, R. Kalpana
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 …
A Proposed Hybrid Model For Adopting Cloud Computing In E-Government, Kh. E. Ali, Sh. A. Mazen, E. E. Hassanein
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 …
Non-Sequential Partitioning Approaches To Decision Tree Classifier, Shankru Guggari, Vijayakumar Kadappa, V. Umadevi
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 …
Feature Based Transition Region Extraction For Image Segmentation: Application To Worm Separation From Leaves, Priyadarsan Parida, Nilamani Bhoi
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 …
Partition Based Clustering Of Large Datasets Using Mapreduce Framework: An Analysis Of Recent Themes And Directions, Tanvir Habib Sardar, Zahid Ansari
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 …
Bio-Inspired Computing: Algorithms Review, Deep Analysis, And The Scope Of Applications, Ashraf Darwish Prof.
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. …
Task Schedul Ing For Cloud Computing Using Multi-Objective Hybrid Bacteria Foraging Algorithm, Sobhanayak Srichandan, Turuk Ashok Kumar, Sahoo Bibhudatta
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 …
An Analysis Of Mapreduce Efficiency In Document Clustering Using Parallel K-Means Algorithm, Tanvir Habib Sardar, Zahid Ansari
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 …
Tga: Team Game Algorithm, M.J. Mahmoodabadi
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 …
An Optimization Approach For Automated Unit Test Generation Tools Using Multi-Objective Evolutionary Algorithms, Samar Ali Abdallah, Ramdan Mowad, Esaam Eldeen Fawzy
An Optimization Approach For Automated Unit Test Generation Tools Using Multi-Objective Evolutionary Algorithms, Samar Ali Abdallah, Ramdan Mowad, Esaam Eldeen Fawzy
Future Computing and Informatics Journal
High code coverage is measured by the process of software testing typically using automatic test case generation tools. This standard approach is usually used for unit testing to improve software reliability. Most automated test case generation tools focused just on code coverage without considering its cost and redundancy between generated test cases. To obtain optimized high code coverage and to ensure minimum cost and redundancy a Multi-Objectives Evolutionary Algorithm approach (MOEA) is set in motion. An efficient approach is proposed and applied to different algorithms from MOEA Frame from the separate library with three fitness functions for Coverage, Cost, and …
Hybrid Energy Aware Clustered Protocol For Iot Heterogeneous Network, Rowayda A. Sadek
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 …
A Fast Sift Based Method For Copy Move Forgery Detection, Hesham A. Alberry, Abdelfatah A. Hegazy, Gouda I. Salama
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 …
Withdrawn: Forecasting Of Nonlinear Time Series Using Artificial Neural Network, Amr Badr
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 …
Attribute Selection Using Fuzzy Roughset Based Customized Similarity Measure For Lung Can Cer Microarra Y Gene Expression Data, C. Arunkumar, S. Ramakrishnan
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 …
Hcidl: Human-Computer Interface Description Language For Multi-Target, Multimodal, Plastic User Interfaces, Abdelkrim Benamar, Lamia Gaouar, Olivier Le Goaer, Frédérique Biennier
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 …
A Survey On Opinion Summarization Technique S For Social Media, Mohammed Elsaid Moussa, Ensaf Hussein Mohamed, Mohamed H. Haggag
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, …
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
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 …
Classification Using Deep Learning Neural Networks For Brain Tumors, Heba Mohsen
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 …
Depth-Based Human Activity Recognition: A Comparative Perspective Study On Feature Extraction, Heba Hamdy Ali, Hossam M. Moftah, Aliaa A.A. Youssif
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 …
Privacy-Preserving Data Aggregation In Resource-Constrained Sensor Nodes In Internet Of Things: A Review, Inayat Ali
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 …
Simultaneous Ranking And Selection Of Keystroke Dynamics Features Through A Novel Multi-Objective Binary Bat Algorithm, Taha M. Mohamed, Hossam M. Moftah
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 …
Overcoming Business Process Reengineering Obstacles Using Ontology-Based Knowledge Map Methodology, Mahmoud Abdellatif, Marwa Salah Farhan, Naglaa Saeed Shehata
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. …
Pulsar Selection Using Fuzzy Knn Classifier, Taha M. Mohamed
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 …
A Robust 3d Mesh Watermarking Algorithm Utilizing Fuzzy C-Means Clustering, Ola M. El Zein, Lamiaa M. El Bakrawy, Neveen I. Ghali Prof.
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 …
An Improved Rank Based Disease Prediction Using Web Navigation Patterns On Bio-Medical Databases, P. Dhanalakshmi, K. Ramani
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 …
A Framework For Safer Driving In Mauritius, V Bassoo, V Hurbungs, V. Ramnarain Seetohul, T.P Fowdur, Y Beeharry
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 …
Feature Level Review Table Generation For E-Commerce Websites To Produce Qualitative Rating Of The Products, Kumar Raja, S Pushpa
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 …
Pentagonal Fuzzy Number, Its Properties And Application In Fuzzy Equation, Sankar Mondal
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
A Thresholding Based Technique To Extract Retinal Blood Vessels From Fundus Images, Jyotiprava Dash, Nilamani Bhoi
A Thresholding Based Technique To Extract Retinal Blood Vessels From Fundus Images, Jyotiprava Dash, Nilamani Bhoi
Future Computing and Informatics Journal
Retinal imaging has become the significant tool among all the medical imaging technology, due to its capability to extract many data which is linked to various eye diseases. So, the accurate extraction of blood vessel is necessary that helps the eye care specialists and ophthalmologist to identify the diseases at the early stages. In this paper, we have proposed a computerized technique for extraction of blood vessels from fundus images. The process is conducted in three phases: (i) pre-processing where the image is enhanced using contrast limited adaptive histogram equalization and median filter, (ii) segmentation using mean-C thresholding to extract …