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Sustainability Action Tracker, Gladys Hilerio, Isabelle Termaat, Patricia Ornelas Jauregui 2020 Santa Clara University

Sustainability Action Tracker, Gladys Hilerio, Isabelle Termaat, Patricia Ornelas Jauregui

Computer Science and Engineering Senior Theses

The Center for Sustainability at Santa Clara University is actively looking for ways to involve students in sustainable actions and accountability. With our help, they would like to create a site where students and faculty may track their sustainable behavior. This site will provide users with all the information they need to live a sustainable life, and include milestones in the form of progress bars and badges. The Center for Sustainability will be able to collect the data from this site to evaluate the progress of our university as well as the success of the site. Our motivation for this ...


Antlion Optimization And Boosting Classifier For Spam Email Detection, Amany A. Naem, Neveen I. Ghali Prof., Afaf A. Saleh 2020 Al-Azhar University, Faculty of Science, Cairo, Egypt

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 ...


A New Online Scheduling Approach For Enhancing Qos In Cloud, Aida A. Nasr, Nirmeen A. El-Bahnasawy, Gamal Attiya, Ayman El-Sayed 2020 Faculty of Electronic Engineering, Menofia University, Department of Computer Science and Engineering, Menouf 32952, Egypt

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 ...


Automatic Labeling Of Hidden Web Data Using Multi-Heuristics Annotator, Umamageswari Baskaran, R. Kalpana 2020 Pondicherry Engineering College, Puducherry, India

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 ...


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 2020 Information Systems Department, Faculty of Computers & Information, Helwan University, Cairo, Egypt

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 ...


Stage – Specific Predictive Models For Main Prognosis Measures Of Breast Cancer, Ahmed Attia Said, Laila A. Abd-Elmegid, Sherif Kholeif, Ayman Abdelsamie Gaber 2020 Information Systems Dept., Faculty of Computers and Information, Helwan University, Egypt

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 ...


Applying Spatial Intelligence For Decision Support Systems, Amira Idrees, Mohamed H. Ibrahim 2020 Faculty of Computers and Information Fayoum University, Fayoum, Egypt

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 ...


An Qos Based Multifaceted Matchmaking Framework For Web Services Discovery, G. Sambasivam 2020 Department of CSE, Koneru Lakshmaiah Education Foundation, Andhra Pradesh, 522502, India

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 ...


Medical Image Retrieval Using Self-Organising Map On Texture Features, Shashwati Mishra 2020 Department of Computer Science and Applications, Utkal University, Vani Vihar, Bhubaneswar

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 ...


Benign And Malignant Breast Cancer Segmentation Using Optimized Region Growing Technique, S. Punitha, A. Amuthan, K. Suresh Joseph 2020 Department of Computer Science, Pondicherry University, Pondicherry, India

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 ...


A Genetic Algorithm For Service Flow Management With Budget Constraint In Heterogeneous Computing, Ahmed A. AbdulHamed, Medhat A. Tawfeek, Arabi E. Keshk 2020 Department of Computer Science, Menoufia University, Egypt

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 ...


Time Series Forecasting Using Artificial Neural Networks Methodologies: A Systematic Review, Ahmed Tealab 2020 Computer Science Department, Institute of Statistical Studies and Research, Cairo University

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 ...


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

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 ...


A Low Cost Autonomous Unmanned Ground Vehicle, Leckraj Nagowah 2020 Department of Software and Information Systems, Faculty of Information, Communication and Digital Technologies, University of Mauritius, Réduit, Mauritius

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 2020 Department of Computer Science, Bharathiyar College of Engineering and Technology, Karaikal, India

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 ...


A Proposed Hybrid Model For Adopting Cloud Computing In E-Government, Kh. E. Ali, Sh. A. Mazen, E. E. Hassanein 2020 Department of Information Systems, Faculty of Computers and Information, Cairo University, Cairo, Egypt

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 ...


Non-Sequential Partitioning Approaches To Decision Tree Classifier, Shankru Guggari, Vijayakumar Kadappa, V. Umadevi 2020 Dept. of Computer Science and Engineering, B.M.S. College of Engineering

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 2020 GIET University

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 2020 Computer Science and Engineering, P.A. College of Engineering, Mangalore, India

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. 2020 Helwan University

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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