Showing papers in "International Journal of Computers and Applications in 2020"
TL;DR: The modified WOA developed here is termed as Fitness dependent Randomized Whale Optimization Algorithm (FR-WOA) and the valuable experimental analysis using three datasets confirms the efficient performance of the suggested model.
Abstract: This paper plans to develop an effective machine learning system integrated with the Internet of Things (IoT) to predict the health insurance amount. IoT in healthcare enables interoperability, mac...
106 citations
TL;DR: ROC examination is conducted to distinguish the most significance clinical and laboratory assessments to get joint inflammation (GOUT arthritis) and kidney ailment and the exploratory outcomes demonstrated the adequacy of the dynamic time wrapping technique.
Abstract: In the midst of all the applications empowered by the Internet of Things (IoT), constant health surveying framework is an especially essential one. The leg movement monitoring framework is utilized...
71 citations
TL;DR: The designed system consists of five stages to solve one of the higher education environments using intelligent data analysis (IDA) and the Internet of things (IOTs) and reduces the time rate and effort wasted in taking daily attendance of students in each lecture.
Abstract: The designed system described in this paper consists of five stages to solve one of the higher education environments using intelligent data analysis (IDA) and the Internet of things (IOTs). The ma...
64 citations
TL;DR: ‘QueryOnto’ tool is introduced to verify and validate the MRO by searching, query/answering, and visualizing and, as a case study, evaluates a Military Resource Ontology by using evaluation tools such as OntoMetric, OOPs!
Abstract: The world is witnessing an increasing use of IoT-based devices to collect sensor data in order to perceive the real world and generate abstractions. This data is highly heterogeneous in nature as i...
51 citations
TL;DR: This work proposes an efficient CPPA scheme for VANETs based on the elliptic curve cryptography without relying on any hardware device, which satisfies the security and privacy requirements of VANets, solves private key compromise problem, and provides countermeasure against privilege escalation.
Abstract: Vehicular ad hoc network (VANET) is an emerging technology in wireless communications which has the prospect to improve traffic safety and efficiency, as well as reduce air pollution. The traffic-r...
43 citations
TL;DR: This approach is based on creating an intrusion detection system (IDS) to fulfill the requirements of the monitored environment and able to distinguish between normal and attack traffics, and acquires high detection and accuracy with a low false–positive rate.
Abstract: Modern society is prominently dependent on information and communication technology over the last few decades has carried it with more vulnerability to an enormous variety of cyber-attacks. One of ...
35 citations
TL;DR: This paper enhances IoT security authentication by utilizing cryptographic-based methodologies and secure IoT sensitive data with the help of Optimal Homomorphic Encryption (OHE) with high dependability.
Abstract: Nowadays, Internet of Things (IoT) is turning into an attractive framework to drive a substantive jump on merchandise and enterprises through physical, digital, and social spaces. This paper enhanc...
34 citations
TL;DR: A near real-time Twitter spam detection system which can better protect users from combating spams and acts as a tweets collection tool, allowing researchers to test the performance of trained classifiers in realistic scenarios.
Abstract: The popularity of social media networks, such as Twitter, leads to an increasing number of spamming activities. Researchers employed various machine learning methods to detect Twitter spam. However...
34 citations
TL;DR: A detailed analysis of the nature of the error and its detection will provide as well as a fuzzy-based method to prepare an appropriate response to the error tolerance, and the results indicate a mean superiority in comparison with ABFT method and FFD algorithm.
Abstract: It is generally accepted that with the ever-increasing need of users to various resources, cloud computing is rapidly evolving as one of the new practical technologies. Cloud computing can be categ...
30 citations
TL;DR: A framework for personalized web page recommendation based on a hybridized strategy is proposed and the Personalization is achieved by prioritizing the Web pages based on the Prioritization Vector.
Abstract: The World Wide Web is constantly evolving and is the most dynamic information repository in the world that has ever existed. Since the information on the web is changing continuously and owing to the presence of a large number of similar web pages, it is very challenging to retrieve the most relevant information. With a large number of malicious and fake web pages, it is required to retrieve Web Pages that are trustworthy. Personalization of the recommendation of web pages is certainly necessary to estimate the user interests for suggesting web pages as per their choices. Moreover, the Web is tending towards a more organized Semantic Web which primarily requires semantic techniques for recommending the Web Pages. In this paper, a framework for personalized web page recommendation based on a hybridized strategy is proposed. Web Pages are recommended based on the user query by analyzing the …
25 citations
TL;DR: A model for extracting and classifying emotions in Arabic tweets based on four emotions: sad, joy, disgust, and anger is presented, which improves the state of the art in the classification of Arabic tweets using support vector machine (SVM) and Naïve Bayes (NB) that give the best results.
Abstract: Twitter is one of the most used microblogs in social media communication channels. Emotion detection has recently raised as an important research field. Extracting emotions in Twitter microblogs ha...
TL;DR: This research presents a novel, scalable and scalable approaches called "Smart Cassandra DSP Integration (SCSI)” that automates the very labor-intensive and therefore time-heavy and expensive process of manually cataloging and forecasting individual resource demands at cloud data centers.
Abstract: To maintain elasticity and scalability of resources at cloud data centers, future workload prediction has become an indispensable requirement. However, there is high variance in resource demands, d...
TL;DR: A set of the most common machine learning techniques explored to generate robust weather forecasting model for long periods of time are explored and experimental results of the classifiers show that the decision tree CART, XGBoost and AdaBoost models exhibit better classification accuracy when compared with the other methods.
Abstract: Weather forecasting plays a significant role in different aspects of life such as in the operation of hydro-power plants, renewable energy, flood management, and agriculture. Recently, machine lear...
TL;DR: An influenza epidemic predictive model based on EMRs is successfully constructed, which may be used as a decision support tool for improving influenza surveillance, controlling infection, and managing resources.
Abstract: Seasonal influenza is an important infectious disease monitored by the Centers for Disease Control. Monitoring, early detection, and prediction of influenza outbreaks can accelerate life-saving pub...
TL;DR: The purpose of research is to find the ways to recommend the methods to create active awareness in electronic information literacy for improvement of better utilization of resources.
Abstract: Electronic information professional postgraduate training is the mixed learning strategy used in the present educational era for a better utilization of e-resources in the field like data mining an...
TL;DR: A new fault-tolerant task clustering method called FT-HCC is presented that is designed by including the workflow execution time (makespan) and execution cost constraints, which are used to increase workflow performance.
Abstract: High computation power is required to execute complex scientific workflows. Cloud computing resources are used viably to perform such complex workflows. Task clustering has demonstrated to be an ef...
TL;DR: It is shown in the experimental result that DPSOK can effectively improve the global search capacity of K-means, and it has better segmentation effect compared with K-Means and PSO in image segmentation.
Abstract: In order to solve excessive independence of image segmentation quality of K-means clustering algorithm on initial clustering center for selection, and easily falling into the local optimal solution...
TL;DR: It is proposed that identifying design flaws at a higher level of granularity will save from the vicious cycle of small refactoring operations and their cascaded side-effects.
Abstract: Good software quality is a consequence of good design. Model refactoring counteracts erosion of the software design at an early stage in the software development project complying with the model-dr...
TL;DR: The application of IoT-driven wireless nodes and IoT decision support platform in underground mining areas where location estimation of the miners is a critical task for the mining administrators is summarized.
Abstract: Internet of Things (IoT) connects many physical devices to many individuals from earth to space. This new concept covers almost all applications such as smart cities, industries, autonomous systems...
TL;DR: This research presents an image-processing technique to segment the Leukocyte Nucleus from the blood smear image and categorize them into their constituent classes based on the features drawn from the segmented region.
Abstract: Differential count of leukocytes plays a consequential role in the determination of diagnostic details of a patient. Conventionally, leukocyte identification is performed manually by skilled medica...
TL;DR: The papers presented in this special issue provides insights in fields related to IoT and Fog/edge architecture, including parallel processing of the smart system, presenting new emerging models, performance evaluation and improvements, and IoT application developments.
Abstract: Augmentation and virtualization of resource-poor wireless/mobile smart things are opening the doors to novel context-aware crowd sensing applications, that allow geographically distributed people/m...
TL;DR: This paper reviews energy-efficient sensor, resource-based VM selection approaches for X-IoT applications to distinguish measurement functions, architectures, VM scheduling mechanism challenges, and results consolidate a sensor-cloud framework that implies prevailing solution to CC.
Abstract: Cloud computing (CC) enables enumerable services to manipulate sensor data generated from X-internet of things (IoT) applications. It is accomplished by selecting an accurate decision-makin...
TL;DR: A hybrid verification technique is made which is based on biometric and encryption systems and can provide efficient authentication of cloud computing to avert information access from cloud information stockpiling focuses by unapproved clients.
Abstract: Cloud computing is a unique network or environment where access, maintenance and process can be done from any part of the world. It is a customized internet-based computer server. It is a current t...
TL;DR: In this paper, parameter tuning of Machine Learning (ML) is done to produce the high accuracy results in a binary classification of binary files into malware or benign, using API calls for achieving the high accurate results of the malware classifiers.
Abstract: Detection of malware using traditional malware detection techniques is very hard. Machine Learning (ML) algorithms provide a solution to detect the malware which is being developed at a very high p...
TL;DR: A literature mapping of the state of the art in road obstacle detection using frontal images is presented, based upon a systematic literature review that took into consideration papers published between 2007 and 2019.
Abstract: Obstacle detection is one of the main tasks in intelligent vehicle navigation systems. Several research works focused on the use of passive vision (cameras) to accomplish this task have been publis...
TL;DR: One main finding from security analysis demonstrate that OOB-BA is able to mitigate the security risks such as impersonation attacks leading to stand as an alternative authentication model to be used in future WT adoption.
Abstract: Wearable Technology (WT) devices are growing at a rapid rate for their convenience and capabilities, especially in healthcare and fitness area. As the adoption of WT accelerates and a new level of ...
TL;DR: A deep learning-based food calorie estimating approach that takes into account the actual needs of diabetics to control their blood glucose level at home and calculates the calorie according to the category of the food.
Abstract: Identifying food and estimating its calorie is a novel research area on deep learning. This application comes from the actual needs of diabetics to control their blood glucose level at home. Food c...
TL;DR: A generic, extendable, domain-independent lexicon-based framework for sentiment analysis that overcomes scalability, limitedness, and beats existing models in accuracy.
Abstract: On the internet, people share their opinions and sentiments in many forms of products or services. This behavior creates an extensive collection of opinions and views in the form of texts, which ne...
TL;DR: Formal languages and automata (FLA) theory is perceived by many as one of the hardest topics to teach or learn at the undergraduate level, due to the abstract nature of its contents; often containi...
Abstract: Formal languages and automata (FLA) theory is perceived by many as one of the hardest topics to teach or learn at the undergraduate level, due to the abstract nature of its contents; often containi...
TL;DR: A novel clustering algorithm which uses a weighted combination of several criteria as its fitness function and the suitability of the new method in the case of clustering text documents is demonstrated.
Abstract: In this paper, we propose a novel clustering algorithm which uses a weighted combination of several criteria as its fitness function. We demonstrate the suitability of the new method in the case of...