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Articles 391 - 420 of 675
Full-Text Articles in Computer Sciences
A Systematic Review On Machine Learning Models For Online Learning And Examination Systems, Sanaa Kaddoura, Daniela Elena Popescu, Jude D. Hemanth
A Systematic Review On Machine Learning Models For Online Learning And Examination Systems, Sanaa Kaddoura, Daniela Elena Popescu, Jude D. Hemanth
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Examinations or assessments play a vital role in every student’s life; they determine their future and career paths. The COVID pandemic has left adverse impacts in all areas, including the academic field. The regularized classroom learning and face-to-face real-time examinations were not feasible to avoid widespread infection and ensure safety. During these desperate times, technological advancements stepped in to aid students in continuing their education without any academic breaks. Machine learning is a key to this digital transformation of schools or colleges from real-time to online mode. Online learning and examination during lockdown were made possible by Machine learning methods. …
Building An Integrated Digital Transformation System Framework: A Design Science Research, The Case Of Feduni, Munir Majdalawieh, Shafaq Khan
Building An Integrated Digital Transformation System Framework: A Design Science Research, The Case Of Feduni, Munir Majdalawieh, Shafaq Khan
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The purpose of this paper is to propose an integrated digital transformation system framework (IDTSF) to help support business leaders and teams in making their products, services, and operations more streamlined and competitive. The framework will help organizations to best meet user/customer needs with minimum waste and time and enables businesses to achieve efficiency compared with island and traditional sequential approaches. The proposed framework can also provide insights to help organizations to avoid common failures when deploying digital transformation initiatives. The paper follows the design science research (DSR) and the information systems design science research (ISDSR) methodologies to develop the …
Studying The Role Of Cerebrovascular Changes In Different Compartments In Human Brains In Hypertension Prediction, Heba Kandil, Ahmed Soliman, Nada Elsaid, Ahmed Saied, Norah Saleh Alghamdi, Ali Mahmoud, Fatma Taher, Ayman El-Baz
Studying The Role Of Cerebrovascular Changes In Different Compartments In Human Brains In Hypertension Prediction, Heba Kandil, Ahmed Soliman, Nada Elsaid, Ahmed Saied, Norah Saleh Alghamdi, Ali Mahmoud, Fatma Taher, Ayman El-Baz
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Hypertension is a major cause of mortality of millions of people worldwide. Cerebral vascular changes are clinically observed to precede the onset of hypertension. The early detection and quantification of these cerebral changes would help greatly in the early prediction of the disease. Hence, preparing appropriate medical plans to avoid the disease and mitigate any adverse events. This study aims to investigate whether studying the cerebral changes in specific regions of human brains (specifically, the anterior, and the posterior compartments) separately, would increase the accuracy of hypertension prediction compared to studying the vascular changes occurring over the entire brain’s vasculature. …
Error Level Analysis Technique For Identifying Jpeg Block Unique Signature For Digital Forensic Analysis, Nor Amira Nor Azhan, Richard Adeyemi Ikuesan, Shukor Abd Razak, Victor R. Kebande
Error Level Analysis Technique For Identifying Jpeg Block Unique Signature For Digital Forensic Analysis, Nor Amira Nor Azhan, Richard Adeyemi Ikuesan, Shukor Abd Razak, Victor R. Kebande
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The popularity of unique image compression features of image files opens an interesting research analysis process, given that several digital forensics cases are related to diverse file types. Of interest has been fragmented file carving and recovery which forms a major aspect of digital forensics research on JPEG files. Whilst there exist several challenges, this paper focuses on the challenge of determining the co-existence of JPEG fragments within various file fragment types. Existing works have exhibited a high false-positive rate, therefore rendering the need for manual validation. This study develops a technique that can identify the unique signature of JPEG …
Evaluation Of E-Learning Experience In The Light Of The Covid-19 In Higher Education, Ahmad Mohmmad Al-Smadi, Ahed Abugabah, Ahmad Al Smadi
Evaluation Of E-Learning Experience In The Light Of The Covid-19 In Higher Education, Ahmad Mohmmad Al-Smadi, Ahed Abugabah, Ahmad Al Smadi
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Covid-19 has been stated as a worldwide outbreak of pandemic disease and crisis. The Covid-19 pandemic has dramatically affected the teaching and learning experience at universities and schools. In response, governments and higher education institutions around the world put significant efforts to ensure that students continue to obtain the best possible level of education and learning outcomes. As such effective evaluation of e-learning is essential in order to ensure that students get proper learning and education especially during the current circumstances of Covid-19. Our study was carried out to determine the main elements and factors related to students' satisfaction and …
Afnd: Arabic Fake News Dataset For The Detection And Classification Of Articles Credibility, Ashwaq Khalil, Moath Jarrah, Monther Aldwairi, Manar Jaradat
Afnd: Arabic Fake News Dataset For The Detection And Classification Of Articles Credibility, Ashwaq Khalil, Moath Jarrah, Monther Aldwairi, Manar Jaradat
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The news credibility detection task has started to gain more attention recently due to the rapid increase of news on different social media platforms. This article provides a large, labeled, and diverse Arabic Fake News Dataset (AFND) that is collected from public Arabic news websites. This dataset enables the research community to use supervised and unsupervised machine learning algorithms to classify the credibility of Arabic news articles. AFND consists of 606912 public news articles that were scraped from 134 public news websites of 19 different Arab countries over a 6-month period using Python scripts. The Arabic fact-check platform, Misbar, is …
Deep Convolutional Neural Network-Based System For Fish Classification, Ahmad Al Smadi, Atif Mehmood, Ahed Abugabah, Eiad Almekhlafi, Ahmad Mohammad Al-Smadi
Deep Convolutional Neural Network-Based System For Fish Classification, Ahmad Al Smadi, Atif Mehmood, Ahed Abugabah, Eiad Almekhlafi, Ahmad Mohammad Al-Smadi
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In computer vision, image classification is one of the potential image processing tasks. Nowadays, fish classification is a wide considered issue within the areas of machine learning and image segmentation. Moreover, it has been extended to a variety of domains, such as marketing strategies. This paper presents an effective fish classification method based on convolutional neural networks (CNNs). The experiments were conducted on the new dataset of Bangladesh’s indigenous fish species with three kinds of splitting: 80-20%, 75-25%, and 70-30%. We provide a comprehensive comparison of several popular optimizers of CNN. In total, we perform a comparative analysis of 5 …
How Can Generative Adversarial Networks Impact Computer Generated Art? Insights From Poetry To Melody Conversion, Sakib Shahriar, Noora Al Roken
How Can Generative Adversarial Networks Impact Computer Generated Art? Insights From Poetry To Melody Conversion, Sakib Shahriar, Noora Al Roken
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Recent advances in deep learning and generative adversarial networks (GANs), in particular, has enabled interesting applications including photorealistic image generation, image translation, and automatic caption generation. This has opened up possibilities for many cross-domain applications in computer generated arts and literature. Although there are existing software-based approaches for generating musical accompaniment of a given poetry, there are no existing implementation using GANs. This work proposes a novel poetry to melody generation conditioned on poem emotion using GANs. A dataset containing pairs of poetry and melody based on three emotion categories is introduced. Furthermore, various GAN architectures including SpecGAN and WaveGAN …
Dynamic Qos/Qoe-Aware Reliable Service Composition Framework For Edge Intelligence, Vahideh Hayyolalam, Safa Otoum, Öznur Özkasap
Dynamic Qos/Qoe-Aware Reliable Service Composition Framework For Edge Intelligence, Vahideh Hayyolalam, Safa Otoum, Öznur Özkasap
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Edge intelligence has become popular recently since it brings smartness and copes with some shortcomings of conventional technologies such as cloud computing, Internet of Things (IoT), and centralized AI adoptions. However, although utilizing edge intelligence contributes to providing smart systems such as automated driving systems, smart cities, and connected healthcare systems, it is not free from limitations. There exist various challenges in integrating AI and edge computing, one of which is addressed in this paper. Our main focus is to handle the adoption of AI methods on resource-constrained edge devices. In this regard, we introduce the concept of Edge devices …
Interpretable Deep Learning For The Prediction Of Icu Admission Likelihood And Mortality Of Covid-19 Patients, Amril Nazir, Hyacinth Kwadwo Ampadu
Interpretable Deep Learning For The Prediction Of Icu Admission Likelihood And Mortality Of Covid-19 Patients, Amril Nazir, Hyacinth Kwadwo Ampadu
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The global healthcare system is being overburdened by an increasing number of COVID-19 patients. Physicians are having difficulty allocating resources and focusing their attention on high-risk patients, partly due to the difficulty in identifying high-risk patients early. COVID-19 hospitalizations require specialized treatment capabilities and can cause a burden on healthcare resources. Estimating future hospitalization of COVID-19 patients is, therefore, crucial to saving lives. In this paper, an interpretable deep learning model is developed to predict intensive care unit (ICU) admission and mortality of COVID-19 patients. The study comprised of patients from the Stony Brook University Hospital, with patient information such …
A Non-Invasive Interpretable Diagnosis Of Melanoma Skin Cancer Using Deep Learning And Ensemble Stacking Of Machine Learning Models, Iftiaz A. Alfi, Mahfuzur Rahman, Mohammad Shorfuzzaman, Amril Nazir
A Non-Invasive Interpretable Diagnosis Of Melanoma Skin Cancer Using Deep Learning And Ensemble Stacking Of Machine Learning Models, Iftiaz A. Alfi, Mahfuzur Rahman, Mohammad Shorfuzzaman, Amril Nazir
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A skin lesion is a portion of skin that observes abnormal growth compared to other areas of the skin. The ISIC 2018 lesion dataset has seven classes. A miniature dataset version of it is also available with only two classes: malignant and benign. Malignant tumors are tumors that are cancerous, and benign tumors are non-cancerous. Malignant tumors have the ability to multiply and spread throughout the body at a much faster rate. The early detection of the cancerous skin lesion is crucial for the survival of the patient. Deep learning models and machine learning models play an essential role in …
Deeprobot: A Hybrid Deep Neural Network Model For Social Bot Detection Based On User Profile Data, Kadhim Hayawi, Sujith Mathew, Neethu Venugopal, Mohammad M. Masud, Pin Han Ho
Deeprobot: A Hybrid Deep Neural Network Model For Social Bot Detection Based On User Profile Data, Kadhim Hayawi, Sujith Mathew, Neethu Venugopal, Mohammad M. Masud, Pin Han Ho
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Use of online social networks (OSNs) undoubtedly brings the world closer. OSNs like Twitter provide a space for expressing one’s opinions in a public platform. This great potential is misused by the creation of bot accounts, which spread fake news and manipulate opinions. Hence, distinguishing genuine human accounts from bot accounts has become a pressing issue for researchers. In this paper, we propose a framework based on deep learning to classify Twitter accounts as either ‘human’ or ‘bot.’ We use the information from user profile metadata of the Twitter account like description, follower count and tweet count. We name the …
A Novel Text Mining Approach For Mental Health Prediction Using Bi-Lstm And Bert Model, Kamil Zeberga, Muhammad Attique, Babar Shah, Farman Ali, Yalew Zelalem Jembre, Tae-Sun Chung
A Novel Text Mining Approach For Mental Health Prediction Using Bi-Lstm And Bert Model, Kamil Zeberga, Muhammad Attique, Babar Shah, Farman Ali, Yalew Zelalem Jembre, Tae-Sun Chung
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With the current advancement in the Internet, there has been a growing demand for building intelligent and smart systems that can efficiently address the detection of health-related problems on social media, such as the detection of depression and anxiety. These types of systems, which are mainly dependent on machine learning techniques, must be able to deal with obtaining the semantic and syntactic meaning of texts posted by users on social media. The data generated by users on social media contains unstructured and unpredictable content. Several systems based on machine learning and social media platforms have recently been introduced to identify …
Using Modified Technology Acceptance Model To Evaluate The Adoption Of A Proposed Iot-Based Indoor Disaster Management Software Tool By Rescue Workers, Preetinder Singh Brar, Babar Shah, Jaiteg Singh, Farman Ali, Daehan Kwak
Using Modified Technology Acceptance Model To Evaluate The Adoption Of A Proposed Iot-Based Indoor Disaster Management Software Tool By Rescue Workers, Preetinder Singh Brar, Babar Shah, Jaiteg Singh, Farman Ali, Daehan Kwak
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Advancements in IoT technology have been instrumental in the design and implementation of various ubiquitous services. One such design activity was carried out by the authors of this paper, who proposed a novel cloud-centric IoT-based disaster management framework and developed a multimedia-based prototype that employed real-time geographical maps. The multimediabased system can provide vital information on maps that can improve the planning and execution of evacuation tasks. This study was intended to explore the acceptance of the proposed technology by the specific set of users that could potentially lead to its adoption by rescue agencies for carrying out indoor rescue …
The Role Of 3d Ct Imaging In The Accurate Diagnosis Of Lung Function In Coronavirus Patients, Ibrahim Shawky Farahat, Ahmed Sharafeldeen, Mohamed Elsharkawy, Ahmed Soliman, Ali Mahmoud, Mohammed Ghazal, Fatma Taher, Maha Bilal, Ahmed Abdel Khalek Abdel Razek, Waleed Aladrousy, Samir Elmougy, Ahmed Elsaid Tolba, Moumen El-Melegy, Ayman El-Baz
The Role Of 3d Ct Imaging In The Accurate Diagnosis Of Lung Function In Coronavirus Patients, Ibrahim Shawky Farahat, Ahmed Sharafeldeen, Mohamed Elsharkawy, Ahmed Soliman, Ali Mahmoud, Mohammed Ghazal, Fatma Taher, Maha Bilal, Ahmed Abdel Khalek Abdel Razek, Waleed Aladrousy, Samir Elmougy, Ahmed Elsaid Tolba, Moumen El-Melegy, Ayman El-Baz
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Early grading of coronavirus disease 2019 (COVID-19), as well as ventilator support machines, are prime ways to help the world fight this virus and reduce the mortality rate. To reduce the burden on physicians, we developed an automatic Computer-Aided Diagnostic (CAD) system to grade COVID-19 from Computed Tomography (CT) images. This system segments the lung region from chest CT scans using an unsupervised approach based on an appearance model, followed by 3D rotation invariant Markov–Gibbs Random Field (MGRF)-based morphological constraints. This system analyzes the segmented lung and generates precise, analytical imaging markers by estimating the MGRF-based analytical potentials. Three Gibbs …
Improving User Experience And Communication Of Digitally Enhanced Advanced Services (Deas) Offers In Manufacturing Sector, Mohammed Soheeb Khan, Vassilis Charissis, Phil Godsiff, Zena Wood, Jannat F. Falah, Salsabeel F.M. Alfalah, David K. Harrison
Improving User Experience And Communication Of Digitally Enhanced Advanced Services (Deas) Offers In Manufacturing Sector, Mohammed Soheeb Khan, Vassilis Charissis, Phil Godsiff, Zena Wood, Jannat F. Falah, Salsabeel F.M. Alfalah, David K. Harrison
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Digitally enhanced advanced services (DEAS), offered currently by various industries, could be a challenging concept to comprehend for potential clients. This could result in limited interest in adopting (DEAS) or even understanding its true value with significant financial implications for the providers. Innovative ways to present and simplify complex information are provided by serious games and gamification, which simplify and engage users with intricate information in an enjoyable manner. Despite the use of serious games and gamification in other areas, only a few examples have been documented to convey servitization offers. This research explores the design and development of a …
Reverse-Engineering The Design Rules For Cloud-Based Big Data Platforms, Ravi S. Sharma, Purna N. Mannava, Stephen C. Wingreen
Reverse-Engineering The Design Rules For Cloud-Based Big Data Platforms, Ravi S. Sharma, Purna N. Mannava, Stephen C. Wingreen
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Big Data's 5 V complexities are making it increasingly difficult to develop an understanding of the end to end process. Big Data platforms play a crucial role in many critical systems, combining with Internet-of-Things, Artificial Intelligence and Business Analytics. It is both relevant and important to understand Big Data systems to identify the best tools that fit the requirements of heterogeneous platforms. The objective of this paper is to "discover" a set of design principles and rules for Cloud-based Big Data platforms for complex, heterogeneous environments. The design scope comprises Big Data's significance, challenges and architectural impacts. Using a methodology …
Twin Delayed Deep Deterministic Policy Gradient-Based Target Tracking For Unmanned Aerial Vehicle With Achievement Rewarding And Multistage Training, Najmaddin Abo Mosali, Syariful Syafiq Shamsudin, Omar Alfandi, Rosli Omar, Najib Al-Fadhali
Twin Delayed Deep Deterministic Policy Gradient-Based Target Tracking For Unmanned Aerial Vehicle With Achievement Rewarding And Multistage Training, Najmaddin Abo Mosali, Syariful Syafiq Shamsudin, Omar Alfandi, Rosli Omar, Najib Al-Fadhali
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Target tracking using an unmanned aerial vehicle (UAV) is a challenging robotic problem. It requires handling a high level of nonlinearity and dynamics. Model-free control effectively handles the uncertain nature of the problem, and reinforcement learning (RL)-based approaches are a good candidate for solving this problem. In this article, the Twin Delayed Deep Deterministic Policy Gradient Algorithm (TD3), as recent and composite architecture of RL, was explored as a tracking agent for the UAV-based target tracking problem. Several improvements on the original TD3 were also performed. First, the proportional-differential controller was used to boost the exploration of the TD3 in …
Intelligent Fault-Tolerant Mechanism For Data Centers Of Cloud Infrastructure, Satish Kumar T, Madhusudhan H S, S. M. F. D. Syed Mustapha, Punit Gupta, Rajan Prasad Tripathi
Intelligent Fault-Tolerant Mechanism For Data Centers Of Cloud Infrastructure, Satish Kumar T, Madhusudhan H S, S. M. F. D. Syed Mustapha, Punit Gupta, Rajan Prasad Tripathi
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Fault tolerance in cloud computing is considered as one of the most vital issues to deliver reliable services. Checkpoint/restart is one of the methods used to enhance the reliability of the cloud services. However, many existing methods do not focus on virtual machine (VM) failure that occurs due to the higher response time of a node, byzantine fault, and performance fault, and existing methods also ignore the optimization during the recovery phase. This paper proposes a checkpoint/restart mechanism to enhance reliability of cloud services. Our work is threefold: (1) we design an algorithm to identify virtual machine failure due to …
Early Fire Detection: A New Indoor Laboratory Dataset And Data Distribution Analysis, Amril Nazir, Husam Mosleh, Maen Takruri, Abdul Halim Jallad, Hamad Alhebsi
Early Fire Detection: A New Indoor Laboratory Dataset And Data Distribution Analysis, Amril Nazir, Husam Mosleh, Maen Takruri, Abdul Halim Jallad, Hamad Alhebsi
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Fire alarm systems are typically equipped with various sensors such as heat, smoke, and gas detectors. These provide fire alerts and notifications of emergency exits when a fire has been detected. However, such systems do not give early warning in order to allow appropriate action to be taken when an alarm is first triggered, as the fire may have already caused severe damage. This paper analyzes a new dataset gathered from controlled realistic fire experiments conducted in an indoor laboratory environment. The experiments were conducted in a controlled manner by triggering the source of fire using electrical devices and charcoal …
A Novel Approach To Face Pattern Analysis, Shashi Bhushan, Mohammed Alshehri, Neha Agarwal, Ismail Keshta, Jitendra Rajpurohit, Ahed Abugabah
A Novel Approach To Face Pattern Analysis, Shashi Bhushan, Mohammed Alshehri, Neha Agarwal, Ismail Keshta, Jitendra Rajpurohit, Ahed Abugabah
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Recognizing facial expressions is a major challenge and will be required in the latest fields of research such as the industrial Internet of Things. Currently, the available methods are useful for detecting singular facial images, but they are very hard to extract. The main aim of face detection is to capture an image in real‐time and search for the image in the available dataset. So, by using this biometric feature, one can recognize and verify the person’s image by their facial features. Many researchers have used Principal Component Analysis (PCA), Support Vector Machine (SVM), a combination of PCA and SVM, …
Combatting Digital Addiction: Current Approaches And Future Directions, Deniz Cemiloglu, Mohamed Basel Almourad, John Mcalaney, Raian Ali
Combatting Digital Addiction: Current Approaches And Future Directions, Deniz Cemiloglu, Mohamed Basel Almourad, John Mcalaney, Raian Ali
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In recent years, the notion of digital addiction has become popular. Calls for solutions to combat it, especially in adolescents, are on the rise. Whilst there remains debate on the status of this phenomenon as a diagnosable mental health condition; there is a need for prevention and intervention approaches that encourage individuals to have more control over their digital usage. This narrative review examines digital addiction countermeasures proposed in the last ten years. By countermeasures, we mean strategies and techniques for prevention, harm reduction, and intervention towards addictive digital behaviours. We include studies published in peer-reviewed journals between 2010 and …
Building Smart Contracts For Covid19 Pandemic Over The Blockchain Emerging Technologies, Ala’ Abu Hilal, Mohamad Badra, Abdallah Tubaishat
Building Smart Contracts For Covid19 Pandemic Over The Blockchain Emerging Technologies, Ala’ Abu Hilal, Mohamad Badra, Abdallah Tubaishat
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This research aims to improve and integrate hospital’s healthcare applications with Blockchain and smart contracts technologies to provide huge and secure storage that is immutable. This application will be able to record the patients’ medical history like appointments, medical tests, etc.; As a matter of fact, these resources should be recorded to be securely retrieved, modified, and stored by an authorized party only. The utilization of these critical resources will increase the validity for participants with a high level of liability, where building a scheduling appointment system using the blockchain-based on a smart contract will enhance patients’ privacy and provides …
A Surrogate Assisted Quantum-Behaved Algorithm For Well Placement Optimization, Jahedul Islam, Amril Nazir, Moinul Hossain, Hitmi Khalifa Alhitmi, Muhammad Ashad Kabir, Abdul-Halim Jallad
A Surrogate Assisted Quantum-Behaved Algorithm For Well Placement Optimization, Jahedul Islam, Amril Nazir, Moinul Hossain, Hitmi Khalifa Alhitmi, Muhammad Ashad Kabir, Abdul-Halim Jallad
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The oil and gas industry faces difficulties in optimizing well placement problems. These problems are multimodal, non-convex, and discontinuous in nature. Various traditional and non-traditional optimization algorithms have been developed to resolve these difficulties. Nevertheless, these techniques remain trapped in local optima and provide inconsistent performance for different reservoirs. This study thereby presents a Surrogate Assisted Quantum-behaved Algorithm to obtain a better solution for the well placement optimization problem. The proposed approach utilizes different metaheuristic optimization techniques such as the Quantum-inspired Particle Swarm Optimization and the Quantum-behaved Bat Algorithm in different implementation phases. Two complex reservoirs are used to investigate …
A Systematic Literature Review On Spam Content Detection And Classification, Sanaa Kaddoura, Ganesh Chandrasekaran, Daniela Elena Popescu, Jude Hemanth Duraisamy
A Systematic Literature Review On Spam Content Detection And Classification, Sanaa Kaddoura, Ganesh Chandrasekaran, Daniela Elena Popescu, Jude Hemanth Duraisamy
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The presence of spam content in social media is tremendously increasing, and therefore the detection of spam has become vital. The spam contents increase as people extensively use social media, i.e ., Facebook, Twitter, YouTube, and E-mail. The time spent by people using social media is overgrowing, especially in the time of the pandemic. Users get a lot of text messages through social media, and they cannot recognize the spam content in these messages. Spam messages contain malicious links, apps, fake accounts, fake news, reviews, rumors, etc. To improve social media security, the detection and control of spam text are …
Current Trends In Blockchain Implementations On The Paradigm Of Public Key Infrastructure: A Survey, Daniel Maldonado-Ruiz, Jenny Torres, Nour El Madhoun, Mohamad Badra
Current Trends In Blockchain Implementations On The Paradigm Of Public Key Infrastructure: A Survey, Daniel Maldonado-Ruiz, Jenny Torres, Nour El Madhoun, Mohamad Badra
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Since the emergence of the Bitcoin cryptocurrency, the blockchain technology has become the new Internet tool with which researchers claim to be able to solve any existing online problem. From immutable log ledger applications to authorisation systems applications, the current technological consensus implies that most of Internet problems could be effectively solved by deploying some form of blockchain environment. Regardless this ‘consensus’, there are decentralised Internet-based applications on which blockchain technology can actually solve several problems and improve the functionality of these applications. The development of these new blockchain-based solutions is grouped into a new paradigm called Blockchain 3.0 and …
A Systematic Analysis Of Community Detection In Complex Networks, Haji Gul, Feras Al-Obeidat, Adnan Amin, Muhammad Tahir, Fernando Moreira
A Systematic Analysis Of Community Detection In Complex Networks, Haji Gul, Feras Al-Obeidat, Adnan Amin, Muhammad Tahir, Fernando Moreira
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Numerous techniques have been proposed by researchers to uncover the hidden patterns of real-world complex networks. Finding a hidden community is one of the crucial tasks for community detection in complex networks. Despite the presence of multiple methods for community detection, identification of the best performing method over different complex networks is still an open research question. In this article, we analyzed eight state-of-the-art community detection algorithms on nine complex networks of varying sizes covering various domains including animal, biomedical, terrorist, social, and human contacts. The objective of this article is to identify the best performing algorithm for community detection …
Explicating Consumer Adoption Of Wearable Technologies: A Case Of Smartwatches From The Asean Perspective, Veerisa Chotiyaputta, Donghee Shin
Explicating Consumer Adoption Of Wearable Technologies: A Case Of Smartwatches From The Asean Perspective, Veerisa Chotiyaputta, Donghee Shin
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This research aims to determine the key antecedent factors in consumers' adoption of and their intention to recommend smartwatch wearable technology. The proposed research model combines the current technology acceptance and innovation diffusion theories with perceived aesthetic and perceived privacy risk to explain individuals' smartwatch adoption and subsequent recommendation to other people. Based on a sample of 299 completed individual online surveys, the research employed partial least squares (a variance-based analysis method) for the model and hypotheses testing. The results showed some similarities as well as differences from the previous literature. The study found that performance expectancy, habit, and perceived …
Brain Image Fusion Approach Based On Side Window Filtering, Ahmad Al Smadi, Ahed Abugabah, Atif Mehmood, Shuyuan Yang
Brain Image Fusion Approach Based On Side Window Filtering, Ahmad Al Smadi, Ahed Abugabah, Atif Mehmood, Shuyuan Yang
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Brain medical image fusion plays an important role in framing a contemporary image to enhance the reciprocal and repetitive information for diagnosis purposes. A novel approach using kernel-based image filtering on brain images is presented. Firstly, the Bilateral filter is used to generate a high-frequency component of a source image. Secondly, an intensity component is estimated for the first image. Thirdly, side window filtering is employed on several filters, including the guided filter, gradient guided filter, and weighted guided filter. Thereby minimizing the difference between the intensity component of the first image and the low pass filter of the second …
Multi-Party Contract Management For Microservices, Zakaria Maamar, Noura Faci, Joyce El Haddad, Fadwa Yahya, Mohammad Askar
Multi-Party Contract Management For Microservices, Zakaria Maamar, Noura Faci, Joyce El Haddad, Fadwa Yahya, Mohammad Askar
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This paper discusses the necessary steps and means for ensuring the successful deployment and execution of software components referred to as microservices on top of platforms referred to as Internet of Things (IoT) devices, clouds, and edges. These steps and means are packaged into formal documents known in the literature as contracts. Because of the multi-dimensional nature of deploying and executing microservices, contracts are specialized into discovery, deployment, and collaboration types, capturing each specific aspect of the completion of these contracts. This completion is associated with a set of Quality-of-Service (QoS) parameters that are monitored allowing to identify potential deviations …