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International Computer Science and Engineering Conference (ICSEC)

作者： Panisa Janyasupab Apichat Suratanee Kitiporn Plaimas Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University Bangkok Thailand Department of Mathematics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand Department of Mathematics and Computer Science Faculty of Science Advance Virtual and Intelligent Computing (AVIC) Center Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9781665462730

Hypertrophic cardiomyopathy (HCM) is a cardiovascular disease that is often caused by abnormal genes in the heart muscle. The identification of HCM-related genes is one of the crucial tasks to prevent and treat the patient. Gene expression analysis is a direct approach to screen for a gene with a higher or lower expression level in the HCM cell than in the normal cell. Microarray and RNA-Seq technology are used for measuring transcription levels. Both techniques have different advantages to obtain gene expression data. The integration of microarray and RNA-Seq data has already been effectively used to identify disease biomarkers. The ranking method is an interesting technique and is mostly used for ranking players or teams in sports. Each method has different strengths and can be appropriately applied to integrate various data and used to prioritize the importance genes. In this work, six ranking techniques to integrate microarray and RNA-Seq data were applied to prioritize the HCM-related genes. The performance reveals that the ranking method is also a well-suited technique in this task, and it turns out that the PageRank technique yields the best performance.

关键词： Heart Computer science Data analysis Computational modeling Muscles Biomarkers Gene expression

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THE ROLE OF SOCIAL MEDIA ON SELECTED BUSINESSES IN NIGERIA IN THE ERA OF COVID-19 PANDEMIC

arXiv

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arXiv 2023年

作者： Ihemebiri, Cajetan Ukwandu, Elochukwu Ofusori, Lizzy Olebara, Comfort Department of Applied Computing and Engineering Cardiff School of Technologies Cardiff Metropolitan University Cardiff United Kingdom School of Management Information Technology & Governance University of KwaZulu-Natal Westville Campus Durban South Africa Department of Computer Science Faculty of Physical Science Imo State University Imo State Owerri Nigeria

As several countries were experiencing unprecedented economic slowdowns due to the outbreak of COVID-19 pandemic in early 2020, small business enterprises started adapting to digital technologies for business transactions. However, in Africa, particularly Nigeria, COVID-19 pandemic resulted to some financial crisis that impacted negatively on the sustainability of small and medium-sized (SMEs) businesses. Thus, this study examined the role of social media on selected SMEs in Nigeria in the heat of the COVID-19 pandemic that led to several lock downs in a bid to curtail the spread of the virus. Cross-sectional survey research design was used alongside convenience population sampling techniques. The population was categorised based on selected SMEs businesses, while a quantitative research approach was adopted, and primary data were collected using a questionnaire. The questionnaires were administered to owners and operators of SMEs in Ikotun and Ikeja areas of Lagos State, Nigeria. A total of 190 questionnaires were distributed, where 183 usable responses were analysed. The findings of the study show that SMEs were aware of the usefulness of social media to their businesses as they largely leveraged it in conducting their businesses during the national lockdowns. The study recommended that labour/trade unions should sensitise and encourage business owners on the benefits of continuous use of social media in carrying out their business transactions. © 2023, CC BY-NC-SA.

关键词： COVID-19

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Fast Mumford-Shah Two-Phase Image Segmentation Using Proximal Splitting Scheme

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Journal of applied Mathematics 2021年第none期2021卷 1-13页

作者： Shah, Nilima Patel, Dhanesh Fränti, Pasi Department of Applied Mathematics Faculty of Technology and Engineering Maharaja Sayajirao University of Baroda Vadodara Gujarat India School of Computing University of Eastern Finland Joensuu Finland Shenzhen China

The Mumford-Shah model is extensively used in image segmentation. Its energy functional causes the content of the segments to remain homogeneous and the segment boundaries to become short. However, the problem is that optimization of the functional can be very slow. To attack this problem, we propose a reduced two-phase Mumford-Shah model to segment images having one prominent object. First, initial segmentation is obtained by the k-means clustering technique, further minimizing the Mumford-Shah functional by the Douglas-Rachford algorithm. Evaluation of segmentations with various error metrics shows that 70 percent of the segmentations keep the error values below 50%. Compared to the level set method to solve the Chan-Vese model, our algorithm is significantly faster. At the same time, it gives almost the same or better segmentation results. When compared to the recent k-means variant, it also gives much better segmentation with convex boundaries. The proposed algorithm balances well between time and quality of the segmentation. A crucial step in the design of machine vision systems is the extraction of discriminant features from the images, which is based on low-level segmentation which can be obtained by our approach. © 2021 Nilima Shah et al.

关键词： Image segmentation

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Enterprise problems and proposed solutions using the concept of E-commerce 2

Enterprise problems and proposed solutions using the concept...

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2nd International Conference on Smart computing and Electronic Enterprise, ICSCEE 2021

作者： Mohamad, Mohaizi Bin Kanaan, Anas Ghassan Aseh, Khairi Alawi, Nahg Abdulmajid Amayreh, Khalid Thaher Moaiad, Yazeed Al Al-Hodiany, Zakarya Mohsen Pathmanathan, P. Ravindran El-Ebiary, Yousef A. Baker North Borneo University College Malaysia Petra University Faculty of Management and Financial Sciences Business and E-commerce Department Amman Jordan International Institute of Applied Science Swiss School of Management Netherlands Malaysia and University of Aden Geomatika University College Yemen Irbid National University Faculty of Financial and Business Science Administration Department Irbid Jordan MEDIU Faculty of Computer and Information Technology Malaysia MEDIU Faculty of Finance and Admin. Sciences Malaysia UniSZA Faculty of Informatics and Computing Malaysia

ISBN: (纸本)9781665432221

The noise of e-commerce businesses has seen the extension of number of the online businesses global. Buyers now are opted with online business commerce which is greatly benefit compared to traditional businesses. It is undeniable e-commerce enterprises contribute more profits, comparing to "bricks-and-mortal"traditional enterprises, but not to be avoided the problems and challenges faced by the e- commerce marketplace. This study emphasizes the problems and challenges of e-commerce and a set of recommended solutions to those problems and challenges. Those problems are trust, readiness and security. For each of the problems, proposed solutions are presented. Companies have conducted business electronically by applying a range of electronic commerce solutions. In the current situation, a corporation enters the electronic market by building trading partner agreements with sellers or wholesalers of their choice. These deals may include any items that cannot be agree electronically, like terms of transfer, payment devices, or implementation rules. After discovering the right market relationships, a company must choose the elements of their electronic commerce system. In this paper have been formulate current ecommerce problems, challenges and their effective solutions. In future, e-commerce marketplace should concentrate more on securing payment, e-banking and e-government. With that, problems and challenges in e-commerce can be reduce. © 2021 IEEE.

关键词： Electronic commerce

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Tuberculosis Detection from Chest Radiographs with Pre-trained Deep Learning Scheme: A Study 31

Tuberculosis Detection from Chest Radiographs with Pre-train...

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31st International Conference on Computer Theory and Applications, ICCTA 2021

作者： Kadry, Seifedine Rajinikanth, Venkatesan Chandrasekar, A. Nandhini, A. Noroff University College Faculty of Applied Computing and Technology Kristiansand Norway St. Joseph's College of Engineering Omr Department of Electronics and Instrumentation Engineering Chennai600119 India St. Joseph's College of Engineering Omr Department of Computer Science and Engineering Chennai600119 India

ISBN: (纸本)9781665478540

In human, the abnormality in lung causes a severe respiratory problem and breathing difficulties. Tuberculosis (TB) is one of the common lung abnormality caused due a bacterium named Mycobacterium tuberculosis. TB infection will cause harsh breathing issues and untreated TB will lead to death. Detection of the TB using Chest X-ray is one of the common techniques and in this research work;TB detection using Deep-Learning-Technique (DLT) is demonstrated. The various phases of this research involve;(i) Image collection and resizing, (ii) Deep-Feature (DF) extraction with chosen technique, (iii) Classification using SoftMax classifier and (iv) Performance evaluation with existing technique. The proposed work employs a 5-fold cross validation and the best value is considered as the result. The outcome of this study confirms that, the classification accuracy achieved with ResNetl8 and K-Nearest Neighbor (ResNet+KNN) offered better outcome >97% compared to other DLT of this study. © 2021 IEEE.

关键词： Deep learning

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Direct Antenna Beam Squint Correction Using AI-Equalization Strategy for 3D MIMO Array System

Direct Antenna Beam Squint Correction Using AI-Equalization ...

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Artificial Intelligence and Signal Processing (AISP), INDIA, International Conference on

作者： Riam M Zaal Noora N. Kamal Mohsin Ali Ahmed SABAH HASSAN GHADEER AL–SULTANI SHARUL KAMAL BIN T. A. Oleiwi Media Technology and Communication Engineering Department College of Engineering. University of Information Technology and Communications Baghdad Iraq Department of Computer Techniques Engineering Al Hikma University Baghdad Iraq Cybersecurity and Cloud Computing Department Al-Mamoon University College International Applied and Theoretical Research Center (IATRC) Baghdad Quarter Iraq Faculty of Electrical Engineering Universiti Teknologi Malaysia Islamic University Centre for Scientific Research The Islamic University Najaf Iraq

ISBN: (数字)9798350350654

ISBN: (纸本)9798350350661

Modern printed circuit Multi Input Multi Output (MIMO) antennas played an urgent role to achieve high channel capacity. This research is proposed to develop modern MIMO antenna systems based on highly electromagnetic isolation techniques. Such techniques are invoked to avoid the negative effects of surface waves that limit the antenna bandwidth and increase the mutual coupling. In this work, we proposed an antenna MIMO to cover the frequency ranges from 2GHz to 3GHz, 3.4GHz to 3.9GHz, and 4.4GHz to 5.2GHz; which most of them are applicable to n77, n78, and n79 5G based NR networks. The maximum achieved gain is found to be about 6.2dBi at 3.8GHz with maximum coupling not to exceed -20dB. The envelope correlation coefficient is computed, and it is within the acceptable limit. The developed antenna array is implemented and tested experimentally to be verified for validation. Finally, all the proposed designs are tested closely to a solar panel to realize the concept of green energy harvesting in the context of self-powered wireless systems. The solar panel locations with respect to the proposed MIMO antennas are considered in a way to avoid the nearfield coupling effects. Therefore, it is observed that the projected arrays are outstanding candidates for modern applications in a sub-6GHz for 5G networks.

关键词： Phased arrays Couplings Mutual coupling 5G mobile communication Transmitting antennas Three-dimensional printing MIMO Solar panels Artificial intelligence Antennas

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Quantum-Inspired Resource Optimization for 6G Networks: A Survey

引用

IEEE Communications Surveys and Tutorials 2024年

作者： Butt, Muhammad Omair Waheed, Nazar Duong, Trung Q. Ejaz, Waleed Lakehead University Department of Electrical Engineering ON Canada Faculty of Computing Information Systems Higher Colleges of Technology United Arab Emirates Memorial University Faculty of Engineering and Applied Science St. John'sNLA1C 5S7 Canada Queen's University Belfast School of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of

The Internet of things (IoT) drives an exponential surge in computing and communication devices. Consequently, it triggers capacity, coverage, interference, latency, and security issues in the existing communication networks. The forthcoming sixth-generation (6G) networks will address these issues by providing comprehensive solutions. In particular, quantum communication technology can potentially address the challenges of 6G networks. However, its implementation requires substantial infrastructure upgrades. Therefore, the quantum-inspired (QI) techniques offer an intermediate resort due to their ability to utilize the classical communication infrastructure for design and implementation. Hence, we review QI techniques in this survey that address radio resource optimization challenges across various communication aspects, including channel assignment, reconfigurable intelligent surfaces, spectrum sensing, unmanned aerial vehicle-assisted networks, and related areas. The analysis explores diverse aspects, including objectives, constraints, problem characterization, proposed solutions, and lessons learnt. Research indicates that QI techniques offer advantages such as faster convergence and reduced complexity, providing promising solutions to complex optimization problems in communication networks. Furthermore, we identify the future directions, research gaps, and ongoing challenges from the QI radio resource optimization dataset. © 1998-2012 IEEE.

关键词： Quantum communication

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Detection of Diabetic Macular Edema in Retinal OCT Images with Firefly-Algorithm Selected Features 31

Detection of Diabetic Macular Edema in Retinal OCT Images wi...

引用

31st International Conference on Computer Theory and Applications, ICCTA 2021

作者： Kadry, Seifedine Rajinikanth, Venkatesan Jerry, Jiny Mariam Gifta, R. Carolin Noroff University College Faculty of Applied Computing and Technology Kristiansand Norway St. Joseph's College of Engineering Omr Department of Electronics and Instrumentation Engineering Chennai600119 India St. Joseph's College of Engineering Omr Department of Computer Science and Engineering Chennai600119 India

ISBN: (纸本)9781665478540

In modern hospitals, computer algorithms are widely implemented to diagnose the disease in patients using the medical data collected using a recommended protocol. Recently, the diabetes is human group is gradually rising and the early stage can be predicted by screening the eye. Diabetic-Macular-Edema (DME) is one of the harsh diseases and the untreated disease will initiate various eye abnormalities including the vision loss. In clinics, the retinal image recorded with a chosen imaging system is considered to inspect the disease. In this work, Optical Coherence Tomography (OCT) images are considered for the assessment of the DME in the OCT images. The proposed scheme consist the following stages;(i) Image collection and resizing, (ii) Retinal section extraction using joint thresholding and segmentation, (iii) Feature extraction and dominant feature selection with Firefly-Algorithm, (iv) Binary classification and validation. In this work, 500 numbers of Normal/DME class images with pixel dimension 256 × 256 ×1 pixels are considered and a binary classification with a 5-fold cross validation is implemented. The proposed technique helped to get a detection accuracy of 95% with K-Nearest Neighbors (KNN) classifier. © 2021 IEEE.

关键词： Optical tomography

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Automatic Detection of Breast Cancer in Thermal Images using Optimal Handcrafted Features 31

Automatic Detection of Breast Cancer in Thermal Images using...

引用

31st International Conference on Computer Theory and Applications, ICCTA 2021

作者： Kadry, Seifedine Rajinikanth, Venkatesan Dasari, Susmitha Suvathi, T. Noroff University College Faculty of Applied Computing and Technology Kristiansand Norway St. Joseph's College of Engineering Omr Department of Electronics and Instrumentation Engineering Chennai600119 India St. Joseph's College of Engineering Omr Department of Computer Science and Engineering Chennai600119 India

ISBN: (纸本)9781665478540

Breast Cancer (BC) is one of the harsh illnesses which widely distress the women population and premature recognition is always preferred to reduce its harshness. BC is normally detected in hospitals using a chosen non-invasive medical imaging technique. The proposed work aims to develop and execute the machine learning supported automatic detection of the BC using breast Thermal Images (TI). In TI, examination of thermal silhouette helps to get the necessary information about the normal/cancer infected section. The developed system consist the following phases;(i) Image collection and pre-processing, (ii) Image enhancement and handcrafted feature extraction, (iii) Feature selection with Bat Algorithm, and (iv) Binary classification and validation. In this work, a 5-fold cross validation is employed to classify the test images and the detected accuracy of Fine KNN is better (>92%) compared to the alternatives. The proposed work is tested using benchmark breast TI and the outcome of this research confirms its clinical significance. © 2021 IEEE.

关键词： Image enhancement

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Venturing Into the Metaverse: Innovative AI-Driven Strategies for Advancing Dental Education

Venturing Into the Metaverse: Innovative AI-Driven Strategie...

引用

Intelligent Metaverse Technologies & Applications (iMETA), International Conference on

作者： Ayham Salloum Shirin Abdallah Alimour Dina Tahat Said Salloum Raghad Alfaisal Khalaf Tahat College of Medicine University of Sharjah Sharjah UAE College of Education Al Ain University UAE Applied sociology department Al Ain University UAE Health Economic and Financing Group University of Sharjah Sharjah UAE Faculty of Computing and Meta-Technology Universiti Pendidikan Sultan Idris Malaysia Media & Creative Industries United Arab Emirates University and Yarmouk University Jordan

ISBN: (数字)9798350351514

ISBN: (纸本)9798350351521

the onset of the COVID-19 pandemic brought about significant disruptions in dental education, impeding direct interaction with avant-garde dental practices and sophisticated global equipment. In this scenario, the rise of Metaverse-oriented teaching methods stands out as a creative resolution, meeting the escalating demand for distance learning options in dentistry. Conventional digital learning tools, notably Zoom, have fallen short in delivering an all-encompassing educational experience in the dental realm, steering a transition to more dynamic, immersive learning environments. This shift is notably pronounced in the dental education sphere of the United Arab Emirates (UAE). This study explores dental students' perceptions of the impact of Metaverse technology on meeting their educational goals within the UAE. Our analytical structure spotlights vital elements influencing technology adoption, specifically User Mobility and User Accessibility. An extensive dataset encompassing 291 responses was gathered from several academic institutions. To thoroughly scrutinize our research framework, we employed Partial Least Squares-Structural Equation Modelling (PLS-SEM) alongside a sophisticated Machine Learning (ML) technique, drawing on data from our student survey. The findings accentuate the fundamental role of the Metaverse in shaping decisions regarding technology adoption, heavily influenced by aspects such as User Mobility and Users' Accessibility. Notably, the ML approach showcased superior predictive accuracy in determining the dependent variable compared to other analytical methodologies. This study enriches the academic discussion surrounding artificial intelligence, particularly its nexus with environmental sustainability, and provides critical insights for industry participants, policymakers, and AI developers. The results form a basis for crafting AI-driven solutions that harmonize with user preferences and ecological requirements.

关键词： Surveys Industries Metaverse Pandemics Education Green products Machine learning Mathematical models Dentistry Immersive learning

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