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IST-Africa

作者： Musa CHEMISTO Kassim KALINAKI Ivan Tim OLOYA Tar JL GUTU Percival EGAU Fred KIRYA Darlius Bosco MWEBESA Rashid KISITU Department of Electronics and Computer Engineering HCI Research Lab Soroti University Soroti Uganda Department of Computer Science Islamic University in Uganda Mbale Uganda Faculty of Information and Communications Technology ISBAT University Kampala Uganda

ISBN: (数字)9781905824731

ISBN: (纸本)9798350356595

This paper adapts a Systematic Literature Review (SLR) to investigate the influence of ICTs on Uganda's maternal health sector development based on the premise that ICTs have supported improvements in maternal health services such as antenatal, pregnancy, and postnatal care. The SLR analysed twenty articles and reports, which were classified using the Search, Appraisal, Synthesis, and Analysis (SALSA) framework and Mendeley referencing tool. Six ICT initiatives in maternal health were identified and evaluated, centred on their developmental contributions. Using a theoretical framework for analysis of ICT-based development initiatives, we categorized explanatory development perceptions about the ICT initiatives. Conceptual categories adopted from the framework include better lives for the poor and improved government services. The categories rationalized inferred contextual literature relating to the developmental contributions of the ICT initiatives. Our findings provide an interpretive understanding of the ICT initiative's significance towards service delivery access and improvement. However, the study was limited by insufficient literature about ICTs in Uganda's maternal health sector. Future studies aim to develop an Artificial intelligence system to support improved maternal healthcare in Uganda and a theoretical framework.

关键词： Training Systematics Costs Bibliographies Decision making Medical services Stakeholders

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Capacity Bounds for Identification With Effective Secrecy

arXiv

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arXiv 2023年

作者： Rosenberger, Johannes Ibrahim, Abdalla Bash, Boulat A. Deppe, Christian Ferrara, Roberto Pereg, Uzi TUM School of Computation Information and Technology Technical University of Munich Germany Electrical and Computer Engineering Department University of Arizona United States Faculty of Electrical and Computer Engineering Helen Diller Quantum Center Technion Israel Institute of Technology

An upper bound to the identification capacity of discrete memoryless wiretap channels is derived under the requirement of semantic effective secrecy, combining semantic secrecy and stealth constraints. A previously established lower bound is improved by applying it to a prefix channel, formed by concatenating an auxiliary channel and the actual channel. The bounds are tight if the legitimate channel is more capable than the eavesdropper’s channel. An illustrative example is provided for a wiretap channel that is composed of a point-to-point channel, and a parallel, reversely degraded wiretap channel. A comparison with results for message transmission and for identification with only secrecy constraint is provided. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

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Analysing Vehicle Routing in Urban Pest Control Using a Cluster-First Route-Second Approach

Analysing Vehicle Routing in Urban Pest Control Using a Clus...

引用

International Conference on information technology (ICIT)

作者： Yigit Alisan Faruk Serin Suleyman Mete Eren Ozceylan Department of Information Technology Adana Alpaslan Türkeş Science and Technology University Adana Türkiye Department of Computer Engineering Faculty of Engineering Mersin University Mersin Türkiye Department of Industrial Engineering Faculty of Engineering Gaziantep University Gaziantep Türkiye

Insects are generally characterized as organisms that have negative impacts on both human health and the environment in areas where human habitation exists. These pests typically inhabit and reproduce in locations that contain waste, such as garbage sites, abandoned places, and septic tanks. House flies, for instance, can significantly affect the daily lives of individuals and even prompt widespread epidemics by transmitting diseases to humans. To mitigate the proliferation of pests and minimize their environmental damage, pest control is a crucial responsibility that falls under the jurisdiction of municipalities in Turkey. Municipalities commonly utilize chemical-based methods that are non-hazardous to humans and the environment while concurrently efficacious in exterminating pests or thwarting their reproduction. These chemicals are typically prepared by experts and then applied to the areas in which the pests reside. However, the primary issue that municipalities encounter is the vast expanse of land that needs to be managed, coupled with limited resources in terms of both human labor and equipment, alongside the dispersal of pests' living and breeding locations throughout a broad territory. To address this problem, this study employed the coordinates of previously identified insect nests. These nests were divided into clusters based on predetermined criteria using the k-means method within the municipality borders. Then, utilizing Google or-tools, the distance to be covered by the vehicle for each cluster was calculated. Finally, comparisons were made between the obtained results, and various recommendations were proposed.

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Smart Advertising Based on Customer Preferences and Manage the Supermarket

Smart Advertising Based on Customer Preferences and Manage t...

引用

Advancements in Computing (ICAC), International Conference on

作者： W.H.A. Eishan Dinuka A.Y.S. Wickramasinghe W W.S. Weerasinghe H K.P. Karunaratne G Chethana Liyanapathirana Lakmal Rupasinghe Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398106

As a developing country, Sri Lanka needs to go along with cutting-edge technologies. In the beginning phase of this digital advertising, multiple advertisements were displayed on the users’ feeds, including advertisements despite their preferences. This was a terrible user experience for the users. However, smart advertising based on customer preferences can manage the flow of advertisements on the feed as per the users’ preferences. This same technique can be used in handling advertisements while shopping at supermarkets. These advertisements can be directed based on demographic characteristics like face and gender and previous customer transactions. Additionally, providing the nearest supermarket they can reach based on their current location. Queue management is the next most crucial facility that needs to be provided to a supermarket. However, the manual system of queue management is not effective. But with a modernized queue management system, overcrowded supermarkets can be managed effectively. This proposed system also considers providing a chatbot service to manage customer inquiries in a reliable strategy. In this system, we mainly used the Keras model called VGGFace for face detection, the Conventional Neural Network and Keras-based model for gender detection, the TensorFlow model called Single Shot MultiBox Detection MobileNet for queue and crowd detection, the Apriori algorithm base model for predicting the buying pattern, a Keras-based model for Artificial Intelligence chatbot and finally, google map Application Programming Interface for the nearest supermarket finding are models and technology. This system was developed to manage a supermarket properly.

关键词： Neural networks Manuals Predictive models Developing countries Chatbots Prediction algorithms User experience

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UNet with Two-Fold Training for Effective Segmentation of Lung Section in Chest X-Ray 3

UNet with Two-Fold Training for Effective Segmentation of Lu...

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3rd International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Rajinikanth, Venkatesan Kadry, Seifedine Damasevicius, Robertas Gnanasoundharam, J. Abed Mohammed, Mazin Glan Devadhas, G. Noroff University College Faculty of Applied Computing and Technology Kristiansand94612 Norway Silesian University of Technology Faculty of Applied Mathematics Gliwice44-100 Poland St. Joseph's College of Engineering Omr Department of Electronics and Instrumentation Engineering Chennai600119 India University of Anbar College of Computer Science and Information Technology Ramadi31001 Iraq Vimal Jyothi Engineering College Department of Electronics and Instrumentation Engineering Chemperi India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

Segmentation and evaluation of the Region of Interest (ROI) in medical imaging is a prime task for disease screening and decision-making. Due to accuracy, Convolutional-Neural-Network (CNN) based ROI segmentation has been widely employed in recent years to evaluate a class of medical images recorded using chosen modality. The proposed work aims to demonstrate the segmentation performance of the UNet scheme with a one-fold and two-fold training process. To experimentally verify the merit of the proposed scheme, segmentation of the lung section from the chest X-ray is studied. This research includes the following parts;(i) Resizing the test image and image mask to pixels, (ii) Training the UNet with one-fold and two-fold approaches, (iii) Extracting the ROI, (iv) Comparing the ROI with the mask to compute the image metrics and (v) Validating and confirming the segmentation performance of UNet. The performance of UNet is then verified with UNet+ and UNet++. The investigational ending substantiates that the proposed approach helps to get better Jaccard (>95%), Dice ((>97%), and Accuracy (>98%) in two-fold training compared to other methods considered in this study. © 2022 IEEE.

关键词： Decision making

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Sampled-Data H∞Control for Nonlinear Dynamical Intelligent Fuzzy Systems with Time-Varying Delay 34

Sampled-Data H∞Control for Nonlinear Dynamical Intelligent ...

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34th Chinese Control and Decision Conference, CCDC 2022

作者： Qu, Zifang Du, Zhenbin Zhang, Guangyong Shandong Technology and Business University School of Mathematics and Information Science Yantai264003 China Yantai University School of Computer and Control Engineering Yantai264005 China Wuxi University Faculty of Science Wuxi214105 China

ISBN: (纸本)9781665478960

The manuscript explores the issue of the sampled-data H∞ control for the nonlinear intelligent fuzzy system which has time-varying delay. A T-S fuzzy model is employed to portray the system and the fuzzy controller is a sampled-data signal implemented by a zero-order holder. According to the stability theory of Lyapunov-Krasovskii functional, a fuzzy sampled-data H∞ control algorithm is gained. Moreover, by adopting linear matrix inequalities (LMIs), some sufficient conditions for the controller are acquired, which ensure the H∞ performance under a prescribed level. Furthermore, an application example of a mechanical system displays the proposed design. © 2022 IEEE.

关键词： Linear matrix inequalities

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A Comparative Study of Machine Learning Techniques for Early Prediction of Prostate Cancer

A Comparative Study of Machine Learning Techniques for Early...

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International Conference on Communications and Networking, ComNet

作者： Mowafaq Salem Alzboon Mohammad Al-Batah Muhyeeddin Alqaraleh Ahmad Abuashour Ahmad Fuad Bader Faculty of Information Technology Jadara University Irbid Jordan Faculty of computer studies Arab Open University Al-Ardiya industrial Area Kuwait Faculty of Engineering Jadara University Irbid Jordan

Prostate cancer is one of the leading causes of cancer-related deaths among men. Early detection of Prostate cancer is important in improving the survival rate of patients. In this study, we aimed to develop a machine learning model for the detection and diagnosis of Prostate cancer using clinical and radiological data. We used a dataset of 200 patients with Prostate cancer and 200 healthy controls and extracted a set of features from their clinical and radiological data. We then trained and evaluated several machines learning models, including logistic regression, decision tree, random forest, support vector machine, and neural network models, using 10-fold cross-validation. Our results show that the random forest model achieved the highest accuracy of 0.92, with a sensitivity of 0.95 and a specificity of 0.89. The decision tree model achieved a similar accuracy of 0.91, while the logistic regression, support vector machine, and neural network models achieved lower accuracies of 0.86, 0.87, and 0.88, respectively. Our findings suggest that machine learning models can be effective in detecting and diagnosing Prostate cancer using clinical and radiological data, and that the random forest model may be the most suitable model for this task.

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Pneumonia Detection in Chest X-ray using InceptionV3 and Multi-Class Classification 3

Pneumonia Detection in Chest X-ray using InceptionV3 and Mul...

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3rd International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Rajinikanth, Venkatesan Kadry, Seifedine Damasevicius, Robertas Pandeeswaran, C. Abed Mohammed, Mazin Glan Devadhas, G. Noroff University College Faculty of Applied Computing and Technology Kristiansand94612 Norway Silesian University of Technology Faculty of Applied Mathematics Gliwice44-100 Poland St. Joseph's College of Engineering Omr Department of Electronics and Instrumentation Engineering Chennai600119 India University of Anbar College of Computer Science and Information Technology Ramadi31001 Iraq Vimal Jyothi Engineering College Department of Electronics and Instrumentation Engineering Chemperi670632 India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

The lung is a imperative internal organs in human physiology. The abnormality in the lung will cause severe respiratory problems. Pneumonia is a severe lung infection, and early screening and treatment are essential to heal the illness. This research aims to implement a pre-trained InceptionV3 scheme to detect pneumonia in chest X-ray pictures. This scheme consists of the following phases;(i) Image collection and resizing, (ii) Deep-features extraction using InceptionV3, (iii) Feature reduction with firefly algorithm, (iv) Multi-class classification, and (v) Validation. A four-class classifier is employed in the proposed scheme to classify the X-ray into normal, mild, moderate, and severe classes using 5-fold cross-validation. The experimental outcome of the K-Nearest Neighbor (KNN) classifier confirms that this scheme offered a classification accuracy of 85.18% on the considered image database. © 2022 IEEE.

关键词： Classification (of information)

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Review of Abnormalities Detection in IoT Using Evolutionary Deep Learning

Review of Abnormalities Detection in IoT Using Evolutionary ...

引用

information technology, Applied Mathematics and Statistics (ICITAMS), International Conference on

作者： Sameer Rasim Kokaz Alaa Taima Albu Salih Ahmad Ghandour Faculty of Engineering Islamic University of Lebanon Berut Lebanon College of Computer Science and Information Technology University of Al-Qadisiyah Al-Qadisiyah Iraq

ISBN: (数字)9798350335118

ISBN: (纸本)9798350335125

Today, the Internet is used for various applications such as sending or receiving emails, access to multimedia services, social networks, etc. Moreover, the population of people who use the Internet is increasing. Therefore, the issue of Internet of Things (IoT) security has become a major problem today. Recently, Deep Learning has become one of the most influential and valuable methods for detecting abnormalities in IoT Networks. Further, Deep Learning models produced more effective performance than traditional techniques in abnormalities detection. Moreover, the structure and parameters of ML and DL models can be optimized using evolutionary algorithms (EA). The survey aims to overview recent research on anomaly detection in the IoT-based Deep Learning model that EA has enhanced.

关键词： Deep learning Training Surveys Social networking (online) Sociology Evolutionary computation Mathematical models

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Advancements and Challenges in Arabic Optical Character Recognition: A Comprehensive Survey

arXiv

引用

arXiv 2023年

作者： Kasem, Mahmoud SalahEldin Mahmoud, Mohamed Kang, Hyun-Soo Department of Information and Communication Engineering School of Electrical and Computer Engineering Chungbuk National University Cheongju-si28644 Korea Republic of Information Technology Department Faculty of Computers and Information Assiut University Assiut71526 Egypt Multimedia Department Faculty of Computers and Information Assiut University Assiut71526 Egypt

Optical character recognition (OCR) is a vital process that involves the extraction of handwritten or printed text from scanned or printed images, converting it into a format that can be understood and processed by machines. This enables further data processing activities such as searching and editing. The automatic extraction of text through OCR plays a crucial role in digitizing documents, enhancing productivity, improving accessibility, and preserving historical records. This paper seeks to offer an exhaustive review of contemporary applications, methodologies, and challenges associated with Arabic Optical Character Recognition (OCR). A thorough analysis is conducted on prevailing techniques utilized throughout the OCR process, with a dedicated effort to discern the most efficacious approaches that demonstrate enhanced outcomes. To ensure a thorough evaluation, a meticulous keyword-search methodology is adopted, encompassing a comprehensive analysis of articles relevant to Arabic OCR, including both backward and forward citation reviews. In addition to presenting cutting-edge techniques and methods, this paper critically identifies research gaps within the realm of Arabic OCR. By highlighting these gaps, we shed light on potential areas for future exploration and development, thereby guiding researchers toward promising avenues in the field of Arabic OCR. The outcomes of this study provide valuable insights for researchers, practitioners, and stakeholders involved in Arabic OCR, ultimately fostering advancements in the field and facilitating the creation of more accurate and efficient OCR systems for the Arabic language. © 2023, CC BY.

关键词： Optical character recognition

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