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HealthEdge: A Machine Learning-Based Smart Healthcare Framework for Prediction of Type 2 Diabetes in an Integrated IoT, Edge, and Cloud Computing System 14

HealthEdge: A Machine Learning-Based Smart Healthcare Framew...

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14th International Conference on Ambient systems, Networks and Technologies Networks, ANT 2023 and The 6th International Conference on Emerging Data and Industry 4.0, EDI40 2023

作者： Hennebelle, Alain Materwala, Huned Ismail, Leila Melbourne Australia Research Laboratory Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University United Arab Emirates National Water and Energy Center United Arab Emirates University United Arab Emirates Lab School of Computing and Information Systems The University of Melbourne Australia

Diabetes Mellitus has no permanent cure to date and is one of the leading causes of death globally. The alarming increase in diabetes calls for the need to take precautionary measures to avoid/predict the occurrence of diabetes. This paper proposes HealthEdge, a machine learning-based smart healthcare framework for type 2 diabetes prediction in an integrated IoT-edge-cloud computing system. Numerical experiments and comparative analysis were carried out between the two most used machine learning algorithms in the literature, Random Forest (RF) and Logistic Regression (LR), using two real-life diabetes datasets. The results show that RF predicts diabetes with 6% more accuracy on average compared to LR. © 2023 Elsevier B.V.. All rights reserved.

关键词： Edge computing

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Designing and simulating IoT environments by using a model-driven approach*

Designing and simulating IoT environments by using a model-d...

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Iberian Conference on Information systems and Technologies (CISTI)

作者： José A. Barriga Pedro J. Clemente Department of Computer and Telematic Systems Engineering Quercus Software Engineering Group Universidad de Extremadura C&#x00E1 ceres Spain

Developing, deploying and testing IoT projects require high investments on devices, fog nodes, cloud nodes, analytic nodes, hardware and software. However, in order to decrease the cost associated to develop and test the IoT system it can be previously simulated. In this regard, designing IoT simulation environments has been tackled focusing on low level aspects such as networks, motes and so on more than focusing on the high level concepts related to IoT environments. Model-driven development aims to develop the software systems from domain models which capture at high level the domain concepts and relationships, generating from them the software artefacts by using code-generators. In this paper, a model-driven development approach is applied to define, generate code and deploy IoT systems simulations. The IoT simulation environment generated from each model includes the sensors, actuators, fog nodes, cloud nodes and analytical characteristics. Additionally, a case study, focused on an Industrial IoT environment is presented to show the simulation expressiveness.

关键词： Analytical models Codes Focusing computer architecture Sensor phenomena and characterization software systems systems simulation

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Utilization of Online Collaborative Tools in software engineering: An Empirical Study on Review Meetings 6

Utilization of Online Collaborative Tools in Software Engine...

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6th International Conference on computer Science and engineering, UBMK 2021

作者： Akman, Ibrahim Turhan, Cigdem Hacaloglu, Tuna Dept. of Computer Engineering Atilim University Ankara Turkey Dept of Software Engineering Atilim University Ankara Turkey Dept of Information Systems Engineering Atilim University Ankara Turkey

ISBN: (纸本)9781665429085

software development involves a significant amount of team effort where collaboration and communication of the team members are crucial. The team meetings are core activities in all stages of the software development process. Even though these meetings often are conducted face-to-face (F2F) with a lackof technology utilization, changing global conditions such as the COVID-19 pandemic require other solutions urgently without interrupting the software development schedule. For this purpose, online collaborative tools provide new opportunities for software teams to work together avoiding waste in time and resources and the relevant literature is immature. This study aims to assess the factors affecting the integration of online collaborative tools to SE practices with a special reference to review meetings. For this purpose, a sample of 73 SE sophomore and junior students who are future software professionals participated in experimental review meetings based on predefined scenarios. The findings indicate that the utilization of OCT's has positive effects on the participants' actual performance and improves the interaction between team members compared to F2F meetings. © 2021 IEEE

关键词： software design

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CASolarNet: Channel Attention EfficientNet-based Model for Solar Panel Dust Detection

CASolarNet: Channel Attention EfficientNet-based Model for S...

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Hussein M. A. Mohammed Abdulfattah E. Ba Alawi Energy and Cooling Systems Department Turk Telekom Ankara Turkey Mechatronics and Robotics Engineering Department Faculty of Engineering & IT Taiz University Taiz Yemen Computer Engineering Department Faculty of Engineering Ataturk University Erzurum Turkey Software Engineering Department Faculty of Engineering & IT Taiz University Taiz Yemen

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

The accumulation of dust on solar panels dramatically reduces the efficiency of solar energy systems, an issue that is often overlooked in both urban and rural settings. This work proposes a novel solution to this widespread problem of Solar Dust Detection. Utilizing EfficientNet, which is known for its balanced approach to model depth, width, and resolution, our proposed model accurately identifies dust on solar panels. The suggested model (CASolarNet) employs Channel Attention, EfficientNet, and focal loss to enhance the performance of detecting dust on solar cells. By dynamically modifying feature weights, channel attention techniques enhance dust detection by emphasizing the locations of dust in an image. This capability is crucial for maintaining optimal energy production and extending the lifespan of solar cells. Our model has been extensively tested and validated, resulting in a high accuracy rate of more than 98%. The obtained performance demonstrates the model's effectiveness in various environmental conditions, establishing a new standard in solar maintenance technology. The use of the proposed CASolarNet model has several advantages, including increased energy efficiency, lower maintenance costs, and greater sustainability of solar power systems.

关键词： Image resolution Photovoltaic cells Solar energy Production Feature extraction Maintenance Power systems

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A multi-objective cuckoo search algorithm using generalized Lèvy flight and dissimilar egg identification for multispectral image thresholding

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Applied Soft Computing 2025年 175卷

作者： Pal, Ramen Roy, Pritam Mallick, Srijon Mukhopadhyay, Somnath Sarkar, Sunita Hinchey, Mike Department of Computer Science and Engineering Assam University Silchar Assam India Cognizant Technology Solutions India Pvt. Ltd. India Samsung Semiconductor India Research India Lero the SFI Research Centre for Software Department of Computer Science & Information Systems University of Limerick Limerick Ireland

Cuckoo Search (CS) stands as a highly efficient meta-heuristic optimization algorithm. Existing literature showcases the ability of CS in multi-objective scenarios, delineated by the three fundamental rules. However, the first rule of the algorithm incurs the cost of a generation to update a single nest, while the third rule necessitates hit-and-trial methods for parameter adjustment. To address these concerns, a multi-objective cuckoo search algorithm is proposed in this paper. The algorithm builds upon a generalized concept of Lèvy Flight for generating new solutions. Problem-specific, constraint-based strategies for identifying the best nest and dissimilar eggs are also introduced. The algorithm is further applied to solve multispectral remote sensing image thresholding problem. Prior studies have underscored the efficiency of entropy and clustering-based thresholding methods over other techniques. Nevertheless, most entropy-based approaches entail converting color images to grayscale before segmentation, potentially sacrificing crucial spectral information and consequently degrading segmentation algorithm's performance. To avoid these limitations, this research introduces an entropy-based thresholding method to segment a color image without converting it to grayscale. The experiments are carried out using very high resolution (VHR) and coarse resolution (CR) multispectral (MS) images from the satellite sensors Pl'eidas-1B and Sentinel-2b, respectively. The proposed methods undergo validation against four state-of-the-art techniques on benchmark functions and six clustering indexes, respectively. © 2025 Elsevier B.V.

关键词： Heuristic algorithms

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Ontological Model for Cohesive Smart Health Services Management

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computers, Materials & Continua 2023年第2期74卷 3679-3695页

作者： Muhammad Raza Naqvi Muhammad Waseem Iqbal Syed Khuram Shahzad M.Usman Ashraf Khalid Alsubhi Hani Moaiteq Aljahdali Le Laboratoire Génie de Production de l’École Nationale d’Ingénieurs de Tarbes(LGP-INP-ENIT) Universitéde ToulouseCEDEXTarbes65016France Department of Software Engineering Superior UniversityLahore53700Pakistan Department of Informatics&Systems University of Management&TechnologyLahore54000Pakistan Department of Computer Science University of Management and TechnologySialkot51310Pakistan Department of Computer Science King Abdul-Aziz UniversityJeddah21577Saudi Arabia Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21577Saudi Arabia

Health care has become an essential social-economic concern for all stakeholders(e.g.,patients,doctors,hospitals etc.),health needs,private care and the elderly class of *** massive increase in the usage of health care Internet of things(IoT)applications has great technological evolvement in human *** are various smart health care services like remote patient monitoring,diagnostic,disease-specific remote treatments and *** applications are available in a split fashion and provide solutions for variant diseases,medical resources and remote service *** main objective of this research is to provide a management platform where all these services work as a single unit to facilitate the *** ontological model of integrated healthcare services is proposed by getting requirements from various existing healthcare *** were 26 smart health care services and 26 smart health care services to classify the knowledge-based ontological *** proposed ontological model is derived from different classes,relationships,and constraints to integrate health care *** model is developed using Protégébased on each interrelated/correlated health care service having different *** querying SPARQL protocol and RDF query language(SPARQL)were used for knowledge *** Pellet Reasoner is used to check the validity and relations coherency of the proposed ontology *** to other smart health care services integration systems,the proposed ontological model provides more cohesiveness.

关键词： Ontology internet of things smart health services integration

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The Role of YOLOv8 in Enhancing Strategic Military Equipment Detection

The Role of YOLOv8 in Enhancing Strategic Military Equipment...

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Abdulfattah E. Ba Alawi Hussein M. A. Mohammed Computer Engineering Department Faculty of Engineering Ataturk University Erzurum Turkey Software Engineering Department Faculty of Engineering & IT Taiz University Taiz Yemen Energy and Cooling Systems Department Turk Telekom Ankara Turkey Mechatronics and Robotics Engineering Department Faculty of Engineering & IT Taiz University Taiz Yemen

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

The accurate and fast identification of military equipment on the battlefield is a crucial problem of various military missions and tasks. First, it affects the operation success of the modern armed forces. Second, decision-making is considerably affected by such a capability. In this paper, we address this issue using the potential of the powerful YOLOv8 technique. This allows us to offer an accurate model for identifying various components related to the military and armed forces. The model is tested on the publicly available dataset which contains 11,800 images by evaluating the detection task with YOLOv8-based models. This dataset consists of eleven classes on military-related equipment, which covers different types of military assets. Finally, the YOLOv8x model shows encouraging results in detecting military equipment as demonstrated by a value of 99.1% in terms of mAP50. Through the findings of this study, there has been significant improvement in using AI in military missions, decision-making, and mission readiness which are better than those obtained in the previous studies. According to the obtained findings, this study demonstrates substantial progress in the application of artificial intelligence to military missions and decision-making and operational development.

关键词： Accuracy Decision making Task analysis Artificial intelligence Military equipment

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Integrity Estimation of Twitter Based Event Recognition Using Scrutiny of Analyzed Data

Integrity Estimation of Twitter Based Event Recognition Usin...

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Emerging Trends in Information Technology and engineering (ic-ETITE), Conference on

作者： Siva Rama Lingham N M Parameswari Karthick P T. Subha Rathi Priya G Rajesh J. Jagannathan Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Department of Computer Science and Engineering Knowledge Institute of Technology Salem India Department of Computer Science and Engineering Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College Chennai India School of Engineering and Technology Jeppiaar University Chennai India Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems Vellore Institute of Technology Katpadi Vellore India

Twitter has been observed to be one of the essential data resources for dependable event accreditation. In any case, Twitter-based event affirmation structures can't guarantee assessment concerning their attestation results. Talk statement has been locked in starting late to enable liberal event Recognition. This problem is not yet evident in light of the assumption that most people tend to think that they have a specific limit to the data on Twitter that have frames based on events based on Twitter. Current appraisals see new pieces by seeing and looking at the significant psychological aspects of hitting the details on Twitter. No matter, the scale of the visual cues can be well established, with the intention that it is essential to design an integrated Twitter experiment with another set of extensible data resources to rectify this problem. The problem is the processes by which you should wholeheartedly investigate all converted data because it has different data structures, transfer times, etc. This issue of address, the paper proposes a framework for evaluating the use of Twitter-based events and examines two types of data resources for the reliability of impact testing. Our framework uses the resultant of the request obtaining by various events and relevant to the articles on it. This paper has improved the cleaning test with the proposed process how the integrity estimation of twitter based event can be recognized with the help of group of analyzed data. The evaluation indicates that the proposed system provides visible high-level testing events and a variety of low-level testing events.

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A Hybrid Approach Using Survey and Ism Analysis for Security Coding Risks and Best Practices for Gsd Enterprises

SSRN

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SSRN 2023年

作者： Khan, Rafiq Ahmad Akbar, Muhammad Azeem Alzahrani, Abdulrahman Habibullah, Safa Alwageed, Hathal Salamah Alzahrani, Musaad School of Software Northwestern Polytechnical University Shaanxi Xian710129 China Software Engineering Research Group Department of Computer Science & IT University of Malakand Pakistan Software engineering LUT University Finland Information Systems and Technology Department College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia College of Computer and Information Sciences Jouf University Sakaka42421 Saudi Arabia Department of Computer Science Al-Baha University Al-Baha65799 Saudi Arabia

Context: Global software development (GSD) offers quality results, cost-effectiveness, and uninterrupted project delivery. However, integrating security into GSD remains a ***: This study aims to enhance security in GSD projects by developing a hybrid approach using an empirical survey and Interpretive Structural Model (ISM).Methods: Initially, we conduct a systematic literature review and questionnaire survey with 50 GSD security experts. Moreover, 13 experts were invited to analyze the interrelationships among the practices using ***: Initially, we identified 13 major security-coding risks and 82 practices to mitigate these risks. The ISM analysis revealed that out of the identified security-coding practices, "never submit security measures to illegitimate authority", "avoiding buffer overflow and format string vulnerabilities", "control the brute force attack", and "identify a middleman attack" were considered fully dependent. While "avoid revealing information to achieve a secure design" is entirely independent within the GSD security coding ***: The study aids GSD professionals in assessing readiness in establishing contractual trust, understanding the current process pros and cons, and addressing urgent issues in secure software development processes. © 2023, The Authors. All rights reserved.

关键词： Cost effectiveness

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Intelligent Operational Decision Support System for Sugar Factory Resource Efficiency 5

Intelligent Operational Decision Support System for Sugar Fa...

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5th IEEE International Conference on Modern Electrical and Energy System, MEES 2023

作者： Lutska, Nataliia Zaiets, Nataliia Vlasenko, Lidiia Junge, Stefan National University of Food Technologies Dept. of Automation and Computer Technologies of Control Systems Kyiv Ukraine National University of Life and Environmental Sciences of Ukraine Dept. of Automation and Robotic Systems Kyiv Ukraine State University of Trade and Economics Dept. of Software Engineering and Cyber Security Kyiv Ukraine Berlin University of Applied Sciences Dept. of Packaging Technology Berlin Germany

ISBN: (纸本)9798350359787

With the economic crisis that is looming over the world due to changes in the energy sector and a reduction in the supply of certain types of products, energy and resource efficiency issues are becoming more relevant for the food industry. Also important is the preservation of the environment and the implementation of Cleaner Production trends. Most enterprises follow the concept of Industry 4.0 and increase efficiency through the implementation of intelligent methods, in particular machine learning. The paper proposes a neural network model of sugar production. The model makes it possible to predict the main estimates of resource efficiency used to correct the technological modes of production by the operator-technologist. The structure of the operational decision support system has been developed and is used by personnel to model and predict changes in resource efficiency estimates and KPIs calculated on their basis. Its feature is the integration of methods for achieving resource efficiency, improving environmental performance and ensuring KPIs. To do this, at the initial stage, an analysis of the main flows that affect resource efficiency and an assessment of their importance was carried out. Ensuring Production Performance is confirmed by the simulation and the adequacy of the created neural network accuracy of more than 95%. © 2023 IEEE.

关键词： Decision support systems

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