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10th International Conference on Advanced Informatics: Concept, Theory and Application, ICAICTA 2023

作者： Atika, Syarifah Aulia, Indra Syahputra, Mohammad Fadly Universitas Sumatera Utara Faculty of Computer Science and Information Technology Department of Information Technology Medan Indonesia School of Computing Telkom University Jakarta Indonesia

ISBN: (纸本)9798350329919

Autism Spectrum Disorder cannot be cured, but therapy can reduce the symptoms of this disorder. One of the therapies offered is social story therapy, which utilizes a visual interactive approach in which a social story, or a written narrative, is read to the children by the therapist. The purpose of the story is to assist children in comprehending specific situations or conditions they encounter. The social story game will be developed in a 2D format. The social story that will be incorporated into the game focuses on the experiences of elementary school students in their daily lives. As part of the social story game, the precoding method will be incorporated, which is specifically designed to help children with autism improve their motor skills. Using drag-and-drop playstyles, this precoding technique will be implemented in mobile games. For the game development, we will be using Unity 3D, ensuring compatibility with the Android operating system. The game was tested with observation and usability testing. Observation result indicate that the children are showing interest in learning and playing the game. For the The Usability testing results indicate a 61.35% learnability function, 62% memorability function, 72% efficiency function, and 75% satisfaction function. These metrics were used to evaluate the game's performance and user satisfaction. © 2023 IEEE.

关键词： Android (operating system)

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Enhancing Dog Tracking Through Dynamic Geofencing and Environmental Awareness 5

Enhancing Dog Tracking Through Dynamic Geofencing and Enviro...

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5th International Conference on IoT Based Control Networks and Intelligent systems, ICICNIS 2024

作者： Saikrupa, P.A. Dhaarini, G. Sanjai, R. Sri Sairam Institute of Technology Department of Information Technology Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (数字)9798331518097

ISBN: (纸本)9798331518097

With the development of smart technologies, tracking businesses have evolved as tracking collars are now becoming the most crucial piece of safety equipment as well as monitoring tools for dogs. Various solutions like Fi Smart Collar and SpotOn have promising features such as geofencing and activity tracking but integrate with their smart product with less features lacking dynamic geofencing environmental awareness, as well as intelligent system connectivity. The paper proposed a new dog tracking collar system that integrates the use of GPS, Bluetooth, Wi-Fi, and environmental sensors all together onto a unified platform. The system employs an adaptive geofencing module which is dynamic and responds to changes in the environment, including weather and time, as well as different behaviors of pets, keeping it safe within the intended zones. The other advantage with this collar is the maximization of battery life, as it has used low power GPS tracking and intelligent algorithms to adjust the frequency of tracking in line with the assessment of the movement and risk of the pet. The system further integrates into smart home technology and will notify and automatically respond in real-time to changes that might be detected within the pet's environment. The comparative analysis of the current technologies for pet tracking shows significant improvement in accuracy, battery efficiency, and responsiveness to dynamic conditions. The proposed collar was tested and validated by controlled trials and real-time performance assessments, for which considerable results evidenced the reliability and effectiveness for real-time applications. This proposed framework thus would eventually be able to act as a potential future solution that integrates advanced technologies for enhanced pet welfare and with real-time dynamic geofencing and AI in order to create a whole system of pet monitoring. © 2024 IEEE.

关键词： Environmental monitoring

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Fuzzy clustering for electric field characterization and its application to thunderstorm interpretability

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Digital Communications and Networks 2025年第2期11卷 299-307页

作者： Xu Yang Hongyan Xing Xinyuan Ji Wei Xu Witold Pedrycz School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Department of Electrical and Computer Engineering University of AlbertaEdmonton AB T6G 2R3Canada Systems Research Institute Polish Academy of Sciences00-901 WarsawPoland Department of Computer Engineering Faculty of Engineering and Natural SciencesIstinye University34010 IstanbulTurkey

Changes in the Atmospheric Electric Field Signal(AEFS)are highly correlated with weather changes,especially with thunderstorm ***,little attention has been paid to the ambiguous weather information implicit in AEFS *** this paper,a Fuzzy C-Means(FCM)clustering method is used for the first time to develop an innovative approach to characterize the weather attributes carried by ***,a time series dataset is created in the time domain using AEFS *** AEFS-based weather is evaluated according to the time-series Membership Degree(MD)changes obtained by inputting this dataset into the ***,thunderstorm intensities are reflected by the change in distance from a thunderstorm cloud point charge to an AEF ***,a matching relationship is established between the normalized distance and the thunderstorm dominant MD in the space ***,the rationality and reliability of the proposed method are verified by combining radar charts and expert *** results confirm that this method accurately characterizes the weather attributes and changes in the AEFS,and a negative distance-MD correlation is obtained for the first *** detection of thunderstorm activity by AEF from the perspective of fuzzy set technology provides a meaningful guidance for interpretable thunderstorms.

关键词： Atmospheric electric field(AEF) Thunderstorm Fuzzy C-means(FCM) Attribute

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Implementing Hadoop and Moodle Integrated Student Support system 5

Implementing Hadoop and Moodle Integrated Student Support Sy...

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5th International Conference on Advanced information Technologies, ICAIT 2024

作者： Aung, Myint Myat Min Htet, Shin Set, Hein Myo Hpone Thant, Aung Htut, Sithu Htet, Kyaw Zin Nwe Myint Thein, Nwe University of Information Technology Data Distribution Management Lab Yangon Myanmar University of Information Technology Data Distribution Management Lab Faculty of Computer Science Yangon Myanmar

ISBN: (纸本)9798331510046

Learning management systems (LMS) generate large amounts of real-time data which has the potential to provide valuable insights. Hadoop MapReduce is a scalable framework that is designed to handle such data. This paper presents a system architecture that integrates Hadoop MapReduce into Moodle, a popular LMS, for analyzing academic data. The implementation of the architecture allows users to generate a variety of reports from student attendance logs through a Moodle plugin which utilizes the Hadoop cluster for processing data. Users such as lecturers can then utilize these reports to identify which students do and do not engage in which courses as well as monitor their eligibility for exams. The use of Hadoop MapReduce provides high performance computing (HPC) capabilities that offer distributed parallel processing and economical scalability by means of adding commodity nodes to the cluster. © 2024 IEEE.

关键词： MapReduce

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A Knowledge-based Architecture for Managing Research Documents in Higher Institutions

A Knowledge-based Architecture for Managing Research Documen...

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2024 International Conference on science, Engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Mustapha, Abiodun Muyideen Ogunbiyi, Temitope Elizabeth Okikiola, Folasade Mercy Oyedele, Olusanya Braimah, Joachim Ayodeji Anchor University Department of Mathematical Science Lagos State Lagos Nigeria Bells University of Technology Department of Computer Science and Information Technology Ogun State Ota Nigeria Yaba College of Technology Department of Computer Technology Lagos State Nigeria McPherson University Department of Physical and Computer Sciences Ogun State Seriki-Sotayo Nigeria

ISBN: (纸本)9798350358155

Research documents are part of the necessary documents submitted to earn degrees in higher educational institutions across the world. Higher educational institutions in Nigeria face significant challenges in managing and disseminating these academic research documents efficiently. In this study, an architecture for a Knowledge-Based Research Management system (KBRMS) aimed at transforming the landscape of academic research management is presented. The use of advanced algorithms, such as H2P Matching for autosuggestions based on user input and information Extraction for specific data retrieval makes the system well-structured, efficient, and user-friendly. Beyond serving as a digital archive, the KBRMS aims to redefine how academic research documents are organized, accessed, and utilized. The architecture is particularly tailored for Nigeria's tertiary educational sector, addressing their specific challenges and requirements. Its implementation would leverage cutting-edge web-based development tools like ReactJS and cloud-based backend platforms such as Heroku and Google Cloud. The KBRMS promises to contribute significantly to fostering a knowledge-based economy in Nigeria, thus having a broader societal impact. This approach will facilitate full compliance with academic standards, enhance the quality of research outputs, and pave the way for international recognition of scholarly works originating from Nigeria. © 2024 IEEE.

关键词： Research and development management

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A Usability Management Framework for Securing Healthcare information system

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computer systems science & Engineering 2022年第9期42卷 1015-1030页

作者： Hosam Alhakami Abdullah Baz Wajdi Alhakami Abhishek Kumar Pandey Alka Agrawal Raees Ahmad Khan Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Engineering College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025India

Transformation from conventional business management systems tosmart digital systems is a recurrent trend in the current era. This has led to digitalrevolution, and in this context, the hardwired technologies in the software industry play a significant role However, from the beginning, software security remainsa serious issue for all levels of stakeholders. Software vulnerabilities lead to intrusions that cause data breaches and result in disclosure of sensitive data, compromising the organizations’ reputation that translates into, financial losses andcompromising software usability as well. Most of the data breaches are financiallymotivated, especially in the healthcare sector. The cyber invaders continuouslypenetrate the E- Health data because of the high cost of the data on the darkweb. Therefore, security assessment of healthcare web-based applicationsdemands immediate intervention mechanisms to weed out the threats of cyberattacks for the sake of software usability. The proposed disclosure is a unique process of three phases that are combined by researchers in order to produce andmanage usability management framework for healthcare information system. Inthis most threatened time of digital era where, Healthcare data industry has bornethe brunt of the highest number of data breach episodes in the last few years. Thekey reason for this is attributed to the sensitivity of healthcare data and the highcosts entailed in trading the data over the dark web. Hence, usability managementof healthcare information systems is the need of hour as to identify the vulnerabilities and provide preventive measures as a shield against the breaches. The proposed unique developed model of usability management workflow is preparedby associating steps like learn;analyze and manage. All these steps gives an allin one package for the healthcare information management industry because thereis no systematic model available which associate identification to implementationsteps with d

关键词： Smart healthcare healthcare industry usability security

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Multi-Scale Network for Thoracic Organs Segmentation

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computers, Materials & Continua 2022年第2期70卷 3251-3265页

作者： Muhammad Ibrahim Khalil Samabia Tehsin Mamoona Humayun N.Z Jhanjhi Mohammed A.AlZain Department of Computer Science Bahria UniversityIslamabadPakistan Department of Information systems College of Computer and Information SciencesJouf UniversityKSA School of Computer Science and Engineering(SCE) Taylor’s UniversityMalaysia Center for Smart Society 5.0(CSS5) Faculty of Innovation and Technology(FIT)Taylor’s UniversityMalaysia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Medical Imaging Segmentation is an essential technique for modern medical *** is the foundation of many aspects of clinical diagnosis,oncology,and computer-integrated surgical *** significant successes have been achieved in the segmentation of medical images,DL(deep learning)*** delineation of OARs(organs at risk)is vastly dominant but it is prone to errors given the complex irregularities in shape,low texture diversity between tissues and adjacent blood area,patientwide location of organisms,and weak soft tissue contrast across adjacent organs in CT *** now several models have been implemented onmulti organs segmentation but not caters to the problemof imbalanced classes some organs have relatively small pixels as compared to *** segment OARs in thoracic CT images,we proposed the model based on the encoder-decoder approach using transfer learning with the efficientnetB7 DL *** have built a fully connected CNN(Convolutional Neural network)having 5 layers of encoding and 5 layers of decoding with efficientnetB7 specifically to tackle imbalance class pixels in an accurate way for the segmentation of *** methodology achieves 0.93405 IOU score,0.95138 F1 score and class-wise dice score for esophagus 0.92466,trachea 0.94257,heart 0.95038,aorta 0.9351 and background *** results showed that our proposed framework can be segmented organs accurately.

关键词： Deep learning convolutional neural network computed tomography organs at risk computer-aided diagnostic

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A deep learning model framework for diabetic retinopathy detection

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International Journal of Networking and Virtual Organisations 2022年第2期27卷 107-124页

作者： Padmapriya, M. Pasupathy, S. Sumathi, R. Punitha, V. Department of Computer Science and Engineering Faculty of Engineering and Technology Annamalai University Chidambaram India Department of Computer Science and Engineering Annamalai University Tamilnadu Annamalai Nagar India Department of Information Technology Saranathan College of Engineering Tamilnadu India

Diabetic retinopathy (DR) is the typical diabetic eye issue and a main reason of blindness around the world. As per the International Diabetes Federation (IDF), the rates of diabetes would rise to 552 million by 2034. Breakthroughs in computer science techniques inclusive of artificial intelligence (AI) and deep learning (DL) have multiplied opportunities for early detection of DR. This indicates that the likelihood of a patient's healing will improve, and the risk of eyesight loss could be minimised in due course. A deep learning model (ResNet) for medical DR detection was examined in this article. The dataset of Asia Pacific Tele-Ophthalmology Society (APTOS) 2019 was used to train and test the DL model. To demonstrate the vitality of the chosen ResNet model, performance measures and testing accuracy like recall, precision, and F1 score were determined. The modified ResNet model attained a testing accuracy of around 84% even with only a few dataset images. Also, training time and computational complexity were reduced with this simpler model. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Statistical tests

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Modeling and Verification of the Causal Broadcast Algorithm Using Colored Petri Nets 3

Modeling and Verification of the Causal Broadcast Algorithm ...

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3rd International Conference on Distributed Computing and High Performance Computing, DCHPC 2024

作者： Namvaritazehkand, Leila Pashazadeh, Saied University of Tabriz Faculty of Electrical and Computer Engineering Department of Computer Engineering East Azerbaijan Tabriz Iran University of Tabriz Faculty of Electrical and Computer Engineering Department of Information Technology East Azerbaijan Tabriz Iran

ISBN: (纸本)9798350381580

The Causal Broadcast (CB) algorithms are presented for message passing between processes of distributed systems (DSs). These algorithms play an essential role in distributed computing. Therefore, the correctness of their performance is a high priority. Recently, researchers used the theorem-proving technique to verify causal consistency algorithms. To our knowledge, no CB algorithm presented for message-passing has been modelled and verified by a mechanical proof method. For the first time, this paper models and verifies one of the most basic CB algorithms using one of the formal methods called colored Petri nets because this algorithm has been used as the base algorithm in developing the most recent algorithms. We first model this algorithm hierarchically at the application and protocol layers using the CPN tool. Then, by analyzing the state space, we verify the properties of the CB, namely integrity, causal delivery, validity, and termination. The novelty of this paper lies in its pioneering use of colored Petri nets to model and verify a CB algorithm for the first time. This modeling method can potentially serve as a guiding method for future endeavors in modeling distributed algorithms. © 2024 IEEE.

关键词： Message passing

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Advanced Schedulability Testing for Adaptive Mixed-Criticality systems under Weakly Hard Real-Time Constraints 5

Advanced Schedulability Testing for Adaptive Mixed-Criticali...

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5th CPSSI International Symposium on Cyber-Physical systems (Applications and Theory), CPSAT 2024

作者： Rabbiun, Hossein Mohammadi, Jamal Shirazi, Mahmoud Kargahi, Mehdi Department of Computer Science and Information Technology Zanjan Iran University of Tehran School of Electrical and Computer Engineering College of Engineering Tehran Iran

ISBN: (纸本)9798331529284

This paper advances the schedulability analysis of the Adaptive Mixed-Criticality for Weakly Hard Real-Time systems (AMC-WH) which allows a specified number of consecutive low-criticality (LO) jobs of tasks to be skipped when the system operates in the high-criticality (HI) mode. The current AMC-WH schedulability test, based on the skip-over model, in which low tasks are guaranteed to meet m-s out of m consecutive deadlines, where s is the number of allowed skips and m is the cycle length, only calculates the worst-case response times (WCRT) for low tasks under a fixed execution pattern post-mode switch. To address this limitation, we propose a new sufficient schedulability test for AMC-WH using the (m,k)-firm model, which allows various execution patterns for low tasks after a mode switch, enhancing the flexibility and applicability. Additionally, we develop an exact schedulability test for AMC-WH based on response time analysis (RTA). This test modifies the existing exact tests for the AMC algorithm, incorporating updates to state-space exploration and pruning rules to account for low task execution after a mode switch. Simulation results validate the effectiveness of our tests, demonstrating enhanced schedulability analysis and optimized resource allocation. © 2024 IEEE.

关键词： Space research

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