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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Thiruvenkadam, T. Acharjya, Kalyan Goyal, Manish Kumar Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Application Jaipur India

ISBN: (纸本)9798350383348

This summary outlines how sparse coding in vehicle encoders may be used to come across most cancers. It explains that by using learning sparse representations of raw records, you can benefit from a higher understanding of the underlying dynamics of cancer improvement. Furthermore, this summary outlines two of the most commonplace packages of vehicle encoders for cancer detection: function extraction and fitness tracking. This look gives insights into the capability of car encoders for efficient cancer analysis. For this reason, it should prove to be a vital element of most cancer detection and prevention. Sparse coding has been gaining interest inside the region of auto-encoder-based total methods for most cancer detection. With the increasing complexity of deep getting-to-know fashions being used for detection, the information and mastery of this research approach moderately encoded representations have turned out to be vital. Auto-encoders are used to encapsulate and encode inputs from high-dimensional facts into a lower-dimensional representation to keep the most crucial or crucial data from the facts. A selected type of vehicle encoder, a sparse automobile encoder, is designed to analyze sparsely encoded representations of records by introducing sparsity into the hidden layer of the automobile encoder via sure specialized regularizes. © 2024 IEEE.

关键词： automobile commonplace detection element interest

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Hierarchical Representation Learning for Improved Diagnosis of Prostate Cancer on MRI Scans

Hierarchical Representation Learning for Improved Diagnosis ...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Prabhu, A. Pandeya, Megha Kaushik, Harshita Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Application Jaipur India

ISBN: (纸本)9798350383348

It focuses on using hierarchical illustration mastering (HRL) for the progressed prognosis of most prostate cancers on MRI scans. HRL is a gadget getting-to-know technique using a hierarchy of function vectors to encode record sets, allowing extra complicated non-linear styles to be recognized and applied. In this examination, HRL is compared to a fashionable convolution neural network (CNN) classifier for the challenge of prostate cancer analysis on MRI scans. The effects show that HRL outperforms the CNN classifier, providing a higher accuracy fee and universal predictive performance. Furthermore, HRL results in fewer fake positives and extra correct type accuracy. Its improved overall performance suggests that utilizing HRL in medical decision-making can offer a more correct, practical analysis of most prostate cancers. © 2024 IEEE.

关键词： convolutional improved performance predictive representation

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Exploiting Convolutional Neural Networks for Automated Pathology Image Classification

Exploiting Convolutional Neural Networks for Automated Patho...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Sharma, Sunil Menaka, C. Singh, Akhilendra Pratap Vivekananda Global University Department of Computer Science & Application Jaipur India Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350383348

Convolutional neural networks (CNNs) are a deep mastering method for the computerized pathology photograph category. With the improvement of superior imaging techniques, the quantity of virtual and representable pathology pix has increased notably. Automatic picture evaluation has become increasingly crucial to exploit those photographs for clinical selections. CNNs have attracted huge interest and were established to be very powerful for automated photograph classification and object detection. The improvement of deep getting-to-know based on Convolutional Neural Networks (CNNs) for computerized pathology photo classes has been a focal point of research in current years. This paper critiques the recent advances in CNNs in automatic pathology image type. The key architectures and algorithms for CNNs are summarized, and their capability applicability in pathology picture classification is discussed. This overview also introduces the maximum hit CNN methods that have been proposed and have proven promising consequences in pathology photograph category duties. The paper concludes with a dialogue of future research directions in this area. Convolutional neural networks (CNNs) are a deep mastering method for the computerized pathology photograph category. With the improvement of superior imaging techniques, the quantity of virtual and representable pathology pix has increased notably. To exploit those photographs for clinical selections, automatic picture evaluation has grown to be an increasingly number of crucial. CNNs have attracted huge interest and were established to be very powerful for automated photograph classification and object detection. The improvement of deep getting-to-know based on Convolutional Neural Networks (CNNs) for computerized pathology photo classes has been a focal point of research in current years. This paper critiques the recent advances in CNNs in automatic pathology image type. The key architectures and algorithms for CNNs are summarized,

关键词： classification Convolutional development discussion pathology

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Optimized Sensor Network Design for Real-Time Environmental Monitoring

Optimized Sensor Network Design for Real-Time Environmental ...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Harron, Syed Shukla, Gaurav Kaushik, Harshita Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Application Jaipur India

ISBN: (纸本)9798350383348

A sensor community is a set of interconnected sensors that can degree, monitor, and report phenomena within the environment. Sensor networks have many packages consisting of actual-time environmental tracking. A good way to effectively use these networks for monitoring, an optimized network layout needs to be employed to ensure that the network can meet the necessities of its operational demands. This paper proposes a fashionable-motive sensor network design framework for real-time environmental tracking. The proposed framework gives a step-by-step technique to optimize a sensor network design for the project at hand. It begins with a version of the surroundings that the sensor community will screen, which is used to generate sensor node configurations and topologies. These configurations and topologies are then used to lay out the sensor community such that its deployment is optimized for the surroundings. The design framework makes use of a community optimization set of rules to attain a configuration that maximizes the network's performance and is capable of meeting its operational requirements. The set of rules operates with the aid of looking through the distance of all feasible sensor community topologies, looking for those that have the first-rate value-benefit ratio. The algorithm can be further progressed by way of the usage of the device, gaining knowledge of strategies, which makes it capable of managing extra complex eventualities. © 2024 IEEE.

关键词： Algorithm Community Eventualities Interconnected Requirements Sensor Strategies Value-Benefit

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Microprocessor Instruction Design Tool for RISC-V Architecture 22

Microprocessor Instruction Design Tool for RISC-V Architectu...

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22nd International Symposium on Communications and Information Technologies, ISCIT 2023

作者： Jiahui, Luo Morimoto, Tomoyuki Ogita, Tadahiro Kawamata, Ryota Wang, Ziming Tsutsumi, Toshiyuki Meiji University Computer Science Program Graduate School of Science and Technology Kanagawa Japan Meiji University School of Science and Technology Department of Computer Science Kanagawa Japan

ISBN: (纸本)9781665457316

We have been developing MEIMAT (MEiji Microprocessor Architecture Design Tools). The MEIMAT is essentially designed to be able to represent any instruction of various processors by the MEIMAT meta-instruction in two ways of semantic and functional expressions. In this paper, we have verified the RISC-V support to the MEIMAT, and have improved so that MEIMAT further supports RISC-V. First, we have verified whether the RISC-V instructions can be expressed by the MEIMAT semantic expression. It is also verified that the functional expression is automatically generated from the semantic instruction, and the corresponding correct circuit diagrams are generated in the MEIMAT instruction visualization tool. Then, we have newly developed a stage configuration mechanism to implement the RISC-V instructions. Because the RISC-V architecture is implemented by 4 or 5 processing stages in most actual processors. To develop further an easy-to-understand design tool, we have also introduced illustration windows for RISC-V specified hardware modules such as a register file, especially a status register in the instruction visualization tool. Finally, through these verifications and improvements, we have successfully confirmed that the 43 instructions in the RISCV (RV32I) instructions set of the RISC-V architecture can be converted into MEIMAT meta-instructions, and then they can be represented as circuit diagrams with the RISC-V stage configuration in the MEIMAT instruction visualization tool. © 2023 IEEE.

关键词： Integrated circuit design

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Comparative usability analysis across different driving control scenarios in a driving simulation game

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Procedia computer science 2024年 245卷 330-336页

作者： David Juan Davis Leon Lewis Christian Oliver Muhamad Fajar Galih Dea Pratama Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

This study aims to address the gap in the evaluation of driving simulation games by further assessing and developing ProjectStir (a Driving Simulation Game) through its adaptation to two different driving control devices: a steering wheel and an arcade stick. Despite the growing popularity of simulation games, limited research has been conducted on how different control devices impact user experience and usability. Usability was evaluated through variables including Easiness of Game Control, Learnability of Gameplay, Remembrance, Challenge, Efficiency, Tension, Familiarity, and Satisfaction. Involving 30 respondents from the computer science program at BINUS University, the results revealed no significant differences in usability between the two scenarios (p<0.05), as determined by the Wilcoxon signed-rank test and paired t-test. These findings suggest that ProjectStir offers consistent usability, regardless of whether a steering wheel or an arcade stick is used for gameplay, thus providing valuable insights for future development and refinement of driving simulation games.

关键词： Game Based Leaning Serious Game Usability User Experience

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Improving energy efficiency in scalable WSNs through IoT-driven approach

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International Journal of Information technology (Singapore) 2025年 1-11页

作者： Singh, Omkar Kushwaha, Ajay Shriram Sharma, Col. Rahul Kumar, Lalit National Institute of Fashion Technology Bihar Patna India Department of Computer Science & Application Sharda School of Computing Sciences & Engineering Sharda University UP Greater Noida India School of Computer Science & Engineering ILM University Greater Noida India

A novel QoS-Driven Optimization for Energy-Efficient Clustering Routing (QDOEECR) protocol tailored for IoT-based Wireless Sensor Networks (WSNs), addressing the critical challenge of energy efficiency in sensor nodes with limited battery life. The protocol’s innovative approach lies in its advanced techniques for optimizing the selection of sub-sink nodes and identifying the optimal path to the sink node, ensuring improved adherence to Quality of Service (QoS) standards. Performance evaluations, conducted through MATLAB simulations, demonstrate the QDOEECR protocol's superior performance, achieving significant advancements over existing routing protocols. These include 30–35% reduction in end-to-end delay, 25–30% improvement in throughput, 35–40% decrease in energy consumption, 28–32% reduction in packet loss, and 32–38% extension in network lifetime. These results establish QDOEECR as a groundbreaking solution that not only enhances energy efficiency but also elevates network performance metrics beyond the capabilities of current state-of-the-art protocols like CBCCP, HCSM, and ZEAL. © Bharati Vidyapeeth's Institute of computer applications and Management 2025.

关键词： CBCCP HCSM IoT QDOEECR WSN ZEAL

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Player evaluation and learning outcomes of “NusaVenturas”: A serious game for enhancing player knowledge and interest in Indonesian traditional foods

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Procedia computer science 2024年 245卷 320-329页

作者： Vito Sebastian Sanjaya Nicholas Valenthinus Tanoto Nicholas Tandinata Dimas Ramdhan Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480

The popularity of Indonesian traditional food has been declining due to the increasing influence of foreign cuisine. This study presents the development method that combining Game Development Life Cycle (GDLC) with Experiential Game Learning Design Framework and evaluation of a serious game "NusaVenturas" using usability, learning outcome, and Game Experience Questionnaire (GEQ) that designed to introduce, promote interest, educate, and preserve knowledge of Indonesian traditional foods. "NusaVenturas" is a unique 2D serious game that integrates puzzle-platformer elements with time-management cooking mechanics. The study involved 37 participants aged 18 to 23. Evaluation results indicate that "NusaVenturas" significantly enhances players' knowledge of Indonesian traditional foods, with statistical analysis confirming the significance of the findings.

关键词： serious games culture indonesian foods usability learning outcomes game experience questionnaire

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Development of “Peter's First-Aid Adventure” Virtual Reality-Based Serious Game in First-Aid Education: Usability Analysis of Virtual Reality Interaction Tools

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Procedia computer science 2024年 245卷 309-319页

作者： Alexander Rainer Angeline Setiono Kevin Leonardrich Dimas Ramdhan Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Incidents that threaten lives can occur unexpectedly, highlighting the importance of immediate first aid. Studies show that Virtual Reality (VR)-based Serious Games (SG) are excellent alternatives for learning, especially for physical training, as they provide immersive and realistic scenarios where users can learn and practice their skills in a safe environment. Therefore, this research proposes the design of a VR-based SG for learning first aid procedures. A total of 31 participants tested the game's usability using both VR controllers and hand tracking, playing the game with both tools in random order, and then completing the XR-GUQ and Interaction Categories questionnaire. The results indicate that controllers offer higher usability than hand tracking. However, the game can still effectively utilize both interaction tools, given their satisfactory usability ratings.

关键词： Serious Games Virtual Reality First Aid Hand Tracking Usability Health Interaction Tools Education

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Development of educational game as a media to raise public awareness of illegal animal trafficking issue in Indonesia

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Procedia computer science 2024年 245卷 337-345页

作者： Jonathan William Khalid Ahmadi Muhamad Fajar Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

Abstract The amount of illegal wildlife trade cases increases every year in Indonesia. This causes some unique Indonesian wildlife to become endangered or even extinct. Therefore, the purpose of this research is to raise public awareness to illegal wildlife trade issue by using a game as its media to reduce the number of cases of illegal wildlife trade in Indonesia. The game made in this research will be developed using the GDLC development method and 2021.3.11f1 version of Unity as its game engine. To evaluate the game that has been developed in this research, a comparation to other related games is conducted and resulted in the game that has been developed in this research is significantly better than other related games in Challenge, Learnability and Concentration aspects (p < 0.001).

关键词： Animal Game Wildlife Education Awareness

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