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24th Asia-Pacific Network Operations and Management Symposium, APNOMS 2023

作者： Elangovan, Muthuraman Iqbal, Muhammad Shahid Chen, Chien Chen, Jyh-Cheng EECS International Graduate Program Taiwan Department of Computer Science National Yang Ming Chiao Tung University Taiwan Saviah Technologies Inc. Taiwan

ISBN: (纸本)9788995004395

– The demands of today’s 5G mobile network, especially low latency and high bandwidth, are a big challenge for the 5G Core (5GC) provider. The most critical user data packet handler in the 5GC Network Function (NF) is the User Plane Function (UPF), which is responsible for moving data from the user equipment to the destination data network, and vice versa. Existing work mainly focuses on implementing UPF using the key technologies of high-speed data processing. In this paper, with a mobile core provider called free5GC for a standalone (SA) 5G network, we share our experience with the implementation of UPF by using a programmable hardware appliance, which can offer more Tbps compared to the implementation of software UPF that can offer only a few hundred Gbps. For that, we demonstrate how to build up a more flexible architecture of UPF by using the Software-Defined Networking (SDN) concept due to the opacity of protocol specification. We split the UPF control signal implementation into a software application, and user data packet processing into a programmable hardware appliance. We also show how to integrate a number of current UPF data plane free5GC implementations such as Data Plane Development Kit (DPDK), Linux kernel module, and SmartNIC. Furthermore, we analyze and make use of microservices to support the specific features of the UPF data plane that cannot be implemented in a programmable hardware appliance. We tested our free5GC mobile network and the new UPF design architecture that can run on a real programmable hardware appliance from Accton CSP-7551. The evaluation results show that our programmable user plane can reach the line rate. Copyright 2023 KICS.

关键词： Wireless networks

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Fuzzy Logic for Assessing the Health of a Corn Crop within Family Farming

Fuzzy Logic for Assessing the Health of a Corn Crop within F...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Mendonca, Vanessa Santos, Mikael Munoz, Daniel M. Humberto Llanos, Carlos Federal Institute of Brasilia Department of Computer Science Brazil Mechatronics Graduate Program Department of Mechanical Engineering Brazil Federal Institute of Brasilia Department of Agronomy Brazil University of Brasilia Faculty of Gama Electronics Engineering Undergraduate Program Brasilia Brazil

ISBN: (纸本)9798350374575

Technological advancements are increasingly evident across various sectors, including automobiles, industry, and healthcare. In precision agriculture, significant progress has been made, with AgroTICs and Smart Agriculture gaining substantial traction in the market. However, a gap remains between cutting-edge technology and family farming, presenting a challenge from both social and applied research perspectives. However, there is still a gap between cutting-edge technology and family farming, which creates a challenge from a social and applied research point of view. In this context, this paper proposes a monitoring model based on Fuzzy Logic and sensor automation applied to estimate the health of a corn crop. The proposed Fuzzy inference system involves calculating an indicator of nutrients as well as the average color and area of corn plants. The nutrient indicator is automatically computed by an ESP32 microcontroller using sensor readings, while the average color and area inputs are manually entered via a mobile application. Additionally, the Fuzzy inference is integrated into the ESP32. The model underwent experimental validation on the health of the plantation, and the results were evaluated in four areas: one was designated for testing, and three were for validation. The model achieved an accuracy of 97.5% in Scenario 3, categorized as 'Very Favorable', and an accuracy of 65% in Scenarios 2 and 4, categorized as 'Unfavorable'. The implications of this research contribute to the advancement of AgroTICs among small producers, with the potential to enhance and automate the monitoring of their harvest production. © 2024 IEEE.

关键词： Agribusiness

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White rice stem borer pest detection system using image-based convolution neural network

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Procedia computer science 2024年 245卷 518-527页

作者： Akhmad Saufi Suharjito Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480

Preventing agricultural resource loss caused by pests remains a crucial issue. While technological advancements are being achieved, the current agricultural management methods and equipment have yet to meet the required level for precise pest control, a huge portion of the pest population analysis process is still conducted manually. As a solution to this issue, the development of a White Rice Stem Borer pest detection system has been conducted by applying Convolutional Neural Network (CNN) technology to calculate the pest population count at the research location. This system has been specifically designed to detect the White Rice Stem Borer using available traps. The method involves training data from a direct dataset obtained from the field, categorized into two positive and negative classes of the White Stem Borer pests. Six models have been trained from this dataset, utilizing two different architectures. Out of the six trained models, four showed potential overfitting, one exhibited underfitting, and one model demonstrated optimal results. The highest accuracy in image detection achieved by the most optimal CNN model was 97.35%, with a training accuracy of 98.54%. This best-performing model utilized an architecture with three Convolution layers, 50 Epochs, and an automatic data split with an 80:20 training-validation data ratio. From the research findings, it is concluded that this study can assist in automatically analyzing the quantity of White Stem Borer pests in a specific area without directly counting the number of pests from existing traps. However, the study still encounters a limitation—the detection process still requires substantial server resources and cannot be directly processed on the Raspberry PI device installed in the trap. Consequently, the detection relies on transmitting image data from the field device to the server before the detection process can occur.

关键词： White Rice Stem Borer Stem Borer White Stem Borer Detection Pest Detection Convolutional Neural Network (CNN)

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Cancer Prediction Using Clinical and Genomic Data Fusion: A Systematic Review

Cancer Prediction Using Clinical and Genomic Data Fusion: A ...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Kelvin Julian Kuncahyo Setyo Nugroho Rudi Nirwantono Bens Pardamean Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Biotechnology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331539603

ISBN: (纸本)9798331539610

This systematic review provides a comprehensive overview of the methods used to integrate genomic and clinical data in cancer prediction. The review includes 19 studies across various cancers, including breast, colorectal, melanoma, lung, pancreatic, and thyroid. The studies employed different methods to combine genomic and clinical data, including weighted polygenic risk scores, genetic and non-genetic risk scores, and different machine learning algorithms. The results show significant improvements in model prediction performance accuracy across multiple studies. The review highlights the potential benefits of integrating genetic and phenotypic information to improve disease risk prediction models and inform personalized healthcare strategies.

关键词： Accuracy Machine learning algorithms Genomics Data integration Medical services Predictive models Data models Bioinformatics Cancer Systematic literature review

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Dynamic Terrain Data Exchange in a Collaborative Terrain Editor

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Informatica (Slovenia) 2022年第4期46卷 575-582页

作者： Tarigan, Jos Timanta Sitompul, Opim Salim Zarlis, Muhammad Nababan, Erna Budhiarti Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Information Systems Management Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia

In a computer supported cooperative work (CSCW), data consistency between collaborating users is a crucial issue. Based on the type of the application, ensuring data consistency can be a lengthy process that takes time and affects the system’s performance. In most 3D application, terrain data are massive due to its size. Exchanging this data may be expensive and may cause significant delay. In a real-time collaborative terrain editor, this issue becomes more significant due to terrain data exchange is consistently occurred between collaborating users. We present a solution to perform a conflict-free dynamic terrain data exchange in a real-time collaborative terrain editor. Our objective is to develop a method that able to ensure data consistency amongst collaborating peers in real-time manner. The main idea of our method is to split the terrain into smaller patches and synchronize the changes efficiently by only exchanging the modified patches. We applied our solution to a collaborative terrain editor application to test its performance in a real-time collaborative editing session. The tests were done in multiple scenarios, using different patch model, brush size (in the terrain editor), and connection setup between server and collaborating clients. The result shows that our protocol is capable to maintain data consistency between collaborating clients in a real-time terrain edition session. The delay is varied and highly depends on the data size and client-server environment setup. The overall test shows that it is possible to perform a collaborative terrain editing with an acceptable response time delay. In this paper, we present our proposed method, the implementation, and the result data from the test. © 2022 Slovene Society Informatika. All rights reserved.

关键词： Electronic data interchange

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Investigating the Impact of Data Augmentation for Fine-Grained Grocery Product Classification Based on Vision Transformer

Investigating the Impact of Data Augmentation for Fine-Grain...

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2023 International Conference on Artificial Intelligence Robotics, Signal and Image Processing, AIRoSIP 2023

作者： Rahmania, Rissa Heryadi, Yaya Lukas, Lukas Suparta, Wayan Sonata, Ilvico Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350327472

The existence of fine-grained image classification supporting smart retail provides effectiveness in recognizing products with high similarity. However, the generic classification method performs poorly in identifying products from a subordinate category. This paper aims to identify augmentation techniques to leverage the Vision Transformer (ViT) model to classify the fine-grained grocery product, which involves embedding patches and transformer encoders to extract the main features. First, we develop a fine-grained image dataset with ColorJitter, CutOut, and combining both augmentations. Secondly, we perform experiments and analysis of ViT size, embedded patch size and image size in the patch embedding process. Lastly, the ViT model are evaluated according to the image sizes 224, 384, and 512 in accuracy, loss, and confusion matrix. The highest accuracy was obtained at 0.9922. The ColorJitter and CutOut improved the confusion matrix in ViT-B/16 and ViT-L/16 with an image size of 384 and 512. The results show that both augmentations in the ViT model are able to distinguish fine-grained grocery products. © 2023 IEEE.

关键词： Embeddings

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Developer-Centric Task Allocation: An Intelligent Approach for Enhanced Software Productivity 15

Developer-Centric Task Allocation: An Intelligent Approach f...

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15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Fensterseifer Filho, Evandro L. R. Assuncao, Joaquim V. C. Fontoura, Lisandra M. Federal University of Santa Maria - Ufsm Graduate Program in Computer Science RS Santa Maria Brazil Federal University of Santa Maria - Ufsm Applied Computing Department RS Santa Maria Brazil

ISBN: (纸本)9798350368833

Software projects are affected by technical knowledge as well as the personality of the team. Such factors can reduce or increase the software quality and development speed. For successful task allocation, it is essential to consider the skills and profile of each developer, thus maximizing their productivity. In projects with large teams, task allocation can be challenging, and the help of tools can facilitate its execution. In this work, we propose an intelligent approach for allocating software development tasks suitable to the profile of developers. From the literature, we define the appropriate skills and technical profiles for a development team, and the assessment is based on the developer completing a questionnaire. We developed a recommendation system to suggest tasks to be allocated to developers, employing text processing techniques. For validation, 495 tasks were used from an actual project developing simulator software for military training. The recommended allocations were evaluated by the project developers and used to improve the system. Validations showed that the developed approach makes consistent and coherent task recommendations to developers according to the developer profile, as participants agree with the recommendation for 76% of tasks. © 2024 IEEE.

关键词： Project management

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Smartphone Application for the Deaf and the Deaf Caring Community 6

Smartphone Application for the Deaf and the Deaf Caring Comm...

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6th International Conference on Inventive Computation Technologies, ICICT 2023

作者： Pryandi, Pinnus Dewantara, Muhammad Bayu Warnars, Harco Leslie Hendric Spits Arief, Ramadhan Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Telkom University Bandung11480 Indonesia

ISBN: (纸本)9798350398496

In life, various challenges and problems faced by deaf people such as communication skills and other problems, including emotional, mental, and societal development. However, technology is needed that can help the process. This Smart Application try to build communication between the deaf to share thoughts in group chats, including getting information about the deaf, so that the communication learning process for the deaf becomes easier. The proposed model is using Unified Modeling Languages (UML) diagrams, such as case diagrams for the current proposed idea process and class diagrams for relational tables or database stores. In addition, the User interface (UI) is implemented in this research work, Personal Home Pages (PHP) as a web server programming and MySQL database as an open-source database. © 2023 IEEE.

关键词： User interfaces

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Real-Time 3D Object Detection, Recognition and Presentation Using a Mobile Device for Assistive Navigation

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SN computer science 2023年第5期4卷 1-18页

作者： Chen, Jin Zhu, Zhigang Visual Computing Laboratory Computer Science Department The City College-CUNY New York 10031 NY United States Nearabl Inc. New York 10023 NY United States PhD Program in Computer Science The Graduate Center-CUNY New York 10016 NY United States

This paper presents an integrated solution for 3D object detection, recognition, and presentation to increase accessibility for various user groups in indoor areas through a mobile application. The system has three major components: a 3D object detection module, an object tracking and update module, and a voice and AR-enhanced interface. The 3D object detection module consists of pre-trained 2D object detectors and 3D bounding box estimation methods to detect the 3D poses and sizes of the objects in each camera frame. This module can easily adapt to various 2D object detectors (e.g., YOLO, SSD, mask RCNN) based on the requested task and requirements of the run time and details for the 3D detection result. It can run on a cloud server or mobile application. The object tracking and update module minimizes the computational power for long-term environment scanning by converting 2D tracking results into 3D results. The voice and AR-enhanced interface integrates ARKit and SiriKit to provide voice interaction and AR visualization to improve information delivery for different user groups. The system can be integrated with existing applications, especially assistive navigation, to increase travel safety for people who are blind or have low vision and improve social interaction for individuals with autism spectrum disorder. In addition, it can potentially be used for 3D reconstruction of the environment for other applications. Our preliminary test results for the object detection evaluation and real-time system performance are provided to validate the proposed system. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： 3D object detection ARKit Assistive technology Blind or low vision Voice assistance

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Exploring Cooperation and Competition in computer science Education: An Investigation Based on Game Theory 17

Exploring Cooperation and Competition in Computer Science Ed...

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17th International Conference on computer Supported Education, CSEDU 2025

作者： Moura, Waldir Siqueira Delbem, Edgar França, Juliana Baptista dos Santos Dias, Angélica Fonseca da Silva Computer Science Graduate Program PPGI Federal University of Rio de Janeiro Térreo Bloco E CCMN/NCE University City Rio de Janeiro68.530 Brazil

ISBN: (纸本)9789897587467

The study investigates the use of the game Overcooked as a pedagogical tool in primary education, focusing on cooperation and competition. The research, conducted throughout 2022, analyzed one semester as a baseline and another with pedagogical interventions. Four groups were studied: control (no interventions), game without instructions, game with teamwork guidance, and game without verbal communication. Questionnaires and qualitative/quantitative data assessed engagement, motivation, and cooperation. The interventions significantly improved performance, motivation, and skills such as teamwork and problem-solving, validating gamification as an educational resource. Copyright © 2025 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Teaching

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