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Developing an online information portal for enhancing society awareness of RPTRA (A case study RPTRA MAYA ASRI 13)

Procedia computer science 2023年 216卷 144-150页

作者： Yulyani Arifin Elizabeth Paskahlia Gunawan Margaretha Ohyver Computer Science Departement BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia. Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia. Statistics Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia.

The long COVID-19 pandemic has limited the activities of Ruang Publik Terpadu Ramah Anak (RPTRA) such as environment cleaning, repair of RPTRA infrastructure, learning and others, as well as the lack of public awareness about the existence and importance of RPTRA to the public and foreign tourists encouraging the RPTRA to make changes in the dissemination of information about the activities carried out in the RPTRA through the use of technology to survive and grow even during the Covid-19 Pandemic. The methodology used in this research is Group Discussion Forum with the administrators of the RPTRA Maya ASRI 13 to learn about the needs and expectations of the RPTRA administrators regarding the web portal to be built. Then, the implementation of the conceptual model, development, and evaluation of the effectiveness of the RPTRA information web portal was carried out. The contribution in this research is to implement a conceptual model on the information portal built on the platform of the Website with the PHP framework, which is then evaluated on the results of the pre-test and post-test about RPTRA the Wilcoxon-Signed Rank Test to test the effectiveness of the information web portal for general users. The results obtained from these tests indicate that the RPTRA Information Web Portal can help the public learn more about the existence of RPTRA Maya Asri 13.

关键词： PHP RPTRA The Covid-19 Pandemic Web Portal Web technology

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Towards full-dimensional positioning by leveraging Intelligent Omni-Surface 4

Towards full-dimensional positioning by leveraging Intellige...

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4th International Conference on Internet of Things and Smart City, IoTSC 2024

作者： Zhou, Jiaqi Yang, Ziang Zeng, Shuhao Cheng, Xiang Cui, Bin Bian, Kaigui Xu, Chenren Weng, Xi Song, Lingyang Hunan Institute of Advanced Sensing and Information Technology Xiangtan University Xiangtan China Department of Electronics Peking University Beijing China School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen China School of Computer Science Peking University Beijing China Guanghua School of Management Peking University Beijing China

ISBN: (纸本)9781510681767

Reconfigurable intelligent surface (RIS)-assisted received signal strength (RSS) positioning technology has attracted widespread attention due to its low deployment cost and ability to customize the wireless environment. Through regulating the RIS's electromagnetic responses, the transmission channels are altered to amplify the differences in RSS values between neighbouring locations, thereby enhancing the accuracy of positioning. However, existing works only consider reflective RIS, and thus can only improve the positioning accuracy of users on a single face of the surface. To offer positioning services to users on either sides of the surfaces, we propose to utilize Intelligent Omni-Surface (IOS), a special kind of RIS that is capable of reflecting and refracting incoming signals concurrently, to assist the RSS-based positioning. Specifically, by modulating the RSS distribution on the two sides of the IOS through adjusting the reflection and refraction phase shifts induced by the surface, positioning accuracy for individuals on either sides of the surface can undergo effective improvements, so as to realize full-dimensional localization. However, since the reflection and refraction phase shifts of the IOS are coupled, it is challenging to jointly optimize them so as to minimize the positioning error. To address this challenge, within this letter, we investigated an IOS-aided full-dimensional localization system based on RSS, in which IOS is placed in the centre of the room to adjust the RSS distribution of users on both sides, and designed an IOS-aided localization protocol to coordinate IOS and users. Based on this protocol, we formulate a phase shift optimization problem to reduce users' positioning error, and develop a phase shift optimization algorithm based on gradient descent for iteratively to solve it. Simulation results confirm the efficiency of the suggested IOS-aided positioning method. © 2024 SPIE.

关键词： Refraction

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3D Transfer Learning for Lung Nodule Malignancy Binary Classification

3D Transfer Learning for Lung Nodule Malignancy Binary Class...

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computer sciences, Engineering, and technology Innovation (ICoCSETI), International Conference on

作者： Nur Adhianti Heryanto Mahmud Isnan Matthew Martianus Henry Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331508616

ISBN: (纸本)9798331508623

Many studies have focused on classifying lung nodules in CT scans, primarily utilizing 2D approaches. However, CT scans are inherently 3D representations, which presents challenges for traditional convolutional neural networks (CNNs) designed for 2D images. In this work, a novel combination of 3D transfer learning and batch oversampling was adopted to classify benign and malignant lung nodules using the Lung Nodule Analysis - Intelligent Systems in Medical Imaging (LUNA22-ISMI) dataset. The preprocessing pipeline consisted of excluding indeterminate labeled nodules, clamping patches to the lung window, extracting nodule regions based on diameter, and applying z-score normalization. Batch oversampling with augmentation was implemented for the training set. Multiple models pre-trained on ImageNet with weights adapted for 3D were evaluated using a five-fold cross-validation setup. Notably, EfficientNetB1 achieved the highest overall and balanced metrics on the test sets, surpassing 90% in sensitivity, specificity, precision, and accuracy, highlighting its potential for binary classification of lung nodules. https://***/nheryanto/luna22

关键词： Training Solid modeling Adaptation models Three-dimensional displays Lungs Computed tomography Transfer learning Windows Cancer Biomedical imaging

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Retinal Arteries and Veins Semantic Segmentation Using Modified U-Net Architecture

Retinal Arteries and Veins Semantic Segmentation Using Modif...

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Future Machine Learning and Data science (FMLDS), IEEE International Conference on

作者： Heidi Ahmed Holiel Aya El-Beheiry Essam A. Rashed School of Information Technology and Computer Science Nile University Giza Egypt Graduate School of Information Science University of Hyogo Kobe Japan

ISBN: (数字)9798350391213

ISBN: (纸本)9798350391220

This paper presents a modified U-Net architecture designed for the semantic segmentation of retinal arteries and veins using infrared reflectance retinal imaging. Leveraging the RAVIR dataset, which comprises 46 high-quality retinal images, we focus on addressing the challenges of low contrast and varying lighting conditions often found in retinal images. Our approach incorporates advanced features such as bilinear interpolation and attention mechanisms to enhance segmentation accuracy. The modified U-Net architecture achieves a mean Intersection over Union (mIoU) of 0.8855 and a Dice coefficient of 0.9382, showing a significant improvement over the traditional U-Net. These results demonstrate its potential for practical applications in retinal disease diagnosis and monitoring.

关键词： Reflectivity Interpolation Accuracy Attention mechanisms Veins Semantic segmentation Transfer learning computer architecture Retina Arteries

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Rethinking MedSAM: Performance Discrepancies in Clinical Applications

Rethinking MedSAM: Performance Discrepancies in Clinical App...

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Future Machine Learning and Data science (FMLDS), IEEE International Conference on

作者： Muhammad Nouman Ghada Khoriba Essam A. Rashed Graduate School of Information Science University of Hyogo Kobe Japan School of Information Technology and Computer Science Nile University Giza Egypt

ISBN: (数字)9798350391213

ISBN: (纸本)9798350391220

Segment Anything Model (SAM) has gained significant attention for its versatility and effectiveness in solving various image segmentation problems. Medical image segmentation (MIS) is a complicated problem compared to natural image segmentation, considering the variability in imaging modalities, applications, and clinical requirements. We conduct an evaluation study to validate the usage of MedSAM as a foundation model for the segmentation of medical images, examining its performance in both zero-shot and fine-tuned settings. This paper critically evaluates MedSAM's performance across diverse clinical applications, highlighting performance gaps that question its generalization ability in MIS. Experiments on multiple datasets, including MRI, CT, ultrasound, endoscopy, and retinal fundus images, have shown that MedSAM struggles with complex anatomical structures. Furthermore, the results show that it is sensitive to the bounding box accuracy. These findings suggest that its current implementation lacks the robustness necessary for widespread adoption in clinical practice without fine-tuning. This paper discusses these limitations and proposes strategies for enhancing the MedSAM to address the complexities of MIS.

关键词： Training Image segmentation Weak supervision Ultrasonic imaging Foundation models Zero shot learning Data models Robustness Complexity theory Biomedical imaging

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Formal Verification of Authenticated Encryption with Associated Data with Tamarin Prover

Formal Verification of Authenticated Encryption with Associa...

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2023 Congress in computer science, computer Engineering, and Applied Computing, CSCE 2023

作者： Mieno, Takehiko Okazaki, Hiroyuki Arai, Kenichi Futa, Yuichi Graduate School of Medicine Science and Technology Shinshu University Epson Avasys Corporation 1077-5 Shimonogo Otsu Nagano Ueda City386-1214 Japan Graduate School of Science and Technology Shinshu University 4-17-1 Wakasato Nagano Nagano City380-8553 Japan Graduate School of Engineering Nagasaki University 1-14 Bunkyo-machi Nagasaki City852-8521 Japan School of Computer Science Tokyo University of Technology 1404-1 Katakura machi Hachioji City192-0982 Japan

ISBN: (纸本)9798350327595

Tamarin Prover and ProVerif are automated tools for formally verifying the security of cryptographic protocols. Tamarin Prover is a type of theorem prover, whereas ProVerif is a type of symbolic model checker. In this paper, we formalized the structure of authenticated encryption with associated data (AEAD). To do so, we formalized AEAD as two types of generic compositions, using the Encrypt-then-Message Authentication Code (MAC) and MAC-then-Encrypt constructions presented by Rogaway et al. Using Tamarin Prover, we verified the confidentiality and integrity independent of considering the attacker's capabilities. We demonstrated that the attacker's abilities can be modeled in ProVerif, and we compared our findings with results obtained via ProVerif. We found that ProVerif is superior to Tamarin Prover in the studied scenarios, although future work is needed to consider attacker's abilities. © 2023 IEEE.

关键词： AEAD Cryptographic protocol Formal method MAC ProVerif Tamarin Prover

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Towards Trajectory Planning of a Robot Manipulator with computer Algebra using Bézier Curves for Obstacle Avoidance 10

Towards Trajectory Planning of a Robot Manipulator with Comp...

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10th International Symposium on Symbolic Computation in Software science - Work in Progress Workshop, SCSS 2024 WiP

作者： Hatakeyama, Ryo Terui, Akira Mikawa, Masahiko Master's Program in Mathematics Graduate School of Science and Technology University of Tsukuba Tsukuba305-8571 Japan Institute of Pure and Applied Sciences University of Tsukuba Tsukuba305-8571 Japan Institute of Library Information and Media Science University of Tsukuba Tsukuba305-8550 Japan

This paper discusses the trajectory planning of a robot manipulator with computer algebra. In the operation of robot manipulators, it is important to make the trajectory of the end effector so that it does not collide with obstacles. For this purpose, we have proposed a method of generating a method of trajectory planning using cubic spline curves. However, the method has the disadvantage that the trajectory may not be included in the feasible region of the manipulator, thus an extra test for the inclusion of the curve is needed. In this paper, we propose a new method of generating a trajectory using Bézier curves, which is guaranteed to be included in the feasible region. © 2024 CEUR-WS. All rights reserved.

关键词： Trajectories

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Solving Estimation Problems Using Minimax Polynomials and Gröbner Bases 10

Solving Estimation Problems Using Minimax Polynomials and Gr...

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10th International Symposium on Symbolic Computation in Software science - Work in Progress Workshop, SCSS 2024 WiP

作者： Kuramochi, Kenta Terui, Akira Mikawa, Masahiko Master's Program in Mathematics Graduate School of Science and Technology University of Tsukuba Tsukuba305-8571 Japan Institute of Pure and Applied Sciences University of Tsukuba Tsukuba305-8571 Japan Institute of Library Information and Media Science University of Tsukuba Tsukuba305-8550 Japan

We propose a method for solving the speech direction estimation problem by computer algebra. The method is based on the function approximation using the minimax polynomial. The minimax polynomial is obtained by an iterative method called the Remez exchange algorithm, in which Gröbner bases computation is employed. We present an effective way to compute the minimax polynomial using Gröbner bases. © 2024 CEUR-WS. All rights reserved.

关键词： Iterative methods

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High-Performance Face Identification using Hyperspectral Imaging to Counteract Deep Fake Biometrics

High-Performance Face Identification using Hyperspectral Ima...

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IEEE International Conference on Robotic Computing (IRC)

作者： Sota Furusawa Chinthaka Premachandra Dept. of Electrical Engineering and Computer Science Graduate School of Engineering and Science Shibaura Institute of Technology Tokyo Japan

ISBN: (数字)9798331521554

ISBN: (纸本)9798331521561

This research addresses the security challenges posed by Generative Adversarial Networks (GANs) in biometric authentication, focusing particularly on the use of Hyperspectral Imaging (HSI) to counteract the threat of deep fake biometrics created by GANs. We sought solutions to the issues identified in a previous study, such as the inability to handle images of individuals not previously trained and the high time consumption required for identification. In this paper, we first reduced the dimensionality of hyperspectral face data used for training, and then conducted a binary classification of “target subject (class)” and “nontarget subjects (classes).” A discriminator, based on the Least Squares Generative Adversarial Network (LSGAN) model, was developed using HSI for each class for binary classification. The proposed method significantly reduced identification time and achieved very high accuracy in identification.

关键词： Training Deepfakes Face recognition Biological system modeling Focusing Generative adversarial networks Security Robots Hyperspectral imaging Principal component analysis

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Comments on "An Efficient and Provably Secure Authenticated Key Agreement Protocol for Fog-Based Vehicular Ad-Hoc Networks" 6

Comments on "An Efficient and Provably Secure Authenticated ...

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6th IEEE International Conference on Electronics and Communication Engineering, ICECE 2023

作者： Awais, Syed Muhammad Yucheng, Wu Mahmood, Khalid Kharel, Rupak Chongqing University School of Microelectronics and Communication Engineering Chongqing China University of Central Lancashire National Yunlin University of Science and Technology Preston United Kingdom School of Psychology and Computer Science Graduate School of Intelligent Data Science Yunlin64002 Taiwan University of Central Lancashire Ton Duc Thang University Preston United Kingdom School of Psychology and Computer Science Faculty of Electrical and Electronics Engineering Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350328721

Vehicle ad-hoc networks (VANETs) have experienced rapid growth due to the advancement of cloud computing, IoT technologies, and intelligent transportation systems (ITS). Vehicles are required to have enhanced storage capacity, onboard computing capabilities, improved sensing power, and communication systems. To address real-world demands like low latency, affordable storage, and mobility in VANET deployments, There have been efforts to integrate fog computing with VANETs in a practical implementation. "An Efficient and Provably Secure Authenticated Key Agreement Protocol for Fog-Based Vehicular Ad-Hoc Networks"was proposed by Ma et al. (IEEE Internet of Things Journal, pp 8065-8075, 10.1109/JIOT.2019.2902840). According to their claims, the use of their secure authentication technique can help prevent security threats. However, after careful investigation, we discovered that their authentication protocol is susceptible to vehicle user impersonation attacks and also does not provide vehicle anonymity. In light of this, we have provided some recommendations to address the current flaws in the protocol developed by Ma et al. © 2023 IEEE.

关键词： Vehicular ad hoc networks

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