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Dynamic extended sigmoid-based scheduling with virtualized RB allocation for maximizing frequency numerology efficiency in 5G/B5G NR networks

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computer Networks 2023年 237卷

作者： Chang, Wei-Teng Chang, Ben-Jye Graduate School of Engineering Science and Technology National Yunlin University of Science and Technology Taiwan Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Taiwan

New trends of extremely ultra-low delay, ultra-high reliability, long-distance high-moving, etc., are strongly required for achieving Emergency resecure, Active Safe Driving (ASD), IoV communications, LEO communications, etc. Thus, 3GPP 5 G/B5G specifies flexible numerology technology providing different frequency SCS modes with different slot-times for diverse types of flows requiring different 5QIs in terms of delay, data rate, jitter, loss probability, and reliability. Although based on the frequency numerology, 3GPP Release 17 specifies three types of RB allocations, i.e., Types 0, 1, and dynamic switching allocations for UL access, such static and consecutive RB allocations result in inefficient numerology and frequency spectrum efficiency. As a result, typical critical issues exhibit in B5G NR, including high mutual exclusion (MX) of numerology, RB state independency flow scheduling, and static RB allocations suffering from dynamic flowing traffic. Thus, this paper proposes the Extended Sigmoid-based Scheduling with a Virtualized RB Allocation (SSA) consisting of two phases. Phase 1 proposes an Extended Sigmoid-based Cost-based Flow Scheduling (SCFS) algorithm to dynamically differentiate flow priorities. Phase 2 proposes a dynamic Virtualized RB pre-Allocation (VRBA) mechanism to maximize radio RB utilization and minimize mutual exclusion in 5 G frequency numerology. Numerical results indicate that the proposed SSA outperforms the compared approaches in network delay, jitter, resource utilization, network reward, and net-profit. Consequently, this paper achieves several objectives and contributions: 1) analyzing the QoS requirements of different applications with limited frequency spectrum, 2) proposing vRB state-related dynamic flow scheduling algorithm to maximize network efficiency, 3) minimizing numerology MX for vRB allocation, and 4) proposing adaptive cost-reward-based scheduling. © 2023

关键词： Scheduling algorithms

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CRLock: A SAT and FALL Attacks Resistant Logic Locking Method for Controller at Register Transfer Level∗

CRLock: A SAT and FALL Attacks Resistant Logic Locking Metho...

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作者： Yoshimura, Masayoshi Tsujikawa, Atsuya Hosokawa, Toshinori The Information of Computer Science and Engineering Kyoto Sangyo University Kyoto-shi603-8555 Japan The Graduate School of Industrial Technology Nihon University Narashino-shi275-8575 Japan The College of Industrial Technology Nihon University Narashino-shi275-8575 Japan

In recent years, to meet strict time-to-market constraints, it has become difficult for only one semiconductor design company to design a VLSI. Thus, design companies purchase IP cores from third-party IP vendors and design only the necessary parts. On the other hand, since IP cores have the disadvantage that copyright infringement can be easily performed, logic locking has to be applied to them. Functional logic locking methods using TTLock are resilient to SAT attacks however vulnerable to FALL attacks. Additionally, it is difficult to design logic locking based on TTLock at the gate level. This paper proposes a logic locking method, CRLock, based on SAT attack and FALL attack resistance at the register transfer level. The CRLock is a logic locking method for controllers at RTL in which the designer selects a protected input pattern and modifies the controller based on the protection input pattern. In experimental results, we applied CRLock to MCNC’91 benchmark circuits and showed that all circuits are resistant to SAT and FALL attacks. Copyright © 2024 The Institute of Electronics, information and Communication Engineers.

关键词： Controllers

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A Comparison of Keras Application Models with Pre-Trained Weights in Predicting the Disease of Lanzones Leaf 14

A Comparison of Keras Application Models with Pre-Trained We...

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14th IEEE International Conference on Humanoid, Nanotechnology, information Technology, Communication and Control, Environment, and Management, HNICEM 2022

作者： Muhali, Adzmer Linsangan, Noel Graduate School Mapua University Intramuros Manila Philippines Department of Computer Science Information Technology and Engineering Sulu State College Sulu Jolo Philippines School of Electrical Electronics and Computer Engineering Mapua University Intramuros Manila Philippines

ISBN: (纸本)9781665464932

Much research has already been done to detect diseases on plant leaves using different architectures of the Tensorflow Keras Application. Despite this, no existing or ongoing research on the disease on Lanzone's leaf has been conducted. Lanzones also provide essential health benefits to people and the market demands. This study helps researchers choose the Keras Application's exemplary architecture for detecting the disease on Lanzones Leaf. Hence this study compares four (4) architectures of Keras Application that provide impressive results in other plant disease classification such as VGG16, VGG19, ResNet101, and ResNet152V2 to determine the best model for detecting the Lanzones Leaf disease. In this study, the models saw the healthy leaf and diseases such as Algal Leaf Spot and Leaf Blight Spot of Lanzones Tree. The methods used pre-processing and augmentation on the collected dataset, as well as training the models for more epochs, to improve the models' performance and learning process. The analysis and evaluation results show that VGG16 is the best model among those models utilized in detecting diseases of lanzones leaves;hence, the VGG16 achieved 89.09% of overall accuracy. © 2022 IEEE.

关键词： Plants (botany)

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Where Do You Go? Pedestrian Trajectory Prediction using Scene Features

arXiv

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arXiv 2025年

作者： Rezaei, Mohammad Ali Ayar, Fardin Javanmardi, Ehsan Tsukada, Manabu Javanmardi, Mahdi Department of Computer Engineering Amirkabir University of Technology Tehran Iran Graduate School of Information Science and Technology The University of Tokyo Tokyo Japan

Accurate prediction of pedestrian trajectories is crucial for enhancing the safety of autonomous vehicles and reducing traffic fatalities involving pedestrians. While numerous studies have focused on modeling interactions among pedestrians to forecast their movements, the influence of environmental factors and scene-object placements has been comparatively underexplored. In this paper, we present a novel trajectory prediction model that integrates both pedestrian interactions and environmental context to improve prediction accuracy. Our approach captures spatial and temporal interactions among pedestrians within a sparse graph framework. To account for pedestrian-scene interactions, we employ advanced image enhancement and semantic segmentation techniques to extract detailed scene features. These scene and interaction features are then fused through a cross-attention mechanism, enabling the model to prioritize relevant environmental factors that influence pedestrian movements. Finally, a temporal convolutional network processes the fused features to predict future pedestrian trajectories. Experimental results demonstrate that our method significantly outperforms existing state-of-the-art approaches, achieving ADE and FDE values of 0.252 and 0.372 meters, respectively, underscoring the importance of incorporating both social interactions and environmental context in pedestrian trajectory prediction. © 2025, CC BY.

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Linkedin's Influence on User Success in The Professional World 9

Linkedin's Influence on User Success in The Professional Wor...

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9th International Conference on ICT for Smart Society, ICISS 2022

作者： Oktavia, Tanty Roekman, Faza Fakhriansyah Putera, Muhammad Ikhsan Hidayah, Muhammad Alif Rafi, Muhammad Hosoda, Takaaki Gaol, Ford Lumban BINUS Graduate Program Information System Management Bina Nusantara University Information System Management Department Jakarta Indonesia School of Information Systems Bina Nusantara University Information System Department Jakarta Indonesia Advanced Institute of Industrial Technology Decision Science Department Tokyo Japan BINUS Graduate Program Bina Nusantara University Computer Science Department Jakarta Indonesia

ISBN: (数字)9781665471350

ISBN: (纸本)9781665471350

Social media has now become a place for others to exchange information in the form of writing, photos, videos, and audio. Social media has become a place for humans to interact from all over the world. In the use of social media, attractive professional information is conceptualized as access to relevant information and opening up better career opportunities. User content about work and choosing personal information compilation strategies consistently predict information usefulness. This study discusses the effect of using a linked-in application on the success of its users in the professional world. It is hoped that it can provide insight into the use of this recruitment application, making it easier for users to find work. The research model used in this research is quantitative. The survey was conducted on connected users in Indonesia using an online questionnaire, and the data collected was analyzed using PLS-SEM. Of the 68 respondents who took the survey, it can be said that all research models have a positive relationship with the successful use of the linked-in platform. © 2022 IEEE.

关键词： Surveys

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Hotel information System Management Audit Using COBIT 2019 - APO12

Hotel Information System Management Audit Using COBIT 2019 -...

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Innovation in Technology (INOCON), IEEE International Conference for

作者： Joy Nashar Utamajaya Suhono Harso Supangat Ford Lumban Gaol Benny Ranti BINUS Graduate Program School of Information System BINUS University Jakarta Indonesia School of Electrical Engineering and Informatic Bandung Institute of Technology Bandung Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Faculty of Computer Science University of Indonesia Depok Indonesia

In general, public or private organizations or companies have used information-based technology as a support to improve business performance to be more effective and efficient in order to achieve a company’s business goals. Given the large contribution of information technology in the application of hotel applications as a supporting information system, it is a vital system that must avoid risks that can hinder and cause harm to the hotel management business processes. Therefore, it is necessary to carry out risk management using the COBIT 5 framework to manage possible risks that may occur based on the APO12 (Manage Risk) domain. From the evaluation results of the data obtained through observation and interviews as well as the calculation of the results of the questionnaire based on 6 APO12 subdomains, the results of the risk management level capability assessment in hotel applications are still at level 3 or have reached the level of established process with the target to be achieved at level 4 resulting in a gap of 1 level. Based on the results obtained, it is necessary to propose recommendations that can be used by hotels in improving the application of information technology risk management so that in the future it can achieve the expected target level so that the APO12 level of capability can increase and become more optimal.

关键词： Technological innovation Companies Risk management information technology Interviews information systems

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Classification of Lanzones Tree Leaf Diseases Using Image Processing Technology and a Convolutional Neural Network (CNN) 4

Classification of Lanzones Tree Leaf Diseases Using Image Pr...

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4th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2022

作者： Muhali, Adzmer S. Linsangan, Noel B. Graduate School Mapua University Intramuros Manila Philippines Information Technology and Engineering Sulu State College Department of Computer Science Sulu Jolo Philippines School of Electrical Electronics and Computer Engineering Mapua University Intramuros Manila Philippines

ISBN: (数字)9781665468374

ISBN: (纸本)9781665468374

Nowadays, many artificial intelligence systems are developed to detect and classify plant leaf diseases via image classification, and those researches achieved high-performance results. However, those Artificial Intelligence Systems categorize various leaf diseases, but none precisely for Lanzones. Briefly, no existing or current research has been studied to detect and classify leaf diseases of Lanzones tree in the early stages using an Artificial Intelligence System. This paper presents a device for categorizing the healthy and with diseases (Algal Leaf Spot and Leaf Blight Spot) on the leaves of the Lanzones tree thru image classification using deep learning. It is limited to the device's development and implementation in the target locale. The methods applied include data pre-processing and augmentation techniques to the created CNN model. This will be integrated into a system using the Raspberry Pi 4 Model B and the Tensorflow Lite Interpreter. The performance analysis and evaluation of the system were based on the confusion matrix, which shows how the system successfully classified the healthy and disease of Lanzones leaves with an accuracy rate of 80%. © 2022 IEEE.

关键词： Neural network models

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A Verification Framework Based on EDA Algorithms for E-book Design by Visual programming Language

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IEEE Software 2025年

作者： Koong, Chorng-Shiuh Hsieh, Tung-Li Wu, Chao-Chin Guo, Cheng-Yan National Taichung University of Education Department of Computer Science and Information Engineering Taichung City403514 Taiwan National Kaohsiung University of Science and Technology Department of Electronic Engineering Kaohsiung City807618 Taiwan National Changhua University of Education Department of Computer Science and Information Engineering Changhua50007 Taiwan National Taiwan University Graduate Institute of Electronics Engineering The Graduate School of Advanced Technology Taipei106319 Taiwan

Creating an interactive electronic book (e-book) requires substantial time, skill, and effort. Our study reveals that authoring tools must eliminate users' need for textual programming. We propose a novel interactive e-book design method that uses multimedia reusable components (MRCs) and an e-book description language (EBDL) to implement e-book authoring tools like a circuit design concept. Interactive ebooks can be designed intuitively using MRCs and EBDL without text-based programming, which differs from static syntax analysis of text-based programming languages. The designs using MRCs and EBDL can be verified and tested using the Boolean satisfiability of the electronic design automation algorithm. Notably, verification and debugging are challenging in current visual programming languages. Therefore, our research provides e-book designers reduce the technical requirements of e-book design. The findings can also ensure visual programming languages' consistent behavior and design while detecting design errors. © 1984-2012 IEEE.

关键词： Visual languages

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Electrically tunable planar liquid-crystal singlets for simultaneous spectrometry and imaging

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Light(science & Applications) 2024年第11期13卷 2589-2598页

作者： Zhou Zhou Yiheng Zhang Yingxin Xie Tian Huang Zile Li Peng Chen Yan-qing Lu Shaohua Yu Shuang Zhang Guoxing Zheng Electronic Information School and School of MicroelectronicsWuhan UniversityWuhan 430072China NUS Graduate School National University of SingaporeSingapore 119077Singapore Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore National Laboratory of Solid State Microstructures Key Laboratory of Intelligent Optical Sensing and Manipulationand College of Engineering and Applied SciencesNanjing UniversityNanjing 210093China Peng Cheng Laboratory Shenzhen 518055China New Cornerstone Science Laboratory Department of PhysicsUniversity of Hong KongHong KongChina Department of Electrical and Electronic Engineering University of Hong KongHong KongChina Wuhan Institute of Quantum Technology Wuhan 430206China

Conventional hyperspectral cameras cascade lenses and spectrometers to acquire the spectral datacube,which forms the fundamental framework for hyperspectral ***,this cascading framework involves tradeoffs among spectral and imaging performances when the system is driven toward ***,we propose a spectral singlet lens that unifies optical imaging and computational spectrometry functions,enabling the creation of minimalist,miniaturized and high-performance hyperspectral *** a paradigm,we capitalize on planar liquid crystal optics to implement the proposed framework,with each liquid-crystal unit cell acting as both phase modulator and electrically tunable spectral *** with various targets show that the resulting millimeter-scale hyperspectral camera exhibits both high spectral fidelity(>95%)and high spatial resolutions(~1.7 times the diffraction limit).The proposed“two-in-one”framework can resolve the conflicts between spectral and imaging resolutions,which paves a practical pathway for advancing hyperspectral imaging systems toward miniaturization and portable applications.

关键词： crystal planar singlet

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Development of Detection Lung Disease Stand Alone System Based on Convolutional Neural Network (CNN)

Development of Detection Lung Disease Stand Alone System Bas...

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International Conference of computer and Informatics engineering (IC2IE)

作者： Edgar Caesar Liewarnata Yosica Mariana Sofyan Tan Suryadiputra Liawatimena Winda Astuti Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Product Design Program Industrial Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331505530

ISBN: (纸本)9798331505547

Lung disease, especially Tuberculosis (TBC), placed the highest death rate in Indonesia. Tuberculosis (TB) in Indonesia is ranked second after India. Therefore, it is important to reduce or early detection of the lung disease, to prevent this disease and speed up handling. The system can recognize the disease lung identification, and the system applied as standalone system. In this work, the Convolutional Neural Network (CNN) approach for identifying diseases lung identification is proposed. The Mel Frequency Cepstral Coefficient (MFCC) applied to process the stethoscope sounds which will used as input to the CNN. The performance of the proposed system has been investigated and resulted. The accuracy of 99% and 98%, for training and testing accuracy respectively. Furthermore, the system accurately detects lung diseases identification.

关键词： Training Accuracy Tuberculosis Pulmonary diseases Lungs Stethoscope Recording Convolutional neural networks Mel frequency cepstral coefficient Testing

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