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EXPLORING INFLUENTIAL FACTORS IN KNOWLEDGE SHARING WITHIN INDONESIAN PRISONS 22

EXPLORING INFLUENTIAL FACTORS IN KNOWLEDGE SHARING WITHIN IN...

22nd International Conference on e-Society 2024, ES 2024 and 20th International Conference on Mobile Learning 2024, ML 2024

作者： Imandeka, Ejo Hidayanto, Achmad Nizar Suhartanto, Heru Pidanic, Jan Department of Computer Science Faculty of Computer Science University of Indonesia Depok Indonesia Department of Electrical Engineering Faculty of Electrical Engineering and Informatics Pardubice University Pardubice Czech Republic

The exchange of knowledge is widely recognized as a crucial aspect of effective knowledge management. When it comes to sharing knowledge within Prison settings, things get complicated due to various challenges such as limited resources, social stigma, isolation, communication barriers, and security concerns. Additionally, there's a scarcity of resources dedicated to promoting knowledge sharing in secure environments. This study aims to dig deep into the key factors that influence how knowledge is shared in Indonesian prisons. To navigate this intricate terrain, the study uses questionnaires distributed among Prison officers to understand the complex relationship between the identified critical factors and knowledge sharing in Prison. Leadership support, organizational culture, organizational structure, incentives, and individual beliefs emerge as pivotal elements in knowledge sharing. It's also noted that the connection between these critical factors and the intention to share knowledge is significantly influenced by organizational structure. Recognizing and addressing critical factors in knowledge sharing within prisons not only improves rehabilitation within prison walls but also transforms the broader criminal justice system. This approach fosters evidence-based practices, better communication, and a comprehensive understanding of factors leading to successful rehabilitation and reduced recidivism, ultimately creating a more just and effective system. © 2024 International Conferences e-Society 2024 and Mobile Learning 2024. All rights reserved.

关键词： Critical Factors Indonesia Knowledge Knowledge Sharing Prison

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Surface Functionalized Plasmonic Sensors for Uric Acid Detection With Gold-Graphene Stacked Nanocomposites

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Photonic Sensors 2025年第1期15卷 122-137页

作者： Olabisi Abdullahi ONIFADE Dinie Dayana MOHAMAD AZRI Muhammad Hafiz ABU BAKAR Mohammed Thamer ALRESHEEDI Eng Khoon NG Mohd Adzir MAHDI Ahmad Shukri MUHAMMAD NOOR Department of Computer and Communication Systems Engineering Faculty of EngineeringUniversiti Putra MalaysiaSerdang 43400Malaysia Wireless and Photonics Research Centre of Excellence Faculty of EngineeringUniversiti Putra MalaysiaSerdang43400Malaysia Department of Electrical Engineering College of EngineeringKing Saud UniversityRiyadh 11421Kingdom of SaudiArabia Department of Engineering University of CambridgeCambridge CB30FAThe United Kingdom Institute of Nanoscience and Nanotechnology(ION2) Universiti Putra MalaysiaSerdang 43400Malaysia

This study presented a surface-functionalized sensor probe using 3-aminopropyltriethoxysilane(APTES)self-assembled monolayers on a Kretschmann-configured plasmonic *** probe featured stacked nanocomposites of gold(via sputtering)and graphene quantum dots(GQD,via spin-coating)for highly sensitive and accurate uric acid(UA)detection within the physiological *** encompassed the field emission scanning electron microscopy for detailed imaging,energy-dispersive X-ray spectroscopy for elemental analysis,and Fourier transform infrared spectroscopy for molecular *** functionalization increased sensor sensitivity by 60.64%,achieving 0.0221°/(mg/dL)for the gold-GQD probe and 0.0355°/(mg/dL)for the gold-APTES-GQD probe,with linear correlation coefficients of 0.8249 and 0.8509,*** highest sensitivity was 0.0706°/(mg/dL),with a linear correlation coefficient of 0.993 and a low limit of detection of 0.2 mg/***,binding affinity increased dramatically,with the Langmuir constants of 14.29μM^(-1)for the gold-GQD probe and 0.0001μM^(-1)for the gold-APTES-GQD probe,representing a 142900-fold *** probe demonstrated notable reproducibility and repeatability with relative standard deviations of 0.166%and 0.013%,respectively,and exceptional temporal stability of 99.66%.These findings represented a transformative leap in plasmonic UA sensors,characterized by enhanced precision,reliability,sensitivity,and increased surface binding capacity,synergistically fostering unprecedented practicality.

关键词： Plasmon nanocomposite gold-graphene quantum dot uric acid,functionalize sensor

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Design and Implementation of a Slant Polarized Wideband Vivaldi Antenna Array Feed for Monopulse Radar Reflectors

Design and Implementation of a Slant Polarized Wideband Viva...

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2025 IEEE Radio and Wireless Symposium, RWS 2025

作者： Masoumi, Reza Kazemi, Robab Fathy, Aly E. University of Tabriz Faculty of Electrical and Computer Engineering Tabriz Iran University of Tennessee Department of Electrical Engineering and Computer Science KnoxvilleTN United States

ISBN: (纸本)9798350377743

Traditionally, conical ridge horn antennas are used for feeding large reflectors, but they can cause grating lobes in arrays. This paper introduces a compact Vivaldi antenna for monopulse radar, featuring a planar feed structure that offers a wider bandwidth and simplifies manufacturing. The innovative design of the Vivaldi antenna incorporates strategically placed grooves and a circular dielectric lens to enhance gain and reduce sidelobe levels. Operating from 6 GHz to 18 GHz with proper impedance matching, the antenna is 23 mm wide (0.9λ at 12 GHz), making it over 66% smaller than traditional designs. The antennas are angled in 2 × 2 array configuration to overlap, with a center-to-center spacing of 11.3 mm (0.68λ at 18 GHz), ensuring that no grating lobes are present across the entire bandwidth. This innovative antenna effectively feeds an elliptical reflector, providing high gain, broadband capabilities, and significant null depth, ensuring accurate and efficient performance in monopulse radar applications. © 2025 IEEE.

关键词： Monopulse radar

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Implementation of 5G Network Slicing Using Open Source Software 12

Implementation of 5G Network Slicing Using Open Source Softw...

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12th International electrical engineering Congress, iEECON 2024

作者： Vanichchanunt, Pisit Ritruechai, Onpimon Wuttiananchai, Navy Thossaporn, Peeraporn Wuttisittikulkij, Lunchakorn Paripurana, Sukritta King Mongkut's University Of Technology North Bangkok Faculty Of Engineering Department Of Electrical And Computer Engineering Bangkok Thailand Chulalongkorn University Faculty Of Engineering Department Of Electrical Engineering Bangkok Thailand

ISBN: (纸本)9798350383591

In modern communications, network slicing is essen-tial network operation for creating and managing an independent logical network which meets the requirement of a service. Net-work slicing enables available network resources to be managed and allocated efficiently and dynamically according to varying demands of users. This paper aims to design and implement 5G network slicing using open source software in order to serve very low latency services. The implementation requires the integration of orchestration, network function virtualization, and software defined network technologies to deploy necessary network functions and to manage the life cycles of network slices. Open source software tools such as Open5GS, Open Source MANO, OpenStack, OpenDaylight, and srsRAN are selected for implementing 5G core, orchestration and management functions, cloud computing platform, software defined network, and radio access network respectively since they offer compatibility in the software integration as well as allow the prototype to be created in a timely and economical manner. To obtain very low latency, User Plane Function and edge computing are implemented based on the latency of internal connections. In the experiment, different scenarios of network slices are deployed and tested to measure the key performance indices such as a delay, download speed and upload speed. The results show that the implemented network slices can offer very low latency at the expense of available bandwidth reduction due to the communication for orchestration and management in the hardware. However, this can be improved by using hardware with higher performance. © 2024 IEEE.

关键词： Network function virtualization

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Development of a deep wavelet pyramid scene parsing semantic segmentation network for scene perception in indoor environments

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Journal of Ambient Intelligence and Humanized Computing 2023年第9期14卷 12673-12695页

作者： Aslan, Simge Nur Uçar, Ayşegül Güzeliş, Cüneyt Electronics and Automation Department Vocational School Istanbul Arel University Istanbul34295 Turkey Mechatronics Engineering Department Engineering Faculty Firat University Elazig23119 Turkey Electrical and Engineering Department Engineering Faculty Yaşar University Izmir35100 Turkey

In this paper, a new Deep Wavelet Pyramid Scene Parsing Network (DW-PSPNet) is proposed as an effective combination of Discrete Wavelet Transform (DWT), inception module, the channel and spatial attention modules, and PSPNet. Improved semantic segmentation via the combination, to our best knowledge, is not yet reported in the literature. The paper has two main contributions: (1) a new backbone network into PSPNET introduced by a combination of DWT, inspection modules, and attention mechanisms;(2) a new and improved version of PSPNet base structure. Further, three new modifications are introduced. First, the drop activation function is used to increase validation and test accuracy of the segmentation. Second, a skip connection from the backbone is applied to increase validation and test accuracies by restoring the resolution of feature maps via full utilization of multilevel semantic features. Third, Inverse Wavelet Transform (IWT) and convolution layer are applied to obtain the segmented images without information loss. DW-PSPNet was implemented via our own data generated by using a Robotis-Op3 humanoid robot to detect objects in indoor environments and and benchmark data set. Simulation results show higher performance of the proposed network compared with that of previous successful networks in handling semantic segmentation tasks in indoor environments. Moreover, extensive experiments on the benchmark Ade20K data set were also conducted. DW-PSPNET achieved an mIoU score of 45.97% on the ADE20K validation set, which are new state-of-the-art results. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Discrete wavelet transforms

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Optimizing MR Image Registration for Accurate Brain Volume Measurement in Children with Autism Spectrum Disorder 14

Optimizing MR Image Registration for Accurate Brain Volume M...

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14th International Conference on computer and Knowledge engineering, ICCKE 2024

作者： Sanati, Shiva Saadatmand, Mahdi Department of Computer Engineering Faculty of Engineering Ferdowsi University of Mashhad Mashhad Iran Department of Electrical Engineering Faculty of Engineering Ferdowsi University of Mashhad Mashhad Iran

ISBN: (纸本)9798331511272

Autism Spectrum Disorder (ASD) encompasses a range of neurodevelopmental conditions, underscoring the need for early and accurate diagnosis. This study aims to identify regions of interest (ROIs) in the brain that significantly differ between children with ASD and typically developing subjects (TDS), enabling precise classification. We propose novel MR image registration algorithms using the ICBM152 digital atlas, applying both rigid and non-rigid transformations. The volumes of 116 gray matter regions were measured using the MNI-AAL atlas, aligned with ICBM152, and compared between the two groups. MR images from 26 typically developing and 26 autistic children, aged 5 to 10 years, were obtained from the ABIDE database. Our registration algorithms achieved a cross-correlation coefficient (CCC) of 0.82 for the ASD group, compared to 0.65 with SPM's Powell method. Non-rigid registration further improved the CCC to 0.88 and reduced convergence time by 2.8 times. Significant increases in gray matter volumes were observed in specific brain regions in the ASD group, consistent with the age-specific theory of autism. Finally, our SVM-based classification achieved 92.3% accuracy, with an F1-score of 90.1%, recall of 90.1%, and precision of 89.4%, demonstrating the method’s effectiveness in distinguishing ASD from TDS based on brain features. ©2024 IEEE.

关键词： Magnetic resonance imaging

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Energy Consumption Optimisation for Horticultural Facilities 29

Energy Consumption Optimisation for Horticultural Facilities

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29th IEEE International Conference on Emerging Technologies and Factory automation, ETFA 2024

作者： Zhukovskii, Kirill Ovsiannikova, Polina Jhunjhunwala, Pranay Scarabaggio, Paolo Carli, Raffaele Dotoli, Mariagrazia Vyatkin, Valeriy Luleå Tekniska Universitet Department of Computer Science Computer and Space Engineering Sweden Aalto University Department of Electrical Engineering and Automation Espoo Finland Polytechnic University of Bari Department of Electrical and Information Engineering Bari Italy

ISBN: (纸本)9798350361230

This paper proposes a framework designed to optimise energy consumption in vertical farming. It aims to maximise cost efficiency by balancing between minimising system operations during the electricity price peaks and the ability to trade capacity on the FCR market while also fulfilling constraints on the internal growing process. We consider that the vertical farming system has distributed control with a series of actuators controlled by various spatially distributed PLCs that we refer to as agents, to underline their independence. The paper conducts two experiments for a lO-agent system with a Pareto controller and a lOO-agent system with a Lagrangian approach and shows the balance between more cost-efficient momentary energy consumption control. © 2024 IEEE.

关键词： energy consumption optimisation multi-agent systems vertical farming

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Investigations and Time Estimation on Federated Learning for Future Internet of Vehicles

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IEEE Internet of Things Journal 2025年第11期12卷 17387-17398页

作者： Fukumoto, Shun Li, Ruidong Zeng, Kai Nan, Haihan Su, Zhou Kanazawa University Intelligent Computation and Network Laboratory Division of Electrical Information and Communication Engineering Kanazawa920-1192 Japan Kunming University of Science and Technology Faculty of Information Engineering Automation Kunming066000 China Kanazawa University Division of Electrical Information and Communication Engineering Kanazawa920-1192 Japan George Mason University Electrical and Computer Engineering Department FairfaxVA22030 United States Xi’an Jiaotong University School of Cyber Science and Engineering Xi’an710049 China

For future Internet of Vehicles (IoV), communications and computing will converge to provide services. Federated learning (FL), as one of the typical distributed computing technologies, needs to be integrated with IoV. For such integration, FL suffers from the straggler effect that the entire learning speed is lowered down, because of the existence of the devices, such as low-powered road side units and vehicles, taking more time to complete their tasks. Although the existing mechanisms reduce straggler effects by adopting asynchronous mechanisms and clustering mechanisms, they lack the detailed analysis of the reasons and the impacts of each cause, leading to inefficiencies in the design of algorithm. Additionally, most of the existing work only considered the impact of a single factor in computation, communication, or data distribution, which lacks comprehensive on research for causes of stragglers effects. The bottleneck is that it is laborious to observe the time delay precisely with the existing high-calculating evaluations. In this article, we elaborately explore the effects of computing power, communication capability, and data distributions on the straggler effects with carefully designing and conducting the extensive experiments. After investigations, we propose a novel learning completion time estimation formula for low computing capability devices with mini-batch stochastic gradient decent (SGD). We compare our proposed estimation formula with the one based on floating operation per second (FLOPs). Through the evaluations, our formula can demonstrate the improvement up to 72.4% at docker and 32.4% at Raspberry Pi device compared to the existing work. © 2014 IEEE.

关键词： Stochastic systems

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Mathematical Modeling and Analysis of Permanent Magnet Synchronous Motor in Quaternion Space 12

Mathematical Modeling and Analysis of Permanent Magnet Synch...

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12th International electrical engineering Congress, iEECON 2024

作者： Jiratthivarutkul, Kreetha Pongyart, Witthawas Faculty Of Engineering Department Of Electrical And Computer Engineering 1518 Pracharaj 1 Bangsue Bangkok Thailand

ISBN: (纸本)9798350383591

This paper presents an innovative method for the mathematical modeling of Permanent Magnet Synchronous Motors (PMSMs) using quaternion space. Traditional modeling methods typically assume a balanced three-phase voltage source, enabling the representation of the motor's rotation in a two-dimensional dq-space vector, with the third component set to zero. However, these conventional approaches prove inadequate when confronted with an unbalanced source, as the third component becomes non-zero, necessitating a three-dimensional model for precision. To address this challenge, quaternion space is utilized to formulate a mathematical model of the PMSM in three-dimensional space. In this study, all signals such as voltage, current, and flux are expressed as pure quaternions, and rotations in three-dimensional space are executed through quaternion multiplication. As a result, a mathematical model of the Permanent Magnet Synchronous Motor (PMSM) is formulated within the realm of quaternion space. The construction of this quaternion-based model is intricately explained, providing a comprehensive representation of crucial aspects, including stator voltage, stator-rotor interactions, and critical parameters such as torque and power consumption. Simulation results demonstrate that the PMSM model based on quaternions exhibits behavior consistent with traditional models when subjected to a balanced three-phase voltage source. Notably, the developed model demonstrates adaptability in accurately representing the motor's response even in the presence of unbalanced stator voltage sources. © 2024 IEEE.

关键词： Vector spaces

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Efficient Saliency Map Detection for Low-Light Images Based on Image Gradient

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IEEE Transactions on Circuits and Systems for Video Technology 2024年第2期34卷 852-865页

作者： Lin, Chun-Yi Haq, Muhamad Amirul Chen, Jiun-Han Ruan, Shanq-Jang Naroska, Edwin National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taipei10607 Taiwan Hochschule Niederrhein University of Applied Science Faculty of Electrical Engineering and Computer Science Krefeld47805 Germany

Recently, deep learning has been widely employed across various domains. The Convolution Neural Network (CNN), a popular deep learning algorithm, has been successfully utilized in object recognition tasks, such as face recognition, vehicle recognition, and license plate recognition. However, conventional methods for object recognition may not be appropriate for low-light image recognition due to information loss in the dark regions and unexpected noise that can impair object quality. Therefore, the development of specialized techniques for low-light image enhancement has become a major research focus for object detection. This paper proposed a gradient-based saliency map detection method with an improved ResNet architecture that outperforms previous works in detecting multiple or large objects. Additionally, the proposed method enhances images with the object as the center and emphasizes foreground-background differences. Compared with previous works, this paper achieves1.28× improvements in the parameters and 1.32× faster inference speed than the original ResNet architecture. © 1991-2012 IEEE.

关键词： Neural networks

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