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Blockchain Anchored Federated Learning and Tokenized Traceability for Sustainable Food Supply Chains 4

Blockchain Anchored Federated Learning and Tokenized Traceab...

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4th International Conference on Ubiquitous Computing and Intelligent Information systems, ICUIS 2024

作者： Chaganti, Koushik Reddy Kumar, B. Naveen Gutta, Pruthvi Krishna Elicherla, Sivananda Lahari Reddy Nagesh, C. Raghavendar, K. University of the Cumberlands Dept. of Computer and Information Systems KY United States Vignan Institute of Technology and Science Department of Information Technology Hyderabad India Tesla Dept of It AustinTX United States Dayananda Sagar University Dept of Cse Bangalore India Srinivasa Ramanujan Institute of Technology Dept of Cse Anantapur India Teegala Krishna Reddy Engineering College Dept of Cse Hyderabad India

ISBN: (纸本)9798331529635

The management of food supply chains relates to just about the most imperative issues concerning sustainability, quality, and traceability, where existing methodologies usually fail to meet the demands caused by data privacy, lack of transparency, and inefficiencies concerning collaboration among stakeholders. This compromises data security, and thus there arises single points of failure. Conversely, traditional traceability frameworks fail to incite wide-scale participation and lack real-time accuracy. Having these limitations in mind, we introduce a hybrid framework consisting of three advanced methodologies: Decentralized Federated Learning with Blockchain Anchoring (DFLBA), Dynamic Tokenized Traceability Framework (DTTF), and Adaptive Supply Chain Graph Neural Networks (ASCGNN) process. DFLBA would support privacy-preserving machine learning as such that collaborative training of yield prediction and crop monitoring models by stakeholders without revealing raw data will be feasible. Blockchain anchoring ensures logs of training updates are tamper-proof, thus increasing trust and transparency. DTTF introduces tokenized incentives that enhance traceability in real-time: every product has a digital twin represented by blockchain-anchored tokens updated by stakeholders. Smart contracts enforce the compliance that will improve participation and lifecycle data accuracy. ASCGNN models the food supply chain as a dynamic graph, leveraging graph neural networks to capture stakeholder interdependencies, optimize operations, and detect fraud. Blockchain integration ensures reliability and transparency by securing edge weights. The suggested framework has demonstrated good impact, like 95% model accuracy for yield prediction, 99% traceability coverage, and 92% prediction accuracy for bottlenecks of the supply chain. It provides a scalable, privacy-preserving, and transparent solution that enhances the efficiency of food supply chains, and positively impacts stakeholders in a

关键词： Federated learning

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Knowledge Engineering-Based Quality Management in Prefabricated Construction

Knowledge Engineering-Based Quality Management in Prefabrica...

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2023 International Conference on Construction and Real Estate Management: The Human-Centered Construction Transformation, ICCREM 2023

作者： Chen, Ke Zhang, Yunhan Fang, Weili Tan, Tan School of Civil and Hydraulic Engineering Huazhong Univ. of Science and Technology Wuhan China Dept. of Civil and Building Systems Technische Universität Berlin Berlin Germany Faculty of Architecture and the Built Environment Delft Univ. of Technology Delft Netherlands

ISBN: (数字)9780784485217

ISBN: (纸本)9780784485217

Prefabricated construction (PC) is an increasingly popular construction approach that offers numerous benefits, including greater efficiency, improved safety, and reduced material waste. However, this approach also introduces a new set of quality risks due to the complex process of off-site prefabrication, transportation, and on-site assembly. Currently, quality management (QM) in PC is mainly conducted through manual efforts that rely on human experience and established standards. This approach can be both inefficient and susceptible to human bias, which can lead to quality issues. To address these concerns, this study proposes a knowledge engineering-based framework that utilizes knowledge modeling and reasoning to enable intelligent QM. The framework consists of four layers: data acquisition, knowledge generation, knowledge storage, and value-added application. The proposed framework was applied to a case scenario, and the results showed that the open information stored in the knowledge base can guide the quality control process, and vice versa, enabling the quality control process to promote the updating of the knowledge base. © ASCE.

关键词： Data acquisition

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3D Visualization of Femoral Shaft Fractures 4

3D Visualization of Femoral Shaft Fractures

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4th International Conference on Artificial Intelligence and Data Sciences, AiDAS 2023

作者： Mi, Lam Xin Hoon, Saw Seow Wang, Khor Siak Hui, Saw Seow Utar Faculty of Information and Communication Technology Dept. of Information Systems Perak Malaysia Utar Dr. WLT-CRCD Utar Sg. Long Faculty of Science Dept. of Allied Health Sciences Perak Malaysia Utar Faculty of Information and Communication Technology Department of Computer Science Perak Malaysia

ISBN: (纸本)9798350318432

The absence of an independent learning platform to address femoral shaft fractures poses challenges in understanding and classifying these fractures. The existing anatomy platforms, such as 3D interactive anatomical atlases, are insufficient in providing comprehensive information on the fractures and the high cost of these interactive anatomical atlases can be a barrier for learning to proceed due to the needs of the actual bones and human models. This study aims to develop an accessible, cost-effective educational 3D mobile application that caters to the learning needs associated with human femoral shaft fractures. Although femoral fractures are relatively uncommon, the increased cases of fractures necessitate awareness and preparedness among individuals as well as medical professionals. The proposed mobile application will enhance users' understanding of anatomical structures in femoral shaft fractures and contribute to improved patient care as well as enhance medical education. © 2023 IEEE.

关键词： Fracture

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EMDA-Net: Earth Mover’s Distance (EMD) influenced Attention-aided Neural Network for Medical Image Classification

EMDA-Net: Earth Mover’s Distance (EMD) influenced Attention...

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IEEE International Conference on Cognitive Machine Intelligence (CogMI)

作者： Surya Majumder Kushaj Mallick Wrick Pal Somenath Chakraborty Ram Sarkar Dept. of Computer Science & Engineering Heritage Institute of Technology Kolkata India Dept. of Electrical Engineering Jadavpur University Kolkata India Dept. of Computer Science & Information Systems West Virginia University Institute of Technology West Virginia USA Dept. of Computer Science & Engineering Jadavpur University Kolkata India

ISBN: (数字)9798350386721

ISBN: (纸本)9798350386738

Medical image analysis methods need to be more generalized in order to meet the substantial problems associated with cancer detection and treatment, including skin, cervical, and breast cancer. In this work, we propose a novel lightweight convolutional neural network (CNN) architecture, named EMDA-Net (Earth Mover’s Distance (EMD) influenced Attention-aided Neural Network), specifically designed to meet the requirements of cancer subtype classification. It is built on the MobileNetV2 backbone and is equipped with hybrid statistical mechanism-aided attention mechanisms. Our model ensures high-performance while maintaining a lightweight design by leveraging the capabilities of the MobileNetV2 architecture and the attention mechanism. To improve similarity detection across data channels, we present a novel EMD influenced attention technique. We have examined datasets related to skin, cervical, and breast cancer for experimentation. Our model especially outperforms the state-of-the-art techniques, demonstrating its effectiveness in maximizing diagnosis precision for various cancer types across the datasets. The code of the proposed model will be made public at: https://***/q5DlN

关键词： Earth Attention mechanisms Codes Neural networks Skin Breast cancer Convolutional neural networks Medical diagnostic imaging Machine intelligence Image classification

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LIDS: Lightweight Dynamic Scheduling Technique for 6G-enabled Massive LoRa based IoT systems

LIDS: Lightweight Dynamic Scheduling Technique for 6G-enable...

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2022 IEEE GLOBECOM Workshops, GC Wkshps 2022

作者： Kumbam, Akshitha Choudhury, Nikumani Nasralla, Moustafa M. Birla Institute of Technology & Science Dept. of Computer Science & Information Systems Pilani Hyderabad India Prince Sultan University Dept. of Communications & Networks Engineering Riyadh Saudi Arabia

ISBN: (纸本)9781665459754

The sixth-generation (6G) wireless communication networks are envisioned to deliver improved Quality of Services (QoS) such as data-rate, latency, localization, etc., compared to 5G services. This demand will mainly arise due to the massive Internet of Things (IoT) connections among billions of embedded devices. It is worth noting that these IoT devices are constrained in nature in terms of memory, computation and most importantly power. Low-power wireless computing necessitates a link-layer technology that considers the aforementioned IoT device requirements such as low-power, low data-rate, long-range and energy efficient reliable communications. Long Range Radio (LoRa) technology has recently become widely popular to facilitate low-power, long-range communication, while other similar technologies struggle to achieve long-range transmissions. The LoRA standard defines several PHY and MAC sub-layer specifications for Low-Power Wide Area Networks (LPWAN) that can be used to build several IoT applications. With 6G communications, an IoT application is expected to consist of hundreds of devices connected at a time, and this will need a proper scheduling mechanism among these devices for optimal performance. The LoRa standard does not define any scheduling mechanism and leaves it to the research community to explore. In this paper, we propose a distributed scheduling mechanism under the supervision of a common LoRa gateway. The proposed mechanism focuses on a Lightweight DynamicScheduling (LIDS) scheme to minimize loss in data transmissions through collisions. The proposed mechanism optimizes the power consumption to achieve the desired level of QoS requirements such as throughput and latency. © 2022 IEEE.

关键词： Internet of things

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Towards Eco-Sustainability and Green Analytics Model to Measure the Performance of Big Data systems 9

Towards Eco-Sustainability and Green Analytics Model to Meas...

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9th International Conference on Information Management, ICIM 2023

作者： Jusoh, Yusmadi Yah Abdullah, Rusli Nor, Rozi Nor Haizan Yahaya, Jamaiah Hj. Muhammad, Shireen Arunachalam, Aishwharya Raani Universiti Putra Malaysia Faculty of Computer Science and Information Technology Dept. of Software Engineering and Information Systems Serdang Malaysia Universiti Kebangsaan Malaysia Faculty of Information Science and Technology Bangi Malaysia Faculty of Communication Selangor Malaysia

ISBN: (纸本)9798350336382

Many BDS is doomed to failure because of the missing knowledge on measuring the performance of BDS. The failure to identify the performance measurement and correct will make the problems worsen. This will complicate the efforts of fixing such problems and more importantly, will affect the quality of knowledge, insights, and results expected by the users in the future. In achieving durable performance, the organization needsto understand the factors that contribute to the performance of the eco-sustainability and green analytics metrics for BDS. Although the existence of its importance and awareness was largely neglected. Therefore, the eco-sustainability and green analytic measurement of the BDS is examined in this research. Measuring the BDS performance has the benefit of identifying problems and launching corrective actions before these problems happen and become worsen. The research will investigate the eco-sustainability and green analytic measures which will be proposed and used to capture performance for each process of BDS. Then, based on such measures and metrics, as well as existing performance concepts, frameworks, and models, a measurement model for BDS will be created. The model will be validated through expert evaluations and confirmatory studies with users and practitioners of BDS users. The research has a greater significance in leveraging existing performance concepts in BDS settings and the research proposes users' participation in the sustainability and continuous performance evaluation of theirBDS. © 2023 IEEE.

关键词： Big data

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Reliable Data Storage and Sharing using Block chain technology and Two Fish Encryption 4

Reliable Data Storage and Sharing using Block chain Technolo...

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4th International Conference on Inventive Research in Computing Applications, ICIRCA 2022

作者： Sivanantham, S. Sakthivel, M. Krishnamoorthy, V. Balakrishna, N. Akshaya, V. Sree Vidyanikethan Engineering College Dept. of Computer Science and Systems Engineering Andhra Pradesh Tirupati India Sree Vidyanikethan Engineering College Dept. of Computer Science and Engineering Andhra Pradesh Tirupati India Bannari Amman Institute of Technology Dept. of Computer Science and Engineering Tamilnadu Sathyamangalam India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Digital data that has been certified by a respected institution is valuable and can be saved or transmitted over the internet. However, the issues are ensuring the security and reliability of stored and shared data, as well as ensuring a secure, transparent, and fair data sharing process. As a result, The schemas for data production, storage, and sharing is suggested. A group signature scheme in the data production schema for a collection of respected organisations that provide similar services is used. A member of the group develops precious digital data from RD (raw data) provided by a DO (data owner) and then provides a certification based on the encipher of that data. The system saves the data's access address in the database after data owner uploading his or her data to the system in the data storage schema. Before submitting a data sharing proposal to the DO, every person on the system might validate the quality of shared data. The data sharing mechanism is carried out via a smart contract to incentivize honesty. The schemas assure the security properties of data storage and exchange, which include confidentiality, integrity, privacy, and non-repudiation. © 2022 IEEE.

关键词： Fish

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Low-Latency and Energy-Efficient Task Scheduling for End-Edge-Cloud Collaborative Computing

Low-Latency and Energy-Efficient Task Scheduling for End-Edg...

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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Li, Jingyao Yuan, Haitao Ma, Yaofei Bi, Jing Yang, Jinhong Zhang, Jia School of Automation Science and Electrical Engineering Beihang University Beijing100191 China College of Computer Beijing University of Technology Beijing100124 China Cssc Systems Engineering Research Institute Beijing China Southern Methodist University Dept. of Computer Science DallasTX75275 United States

ISBN: (纸本)9781665410205

Mobile edge computing (MEC) is a new paradigm that improves the quality of service compared with traditional cloud computing. In MEC, computational tasks are submitted by numerous end users and are partially offloaded to edge servers or a central cloud. However, the characteristics of tasks are different from each other, and the limited resources of computational nodes are also heterogeneous, which brings great challenges to computation offloading and resource allocation for MEC. This work establishes an end-edge-cloud collaborative computing network, which consists of end devices, edge servers, and a central cloud. Task execution location and CPU running frequency determine the execution time and energy consumption to finish the tasks. Considering the aforementioned factors, a multi-objective constrained optimization problem is formulated. To solve the problem, an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) with self-adaptive crossover and mutation rates is proposed, which is called Improved NSGA-II with _Self-adaptive Crossover and Mutation (INSCM). The total execution time and energy consumption can be jointly minimized with our proposed INSCM. Numerous experiments are carried out to test the performance of INSCM. Simulation results show that INSCM effectively improves the performance of NSGA-II and surpasses random offloading and NSGA-III, which shows practical use in real-life scenarios. © 2024 IEEE.

关键词： Mobile edge computing

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Analysis of Arabs Publications In the Field of computer Networks

Analysis of Arabs Publications In the Field of Computer Netw...

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International Conference on Information and Communication systems (ICICS)

作者： Emran EL-Bashabsheh Mutaz Younes Mohammed Shatnawi dept. of Computer Information Systems Jordan University of Science and Technology Irbid Jordan dept. of Computer Science Jordan University of Science and Technology Irbid Jordan

Increasing technology led to increasing collaboration between the countries in general, especially the Arabic world. In recent years, many impacts affect the growth of research work in different Arabic countries. In this research, we show the growth of research work and its quality between Arabs and the rest of the world. We collected over 2500 publications and used it to create a new table that contains the intersection between each Arab country and each co-author's continent to show the relationship between each Arabic country with the rest of the world. We divided the data into two periods, before and after 2015, then we used Hue to apply our analysis on the data. We focused on the number of publications and the number of citation for each Arabic country. We noticed the rapid growth in the last period in some Arabic countries such as Jordan, Qatar, United Arab Emirates, and Saudi Arabia. In contrast, the rest of the countries had slow or decreasing growth.

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Predicting Lifespan of Ground-to-Air Multipath Components in mmWave UAV Channels

Predicting Lifespan of Ground-to-Air Multipath Components in...

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IEEE Conference on Wireless Communications and Networking

作者： Wahab Khawaja Rune H. Jacobsen Sajid Hussain Ismail Guvenc Dept. Electrical and Computer Engineering Aarhus University Aarhus Denmark Dept. Computer Systems Engineering Mirpur Univ. Science and Technology Mirpur AJK Pakistan Dept. Electrical and Computer Engineering North Carolina State University Raleigh NC USA

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

In mobile ground-to-air (GA) propagation channels, the birth and death of multipath components (MPCs) are frequently observed, and the wide-sense stationary uncorrelated scattering (WSSUS) assumption does not always hold. Several methods exist for tracking the birth and death of MPCs, however, to the best of knowledge of authors, there is no existing literature that addresses the prediction of the lifespan of the MPCs in non-WSSUS GA propagation channels. In this work, we consider the GA channel as non-WSSUS and individual MPCs across receiver positions are represented as time series based on the Euclidean distance between channel parameters of the MPCs. These time series representations, referred to as path bins, are analyzed using a semi-Markov chain model. The channel parameter variations and dependencies between path bins are used to predict the lifespan of path bins using weighted sum method, machine learning classifiers, and deep neural networks. For comparison, the birth and death of path bins are also modeled using a Poisson distribution and a Markov chain. Simulation results demonstrate that deep neural networks offer highly accurate predictions for the lifespan (including death) of MPC path bins in the considered GA propagation scenario.

关键词： Analytical models Simulation Time series analysis Scattering Artificial neural networks Machine learning Receivers Euclidean distance Autonomous aerial vehicles Millimeter wave communication

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