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Enhancing Cabbage Plant Protection: CNN Algorithm for Insect Identification

Enhancing Cabbage Plant Protection: CNN Algorithm for Insect...

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2024 International Conference on Information Technology Research and Innovation, ICITRI 2024

作者： Senjaya, Remi Musa, Purnawarman Sularsih, Puji Novrina, Novrina Aryunani, Witari Suhartini, Suhartini Gunadarma University dept. of Informatics Engineering Depok Indonesia Gunadarma University dept. of Electrical Engineering Depok Indonesia Gunadarma University dept. of Information Technology Depok Indonesia Gunadarma University dept. of Computer Science Depok Indonesia

ISBN: (纸本)9798350376210

People frequently find it straightforward to identify insects that feed on cabbage plants based on the insects' characteristics. However, challenges arise when employing a computer for precise bug categorization and identification. The implementation of Deep Learning (DL) utilizes the Convolutional Neural Network (CNN) technique, renowned for its effectiveness in categorizing and recognizing objects in digital photo data. The CNN algorithm delivers notable results in photo identification, simulating the human visual brain's image recognition through artificial neural networks in the Python programming language. To enrich the user experience, frameworks like Keras and TensorFlow are employed in neural network development. Our research will use the CNN algorithm to determine insect species in cabbage images. Achieving high accuracy involves coupling the CNN algorithm with the VGGNet architectural model. Notably, utilizing an epoch value of 150 resulted in a 97.75% accuracy rate during the training model technique;however, the validation accuracy was slightly lower at 94.25%. The corresponding loss and validation rates were 0.0613% and 0.2945%, respectively. Moreover, based on the model (150 epochs), the testing outcomes in the study, involving 48 images beyond the dataset and incorporating additional information, resulted in an accuracy rate of 91.66%. © 2024 IEEE.

关键词： Convolutional neural networks

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GPU Reliability Assessment: Insights Across the Abstraction Layers

GPU Reliability Assessment: Insights Across the Abstraction ...

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2024 IEEE International Conference on Cluster Computing, CLUSTER 2024

作者： Yang, Lishan Papadimitriou, George Sartzetakis, Dimitris Jog, Adwait Smirni, Evgenia Gizopoulos, Dimitris George Mason University Department of Computer Science United States University of Athens Dept. of Informatics & Telecomm. Greece University of Virginia Department of Computer Science United States William & Mary Department of Computer Science United States

ISBN: (纸本)9798350358711

Graphics Processing Units (GPUs) are widely de-ployed and utilized across various computing domains including cloud and high-performance computing. Considering its extensive usage and increasing popularity, ensuring GPU reliability is cru-cial. Software-based reliability evaluation methodologies, though fast, often neglect the complex hardware details of modern GPU designs. This oversight could lead to misleading measurements and misguided decisions regarding protection strategies. This paper breaks new ground by conducting an in-dept. examination of well-established vulnerability assessment methods for modern GPU architectures, from the microarchitecture all the way to the software layers. It highlights divergences between popular software-based vulnerability evaluation methods and the ground truth cross-layer evaluation, which persist even under strong protections like triple modular redundancy. Accurate evaluation requires considering fault distribution from hardware to software. Our comprehensive measurements offer valuable insights into the accurate assessment of GPU reliability. © 2024 IEEE.

关键词： Program processors

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Precision Localization: An Experimental Study on BLE Fingerprinting and Trilateration with ESP32 1

Precision Localization: An Experimental Study on BLE Fingerp...

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1st IEEE International Conference on Advances in Electronics, Communication, Computing and Intelligent Information Systems, ICAECIS 2023

作者： Elhusseiny, Ahmed H. Zamzam, Marwa Zaghloul, Yasmine The German International University Dept. of Electrical Engineering Cairo Egypt The German International University Dept. of Informatics and Computer Science Cairo Egypt

ISBN: (纸本)9798350348057

This paper presents a method for indoor localization using two complementary techniques: Fingerprinting (FP) and Trilateration. The system is based on Bluetooth Low Energy (BLE) technology and a network of wireless anchors to determine the location of a mobile device. The FP approach collects Received Signal Strength Indicator (RSSI) data from BLE anchors in various indoor locations and creates a map of the environment in an offline stage. During the online stage, the device's location is determined by comparing its current RSSI measurements to the map. The FP technique showed an accuracy of 79.31% without positions on the other side of a separating concrete wall and 71.88% including those positions. In contrast, trilateration calculates the position of the device using distance measurements from multiple anchors, achieving an accuracy of 44.44%. Both techniques were tested in various environments and layouts, and the results indicate that FP is more suitable for indoor localization, particularly in large buildings with many rooms. This paper highlights the potential of these two techniques for practical indoor localization applications. Moreover, one of the experimental setups for the fingerprinting technique was tested in multiple rooms separated by a concrete wall to provide information about the potential scalability of the technique. © 2023 IEEE.

关键词： Bluetooth

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On Min-Max Graph Balancing with Strict Negative Correlation Constraints 34

On Min-Max Graph Balancing with Strict Negative Correlation ...

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34th International Symposium on Algorithms and Computation, ISAAC 2023

作者： Kuo, Ting-Yu Chen, Yu-Han Frosini, Andrea Hsieh, Sun-Yuan Tsai, Shi-Chun Kao, Mong-Jen Dept. of Computer Science National Yang-Ming Chiao-Tung University Hsinchu Taiwan Dept. of Computer Science and Information Engineering National Cheng-Kung University Tainan Taiwan Dept. of Mathematics and Informatics University of Florence Italy Dept. of Computer Science and Information Engineering National Chi-Nan University Puli Taiwan

ISBN: (纸本)9783959772891

We consider the min-max graph balancing problem with strict negative correlation (SNC) constraints. The graph balancing problem arises as an equivalent formulation of the classic unrelated machine scheduling problem, where we are given a hypergraph G = (V, E) with vertex-dependent edge weight function p: E × V 7→ Z≥0 that represents the processing time of the edges (jobs). The SNC constraints, which are given as edge subsets C1, C2, . . ., Ck, require that the edges in the same subset cannot be assigned to the same vertex at the same time. Under these constraints, the goal is to compute an edge orientation (assignment) that minimizes the maximum workload of the vertices. In this paper, we conduct a general study on the approximability of this problem. First, we show that, in the presence of SNC constraints, the case with maxe∈E |e| = maxi |Ci| = 2 is the only case for which approximation solutions can be obtained. Further generalization on either direction, e.g., maxe∈E |e| or maxi |Ci|, will directly make computing a feasible solution an NP-complete problem to solve. Then, we present a 2-approximation algorithm for the case with maxe∈E |e| = maxi |Ci| = 2, based on a set of structural simplifications and a tailored assignment LP for this problem. We note that our approach is general and can be applied to similar settings, e.g., scheduling with SNC constraints to minimize the weighted completion time, to obtain similar approximation guarantees. Further cases are discussed to describe the landscape of the approximability of this prbolem. For the case with |V | ≤ 2, which is already known to be NP-hard, we present a fully-polynomial time approximation scheme (FPTAS). On the other hand, we show that the problem is at least as hard as vertex cover to approximate when |V | ≥ 3. © Ting-Yu Kuo, Yu-Han Chen, Andrea Frosini, Sun-Yuan Hsieh, Shi-Chun Tsai, and Mong-Jen Kao;licensed under Creative Commons License CC-BY 4.0.

关键词： Computational complexity

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Reconfiguration Cost for Reconfigurable Computing Architectures 23

Reconfiguration Cost for Reconfigurable Computing Architectu...

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23rd ACIS International Summer Virtual Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD-Summer 2022

作者： Takano, Shigeyuki Amano, Hideharu Keio University Dept. of Informatics and Computer Science Kanagawa Japan

ISBN: (纸本)9798350396379

Reconfigurable computing systems show the advantage of high flexibility and high-performance or low-power relative to traditional computing systems. Reconfiguration can change user logic statically or dynamically. The reconfiguration is a key feature in the reconfigurable computing system, however, the reconfiguration techniques are not considered enough. One of the reconfiguration techniques must be chosen for usage target characteristics of reconfiguration. This article shows the cost of typical reconfiguration techniques which can be applied to not only field-programmable gate arrays (FPGAs) but also coarse-grained reconfigurable arrays (CGRAs). We call these microarchitectures, field-programmable logic (FPL). We focus on three device classes;traditional configurable FPL (ex. FPGA), a partially reconfigurable FPL and a multi-context FPL. We investigate how the size and frequency of reconfiguration can be taken care of and how much speed-up is theoretically expected from a perspective of reconfiguration cost. In addition, the investigation introduces temporal and spatial configuration cache techniques. © 2022 IEEE.

关键词： Reconfigurable architectures

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Netstaldi: A Modular Distributed Architecture for Incremental Network Discovery 8

Netstaldi: A Modular Distributed Architecture for Incrementa...

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8th Italian Conference on Cyber Security, ITASEC 2024

作者： Paier, Matteo Pizzolitto, Mattia Foresti, Gian Luca Miculan, Marino University of Udine Dept. of Mathematics Computer Science and Physics Italy IMT Alti Studi Lucca Italy Ca'Foscari University of Venice Dept. of Environmental Sciences Informatics and Statistics Italy

Maintaining a comprehensive understanding of a network's connected devices is fundamental for robust security. This knowledge is crucial for tasks like vulnerability assessments, identifying potential attack surfaces, and network mapping. In this paper, we propose Netstaldi, a distributed architecture specifically designed for incremental and secure network discovery. Our architecture leverages non-intrusive network scanning techniques based on standard TCP/IP protocols, eliminating the need for monitoring agents on individual devices. This approach prioritizes scalability, modularity, and resilience, making it well-suited to handle large and dynamic network environments. We have implemented a prototype system based on this architecture, utilizing established open source tools. This system has been successfully tested on a large, real-world network. The results are promising: the tool efficiently scans the entire network within a few hours, and the intuitive GUI allows administrators to interactively explore the generated network map to identify and address potential vulnerabilities and misconfigurations. Copyright © 2024 for this paper by its authors.

关键词： Network security

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ECC's Achilles'Heel: Unveiling Weak Keys in Standardized Curves 8

ECC's Achilles'Heel: Unveiling Weak Keys in Standardized Cur...

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8th Italian Conference on Cyber Security, ITASEC 2024

作者： Talotti, Enrico Paier, Matteo Miculan, Marino University of Udine Dept. of Mathematics Computer Science and Physics Italy IMT Alti Studi Lucca Italy Ca' Foscari University of Venice Dept. of Environmental Sciences Informatics and Statistics Italy

The strength of Elliptic curve cryptography (ECC) relies on curve choice. This work analyzes weak keys in standardized curves, i.e., private keys within small subgroups of the auxiliary group ∗p. We quantify weak key prevalence across standardized curves, revealing a potential vulnerability due to numerous small divisors in auxiliary group orders. To address this, we leverage the implicit baby-steps giant-steps algorithm, which transforms the complex elliptic curve discrete logarithm problem into a simpler problem within ∗p. This enables efficient detection of weak keys in small-order subgroups. Our findings highlight the importance of rigorous key testing in applications using standardized ECC. While random weak keys are unlikely, malicious actors could exploit this by manipulating key generation libraries. To this end, we show how users can assess their private key vulnerabilities and mitigate risks by eliminating weak keys. Hence, this work contributes to improved ECC security through proactive key management practices. Copyright © 2024 for this paper by its authors.

关键词： Geometry

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Small Data, Big Impact: A Multi-Locale Bone Fracture Detection on an Extremely Limited Dataset Via Crack-Informed YOLOv9 Variants

Small Data, Big Impact: A Multi-Locale Bone Fracture Detecti...

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2024 International Conference on Frontiers of Information Technology, FIT 2024

作者： Ahmed, Ammar Manaf, Abdul Imran, Ali Shariq Kastrati, Zenun Daudpota, Sher Muhammad NTNU Gjøvik2815 Norway Dept. of Computer Science Sukkur IBA University Sukkur65200 Pakistan Dept. of Informatics Linnaeus University Växjö351 95 Sweden

ISBN: (纸本)9798331510503

Automated wrist fracture recognition has become a crucial research area due to the challenge of accurate X-ray interpretation in clinical settings without specialized expertise. With the development of neural networks, YOLO models have been extensively applied to fracture detection recently. However, detection models can struggle when trained on small datasets, which is often the case in medical scenarios. In this study, we utilize an extremely small multi-region fracture dataset and hypothesize that the structural similarities between surface cracks and bone fractures can allow YOLOv9 with a generalized efficient layer and programmable gradient information control to transfer knowledge effectively. We show that pre-training YOLOv9 on surface cracks rather than on COCO, which is how YOLO models are typically pre-trained, and fine-tuning it on the fracture dataset yields substantial performance improvements. We also show that knowledge gained from the surface cracks requires fewer epochs to converge and minimizes overfitting. We achieved state-of-the-art (SOTA) performance on the newly released FracAtlas dataset, surpassing the previously established benchmark. Our approach improved the mean average precision (mAP) score by 7% and sensitivity by 13%. © 2024 IEEE.

关键词： Transfer learning

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Investigating the effect of video extraction summarization techniques on the accuracy of impression conveyance in group dialogue 35

Investigating the effect of video extraction summarization t...

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35th Australian computer-Human Interaction Conference, OzCHI 2023

作者： Takayama, Chihiro Eitoku, Shinichirou Nihei, Fumio Ishii, Ryo Nakano, Yukiko Fukayama, Atsushi Ntt Human Informatics Laboratories Ntt Corporation Japan Dept. of Computer and Information Science Seikei University Japan

ISBN: (纸本)9798400717079

As video-recording devices have become inexpensive and easily available, and the use of web conferencing for remote work has become common, video recording of dialogue content has become widely used. While this video is an accurate record of the dialogue, it takes more time to view than the actual dialogue, so there is a need for a technique to efficiently determine the dialogue content. In previous dialogue-summarization studies, only the conveyance of the content was subject to evaluation. However, in understanding dialogue, not only the conclusion but also the flow of discussion leading to the conclusion, the atmosphere, and the impression of the dialogue are important. To develop an extractive video-summarization technique, we focused on dialogue acts and investigated the changes in impressions of conversation caused by different extractive summarization techniques. The two subject experiments showed the importance of questions and reactions in dialogue summarization, which are deleted with traditional summarization techniques that extract important statements. © 2023 ACM.

关键词： Video recording

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An Image Processing and Utilization System Using Deep Learning for Tourism Promotion

An Image Processing and Utilization System Using Deep Learni...

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2023 IEEE Asia-Pacific Conference on computer science and Data Engineering, CSDE 2023

作者： Tu, Yunhao Kinugasa, Masato Urata, Mayu Endo, Mamoru Yasuda, Takami Chubu University Dept. of Computer Science Kasugai Japan Graduate School of Informatics Nagoya University Nagoya Japan

ISBN: (纸本)9798350341072

In recent years, digitalization has made significant developments in all areas of modern society. Data analysis and the application of information technology are becoming increasingly important in the tourism industry, which is an important pillar industry in Japan. Therefore, we propose a system with four main functions to support local governments in processing and using image data and deep learning to promote tourism. Function 1: The system classifies images by detecting faces and selects images without faces and personal information that can be used for local tourism promotion. Function 2: The system protects personal information by transforming image styles or adding mosaics, and the processed data can be used for image publishing and display. Function 3: The system classifies images according to season and other factors to organize tourism promotion materials. Function 4: The system expands the application by adding captions to the images, such as using the original image and captions to promote local scenery and festivals. These functions can help users to better utilize the image data for tourism promotion in local governments. Our goal is to reduce the workload of local governments and improve the efficiency of image data utilization. We also use image data to promote urban promotion and achieve regional revitalization. We have confirmed the usefulness of the proposed system for data processing and tourism promotion through cooperation with local govemments. © 2023 IEEE.

关键词： Object detection

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