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11th International Conference on Future Data and Security engineering, FDSE 2024

作者： Le, Kim-Ngoc T. Le, Duc-Tai Choo, Hyunseung Department of AI Systems Engineering Sungkyunkwan University Seoul Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Seoul Korea Republic of College of Computing and Informatics Sungkyunkwan University Seoul Korea Republic of

ISBN: (纸本)9789819604364

Deep neural network (DNN) models have shown promise in lung disease classification using spectrogram transformations of respiratory sounds. However, these models typically process entire images, which can be computationally expensive, and they require large datasets for effective training. With the largest available respiratory dataset, ICBHI, containing only 920 recordings, training a robust DNN becomes challenging. To address this issue, this paper introduces a simplified DNN framework that incorporates novel techniques such as patch splitting and transfer learning. Specifically, the proposed framework splits the spectrogram image into a sequence of fixed-size patches, effectively reducing computational demands. These patches are processed with the position embeddings by DNN encoders to capture acoustic characteristics, leveraging a pre-trained ImageNet model to make efficient use of the limited dataset. Evaluation experiments on the ICBHI dataset show that the proposed method improves the state-of-the-art 8-class classification accuracy by 1.91%. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Lung cancer

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Seafloor Imaging Maps by Incorporating Side Scan Sonar Technology on Hybrid Autonomous Underwater Glider 6

Seafloor Imaging Maps by Incorporating Side Scan Sonar Techn...

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6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Atmaja, Ardian Budi Kusuma Hidayat, Egi Muhammad Idris Riyanto Trilaksono, Bambang Siregar, Simon Habibullah, Natsir School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Institut Teknologi Bandung Telkom University Doctoral Program of Electrical Engineering Department Computer Engineering Faculty of Applied Science Indonesia

ISBN: (纸本)9798350358346

This research aims to construct a two-dimensional image to represent an underwater geometry map with a Side Scan Sonar (SSS) mounted on a Hybrid Autonomous Underwater Glider (HAUG). Building the underwater map has two stages of the process. The first stage is preprocessing which includes Time-varying gains (TVG), slant range correction, and ground range correction. The second is HAUG navigation, the movement of HAUG orientation to the angle and distance of SSS readings and plotting the geometry of the grid map. With these two stages, a two-dimensional grid map will be formed. Meanwhile, the 3D plot utilizes slant range and ground range correction to obtain the surface height of the bottom of the pool. From the experiments conducted to conduct mapping in the pool, two-dimensional and three-dimensional visual forms of the pool floor and pool walls were produced. The results of the estimated measurement of the width of the pool obtained 14.05 meters and the height of the pool 3.199 meters with an SSS beam angle of 58 degrees. © 2023 IEEE.

关键词： Geometry

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Eye and People Counting Using Haar Cascade and NVIDIA Jetson Nano for Ad Analysis 1

Eye and People Counting Using Haar Cascade and NVIDIA Jetson...

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1st International Conference on Advanced engineering and Technologies, ICONNIC 2023

作者： Wicaksana, Cakra Adipura Hidayat, Wahyu Santoso, Muhammad Iman Alfanz, Rocky Fatkhurrokhman, Mohammad Yusfia Hafid, A. University of Sultan Ageng Tirtayasa Department of Informatics Cilegon Indonesia University of Sultan Ageng Tirtayasa Department of Electrical Engineering Cilegon Indonesia Vocational Education University of Sultan Ageng Tirtayasa Department of Electrical Engineering Serang Indonesia Sebelas Maret University Department of Informatics and Computer Engineering Education Surakarta Indonesia

ISBN: (纸本)9798350306484

Eye-detection technology is used to improve the effectiveness of advertisements. This research uses a mirrorless camera, the Harr Cascade method to detect eyes and faces, and the NVIDIA Jetson Nano as a microcontroller. The results show that the system can detect with high accuracy, even with differences in distance and face accuracy, even with differences in distance and the number of people looking at the camera. camera. This system can be used to calculate the number of effective ad readers. effective advertising readership. In the three cases tested, the system had an accuracy of 91 %,97%, and 90% for calculating the number of people viewing an advertisement, as well as an accuracy of 87% for face detection. © 2023 IEEE.

关键词： Cameras

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Depth and Pitch Control of Autonomous Underwater Glider Using Model Predictive Control with ARX Model

Depth and Pitch Control of Autonomous Underwater Glider Usin...

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2023 International Conference on electrical engineering and informatics, ICEEI 2023

作者： Jeremy, Jason Hidayat, Egi Muhammad Idris Siregar, Simon Trilaksono, Bambang Riyanto Habibullah, Natsir School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Telkom University Faculty of Applied Science Department Computer Engineering Bandung Indonesia

ISBN: (纸本)9798350381290

Autonomous Underwater Gliders (AUGs) are extensively developed vehicles capable of prolonged exploration and observation in complex marine environments. Control of the AUG is challenging due to its slow response system and its constraints. In this research, a linear model representation of AutoRegressive eXogenous input (ARX) will be constructed using input and output data from the AUG system, built Model Predictive Control (MPC), analyzed the performance, comparing with traditional Proportional-Integral-Derivative (PID). The objective is to enhance setpoint tracking accuracy and minimize energy to extend exploration time while faced with constraints. Simulation results reveal MPC exhibits potential setpoint tracking, low overshoot as low as 0.6% up to 0.3m/s maximum depth rate, has relatively low input changes indicating good efficiency compared to PID. MPC approach effectively addresses slow response systems, managing momentum, and handling actuator constraints commonly encountered in AUG. © 2023 IEEE.

关键词： Model predictive control

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Performance Evaluation of Intrusion Detection System with SVM 6

Performance Evaluation of Intrusion Detection System with SV...

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Diaz, Ricky Aurelius Nurtanto Putra, I. Ketut Gede Darma Sudarma, Made Sukarsa, I. Made Department of Computer Systems Faculty of Informatics and Computer Institut Teknologi dan Bisnis STIKOM Bali Bali Indonesia Department of Information Technology Faculty of Engineering Udayana University Jimbaran Hill Bali Indonesia Department of Electrical Engineering Faculty of Engineering Udayana University Jimbaran Hill Bali Indonesia

ISBN: (纸本)9798331539603

Various machine learning techniques have been proposed to improve the effectiveness of Intrusion Detection Systems (IDS), where IDS is one of the important parts of the network that functions to maintain network security. With its various capabilities and reputation, Support Vector Machine (SVM) is often applied in various classification cases. However, it has constraints with accuracy and computing time when it comes to data that has large dimensions. Utilizing metaheuristic techniques is one possibility that researchers can use to solve this problem. To overcome this, in this study, we will evaluate the performance of SVM for the IDS case by utilizing the metaheuristic Grey Wolf Optimization (GWO) algorithm. From the experiments with three different iteration models, the best results of the combination of SVM and GWO were found in a model with 10 GWO iterations and 10 populations with an accuracy of 97.47% using 15 features out of 48 original features of the UKM-IDS20 dataset. © 2024 IEEE.

关键词： Network intrusion

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Private Blockchain-Based Platform for Cool Box Truck Based on LoRa Communication Protocol 1

Private Blockchain-Based Platform for Cool Box Truck Based o...

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1st IEEE International Symposium on Consumer Technology, ISCT 2024

作者： Prayudi, Agus Hakim, Oktafian Sultan Zainuddin, Muhammad Agus Sukaridhoto, Sritrusta Budiarti, Rizqi Putri Nourma Politeknik Elektronika Negeri Surabaya Department of Electrical Engineering Surabaya Indonesia Politeknik Elektronika Negeri Surabaya Department of Informatics and Computer Engineering Surabaya Indonesia Universitas Nadhlatul Ulama Surabaya Department of Information System Surabaya Indonesia

ISBN: (纸本)9798350365191

The Internet of Things utilizes software, embedded system, sensor, and network connectivity to control and monitor business processes such as supply chains. One of the implementations of IoT is LoRa (Long Range) which enables data transactions in long-range without using radio frequency. Currently, a combination of IoT and blockchain is able to increase the security level of IoT applications. Implementation of IoT in the supply chain has been done in several research by implementing blockchain and LoRa. Approximately 6.43% of the Gross Domestic Product (GDP) is attributed to logistics, with cold and hot logistics constituting around 11%. Among these, cold chain logistics, a specialized form, accounts for 9.7% of tonnage. Cold chain logistics, characterized by comprehensive temperature control, is a sophisticated system closely intertwined with advanced technology. Despite its complexity, there are still technological drawbacks leading to significant material losses on an annual basis. In this research, to overcome that problem, we proposed Blockchain-Based Monitoring System on Cool Box Trucks using LoRa. The proposed system implemented LoRa for data communication and Blockchain as decentralized databases. We simulated the LoRa environment by using FLoRa framework to obtain the optimal parameters such as Transmission Power (TP), Packet Delivery Ratio (PDR), and Spread Factor (SF) that used in TTGO T-Beam V1. © 2024 IEEE.

关键词： Trucks

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Data Driven Methods to Predict Vertical Profiles of the Rails: A Case Study 10

Data Driven Methods to Predict Vertical Profiles of the Rail...

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Nugraha, Ade Chandra Supangkat, Suhono Harso Nugraha, Igb Baskara Handoko, Yunendar Aryo Purwadinata, Awan Hermawan Saputro, Dimas Wisnu Bandung State of Polytechnic School of Electrical Engineering and Informatics Bandung Institute of Technology Department of Computer Engineering and Informatics Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Smart City and Community Innovation Center Bandung Indonesia Bandung Institute of Technology Faculty of Mechanical and Aerospace Engineering Bandung Indonesia PT Kereta Api Indonesia Managing Director of Infrastructure Bandung Indonesia Bandung State of Polytechnic Department of Computer Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9798350339543

Predicting the value of railroad track geometry is needed to reduce the cost and time of rail condition measurements that have been carried out periodically every three months by railroad operators in Indonesia (PT Kereta Api Indonesia/PT KAI). Four track geometry parameters - vertical profile, horizontal alignment, twist, and gauge - are the reference measurements that will be mapped with alternative measurement results using accelerometers installed on regular trains (in-service trains). In this paper, eight prediction algorithms from the machine learning model are applied to map the vertical profile with 73 kilometers of measurement data in the Jakarta to Padalarang railroad segment, precisely on the Jatinegara-Cikampek measuring trip conducted from April 2019 to June 2022. The evaluation performance of the prediction results has been measured with the GadientBoosting Regressor algorithm is the best algorithm with MSE = 0.791, R2 = 0.507 and feature importance on the Train speed and Az attributes. The research can be continued to detect the correlation of three other track geometry parameters referring to the dataset of rail geometry condition measurement results through accelerometers on regular trains (in-service trains). © 2023 IEEE.

关键词： Forecasting

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Ergodic Capacity Analysis of RIS-aided System Relying on User Grouping and Fixed Power Allocation 5th

Ergodic Capacity Analysis of RIS-aided System Relying on Use...

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5th International Conference on Communication, Device and Networking, ICCDN 2021

作者： Umamaheswari, Kaveti Fazal-E-Asim Do, Dinh-Thuan Department of Computer Science and Information Engineering College of Information and Electrical Engineering Asia University Taichung41354 Taiwan Department of Tele Informatics Engineering Federal University of Cear ´a Fortaleza Brazil

ISBN: (纸本)9789811920035

In this paper, we focus on the ergodic capacity of RIS-assisted NOMA in wireless communication systems. The closed upper bound of ergodic capacity analysis is obtained for the proposed technique by using both Rayleigh and Rician fading channel environments for multiple users. Compared to simulations, numerical results demonstrate the tightness and effectiveness of our closed-form expressions. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Rayleigh fading

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A comprehensive evaluation of large language models in mining gene relations and pathway knowledge

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Quantitative Biology 2024年第4期12卷 360-374页

作者： Muhammad Azam Yibo Chen Micheal Olaolu Arowolo Haowang Liu Mihail Popescu Dong Xu Department of Electrical Engineering and Computer Science University of MissouriColumbiaMissouriUSA Bond Life Sciences Center University of MissouriColumbiaMissouriUSA Institute for Data Science and Informatics University of MissouriColumbiaMissouriUSA Department of Biomedical Informatics Biostatistics and Medical EpidemiologyUniversity of MissouriColumbiaMissouriUSA

Understanding complex biological pathways,including gene–gene interactions and gene regulatory networks,is critical for exploring disease mechanisms and drug *** literature curation of biological pathways cannot keep up with the exponential growth of new discoveries in the ***-scale language models(LLMs)trained on extensive text corpora contain rich biological information,and they can be mined as a biological knowledge *** study assesses 21 LLMs,including both application programming interface(API)-based models and open-source models in their capacities of retrieving biological *** evaluation focuses on predicting gene regulatory relations(activation,inhibition,and phosphorylation)and the Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway *** indicated a significant disparity in model ***-based models GPT-4 and Claude-Pro showed superior performance,with an F1 score of 0.4448 and 0.4386 for the gene regulatory relation prediction,and a Jaccard similarity index of 0.2778 and 0.2657 for the KEGG pathway prediction,***-source models lagged behind their API-based counterparts,whereas Falcon-180b and llama2-7b had the highest F1 scores of 0.2787 and 0.1923 in gene regulatory relations,*** KEGG pathway recognition had a Jaccard similarity index of 0.2237 for Falcon-180b and 0.2207 for *** study suggests that LLMs are informative in gene network analysis and pathway mapping,but their effectiveness varies,necessitating careful model *** work also provides a case study and insight into using LLMs das knowledge *** code is publicly available at the website of GitHub(Muh-aza).

关键词： biomedical text mining gene-gene interaction KEGG pathway large language model

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Open-Source Online Mission-Planning in Emergent Environments with PDDL for Multi-robot Applications 13th

Open-Source Online Mission-Planning in Emergent Environments...

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13th Mining Humanistic Data Workshop, MHDW 2024, 9th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2024 and 1st Workshop on AI in Applications for Achieving the Green Deal Targets, AI4GD 2024 held as parallel events of the IFIP WG 12.5 International Workshops on Artificial Intelligence Applications and Innovations, AIAI 2024

作者： Michailidis, Iakovos T. Michailidis, Panagiotis Kosmatopoulos, Elias Bassiliades, Nick Information Technologies Institute Thessaloniki Greece Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece School of Informatics Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (纸本)9783031632266

The current study focuses on the development of an open-source framework which is outsourcing the lack of expressivity of the standardized Planning Domain Definition Language – PDDL, leveraging the capacity and flexibility of the hosting environment in Python 3.8. The implementation was based on the definition and logic of a PDDL domain modeling an object stacking/collecting problem, in specified order and locations, by a fleet of autonomous synergetic vehicles by a centralized management agent. A PDDL-parser was utilized to instantiate the solver. Random changes were imposed in the fully-observable environment during mission execution. The proposed framework considered dynamic replanning of the currently valid mission, every time the state space – and consequently the corresponding state graph representation – is stochastically changed. Appropriate test scenarios were defined, to validate the capacity of the implemented framework and establish that it could serve as an interoperable and extensible foundation for other add-ons and graph-searching tools. The evidence from the simulation results indicates the speed and flexibility of the implemented environment for emulating the dynamic replanning problems in highly emergent scenario cases where the state space changes stochastically. © IFIP International Federation for Information Processing 2024.

关键词： Autonomous agents

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