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Optimization of Building Construction Control System Based on Nonlinear Image Enhancement

computer-Aided Design and Applications 2023年 20卷 213-224页

作者： Liu, Congru Lin, Mingsen Ghafoor, Kayhan Zrar Al-Dabagh, Mustafa Zuhaer Nayef Karras, Dimitrios A. School of Urban Construction Wuhan University of Science and Technology Wuhan China Changjiang Polytechnic Wuhan China Department of Computer Science Knowledge University Erbil44001 Iraq Department of Software & Informatics Engineering Salahaddin University-Erbil Erbil44001 Iraq School of Science Dept. General Athens Greece

To reflect the nonlinear characteristics of the building structural adjustment system, an active vibration control strategy based on the nonlinear is proposed. In this method, the size of the structural control force is determined by comparing the allowable energy with the actual energy, and its direction is determined by taking the derivative of the energy. Because there is no need to solve the linear matrix inequality, the calculation is simple and the operation is convenient. Moreover, when multiple actuators with the same capacity limit are used, the control output force is consistent, thus avoiding the design of multiple control systems and simplifying the controller design. The simulation results show that the maximum controlled displacements of floor 6 to floor 8 are 1.16cm, 1.12cm, and 0.97cm, respectively. The proposed nonlinear energy control method has the advantages of simple control process and avoiding actuator saturation. © 2023 CAD Solutions, LLC.

关键词： Floors

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Integrating Multimodal Contrastive Learning and Cross-Modal Attention for Alzheimer's Disease Prediction in Brain Imaging Genetics

Integrating Multimodal Contrastive Learning and Cross-Modal ...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Zhou, Rong Zhou, Houliang Shen, Li Chen, Brian Y. Zhang, Yu He, Lifang Lehigh University Department of Computer Science and Engineering BethlehemPA United States University of Pennsylvania Department of Biostatistics Epidemiology and Informatics PhiladelphiaPA United States Lehigh University Department of Bioengineering BethlehemPA United States

ISBN: (纸本)9798350337488

High annotation costs serve as a significant hurdle in deploying modern deep learning architectures for clinically relevant medical applications, especially when dealing with the inherent heterogeneity of multimodal data, proving the critical need for innovative algorithms that can effectively utilize unlabeled data. In this paper, we propose a model named MCLCA, which integrates multimodal contrastive learning and cross-modal attention to diagnose Alzheimer's Disease (AD) and identify biomarkers using both labeled and unlabeled multimodal brain imaging genetics data. Through multimodal contrastive learning, MCLCA can effectively learn representations even in the absence of sufficient labels. By utilizing cross-modal attention blocks, the model captures deep connections between different modalities, providing a more comprehensive view of diagnosis. Our proposed MCLCA model is evaluated using the ADNI database with three imaging modalities (VBM-MRI, FDG-PET, and AV45-PET) and genetic SNP data. The results demonstrate that MCLCA can identify important biomarkers with better prediction accuracy compared to the existing methods. The source code is available at https://***/MCLCA. © 2023 IEEE.

关键词： Alzheimer's disease Brain imaging genetics contrastive learning cross-modal attention

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Cost-Effective HWIL testing methodology for SALS guided missiles

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Materials Today: Proceedings 2022年 62卷 2509-2515页

作者： Todi, Ivana Kuzmanovi, Vladimir University of Belgrade Faculty of Mechanical Engineering Weapon Systems Department Kraljice Marije 16 Belgrade 11120 Serbia University of Belgrade Faculty of Mathematics Department for Computer Science and Informatics Studentski Trg 16 Belgrade 11000 Serbia

Verifying a new missile design requires a series of successful real-life tests on a firing range in various scenarios. Such an approach is extremely expensive and requires complex infrastructure and logistics. The costs of developing a new missile design can be significantly reduced by applying extensive and well thought out laboratory testing prior to any real-life test. Laboratory tests such as Hardware-In-The-Loop (HWIL) simulation enable the missile to be tested in a controlled environment inside a laboratory. HWIL testing methodology enables engineers to test the missile or its components in various simulated scenarios that correspond to real-life flights. Usually, a five-axis motion platform is used to perform HWIL simulation of terminal guidance. Three inner axes of the five-axis motion platform are used for simulation of the missiles body angles, while the two outer axes are used for simulation of the target movement relative to the missile. Such an approach requires spacious laboratories and expensive equipment. In this paper, we present a cost-effective HWIL testing methodology for Semi-Active-Laser-Seeker (SALS) guided missiles. The presented methodology requires only a three-axis motion platform and a fixed laser source. In the paper, we propose a two-stage HWIL testing procedure. In the first stage, the INS algorithm, guidance algorithm and autopilot algorithms are verified. In the second stage of the proposed HWIL testing methodology, the terminal guidance algorithm based on SALS angles is verified. Besides the HWIL testing methodology, we present the guidance law used in the testing procedure as well as the design of intercommunication between all the devices required to perform the tests. Next, the obtained results after each stage of the proposed HWIL testing methodology are presented and analyzed. Finally, a conclusion is drawn and limitations of the proposed testing methodology are explained. © 2020

关键词： Embedded systems

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Prediction of the Effect of Electrical Defibrillation Based on the Wavelet Transform with Pseudo-Differential Operators 5

Prediction of the Effect of Electrical Defibrillation Based ...

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5th International Conference on Electrical, Control and Instrumentation engineering, ICECIE 2023

作者： Yoshikawa, Yuta Okai, Takayuki Oya, Hidetoshi Hoshi, Yoshikatsu Nakano, Kazushi Tokyo City University Graduate School of Integrative Science and Engineering Tokyo Japan Tokyo City University Department of Computer Science Tokyo Japan The University of Electro-Communications Graduate School of Informatics and Engineering Tokyo Japan

ISBN: (纸本)9798350325041

This paper proposes a prediction system of the effect of electrical defibrillation based on the wavelet transform with pseudo-differential operators. To construct this system first, we analyze and extract features from pre-shock (before defibrillation) ECGs (ElectroCardioGrams) by using Gabor wavelet transform with pseudo-differential operators. Next, the effective feature parameters are selected based on the ?2 test. Finally, this system predicts two states such as "Effective"and "Ineffective"defibrillation by using the SVM (Support Vector Machine). In this way, we show the effectiveness of the proposed feature extraction method and prediction system. © 2023 IEEE.

关键词： Wavelet transforms

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Overview of Image Detection Algorithms: Performance Analysis and Technology Trends

Overview of Image Detection Algorithms: Performance Analysis...

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International Conference on informatics and Computing (ICIC)

作者： Nurul Hidayat R. Rizal Isnanto Department of Informatics Jenderal Soedirman University Purwokerto Indonesia Department of Computer Engineering Diponegoro University Semarang Indonesia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

Image detection plays a vital role in digital image processing and artificial intelligence, with applications ranging from security surveillance to autonomous vehicles and medical image analysis. This study employs a qualitative approach to review the performance of image detection algorithms, focusing on deep learning methods such as YOLO, SSD, and CNN. Through computational experiments using quantitative data, this research provides performance comparisons based on accuracy, precision, recall, and computational efficiency. The results highlight YOLO’s superior performance in terms of both accuracy ($\mathbf{9 2} .5 \%$) and inference speed (75.2 fps), making it suitable for real-time applications. This study contributes by addressing the gap in balancing computational efficiency and adaptability for real-world applications.

关键词： YOLO Deep learning Machine learning algorithms Accuracy Computational modeling Real-time systems Inference algorithms Computational efficiency Detection algorithms Edge computing

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Distraction Detection in Driving Using Pose Extraction and Machine Learning Techniques 7

Distraction Detection in Driving Using Pose Extraction and M...

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7th International Conference on Information Technology, Information Systems and Electrical engineering, ICITISEE 2023

作者： Bachtiar, Fitra Abdurrachman Arwani, Issa Prasetyo, Ridwan Aji Budi Pangestu, Gusti Soetedjo, Riza Setiawan Mahesa, Al Ravie Muthiar Brawijaya University Informatics Engineering Department Malang Indonesia Brawijaya University Information System Department Malang Indonesia Brawijaya University Psychology Department Malang Indonesia School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798350382266

There are a lot of technologies have been implemented in the modern cars these days, ranging from preventive braking system to driving assistance. It is believe that equipping car with modern technology would enhance safety. However, there are other aspects need to be considered in safety driving, that is human factor. Human factors are believed have high contribution in road accidents. Human factors such as emotional control and distraction may leads to dangerous driving behaviours. This study investigates the driver pose distraction. The distracted driver pose detected through pose detection using landmark feature extraction. The dataset used in this study is State Farm Distracted Driving Detection which is a secondary dataset. The extracted driver pose are in numeric form and used as the input for the classification model to detect ten kinds of driving distraction ranging from safety driving to talking to passenger. Four classifiers used to detect distracted driver are CatBoost, Decision Tress, Random Forest and SVM. The model performance evaluated using Precision, Recall, Accuracy, and F1-score. Furthermore, prediction time recorded to determine the best model to detect driver distraction. The results shows that CatBoost model outperformed all other model with F1-score and prediction time of 0.899 and 0.014 second. Random Forest model performance is the second highest compared to four other with F1-score and prediction time of 0.881 and 0.028 seconds. CatBoost model is the best model even though Cat Boost model execution time is not the highest and the model performance is not significantly different compared to Random Forest. © 2023 IEEE.

关键词： Extraction

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Area-Delay Efficient Security Scheme for Smart Hospital Systems

Area-Delay Efficient Security Scheme for Smart Hospital Syst...

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Cyber Security and Resilience (CSR), IEEE International Conference on

作者： Kyriaki Tsantikidou Dimitrios Boufeas Nicolas Sklavos Computer Engineering and Informatics Department SCYTALE Group University of Patras Hellas Electrical and Computer Engineering Department University of Patras Hellas

In recent years, traditional Hospital facilities are adopting new technologies. Smart Hospitals mostly utilize the Internet of Things (loT) technology due to its vast capabilities in connectivity. This loT network requires specific protocols for proper functionality. Message Queuing Telemetry Transport (MQTT) protocol is suitable for managing the communication and routing procedures of the resource constrained loT environment. Nevertheless, both MQTT and loT have various vulnerabilities and threats that must first be addressed. In this paper, a lightweight key management procedure is analyzed, an end-to-end payload encryption method is followed, and a processor with different cryptographic mechanisms is implemented. This combination of processes best complements the E-Health-based Hospital architecture, requiring minimum resources and complete security. The proposed crypto processor efficiently implements three different cryptographic primitives in a RISC- V architecture, providing flexibility. It achieves the best area-delay compared to other hardware-based security schemes, with 61.3% resource reduction and minimum added computation overhead. This is accomplished due to proper formatting of specific instructions and a function, operation and register sharing methodology.

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What Appears Suboptimal May Surprise You: A Fixed-Rate Scheduling Policy for Geo-Distributed CoFlows 29

What Appears Suboptimal May Surprise You: A Fixed-Rate Sched...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Liu, Haoyu Ding, Feiyan Wang, Yao Xiang, Qiao Shu, Jiwu Du, Haizhou Kong, Linghe Liu, Xue Xiamen University School of Informatics Xiamen China University of Electric Power of Shanghai School of Computer Science and Technology Shanghai China Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai China McGill University School of Computer Science Montreal Canada

ISBN: (纸本)9798350330717

All existing coflow scheduling algorithms compute dynamic-rate schedules that change the rates of flows during transmission. In this paper, we make a crucial finding: although dynamically adjusting the rates of flows could lead to a better coflow completion time (CCT) in theory, it would introduce additional pressures on the congestion control mechanism in the underlying network, which result in poor CCT in practice. This difference between theoretical CCT and practical CCT is further exacerbated in wide-area networks, where the topology does not provide any bisection guarantee as data center networks do. To this end, we designed a fixed-rate coflow scheduling policy called FSCO. Although in theory, the best fixed-rate schedule is usually suboptimal, it keeps the in-flight traffic relatively steady, reducing the risk of triggering congestion control. The core of FSCO is an efficient scheduling algorithm based on the classic network utilization maximization (NUM) framework. We implement a prototype of FSCO and evaluate its performance extensively using real-world topologies and coflow traces. Experimental results show that the total CCT reduces up to 30% compared to baselines while yielding up to 12× speedups compared to the solver. © 2023 IEEE.

关键词： Coflow Scheduling Dual decomposition Network Utility Maximization

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Non-invasive Face Registration for Surgical Navigation

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Journal of Computing Science and engineering 2022年第4期16卷 211-221页

作者： Kang, Seungwoo Kim, Hyeonjun Park, Taeyong Lee, Jeongjin Song, Hyunjoo School of Computer Science and Engineering Soongsil University Seoul Korea Republic of R&D Department INKA Entworks Seoul Korea Republic of Department of Biomedical Informatics Hallym University Medical Center Dongtan Korea Republic of

This study aims to propose a precise rigid-body face registration method that does not require an invasive marker attachment for surgical navigation devices. The non-invasive face registration involved the following steps: anatomical feature points such as the eyes and nose are found from the computed tomography (CT) image and the location tracking device attached to the patient's forehead prior to the procedure;an initial registration is attempted on the two previously extracted feature points;secondary registration was performed using a coherent point drift (CPD) algorithm;and using the Powell method, precise registration was performed to minimize the closest point registration error (CPRE). The CPRE co-registration accuracy was measured for the original and sampled phantom data, and the error was found to be 1.07 mm on average for skin coordinate data. The method introduced in this study enabled precise rigid-body face registration in a non-invasive manner using only skin coordinates. © (2022) The Korean Institute of Information Scientists and Engineers.

关键词： computerized tomography

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Compressing Time Series Towards Lightweight Integrity Commitments 8

Compressing Time Series Towards Lightweight Integrity Commit...

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8th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2023

作者： Katsika, Angeliki Papageorgiou, Konstantinos Fakis, Alexandros Kakarountas, Athanasios Andritsopoulos, Fotis Plagianakos, Vassilis Spathoulas, Georgios University of the Aegean Department of Information and Communication Systems Engineering Samos Greece ITrack Athens Greece University of Thessaly Department of Computer Science and Biomedical Informatics Lamia Greece Department of Information Security and Communication Technology Gjovik Norway

ISBN: (纸本)9798350383676

In the current era of big data, the generation and preservation of time series data has seen widespread adoption in various sectors such as trade, healthcare, and industry. At the same time, data have become a prized asset, as we are witnessing an unprecedented explosion in the volume of data generated and collected. This includes data from various sources, such as sensors, social media, and transactions, offering a competitive edge to organizations that harness the power of data, leading them to informed decisions and rapid responses to changing conditions. However, it is essential to responsibly manage data, addressing privacy and security concerns to ensure their integrity and availability, while efficiently managing the cost of storage and operations. To address these challenges, there is a compelling de-mand for methods that compress these time series while ensuring that the compressed versions faithfully represent the original data and remain secure against tampering or unauthorized alterations. This paper introduces a novel approach to condensing time-series data into lightweight integrity commitments, leveraging polynomial vector commitments as a key component. These integrity commitments are integrated with blockchain technology, serving as a cornerstone in guaranteeing data integrity and authenticity, particularly in supply chain scenarios where trust and transparency are of the utmost importance. © 2023 IEEE.

关键词： Time series

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