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Proceedings of the 7th International Conference on Sustainable Information engineering and Technology

作者： Nadi Rahmat Endrawan Barlian Henryranu Prasetio Rizal Maulana Computer Engineering Brawijaya University Indonesia Faculty of Computer Science University of Brawijaya Indonesia Faculty of Computer Science Brawijaya University Indonesia

ISBN: (纸本)9781450397117

Every year, Indonesians still suffer from heart and lung diseases. To anticipate many lethal effects caused by these diseases, an early diagnosis solution is needed. This research discusses the implementation of a heart and lung auscultation monitoring system that aims to facilitate doctors in diagnosing patients. The system has three main components: sampler, signal conditioner, and interface. The sampler samples the signal with a period of 250 μs which is also the deadline of task completion in the system. The signal conditioner will filter the signal according to the doctor's wishes with a choice of two modes (heart and lung). Then the interface can display heart rate (HR) or respiration rate (RR) parameters according to the selected mode and other features such as sound output and signal visualization. The test results show that the system completes the task faster than the deadline with an average of each sampler, signal conditioner, and interface: 21.6 μs, 185.13 μs, and 122.62 μs. There is an increase in the signal-to-noise ratio value of both filters after filtering with a value of 35.05 for the heart and 23.64 for the lungs. Finally, the performance of the Smoothed Z score algorithm in predicting HR and RR gives an accuracy of 94% and 82%.

关键词： Auscultation respiration rate heart rate Smoothed Z Score FIR Filter

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Brain Drug Effect Detection on Impulsivity with Ensemble Bagged Trees Method 7

Brain Drug Effect Detection on Impulsivity with Ensemble Bag...

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7th IEEE International Conference of computer science and Information Technology, ICOSNIKOM 2023

作者： Rahajoe, Ani Dijah Wibowo, Alvito Dwinovan Agussalim Aisyah, Siti Sitanggang, Delima Turnip, Arjon Universitas Pembangunan Nasional Department of Computer Science Indonesia Universitas Padjadjaran Depertment of Electrical Engineering Sumedang Indonesia Universitas Pembangunan Nasional Department of Computer Science Indonesia Universitas Prima Indonesia Faculty of Sciences and Technology Medan Indonesia Universitas Padjadjaran Department of Electrical Engineering Sumedang Indonesia

ISBN: (纸本)9798350360752

The rise of drug trafficking and abuse is something that must be addressed immediately. The impact caused is quite damaging because it can interfere with brain performance, and cause addiction to death. Methods for drug detection using medical methods have been widely practiced, but using non-medical technology is still quite rare. In this study, drug detection is performed using brain waves obtained from electroencephalography signal with the proposed Ensemble Bagged Trees (EBT) classifier. Experimental trials were conducted on 40 subjects in one of the prisons in West Java. Extraction and classification results using EBT with 93.8% accuracy were obtained. These results indicate the potential of the proposed technology to be used for drug detection. © 2023 IEEE.

关键词： Electroencephalography

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A Lumped Element Method for Acoustoelectric Imaging Reconstruction: A Numerical Study

A Lumped Element Method for Acoustoelectric Imaging Reconstr...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Tan, Rick Hao McDermott, Conor Rossa, Carlos Ontario Tech University Faculty of Engineering and Applied Science Oshawa Canada Carelton University Systems and Computer Engineering OttawaON Canada

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Acoustoelectric impedance tomography (AET) is a new non-invasive medical imaging procedure used to map the electrical properties of biological tissues with higher spatial resolution than traditional electrical impedance tomography (EIT). It exploits the acoustoelectric effect where modulated ultrasonic pressure changes the local tissue conductivity. This provides additional information to reconstruct a tomographic image, and has a stabilizing effect on an otherwise highly unstable inverse *** this paper, a novel approach to solving the AET inverse problem for image reconstruction is proposed. In the algorithm, the acoustoelectric effect is assumed to create small perturbations in the local resistance of the medium under observation. A lumped model consisting of a finite mesh of resistors approximates the medium under observation, through which boundary voltage differences between the excited and unexcited medium are calculated. A variation of the Modified Newton Raphson (MNR) algorithm is then proposed, where each pattern in the algorithm is created from small perturbations of the tissue conductivity. A total of eight simulation scenarios are evaluated, where the conductivity perturbations are in the order of 1%, 2.5% to 5% of the nominal tissue conductivity. The algorithm can successfully reconstruct the images in the presence of random noise. The obtained images are compared against traditional EIT where the percentage error is calculated for each simulated tomographic image. The simulation results indicate that the proposed approach is superior to traditional EIT as it constructs more distinct and high contrasting images with less percentage error. © 2022 IEEE.

关键词： Inverse problems

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A Review of Algorithms's Complexities on Different Valued Sorted and Unsorted Data

A Review of Algorithms's Complexities on Different Valued So...

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2023 International Conference on IT and Industrial Technologies, ICIT 2023

作者： Shabbir, Attia Majeed, Asad Iftikhar, Mahnoor Ali, Raja Hashim Arshad, Usama Shabbir, Muhammad Zeeshan Zeeshan Ijaz, Ali Ali, Nisar Aftab, Ali Gik Institute of Engg. Sciences & Technology Faculty of Computer Science & Engineering Topi Pakistan University of Europe for Applied Sciences Dept. of Technology & Software Engineering Berlin Germany Department of Electrical Engineering Lahore Pakistan University of Regina Faculty of Electronic Systems Engineering Regina Canada

ISBN: (纸本)9798350315974

Sorting and searching are critical processes for effecttive data analysis. In this paper, we evaluate the performance of various sorting and searching algorithms and compare their time and space complexities on both sorted and unsorted data. The algorithms we analyzed include six common sorting algorithms (insertion, radix, bucket, merge, bubble, and quick sort) and three search algorithms (linear, binary, and jump search). The results of our study provide insights into the best algorithms to use for different input sizes and types of data. It was found that for small input sizes, all algorithms perform similarly, but for larger input sizes, insertion and radix sorts are better for time complexity while bubble sort is better for space complexity. Additionally, jump search outperformed linear and binary search algorithms in both time and space complexity. Besides, difference between time and space complexity of sorted and unsorted data was significant. © 2023 IEEE.

关键词： Computational complexity

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Movement Impacts on Eyeblink Detection Using FMCW Radar 9

Movement Impacts on Eyeblink Detection Using FMCW Radar

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9th IEEE Smart World Congress, SWC 2023

作者： Zhang, Xinze Brahim, Walid Ma, Jianhua Apduhan, Bernady O. Hosei University Graduate School of Computer and Information Sciences Tokyo184-8584 Japan Kyushu Sangyo University Faculty of Science and Engineering Department of Information Science Fukuoka813-0004 Japan

ISBN: (纸本)9798350319804

Eyeblink detection is essential for assessing physiological and psychological states in various applications. Radar technology offers a promising solution for non-intrusive and reliable eyeblink detection. This ongoing work investigates the effects of movements on eyeblink detectability using FMCW radar. The proposed methodology relies on the use of Adaptive Variational Mode Decomposition algorithm (AVMD) for blink signal extraction. Extensive experiments were performed to assess the performance under challenging conditions, analyzing the influence of body, head, and mouth movements on blink detectability. An in-depth analysis of movement impacts, identification of underlying reasons, and potential mitigation strategies is presented. This research provides a comprehensive evaluation, useful for the next step of research to provide a more reliable radar-based blink detection solution. © 2023 IEEE.

关键词： AVMD body Eyeblink FMCW radar head mouth movement impact

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Price Prediction of Seasonal Items Using Time Series Analysis

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computer Systems science & engineering 2023年第7期46卷 445-460页

作者： Ahmed Salah Mahmoud Bekhit Esraa Eldesouky Ahmed Ali Ahmed Fathalla Faculty of Computers and Informatics Zagazig UniversitySharkeya44523Egypt Information Technology Department the University of Technology and Applied SciencesIbriOman School of Electrical and Data Engineering University of Technology SydneySydney2007Australia College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Computer Science Department Faculty of Computers and InformaticsSuez Canal UniversityIsmailia41522Egypt Higher Future Institute for Specialized Technological Studies Cairo3044Egypt Department of Mathematics Faculty of ScienceSuez Canal UniversityIsmailia41522Egypt

The price prediction task is a well-studied problem due to its impact on the business *** are several research studies that have been conducted to predict the future price of items by capturing the patterns of price change,but there is very limited work to study the price prediction of seasonal goods(e.g.,Christmas gifts).Seasonal items’prices have different patterns than normal items;this can be linked to the offers and discounted prices of seasonal *** lack of research studies motivates the current work to investigate the problem of seasonal items’prices as a time series *** proposed utilizing two different approaches to address this problem,namely,1)machine learning(ML)-based models and 2)deep learning(DL)-based ***,this research tuned a set of well-known predictive models on a real-life *** models are ensemble learning-based models,random forest,Ridge,Lasso,and Linear ***,two new DL architectures based on gated recurrent unit(GRU)and long short-term memory(LSTM)models are ***,the performance of the utilized ensemble learning and classic ML models are compared against the proposed two DL architectures on different accuracy metrics,where the evaluation includes both numerical and visual comparisons of the examined *** obtained results show that the ensemble learning models outperformed the classic machine learning-based models(e.g.,linear regression and random forest)and the DL-based models.

关键词： Deep learning price prediction seasonal goods time series analysis

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A 60 GHz and 2.08 mW Active Quasi-Circulator in 22 nm FDSOI Technology 66

A 60 GHz and 2.08 mW Active Quasi-Circulator in 22 nm FDSOI ...

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2023 IEEE 66th International Midwest Symposium on Circuits and Systems, MWSCAS 2023

作者： Chowdhury, Sujan Chakraborty, Arindom Joy, Upal Barna Fahim, Abrar Chowdhury, Muhtasim Alam Hasan, Mehedi Technical University of Dresden Faculty of Electrical and Computer Engineering Dresden Germany University of Science and Technology Chittagong Depertment of Electrical and Electronic Engineering Chattogram Bangladesh New York University Depertment of Electrical and Computer Engineering New York United States University of Arizona Depertment of Electrical and Computer Engineering Arizona United States University of Maryland Depertment of Electrical and Computer Engineering College ParkMD United States

ISBN: (纸本)9798350302103

In recent years, circuit design of high-frequency active quasi-circulator for full-duplex wireless systems have attracted wide attention in the area of Microwave and Radio Frequency (RF) circuits. This paper presents the design of an active quasi-circulator intended for operation in the 60 GHz Industrial, Scientific, and Medical (ISM) radio band, employing 22nm FD-SOI technology. The goal is to achieve a low noise figure, superior isolation, and a high-power handling capability, as measured by the 1 dB compression point. The quasi-circulator design incorporates a Wilkinson power divider and low noise amplifier, yielding a noise figure of 7 dB, 18 dBm power handling, 20 dB isolation, and 2.08 mW power consumption. © 2023 IEEE.

关键词： active circulator circulator isolation quasi-circulator Wilkinson divider

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Simulation of the Quasigroup Redundancy Check Code’s Ability to Detect Errors 16th

Simulation of the Quasigroup Redundancy Check Code’s Abil...

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16th International Conference on ICT Innovations, ICT Innovations 2024

作者： Ilievska, Natasha Faculty of Computer Science and Engineering Ss. Cyril and Methodius University Skopje Macedonia

ISBN: (纸本)9783031861611

This paper contains experimental results for one important parameter of a code for error detection. The considered code is previously defined. In the definition of the check symbols is used algebraic structure quasigroup. In this paper will be considered the case when for coding are used quasigroups of order 8 for which the code has smallest probability of undetected errors. Namely, using simulations we will obtain experimental results for the largest number of erroneous bits up to which the code is guaranteed to detect errors when such quasigroup is used for coding. Since all these quasigroups are linear, we will conclude whether the free term has an influence on the value of this parameter. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Error detection

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SMGC-SBERT: A Multi-Feature Fusion Chinese Short Text Similarity Computation Model Based on Optimised SBERT

SMGC-SBERT: A Multi-Feature Fusion Chinese Short Text Simila...

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

作者： Zhao, Shuo Gu, Qiliang Zhang, Jianqiang Song, Gongpeng Lu, Qin Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Shandong Branch of China Mobile Communication Group Design Institute Co. Jinan China

ISBN: (纸本)9781665410205

Chinese short text similarity computation stands as a pivotal task within natural language processing, garnering significant attention. However, existing models grapple with limitations in handling intricate semantic relationships, such as the challenge of discerning subtle semantic nuances in text, inadequacies in effectively integrating diverse levels of semantic information, and the struggle to capture polysemous meanings accurately. In addressing these issues, this paper introduces an innovative Chinese short text similarity computation model, SMGC-SBERT. This model addresses shortcomings of the existing models by employing a multi-module fusion strategy, thereby enabling a more precise measurement of semantic similarity between texts. Primarily, the model incorporates SAT embedding to acquire phrase-level semantic information and leverages the MS-BERT model to encode text, improving the model's comprehension of textual polysemy and obtaining richer semantic representation. Then, the fusion of module features, including multi-branch convolutional networks and mix pooling, enables the extraction of textual features from varied levels, bolstering the model's representational capacity. Additionally, to further reduce overfitting risks while improving accuracy and other performance, a multi-layer feature adjustment network is utilized for short text similarity calculation. The final resultant experimental findings showcase the superiority of the SMGC-SBERT model over other neural network models, demonstrating significant advancements across both Chinese-SNLI and CCKS2018_Task3 Chinese short text datasets. © 2024 IEEE.

关键词： Semantics

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A Rule-Based Deep Learning Method for Predicting Price of Used Cars 4th

A Rule-Based Deep Learning Method for Predicting Price of Us...

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4th International Conference on Machine Intelligence and Signal Processing, MISP 2022

作者： Ayo, Femi Emmanuel Awotunde, Joseph Bamidele Misra, Sanjay Ajagbe, Sunday Adeola Mishra, Nishchol Department of Computer Science McPherson University Seriki-Sotayo Abeokuta Nigeria Department of Computer Science Faculty of Information and Communication Sciences University of Ilorin Ilorin240003 Nigeria Department of Computer Science and Communication Ostfold University College Halden Norway Department of Computer Engineering Ladoke Akintola University of Technology Ogbomoso Nigeria Rajiv Gandhi Technical University Bhopal India

ISBN: (纸本)9789819900466

The growth of internet used automobile shopping has been tremendous in recent years. It is important for sellers to correctly evaluate the price of the used cars. From the literature, classification is an approach that assists in data interpretation by analyzing data and providing a second opinion on data among other tasks most of the classifiers used for car price prediction suffered from lower accuracy ratios and higher error ratios. In this work, a hybrid feature selection model for predicting the price of used cars was developed. The developed model includes a CfsSubsetEval to determine the best feature subset, rule-based GA to search for the best solution, and a neural network for the final price prediction based on the selected features. The developed model was implemented in a Java programming language. The evaluation showed that the developed hybrid feature selection model achieved better performances with the correlation coefficient, mean absolute error and root mean square error of 0.9818, 1.1809, and 1.5643 respectively, compared to other related state-of-the-art algorithms. The results validated the efficiency of the developed model for used car price prediction. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Java programming language

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