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High-Throughput Independent Component Analysis Processor for Full Duplex Systems

IEEE Journal on Selected Areas in Communications 2023年第9期41卷 2821-2832页

作者： Cheng, Jen-Hao Chang, Tien-Min Shen, Chung-An Fouda, Mohammed E. Eltawil, Ahmed M. National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taipei10607 Taiwan University of California at Irvine Electrical Engineering and Computer Science Department IrvineCA92697 United States King Abdullah University of Science and Technology Electrical and Computer Engineering Program Thuwal23955 Saudi Arabia

This paper presents the algorithm and very-large-scale integration (VLSI) architecture of a high-throughput and highly efficient independent component analysis (ICA) processor for self-interference cancellation (SIC) in in-band full-duplex (IBFD) systems. This is the first VLSI architecture reported in the literature based on the state-of-the-art entropy bound minimization (EBM) approach. A novel ICA algorithm is presented in this paper with momentum gradient descent optimization. Simulation results show that the number of iterations for the proposed algorithm is significantly reduced compared to the conventional ICA algorithms. Furthermore, a novel early-distribution estimation scheme is proposed in the designed ICA processor to compute multiple distribution functions with low latency and low complexity. The processing flow and the efficiency for the hardware utilization are specifically designed so that the processing speed is maximized with minimum employment of hardware components. The proposed ICA processor is designed and implemented based on the application-specific-integrated circuit (ASIC) flow. The post-layout estimations show that compared with the conventional EBM-based scheme, the proposed design improves the throughput and efficiency by 30x. In addition, compared to prior designs shown in the literature, the proposed ICA processor also demonstrates a significant enhancement in terms of throughput and efficiency. © 1983-2012 IEEE.

关键词： VLSI circuits

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Electronic-offering of fresh fruit bunches oil palm by independent farmer with a blockchain approach

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AIP Conference Proceedings 2025年第1期3223卷

作者： Harison Marimin Sukardi Faqih Udin Yani Nurhadriyani Engineer Professional Education Study Program Universitas Andalas Padang Indonesia - 25000 Department of Agro-industrial Technology Faculty of Agricultural Engineering and Technology IPB University Bogor Indonesia - 16680 Department of Computer Science Faculty of Mathematics and Natural Sciences IPB University Bogor Indonesia – 16680

Indonesia meets the needs of 50% of the world's palm oil needs. Sources of Indonesian palm oil, 34 % are produced by independent smallholders. The lack of governance of independent smallholders leads to low productivity of their crops. Global market demands for palm oil derivative sources become an obligation to compete. The development of blockchain technology that favors traceability and transparency is applied in the supply agriculture sector, and this is an opportunity for how blockchain technology can help the palm oil supply chain become transparent and can find its source. This research uses the system development life cycle (SDLC) method. And business process model and notation in business model design. The results of the design of the FFB sale and purchase transaction system with blockchain technology have succeeded in connecting farmer transactions as FFB providers with traders and PKS as FFB buyers. Every transaction sent by the farmer will be locked by a hash, as immunity makes the data sent immutable. The system can display the traceability of transactions while maintaining the integrity of member information.

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Optimal Deep Canonically Correlated Autoencoder-Enabled Prediction Model for Customer Churn Prediction

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computers, Materials & Continua 2022年第11期73卷 3757-3769页

作者： Olfat M.Mirza GJose Moses R.Rajender E.Laxmi Lydia Seifedine Kadry Cheadchai Me-Ead Orawit Thinnukool Department of Computer Science College of Computers and Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science Engineering Malla Reddy Engineering College500100India Department of Computer Science Engineering Lendi Institute of Engineering&TechnologyDenkada535005India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeNorway Program in Statistics and Information Management Faculty of ScienceMaejo UniversityChiang Mai50290Thailand Department of Modern Management and Information Technology College of Arts Media and TechnologyChiang Mai UniversityChiang Mai50200Thailand

Presently,customer retention is essential for reducing customer churn in telecommunication *** churn prediction(CCP)is important to predict the possibility of customer retention in the quality of *** risks of customer churn also get essential,the rise of machine learning(ML)models can be employed to investigate the characteristics of customer ***,deep learning(DL)models help in prediction of the customer behavior based characteristic *** the DL models necessitate hyperparameter modelling and effort,the process is difficult for research communities and business *** this view,this study designs an optimal deep canonically correlated autoencoder based prediction(ODCCAEP)model for competitive customer dependent application *** addition,the O-DCCAEP method purposes for determining the churning nature of the *** O-DCCAEP technique encompasses preprocessing,classification,and hyperparameter ***,the DCCAE model is employed to classify the churners or ***,the hyperparameter optimization of the DCCAE technique occurs utilizing the deer hunting optimization algorithm(DHOA).The experimental evaluation of the O-DCCAEP technique is carried out against an own dataset and the outcomes highlighted the betterment of the presented O-DCCAEP approach on existing approaches.

关键词： Churn prediction customer retention deep learning machine learning archimedes optimization algorithm

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Frequency modulation using digital sinusoidal oscillator

Frequency modulation using digital sinusoidal oscillator

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2012 9th International Conference on Electrical engineering/Electronics, computer, Telecommunications and Information technology, ECTI-CON 2012

作者： Punchalard, R. Nosan, A. Department of Telecommunication Engineering Mahanakorn University of Technology Bangkok Thailand Computer Engineering Graduate Program Faculty of Engineering Mahanakorn University of Technology Thailand

ISBN: (纸本)9781467320245

This paper presents an alternative method to generate the digital frequency modulation (FM) signal. By summing an information signal m(k) with the oscillating frequency ω0 and putting the result into the cosine function of digital oscillator coefficient which is -2 cos (ω0 +m(k)), the FM signal is obtained. computer simulations are conducted to show the validity of the proposed FM signal generator. © 2012 IEEE.

关键词： Frequency modulation

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The embedded development tools you did not have when growing up

The embedded development tools you did not have when growing...

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120th ASEE Annual Conference and Exposition

作者： Mondragon, Antonio Francisco Becker-Gomez, Adriana Bovalino III, Carmen A. Jones, Michael B. Brazil, Derrick Caldwell, Michael R. Electrical Computer and Telecommunications Engineering Technology Department Rochester Institute of Technology United States Computer Engineer Department Kate Gleason College of Engineering United States Department of Computer Engineering Technology Rochester Institute of Technology Rochester NY United States Department of Mechanical Engineering Technology Rochester Institute of Technology United States Computer Engineering Technology Program Rochester Institute of Technology United States Department of Electrical Engineering Rochester Institute of Technology United States

In this paper we give a broad overview of the embedded tools that engineering technology students at the Rochester Institute of technology (RIT) have been discovering and using for courses, laboratories, senior design and in their personal projects. By no means is this an extensive but a comprehensive list of embedded debugging tools used by students and faculty in our department. The important aspect is that in most of the cases, students have discovered these tools and integrated them into their toolboxes. Faculty and universities should also be on the lookout to integrate these tools into the curriculum by listening to students and their needs. © American Society for engineering Education, 2013.

关键词： Students

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Monitoring blood pressure through a single hybrid hemodynamic signal with a flexible optoelectronic patch

Device

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Device 2025年

作者： Zhong, Yizhou Zhang, Yongcao Pu, Jing Wustoni, Shofarul Uribe, Johana Lopez-Larrea, Naroa Marks, Adam McCulloch, Iain Mecerreyes, David Baran, Derya Inal, Sahika Organic Bioelectronics Laboratory Biological and Environmental Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Materials Science and Engineering Program (MSE) Physical Sciences and Engineering Division (PSE) KAUST Thuwal 23955-6900 Saudi Arabia POLYMAT University of the Basque Country UPV/EHU Avenida Tolosa 72 Guipuzcoa Donostia-San Sebastian 20018 Spain Department of Chemistry University of Oxford Oxford OX1 3TF United Kingdom Andlinger Center for Energy and the Environment and Department of Electrical and Computer Engineering Princeton University Princeton 08544 NJ United States IKERBASQUE Basque Foundation for Science Plaza Euskadi 5 Bilbao 48009 Spain

Hemodynamics, the study of blood flow and circulatory forces, is fundamental for assessing cardiovascular health, disease states, and therapeutic outcomes. Here, we introduce a skin-conformable organic optoelectronic thin-film patch (ePatch) designed to simultaneously capture electrocardiography (ECG) and photoplethysmography (PPG) signals as a single hybrid signal, named the electrocardio-photoplethysmogram (EC-PPG). The ePatch integrates an organic electrochemical transistor (OECT), an organic photodiode, surface-mounted light-emitting diodes, and electrochemical electrodes on a flexible, skin-conforming substrate. By training deep learning models on the hybrid EC-PPG data, we achieved accurate arterial blood pressure estimations, with mean errors of just 1.69 mmHg for systolic and 0.89 mmHg for diastolic blood pressure, outperforming traditional predictions that rely on individual physiological signals as inputs. Our findings underscore the potential of EC-PPG as a compound hemodynamic signal for AI-driven vital sign monitoring and integrated, solution-processable soft electronics for clinical and point-of-care applications. © 2025 The Authors

关键词： DTI-3: Develop electrocardiography electrophysiology flexible electronics OECT OPD organic electrochemical transistor photoplethysmography wearable electronics

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Empirical mode decomposition of near-infrared spectroscopy signals for predicting oil content in palm fruits

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Information Processing in Agriculture 2023年第3期10卷 289-300页

作者： Inna Novianty Ringga Gilang Baskoro Muhammad Iqbal Nurulhaq Muhammad Achirul Nanda Computer Engineering Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Informatics Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Technology and Plantation Production Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Department of Agricultural and Biosystem Engineering Faculty of Agro-Industrial TechnologyUniversitas PadjadjaranJatinangor 45363Indonesia

Oil content estimation in palm fruits is a precious property that significantly impacts oil palm production,starting from the upstream and *** content can be used to monitor the progress of the oil palm fresh fruit bunch(FFB)and be applied to identify product *** on the near-infrared(NIR)signals,this study proposes an empirical mode decomposition(EMD)technique to decompose signals and predict the oil content of palm ***,350 palm fruits with Tenera varieties(Elaeis guineensis ***),at various ages of maturity,were harvested from the Cikabayan Oil Palm Plantation(IPB University,Indonesia).Second,each sample was sent directly to the laboratory for NIR signal measurements and oil content ***,the EMD analysis and arti-ficial neural network(ANN)were employed to correlate the NIR signals and oil ***,a robust EMD-ANN model is generated by optimizing the lowest possible *** on performance evaluation,the proposed technique can predict oil content with a coefficient of determination(R2)of 0.933±0.015 and a root mean squared error(RMSE)of 1.446±*** results demonstrate that the model has a good predictive capacity and has the potential to predict the oil content of palm fruits directly,without neither solvents nor reagents,which makes it environmentally ***,the proposed technique has a promising potential to be applied in the oil palm *** like this will lead to the effective and efficient management of oil palm production.

关键词： Artificial neural network Empirical mode decomposition Oil palm Oil content prediction

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Teaching Abstraction to Novices: Pattern-Based and ADT-Based Problem-Solving Processes

Teaching Abstraction to Novices: Pattern-Based and ADT-Based...

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IEEE Frontiers in Education Conference 2008

作者： Haberman, Bruria Muller, Orna Computer Science Department Holon Institute of Technology Israel CS Academia and Industry Program Israel Science Education Department Computer Science Group Tel-Aviv University Israel Software Engineering Department Ort Braude College of Engineering Israel

ISBN: (纸本)9781424419692

is taught to computer-science students as part of a comprehensive curriculum. The students encounter the concept of abstraction in various contexts while learning the different modules, each of which emphasizes some specific aspects of the concept. In this paper we present two instructional approaches, both related to utilizing abstraction in problem-solving processes: (1) pattern-oriented instruction (POI), and (2) abstract data type (ADT)-oriented instruction. We present these methods with respect to their employment in teaching problem solving to novices, and elaborate on abstraction processes.

关键词： Abstraction algorithmic patterns abstract data types problem solving

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Absolute gradient algorithm for adaptive IIR notch filter

Absolute gradient algorithm for adaptive IIR notch filter

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2012 9th International Conference on Electrical engineering/Electronics, computer, Telecommunications and Information technology, ECTI-CON 2012

作者： Nosan, A. Punchalard, R. Computer Engineering Graduate Program Faculty of Engineering Mahanakorn University of Technology Bangkok Thailand Department of Telecommunication Engineering Mahanakorn University of Technology Bangkok Thailand

ISBN: (纸本)9781467320245

The gradient algorithm used absolute value of error signal as a criterion to adjust the filter coefficient of adaptive IIR notch filter is presented in this paper. The objective is to estimate or track the frequency of a single sinusoidal signal corrupted by additive white Gaussian noise. The proposed algorithm can solve the problem of selecting an initial condition as met in the previous method. Moreover, it also has a high convergence speed. © 2012 IEEE.

关键词： Notch filters

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Deep Semantic and Attentive Network for Unsupervised Video Summarization

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ACM Transactions on Multimedia Computing, Communications and Applications 2022年第2期18卷 1-21页

作者： Zhong, Sheng-Hua Lin, Jingxu Lu, Jianglin Fares, Ahmed Ren, Tongwei College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Electrical Engineering Computer Systems Engineering Program Faculty of Engineering at Shoubra Benha University Cairo Egypt State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China

With the rapid growth of video data, video summarization is a promising approach to shorten a lengthy video into a compact version. Although supervised summarization approaches have achieved state-of-the-art performance, they require frame-level annotated labels. Such an annotation process is time-consuming and tedious. In this article, we propose a novel deep summarization framework named Deep Semantic and Attentive Network for Video Summarization (DSAVS) that can select the most semantically representative summary by minimizing the distance between video representation and text representation without any frame-level labels. Another challenge associated with video summarization tasks mainly originates from the difficulty of considering temporal information over a long time. Long Short-Term Memory (LSTM) performs well for temporal dependencies modeling but does not work well with long video clips. Therefore, we introduce a self-attention mechanism into our summarization framework to capture the long-range temporal dependencies among the frames. Extensive experiments on two popular benchmark datasets, i.e., SumMe and TVSum, show that our proposed framework outperforms other state-of-the-art unsupervised approaches and even most supervised methods. © 2022 Association for Computing Machinery.

关键词： Semantics

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