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Multiple-Input Floating-Point Adders: A Comprehensive Review

IEEE Access 2025年 13卷 91012-91024页

作者： Haq, Sami Ul El-Maleh, Aiman H. Alsuwaiyan, Ali King Fahd University of Petroleum & Minerals Computer Engineering Department Dhahran Saudi Arabia King Fahd University of Petroleum & Minerals Interdisciplinary Research Center for Intelligent Secure Systems Dhahran Saudi Arabia

Floating-point addition is pivotal in various computational applications, including scientific computing, machine learning, and graphics processing. Traditional two-input floating-point adders (FPADD2) are widely used but become bottlenecks in scenarios requiring efficient multi-operand summation. The growing demand for high-performance computing has spurred interest in multiple-input floating-point adders (FPADDn), which simultaneously handle multiple operands to enhance throughput and reduce latency. This paper provides a comprehensive review of FPADDn architectures, exploring key design principles, implementation techniques, and challenges such as precision, hardware complexity, and rounding errors. Modern approaches leveraging hierarchical tree structures, parallelism, and pipelining are discussed, highlighting their advantages and trade-offs. © 2013 IEEE.

关键词： Floating-point adders Floating-point arithmetic High-performance computing Multiple-input floating-point adders

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Bagging System Performance Analysis Using Artificial Neural Network, Random Forest Regression, Linear Regression, and Support Vector Regression 1

Bagging System Performance Analysis Using Artificial Neural ...

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1st IEEE International Symposium on Consumer Technology, ISCT 2024

作者： Primantara, Ari Ciptomulyono, Udisubakti Al Kindhi, Berlian Interdisciplinary School of Management Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Industrial and Systems Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Electrical Automation Engineering Surabaya Indonesia

ISBN: (纸本)9798350365191

Agriculture is one of the most important sectors in the world because it provides commodities such as rice, cassava, corn, rubber, and palm oil. Urea fertilizer is essential for use in crops, and the demand for this product increases every year due to rapid globalization. Fertilizer firms must reduce production costs and product losses to remain competitive. This study introduces the use of machine learning to predict which algorithm could give the best result in predicting fertilizer weight losses. The algorithms studied were linear regression, artificial neural network, random forest regression, and support vector regression. The results show R2, MAE, and RMSE for each method. The R2 values for ANN, Random Forest, Linear Regression, and Support Vector Regression are 0.9509;0.9759;0.9507;and 0.9367, respectively. Random Forest shows the best result compared with the three other algorithms, implying that it is the most accurate algorithm for this research, followed by the supporting result MAE value of 0.0829, which is smaller than the other. © 2024 IEEE.

关键词： Support vector regression

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A Conjoint-based Approach on Determining the Factors Affecting on Preference of Subscribing a Netflix Plan

A Conjoint-based Approach on Determining the Factors Affecti...

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2024 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2024

作者： Park, Ji Yong Prasetyo, Yogi Tri Cahigas, Maela Madel L. Nadlifatin, Reny School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines International Bachelor Program in Engineering Yuan Ze University Taoyuan Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan Taiwan Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9798350386097

This study uses a conjoint analysis approach to determine the key factors influencing subscriber preferences for subscribing to Netflix plan. In a rapidly evolving industry, understanding the drivers of subscription choices is critical for market success. Through a designed survey, respondents are presented with different hypothetical Netflix subscription plans characterized by attributes such as price, resolution, same time watch device, downloadable device and device specs. By analyzing respondents' answers from these attributes, researchers aim to find out the relatedness of each attribute and levels with the subscription preference. The study's findings can help Netflix make more strategic decisions about plan options and pricing policies, so that it can better serve the wide range of demands and tastes of customers in the cutthroat streaming market. © 2024 IEEE.

关键词： Conjoint analysis Netflix streaming market subscription plan

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Deep Learning for Multivariate Prediction of Building Energy Performance of Residential Buildings

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Computers, Materials & Continua 2023年第6期75卷 5947-5964页

作者： Ibrahim Aliyu Tai-Won Um Sang-Joon Lee Chang Gyoon Lim Jinsul Kim Department of ICT Convergence System Engineering Chonnam National UniversityGwangju61186Korea Graduate School of Data Science Chonnam National UniversityGwangju61186Korea Interdisciplinary Program of Digital Future Convergence Service Chonnam National UniversityGwangju61186Korea Department of Computer Engineering Chonnam National UniversityYeosu59626Korea

In the quest to minimize energy waste,the energy performance of buildings(EPB)has been a focus because building appliances,such as heating,ventilation,and air conditioning,consume the highest ***,effective design and planning for estimating heating load(HL)and cooling load(CL)for energy saving have become *** this vein,efforts have been made to predict the HL and CL using a univariate ***,this approach necessitates two models for learning HL and CL,requiring more computational ***,the one-dimensional(1D)convolutional neural network(CNN)has gained popularity due to its nominal computa-tional complexity,high performance,and low-cost hardware *** this paper,we formulate the prediction as a multivariate regression problem in which the HL and CL are simultaneously predicted using the 1D *** the building shape characteristics,one kernel size is adopted to create the receptive fields of the 1D CNN to extract the feature maps,a dense layer to interpret the maps,and an output layer with two neurons to predict the two real-valued responses,HL and *** the 1D data are not affected by excessive parameters,the pooling layer is not applied in this ***,the use of pooling has been questioned by recent *** performance of the proposed model displays a comparative advantage over existing models in terms of the mean squared error(MSE).Thus,the proposed model is effective for EPB prediction because it reduces computational time and significantly lowers the MSE.

关键词： Artificial intelligence(AI) convolutional neural network(CNN) cooling load deep learning energy energy load energy building performance heating load prediction

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A Novel Hydroponic Based on Hybrid Renewable Energy System 6

A Novel Hydroponic Based on Hybrid Renewable Energy System

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6th International Symposium on Advanced Electrical and Communication Technologies, ISAECT 2024

作者： Ahmed, Abeer Khalid, Muhammad King Fahd University of Petroleum & Minerals Electrical Engineering Department Dhahran31261 Saudi Arabia Interdisciplinary Research Center for Sustainable Energy Systems King Fahd University of Petroleum & Minerals Electrical Engineering Department Dhahran31261 Saudi Arabia

ISBN: (纸本)9798331529987

Hydroponic farming, a soilless technique, has become increasingly popular and is considered the future of agriculture in water-deficient areas like Saudi Arabia. These regions tackle the challenge of cultivating fruits and vegetables with an automated hydroponic system. This system uses ozone filtration, is self-installed, and includes PV, DG, battery, converter, and AI for independent functioning. It employs ozonic methods to cleanse and filter water, eliminating the need for human intervention, and offers customizable options to accommodate various locations. The proposed hydroponic system will use sensors as input and output devices, run on a hybrid renewable energy system (HRES), and integrate water pumps, dosing pumps, and lighting sources. By integrating solar panels, batteries, converters, and a diesel generator (DG), the goal is to decrease CO2 emissions, water, and power usage, and utilize AI for disease detection. This cutting-edge system tackles multiple challenges in hydroponic agriculture, such as sporadic solar energy, efficient energy storage, converter performance, and diesel generator emissions, aiming to reduce energy wastage and emissions while maintaining dependable operation. The proposed design method assesses the energy needs for growing hydroponic lettuce, cutting down on water and energy usage by decreasing the water pump's running time to only 4 hours instead of 24 hours. This results in a 40% reduction in energy and cost savings with the ideal sizes of PV, battery, DG, and converter. The system, utilizing HOMER and GAMS software, presents cost and energy savings and operational expense reductions, offering advantages for business owners, agricultural enthusiasts, and individuals looking into agricultural investments. This system could boost local investment in agriculture and technology sectors, in line with Saudi Vision 2030. © 2024 IEEE.

关键词： Hydroponics

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Wet tissue adhesive polymeric powder hydrogels for skeletal muscle regeneration

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Bioactive Materials 2024年第10期40卷 334-344页

作者： Mingyu Lee Daun Seo Junggeon Park Sun Hong Lee Jin Jeon Woochan Kim Jangho Kim Hee Seok Yang Jae Young Lee School of Materials Science and Engineering Gwangju Institute of Science and TechnologyGwangju61005Republic of Korea Department of Nanobiomedical Science&BK21 FOUR NBM Global Research Center for Regenerative Medicine Dankook UniversityCheonan31116Republic of Korea Department of Convergence Biosystems Engineering Chonnam National UniversityGwangju61186Republic of Korea Department of Rural and Biosystems Engineering Chonnam National UniversityGwangjuRepublic of Korea Interdisciplinary Program in IT-Bio Convergence System Chonnam National UniversityGwangju61186Republic of Korea

Volumetric muscle loss(VML)frequently results from traumatic incidents and can lead to severe functional *** have been widely employed for VML tissue regeneration,which are unfortunately ineffective because of the lack of intimate contact with injured tissue for structural and mechanical *** hydrogels allow for strong tissue connections for wound ***,conventional adhesive hydrogels exhibit poor tissue adhesion in moist,bleeding wounds due to the hydration layer at the tissue–hydrogel interfaces,resulting in insufficient *** this study,we developed a novel,biocompatible,wet tissue adhesive powder hydrogel consisting of dextran-aldehyde(dex-ald)and gelatin for the regeneration of *** powder absorbs the interfacial tissue fluid and buffer solution on the tissue,spontaneously forms a hydrogel,and strongly adheres to the tissue via various molecular interactions,including the Schiff base *** particular,the powder composition with a 1:4 ratio of dex-ald to gelatin exhibited optimal characteristics with an appropriate gelation time(258 s),strong tissue adhesion(14.5 kPa),and ***-ald/gelatin powder hydrogels presented strong adhesion to various organs and excellent hemostasis compared to other wet hydrogels and fibrin glue.A mouse VML injury model revealed that the dex-ald/gelatin powder hydrogel significantly improved muscle regeneration,reduced fibrosis,enhanced vascularization,and decreased ***,our wet-adhesive powder hydrogel can serve as an effective platform for repairing various tissues,including the heart,muscle,and nerve tissues.

关键词： Powder Hydrogel Wet-adhesive Skeletal muscle regeneration

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Metasurfaces for next-generation wireless communication systems

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National Science Review 2023年第8期10卷 17-19页

作者： Younes Ra'di Nikita Nefedkin Petar Popovski Andrea Alù Department of Electrical Engineering and Computer Science Syracuse University Photonics Initiative Advanced Science Research Center City University of New York Department of Electronic Systems Aalborg University Physics Program Graduate Center City University of New York

The pace of development in the world of 5G communication systems has proven to be much more demanding than previous generations, with 5G-Advanced seemingly around the corner [1]. Extensive research is already underway to structure the next generation of wireless systems(i.e. 6G), which may potentially enable an unprecedented level of human–machine interaction [2].

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Random suppression of ECG artifacts using a NLSRLMMN-based cascaded noise canceller 58

Random suppression of ECG artifacts using a NLSRLMMN-based c...

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58th Asilomar Conference on Signals, systems and Computers, ACSSC 2024

作者： Faiz, Mohammed Mujahid Ulla Zerguine, Azzedine Kale, Izzet Presidency University Department of Electrical and Computer Engineering Karnataka Bengaluru560064 India Interdisciplinary Research Center for Communication Systems and Sensing Kfupm Electrical Engineering Department Dhahran31261 Saudi Arabia Department of Computer Science and Engineering LondonW1W 6UW United Kingdom

ISBN: (纸本)9798350354058

Normally, the electrocardiogram (ECG) signal artifacts are removed in a particular sequence starting with baseline wander removal at the beginning. In this work, a methodology has been proposed using a novel algorithm called the Normalized Leaky Sign Regressor Least Mean Mixed Norm (NLSRLMMN) algorithm to remove multiple ECG artifacts such as baseline wander, motion artifacts, muscle artifacts, and power line interference randomly without following a particular sequence. Through rigorous simulations we have shown that if we remove multiple ECG artifacts randomly using our proposed approach then an improvement in signal to noise ratio and mean square error is observed as opposed to a conventional method that employs the Least Mean Square (LMS) algorithm in all the cascaded adaptive noise canceller stages. © 2024 IEEE.

关键词： Mean square error

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Implications of electrode modifications in aqueous organic redox flow batteries

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Journal of Energy Chemistry 2024年第8期95卷 499-510,I0011页

作者： Zahid Manzoor Bhat Mohammad Furquan Muhammad Aurang Zeb Gul Sial Umair Alam Atif Saeed Alzahrani Mohammad Qamar Interdisciplinary Research Center for Hydrogen Technologies and Carbon Management(IRC-HTCM) King Fahd University of Petroleum&Minerals(KFUPM)Dhahran 31261Saudi Arabia Department of Materials Science and Engineering King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia Interdisciplinary Research Center for Sustainable Energy Systems(IRC-SES) King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia

Aqueous organic redox flow batteries(RFBs)exhibit favorable characteristics,such as tunability,multielectron transfer capability,and stability of the redox active molecules utilized as anolytes and catholytes,making them very viable contenders for large-scale grid storage *** attention has been paid on the development of efficient redox-active molecules and their performance optimization through chemical substitutions at various places on the backbone as part of the pursuit for high-performance *** the fact that electrodes are vital to optimal performance,they have not garnered significant *** research has been conducted on the effects of electrode modifications to improve the performance of *** primary emphasis has been given on the impact of electrode engineering to augment the efficiency of aqueous organic *** overview of electron transfer at the electrode-electrolyte interface is *** implications of electrode modification on the performance of redox flow batteries,with a particular focus on the anodic and cathodic half-cells separately,are then *** each section,significant discrepancies surrounding the effects of electrode engineering are thoroughly examined and ***,we have presented a comprehensive assessment along with our perspectives on the future trajectory.

关键词： Redox flow batteries Electrode modification Organic redox molecules Outer sphere and inner sphere

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A Player Position Tracking Method Based on a Wide-Area Pan-Tilt-Zoom Video 12

A Player Position Tracking Method Based on a Wide-Area Pan-T...

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Proceedings of the 12th International Conference on Sport Sciences Research and Technology Support, icSPORTS 2024

作者： Yamagishi, Shunzo Xie, Chun Shishido, Hidehiko Kitahara, Itaru Master's and Doctoral Program in Intelligent Mechanical Interaction Systems University of Tsukuba Ibaraki Japan Center for Computational Sciences University of Tsukuba Ibaraki Japan Faculty of Science and Engineering Department of Information Systems Engineering Soka University Tokyo Japan

ISBN: (纸本)9789897587191

This paper proposes a method to estimate the posture of an athlete moving on a vast field in a sporting event using a pan-tilt-zoom camera. In order to estimate the posture of an athlete on a sports field from a dynamic video sequence, our method extracts image features to search correspondence points among successive frames and computes the homography transformation matrix that compensates for changes the camera parameters (e.g., angle of view and posture). The effectiveness of this method is qualitatively verified using MLB TV broadcast video. The accuracy and error factors are also quantitatively verified by CG simulation. Copyright © 2024 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Pan-Tilt-Zoom Camera Player Tracking Sports Analytics Video Processing Wide-Area

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