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International Conference on Communications and Networking, ComNet

作者： Widad Belaoura Khalida Ghanem Mohummed Zeeshan Shakir Khalid Qaraqe Ecole nationale polytechnique (ENP) Algiers Algeria System Architecture Laboratory Center of development of advanced techniques (CDTA) Algiers Algeria School of Computing Engineering and Physical Sciences University of the West of Scotland Paisley Scotland UK Texas A&M University at Qatar Doha Qatar

ISBN: (数字)9781728153209

ISBN: (纸本)9781728153216

The impact of hardware impairments play an crucial role in any practical communication systems, yet they are generally omitted when investigating the performance of distributed massive multiple input multiple output (MIMO) systems. In particularly, for millimeter-Wave (mm-Wave) bands, no study has been addressed yet. To overcome this limitation, in this paper a mm-Wave distributed massive multi-user (MU) MIMO system based-hybrid beamforming structure, in which the residual hardware impairments have been incorporated in the transmitter processing, is presented. At each base station (BS), a zero-forcing (ZF) baseband processing is designed over the effective channel to efficiently remove the multi-user (MU) interference. The results show that, relative to the co-located mm-Wave massive MIMO with the same antenna configurations, mm-Wave distributed MIMO achieves a significantly higher performance while reducing the impingement of hardware practical defects.

关键词： Array signal processing Transmitting antennas Massive MIMO Hardware Millimeter wave communication Antenna arrays Signal to noise ratio

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Overcoming Thermal Quenching in X-ray Scintillators through Multi-Excited State Switching

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Angewandte Chemie 2024年第18期136卷

作者： Dr. Min Wang Dr. Zhongbo Zhang Dr. Jing Lyu Jian Qiu Chang Gu He Zhao Dr. Tao Wang Yiwen Ren Prof. Shuo-Wang Yang Prof. Guo Qin Xu Prof. Xiaogang Liu Department of Chemistry National University of Singapore 117543 Singapore Singapore School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University 637459 Singapore Singapore International Campus of Tianjin University Joint School of National University of Singapore and Tianjin University 350207 Fuzhou China Institute of Landscape Architecture Zhejiang University 310058 Hangzhou China Institute of High-Performance Computing Agency for Science Technology and Research 138632 Singapore Singapore Center for Functional Materials National University of Singapore Suzhou Research Institute 215123 Suzhou China

X-ray scintillators have gained significant attention in medical diagnostics and industrial applications. Despite their widespread utility, scintillator development faces a significant hurdle when exposed to elevated temperatures, as it usually results in reduced scintillation efficiency and diminished luminescence output. Here we report a molecular design strategy based on a hybrid perovskite (TpyBiCl 5 ) that overcomes thermal quenching through multi-excited state switching. The structure of perovskite provides a platform to modulate the luminescence centers. The rigid framework constructed by this perovskite structure stabilized its triplet states, resulting in TpyBiCl 5 exhibiting an approximately 12 times higher (45 % vs. 3.8 %) photoluminescence quantum yield of room temperature phosphorescence than that of its organic ligand (Tpy). Most importantly, the interactions between the components of this perovskite enable the mixing of different excited states, which has been revealed by experimental and theoretical investigations. The TpyBiCl 5 scintillator exhibits a detection limit of 38.92 nGy s −1 at 213 K and a detection limit of 196.31 nGy s −1 at 353 K through scintillation mode switching between thermally activated delayed fluorescence and phosphorescence. This work opens up the possibility of solving the thermal quenching in X-ray scintillators by tuning different excited states.

关键词： Scintillator Thermal Quenching Hybrid Perovskites Multi-Excited State Switching

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Quantification electroencephalography response to procedural pain during heel puncture in preterm infants

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Physiological measurement 2025年第6期46卷 2025 Jun 2页

作者： Nusreena Hohsoh Osuke Iwata Tomoko Suzuki Chinami Hanai Ming Huang Kiyoko Yokoyama Graduate School of Design and Architecture Nagoya City University 2-1-10 Kitachikusa Chikusa-ku Nagoya Aichi Prefecture 464-0083 JAPAN. Nagoya City University Graduate School of Medical Sciences and Medical School 1 Kawasumi Mizuho-cho Nizuho-ku Nagoya Aichi Prefecture 467-8601 JAPAN. Nagoya City University Graduate School of Medical Sciences and Medical School 1 Kawasumi Mizuho-cho Mizuho-ku Nagoya Aichi Prefecture 467-8601 JAPAN. Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Shenzhen Guangdong 518103 CHINA. School of Data Science Nagoya Shiritsu Daigaku 2-1-10 Kitachikusa. Chikusa-ku Nagoya 464-0083 JAPAN.

OBJECTIVE:Pain assessment in preterm infants is often based on subjective observations, which may lack objectivity and are labor-intensive. Non-invasive EEG can serve as an objective assessment tool. However, no specific EEG feature within a particular frequency band and brain region has been reported for pain detection in the objective pain assessment of preterm infants. This study quantified electroencephalography (EEG) responses to procedural pain during a puncture in preterm infants, specifically analyzing three EEG parameters. APPROACH:Fifty-seven EEG datasets from forty-two preterm infants were analyzed across eight EEG channels. The differences between the upper and lower margins (UM-LM) of amplitude-integrated EEG (aEEG), as well as the five frequency bands (low delta, high delta, theta, alpha, and beta) of frequency power and time-frequency power, were used to characterize the response of the brain to pain during specific periods: before, during, and after the puncture. MAIN RESULTS:The Fp1 and Fp2 exhibited the most significant differences in the UM-LM aEEG differences between before vs. during (Fp1: p = 0.0060, Fp2: p = 0.0031), before vs. after (p < 0.0001), and during vs. after (Fp1: p = 0.0427, Fp2: p = 0.025) the puncture. The C3 and C4 responded significantly to pain during the puncture in the frequency and time-frequency power, notably the time-frequency power in the low delta, which showed the most significant differences between the periods before vs. during (p < 0.0001), before vs. after (p < 0.0001), and during vs. after (p < 0.0002) the puncture. SIGNIFICANCE:The central brain region responds significantly to procedural pain in preterm infants, which is prominently detected in the low delta of time-frequency power. These findings support the use of EEG application as an objective and non-invasive method to identify and detect pain in nonverbal populations, focusing on specific critical channels and frequency bands.

关键词： Brain activity EEG analysis Heel puncture Preterm newborns Procedural pain

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A Non-Stop Double Buffering Mechanism for Dataflow architecture

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Journal of Computer Science & Technology 2018年第1期33卷 145-157页

作者： Xu Tan Xiao-Wei Shen Xiao-Chun Ye Da Wang Dong-Rui Fan Lunkai Zhang Wen-Ming Li Zhi-Min Zhang Zhi-Min Tang State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing 100049 China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125 China Department of Computer Science The University of Chicago Chicago IL 60637 U.S.A.

Double buffering is an effective mechanism to hide the latency of data transfers between on-chip and off-chip memory. However, in dataflow architecture, the swapping of two buffers during the execution of many tiles decreases the performance because of repetitive filling and draining of the dataflow accelerator. In this work, we propose a non-stop double buffering mechanism for dataflow architecture. The proposed non-stop mechanism assigns tiles to the processing element array without stopping the execution of processing elements through optimizing control logic in dataflow architecture. Moreover, we propose a work-flow program to cooperate with the non-stop double buffering mechanism. After optimizations both on control logic and on work-flow program, the filling and draining of the array needs to be done only once across the execution of all tiles belonging to the same dataflow graph. Experimental results show that the proposed double buffering mechanism for dataftow architecture achieves a 16.2% average efficiency improvement over that without the optimization.

关键词： non-stop double buffering dataflow architecture high-performance computing

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To what extent can solar control be effective in enhancing indoor comfort in a fully glazed office building?

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IOP Conference Series: Earth and Environmental Science 2020年第3期588卷

作者： H Farouk H Elsharkawy Department of Architecture and Visual Arts School of Architecture Computing and Engineering University of East London UK E162RD

It is acknowledged that people spend almost 90 percent of their time in indoor spaces. Therefore, achieving a comfortable indoor environment that encourages productivity is crucial, particularly in office buildings. This paper investigates the design and performance of a modern office building in London characterized by fully glazed facades of open plan office spaces with no natural ventilation. The purpose of the research is to investigate the correlations between the control of direct solar radiation access and the effect on occupants' thermal comfort in the summer followed by assessing the potential effect of the application of passive solar shading on thermal comfort levels in the office spaces. The research methodology involves a survey questionnaire undertaken with employees of the office building, followed by dynamic thermal modelling of the building using Integrated Environmental Solutions (IES) software. The questionnaire has been designed to understand occupants' experiences within their office spaces and their strategies to improve the indoor environment. Furthermore, IES modelling and simulation provide in depth understanding of the building thermal performance and investigating the solar shading strategies. Overall, 66 questionnaire forms were completed where preliminary results demonstrated that most employees relied heavily on secondary cooling and heating systems to adjust the indoor air temperature for more satisfactory thermal comfort levels in their office spaces. The building modelling and simulation is used to quantify the direct solar radiation accessing the office space, the risks of overheating and the potential impact of solar control on occupants' indoor comfort. The findings from this study demonstrate the potentially high hours of discomfort in the summer within the office spaces mainly due to the lack of control of direct solar access through the extensive area of glazed facades. In order to maintain the thermal environment within the co

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Context-Aware Driver Distraction Severity Classification using LSTM Network

Context-Aware Driver Distraction Severity Classification usi...

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International Conference on computing, Electronics & Communications engineering (iCCECE)

作者： Adebamigbe Fasanmade Suleiman Aliyu Ying He Ali H. Al-Bayatti Mhd Saeed Sharif Ahmed S. Alfakeeh Faculty of Computing Engineering and Media De Montfort University Leicester UK School of Architecture Computing and Engineering College of Arts Technology and Innovation UEL University Way Dockland Campus London UK Faculty of Computing and Information Technology King Abdulaziz University Jeddah KSA

ISBN: (纸本)9781728121390

Advanced Driving Assistance Systems (ADAS) has been a critical component in vehicles and vital to the safety of vehicle drivers and public road transportation systems. In this paper, we present a deep learning technique that classifies drivers' distraction behaviour using three contextual awareness parameters: speed, manoeuver and event type. Using a video coding taxonomy, we study drivers' distractions based on events information from Regions of Interest (RoI) such as hand gestures, facial orientation and eye gaze estimation. Furthermore, a novel probabilistic (Bayesian) model based on the Long short-term memory (LSTM) network is developed for classifying driver's distraction severity. This paper also proposes the use of frame-based contextual data from the multi-view TeleFOT naturalistic driving study (NDS) data monitoring to classify the severity of driver distractions. Our proposed methodology entails recurrent deep neural network layers trained to predict driver distraction severity from time series data.

关键词： Vehicles Accidents Monitoring Task analysis Safety Visualization

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Effect of superabsorbent polymers on microstructure and strength of blended cements mortars reinforced by polymeric fibre

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CEMENT 2022年 9卷

作者： Rostami Rohollah Klemm Agnieszka J． Fernando C.R. Almeida Glasgow Caledonian University School of Computing Engineering and Built Environment 70 Cowcaddens Road Glasgow G4 0BA UK University of Brighton School of Architecture Technology and Engineering Cockcroft Building Lewes Road BN2 4GJ Brighton UK Federal University of Minas Gerais Department of Materials Engineering and Construction Av. Presidente Antônio Carlos 6627 Belo Horizonte MG 31270-901 Brazil

Superabsorbent polymers (SAPs) efficiently reduce total shrinkage and cracking susceptibility of fibre reinforced mortars (FRM). This paper discusses the effects of SAPs on the microstructure and mechanical properties of FRM containing fly ash (FA) and ground granulated blast-furnace slag (GGBS) during a period of 180 days. Three types of cement including CEM I, CEM II/B-V and CEM III/A and three types of SAP with different chemical compositions and particle gradings were studied. The paper argues SAP's contribution to hydration of FA and GGBS and a subsequent deposition of these products on the fibres surface and in pores below 20 nm diameter. The analysis confirmed that SAPs provide additional water for hydration (internal curing) but also a required space for later hydration products (additional refilling of collapsed SAPs), resulting in more homogenous internal microstructure. This improvement is more prominent in mortars containing finer SAP (around 80 μm), which can facilitate strength recovery of up to 50%. The strength recovering process in FRM-SCM samples is boosted after the 2nd week, and is more dominant for samples containing CEM III/A.

关键词： Superabsorbent polymers (SAPs) Supplementary cementitious materials (SCMs) Polymeric fibre (PF) Microstructure Mechanical properties

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BTI Aging Monitoring based on SRAM Start-up Behavior

BTI Aging Monitoring based on SRAM Start-up Behavior

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Asian Test Symposium (ATS)

作者： Shengyu Duan Peng Wang Gaole Sai School of Computer Engineering and Science Shanghai University Shanghai China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China

ISBN: (数字)9781728174679

ISBN: (纸本)9781728174686

Bias Temperature Instability (BTI) is one of the dominant CMOS aging mechanisms. It causes time-dependent variation, threatening circuit lifetime reliability. BTI-induced circuit errors are not detectable at the fabrication stage. On-line monitoring schemes are therefore necessary to capture the degradations during the operational time. Traditional aging monitoring techniques exhibit high implementation complexity and low stability. In this paper, we propose a BTI monitoring approach by simply tracking the start-up behavior of SRAM cells. SRAM is a widely used on-chip device in many applications. We study the impact of BTI for SRAM start-up values and age some cells in a manipulated manner. The BTI degradation is evaluated based on the number of SRAM cells starting with a certain value. This technique can be used to estimate the degradation for on-chip logic circuits without introducing additional circuitry, and thus has very low implementation complexity. We use an SRAM array with 1024 cells to estimate the degradations for multiple logic circuits, and show the average mean absolute percentage error as 8.48%. In addition, this technique is robust considering process, voltage and temperature variations.

关键词： Degradation Monitoring Logic circuits Transistors SRAM cells Aging System-on-chip

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Integrated workflow for evaluating sustainability and resiliency of building systems 13

Integrated workflow for evaluating sustainability and resili...

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13th International Conference on Applications of Statistics and Probability in Civil engineering, ICASP 2019

作者： Angeles, Karen Patsialis, Dimitrios Taflanidis, Alexandros A. Kijewski-Correa, Tracy L. Buccellato, Aimee Vardeman, Charles Dept. of Civil and Environmental Engineering and Earth Sciences University of Notre Dame Notre DameIN United States Dept. of Civil and Environmental Engineering and Earth Sciences and Keough School of Global Affairs University of Notre Dame Notre DameIN United States School of Architecture University of Notre Dame Notre DameIN United States Center for Research Computing University of Notre Dame Notre DameIN United States

This study describes the development of a workflow for integrated life-cycle assessment (iLCA) of buildings that is capable of capturing the dependencies between multi-hazard resilience and sustainability using tools native to professional practice. Modules dedicated to hazard characterization, structural response, damage, repair/loss, and environmental impact (embodied and operating energy) are developed using Application Programming Interfaces (APIs) and semantic data perspectives from computer science. A unifying probabilistic framework is utilized to quantify life-cycle performance and a common, versatile, simulation-based approach is adopted for estimation of performance. This approach supports various resilience/sustainability metrics, including monetary losses, downtime, total embodied energy (initial construction and repairs), and operating energy. A case study executed in the Revit environment evaluates the performance of a special reinforced concrete frame located near Los Angeles International Airport (LAX). Two design alternatives are considered to illustrate the impact of design and material decisions, ultimately revealing design choices which best achieve joint resiliency and sustainability. © 13th International Conference on Applications of Statistics and Probability in Civil engineering, ICASP 2019. All rights reserved.

关键词： Sustainable development

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Predicting the Standard and Deviant Patterns in EEG Signals Based on Deep Learning Model

Predicting the Standard and Deviant Patterns in EEG Signals ...

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International Conference on computing, Electronics & Communications engineering (iCCECE)

作者： Mhd Saeed Sharif Ali H. Al-Bayatti Ahmed S. Alfakeeh School of Architecture Computing and Engineering College of Arts Technology and Innovation UEL University Way Dockland Campus London UK Facultiy of Computing Engineering and Media De montfort University The Gateway Leicester UK Faculty of Computing and Information Technology King Abdulaziz University Jeddah KSA

ISBN: (纸本)9781728121390

In the recent years, there has been a significant growth in the area of brain computer interference. The main aim of such area is to read the brain activities, formulate a specific/desired output and power a specific approach using such output. Electroencephalography (EEG) may provide an insight into the analysis procedure of the human behavior and the level of the attention. Using the deep learning based neural network has a great success in different applications recently, such as making a decision, classifying a pattern and predicting an outcome by learning from a set of data and build the right weight matrices to represent the prediction outcome or the learning patterns. This research work proposes a novel model based on long short-term memory network to predict the standard and the deviant cases within EEG data sets. The EEG signals are acquired utilizing all the 128 electrodes that represent the 128 channels from infants aged between 5 and 7 months. Statistical approaches, principal component analysis (PCA) and autoregressive (AR) power spectral density estimate have been employed to extract the features from the EEG data sets. The proposed deep learning based model has shown great robustness dealing with different types of features extracted from the processed data sets. Very promising results have been achieved in predicting the standard and deviant cases. The standard case was presented with frequent, repetitive stimulus and the deviant case was presented with infrequent sounds.

关键词： Electroencephalography Principal component analysis Deep learning Feature extraction Brain modeling Wavelet transforms

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