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

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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Absorption enhancement in thin film a-Si solar cells with double-sided SiO_2 particle layers

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Chinese Physics B 2015年第10期24卷 186-190页

作者：陈乐王庆康沈向前陈文黄堃刘代明 Key Laboratory for Thin Film and Micro-fabrication of the Ministry of Education Department of Microelectronics and NanoscienceShanghai Jiao Tong University School of Physical Science and Technology Engineering Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data ProcessingYulin Normal University

Light absorption enhancement is very important for improving the power conversion efficiency of a thin film a-Si solar cell. In this paper, a thin-film a-Si solar cell model with double-sided SiO2 particle layers is designed, and then the underlying mechanism of absorption enhancement is investigated by finite difference time domain（FDTD） simulation;finally the feasible experimental scheme for preparing the SiO2 particle layer is discussed. It is found that the top and bottom SiO2 particle layers play an important role in anti-reflection and light trapping, respectively. The light absorption of the cell with double-sided SiO2 layers greatly increases in a wavelength range of 300 nm-800 nm, and the ultimate efficiency increases more than 22% compared with that of the flat device. The cell model with double-sided SiO2 particle layers reported here can be used in varieties of thin film solar cells to further improve their performances.

关键词： thin film a-Si solar cells light trapping anti-reflection Si02 particle

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The IDC system for Sentiment Classification and Sarcasm Detection in Arabic 6

The IDC System for Sentiment Classification and Sarcasm Dete...

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6th Arabic Natural Language Processing Workshop, WANLP 2021

作者： Israeli, Abraham Nahum, Yotam Fine, Shai Bar, Kfir Data Science Institute Interdisciplinary Center Herzliya Israel Department of Software and Information System Engineering Ben-Gurion University of the Negev Beer-Sheva Israel

ISBN: (纸本)9781954085091

Sentiment classification and sarcasm detection attract a lot of attention by the NLP research community. However, solving these two problems in Arabic and on the basis of socialnetwork data (i.e., Twitter) is still of lower interest. In this paper we present designated solutions for sentiment classification and sarcasm detection tasks that were introduced as part of a shared task by Abu Farha et al. (2021). We adjust the existing state-of-the-art transformer pretrained models for our needs. In addition, we use a variety of machine-learning techniques such as down-sampling, augmentation, bagging, and usage of meta-features to improve the models performance. We achieve an F1-score of 0.75 over the sentiment classification problem where the F1-score is calculated over the positive and negative classes (the neutral class is not taken into account). We achieve an F1-score of 0.66 over the sarcasm detection problem where the F1-score is calculated over the sarcastic class only. In both cases, the above reported results are evaluated over the ArSarcasm-v2-an extended dataset of the ArSarcasm (Farha and Magdy, 2020) that was introduced as part of the shared task. This reflects an improvement to the state-of-the-art results in both tasks. © WANLP 2021 - 6th Arabic Natural Language Processing Workshop

关键词： Natural language processing systems

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Highly parallel FPGA emulation for LDPC error floor characterization in perpendicular magnetic recording channel

Highly parallel FPGA emulation for LDPC error floor characte...

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作者： Cai, Yu Jeon, Seungjune Mai, Ken Kumar, B. V. K. Vijaya Data Storage System Center Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA 15213 United States

Low-density parity-check (LDPC) codes offer a promising error correction approach for high-density magnetic recording systems due to their near-Shannon limit error-correcting performance. However, evaluation of LDPC codes at the extremely low bit error rates (BER) required by hard disk drive systems, typically around 10-12 to 10 -15, cannot be carried out on high-performance workstations using conventional Monte Carlo techniques in a tractable amount of time. Even field-programmable gate array (FPGA) emulation platforms take a few weeks to reach BER between 10-11 and 10 -12. Thus, we implemented a highly parallel FPGA processing cluster to emulate a perpendicular magnetic recording channel, which enabled us to accelerate the emulation by > 100 × over the fastest reported emulation. This increased throughput enabled us to characterize the performance of LDPC code BER down to near 10-14 and investigate its error floor. © 2009 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Modeling and Control of a Conical Dielectric Elastomer Actuator Motion system With Springs and Input Square Term

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IEEE/ASME Transactions on Mechatronics 2025年

作者： Zhang, Xiuyu Liu, Xiru Xu, Junjie Chen, Xinkai Northeast Electric Power University School of Automation Engineering Jilin Province International Research Center of Precision Drive and Intelligent Control Jilin 132012 China Jilin Medical University School of Basic Medical Science Department of Biochemistry and Molecular Biology Jilin 132013 China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen 518060 China

Dielectric elastomer actuator (DEA) is a kind of flexible intelligent material actuators and widely used in motion driving devices of soft biomimetic robots. However, both the butterfly-like hysteresis and the square term of the control input make the controller design become challenging. To this end, this article proposes an effective control scheme for a motion platform driven by DEA with the following contributions: first, a new butterfly-like KP (BKP) hysteresis nonlinear mathematical model is constructed to accurately curve the butterfly-like hysteresis in DEA. Second, an implicit inverse compensation control algorithm is proposed, where a novel searching mechanism is designed to extract the actual control signal from the hysteresis temporary controller with input square term. Third, the conical dielectric elastomer motion platform with spring is constructed and the effectiveness of the proposed BKP hysteresis model and input square implicit inverse control strategy is verified through the constructed motion platform. © 1996-2012 IEEE.

关键词： Flexible actuators of soft robotics hysteresis input squared system

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Combination Clustering Evaluation Research on Different data Distribution Patterns

Combination Clustering Evaluation Research on Different Data...

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4th International Conference on Manufacturing Science and engineering (ICMSE 2013)

作者： Song, Yu-Chen Jia, Xiao-Liang Meng, Hai-Dong Center for Inner Mongolia Industry Informationization and Innovation Department of Mining Information System Laboratory for Data Engineering Inner Mongolia University of Science and Technology Inner Mongolia Baotou 014010 China

ISBN: (纸本)9783037856932

Clustering analysis, as a practical data mining method, has wide-ranging applications in many fields. But because of different original data resources, clustering results of different data distribution patterns and applicable clustering evaluation methods are different from each other. Aiming at different data distribution patterns, only reasonable clustering evaluation methods can achieve a better recognition of different clustering results for realizing the application value of clustering technology. In this paper, the combination clustering evaluation model is constructed form three angles, through clustering experiment of different artificial simulated data distribution patterns, comparative analysis draw a conclusion that the combination clustering evaluation model constructed is reasonable, and according to applicable clustering and clustering evaluation methods based on different data distribution patterns, the optimization clustering process is constructed for improving the effectiveness and interpretability of different clustering results.

关键词： Clustering data Distribution Combination Evaluation Visualization Technology

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JSGuard: Shellcode detection in JavaScript

JSGuard: Shellcode detection in JavaScript

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8th International ICST Conference on Security and Privacy in Communication Networks, SecureComm 2012

作者： Gu, Boxuan Zhang, Wenbin Bai, Xiaole Champion, Adam C. Qin, Feng Xuan, Dong Department of Computer Science and Engineering Ohio State University Columbus OH 43202 United States Alliance Data System Columbus OH 43202 United States

ISBN: (纸本)9783642368820

JavaScript (JS) based shellcode injections are among the most dangerous attacks to computer systems. Existing approaches have various limitations in detecting such attacks. In this paper, we propose a new detection methodology that overcomes these limitations by fully using JS code execution environment information. We leverage this information and create a virtual execution environment where shellcodes' real behavior can be precisely monitored and detection redundancy can be reduced. Following this methodology, we implement JSGuard, a prototype malicious JS code detection system in Debian Linux with kernel version 2.6.26. Our extensive experiments show that JSGuard reports very few false positives and false negatives with acceptable overhead. © 2013 ICST Institute for Computer Science, Social Informatics and Telecommunications engineering.

关键词： Intrusion detection

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GHVC-Net: Hypervolume Contribution Approximation Based on Graph Neural Network

GHVC-Net: Hypervolume Contribution Approximation Based on Gr...

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

作者： Wu, Guotong Nan, Yang Shang, Ke Ishibuchi, Hisao Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen518055 China

ISBN: (纸本)9781665410205

This paper proposes a framework called GHVC-Net that uses the graph neural network (GNN) model to approximate each solution's hypervolume contribution (HVC). GHVC-Net is permutation invariant and can handle solution sets of arbitrary size, similar to the properties of GNN. Compared to HVC-Net (i.e., a machine learning model for HVC approximation), GHVC-Net achieves better accuracy with less training time. GHVC-Net is also compared with traditional approximation methods, such as line-based and point-based methods, to demonstrate its ability to identify the solution with the smallest (largest) HVC. © 2024 IEEE.

关键词： Neural network models

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F-HMTC: Detecting financial events for investment decisions based on neural hierarchical multi-label text classification 29

F-HMTC: Detecting financial events for investment decisions ...

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29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Liang, Xin Cheng, Dawei Yang, Fangzhou Luo, Yifeng Qian, Weining Zhou, Aoying Shanghai Engineering Research Center on Big Data Management System Shanghai China School of Data Science and Engineering East China Normal University Shanghai China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China SeekData Inc. Shanghai China

ISBN: (纸本)9780999241165

The share prices of listed companies in the stock trading market are prone to be influenced by various events. Performing event detection could help people to timely identify investment risks and opportunities accompanying these events. The financial events inherently present hierarchical structures, which could be represented as tree-structured schemes in real-life applications, and detecting events could be modeled as a hierarchical multi-label text classification problem, where an event is designated to a tree node with a sequence of hierarchical event category labels. Conventional hierarchical multi-label text classification methods usually ignore the hierarchical relationships existing in the event classification scheme, and treat the hierarchical labels associated with an event as uniform labels, where correct or wrong label predictions are assigned with equal rewards or penalties. In this paper, we propose a neural hierarchical multi-label text classification method, namely F-HMTC, for a financial application scenario with massive event category labels. F-HMTC learns the latent features based on bidirectional encoder representations from transformers, and directly maps them to hierarchical labels with a delicate hierarchy-based loss layer. We conduct extensive experiments on a private financial dataset with elaborately-annotated labels, and F-HMTC consistently outperforms state-of-art baselines by substantial margins. We will release both the source codes and dataset on a public repository1,. © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Forestry

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Resource Allocation in UAV-NOMA Communication systems Based on Proportional Fairness

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Journal of Communications and Information Networks 2020年第2期5卷 111-120页

作者： Hui Zhang Baoji Wang Chen Chen Xiang Cheng Hang Li State Key Laboratory of Advanced Optical Communication Systems and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China Shanghai Institute of Microsystem and Information Tech-nology Chinese Academy of SciencesShanghai 200050China Data-Driven Information System Laboratory Shenzhen Re-search Institute of Big DataShenzhen 518172China

This paper investigates the power allocation problem in non-orthogonal multiple access(NOMA)integrated unmanned aerial vehicle(UAV)communication *** particular,we propose a novel resource allocation scheme to increase the transmission rate of the users that have relatively worse channel state information,while reducing the sum rate *** solve this problem efficiently,we decouple the optimization problem into three ***,we solve the problem of user pairing and subchannel ***,the optimum power proportional factor is derived to allocate transmit power among different users on the same *** last,different subchannels are allocated with appropriate power to improve the performance of the *** results show that the proposed scheme can enjoy a better performance than the benchmark methods since it can achieve a proper trade-off between the system sum rate and the proportional fairness.

关键词： UAV communications NOMA power allo-cation proportional fairness

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