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Multivariate Time-Series Deep Learning for Joint Prediction of Temperature and Relative Humidity in a Closed Space

Procedia computer science 2023年 227卷 1046-1053页

作者： Fergianto E. Gunawan Arief S. Budiman Bens Pardamean Endang Juana Sugiarto Romeli Tjeng W. Cenggoro Kartika Purwandari Alam A. Hidayat Anak. A.N.P. Redi Muhammad Asrol Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta 11440 Indonesia PT Impack Pratama Industri Jakarta 14350 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Mathematics Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

An accurate predictive model of temperature and humidity plays a vital role in many industrial processes that utilize a closed space such as in agriculture and building management. With the exceptional performance of deep learning on time-series data, developing a predictive temperature and humidity model with deep learning is propitious. In this study, we demonstrated that deep learning models with multivariate time-series data produce remarkable performance for temperature and relative humidity prediction in a closed space. In detail, all deep learning models that we developed in this study achieve almost perfect performance with an R value over 0.99.

关键词： closed space deep learning humity prediction indoor temperature prediction

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Density Based Spatial Clustering of Applications with Noise and Sentence Bert Embedding for Indonesian Utterance Clustering

Density Based Spatial Clustering of Applications with Noise ...

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computer science, Information Technology and engineering (ICCoSITE), international Conference on

作者： Muhammad Fikri Hasani Yaya Heryadi Yulyani Arifin Lukas Wayan Suparta Computer Science Department BINUS Graduate Program Computer Science School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

Task oriented chatbots are a sub-topic related to chatbots, where chatbots will perform certain tasks with specific goals. One part of creating a task-oriented chatbot is doing intent classification. Intent classification is a task of text classification. As in general text classification, the required dataset requires a label to carry out the classification process. To speed up and help the utterance analysis process, there is already a method, namely clustering, and Density-based clustering is a part of clustering that can determine cluster patterns based on arbitrary data, with DBScan as one of its algorithms. This research used 10000 client utterance data of awhatsapp based e-commerce conversation. SentenceBert also used as a state of art sentence embedding. This research yield silhouette score of 0.327 as the best result from eps of 0.1 and MinPts of 95. However, based on the cluster result, sentences labelled as noise can be further clustered. Text Preprocessing, text augmentation and sentence embedding techniques can be explored to increase the cluster performance.

关键词： computer science Art Text categorization Clustering algorithms Oral communication Chatbots Classification algorithms

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A Transparent Ultrasound Array for Real-Time Optical,Ultrasound,and Photoacoustic Imaging

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Biomedical engineering Frontiers 2022年第1期3卷 284-297页

作者： Haoyang Chen Sumit Agrawal Mohamed Osman Josiah Minotto Shubham Mirg Jinyun Liu Ajay Dangi Quyen Tran Thomas Jackson Sri-Rajasekhar Kothapalli Department of Biomedical Engineering The Pennsylvania State UniversityUniversity ParkPA 16802USA School of Electrical Engineering and Computer Science The Pennsylvania State UniversityUniversity ParkPA 16802USA Penn State Cancer Institute The Pennsylvania State UniversityHersheyPA 17033USA Graduate Program in Acoustics The Pennsylvania State UniversityUniversity ParkPA 16802USA

Objective and Impact *** imaging of ultrasound and optical contrasts can help map structural,functional,and molecular biomarkers inside living subjects with high spatial *** is a need to develop a platform to facilitate this multimodal imaging capability to improve diagnostic sensitivity and ***,combining ultrasound,photoacoustic,and optical imaging modalities is challenging because conventional ultrasound transducer arrays are optically *** a result,complex geometries are used to coalign both optical and ultrasound waves in the same field of *** elegant solution is to make the ultrasound transducer transparent to ***,we demonstrate a novel transparent ultrasound transducer(TUT)linear array fabricated using a transparent lithium niobate piezoelectric material for real-time multimodal *** TUT-array consists of 64 elements and centered at~6 MHz *** demonstrate a quad-mode ultrasound,Doppler ultrasound,photoacoustic,and fluorescence imaging in real-time using the TUT-array directly coupled to the tissue mimicking *** TUT-array successfully showed a multimodal imaging capability and has potential applications in diagnosing cancer,neurological,and vascular diseases,including image-guided endoscopy and wearable imaging.

关键词： Ultrasound specificity transparent

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Uncertainty Quantification Using Subsampling for Assembly-Free Estimates of Genomic Distance and Phylogenetic Relationships 26th

Uncertainty Quantification Using Subsampling for Assembly-F...

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26th international Conference on Research in Computational Molecular Biology, RECOMB 2022

作者： Rachtman, Eleonora Sarmashghi, Shahab Bafna, Vineet Mirarab, Siavash Bioinformatics and Systems Biology Graduate Program UC San Diego La JollaCA United States Department of Electrical and Computer Engineering UC San Diego La JollaCA United States Department of Computer Science and Engineering UC San Diego La JollaCA United States

Computing the distance between two genomes, often without using alignments or even access to assembled sequences, is fundamental to many downstream analyses. © 2022, The Author(s), under exclusive license to Spri... 详细信息

ISBN: (纸本)9783031047480

关键词： Uncertainty analysis

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Advances and Challenges in Multi-Domain Task-Oriented Dialogue Policy Optimization

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APSIPA Transactions on Signal and Information Processing 2023年第1期12卷

作者： Rohmatillah, Mahdin Chien, Jen-Tzung EECS International Graduate Program National Yang Ming Chiao Tung University Taiwan Institute of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan

Developing a successful dialogue policy for a multi-domain task-oriented dialogue (MDTD) system is a challenging task. Basically, a desirable dialogue policy acts as the decision-making agent who understands the user's intention to provide suitable responses within a short conversation. Furthermore, offering the precise answers to satisfy the user requirements makes the task even more challenging. This paper surveys recent advances in multi-domain task-oriented dialogue policy optimization and summarizes a number of solutions to policy learning. In particular, the case study on the task of travel assistance using the MDTD dataset based on MultiWOZ containing seven different domains is investigated. The dialogue policy optimization methods, categorized into dialogue act level and word level, are systematically presented. Moreover, this paper addresses a number of challenges and difficulties including the user simulator design and the dialogue policy evaluation which need to be resolved to further enhance the robustness and effectiveness in multi-domain dialogue policy representation. © 2023 M. Rohmatillah and J.-T. Chien.

关键词： Reinforcement learning

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Electronic-photonic quantum systems on-chip

Electronic-photonic quantum systems on-chip

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Quantum 2.0, QUANTUM 2022

作者： Wang, Imbert Ramesh, Anirudh Kramnik, Danielius Fargas Cabanillas, Josep M. Stojanović, Vladimir Kumar, Prem Popović, Miloš A. Department of Electrical and Computer Engineering Photonics Center Boston University BostonMA02215 United States Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Department of Electrical Engineering and Computer Science UC Berkeley BerkeleyCA94720 United States Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States

We present progress towards realizing electronic-photonic quantum systems on-chip;particularly, entangled photon-pair sources, placing them in the context of previous work, and outlining our vision for mass-producible... 详细信息

ISBN: (纸本)9781957171111

关键词： Quantum entanglement

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Deep learning-based channel estimation for RIS-assisted UAV-enabled wireless communications system

Deep learning-based channel estimation for RIS-assisted UAV-...

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international Conference on Innovation, Communication and engineering (ICICE 2023)

作者： Belayneh A Tesfaw Hsin-piao Lin Getaneh B Tarekegn Rong-Terng Juang Shiann-Shiun Jeng Department of International Graduate Program in Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan Institute of Aerospace and System Engineering National Taipei University of Technology Taipei 10608 Taiwan Department of Electrical and Computer Engineering National Yang-Ming Chiao Tung University Hsinchu 30010 Taiwan Department of Electrical Engineering National Dong Hwa University Hualien Taiwan

ISBN: (数字)9781839539954

Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. This problem can be effectively addressed by employing reconfigurable intelligent surfaces (RIS). To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communications system. Simulation results showed that LSTM can effectively improve the channel estimation performance of RIS-assisted UAV-enabled wireless communications.

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A weighted multivariate fuzzy time series method for multiple output high-dimensional time series forecasting in IoT applications

A weighted multivariate fuzzy time series method for multipl...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Bitencourt, Hugo Vinicius De Oliveira Lucas, Patricia Orang, Omid Silva, Petronio Guimaraes, Frederico Gadelha Universidade Federal de Minas Gerais Graduate Program in Electrical Engineering Belo Horizonte31270-901 Brazil Instituto Federal Do Norte de Minas Gerais Salinas Brazil Universidade Federal de Minas Gerais Department of Computer Science Belo Horizonte31270-901 Brazil Instituto Federal Do Norte de Minas Gerais Januária Brazil

ISBN: (纸本)9798350374575

In Internet of Things (IoT) applications, data flows are continuous streams of high-dimensional time series that aggregate various data sources. In this context, decision-making processes frequently encompass multiple factors and criteria that demand forecasting these time series. This paper introduces MO-WMVFTS, a novel multiple-input multiple-output (MIMO) fuzzy time series (FTS) method for tackling this complex scenario. MO-WMVFTS is a hybrid forecasting method that fuses weighted multivariate FTS (WMVFTS) with embedding transformations, designed for IoT applications. To assess the performance of the proposed method, it was applied to the prediction of energy consumption in smart homes and air quality in smart cities. Here, three real-world datasets are used to assess the validity of our proposed approach, and the results obtained are highly competitive when compared to other existing methods. © 2024 IEEE.

关键词： Smart homes

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On the Second Order Asymptotics of Covert Communications over AWGN Channels

On the Second Order Asymptotics of Covert Communications ove...

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IEEE international Conference on Communications (ICC)

作者： Y. Xinchun Shuangqing Wei Shao-Lun Huang Xiao Ping Zhang Shenzhen Key Laboratory of Ubiquitous Data Enabling Shenzhen International Graduate School Tsinghua University Shenzhen China School of Electrical Engineering and Computer Science Louisiana State University Baton Rouge USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

This work tackles the asymptotics of the maximal throughput of covert communications over AWGN channels when the covert metric is Kullback-Leibler divergence (KL divergence). It is shown that the first and second order asymptotics of the maximal throughput are $\sqrt{n\delta\log e}$ and (2) ${ }^{\frac{1}{2}}(n \delta)^{\frac{1}{4}}(\log e)^{\frac{3}{4}} \cdot Q^{-1}(\epsilon)$ , respectively by $n$ channel uses, where $\delta$ and $\epsilon$ are constraints imposed on covertness and channel decoding error probabilities, respectively. The technique we use in the achievability is quasi- $\varepsilon$ -neighborhood notion from information geometry. For finite blocklength $n$ , the generating distributions are chosen to be a family of truncated Gaussian distributions with decreasing variances. The law of decreasing is carefully designed so that it maximizes the throughput at the main channel in the asymptotic sense under the condition that the output distributions satisfy the covert constraint. For the converse, the optimality of Gaussian distribution for minimizing KL divergence under second order moment constraint is extended from dimension 1 to dimension $n$ , which further leads to the direct converse bound in terms of covert metric.

关键词： AWGN channels Measurement Information geometry Error probability Memory management Gaussian distribution Throughput

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ICE: An Intelligent Cognition Engine with 3D NAND-Based In-Memory Computing for Vector Similarity Search Acceleration 22

ICE: An Intelligent Cognition Engine with 3D NAND-Based In-M...

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Proceedings of the 55th Annual IEEE/ACM international Symposium on Microarchitecture

作者： Han-Wen Hu Wei-Chen Wang Yuan-Hao Chang Yung-Chun Lee Bo-Rong Lin Huai-Mu Wang Yen-Po Lin Yu-Ming Huang Chong-Ying Lee Tzu-Hsiang Su Chih-Chang Hsieh Chia-Ming Hu Yi-Ting Lai Chung-Kuang Chen Han-Sung Chen Hsiang-Pang Li Tei-Wei Kuo Meng-Fan Chang Keh-Chung Wang Chun-Hsiung Hung Chih-Yuan Lu Macronix International Co. Ltd. and Department of Electrical Engineering National Tsing Hua University Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology and Macronix International Co. Ltd. Institute of Information Science Academia Sinica Macronix International Co. Ltd Macronix International Co. Ltd. and Graduate Institute of Electronics Engineering National Taiwan University Department of Computer Science and Information Engineering National Taiwan University and Graduate Institute of Electronics Engineering National Taiwan University Department of Electrical Engineering National Tsing Hua University

ISBN: (纸本)9781665462723

Vector similarity search (VSS) for unstructured vectors generated via machine learning methods is a promising solution for many applications, such as face search. With increasing awareness and concern about data security requirements, there is a compelling need to store data and process VSS applications locally on edge devices rather than send data to servers for computation. However, the explosive amount of data movement from NAND storage to DRAM across memory hierarchy and data processing of the entire dataset consume enormous energy and require long latency for VSS applications. Specifically, edge devices with insufficient DRAM capacity will trigger data swap and deteriorate the execution performance. To overcome this crucial hurdle, we propose an intelligent cognition engine (ICE) with cognitive 3D NAND, featuring non-volatile in-memory computing (nvIMC) to accelerate the processing, suppress the data movement, and reduce data swap between the processor and storage. This cognitive 3D NAND features digital nvIMC techniques (i.e., ADC/DAC-free approach), high-density 3D NAND, and compatibility with standard 3D NAND products with minor modifications. To facilitate parallel INT8/INT4 vector-vector multiplication (VVM) and mitigate the reliability issue of 3D NAND, we develop a bit-error-tolerance data encoding and a two's complement-based digital accumulator. VVM can support similarity computations (e.g., cosine similarity and Euclidean distance), which are required to search "the most similar data" right where they are stored. In addition, the proposed solution can be realized on edge storage products, e.g., embedded MultiMedia Card (eMMC). The measured and simulated results on real 3D NAND chips show that ICE enhances the system execution time by 17× to 95× and energy efficiency by 11× to 140×, compared to traditional von Neumann approaches using state-of-the-art edge systems with MobileFaceNet on CASIA-WebFace dataset. To the best of our knowledge, this work demo

关键词： 3D NAND in-memory computing vector similarity search unstructured data search

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