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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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Sentiment Analysis of User Review on Indonesian Food and Beverage Group using Machine Learning Techniques

Sentiment Analysis of User Review on Indonesian Food and Bev...

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Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Yanfi Yanfi Yaya Heryadi Lukas Lukas Wayan Suparta Yulyani Arifin 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

A vast number of technologies based on Artificial Intelligence (AI) have proliferated into various application domains. As part of its objectives to develop agents which can behave and think like humans, some branches of AI have focused on developing various algorithms that can learn from input data without explicitly being programmed. In the food industry, notably in restaurants, smartphone technology is typically used to collect data from customers efficiently such as orders or feedback toward the services provided. The use of smartphones by some restaurants is motivated by their convenience and efficiency. Furthermore, various promotions, discounts, and membership benefits offered by cellular service providers have attracted the use of smartphones as devices for improving restaurant services to their customers. This study aimed to conduct a sentiment analysis related to multi-brand restaurants in Indonesia based on customer feedback. The data retrieved from the Google Play Store consists of 756 reviews from Boga, Champs, Hangry, Ismaya, Kulo, and Union groups. In this study, TF-IDF was used as a vectorizer to represent customer feedback as numeric vectors. The polarity sentiment of customer feedback was recognized using classifier models based on machine learning such as Logistic Regression, Naive Bayes (NB), Random Forest, and Support Vector Machine (SVM) as the classifier. The empirical results showed that SVM has the best accuracy of 93.10 % average accuracy followed by Logistic Regression with 92.41 %, Random Forest with 84.14 % average accuracy, and Naive Bayes with 76.55 % average accuracy.

关键词： Support vector machines Sentiment analysis Analytical models Machine learning algorithms Food industry Companies Classification algorithms

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The 2020 power blackout in the brazilian state of amapá: Lessons learned and opportunities

The 2020 power blackout in the brazilian state of amapá: Le...

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2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2021

作者： Do Prado, Josue Campos Santos, Marcos Vinicius Ramos, Lucas Feksa Canha, Luciane Neves Konzen, Gabriel School of Engineering Computer Science Washington State University VancouverWA98686 United States School of Engineering Newcastle University Newcastle Upon TyneNE1 7RU United Kingdom Federal University of Rondônia Department of Electrical Engineering Porto Velho Brazil Graduate Program in Electrical Engineering Federal University of Santa Maria Santa Maria Brazil Division of Energy Economics and Environmental Studies Rio de Janeiro Brazil

ISBN: (纸本)9781665444217

The Brazilian state of Amapa=-notable for having 70% of its area consisting of unexplored Amazonian forests-experienced a massive power blackout in November 2020. An internal short-circuit in a transformer led to an explosion followed by a fire at the Macapa substation. This event left about 90% of the Amapa's population without power for several days in the middle of the COVID-19 pandemic, disrupting the lives of hundreds of thousands of people and raising concerns from several electricity sector stakeholders. This paper discusses select lessons learned from the power blackout and presents future opportunities to improve power system reliability and resilience for the grids in Amapá, and other similar Brazilian states, with a special focus on the increasingly important role of of distributed energy resources and smart grid technologies. © 2021 IEEE.

关键词： Outages

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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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Smart Environmental Architecture for Node Localization in a Wireless Sensor Network

Smart Environmental Architecture for Node Localization in a ...

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International Conference on Intelligent Environments (IE)

作者： Salvador Jauregui-Ortiz Mario Siller Felix Ramos Edson Scalabrin Electrical Engineering and Computer Science Department Center of Research and Advanced Studies of the IPN Guadalajara Jalisco Mexico Graduate Program in Computer Science Pontifical Catholic University Parana Brazil Curitiba Parana Brazil

As far as we know, there is not a Node Localization Algorithm (NLA) that presents the same accuracy for all possible scenarios. We believe that a NLA should be able to "interpret" the dynamic information of the environment. In this sense, simple NLAs are rather focused and might perform well for specific scenarios and applications. Therefore, information fusion and context awareness seems to be an appropriate approach to address this issue. We propose the Smart Environmental Architecture for Node Localization (SEA-NL), which is composed by two main elements: (i) the Smart Beacon Nodes (SBNs) and (ii) the Logical Position of Nodes (LPN). In (i) the obstruction level indicator is estimated and can improve the estimation of distances among nodes. In (ii) environment information and a one to one relation between a node and an object are used and can also improve location estimation. Via simulation, our architecture was tested indoors and outdoors considering three localization algorithms: the Weighed Centroid Localization (WCL), the Centroid Localization, and the Triangular Centroid Localization. Finally, we present an accuracy comparison among NLAs used in isolated way, and by using the SBNs, the LPN, and the SEA-NL, where our architecture improves WCL up to ~30.88%.

关键词： Wireless sensor networks Accuracy Estimation computer architecture Buildings Attenuation Monitoring

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Handling failures of static sensor nodes in wireless sensor network by use of mobile sensors

Handling failures of static sensor nodes in wireless sensor ...

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25th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2011

作者： Pignaton De Freitas, Edison Heimfarth, Tales Netto, Ivayr Farah Pereira, Carlos Eduardo Ferreira, Armando Morado Wagner, Flávio Rech Larsson, Tony IDE Halmstad University Halmstad Sweden Institute of Informatics Federal University of Rio Grande Do Sul Porto Alegre Brazil Computer Science Department Federal University of Lavras Lavras Brazil Electrical Engineering Department Federal University of Rio Grande Do Sul Porto Alegre Brazil Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

ISBN: (纸本)9780769543383

Node failures in Wireless Sensor Networks composed by static sensor nodes are common due to the nature of the sensor devices and the usually harsh environments in which they are deployed. Node failures can diminish the performance of the network as a whole, thus affecting its functionality in delivering the desired services. For instance, significant regions can become uncovered due to failure of several nearby nodes. This paper reports a study about the use of mobile sensor nodes acting in cooperation with static ones in order to fill gaps created by faulty static nodes. The proposed fault handling mechanism presents alternative policies with pros and cons, depending on the user priorities imposed to the system and the occurrence of failures. A discussion about this topic is presented based on results obtained by simulation of the proposed mechanisms. © 2011 IEEE.

关键词： Sensor nodes

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A nanoscale approach to stamp fabrication in hard materials using high intensity ultrafast lasers

A nanoscale approach to stamp fabrication in hard materials ...

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2003 MRS Fall Meeting

作者： McDonald, Joel P. Picard, Yoosuf N. Yalisove, Steven M. Liu, Hsiao-Hua Blaszczak, Joseph Guo, Lingji J. Dept. of Materials Science and Engineering University of Michigan Ann Arbor MI 48109-2176 United States Center for Ultrafast Optical Science University of Michigan Ann Arbor MI 48109-2099 United States Applied Physics Program University of Michigan Ann Arbor MI 48109-1120 United States Dept. of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109-2122

Nanomorphing with ultrafast lasers may have a significant role in direct write stamp production. Surface conditions play a critical role in the ablative properties of materials. We have conducted femtosecond laser (pulse duration;120 fs, wavelength;780 nm) threshold studies of silicon with the native oxide and silicon with atomically clean surfaces in an ultra-high vacuum environment. We have discovered that a -1.5 nm thick oxide layer can alter the ablation threshold of Si (100) by 25 ± 5%. Additionally, our work has shown that collateral damage can be controlled on the nanoscale. Transmission electron microscopy (TEM) images of femtosecond laser machined holes in Si (100) show that collateral damage extends only 10 nm from the edge. © 2004 Materials Research Society.

关键词： Ultrafast phenomena

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Phase transition behavior in microcantilevers coated with M 1-phase VO2 and M2-phase VO2:Cr thin films

Phase transition behavior in microcantilevers coated with M ...

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作者： Rúa, Armando Cabrera, Rafmag Coy, Horacio Merced, Emmanuelle Sepúlveda, Nelson Fernández, Félix E. Department of Physics University of Puerto Rico Mayagüez 00681-9000 Puerto Rico Doctoral Program in Physics Graduate Center City University of New York New York 10016 United States Applied Materials Group Electrical and Computer Engineering Department Michigan State University E. Lansing MI 48824 United States

Silicon microcantilevers were coated by pulsed laser deposition with vanadium dioxide (VO2) (monoclinic M1 phase) and V 1-xCrxO2 with x near 0.024 (monoclinic M 2 phase), and their mechanical characteristics were studied as a function of temperature through the films' insulator-to-metal transition (IMT). The undoped VO2 films grew with (011)M1 planes parallel to the substrate, while Cr-doped VO2 films grew oriented with (201)M2 and (2 01)M2 planes parallel to the substrate. In both cases, the films transformed reversibly through the IMT to the tetragonal (rutile, R) phase, with film (110)R planes oriented parallel to the substrate. The fundamental resonant frequencies of the cantilevers were measured as the temperature was cycled from ambient temperature, through the IMT, and up to 100 °C. Very high resonant frequency changes were observed through the transition for both types of samples, with increases during heating of over 11 and over 15 for the cantilevers coated with pure and Cr-doped VO2, respectively. From the resonant frequencies measured at room temperature for the bare and coated cantilevers in each case, the effective Young's moduli of the films were determined. The values obtained, assuming bulk densities for the films, are 156 ± 7.5 GPa for VO2 (M1 phase) and 102 ± 3 GPa for Cr-doped VO2 (M2 phase). Strong curvature changes during the transition to the R phase were also observed for cantilevers coated with both types of films, but these were significantly higher in the case for the Cr-doped film. Curvature changes for temperature ranges outside the IMT region were small and attributed to differential thermal expansion between film and silicon substrate. From measured cantilever tip displacements in this post-transition range-for the undoped VO 2-coated microcantilevers-a rough estimate of 110 GPa was obtained for the effective Young's modulus for R-phase VO2. The substantially higher changes in resonant frequency and curvature for V1-xCr xO2-coated cant

关键词： Thin films

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Implementation of Augmented Reality in Pretend Play Therapy for Children with Autism Spectrum Disorder 3

Implementation of Augmented Reality in Pretend Play Therapy ...

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3rd International Conference on Computing and applied Informatics 2018, ICCAI 2018

作者： Syahputra, M.F. Angkasih, A.P. Purnamawati, S. Andayani, U. Abdullah, D. Sriadhi, S. Iskandar, A. Rosida, T.M. Fitriany, J. Sari, I.N. Utama, M.D. Nanuru, R.F. Department of Information Technology Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Pediatric Universitas Malikussaleh Aceh Utara Indonesia Departement of Social Science Education Program Post Graduate Program Universitas Kanjuruhan Malang Malang Indonesia Faculty of Social and Political Science Universitas Kristen Indonesia Maluku Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia

Autism Spectrum Disorder is a pervasive developmental disorder that will affect children in terms of interpersonal communication, social interaction, and imaginative levels in play. Many therapies to help the motor neuron performance is one of them Pretend Play. Pretend Play is a therapy that invites children in playing to demonstrate something else and tell how to use objects that are considered in the child's imagination. However, in the era of highly developed technology, many fields have used the Augmented Reality method as a visualization of various aspects. With this method researchers will present the therapeutic visualization of the block to 3D transportation tool that is useful for strengthening motor nerves and visual strength of the child. The system can run well during marker detection, marker movement, and 3D object display with the accuracy of precision angle and distance between virtual world with real world reach 100% with angle 0 at distance 31 cm and the maximum distance from the marker is 46 cm and the maximum angle is 30. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Augmented reality

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BioN∅T: A searchable database of biomedical negated sentences

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BMC Bioinformatics 2011年第1期12卷 1-7页

作者： Agarwal, Shashank Yu, Hong Kohane, Issac Medical Informatics College of Engineering and Applied Sciences University of Wisconsin-Milwaukee 3200 N. Cramer St. Milwaukee WI 53201-0784 United States Department of Computer Science and Electrical Engineering College of Engineering and Applied Sciences University of Wisconsin-Milwaukee 3200 N. Cramer St. Milwaukee WI 53201-0784 United States Department of Health Sciences College of Health Science University of Wisconsin-Milwaukee 2400 E. Hartford Ave. Milwaukee WI 53211 United States Children's Hospital Informatics Program Children's Hospital 300 Longwood Ave. Enders-6 Boston MA 02115 United States

Background: Negated biomedical events are often ignored by text-mining applications;however, such events carry scientific significance. We report on the development of BioN∅T, a database of negated sentences that can be used to extract such negated ***: Currently BioN∅T incorporates ≈32 million negated sentences, extracted from over 336 million biomedical sentences from three resources: ≈2 million full-text biomedical articles in Elsevier and the PubMed Central, as well as ≈20 million abstracts in PubMed. We evaluated BioN∅T on three important genetic disorders: autism, Alzheimer's disease and Parkinson's disease, and found that BioN∅T is able to capture negated events that may be ignored by ***: The BioN∅T database can be a useful resource for biomedical researchers. BioN∅T is freely available at http://***/. In future work, we will develop semantic web related technologies to enrich BioN∅T. © 2011 Agarwal et al;licensee BioMed Central Ltd.

关键词： Database systems

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