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Tracking chronically recorded single-units in cortically controlled brain machine interfaces

Tracking chronically recorded single-units in cortically con...

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International IEEE/EMBS Conference on Neural engineering, CNE

作者： Ahmed Eleryan Mukta Vaidya Joshua Southerland Islam Badreldin Karthikeyan Balasubramanian Andrew Fagg Nicholas Hatsopoulos Karim Oweiss Department of Electrical and Computer Engineering Michigan State University MI USA Committee of Computational Neuroscience University of Chicago IL USA Department of Computer Science and Bioengineering University of Oklahoma OK USA Cognitive Science Program Michigan State University MI USA

Multiple single-units recorded from chronically-implanted microelectrode arrays frequently exhibit variability in their spike waveform features and firing characteristics, making it challenging to ascertain the identity of recorded neurons across days. In this study, we present a fast and efficient algorithm that tracks multiple single-units, recorded in a nonhuman primate performing brain control of a robotic arm, across days based on features extracted from units' average waveforms. Furthermore, the algorithm does not require long recording duration to perform the analysis and can be applied at the start of each recording session without requiring the subject to be engaged in a behavioral task. The algorithm achieves a classification accuracy of up to 92% compared to experts' manual tracking.

关键词： Feature extraction Support vector machines Training Neurons Measurement Educational institutions Niobium

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Sentiment Analysis of Hashtag Activism on Social Media Twitter

Sentiment Analysis of Hashtag Activism on Social Media Twitt...

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Computer science, Information Technology and engineering (ICCoSITE), International Conference on

作者： Sidharta Sidharta Yaya Heryadi Lukas Lukas Wayan Suparta Yulyani Arifin Computer Science Department BINUS Graduated 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

Currently, the performance of the police in Indonesia is often in the spotlight of the public with cases that occur, both on a national and regional scale, including personal experiences who also feel disappointed with the performance of the police. The cases, such as the rape of three children by a biological father in East Luwu, and the barrage of other cases that have occurred, in their handling have left the public disappointed, giving rise to the hashtag percumlaporpolisi on social media, especially on twitter. This hashtag became trending and was widely responded to by the public. Using free hashtag keywords, tweet data is collected using Twitter’s API for sentiment analysis. The datasets obtained from the crawling results is the latest data with a total of 100 datasets. This study applies the naïve bayes algorithm using textblob which aims to determine the value of polarity and subjectivity. From the results of the analysis carried out, the words that appear most often are useless police, police chief, and policeman. While the results of the sentiment analysis that has been carried out are 40 percent positive sentiment, 40 percent are neutral sentiment and 10 percent are negative sentiment from the hashtags used. From these results, according to the keywords used, the percentage of negative sentiment should be greater than positive and neutral sentiment. It is necessary to conduct a more in-depth study related to the model used in the next research.

关键词： Computer science Sentiment analysis Pediatrics Law enforcement Social networking (online) Blogs Biology

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Deep Learning Model for Classifying Public Opinions on Energy Sector IHSG Stocks on the Twitter Social Media Platform

Deep Learning Model for Classifying Public Opinions on Energ...

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Artificial Intelligence Robotics, Signal and Image Processing (AIRoSIP), International Conference on

作者： Bambang Sulistio Yaya Heryadi Lukas Wayan Suparta Ilvico Sonata Computer Science Department Binus Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350327472

ISBN: (纸本)9798350327489

Capital market transactions provide an opportunity for investors to acquire ownership of company shares and capital gains, as well as dividends. However, alongside the benefits, there are risks of capital loss and liquidation, leading to stress and depression due to profit targets and decision-making errors. To mitigate the risk of decision-making errors in investment, data analysis is needed, including sentiment analysis, which influences stock prices. This study aims to develop a new deep learning model to classify Indonesian public opinion on JCI stocks, especially the Energy sector, obtained from the Twitter social media platform. The model will perform sentiment analysis and categorize opinions as negative, neutral, or positive. We created a dataset that was trained using Bidirectional Encoder Representations from Transformers (BERT) to summarize the analysis of public sentiment above so that it can assist investors in studying public sentiment as a reference for investing with a yield precision of 76%, Recall of 77%, and F1-score on 76%.

关键词： Deep learning Sentiment analysis Analytical models Social networking (online) Blogs Decision making Text categorization Bidirectional control Transformers Encoding

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Social Influence Models Based on Starbucks Networks

Social Influence Models Based on Starbucks Networks

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International Conference on Computational Aspects of Social Networks, CASON

作者： Minkyoung Kim Byoung-Tak Zhang June-Sup Lee Personalization Team SK Telecom South Korea Interdisciplinary Program in Cognitive Science Seoul National University South Korea School of Computer Science and Engineering Seoul National University Seoul South Korea Personalization Team SK Telecom Seoul South Korea

Starbucks coffee shops have been spread rapidly and widely all over the world, which implies that there may be diffusive powers among them and thus can be represented as social networks. In particular, the spreading speed of Starbuck Korea was at record levels. In this paper, we constructed social networks using the information about Starbuck Korea (ex. latitude and longitude of each Starbucks store in Korea, the opening date of them, opening orders of them, etc.) and evaluated influence scores of each store to measure the spreading power of Starbucks in Korea. Here, we proposed two network evaluation models, Dynamic Influence Model and Static Influence Model. Through these models, we can represent location based social networks and evaluate each node's diffusive power for expanding the size of networks and for spreading coverage all over the network.

关键词： Social network services Technological innovation Computer networks Telecommunication computing cognitive science Computer science Power engineering and energy Power measurement TV Joining processes

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On Training Flexible Robots using Deep Reinforcement Learning

On Training Flexible Robots using Deep Reinforcement Learnin...

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2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Zach Dwiel Madhavun Candadai Mariano Phielipp Intel AI Labs Bloomington IN U.S.A Program in Cognitive Science and School of Informatics Computing and Engineering at Indiana University Bloomington IN U.S.A Intel AI Labs Phoenix AZ U.S.A

The use of robotics in controlled environments has flourished over the last several decades and training robots to perform tasks using control strategies developed from dynamical models of their hardware have proven very effective. However, in many real-world settings, the uncertainties of the environment, the safety requirements and generalized capabilities that are expected of robots make rigid industrial robots unsuitable. This created great research interest in developing control strategies for flexible robot hardware for which building dynamical models are challenging. In this paper, inspired by the success of deep reinforcement learning (DRL), we systematically study the efficacy of policy search methods using DRL in training flexible robots. Our results indicate that DRL is successfully able to learn efficient and robust policies for complex tasks at various degrees of flexibility. We also note that DRL using Deep Deterministic Policy Gradients can be sensitive to the choice of sensors and adding more informative sensors does not necessarily make the task easier to learn.

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The Role of Certainty and Time Delay in Students' Cheating Decisions during Online Testing 37

The Role of Certainty and Time Delay in Students' Cheating D...

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37th Annual Meeting of the cognitive science Society: Mind, Technology, and Society, CogSci 2015

作者： Chuang, Chia-Yuan Craig, Scotty D. Femiani, John Arizona State University Simulation Modeling and Applied Cognitive Science Program 7171 E Sonoran Arroyo Mall MesaAZ85212 United States Arizona State University Human Systems Engineering 7171 E Sonoran Arroyo Mall MesaAZ85212 United States Arizona State University School of Computing Informatics and Decision System Engineering Peralta Hall 7171 E Sonoran Arroyo Mall Rm 230U MesaAZ85212 United States

ISBN: (纸本)9780991196722

In an attempt to assist proctors to prevent test takers from academic dishonesty in remotely administrated exams, this study investigated the ability of test takers' behaviors during online assessments to predict their cheating decisions. Specifically, this experimental study focused on the role of students' time delay and certainty rating during lab based online testing sessions. The analysis of hierarchical logistic regression indicated that not only time delay but also certainty rating had significantly statistical relation to test takers' cheating decisions. The importance of the two proposed factors during online assessments was discussed and the prospects of the improvements of online proctoring systems were addressed. © cognitive science Society, CogSci *** rights reserved.

关键词： Time delay

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Synthetic Batik Pattern Generator Using Wasserstein Generative Adversarial Network with Gradient Penalty

Synthetic Batik Pattern Generator Using Wasserstein Generati...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Kus Andriadi Yaya Heryadi Lukas Wayan Suparta Ilvico Sonata Computer Science Department Binus Graduate Program Doctor of 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

Batik is an Indonesian world cultural heritage. Batik consists of many kinds of patterns depending on where the batik comes from, Batik-making techniques continue to develop along with technology development. Among the batik making techniques that are widely used are hand-written, stamping, and printing. Batik motifs have been widely used as research material, especially in the field of artificial intelligence. The diverse appearance of batik motifs has attracted many researchers to carry out research on making synthetic batik patterns, one of which uses a Generative Adversarial Network. This paper presents a synthetic batik pattern model based on the Wasserstein Generative Adversarial Network with Gradient Penalty. This model has been proven to create new synthetic batik patterns quite well and almost identical with images provided in the dataset, with the notes if the dataset provided is large.

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Implementation of new services to support ubiquitous computing for campus life

Implementation of new services to support ubiquitous computi...

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Proceedings - Second IEEE Workshop on Software Technologies for Future Embedded and Ubiquitous Systems

作者： Han, Tack-Don Cheong, Cheolho Ahn, Jae-Won Kim, Jong-Young Yoon, Hyung-Min Lee, Chang-Su Shin, Hyon-Gu Lee, Young-Jin Yook, Hyoung-Min Jeon, Myoung-Hoon Choi, Jung Soo Lee, Joo-Hyeon Sohn, Young-Woo Baek, Yoon Su Lee, Sang-Yong Shin, Eun-Dong Kang, WooShik Kim, SeongWoon Dept. of Computer Science Yonsei University Seoul Korea Republic of Dept. of Clothing and Textiles Yonsei University Seoul Korea Republic of Dept. of Psychology Yonsei University Seoul Korea Republic of Grad. Program in Cognitive Science Yonsei University Seoul Korea Republic of Dept. of Mechanical Engineering Yonsei University Seoul Korea Republic of ColorZip Media Inc. Seoul Korea Republic of Samsung Adv. Institute of Technology Seoul Korea Republic of

ISBN: (纸本)0769521231

Many new services have emerged to realize ubiquitous computing environments, owing to the increasing supply of mobile devices and more widespread Internet and wireless network facilities. This paper introduces the U-Campus (Ubiquitous computing for Campus) service. This study has been conducted through interdisciplinary research by four participating departments. The U-Campus Project is part of the UTOPIA project (Ubiquitous computing TOwn Project: Intelligent context Awareness), which covers town- and city-wide environments. Currently, a test bed for U-Campus has been constructed to support various services such as U-Profile, U-Messaging and U-Campus Tour Guide services. Students, professors, school staffs, and campus visitors can easily access the various available campus services by using image-based sensors and mobile devices such as CDMA cellular phones or WiFi smart phones. The major purpose of this research is to provide a context-aware U-Campus environment to users by utilizing sensors and mobile devices currently available in the public sector and the marketplace.

关键词： Computer science

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Cloud-Native Mobile Application Applied for Law and Regulations Harmonization

Cloud-Native Mobile Application Applied for Law and Regulati...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Muhammad Juan Al Qausar Yaya Heryadi Lukas Lukas Wayan Suparta Ilvico Sonata Computer Science Department Binus Graduate Program Doctor of 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

Navigating the complex legal and regulatory landscape requires a sophisticated platform that is not only comprehensive but also user-friendly and enables seamless analysis and document comparison in the legal realm. To address this challenging requirement, this research is dedicated to the user experience (UX) design of state-of the-art cloud-native mobile applications specifically designed for legal and regulatory harmonization. The methodology used is based on design thinking principles and takes advantage of the benefits of cloud computing. These include, but are not limited to, scalability, reliability, and security. The result is a solution that is not only powerful but also cost-effective. The core of this application follows a user-centered design philosophy and involves potential users closely in the design process. A comprehensive evaluation is performed using the System Usability Scale (SUS) methodology to measure the effectiveness and usability of the application. The results of this comprehensive approach are convincing. The application has an impressive 95.5% usage rate, indicating strong user engagement. Furthermore, user satisfaction ratings are particularly high and transformative impact of this application in a complex environment of legal harmonization. Through its innovative design, seamless functionality, and user-centric approach, this application has proven to be not only a technical solution, but also a catalyst for positive change in the legal and regulatory harmonization process.

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Neurocognitive assessment under various human-robot teaming environments

Neurocognitive assessment under various human-robot teaming ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Anna L. Packy Jayesh Jayahankar Arya Teymourlouei Joshua Stone Hyuk Oh Garrett E. Katz James A. Reggia Rodolphe J. Gentili Neuroscience and Cognitive Science Program University of Maryland College Park USA Department of Computer Science University of Maryland College Park USA Department of Electrical & Computer Engineering University of Maryland College Park USA Department of Kinesiology University of Maryland College Park USA Department of Electrical Engineering & Computer Science Syracuse University Syracuse USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Human-robot teaming has become increasingly important with the advent of intelligent machines. Prior efforts suggest that performance, mental workload, and trust are critical elements of human-robot dynamics that can be altered by the robot’s behavior. Most prior human-robot teaming studies used behavioral analyses, but a limited number used neural markers, without the use of physical robots and complex tasks. Here we combine behavioral and EEG cortical dynamics to examine cognitive-motor processes when individuals complete a complex task under various team environments with a robot. The results revealed that altering the robot quality affected both behavioral and EEG dynamics. Task completion with an experienced robot led to greater team performance and human trust along with lower mental workload compared to an inexperienced teammate or when individuals performed alone. EEG changes suggest that different attentional processes were engaged when humans worked with the robot and performed alone, and that visual processing was more prominent when teaming with an inexperienced teammate. This work can inform human cognitive-motor processes and the design of robotic controllers in human-robot teams.

关键词： Visualization Process control Humanoid robots Collaboration Human factors Control systems Electroencephalography Behavioral sciences engineering in medicine and biology Robots

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