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What's in a cue?: Using natural language processing to quantify content characteristics of episodic future thinking in the context of overweight and obesity

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Health psychology and behavioral medicine 2025年第1期13卷 2510417页

作者： Haylee Downey Shuangshuang Xu Sareh Ahmadi Aditya Shah Jeremiah M Brown Warren K Bickel Leonard H Epstein Allison N Tegge Edward A Fox Jeffrey S Stein Fralin Biomedical Research Institute at VTC Roanoke VA USA. Graduate Program in Translational Biology Medicine and Health Virginia Tech Blacksburg VA USA. Department of Computer Science Blacksburg VA USA. Department of Pediatrics University at Buffalo Jacobs School of Medicine and Biomedical Sciences Buffalo NY USA. Department of Human Nutrition Foods and Exercise Virginia Tech Blacksburg VA USA.

Episodic future thinking (EFT), an intervention in which participants vividly imagine their future, has been explored as a cognitive intervention to reduce delay discounting and decrease engagement in harmful health behaviors. In these studies, participants generate text descriptions of personally meaningful future events. The content of these text descriptions, or cues, is heterogeneous and can vary along several dimensions (e.g. references to health, celebrations, family; vividness; emotional valence). However, little work has quantified this heterogeneity or potential importance for EFT's efficacy. To better understand the potential impact of EFT content in the context of health behavior change (e.g. diet) among people with or at risk for obesity and related conditions, we used data from 19 prior EFT studies, including 1705 participants (mean body mass index = 33.1) who generated 9714 cues. We used natural language processing to classify EFT content and examined whether EFT content moderated effects on delay discounting. Cues most commonly involved recreation, food, and spending time with family, and least commonly involved references to health and self-improvement. Cues were generally classified as highly vivid, episodic, and positively valent (consistent with the intervention's design). In multivariate regression with model selection, EFT content did not significantly moderate the effect of the episodic thinking intervention. Thus, we find no evidence that any of the content characteristics we examined were important moderators of the efficacy of EFT in reducing delay discounting. This suggests that EFT's efficacy is robust against variability in these characteristics. However, note that in all studies, EFT methods were designed to generate high levels of vividness, episodicity, and emotional valence, potentially resulting in a ceiling effect in these content areas. Moreover, EFT content was not experimentally manipulated, limiting causal inference. Future stud

关键词： Delay discounting episodic future thinking intervention effectiveness natural language processing obesity type 2 diabetes

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Multi-Kernel Fusion for RBF Neural Networks

arXiv

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arXiv 2020年

作者： Atif, Syed Muhammad Khan, Shujaat Naseem, Imran Togneri, Roberto Bennamoun, Mohammed Graduate School of Science and Engineering Karachi Institute of Economics and Technology Korangi Creek Karachi75190 Pakistan Daejeon34141 Korea Republic of College of Engineering Karachi Institute of Economics and Technology Korangi Creek Karachi75190 Pakistan School of Electrical Electronic and Computer Engineering University of Western Australia 35 Stirling Highway CrawleyWA6009 Australia School of Computer Science and Software Engineering University of Western Australia 35 Stirling Highway CrawleyWA6009 Australia

A simple yet effective architectural design of radial basis function neural networks (RBFNN) makes them amongst the most popular conventional neural networks. The current generation of radial basis function neural network is equipped with multiple kernels which provide significant performance benefits compared to the previous generation using only a single kernel. In existing multi-kernel RBF algorithms, multi-kernel is formed by the convex combination of the base/primary kernels. In this paper, we propose a novel multi-kernel RBFNN in which every base kernel has its own (local) weight. This novel flexibility in the network provides better performance such as faster convergence rate, better local minima and resilience against stucking in poor local minima. These performance gains are achieved at a competitive computational complexity compared to the contemporary multi-kernel RBF algorithms. The proposed algorithm is thoroughly analysed for performance gain using mathematical and graphical illustrations and also evaluated on three different types of problems namely: (i) pattern classification, (ii) system identification and (iii) function approximation. Empirical results clearly show the superiority of the proposed algorithm compared to the existing state-of-the-art multi-kernel approaches. Copyright © 2020, The Authors. All rights reserved.

关键词： Radial basis function networks

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Control Method of Effect of Robust Optimization in Multi-Player Multi-Objective Decision-Making

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American Journal of Operations Research 2019年第4期9卷 175-191页

作者： Tomoaki Yatsuka Aya Ishigaki Yuki Kinoshita Tetsuo Yamada Masato Inoue Department of Industrial Administration Graduate School of Science and Technology Tokyo University of Science Chiba Japan Management Science and Social Informatics Program Department of Informatics Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo Japan Department of Mechanical Engineering Informatics Meiji University Kanagawa Japan

In the real situations of supply chain, there are different parts such as facilities, logistics warehouses and retail stores and they handle common kinds of products. In this research, these situations are focused on as the background of this research. They deal with the common quantities of their products, but due to their different environments, the optimal production quantity of one part can be unacceptable to another part and it may suffer a heavy loss. To avoid that kind of unacceptable situations, the common production quantities should be acceptable to all parts in one supply chain. Therefore, the motivation of this research is the necessity of the method to find the production quantities that make all decision makers acceptable is needed. However, it is difficult to find the production quantities that make all decision makers acceptable. Moreover, their acceptable ranges do not always have common ranges. In the decision making of car design, there are similar situations to this type of decision making. The performance of a car consists of purposes such as fuel efficiency, size and so on. Improving one purpose makes another worse and the relationship between these purposes is tradeoff. In these cases, Suriawase process is applied. This process consists of negotiations and reviews of the requirements of the purposes. In the step of negotiations, the requirements of the purposes are share among all decision makers and the solution that makes them as satisfied as possible. In the step of reviews of the requirements, they are reviewed based on the result of the negotiation if the result is unacceptable to some of decision makers. Therefore, through the iterations of the two steps, the solution that makes all decision makers satisfied is obtained. However, in the previous research, the effects that one decision maker reviews requirements in Suriawase process are quantified, but the mathematical model to modify the ranges of production quantities of all decision ma

关键词： Linear Physical programming Suriawase Process Multi-Player Decision-Making Supply Chain Coordination Robust Optimization

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LearningEMS: A Unified Framework and Open-source Benchmark for Learning-based Energy Management of Electric Vehicles

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Engineering 2024年

作者： Yong Wang Hongwen He Yuankai Wu Pei Wang Haoyu Wang Renzong Lian Jingda Wu Qin Li Xiangfei Meng Yingjuan Tang Fengchun Sun Amir Khajepour School of Mechanical Engineering Beijing Institute of Technology Beijing 100081 China College of Computer Science Sichuan University Chengdu 100081 China Shenzhen International Graduate School Tsinghua University Shenzhen 518000 China The Hong Kong Polytechnic University Hong Kong 999077 China School of Mechanical Engineering Guangxi University Nanning 530000 China Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON N2L3G1 Canada

An effective energy management strategy (EMS) is essential to optimize the energy efficiency of electric vehicles (EVs). With the advent of advanced machine learning techniques, the focus on developing sophisticated EMS for EVs is increasing. Here, we introduce LearningEMS: a unified framework and open-source benchmark designed to facilitate rapid development and assessment of EMS. LearningEMS is distinguished by its ability to support a variety of EV configurations, including hybrid EVs, fuel cell EVs, and plug-in EVs, offering a general platform for the development of EMS. The framework enables detailed comparisons of several EMS algorithms, encompassing imitation learning, deep reinforcement learning (RL), offline RL, model predictive control, and dynamic programming. We rigorously evaluated these algorithms across multiple perspectives: energy efficiency, consistency, adaptability, and practicability. Furthermore, we discuss state, reward, and action settings for RL in EV energy management, introduce a policy extraction and reconstruction method for learning-based EMS deployment, and conduct hardware-in-the-loop experiments. In summary, we offer a unified and comprehensive framework that comes with three distinct EV platforms, over 10 000 km of EMS policy data set, ten state-of-the-art algorithms, and over 160 benchmark tasks, along with three learning libraries. Its flexible design allows easy expansion for additional tasks and applications. The open-source algorithms, models, data sets, and deployment processes foster additional research and innovation in EV and broader engineering domains.

关键词： Energy management Electric vehicles Reinforcement learning Machine learning Open-source benchmark

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Room-Temperature Charge-to-Spin Conversion from Quasi-2D Electron Gas at SrTiO3-Based Interfaces

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physica status solidi (RRL) – Rapid Research Letters 2023年第6期17卷

作者： Utkarsh Shashank Angshuman Deka Chen Ye Surbhi Gupta Rohit Medwal Rajdeep Singh Rawat Hironori Asada X. Renshaw Wang Yasuhiro Fukuma Department of Physics and Information Technology Faculty of Computer Science and System Engineering Kyushu Institute of Technology 680-4 Kawazu Iizuka 820-8502 Japan Birck Nanotechnology Center School of Electrical and Computer Engineering Purdue University West Lafayette IN 47907 USA School of Physical and Mathematical Sciences Nanyang Technological University 637616 Singapore Natural Sciences and Science Education National Institute of Education Nanyang Technological University 637616 Singapore Department of Physics Indian Institute of Technology Kanpur Kanpur 208016 India Graduate School of Sciences and Technology for Innovation Yamaguchi University 2-16-1 Tokiwadai Ube 755-8611 Japan School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore Research Center for Neuromorphic AI hardware Kyushu Institute of Technology Kitakyushu 808-0196 Japan

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The brain that understands different cultures: MRI-measured brain structure correlates with cultural intelligence

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Acta Psychologica 2025年 258卷

作者： Keisuke Kokubun Kiyotaka Nemoto Yoshinori Yamakawa Open Innovation Institute Kyoto University Kyoto Japan Graduate School of Management Kyoto University Kyoto Japan Department of Psychiatry Institute of Medicine University of Tsukuba Tsukuba Japan Institute of Innovative Research Tokyo Institute of Technology Meguro Tokyo Japan ImPACT Program of Council for Science Technology and Innovation (Cabinet Office Government of Japan) Chiyoda Tokyo Japan Office for Academic and Industrial Innovation Kobe University Kobe Japan Brain Impact Kyoto Japan

In today's world of increasing globalization, the importance of cultural intelligence (CQ), a necessary capability for cross-cultural adaptation, is becoming more and more recognized. Therefore, the purpose of this paper is to clarify the relationship between brain structure measured by gray matter volume (GMV) and CQ. Using data from 310 healthy men and women collected in Japan, we investigated whole-brain and regional GMV and Metacognitive, Motivational, and Behavioral CQ. As a result, significant positive correlations surviving multiple comparisons were found between whole-brain, frontal, limbic, occipital, and parietal GMV and Behavioral CQ, and between subcortical GMV and Motivational CQ. Subsequent exploratory analyses found significant correlations surviving multiple comparisons between the left angular gyrus and Behavioral CQ, and also suggested relationships between other regions, such as the anterior cingulate cortex, calcarine sulcus, caudate nucleus, and Rolandic operculum, and Behavioral CQ or Motivational CQ. This is the first study to clarify the relationship between cultural intelligence and brain structure.

关键词： Anterior cingulate cortex Angular gyrus Caudate nucleus Calcarine sulcus Cultural intelligence Gray matter volume Rolandic operculum

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Designing Fiber Optic Network using Voronoi Diagram Approach 3

Designing Fiber Optic Network using Voronoi Diagram Approach

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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Mansuan, Melki Sadekh Soewito, Benfano Hamdani, Mohammad Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Fiber optic is a transmission medium which is currently the most good for data transmits, because it also can be transmitted even voice and video. In most cases a fiber optic network has been implemented using clustering method, where this method assumed inefficient due to the utilization of fiber optic that is not maximized, and the numbers of the Distribution Point used is more. Thus, this paper proposed new design using Voronoi diagrams in selecting the strategic location of the Distribution Point. By utilizing an image from Google map and html code, we created polygons of Voronoi based on the coordinate point of the candidate's location. The results are getting a value reduction/efficiency in context the use of the Distribution Point is 48%, reduction of unused fiber optics is from 171.23% to 39.72%, and cost efficiency is 50.39%. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Fiber optics

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Human Anatomy Learning Systems Using Augmented Reality on Mobile Application 3

Human Anatomy Learning Systems Using Augmented Reality on Mo...

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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Kurniawan, Michael H. Suharjito Diana Witjaksono, Gunawan Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Students generally experience difficulties in learning human body anatomy due to constraints to visualize the body anatomy from 2D into 3D image. This research aims to develop a human anatomy learning system using augmented reality technology. By using this system, it is expected that students can easily understand the anatomy of the human body using a 3D image visualization. The method used in this system is augmented reality marker on mobile computing platform. The marker is captured by taking a picture. Then, the captured image is divided into pieces and the pattern is matched with images stored in the database. In this research, we use Floating Euphoria Framework and combine it with the SQLite database. Augmented reality anatomy system of the human body has features that can interactively display the whole body or parts of the human organs. To evaluate the usefulness of the application, we tested the augmented reality anatomy system with high school students and medical students for learning the anatomy of the human body. The results show that the human anatomy learning system with interactive augmented reality visualization helps students learn human anatomy more easily. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Augmented reality

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Elucidation of local structure deformation in κ−(BEDT−TTF)2Cu[N(CN)2]Br by x-ray fluorescence holography

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Physical Review B 2021年第21期103卷 214106-214106页

作者： Artoni Kevin R. Ang Riho Marumi Ayana Sato-Tomita Koji Kimura Naohisa Happo Kazuto Akagi Takahiko Sasaki Kouichi Hayashi Department of Physical Science and Engineering Nagoya Institute of Technology Gokiso Showa Nagoya 466–8555 Japan Division of Biophysics Department of Physiology Jichi Medical University Yakushiji Shimotsuke Tochigi 329–0498 Japan Department of Computer and Network Engineering Graduate School of Information Sciences Hiroshima City University Asa Minami-ku Hiroshima 731–3194 Japan Advanced Institute for Materials Research (AIMR) Tohoku University 2-1-1 Katahira Aoba Sendai 980–8577 Japan Institute for Materials Research Tohoku University 2-1-1 Katahira Aoba Sendai 980–8577 Japan Frontier Research Institute for Materials Science Nagoya Institute of Technology Gokiso Showa Nagoya 466–8555 Japan

κ−(BEDT−TTF)2Cu[N(CN)2]Br (κ−Br) is an organic superconductor that changes to an Anderson-type insulator due to the random defects introduced by x-ray irradiation. In this study, we directly investigated the effects of irradiation on the local structures in the anion layer of κ−Br using x-ray fluorescence holography. The local structures around the Cu atoms in the anion layer were directly reconstructed from holograms. Prior to radiation damage, the reconstruction clearly shows the atomic images of the Br and N atoms that are directly coordinated to Cu. In the irradiated samples, the N images in the reconstructions were strongly suppressed as a result of the positional fluctuations of N introduced by the defects induced by irradiation. Using the previously proposed “bond-shifted” model and the thermal vibration amplitudes calculated from molecular dynamics simulations, we simulated the holograms and the atomic reconstructions of the anion layer. The simulations show that the “bond-shifted” model, along with thermal vibrations at 100 K, suppresses the N atomic images, as was observed in the experimental reconstructions.

关键词： Defects Radiation damage Organic compounds Molecular dynamics X-ray fluorescence holography

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Waiting-Time Estimation in Bank Customer Queues using RPROP Neural Networks 3

Waiting-Time Estimation in Bank Customer Queues using RPROP ...

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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Satya Hermanto, Rinda Parama Suharjito Diana Nugroho, Ariadi Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

In daily banking customer queues, unknown waiting-time could lower customer experience. Little's Law formula in Queue Theory provides a generic formula for waiting-time, but it cannot be implemented directly to give finite wait-time estimation in real-life. This study aims to investigate predictive variables that explain waiting-time duration. This paper uses Fast Artificial Neural Network engine to implement Artificial Neural Networks method. To train Artificial Neural Networks, Resilient Propagation was used. Time-series approach and structural approach for input neuron was compared. Average duration from previous interval and number of server was proposed to increase structural variable like Queue Length and Head of Line Duration estimator variable. To determine the best configuration for number of neuron in input and hidden layer, experimental method was used. The results of this study show that structural approach provides better estimation than time-series approach. Furthermore, modified helper variable combination provides a more refined result. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Time series

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