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International Journal of Multimedia and Ubiquitous engineering 2016年第7期11卷 145-150页

作者： Kim, Jong-Yun Park, Se-Hwan Kyungdong University Dept of Computer Engineering Kosung Korea Republic of ReSEAT Program Seoul Korea Republic of

With the rapid popularization of explosive smart terminals due to the increase in broadband, a high speed transfer rate can realize the need for 5G mobile technology. Future mobile service technology can accommodate mobile cloud and low-cost media realize an energy efficiency improved mobile communication environment. In addition to a variety of high-tech components, technology development and the convergence of fixed and mobile network/based on the service side of the CPND technical characteristics are required. In addition, the networking and wireless Internet 5G mobile communication system-related key technologies can be combined in a variety of technical characteristics, while 5G of technology convergence in the system should be developed in a way that can make it easier to combine with other technologies. 5G mobile communication system is the rate of transmission of holographic 3D 100Gbps that can transmit images to a mobile network. © 2016 SERSC.

关键词： Energy efficiency

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Investigation of the visual attention role in clinical bioethics decision-making using machine learning algorithms

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Procedia computer Science 2017年 108卷 1165-1174页

作者： Daniel L. Fernandes Rodrigo Siqueira-Batista Andréia P. Gomes Camila R. Souza Israel T. da Costa Felippe da S.L. Cardoso João V. de Assis Gustavo H.L. Caetano Fabio R. Cerqueira Graduate Program in Computer Science Universidade Federal de Viçosa Minas Gerais Brazil Department of Medicine and Nursing Universidade Federal de Viçosa Minas Gerais Brazil Department of Physical Education Universidade Federal de Viçosa Minas Gerais Brazil Department of Production Engineering Universidade Federal Fluminense Rio de Janeiro Brazil

This study proposes the use of a computational approach based on machine learning (ML) algorithms to build predictive models using eye tracking data. Our intention is to provide results that may support the study of medical investigation in the decision-making process in clinical bioethics, particularly in this work, in cases of euthanasia. The data used in the approach were collected from 75 students of the nursing undergraduate course using an eye tracker. The available data were processed through feature selection methods, and were later used to create models capable of predicting the euthanasia decision through ML algorithms. Statistical experiments showed that the predictive model resultant from the multilayer perceptron (MLP) algorithm led to the best performance compared with the other tested algorithms, presenting an accuracy of 90.7% and a mean area under the ROC curve of 0.90. Interesting knowledge (patterns and rules) for the studied bioethical decision-making was extracted using simulations with MLP models and inspecting the obtained decision-tree rules. The good performance shown by the obtained MLP predictive model demonstrates that the proposed investigation approach may be used to test scientific hypotheses related to visual attention and decision-making.

关键词： Visual attention Decision-making in bioethics Mobile eye tracking Machine learning in medicine

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BrainNet: A Multi-Person Brain-to-Brain Interface for Direct Collaboration Between Brains

arXiv

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arXiv 2018年

作者： Jiang, Linxing Stocco, Andrea Losey, Darby M. Abernethy, Justin A. Prat, Chantel S. Rao, Rajesh P.N. University of Washington Paul G. Allen School of Computer Science & Engineering SeattleWA98195 United States University of Washington Department of Psychology SeattleWA98195 United States University of Washington Institute for Learning and Brain Sciences SeattleWA98195 United States Carnegie Mellon University Joint Program in Neural Computation & Machine Learning PittsburghPA15213 United States Carnegie Mellon University Center for the Neural Basis of Cognition PittsburghPA15213 United States University of Washington Institute for Neuroengineering SeattleWA98195 United States University of Washington Center for Neurotechnology SeattleWA98195 United States

We present BrainNet which, to our knowledge, is the first multi-person non-invasive direct brain-to-brain interface for collaborative problem solving. The interface combines electroencephalography (EEG) to record brain signals and transcranial magnetic stimulation (TMS) to deliver information noninvasively to the brain. The interface allows three human subjects to collaborate and solve a task using direct brain-to-brain communication. Two of the three subjects are designated as "Senders" whose brain signals are decoded using real-time EEG data analysis. The decoding process extracts each Sender’s decision about whether to rotate a block in a Tetris-like game before it is dropped to fill a line. The Senders’ decisions are transmitted via the Internet to the brain of a third subject, the "Receiver," who cannot see the game screen. The Senders’ decisions are delivered to the Receiver’s brain via magnetic stimulation of the occipital cortex. The Receiver integrates the information received from the two Senders and uses an EEG interface to make a decision about either turning the block or keeping it in the same orientation. A second round of the game provides an additional chance for the Senders to evaluate the Receiver’s decision and send feedback to the Receiver’s brain, and for the Receiver to rectify a possible incorrect decision made in the first round. We evaluated the performance of BrainNet in terms of (1) Group-level performance during the game, (2) True/False positive rates of subjects’ decisions, and (3) Mutual information between subjects. Five groups, each with three human subjects, successfully used BrainNet to perform the collaborative task, with an average accuracy of 81.25%. Furthermore, by varying the information reliability of the Senders by artificially injecting noise into one Sender’s signal, we investigated how the Receiver learns to integrate noisy signals in order to make a correct decision. We found that like conventional social networks, BrainN

关键词： Electrophysiology

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Long-term Room Temperature Instability in Thermal Conductivity of InGaZnO Thin Films

Long-term Room Temperature Instability in Thermal Conductivi...

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作者： Cui, Boya Bruce Buchholz, D. Zeng, Li Bedzyk, Michael Chang, Robert P. H. Grayson, Matthew Applied Physics Program Northwestern University EvanstonIL60208 United States Electrical Engineering and Computer Science Northwestern University EvanstonIL60208 United States Material Science and Engineering Northwestern University EvanstonIL60208 United States

The cross-plane thermal conductivities of InGaZnO (IGZO) thin films in different morphologies were measured on three occasions within 19 months, using the 3ω method at room temperature 300 K. Amorphous (a-), semi-crystalline (semi-c-) and crystalline (c-) IGZO films were grown by pulsed laser deposition (PLD), followed by X-ray diffraction (XRD) for evaluation of film quality and crystallinity. Semi-c-IGZO shows the highest thermal conductivity, even higher than the most ordered crystal-like phase. After being stored in dry low-oxygen environment for months, a drastic decrease of semi-c-IGZO thermal conductivity was observed, while the thermal conductivity slightly reduced in c-IGZO and remained unchanged in a-IGZO. This change in thermal conductivity with storage time can be attributed to film structural relaxation and vacancy diffusion to grain boundaries. © 2016 Materials Research Society.

关键词： Thin films

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Physiotherapy intervention during level I of pulmonary rehabilitation on chronic obstructive pulmonary disease: A systematic review

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Open Respiratory Medicine Journal 2016年 10卷 12-19页

作者： de Alvarenga, Guilherme Medeiros Gamba, Humberto Remigio Hellman, Lilian Elisa Ferrari, Vanusa Ganzert de Macedo, Rafael Michel Graduate Program in Electrical and Computer Engineering Universidade Tecnológica Federal do Paraná Curitiba PR Brazil Specialization Program in Physiotherapy on Gerontology Universidade Positivo Curitiba PR Brazil Heart Academy Rehabilitation Service from Hospital Cardiológico Costantini Curitiba PR Brazil Graduate Program in Health Sciences Pontifícia Universidade Católica do Paraná Curitiba PR Brazil

Background: The progressive and chronic course of COPD, characterized by difficulty in breathing, can be aggravated by periods of increased symptoms (exacerbation). The treatment often involves in-hospital care and among the interventions applied in COPD patients, physical therapy prompts good results. However the most used techniques are not properly pinpointed and there is no consensus in the literature regarding its effectiveness. Methods: A systematic review was performed to identify which physical therapy treatment was applied in these cases. The following bibliographic databases were consulted: PubMed, and Bireme Portal, Periódicos Capes. Controlled randomized clinical trials that is under went physical therapy intervention in patients hospitalized for exacerbated COPD without the use of NIV (non-invasive ventilation) were included in the study. The PEDro scale, which has a score of 0-10, was used to evaluate the quality of studies included in this review. Results: The electronic search yielded a total of 302 references published in English, of which only 6 met the criteria for inclusion and exclusion. Conclusion: It is possible to infer that physiotherapy’s techniques used in patients hospitalized for COPD exacerbation, based on this review, were the high frequency chest wall oscillation (HFCWO) on the chest;relaxing massage and active exercises, electrical stimulation via electro-acupuncture;strengthening of the quadriceps;the ELTGOL bronchial drainage technique (expiration with the glottis open in the lateral posture) and an incentive spirometer. © 2016, de Alvarenga et al.;Licensee Bentham Open.

关键词： COPD Exacerbation Hospitalization Physiotherapy intervention

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An Improvement Data Hiding Scheme Based on Formula Fully Exploiting Modification Directions and Pixel Value Differencing Method 11

An Improvement Data Hiding Scheme Based on Formula Fully Exp...

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11th Asia Joint Conference on Information Security, AsiaJCIS 2016

作者： Kuo, Wen-Chung Li, Jyun-Jia Wang, Chun-Cheng Wuu, Lih-Chyau Huang, Yu-Chih Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Taiwan Graduate School of Engineering Science and Technology Doctoral Program National Yunlin University of Science and Technology Taiwan Department of Information Management Tainan University of Technology Taiwan

ISBN: (纸本)9781509022854

Recently, a modified data hiding scheme based on pixel value differencing and improving exploiting modification directions is proposed by Shen and Huang. There are two major contributions in this scheme. One is to enhance the embedding rate and good embedding capacity and the other is an optimization problem used to solve the overflow/ underflow problem. In fact, they propose the similar brute force method to solve overflow/underflow problem in their proposed scheme. To overcome the overflow/underflow problem exactly, we will propose the close form to solve this problem in this paper. Then, an improvement data hiding scheme based on FFEMD (Formula Fully Exploiting Modification Directions) and pixel value differencing method is proposed. According to our analysis, it is not only to keep the advantages of Shen-Huang scheme but also to use the close form to solve the overflow/ underflow problem. © 2016 IEEE.

关键词： Pixels

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On Social Network Firewall Selection

On Social Network Firewall Selection

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International Conference on Computing, Networking and Communications

作者： Anisha Mazumder Arunabha Sen Computer Science and Engineering Program School of Computing Informatics and Decision System Engineering Arizona State University

ISBN: (纸本)9781467385800

It is common knowledge that the decision of an individual regarding adoption of a product or technology is, more often than not, heavily influenced by their friends and acquaintances. In real world, there are different competing products and innovations that try to garner as many loyal followers as possible. Over the past few years, there has been a significant interest in the research community to study social network problems with a flavor of competition. Such problems often focus on identification of a set of people in a given social network by the competing players in order to achieve some goal. In this paper, we introduce the weighted Segregating Vertex Set (wSVS) problem, in which we are given a weighted undirected graph with a subset of nodes identified as the seedset of the first player and the goal for the second player is to identify a subset of nodes (firewall) of minimum cumulative weight, such that the total weight of the nodes reachable by the first player is strictly less than the total weight of the nodes not reachable by the first player. Thus, the second player tries to contain the reach of the first player within the social network community. This problem is also relevant for containment of disease in epidemiology, containment of forest fire and several other domains. We prove that this problem is NP-complete and provide an optimal solution through the use of Mixed Integer Linear programming. We also provide a heuristic solution for the wSVS problem and show its efficacy through detailed experimentation. Our heuristic solution delivers near optimal solution in lesser time compared to that needed to find the optimal solution.

关键词： Social network services Sociology Statistics Companies Particle separators Diseases Social computing

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Forecasting: theory and practice

arXiv

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arXiv 2020年

作者： Petropoulos, Fotios Apiletti, Daniele Assimakopoulos, Vassilios Babai, Mohamed Zied Barrow, Devon K. Taieb, Souhaib Ben Bergmeir, Christoph Bessa, Ricardo J. Bijak, Jakub Boylan, John E. Browell, Jethro Carnevale, Claudio Castle, Jennifer L. Cirillo, Pasquale Clements, Michael P. Cordeiro, Clara Oliveira, Fernando Luiz Cyrino de Baets, Shari Dokumentov, Alexander Ellison, Joanne Fiszeder, Piotr Franses, Philip Hans Frazier, David T. Gilliland, Michael Gönül, M. Sinan Goodwin, Paul Grossi, Luigi Grushka-Cockayne, Yael Guidolin, Mariangela Guidolin, Massimo Gunter, Ulrich Guo, Xiaojia Guseo, Renato Harvey, Nigel Hendry, David F. Hollyman, Ross Januschowski, Tim Jeon, Jooyoung Jose, Victor Richmond R. Kang, Yanfei Koehler, Anne B. Kolassa, Stephan Kourentzes, Nikolaos Leva, Sonia Li, Feng Litsiou, Konstantia Makridakis, Spyros Martin, Gael M. Martinez, Andrew B. Meeran, Sheik Modis, Theodore Nikolopoulos, Konstantinos Önkal, Dilek Paccagnini, Alessia Panagiotelis, Anastasios Panapakidis, Ioannis Pavía, Jose M. Pedio, Manuela Pedregal, Diego J. Pinson, Pierre Ramos, Patrícia Rapach, David E. Reade, J. James Rostami-Tabar, Bahman Rubaszek, Michal Sermpinis, Georgios Shang, Han Lin Spiliotis, Evangelos Syntetos, Aris A. Talagala, Priyanga Dilini Talagala, Thiyanga S. Tashman, Len Thomakos, Dimitrios Thorarinsdottir, Thordis Todini, Ezio Arenas, Juan Ramón Trapero Wang, Xiaoqian Winkler, Robert L. Yusupova, Alisa Ziel, Florian School of Management University of Bath United Kingdom Politecnico di Torino Turin Italy Forecasting and Strategy Unit School of Electrical and Computer Engineering National Technical University of Athens Greece Kedge Business School France Department of Management Birmingham Business School University of Birmingham United Kingdom Belgium Faculty of Information Technology Monash University Melbourne Australia INESC TEC – Institute for Systems and Computer Engineering Technology and Science Porto Portugal Department of Social Statistics and Demography University of Southampton United Kingdom Centre for Marketing Analytics and Forecasting Lancaster University Management School Lancaster University United Kingdom School of Mathematics and Statistics University of Glasgow United Kingdom Department of Mechanical and Industrial Engineering University of Brescia Italy Magdalen College University of Oxford United Kingdom ZHAW School of Management and Law Zurich University of Applied Sciences Switzerland ICMA Centre Henley Business School University of Reading United Kingdom Faculdade de Ciências e Tecnologia Universidade do Algarve Portugal CEAUL Faculdade de Ciências Universidade de Lisboa Portugal Brazil Department of Business Informatics and Operations Management Faculty of Economics and Business Administration Universiteit Gent Belgium Let’s Forecast Australia Faculty of Economic Sciences and Management Nicolaus Copernicus University in Torun Poland Econometric Institute Erasmus School of Economics Rotterdam Netherlands Department of Econometrics and Business Statistics Monash University Melbourne Australia SAS United States Newcastle Business School Northumbria University Newcastle upon Tyne United Kingdom Department of Statistical Sciences University of Padua Italy Darden School of Business University of Virginia United States Finance Department Bocconi University Baffi-CAREFIN Centre Milan Italy Department of Tourism and Service Management MODUL Un

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases. © 2020, CC BY.

关键词： Forecasting

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The development of bank applications for debtors' selection by using Naïve Bayes classifier technique

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IOP Conference Series: Materials Science and engineering 2018年第1期407卷

作者： S L B Ginting J Adler Y R Ginting A H Kurniadi Study Program of Computer System Universitas Komputer Indonesia Jl. Dipati Ukur 112-116 Bandung 40132 Indonesia. Department of Mechanical Engineering Universitas Riau Kampus Bina Widya KM 125 Simpang Baru Pekanbaru 28293 Indonesia.

The purpose of this study is to create an application which functions automatically with high accuracy when analyzing bank customer data. This needed due to non-performing loans occurring frequently caused by the inaccuracy of credit analysts in the assessment of creditworthiness. This can be seen in the incident occurred in a public bank located in Bandung. This bank does not have the database that serves to accommodate data history and the method used in assessing creditworthiness is merely based on the simple statistical analysis. This leads to reduced accuracy and speed in the decision-making process. This research applies Naïve Bayes Classifier (NBC) method, a Data Mining technique. This helps credit analysts to select customers who are truly eligible to be given credit so that non-performing loan can be avoided. NBC calculates the probability of one class from each group of attributes and determines which class is most optimal. The accuracy of the NBC sampling test from 501 data is 94% compared to the decision made by a credit analyst. It can be concluded that this application is very helpful for credit analysts in recommending customers who are eligible for a loan to the bank's decision maker.

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Mesostructured composite materials with electrically tunable upconversion properties

arXiv

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arXiv 2017年

作者： Mundoor, Haridas Smalyukh, Ivan I. Department of Physics and Department of Electrical Computer and Energy Engineering Liquid Crystal Materials Research Center University of Colorado BoulderCO80309 Singapore Materials Science and Engineering Program Liquid Crystal Materials Research Center University of Colorado BoulderCO80309 Renewable and Sustainable Energy Institute National Renewable Energy Laboratory University of Colorado BoulderCO80309 United States

A promising approach of designing mesostructured materials with novel physical behavior is to combine unique optical and electronic properties of solid nanoparticles with long-range ordering and facile response of soft matter to weak external stimuli. Here we design, practically realize, and characterize orientationally ordered nematic liquid crystalline dispersions of rod-like upconversion nanoparticles. Boundary conditions on particle surfaces, defined through surface functionalization, promote spontaneous unidirectional self-alignment of the dispersed rod-like nanoparticles, mechanically coupled to the molecular ordering direction of the thermotropic nematic liquid crystal host. As host is electrically switched at low voltages . 1V, nanorods rotate, yielding tunable upconversion and polarized luminescence properties of the composite. We characterize spectral and polarization dependencies, explain them through invoking models of electrical switching and upconversion dependence on crystalline matrices of nanorods, and discuss potential practical uses. Copyright © 2017, The Authors. All rights reserved.

关键词： Nanorods

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