scholarly journals Emotional agents - state of the art and applications

2015 ◽  
Vol 12 (4) ◽  
pp. 1121-1148 ◽  
Author(s):  
Mirjana Ivanovic ◽  
Zoran Budimac ◽  
Milos Radovanovic ◽  
Vladimir Kurbalija ◽  
Weihui Dai ◽  
...  
Keyword(s):  
Emotional Intelligence ◽  
State Of The Art ◽  
Real Life ◽  
Data Sets ◽  
Emotional Information ◽  
Intelligent Software ◽  
Research Activities ◽  
Intelligent Software Agents ◽  
Wide Range ◽  
Emotional Agents

last decade, intensive research on emotional intelligence has advanced significantly from its theoretical basis, analytical studies and processing technology to exploratory applications in a wide range of real-life domains. This paper brings new insights in the field of emotional, intelligent software agents. The first part is devoted to an overview of the state-of-the-art in emotional intelligence research with emphasis on emotional agents. A wide range of applications in different areas like modeling emotional agents, aspects of learning in emotional environments, interactive emotional systems and so on are presented. After that we suggest a systematic order of research steps with the idea of proposing an adequate framework for several possible real-life applications of emotional agents. We recognize that it is necessary to apply specific methods for dynamic data analysis in order to identify and discover new knowledge from available emotional information and data sets. The last part of the paper discusses research activities for designing an agent-based architecture, in which agents are capable of reasoning about and displaying some kind of emotions based on emotions detected in human speech, as well as online documents.

A Study of the State of the Art in Synthetic Emotional Intelligence in Affective Computing

2016 ◽  
Vol 7 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Syeda Erfana Zohora ◽  
A. M. Khan ◽  
Arvind K. Srivastava ◽  
Nhu Gia Nguyen ◽  
Nilanjan Dey
Keyword(s):  
Emotional Intelligence ◽  
Affective Computing ◽  
Ethical Issues ◽  
State Of The Art ◽  
Real Life ◽  
Life Time ◽  
The State ◽  
Point Of View ◽  
General Idea ◽  
Research Activities

In the last few decades there has been a tremendous amount of research on synthetic emotional intelligence related to affective computing that has significantly advanced from the technological point of view that refers to academic studies, systematic learning and developing knowledge and affective technology to a extensive area of real life time systems coupled with their applications. The objective of this paper is to present a general idea on the area of emotional intelligence in affective computing. The overview of the state of the art in emotional intelligence comprises of basic definitions and terminology, a study of current technological scenario. The paper also proposes research activities with a detailed study of ethical issues, challenges with importance on affective computing. Lastly, we present a broad area of applications such as interactive learning emotional systems, modeling emotional agents with an intention of employing these agents in human computer interactions as well as in education.

scholarly journals An Interoperability Platform Enabling Reuse of Electronic Health Records for Signal Verification Studies

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Mustafa Yuksel ◽  
Suat Gonul ◽  
Gokce Banu Laleci Erturkmen ◽  
Ali Anil Sinaci ◽  
Paolo Invernizzi ◽  
...  
Keyword(s):  
Real Life ◽  
Case Series ◽  
Background Information ◽  
Data Sets ◽  
Local Data ◽  
Lombardy Region ◽  
Common Information ◽  
Spontaneous Reports ◽  
Wide Range ◽  
Common Information Model

Depending mostly on voluntarily sent spontaneous reports, pharmacovigilance studies are hampered by low quantity and quality of patient data. Our objective is to improve postmarket safety studies by enabling safety analysts to seamlessly access a wide range of EHR sources for collecting deidentified medical data sets of selected patient populations and tracing the reported incidents back to original EHRs. We have developed an ontological framework where EHR sources and target clinical research systems can continue using their own local data models, interfaces, and terminology systems, while structural interoperability and Semantic Interoperability are handled through rule-based reasoning on formal representations of different models and terminology systems maintained in the SALUS Semantic Resource Set. SALUS Common Information Model at the core of this set acts as the common mediator. We demonstrate the capabilities of our framework through one of the SALUS safety analysis tools, namely, the Case Series Characterization Tool, which have been deployed on top of regional EHR Data Warehouse of the Lombardy Region containing about 1 billion records from 16 million patients and validated by several pharmacovigilance researchers with real-life cases. The results confirm significant improvements in signal detection and evaluation compared to traditional methods with the missing background information.

A Study of the State of the Art in Synthetic Emotional Intelligence in Affective Computing

2020 ◽  
pp. 1199-1212
Author(s):  
Syeda Erfana Zohora ◽  
A. M. Khan ◽  
Arvind K. Srivastava ◽  
Nhu Gia Nguyen ◽  
Nilanjan Dey
Keyword(s):  
Emotional Intelligence ◽  
Affective Computing ◽  
Ethical Issues ◽  
State Of The Art ◽  
Real Life ◽  
Life Time ◽  
The State ◽  
Point Of View ◽  
General Idea ◽  
Tremendous Amount

In the last few decades there has been a tremendous amount of research on synthetic emotional intelligence related to affective computing that has significantly advanced from the technological point of view that refers to academic studies, systematic learning and developing knowledge and affective technology to a extensive area of real life time systems coupled with their applications. The objective of this paper is to present a general idea on the area of emotional intelligence in affective computing. The overview of the state of the art in emotional intelligence comprises of basic definitions and terminology, a study of current technological scenario. The paper also proposes research activities with a detailed study of ethical issues, challenges with importance on affective computing. Lastly, we present a broad area of applications such as interactive learning emotional systems, modeling emotional agents with an intention of employing these agents in human computer interactions as well as in education.

scholarly journals Robust Asymmetric Bayesian Adaptive Matrix Factorization

2017 ◽  
Author(s):  
Xin Guo ◽  
Boyuan Pan ◽  
Deng Cai ◽  
Xiaofei He
Keyword(s):  
Real World ◽  
Matrix Factorization ◽  
State Of The Art ◽  
Low Rank ◽  
Data Sets ◽  
Real World Application ◽  
Factorization Model ◽  
Rank Matrix ◽  
Wide Range ◽  
Low Rank Matrix

Low rank matrix factorizations(LRMF) have attracted much attention due to its wide range of applications in computer vision, such as image impainting and video denoising. Most of the existing methods assume that the loss between an observed measurement matrix and its bilinear factorization follows symmetric distribution, like gaussian or gamma families. However, in real-world situations, this assumption is often found too idealized, because pictures under various illumination and angles may suffer from multi-peaks, asymmetric and irregular noises. To address these problems, this paper assumes that the loss follows a mixture of Asymmetric Laplace distributions and proposes robust Asymmetric Laplace Adaptive Matrix Factorization model(ALAMF) under bayesian matrix factorization framework. The assumption of Laplace distribution makes our model more robust and the asymmetric attribute makes our model more flexible and adaptable to real-world noise. A variational method is then devised for model inference. We compare ALAMF with other state-of-the-art matrix factorization methods both on data sets ranging from synthetic and real-world application. The experimental results demonstrate the effectiveness of our proposed approach.

Intelligent Software Agents with Applications in Focus

2011 ◽  
pp. 950-955
Author(s):  
Mario Jankovic-Romano ◽  
Milan Stankovic ◽  
Uroš Krcadinac
Keyword(s):  
Traffic Control ◽  
Software Agents ◽  
Real Life ◽  
Object Oriented Programming ◽  
Mobile Systems ◽  
Multi Agent Systems ◽  
Information Recovery ◽  
Intelligent Software ◽  
Intelligent Software Agents ◽  
Multi Agent

Most people are familiar with the concept of agents in real life. There are stock-market agents, sports agents, real-estate agents, etc. Agents are used to filter and present information to consumers. Likewise, during the last couple of decades, people have developed software agents, that have the similar role. They behave intelligently, run on computers, and are autonomous, but are not human beings. Basically, an agent is a computer program that is capable of performing a flexible and independent action in typically dynamic and unpredictable domains (Luck, McBurney, Shehory, & Willmott, 2005). Agents are capable of performing actions and making decisions without the guidance of a human. Software agents emerged in the IT because of the ever-growing need for information processing, and the problems concerning dealing and working with large quantities of data. Especially important is how agents act with other agents in the same environment, and the connections they form to find, refine and present the information in a best way. Agents certainly can do tasks better if they perform together, and that is why the multi-agent systems were developed. The concept of an agent has become important in a diverse range of sub-disciplines of IT, including software engineering, networking, mobile systems, control systems, decision support, information recovery and management, e-commerce, and many others. Agents are now used in an increasingly wide number of applications — ranging from comparatively small systems such as web or e-mail filters to large, complex systems such as air-traffic control, that have a large dependency on fast and precise decision making. Undoubtedly, the main contribution to the field of intelligent software agents came from the field of artificial intelligence (AI). The main focus of AI is to build intelligent entities and if these entities sense and act in some environment, then they can be considered agents (Russell & Norvig, 1995). Also, object-oriented programming (Booch, 2004), concurrent object-based systems (Agha, Wegner, and Yonezawa, 1993), and human- computer interaction (Maes, 1994) are fields that constantly drive forward the development of agents.

scholarly journals DeepSTN+: Context-Aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis

2019 ◽  
Vol 33 ◽  
pp. 1020-1027 ◽  
Author(s):  
Ziqian Lin ◽  
Jie Feng ◽  
Ziyang Lu ◽  
Yong Li ◽  
Depeng Jin
Keyword(s):  
Traffic Control ◽  
State Of The Art ◽  
Real Life ◽  
Time Interval ◽  
Context Aware ◽  
Training Process ◽  
Flow Prediction ◽  
Wide Range ◽  
The City ◽  
Historical Flow

Crowd flow prediction is of great importance in a wide range of applications from urban planning, traffic control to public safety. It aims to predict the inflow (the traffic of crowds entering a region in a given time interval) and outflow (the traffic of crowds leaving a region for other places) of each region in the city with knowing the historical flow data. In this paper, we propose DeepSTN+, a deep learning-based convolutional model, to predict crowd flows in the metropolis. First, DeepSTN+ employs the ConvPlus structure to model the longrange spatial dependence among crowd flows in different regions. Further, PoI distributions and time factor are combined to express the effect of location attributes to introduce prior knowledge of the crowd movements. Finally, we propose an effective fusion mechanism to stabilize the training process, which further improves the performance. Extensive experimental results based on two real-life datasets demonstrate the superiority of our model, i.e., DeepSTN+ reduces the error of the crowd flow prediction by approximately 8%∼13% compared with the state-of-the-art baselines.

scholarly journals Book Proposal on Biomimetic Tissue Simulants

2020 ◽  
Author(s):  
Arnab Chanda
Keyword(s):  
Soft Tissue ◽  
Ethical Issues ◽  
State Of The Art ◽  
Academic Research ◽  
Real Life ◽  
Test Results ◽  
Animal Tissues ◽  
Female Pelvis ◽  
Wide Range ◽  
Computational Research

Soft tissue surrogate based test dummies are used across industries to simulate real life accidents. To date, there are a wide range of surrogates available in the market, including gels, elastomers, and animal tissues, which are backdated and have mechanical properties very different from actual human tissues. However, in academic research, biofidelic soft tissue surrogates have evolved in the last two decades, but have lacked technology transfer. This book aims to bridge the gap between the industry and academia with the state of the art in soft tissue surrogate research. Surrogates are presented with respect to skin, muscles, brain tissue, arteries, and female pelvis. Fabrication techniques, mechanical testing, and test results required for reproducing these surrogates are discussed. Also, characterization methodologies and limitations of each type of surrogate are presented, for their use in both experimental and computational research. Some major industries which can use these biofidelic surrogates are car manufacturers, prosthetics and orthotics designers, ballistic testing facilities, military and sports equipment manufacturers. Also, hospitals and medical centres can take advantage of these synthetic surrogates over actual tissues for surgical training with minimal biosafety approvals and ethical issues.

scholarly journals Detecting breakpoints in artificially modified- and real-life time series using three state-of-the-art methods

2016 ◽  
Vol 8 (1) ◽  
pp. 78-98 ◽  
Author(s):  
Dániel Topál ◽  
István Matyasovszkyt ◽  
Zoltán Kern ◽  
István Gábor Hatvani
Keyword(s):  
Time Series ◽  
State Of The Art ◽  
Real Life ◽  
Life Time ◽  
Detection Methods ◽  
Data Sets ◽  
Life Data ◽  
Real Life Data ◽  
Breakpoint Detection ◽  
Insight Into

AbstractTime series often contain breakpoints of different origin, i.e. breakpoints, caused by (i) shifts in trend, (ii) other changes in trend and/or, (iii) changes in variance. In the present study, artificially generated time series with white and red noise structures are analyzed using three recently developed breakpoint detection methods. The time series are modified so that the exact “locations” of the artificial breakpoints are prescribed, making it possible to evaluate the methods exactly. Hence, the study provides a deeper insight into the behaviour of the three different breakpoint detection methods. Utilizing this experience can help solving breakpoint detection problems in real-life data sets, as is demonstrated with two examples taken from the fields of paleoclimate research and petrology.

The Science of Emotional Intelligence

2008 ◽  
Vol 13 (1) ◽  
pp. 64-78 ◽  
Author(s):  
Moshe Zeidner ◽  
Richard D. Roberts ◽  
Gerald Matthews
Keyword(s):  
Emotional Intelligence ◽  
State Of The Art ◽  
Real Life ◽  
The State ◽  
Current Status ◽  
Practical Applications ◽  
Degree Of Confidence ◽  
New Research

Almost from its inception, the emotional intelligence (EI) construct has been an elusive one. After nearly 2 decades of research, there still appears to be little consensus over how EI should be conceptualized or assessed and the efficacy of practical applications in real life settings. This paper aims at providing a snapshot of the state-of-the-art in research involving this newly minted construct. Specifically, in separate sections of this article, we set out to distinguish what is known from what is unknown in relation to three paramount concerns of EI research, i.e., conceptualization, assessment, and applications. In each section, we start by discussing assertions that may be made with some degree of confidence, elucidating what are essentially sources of consensus concerning EI. We move then to discuss sources of controversy; those things for which there is less agreement among EI researchers. We hope that this “straight talk” about the current status of EI research will provide a platform for new research in both basic and applied domains.

Design of the Tableau Reasoner TGC2 for Description Logics

2016 ◽  
Vol 26 (08) ◽  
pp. 1315-1333 ◽  
Author(s):  
Linh Anh Nguyen
Keyword(s):  
Web Sites ◽  
Information Integration ◽  
Description Logics ◽  
Optimization Techniques ◽  
Preliminary Evaluation ◽  
Intelligent Software ◽  
Ontology Language ◽  
Intelligent Software Agents ◽  
Wide Range ◽  
Global Caching

Ontologies have been applied in a wide range of practical domains. They play a key role in data modeling, information integration, and the creation of semantic web services, intelligent web sites and intelligent software agents. The Web ontology language OWL, recommended by W3C, is based on description logics (DLs). Automated reasoning in DLs is very important for the success of OWL, as it provides support for visualization, debugging, and querying of ontologies. The existing ontology reasoners are not yet satisfactory, especially when dealing with qualified number restrictions and large ontologies. In this paper, we present the design of our new reasoner TGC2, which uses tableaux with global caching for reasoning in E xpTime-complete DLs. The characteristic of TGC2 is that it is based on our tableau methods with the optimal ( ExpTime) complexity, while the existing well-known tableau-based reasoners for DLs have a non-optimal complexity (at least NExpTime). We briefly describe the tableau methods used by TGC2. We then provide the design principles of TGC2 and some important optimization techniques for increasing the efficiency of this reasoner. We also present preliminary evaluation results of TGC2. They show that TGC2 deals with qualified number restrictions much better than the other existing reasoners.

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