arXiv subjects

Huansheng Ning

Publications and source records attributed to Huansheng Ning.

63 records · Page 4Linked to original sources

arXiv2021

A Tutorial of Cyber-Syndrome viewed from Cyber-Physical-Social-Thinking Space and Maslow's Hierarchy of Needs

With the increase of active Internet users, various physical, social, and mental disorders have recently emerged because of the excessive use of technology. Cyber-Syndrome is known as the condition that appears due to the excessive interaction with the cyberspace, and it affects the users' physical, social, and mental states. In this paper, we discuss the etiology and symptoms of Cyber-Syndrome according to theories of Cyber-Physical-Social-Thinking (CPST) space and Maslow's Hierarchy of Needs. In addition, we also propose an entropy-based mechanism for recovery of Cyber-Syndrome, to provide potential guidance for clinical detection and diagnosis. Cyber-Syndrome has attracted much attention these days, and more in-depth exploration is needed in the future.

cs.HC↗

arXiv2021

Big-Five, MPTI, Eysenck or HEXACO: The Ideal Personality Model for Personality-aware Recommendation Systems

Personality-aware recommendation systems have been proven to achieve high accuracy compared to conventional recommendation systems. In addition to that, personality-aware recommendation systems could help alleviate cold start and data sparsity problems. Most of the existing works use Big-Five personality model to represent the user's personality, this is due to the popularity of Big-Five model in the literature of psychology. However, from personality computing perspective, the choice of the most suitable personality model that satisfy the requirements of the recommendation application and the recommended content type still needs further investigation. In this paper, we study and compare four personality-aware recommendation systems based on different personality models, namely Big-Five, Eysenck and HEXACO from the personality traits theory, and Myers-Briggs Type Indicator (MPTI) from the personality types theory. Following that, we propose a hybrid personality model for recommendation that takes advantage of the personality traits models, as well as the personality types models. Through extensive experiments on recommendation dataset, we prove the efficiency of the proposed model, especially in cold start settings.

cs.IR↗

arXiv2021

IoT-Enabled Social Relationships Meet Artificial Social Intelligence

With the recent advances of the Internet of Things, and the increasing accessibility of ubiquitous computing resources and mobile devices, the prevalence of rich media contents, and the ensuing social, economic, and cultural changes, computing technology and applications have evolved quickly over the past decade. They now go beyond personal computing, facilitating collaboration and social interactions in general, causing a quick proliferation of social relationships among IoT entities. The increasing number of these relationships and their heterogeneous social features have led to computing and communication bottlenecks that prevent the IoT network from taking advantage of these relationships to improve the offered services and customize the delivered content, known as relationship explosion. On the other hand, the quick advances in artificial intelligence applications in social computing have led to the emerging of a promising research field known as Artificial Social Intelligence (ASI) that has the potential to tackle the social relationship explosion problem. This paper discusses the role of IoT in social relationships detection and management, the problem of social relationships explosion in IoT and reviews the proposed solutions using ASI, including social-oriented machine-learning and deep-learning techniques.

cs.CY↗

arXiv2021

Social Behavior and Mental Health: A Snapshot Survey under COVID-19 Pandemic

Online social media provides a channel for monitoring people's social behaviors and their mental distress. Due to the restrictions imposed by COVID-19 people are increasingly using online social networks to express their feelings. Consequently, there is a significant amount of diverse user-generated social media content. However, COVID-19 pandemic has changed the way we live, study, socialize and recreate and this has affected our well-being and mental health problems. There are growing researches that leverage online social media analysis to detect and assess user's mental status. In this paper, we survey the literature of social media analysis for mental disorders detection, with a special focus on the studies conducted in the context of COVID-19 during 2020-2021. Firstly, we classify the surveyed studies in terms of feature extraction types, varying from language usage patterns to aesthetic preferences and online behaviors. Secondly, we explore detection methods used for mental disorders detection including machine learning and deep learning detection methods. Finally, we discuss the challenges of mental disorder detection using social media data, including the privacy and ethical concerns, as well as the technical challenges of scaling and deploying such systems at large scales, and discuss the learnt lessons over the last few years.

cs.SI↗

arXiv2021

The Internet of People: A Survey and Tutorial

Along with the rapid development of Internet and cyber techniques, the Internet of People (IoP) has been emerging as a novel paradigm which establishes ubiquitous connections between social space and cyberspace. Unlike the Internet of Things (IoT), human nodes in IoP are not only terminal users, but also significant participants bonded with tighter relationships. Note that IoP has deeply influenced our lives. For example, the prosperity of social media enables us to build and maintain new relationships without considering physical boundaries. In this paper, we give a comprehensive overview of IoP by comparing it with IoT, introduce its enabling techniques from aspects of sensing, communication and application. In addition, we summarize and compare popular IoP-enabled platforms according to different functions, and finally envision open issues needed to be further discussed in IoP. It provides constructive suggestions, lays solid foundations, and makes a basic blueprint for the future development of IoP paradigm.

cs.CY↗

arXiv2021

A Review on Serious Games for ADHD

Attention deficit and hyperactivity disorder (ADHD) have two main characteristics: inattention and impulsivity.It has many obstacles to the normal development of children and is very common among children.As an intervention, Serious games for ADHD(SGADs) have shown great potential and are very effective for these ADHD patients.Although many serious games have been developed for ADHD patients, but a review paper that summarizes and generalizes the topic of video games has not yet appeared.In this article, we first classified serious games about ADHD according to different platforms developed by video games, and then we conducted a systematic review of video games that can help children with ADHD diagnose and treat. Finally, we discussed and made suggestions based on the current development of SGADs.

cs.HC↗

arXiv2021

A Survey of Hybrid Human-Artificial Intelligence for Social Computing

Along with the development of modern computing technology and social sciences, both theoretical research and practical applications of social computing have been continuously extended. In particular with the boom of artificial intelligence (AI), social computing is significantly influenced by AI. However, the conventional technologies of AI have drawbacks in dealing with more complicated and dynamic problems. Such deficiency can be rectified by hybrid human-artificial intelligence (H-AI) which integrates both human intelligence and AI into one unity, forming a new enhanced intelligence. H-AI in dealing with social problems shows the advantages that AI can not surpass. This paper firstly introduces the concept of H-AI. AI is the intelligence in the transition stage of H-AI, so the latest research progresses of AI in social computing are reviewed. Secondly, it summarizes typical challenges faced by AI in social computing, and makes it possible to introduce H-AI to solve these challenges. Finally, the paper proposes a holistic framework of social computing combining with H-AI, which consists of four layers: object layer, base layer, analysis layer, and application layer. It represents H-AI has significant advantages over AI in solving social problems.

cs.AI↗

arXiv2020

Could robots be regarded as humans in future?

With the overwhelming advances in Artificial Intelligence (AI), brain science and neuroscience, robots are developing towards a direction of much more human-like and human-friendly. We can't help but wonder whether robots could be regarded as humans in future? In this article, we propose a novel perspective to analyze the essential difference between humans and robots, that is based on their respective living spaces, particularly the independent and intrinsic thinking space. We finally come to the conclusion that, only when robots own the independent and intrinsic thinking space as humans, could they have the prerequisites to be regarded as humans.

cs.RO↗

arXiv2013

A Survey on Gas Sensing Technology

Sensing technology has been widely investigated and utilized for gas detection. Due to the different applicability and inherent limitations of different gas sensing technologies, researchers have been working on different scenarios with enhanced gas sensor calibration. This paper reviews the descriptions, evaluation, comparison and recent developments in existing gas sensing technologies. A classification of sensing technologies is given, based on the variation of electrical and other properties. Detailed introduction to sensing methods based on electrical variation is discussed through further classification according to sensing materials, including metal oxide semiconductors, polymers, carbon nanotubes, and moisture absorbing materials. Methods based on other kinds of variations such as optical, calorimetric, acoustic and gas-chromatographic, are presented in a general way. Several suggestions related to future development are also discussed. Furthermore, this paper focuses on sensitivity and selectivity for performance indicators to compare different sensing technologies, analyzes the factors that influence these two indicators, and lists several corresponding improved approaches.

physics.ins-det↗