scholarly journals Sensors and Artificial Intelligence Methods and Algorithms for Human–Computer Intelligent Interaction: A Systematic Mapping Study

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 20
Author(s):  
Boštjan Šumak ◽  
Saša Brdnik ◽  
Maja Pušnik
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Learning Algorithm ◽  
Sensor Technology ◽  
Future Research ◽  
Systematic Mapping Study ◽  
Human Communication ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Intelligent Interaction

To equip computers with human communication skills and to enable natural interaction between the computer and a human, intelligent solutions are required based on artificial intelligence (AI) methods, algorithms, and sensor technology. This study aimed at identifying and analyzing the state-of-the-art AI methods and algorithms and sensors technology in existing human–computer intelligent interaction (HCII) research to explore trends in HCII research, categorize existing evidence, and identify potential directions for future research. We conduct a systematic mapping study of the HCII body of research. Four hundred fifty-four studies published in various journals and conferences between 2010 and 2021 were identified and analyzed. Studies in the HCII and IUI fields have primarily been focused on intelligent recognition of emotion, gestures, and facial expressions using sensors technology, such as the camera, EEG, Kinect, wearable sensors, eye tracker, gyroscope, and others. Researchers most often apply deep-learning and instance-based AI methods and algorithms. The support sector machine (SVM) is the most widely used algorithm for various kinds of recognition, primarily an emotion, facial expression, and gesture. The convolutional neural network (CNN) is the often-used deep-learning algorithm for emotion recognition, facial recognition, and gesture recognition solutions.

A Systematic Mapping on the Learning Analytics Field and Its Analysis in the Massive Open Online Courses Context

2015 ◽  
Vol 13 (3) ◽  
pp. 1-24 ◽  
Author(s):  
Barbara Moissa ◽  
Isabela Gasparini ◽  
Avanilde Kemczinski
Keyword(s):  
Learning Analytics ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
Future Research ◽  
Systematic Mapping Study ◽  
Mapping Study ◽  
Data Types ◽  
Massive Open Online ◽  
Systematic Mapping ◽  
Dynamical Processes

Learning Analytics (LA) is a field that aims to optimize learning through the study of dynamical processes occurring in the students' context. It covers the measurement, collection, analysis and reporting of data about students and their contexts. This study aims at surveying existing research on LA to identify approaches, topics, and needs for future research. A systematic mapping study is launched to find as much literature as possible. The 127 papers found (resulting in 116 works) are classified with respect to goals, data types, techniques, stakeholders and interventions. Despite the increasing interest in field, there are no studies relating it to the Massive Open Online Courses (MOOCs) context. The goal of this paper is twofold, first we present the systematic mapping on LA and after we analyze its findings in the MOOCs context. As results we provide an overview of LA and identify perspectives and challenges in the MOOCs context.

Requirements Engineering in Cloud and Service-Oriented Systems: A Systematic Mapping Study

2020 ◽  
Vol 19 (01) ◽  
pp. 2040010
Author(s):  
Samah Ridha ◽  
Mali Senapathi
Keyword(s):  
Requirements Engineering ◽  
Relevant Literature ◽  
Current Status ◽  
Future Research ◽  
Systematic Mapping Study ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Current State ◽  
Service Oriented ◽  
Validation Research

The domain of Cloud and Service-oriented requirements engineering (SORE) focuses on modelling, specifying, and analysing requirements to enable software development in a service-oriented manner. Even though Cloud and SORE has received increasing attention over the past decade, there is no clear view of the current state of knowledge. Our goal is to gain insights into the current status of Cloud and SORE research published to date. To this end, we conducted a systematic mapping study to develop a map to classify relevant literature published between 2007 and 2018. Out of the 326 studies that were examined, we selected 24 studies as primary studies. The resulting map provides an overview of the existing work on Cloud and SORE and makes it possible to identify gaps and plan and position future research. Our findings suggest that Cloud and SORE as a research context needs specific attention. More evaluation and validation research is needed to better understand the implementation and impact of the various solutions (e.g. frameworks, tools) that are proposed in the Cloud and SORE context.

Research on Energy Efficiency of Embedded Systems: A Systematic Mapping Study

2012 ◽  
Vol 588-589 ◽  
pp. 2088-2092
Author(s):  
Ehsan Ahmad ◽  
Yun Wei Dong ◽  
Bin Gu
Keyword(s):  
Energy Efficiency ◽  
Embedded Systems ◽  
State Of The Art ◽  
Future Research ◽  
Systematic Mapping Study ◽  
Mapping Study ◽  
Research Focus ◽  
Research Papers ◽  
Systematic Mapping ◽  
Research Type

The main object of this study is to systematically review existing research on energy efficiency of embedded systems in order to identify investigated aspects and needs for future research. We have conducted a systematic mapping study of the state-of-the-art on energy efficiency of embedded systems. 186 papers have been identified as primary studies from year 1994 to 2011 and classified by research focus, research type, and contribution type. 71% of the research papers are solutions proposals; power estimation is the most investigated aspect in terms of research focus (34%) and majority of the studies contributed in terms of methods.

Co-creation in tourism: a systematic mapping study

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fatemeh Mohammadi ◽  
Hamid Reza Yazdani ◽  
Mona Jami Pour ◽  
Morteza Soltani
Keyword(s):  
Research Field ◽  
Survey Method ◽  
Future Research ◽  
Systematic Mapping Study ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Content Type ◽  
The Status ◽  
Minimum Number ◽  
Research Gap

Purpose The purpose of this study is to organize and analyze the existing literature on co-creation in tourism to identify the state-of-the-art studies and the research gap in this field. Design/methodology/approach As the research questions seek to provide an overview of the studies in the available literature, the systematic mapping study (SMS) has been selected as the research method. A suitable mapping study method for analyzing and structuring a broad research field concerning methods, designs and research focuses on the existing publications. In total, 137 articles published during 2006–2019 in reliable academic databases such as Science Direct, Emerald, Scopus, Wiley, ProQuest, Sage, Web of Science and Taylor and Francis were selected and analyzed. Findings The results show a rising trend of published articles in tourism, with the maximum number published in 2019 and the minimum number in 2006. Also, analysis of input articles revealed that most of the studies focused on the antecedents and prerequisites for co-creation and paid less attention to the co-creation context. Other findings show that in the field of tourism, the hospitality sector, especially hotels have paid special attention to co-creation. The majority of papers were the empirical type with quantitative design. Furthermore, most studies used the survey method, while the case study and other methods were the next choices. Originality/value This study addresses a major research gap by summarizing the literature related to value co-creation with a specific focus on tourism using the SMS method that provides an overview of the studies in this field. Categorizing papers through SMS helps researchers to review the status of studies in a visual summary to identify gaps and directions for future research.

scholarly journals Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study

2021 ◽  
Vol 11 (9) ◽  
pp. 3986
Author(s):  
Zenun Kastrati ◽  
Fisnik Dalipi ◽  
Ali Shariq Imran ◽  
Krenare Pireva Nuci ◽  
Mudasir Ahmad Wani
Keyword(s):  
Deep Learning ◽  
Sentiment Analysis ◽  
Language Processing ◽  
The Body ◽  
Systematic Mapping Study ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Learning Platform ◽  
Literature Reviews ◽  
Complicated Task

In the last decade, sentiment analysis has been widely applied in many domains, including business, social networks and education. Particularly in the education domain, where dealing with and processing students’ opinions is a complicated task due to the nature of the language used by students and the large volume of information, the application of sentiment analysis is growing yet remains challenging. Several literature reviews reveal the state of the application of sentiment analysis in this domain from different perspectives and contexts. However, the body of literature is lacking a review that systematically classifies the research and results of the application of natural language processing (NLP), deep learning (DL), and machine learning (ML) solutions for sentiment analysis in the education domain. In this article, we present the results of a systematic mapping study to structure the published information available. We used a stepwise PRISMA framework to guide the search process and searched for studies conducted between 2015 and 2020 in the electronic research databases of the scientific literature. We identified 92 relevant studies out of 612 that were initially found on the sentiment analysis of students’ feedback in learning platform environments. The mapping results showed that, despite the identified challenges, the field is rapidly growing, especially regarding the application of DL, which is the most recent trend. We identified various aspects that need to be considered in order to contribute to the maturity of research and development in the field. Among these aspects, we highlighted the need of having structured datasets, standardized solutions and increased focus on emotional expression and detection.

scholarly journals Gamification in IT Service Management: A Systematic Mapping Study

2021 ◽  
Vol 11 (8) ◽  
pp. 3384
Author(s):  
Manuel Trinidad ◽  
Elena Orta ◽  
Mercedes Ruiz
Keyword(s):  
Service Management ◽  
Positive Impact ◽  
Future Research ◽  
Actual State ◽  
Systematic Mapping Study ◽  
It Service Management ◽  
Mapping Study ◽  
Systematic Mapping ◽  
It Service ◽  
Motivation And Engagement

Despite the benefits of adopting IT Service Management (ITSM) reference models, such initiatives do not always produce the expected results. The research literature in this area concludes that motivation, engagement, skills, experience, performance and willingness to change of the personnel involved are among the critical factors for an effective ITSM implementation. Gamification has the capability to improve people’s motivation and engagement and to drive people’s behavior to meet the objectives set. Besides, gamification is widely used in learning systems for increasing students’ skills and competences. In the last years, many researchers have added gamification to their process improvement initiatives to increase the motivation and engagement of process participants and to address their behavior throughout the process. Thus, we consider that adopting gamification in ITSM processes can be an interesting area of study. In this paper, we conducted a systematic mapping study to analyze the actual state of research in the field of ITSM gamification and identify the key challenges that justify future research. The results of our study highlight the positive impact of adopting gamification in ITSM processes and that ITSM gamification is a novel an attractive research area with many action possibilities.

scholarly journals Why Should the Q-method Be Integrated Into the Design Science Research? A Systematic Mapping Study

2019 ◽  
Author(s):  
Irawan Nurhas
Keyword(s):  
Information Systems ◽  
Q Methodology ◽  
System Analysis ◽  
Future Research ◽  
Systematic Mapping Study ◽  
Q Method ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Main Research ◽  
Analysis And Design

The Q-method has been utilized over time in various areas, including information systems. In this study, we used a systematic mapping to illustrate how the Q-method was applied within Information Systems (IS) community and proposing towards integration of Q-method into the Design Sciences Research (DSR) process as a tool for future research DSR-based IS studies. In this mapping study, we collected peer-reviewed journals from Basket-of-Eight journals and the digital library of the Association for Information Systems (AIS). Then we grouped the publications according to the process of DSR, and different variables for preparing Q-method from IS publications. We found that the potential of the Q-methodology can be used to support each main research stage of DSR processes and can serve as the useful tool to evaluate a system in the IS topic of system analysis and design.

Software Design and Artificial Intelligence: A Systematic Mapping Study

2021 ◽  
Author(s):  
Alfonso Robles-Aguilar ◽  
Jorge Octavio Ocharan-Hernandez ◽  
Angel J. Sanchez-Garcia ◽  
Xavier Limon
Keyword(s):  
Artificial Intelligence ◽  
Software Design ◽  
Systematic Mapping Study ◽  
Mapping Study ◽  
Systematic Mapping

scholarly journals Current Research Trends in IoT Security: A Systematic Mapping Study

2021 ◽  
Vol 2021 ◽  
pp. 1-25
Author(s):  
Jee Young Lee ◽  
Jungwoo Lee
Keyword(s):  
Industrial Revolution ◽  
Mobile Internet ◽  
Future Research ◽  
Systematic Mapping Study ◽  
Research Subjects ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Iot Security ◽  
Future Research Directions ◽  
Smart Mobile

The smart mobile Internet-of-things (IoT) network lays the foundation of the fourth industrial revolution, the era of hyperconnectivity, hyperintelligence, and hyperconvergence. As this revolution gains momentum, the security of smart mobile IoT networks becomes an essential research topic. This study aimed to provide comprehensive insights on IoT security. To this end, we conducted a systematic mapping study of the literature to identify evolving trends in IoT security and determine research subjects. We reviewed the literature from January 2009 to August 2020 to identify influential researchers and trends of keywords. We additionally performed structural topic modeling to identify current research topics and the most promising ones via topic trend estimation. We synthesized and interpreted the results of the systematic mapping study to devise future research directions. The results obtained from this study are useful to understand current trends in IoT security and provide insights into research and development of IoT security.

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