Search results for: emotional intelligent

Authors: Bo Zhang, Ellen S. Wilschut, Dehlia M. C. Willemsen, Marieke H. Martens

Abstract:

With the rapid development of intelligent transportation systems, automated platooning of trucks is drawing increasing interest for its beneficial effects on safety, energy consumption and traffic flow efficiency. Nevertheless, one major challenge lies in the safe transition of control from the automated system back to the human drivers, especially when they have been inattentive after a long period of highly automated driving. In this study, we investigated driver take-over time after a system initiated request to leave the platooning system Virtual Tow Bar in a non-critical scenario. 22 professional truck drivers participated in the truck driving simulator experiment, and each was instructed to drive under three experimental conditions before the presentation of the take-over request (TOR): driver ready (drivers were instructed to monitor the road constantly), driver not-ready (drivers were provided with a tablet) and eye-shut. The results showed significantly longer take-over time in both driver not-ready and eye-shut conditions compared with the driver ready condition. Further analysis revealed hand movement time as the main factor causing long response time in the driver not-ready condition, while in the eye-shut condition, gaze reaction time also influenced the total take-over time largely. In addition to comparing the means, large individual differences can be found especially in two driver, not attentive conditions. The importance of a personalized driver readiness predictor for a safe transition is concluded.

Keywords: driving simulation, highly automated driving, take-over time, transition of control, truck platooning

Procedia PDF Downloads 253

Authors: Hamze Torabian, Mohammad Mehrabioun Mohammadi

Abstract:

Like many other industries, the payment industry has been affected by digital transformation. The importance of digital transformation in the payment industry is very crucial. Because the payment industry is considered a leading industry in digital and emerging technologies, and the digitalization of other industries such as retail, health, and telecommunication, it also depends on the growth rate of digitalized payment systems. One of the technological innovations in service management is Field Service Management (FSM). Despite the widespread use of FSM in various industries such as petrochemical, health, maintenance, etc., this technology can also be recruited in the payment industry, transforming the payment industry into a more agile and efficient one. Accordingly, the present study pays close attention to the application of FSM in the payment industry. Given the importance of merchants' bargaining power in the payment industry, this study aims to use FSM in the digital transformation initiative with a targeted focus on providing real-time services to merchants. The research method consists of three parts. Firstly, conducting the review of past research, applications of FSM in the payment industry are considered. In the next step, merchants' benefits such as emotional, functional, economic, and social benefits in using FSM are identified using in-depth interviews and content analysis methods. The related business model in helping the payment industry transforming into a more agile and efficient industry is considered in the following step. The results revealed the 10 main pillars required to realize the digital transformation of payment systems using FSM.

Keywords: digital transformation, field service management, merchant support systems, payment industry

Procedia PDF Downloads 168

Authors: Yorgos Darlas

Abstract:

This original research aims at creating a wine tourism experience specially designed for Thessaloniki, based on retsina, a traditional Greek wine produced continuously since 5400 BC. Wine is a staple of the Greek dinner table, and this is particularly true for Thessaloniki, a city with a rich culinary tradition member of the UNESCO Creative Cities Network for gastronomy. Our methodology is based on historical and folklore research in order to shed light on the history and culture around the production and enjoyment of wine. In addition, we use quantitative and qualitative market research with the aim of recording modern habits and trends related to wine enjoyment. The above research has revealed the habits, rules, and rituals of the people of Thessaloniki, demonstrating the close link between the city’s culinary heritage and retsina. Thanks to this close link, the people of the city have a strong emotional bond with retsina, always ready to share a relevant story loaded with memories. Based on the findings of the research, our aim is to create a new wine tourism product for Thessaloniki based on storytelling. This wine tourism experience will provide visitors with the opportunity to discover the city through the personal stories of locals. At the same time, they will be acquainted with the history and the culture of retsina by visiting landmarks associated with its production and consumption and discovering the city’s multifaceted gastronomic heritage through pairings with retsina.

Keywords: retsina, Thessaloniki, wine tourism, marketing, storytelling

Procedia PDF Downloads 75

Authors: Elahesadat Emrani

Abstract:

The role of psychology in language teaching has gained significant recognition and importance in recent years. This article explores the intersection of psychology and language teaching and highlights the profound impact that psychological principles and theories have on language learning and instruction. It discusses how an understanding of learners' cognitive processes, motivations, and affective factors can inform instructional strategies, curriculum design, and assessment practices. Additionally, the article sheds light on the importance of considering individual differences and diverse learning styles within the psychological framework of language teaching. This article emphasizes the significance of incorporating psychological insights into language classrooms to create a supportive and effective learning environment. Furthermore, it acknowledges the role of psychology in fostering learner autonomy, enhancing learner motivation, promoting effective communication, and facilitating language acquisition. Overall, this article underscores the necessity of integrating psychology into language teaching practices to optimize learning outcomes and nurture learners' linguistic and socio-emotional development. So far, no complete research has been done in this regard, and this article deals with this important issue for the first time. The research method is based on qualitative method and case studies, and the role of psychological principles in strengthening the learner's independence, increasing motivation, and facilitating language learning. Also, the optimization of learning results and fostering language and social development are among the findings of the research.

Keywords: language, teaching, psychology, methods

Procedia PDF Downloads 67

Authors: Siwei Chang, Heng Li, Haitao Wu, Xin Fang

Abstract:

Construction robots are receiving more and more attention as a promising solution to the manpower shortage issue in the construction industry. The development of intelligent control techniques that assist in controlling the robots to avoid transparency and reflected building obstacles is crucial for guaranteeing the adaptability and flexibility of mobile construction robots in complex construction environments. With the boom of computer vision techniques, a number of studies have proposed vision-based methods for transparent obstacle avoidance to improve operation accuracy. However, vision-based methods are also associated with disadvantages such as high computational costs. To provide better perception and value evaluation, this study aims to analyze the performance of vision-based techniques for avoiding transparent building obstacles. To achieve this, commonly used sensors, including a lidar, an ultrasonic sensor, and a USB camera, are equipped on the robotic platform to detect obstacles. A Raspberry Pi 3 computer board is employed to compute data collecting and control algorithms. The turtlebot3 burger is employed to test the programs. On-site experiments are carried out to observe the performance in terms of success rate and detection distance. Control variables include obstacle shapes and environmental conditions. The findings contribute to demonstrating how effectively vision-based obstacle avoidance strategies for transparent building obstacle avoidance and provide insights and informed knowledge when introducing computer vision techniques in the aforementioned domain.

Keywords: construction robot, obstacle avoidance, computer vision, transparent obstacle

Procedia PDF Downloads 80

Authors: Delies L. Alejo

Abstract:

This study explores the psychosocial influences of Spinal Cord Injury (SCI) on patients in the Philippine Orthopedic Center Hospital in the Philippines, examining their social functioning and proposing interventions for reintegration. Quantitative data were collected through surveys using a concurrent triangulation research design, while qualitative insights were obtained via interviews. Findings revealed significant psychosocial challenges among SCI patients, impacting relationships, family dynamics, work, friendships, parenting, education, and self-care. Demographic profiles indicated variations in psychosocial functioning. The study underscores the importance of tailored interventions for SCI patients based on age, marital status, gender, education, and occupation. Triangulation of data enhanced understanding, revealing four themes: ‘Resilient Navigation of Intimacy and Connection,’ ‘Family Dynamics and Care Challenges,’ ‘Occupational Hurdles and Work Engagement,’ and ‘Social and Community Integration Obstacles.’ The study proposes a holistic intervention plan, addressing emotional challenges, creating support networks, implementing vocational rehabilitation, promoting community engagement, and sustaining collaboration with healthcare professionals.

Keywords: spinal cord injury, psychosocial influences, social functioning, concurrent triangulation, intervention plan

Procedia PDF Downloads 47

Authors: Y. Bai, M. Bodlak, V. Frolov, S. Huber, V. Jary, I. Konorov, D. Levit, J. Novy, D. Steffen, O. Subrt, M. Virius

Abstract:

In general, state-of-the-art Data Acquisition Systems (DAQ) in high energy physics experiments must satisfy high requirements in terms of reliability, efficiency and data rate capability. This paper presents the development and deployment of a debugging tool named DAQ Debugger for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. Utilizing a hardware event builder, the iFDAQ is designed to be able to readout data at the average maximum rate of 1.5 GB/s of the experiment. In complex softwares, such as the iFDAQ, having thousands of lines of code, the debugging process is absolutely essential to reveal all software issues. Unfortunately, conventional debugging of the iFDAQ is not possible during the real data taking. The DAQ Debugger is a tool for identifying a problem, isolating the source of the problem, and then either correcting the problem or determining a way to work around it. It provides the layer for an easy integration to any process and has no impact on the process performance. Based on handling of system signals, the DAQ Debugger represents an alternative to conventional debuggers provided by most integrated development environments. Whenever problem occurs, it generates reports containing all necessary information important for a deeper investigation and analysis. The DAQ Debugger was fully incorporated to all processes in the iFDAQ during the run 2016. It helped to reveal remaining software issues and improved significantly the stability of the system in comparison with the previous run. In the paper, we present the DAQ Debugger from several insights and discuss it in a detailed way.

Keywords: DAQ Debugger, data acquisition system, FPGA, system signals, Qt framework

Procedia PDF Downloads 284

Authors: Yibeltal Chanie Manie, Zebider Asire Munyelet

Abstract:

5G and 6G technology offers enhanced quality of service with high data transmission rates, which necessitates the implementation of the Internet of Things (IoT) in 5G/6G architecture. In this paper, we proposed the integration of free space optical communication (FSO) with fiber sensor networks for IoT applications. Recently, free-space optical communications (FSO) are gaining popularity as an effective alternative technology to the limited availability of radio frequency (RF) spectrum. FSO is gaining popularity due to flexibility, high achievable optical bandwidth, and low power consumption in several applications of communications, such as disaster recovery, last-mile connectivity, drones, surveillance, backhaul, and satellite communications. Hence, high-speed FSO is an optimal choice for wireless networks to satisfy the full potential of 5G/6G technology, offering 100 Gbit/s or more speed in IoT applications. Moreover, machine learning must be integrated into the design, planning, and optimization of future optical wireless communication networks in order to actualize this vision of intelligent processing and operation. In addition, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. Moreover, we proposed deep learning techniques to estimate the strain changes and peak wavelength of multiple Fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment.

Keywords: optical sensor, artificial Intelligence, Internet of Things, free-space optics

Procedia PDF Downloads 63

Authors: Abdulkader Helwan

Abstract:

Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

Procedia PDF Downloads 503

Authors: Intan Abida Abu Bakar

Abstract:

This paper investigates the effectiveness of anti-smoking campaign towards youth in Bandar Sunway institution. Based from the Ministry of Health, Malaysia and the national newspapers in the country reveal that the campaigns were not effective enough to curb smoking in Malaysia. In the past, from the year 2004 to 2014, the Malaysian Health Ministry were determined to curb the smoking issue that were arising in the country especially among the youths. “Tak Nak” smoking campaign was launched and broadcast on all forms of media in Malaysia. The campaigns are to educate and create an awareness to encourage people to quit smoking besides discourage non-smokers from starting to smoke. The main objective of this research is to investigate and study the concept, storyline and appeal of ‘Tak Nak Merokok’ advertisement campaigns from 2004 to 2014. Data from questionnaires and focus group discussions indicate that the advertisement contained fear and emotional appeal with good concept and storyline are more appealing and effective compared to the humour and informational rational appeal. This research could be a guideline for advertisers who want to come up with creative anti-smoking campaigns in Malaysia. In the future, the focus group can be expanded and more feedbacks and reviews could contribute to marketers and advertisers to determine the most suitable advertisements to tackle this smoking issue.

Keywords: effectiveness, anti-smoking campaign, young adults, smoking

Procedia PDF Downloads 255

Authors: Ummuhan Bas Aslan, Sehmus Aslan

Abstract:

Objective: Physical disability includes impairments, activity limitations, and participation restrictions. Individuals with physical disabilities have lower self-esteem compared non-disabled people. Self-esteem is widely accepted as a key indicator of emotional stability and adjustment to life demands. There is very limited study to investigate the effect of sports on self-esteem in physically disabled people. The aim of the present study was to evaluate of self-esteem in physically disabled adults who participated in sports. Methods: Fifty physically disabled adults who participated in sports aged between 18 to 35 years participated in the study. Self-esteem of the participants was assessed by Rosenberg Self-Esteem Scale. The scale is a 10-item measure of global self-esteem. The higher score on the scale indicates greater self-esteem. Scores between 15 and 25 are the normal range of and scores below 15 suggest low self-esteem. Results: Average age of participants was 25.18±6.20 years. 58% of the participants were 23 (46.0%) of the participants were wheelchair users, 8 (16.0%) were mobile with a walking aid and 19 (38.0%) were mobile without a walking aid. The length of physically disabled adults had been participating in their sports (basketball: 54%, athleticism: 32%, volleyball: 6%, cycling: 6%) was 4.94±3.86 years. The average Rosenberg Self-Esteem Scale score of the participants was 21.88 ±4.34. Conclusions: Our results suggest that physically disabled adults who participated in sports have the healthy level of self-esteem. Participating in sports could have positive effects on self-esteem in that physically, disabled people. There is needed future comparative studies on this topic.

Keywords: adult, physical disability, self-esteem, sport

Procedia PDF Downloads 265

Authors: Qasim HamaKhurshid HamaMurad, Normal Mat Jusoh, Uznir Ujang

Abstract:

The concept of the city with an infrastructure of (information and communication) Technology embraces several definitions depending on the meanings of the word "smart" are (intelligent city, smart city, knowledge city, ubiquitous city, sustainable city, digital city). Many definitions of the city exist, but this chapter explores which one has been universally acknowledged. From literature analysis, it emerges that Smart City is the most used terminologies in literature through the digital database to indicate the smartness of a city. This paper share exploration the research from main seven website digital databases and journal about Smart City from "January 2015 to the February of 2020" to (a) Time research, to examine the causes of the Smart City phenomenon and other concept literature in the last five years (b) Review of words, to see how and where the smart city specification and relation different definition And(c) Geographical research to consider where Smart Cities' greatest concentrations are in the world and are Malaysia has interacting with the smart city, and (d) how many papers published from all Malaysia from 2015 to 2020 about smart citie. Three steps are followed to accomplish the goal. (1)The analysis covered publications Build a systematic literature review search strategy to gather a representative sub-set of papers on Smart City and other definitions utilizing (GoogleScholar, Elsevier, Scopus, ScienceDirect, IEEEXplore, WebofScience, Springer) January2015-February2020. (2)A bibliometric map was formed based on the bibliometric evaluation using the mapping technique VOSviewer to visualize differences. (3)VOSviewer application program was used to build initial clusters. The Map of Bibliometric Visualizes the analytical findings which targeted the word harmony.

Keywords: bibliometric research, smart city, ICT, VOSviewer, urban modernization

Procedia PDF Downloads 202

Authors: Juhi Faridi, Mohd. Ajmal Kafeel

Abstract:

The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems

Procedia PDF Downloads 174

Authors: Lianxue Shi

Abstract:

Riverfront street has the dual characteristics of street space and waterfront space, which is not only a vital place for residents to travel and communicate but also a high-frequency space for people's leisure and entertainment. However, under the development of cities and towns pursuing efficiency, riverfront streets appear to have a variety of problems, such as a lack of multifunctionality, insufficient facilities, and loss of characteristics, which fail to meet the needs of various groups of people, and their inclusiveness is facing a great challenge. It is, therefore, evident that the optimization of riverfront street space from an inclusivity perspective is important to the establishment of a human-centered, high-quality urban space. Therefore, this article starts by exploring the interactive relationship between inclusive design and street space. Based on the analysis of the characteristics of the riverfront street space and people's needs, it proposes the four inclusive design orientations of natural inclusion, group inclusion, spatial inclusion, and social inclusion. It then constructs a design framework for the inclusive optimization of riverfront street space, aiming to create streets that are “safe and accessible, diverse and shared, distinctive and friendly, green and sustainable”. Riverfront streets in Wansheng District, Chongqing, are selected as a practice case, and specific strategies are put forward in four aspects: the creation of an accessible slow-traffic system, the provision of diversified functional services, the reshaping of emotional bonds and the integration of ecological spaces.

Keywords: inclusiveness design, riverfront street, spatial optimization, street spaces

Procedia PDF Downloads 33

Authors: Hazaila Hassan

Abstract:

This research aims and discusses about the effectiveness of the Psynnova i-Behaviour Modification Technique (iBMT) module towards the change in behaviour of low-performing employees. The purpose of the study is to examine the effectiveness of the Psynnova Module on changing behaviour through five factors among low-performing employees in the public sector. The five main factors/constructs were cognitive enhancement and rationality, emotional stability, attitude alignment and adjustment, social skills development and psycho-spirituality enhancement. In this research, 5 main constructs will be using to indicate behaviour changing performance of the employees after attending The Psynnova Program that using this Psynnova IBMT Module. The respondents are among those who have low scores in terms of annual performance through annual performance value reports and have gone through various stages before being required to attend Psynnova Program. Besides that, the research plan was also to critically examine and understand the change in behaviour among the low-performing employees through the five dimensions in the Psynnova Module. A total of 50 respondent will purposively sampled to be the respondents of this research. This study will use the Experimental Method to One Group Purposively Pre and Post Test using the Time Series Design. Experimental SPSS software version 22.0 will be used to analyse this data. Hopefully this research can see the changing of their behaviour in five factors as an indicator to the respondent after attending the Psynnova Programme. Findings from this study are also used to propose to assisting psychologist to see the changes that occurred to the respondents with the best framework of behaviour changing for them.

Keywords: five dimension of behaviour changing, among adult, low performance, modul effectiveness

Procedia PDF Downloads 171

Authors: Antoine Vikkey Hinson, Ranty Jolianelle Dassi, Menonli Adjobimey, Rose Mikponhoue, Paul Ayelo

Abstract:

Introduction: The psychological hardship of the teaching profession maintains a chronic stress that inevitably evolves into burnout (BO) in the absence of adequate preventive measures. The objective of this study is to study the prevalence and factors associated with burnout among secondary school teachers in the city of Cotonou in 2022. Methods: This was a descriptive cross-sectional study with an analytical aim and prospective data collection that took place over a period of 2 months, from July 19 to August 19 and from October 1 to October 31, 2022. Sampling was done using a three-stage probability sampling technique. Data analysis was performed using R 4.1.1 software. Bivariate logistic regression was used to identify associated factors. The significance level chosen was 5% (p < 0.05). Results: A total of 270 teachers were included in the study, of whom 208 (77.00%) were men. The mean age of the workers was 38.03 ± 8.30 years. According to the Maslach Burnout Inventory, 58.51% of the teachers had burnout, with 41.10% of teachers in emotional exhaustion, 27.40% in depersonalization and 21.90% in loss of personal accomplishment. The severity of the syndrome was low to moderate in almost all teachers. The occurrence of BO was associated with), not practicing sports (ORa= 2,38 [1,32; 4,28]), jobs training (ORa= 1,86 [1,04; 3,34]) and an imbalance of effort/reward (ORa= 5,98 [2,24;15,98]). Conclusion: The prevalence of BO is high among secondary school teachers in the city of Cotonou. A larger scale study, including research on its consequences on the teacher and the learner, is necessary in order to act quickly to implement a prevention program.

Keywords: burnout, teachers, Maslach burnout inventory, associated factors, Benin

Procedia PDF Downloads 76

Authors: Shaode Yu, Jiajian Meng, Bing Zhu, Hang Yu, Qiurui Sun

Abstract:

Speech emotion recognition (SER) is for recognizing human subjective emotions through audio data in-depth analysis. From speech audios, how to comprehensively extract emotional information and how to effectively fuse extracted features remain challenging. This paper presents a dual-stream SER framework that embraces both full training and transfer learning of different networks for thorough feature encoding. Besides, a plug-and-play cross-attention fusion (CAF) module is implemented for the valid integration of the dual-stream encoder output. The effectiveness of the proposed CAF module is compared to the other three fusion modules (feature summation, feature concatenation, and feature-wise linear modulation) on two databases (RAVDESS and IEMO-CAP) using different dual-stream encoders (full training network, DPCNN or TextRCNN; transfer learning network, HuBERT or Wav2Vec2). Experimental results suggest that the CAF module can effectively reconcile conflicts between features from different encoders and outperform the other three feature fusion modules on the SER task. In the future, the plug-and-play CAF module can be extended for multi-branch feature fusion, and the dual-stream SER framework can be widened for multi-stream data representation to improve the recognition performance and generalization capacity.

Keywords: speech emotion recognition, cross-attention fusion, dual-stream, pre-trained

Procedia PDF Downloads 75

Authors: Mohammadhossein Moghimi, Robert Stone, Pia Rotshtein

Abstract:

Recording psychological and physiological correlates of human performance within virtual environments and interpreting their impacts on human engagement, ‘immersion’ and related emotional or ‘effective’ states is both academically and technologically challenging. By exposing participants to an effective, real-time (game-like) virtual environment, designed and evaluated in an earlier study, a psychophysiological database containing the EEG, GSR and Heart Rate of 30 male and female gamers, exposed to 10 games, was constructed. Some 174 features were subsequently identified and extracted from a number of windows, with 28 different timing lengths (e.g. 2, 3, 5, etc. seconds). After reducing the number of features to 30, using a feature selection technique, K-Nearest Neighbour (KNN) and Support Vector Machine (SVM) methods were subsequently employed for the classification process. The classifiers categorised the psychophysiological database into four effective clusters (defined based on a 3-dimensional space – valence, arousal and dominance) and eight emotion labels (relaxed, content, happy, excited, angry, afraid, sad, and bored). The KNN and SVM classifiers achieved average cross-validation accuracies of 97.01% (±1.3%) and 92.84% (±3.67%), respectively. However, no significant differences were found in the classification process based on effective clusters or emotion labels.

Keywords: virtual reality, effective computing, effective VR, emotion-based effective physiological database

Procedia PDF Downloads 233

Authors: John G. Vongas, Raghid Al Hajj

Abstract:

In recent years, there has been a surge in research on empathy across disciplines ranging from management and psychology to philosophy and neuroscience. In organizational behavior, in particular, scholars have become interested in leader empathy given the rise of workplace diversity and the growing perception of leaders as managers of group emotions. It would appear that the current zeitgeist in behavioral and philosophical science is that empathy is a cornerstone of morality and that our world would be better off if only more people – and by extension, more leaders – were empathic. In spite of these claims, however, researchers have used different terminologies to explore empathy, confusing it at times with other related constructs such as emotional intelligence and compassion. Second, extant research that specifies what empathic leaders do and how their behavior affects organizational stakeholders, including themselves, does not devolve from a unifying theoretical framework. These problems plague knowledge development in this important research domain. Therefore, to the authors' best knowledge, this paper provides the first comprehensive review and synthesis of the literature on leader empathy by drawing on disparate yet complementary fields of inquiry. It clarifies empathy from other constructs and presents a theoretical model that elucidates the mechanisms by which a leader’s empathy translates into behaviors that could be either beneficial or harmful to the leaders themselves, as well as to their followers and groups. And third, it specifies the boundary conditions under which a leader’s empathy will become manifest. Finally, it suggests ways in which training could be implemented to improve empathy in practice while also remaining skeptical of its conceptualization as a moral or even effective guide in human affairs.

Keywords: compassion, empathy, leadership, group outcomes

Procedia PDF Downloads 135

Authors: Edwina Owusu Panin, Derrick Antwi

Abstract:

Autism and cerebral palsy are fraternal twins in the world of communication and social interaction challenges. Caring for autistic and cerebral palsied female teenagers in Ghana can be difficult and stressful for parents. We highlight the findings of dealing with stress, where female teenagers are more daunting than male teenagers, related to the demand for a lot of attention linked to the puberty transition. This brief examines the challenges that parents face in caring for teenagers with autism and cerebral palsy in Ghana and the stress that can develop from parental care. The article also highlights the importance of identifying and addressing mental health and self-care issues in parents of disabled female teenagers, as these issues can significantly affect the well-being of both parents and their children. Parents of teenagers with disabilities often face a variety of challenges, including managing their children's care and medical needs, navigating the educational system, and addressing social and emotional needs. These challenges can be even more disheartening in Ghana, where resources and support for families of children with disabilities are limited. In a nutshell, the challenges of caring for female teenagers with autism and cerebral palsy can be significant in Ghana. The article outlines methods that parents in Ghana can take to manage their stress and provide a brighter future for their female teenagers. Parents are better able to cope with the challenges of parenting and provide the best care possible for their female teenagers with disabilities.

Keywords: autism, cerebral palsy, female teenagers, parental care

Procedia PDF Downloads 88

Authors: Xie Weifan, Wang Zhongde

Abstract:

Everyday landscape in the countryside has long played an important role as a cultural representation of the countryside and a link between the countryside and social relations. In the transformation of modernization, the daily landscape in the countryside needs to change with the transformation of daily life in countryside therefore, interpreting the daily landscape in the countryside and understanding the basic characteristics and value perception of the daily landscape from the villagers' perspective can help to understand the daily landscape in the countryside and its conservation and development. Taking Lizi Village in Qianjiang District, Chongqing Municipality, China, as a case study, we collected important daily landscapes in villagers' perceptions through in-depth interviews, categorized them into personal living space, public affairs space, and public activity space, and analyzed the characteristics of the spatial distribution of daily landscapes. The perceptual characteristics of the villagers' perceptions are analyzed and divided into four major types, namely, physical environment perception, atmosphere and culture perception, emotional feelings, and behavioral preferences, and their perceptual characteristics are analyzed respectively to understand the important characteristics of the villagers' perceptions of the daily landscapes. Finally, it is proposed that the protection and development of daily landscape in villages need to improve the mechanism of discovering and evaluating daily landscape, encourage residents to participate in the construction of daily landscape, protect the high-value daily landscape, and promote the innovative development of daily landscape.

Keywords: rural landscape, everyday landscape, landscape perception, conservation and development

Procedia PDF Downloads 25

Authors: Erika Price, Lisa Johnson

Abstract:

Cognitive and dispositional empathy is decreasing among students worldwide, particularly those at university. This paper looks at the effects of encouraging empathetic positioning in divisive topics by teaching listening skills and moral discovery to university students. Two groups of university students were given the assignment to interview individuals they disagreed with on social issues (e.g. abortion, gun control, legalization of drugs, involvement in Ukraine, etc.). One group completed the assignment with no other instruction. The second group completed the assignment after receiving instruction in active listening and Jonathan Haidt’s theory of moral foundations in politics. Results show that when students are given both active listening techniques and awareness of moral foundations, they are significantly more likely to have socially positive interactions with those they disagree with on issues as compared to those who listen passively to ideological opponents. As students interacted with those they disagreed with, they evidenced prosocial behaviors of acknowledgement, validation, and even commonalities with their opponents’ viewpoints, signifying a heartening trend of empathetic connection that is waning in students. The research suggests that empathy is a skill that can be nurtured by active listening but that it is more fully cultivated when paired with the concept of moral foundations underpinning political ideologies. These findings shed light on how to create more effective pedagogies for social and emotional learning, as well as inclusion.

Keywords: empathy, listening skills, moral discovery, pedagogy, prosocial behavior

Procedia PDF Downloads 68

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: deep learning, artificial neural networks, energy price forecasting, turkey

Procedia PDF Downloads 292

Authors: Mirna John Shawky Demian

Abstract:

Mobile phones are now one of the direct marketing tools used to reach hard-to-reach consumers. Cell phones are very personal devices that you can carry with you anytime, anywhere. This gives marketers the ability to create personalized marketing messages and send them at the right time and place. The study examined consumer attitudes towards mobile marketing, particularly SMS marketing. Unlike similar studies, this study does not focus on young people, but the field study included consumers between the ages of 18 and 70.The results showed that the majority of participants found SMS marketing destructive. The biggest problem with SMS marketing is subscribing to message lists without the recipient's consent; large number of messages sent; and the irrelevance of message content. Experiential marketing is an unforgettable experience that remains deeply anchored in the customer's memory. Furthermore, customer satisfaction is defined as the emotional response to the experience provided to the customer in relation to specific products or services purchased. Therefore, experiential marketing activities can influence the level of customer satisfaction and loyalty.In this context, the study aims to examine the relationship between experiential marketing, customer satisfaction and loyalty to beauty products in Konya. The results of this study showed that experiential marketing is an important indicator of customer satisfaction and loyalty and that experiential marketing has a significant positive impact on customer satisfaction and loyalty.

Keywords: direct marketing, mobile phones mobile marketing, sms advertising, marketing sponsorship, marketing communication theories, marketing communication tools

Procedia PDF Downloads 47

Authors: Hao Wang, Shuguo Pan

Abstract:

The Global Navigation Satellite System (GNSS) signal received by the dynamic vehicle in the harsh environment will be frequently interfered with and blocked, which generates gross error affecting the positioning accuracy of the GNSS/Inertial Navigation System (INS) integrated navigation. Therefore, this paper put forward an improved robust Cubature Kalman filter (CKF) algorithm for single-frequency GNSS/INS tightly coupled system ambiguity resolution. Firstly, the dynamic model and measurement model of a single-frequency GNSS/INS tightly coupled system was established, and the method for GNSS integer ambiguity resolution with INS aided is studied. Then, we analyzed the influence of pseudo-range observation with gross error on GNSS/INS integrated positioning accuracy. To reduce the influence of outliers, this paper improved the CKF algorithm and realized an intelligent selection of robust strategies by judging the ill-conditioned matrix. Finally, a field navigation test was performed to demonstrate the effectiveness of the proposed algorithm based on the double-differenced solution mode. The experiment has proved the improved robust algorithm can greatly weaken the influence of separate, continuous, and hybrid observation anomalies for enhancing the reliability and accuracy of GNSS/INS tightly coupled navigation solutions.

Keywords: GNSS/INS integrated navigation, ambiguity resolution, Cubature Kalman filter, Robust algorithm

Procedia PDF Downloads 97

Authors: Serge Tshibangu, Turgay Celik, Zenzo Ncube

Abstract:

Road crashes kill nearly over a million people every year, and leave millions more injured or permanently disabled. Various annual reports reveal that the percentage of fatal crashes due to fatigue/driver falling asleep comes directly after the percentage of fatal crashes due to intoxicated drivers. This percentage is higher than the combined percentage of fatal crashes due to illegal/Un-Safe U-turn and illegal/Un-Safe reversing. Although a relatively small percentage of police reports on road accidents highlights drowsiness and fatigue, the importance of these factors is greater than we might think, hidden by the undercounting of their events. Some scenarios show that these factors are significant in accidents with killed and injured people. Thus the need for an automatic drivers fatigue detection system in order to considerably reduce the number of accidents owing to fatigue.This research approaches the drivers fatigue detection problem in an innovative way by combining cues collected from both temporal analysis of drivers’ faces and environment. Monotony in driving environment is inter-related with visual symptoms of fatigue on drivers’ faces to achieve fatigue detection. Optical and infrared (IR) sensors are used to analyse the monotony in driving environment and to detect the visual symptoms of fatigue on human face. Internal cues from drivers faces and external cues from environment are combined together using machine learning algorithms to automatically detect fatigue.

Keywords: intelligent transportation systems, bayesian networks, yawning computing, machine learning algorithms

Procedia PDF Downloads 455

Authors: Anastasia Sorokina

Abstract:

Graduate language loss or attrition has been well documented in individuals who migrate and become emersed in a different language environment. This phenomenon of first language (L1) attrition is an example of non-pathological (not due to trauma) and can manifest itself in frequent pauses, search for words, or grammatical errors. While the widely experienced loss of one’s first language might seem harmless, there is convincing evidence from the disciplines of Developmental Psychology, Bilingual Studies, and even Psychotherapy that language plays a crucial role in the memory of self. In fact, we remember, store, and share personal memories with the help of language. Dual-Coding Theory suggests that language memory code deterioration could lead to forgetting. Yet, no one has investigated a possible connection between language loss and memory. The present study aims to address this research gap by examining a corpus of 1,495 memories of Russian-English bilinguals who are on a continuum of L1 (first language) attrition. Since phenomenological properties capture how well a memory is remembered, the following descriptors were selected - vividness, ease of recall, emotional valence, personal significance, and confidence in the event. A series of linear regression statistical analyses were run to examine the possible negative effects of L1 attrition on autobiographical memory. The results revealed that L1 attrition might compromise perceived vividness and confidence in the event, which is indicative of memory deterioration. These findings suggest the importance of heritage language maintenance in immigrant communities who might be forced to assimilate as language loss might negatively affect the memory of self.

Keywords: L1 attrition, autobiographical memory, language loss, memory phenomenology, dual coding

Procedia PDF Downloads 119

Authors: Selina Doncevic, Lisa Perla, Angela Kindvall

Abstract:

The Global War on Terror which began after September 11, 2011, increased survivability of severe injuries requiring varying trajectories of rehabilitation and recovery. The costs encompass physiologic, functional, social, emotional, psychological, vocational and scholastic domains of life. The purpose of this poster is to inform private sector health care practitioners and clinicians at various levels of the unique and long term dynamics of healthcare recovery for polytrauma, and traumatic brain injured service members and veterans in the United States of America. Challenges include care delivery between the private sector, the department of defense, and veterans affairs healthcare systems while simultaneously supporting the dynamics of acute as well as latent complications associated with severe injury and illness. Clinical relevance, subtleties of protracted recovery, and overwhelmed systems of care are discussed in the context of lessons learned and in reflection on previous wars. Additional concerns for consideration and discussion include: the cost of protracted healthcare, various U.S. healthcare payer systems, lingering community reintegration challenges, ongoing care giver support, the rise of veterans support groups and the development of private sector clinical partnerships.

Keywords: brain injury, future, polytrauma, rehabilitation

Procedia PDF Downloads 198

Authors: Melody Yin

Abstract:

Concussions impact a large amount of adolescents; they make up as much as half of the diagnosed concussions in America. This research proposes a hybrid machine learning model based on the combination of human/knowledge-based domains and computer-generated feature rankings to improve the accuracy of diagnosing sports related concussion (SRC). Using a data set of symptoms collected on the sideline post-SRC events, the symptom selection criteria method has been developed by using Google AutoML's important score function to identify the top 10 symptom features. In addition, symptom domains have been introduced as another parameter, categorizing the symptoms into physical, cognitive, sleep, and emotional domains. The hybrid machine learning model has been trained with a combination of the top 10 symptoms and 4 domains. From the results, the hybrid model was the best performer for symptom resolution time prediction in 2 and 4-week thresholds. This research is a proof of concept study in the use of domains along with machine learning in order to improve concussion prediction accuracy. It is also possible that the use of domains can make the model more efficient due to reduced training time. This research examines the use of a hybrid method in predicting sports-related concussion. This achievement is based on data preprocessing, using a hybrid method to select criteria to achieve high performance.

Keywords: hybrid model, machine learning, sports related concussion, symptom resolution time

Procedia PDF Downloads 168

Authors: Rashmi Motwani, Ritu Raj

Abstract:

The emergence of online educational environments has changed the way adolescents learn, which has benefits and drawbacks for their development. This review has as its goal the examination of how personality traits and adolescents’ well-being are associated in the setting of online education. This review analyses the effects of a variety of personality traits on the mental, emotional, and social health of online school-going adolescents by looking at a wide range of previous research. This research explores the mechanisms that mediate or regulate the connection between one's personality traits and well-being in an online educational environment. The elements can be broken down into two categories: technological, like internet availability and digital literacy, and social, including social support, peer interaction, and teacher-student connections. To improve the well-being of adolescents in online learning environments, it is essential to understand factors that moderate the effects of interventions and support systems. This review concludes by emphasising the complex nature of the association between individual differences in personality and the success of online students aged 13 to 18. This review contributes to the development of evidence-based strategies for promoting positive mental health and overall well-being among adolescents engaged in online educational settings by shedding light on the impact of personality traits on various dimensions of well-being and by identifying the mediating or moderating factors. Educators, governments, and parents can use the findings of this review to create an online learning environment that is safe and well-being for adolescents.

Keywords: personality traits, adolescent, wellbeing, online education

Procedia PDF Downloads 52