Smooth Interaction Research Articles

A Qualitative Report of Sport Facilities Management

Background: Facility management is the process of planning, administering, coordinating, and evaluating the day-to-day operation of facilities, the technological dimension as applied in sports facility management is used in enhancing the value of facilities and acting as a foundation for smooth operation or processes that define smooth interactions between people and places. Aim: This study aims to assess the state of management of Tirunesh Dibaba and the director of facilities management for the South Youth and Sports Office and facilities and to compare the practices of two different venue facility management positions. Method: This study used qualitative data with in-depth semi-structured interviews with sports facility managers and a purposive sampling approach was used to select sports facility managers. Findings: The results of the study showed that the FM had come a long way to establish itself as a new business opportunity, especially with technological advances, international competition, and tight budget controls every organization wants to concentrate only on core business activities, this gives an opportunity for FM business to grow rapidly. It also requires seasoned professionals with technical and soft skills coupled with the right attitude to make business areas more user-friendly and liked by premise occupants

A Qualitative Report of Sport Facilities Management

Background: Facility management is the process of planning, administering, coordinating, and evaluating the day-to-day operation of facilities, the technological dimension as applied in sports facility management is used in enhancing the value of facilities and acting as a foundation for smooth operation or processes that define smooth interactions between people and places. Aim: This study aims to assess the state of management of Tirunesh Dibaba and the director of facilities management for the South Youth and Sports Office and facilities and to compare the practices of two different venue facility management positions. Method: This study used qualitative data with in-depth semi-structured interviews with sports facility managers and a purposive sampling approach was used to select sports facility managers. Findings: The results of the study showed that the FM had come a long way to establish itself as a new business opportunity, especially with technological advances, international competition, and tight budget controls every organization wants to concentrate only on core business activities, this gives an opportunity for FM business to grow rapidly. It also requires seasoned professionals with technical and soft skills coupled with the right attitude to make business areas more user-friendly and liked by premise occupants

COVID-19 상황에서 간호대학생의 블렌디드 러닝 기반 시뮬레이션 실습에 대한 만족 경험 탐색

Objectives The purpose of this study is to explore the nursing students’ experiences of a blended learning in simulation practicum based on ERG theory and to present the strategies of nursing education. Methods Study design of this study is a qualitative study that analyzed the contents of nursing students’ practicum satisfaction survey. A total 69 nursing students in U city in 2020 participated in this study. Semi structured survey based on the Existence-Relatedness-Growth theory was used to collect data and data analyzed using the directed content analysis. Results The results of this study, 3 main-categories including existence, relatedness, and growth and 10 sub-categories were derived. In the existence in main-categories, ‘practical environment with quarantine rules applied’, ‘inexperienced using non-face-to-face system’, ‘practicum that reproducing clinical situation’, and ‘safe practicum using face-to-face and non-face-to-face methods’ were analyzed. In the relatedness in main-categories, ‘smooth interaction’, ‘limitation of non-face-to-face communication’, and ‘serious and comfortable practicum’ were derived, and in the growth in main-categories, ‘improvement of clinical nursing performance’, ‘increasing confidence in nursing practice’, and ‘realization to grow as a nurse’ were analyzed. Conclusions The positive and negative experiences through a blended learning in simulation practicum were identified. Based on this results, it is needed to develop diverse teaching methods to adapt effective simulation education and to increase educational satisfaction.

Intervensi Fleksibiliti Pendidikan Digital Merintis Kemahiran Kebolehpasaran Graduan

The emergence of the Covid-19 pandemic has drastically disrupted various sectors including the education system. The education system changed from a conventional landscape to online one for fulfil sustainability of the education system. Even so, there are weaknesses and deficiencies including smooth interaction and communication involving lecturers and students. This study examines three main objectives which are to identify the level of interaction between students and lecturers, to identify the level of interaction between students and students and to study the distribution of changes in action research interventions. This study uses a quantitative approach using questionnaire instruments. The findings ofthe study were analysed descriptively by viewing at the mean value, frequency and percentage. A total of 45 students from one section of the Malaysian Nationality and Development Introductory Course for the entry of the special semester of 2021. The results of the study showed that student interaction experienced positive changes based on the pre-and post-test findings. The distribution of action research findings also presented a decent improvement between the pre-and post-test. This evidently proves that interventions that emphasize the aspect of flexibility are effective and change the perception of student interaction satisfaction while learning online.

Machine Learning Amplified Control System for HASEL Actuator Soft Robot System

The HASEL actuator is a cutting-edge soft robot compound that is well suited for tasks in unstructured, dynamic environments and has the penitential for superiorly comfortable and smooth human-robot Interaction. However, the nonlinear relation between the input voltage, output strain of the actuators, and the difficulty of analytical modelling makes it hard to design its control software due to the various source of kinematic noises. Machine learning technics, however, which are invented to study the implicit relations in multiparameter problems that do not require pre-existing knowledge, are well suited for HASEL actuators. Traditionally, researchers consider the behavior of this time-dependent system as a sequence of consecutive statuses and use machine learning to enhance conventional algorithms that consume previous and current status and target and adjust the system using varying control input. However, HASEL actuators’ unique propriety of self-stable and negligible lag in response to input changing makes it possible to consider the spatial path of the structure as a whole and control it based on pattern matching. Introducing Recurrent Neural Networks (RNN) and multilayer perceptron (MLP), this paper presents a pattern-matching-based predictive control algorithm for the HASEL actuator system with acceptable size and high accuracy.

Aspect-Driven User Preference and News Representation Learning for News Recommendation

Intelligent human-device interfaces play key roles in fully automated vehicles (FAVs), ensuring smooth interactions and improving the driving experience. Listening to news is a popular method of relaxing during a journey; as a result, travelers require automatic recommendations of preferred news programs. Most existing news recommender systems usually learn topic-level representations of users and news for recommendations while neglecting to learn more informative aspect-level features, resulting in limited recommendation performance. To bridge this significant gap, we propose a novel Aspect-driven News Recommender System (ANRS) built on aspect-level user preferences and news representation learning. In ANRS, a news aspect-level encoder and a user aspect-level encoder are devised to learn the fine-grained aspect-level representations of users’ preferences and news characteristics respectively. These representations are subsequently fed into a click predictor to predict the probability of a given user clicking on the candidate news item. Extensive experiments demonstrate the superiority of our method over state-of-the-art baseline methods.

Single-cell transcriptomic, transcriptomic, and metabolomic characterization of human atherosclerosis

Atherosclerosis is the main cause of many cardiovascular and cerebrovascular diseases (CVDs), and gaining a deeper understanding of the intercellular connections and key central genes which mediate formation of atherosclerotic plaques is required. We performed a comprehensive bioinformatics analysis of differential genetic screening, Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway annotation, protein-protein interactions (PPIs), pseudo-timing, intercellular communication, transcription factors on carotid single-cell sequencing data, and aortic bulk transcriptome and metabolomic data. Ten cell types were identified in the data: T cells, monocytes, smooth muscle cells, endothelial cells, B cells, fibroblasts, plasma cells, mast cells, dendritic cells, and natural killer cells. Endothelial, fibroblast, macrophage, and smooth muscle cell subtype differentiation trajectories, interaction networks, and important transcription factors were characterized in detail. Finally, using this information combined with transcriptome and metabolome analyses, we found the key genes and signaling pathways of atherosclerosis, especially the advanced glycation end products and receptor for advanced glycation end products signaling pathway (AGE-RAGE signaling pathway) in diabetic complications, linked the differential metabolites with fibroblasts and atherosclerosis and contributed to it in patients with diabetes. Collectively, this study provides key genes, signaling pathways, cellular communication, and transcription factors among endothelial cells, fibroblasts, macrophages, and smooth muscle cells for the study of atherosclerotic plaques, and provides a basis for the diagnosis and treatment of atherosclerosis-like sclerosis.

Importance of Multi-disciplinary Tumor Boards during the COVID-19 Global Pandemic in a Resource Constrained Country

Background: Multidisciplinary tumor boards (MDTB) are an integral part of cancer management. However, owing to COVID 19 global pandemic it becomes a challenge to have a MDTBs maintaining the social distance norms. Objectives: To assess the technical challenges faced during a virtual tumor board (VTB) discussion Advantages and Disadvantages of a VTBs. Methods: Technical support for various group meetings taking place virtually were considered. Various trials which have assessed the technical difficulties for conducting such a meeting were assessed. The advantages and disadvantages for using various platforms of social media for such a virtual meeting were assessed and various feedbacks and reviews were taken into consideration. Results: VTBs can be implemented either by a video conferencing or web based conferencing. High speed internet connections of 4 mbps for a 30fps at 4k monitor would be required for smooth lag free interaction. The processors should have a minimum of 2 GB of RAM with quad core processor. Platforms which offer the ability for digital signatures are of paramount importance. Having a VTBs during a global pandemic is of paramount importance for a cancer patient. Conclusion: VTBs are very important for management of cancer patients during a global pandemic. We in our paper have tried to summarize the technical support need for such a platform and also have tried to discuss the advantages and disadvantages of such a platform. We would also like to conclude that setting up such a virtual platform is not technically challenging and can be implemented in smaller centers even through a mobile phone connection. VTBs should be implemented in all cancer centers during a pandemic when in person meetings are a challenge and a health risk.

To Be or Not to Be …Human? Theorizing the Role of Human-Like Competencies in Conversational Artificial Intelligence Agents

ABSTRACT Driven by the need to provide continuous, timely, and efficient customer service, firms are constantly experimenting with emerging technological solutions. In recent times firms have shown an increased interest in designing and implementing artificial intelligence (AI)-based interactional technologies, such as conversational AI agents and chatbots, that obviate the need for having human service agents for the provision of customer service. However, the business impact of conversational AI is contingent on customers using and adequately engaging with these tools. This engagement depends, in turn, on conversational AI’s similarity, or likeness to the human beings it is intended to replace. Businesses therefore need to understand what human-like characteristics and competencies should be embedded in customer-facing conversational AI agents to facilitate smooth user interaction. This focus on “human-likeness” for facilitating user engagement in the case of conversational AI agents is in sharp contrast to most prior information systems (IS) user engagement research, which is predicated on the “instrumental value” of information technology (IT). Grounding our work in the individual human competency and media naturalness literatures, we theorize the key role of human-like interactional competencies in conversational AI agents—specifically, cognitive, relational, and emotional competencies—in facilitating user engagement. We also hypothesize the mediating role of user trust in these relationships. Following a sequential mixed methods approach, we use a quantitative two-wave, survey-based study to test our model. We then examine the results in light of findings from qualitative follow-up interviews with a sampled set of conversational AI users. Together, the results offer a nuanced understanding of desirable human-like competencies in conversational AI agents and the salient role of user trust in fostering user engagement with them. We also discuss the implications of our study for research and practice.

Barriers and Strategies of Intercultural Manadonese and Japanese Communication in Japan

A strategy is often needed in the communication process to support smooth interaction. Therefore, this study aimed to evaluate the barriers and strategies of intercultural Manadonese and Japanese communication in Japan. An open questionnaire model was used to obtain data for both natives, as 182 respondents submitted complete results with an age range between 20 and 60 years old. The data instrument also contained five questions on the barriers and implementation of intercultural communication strategies. However, the strategies of the Japanese and Manadonese natives had obstacles in their implementation. Because of cultural and social differences, the methods by which different levels of understanding are utilized were considered. The results showed that this communication strategy had a significant high-level cultural difference, according to the Manadonese native perspective. Meanwhile, the Japanese focused on the parties subject to the application of the strategy, which subsequently showed high respect for the interlocutor.

Literary-stylistics of engagement in Femi Osofisan’s The Engagement

ABSTRACT Existing linguistic and non-linguistic studies on Femi Osofisan’s The Engagement (TE) and his other plays have articulated the revolutionary dialectics that characterise his works. Besides the fact that TE has not been sufficiently explored, scholarly information on Osofisan’s construction of marriage proposal remains under-reported. Taking insights from aspects of literary stylistics (LS), this study examines the construction of marriage proposal in TE with a view to describing the implications of such construction for Yoruba culture. Engaging aspects of LS, ten purposively selected excerpts, relating to contextual construction of engagement are subjected to literary stylistic analysis. The study reveals that Osofisan adopts satire, humour and songs to trivialise marriage proposal as a relevant aspect of Yoruba cultural belief. Rather than describing the contextual description of marriage proposal within the Yoruba cultural perspective, Osofisan satirises marriage institution by creating conflict to orchestrate to characters’ follies, lampoon inherent complexities in human relations and depict the collapse of good parenting, especially in marriage. A literary stylistic reading of TE reveals the robust attachment of Osofisan to the Yoruba cultural values, and describes the smooth interaction between his art and social commitment.

Pengaruh Komunikasi Guru Sejarah Terhadap Interaksi Pembelajaran Melalui Kelas Virtual di Madrasah Aliyah Negeri 1 Medan

This study discusses the effect of communication between teachers and students on learning interactions through virtual classes at Madrasah Aliyah Negeri 1 Medan. The background of this research is that the success of the teaching and learning process is determined by the teacher factor. The teacher's task is to convey subject matter to students through communication interactions in the teaching and learning process that he does. The success of the teacher in delivering the material really depends on the smooth interaction of communication between the teacher and his students. The lack of communication has an impact on the message conveyed by the teacher. To achieve teaching and learning interactions, it is necessary to have clear communication between teachers (communicators) and students (communicants). So that students can be successful in their learning tasks, as well as teachers can successfully teach and educate in accordance with the goals to be achieved. This study uses simple linear regression data analysis which aims to determine whether there is an influence between teacher and student communication on learning interactions through virtual classes. Data collection techniques with the method of documentation and questionnaires. The questionnaire method was used to determine the level of communication between teachers and students on learning interactions through virtual classes. Based on the results of this study, it is hoped that it can provide information and input for teachers and students that communication in education is very important and has a good effect on learning interactions through students' virtual classes.

Spontaneous gaze interaction based on smooth pursuit eye movement using difference gaze pattern method

Human gaze is a promising input modality for being able to be used as natural user interface in touchless technology during Covid-19 pandemic. Spontaneous gaze interaction is required to allow participants to directly interact with an application without any prior eye tracking calibration. Smooth pursuit eye movement is commonly used in this kind of spontaneous gaze-based interaction. Many studies have been focused on various object selection techniques in smooth pursuit-based gaze interaction; however, challenges in spatial accuracy and implementation complexity have not been resolved yet. To address these problems, we then proposed an approach using difference patterns between gaze and dynamic objects' trajectories for object selection named Difference Gaze Pattern method (DGP). Based on the experimental results, our proposed method yielded the best object selection accuracy of and success time of ms. The experimental results also showed the robustness of object selection using difference patterns to spatial accuracy and it was relatively simpler to be implemented. The results also suggested that our proposed method can contribute to spontaneous gaze interaction.

Ethical, Legal & Participatory Concerns in the Development of Human-Robot Interaction

Abstract Research on Human-Robot Interaction is increasing as system become widely available and reached a level that enables smooth interactions. Yet, many research projects act in a silo mentality, in regard of participatory, ethical, or legal matters of social robotics. Knowledge about specific challenges is not universal and has often to be transferred from non-robotic contexts. We present findings in the three dimensions: participatory design, ethics for social robots and legal aspects. We accompanied eight research projects on social robots in real-world scenarios for three years. During that time, we spoke, observed, and helped (where possible) the research projects. This gave us specific insights into their work. Our findings work in three dimensions. In participatory design we observed that the trust relationship to users is essential to gain truthful insights and that a mixed method approach is promising. Regarding ethical aspects, we could see that ethical matters should be answered early on. And in the legal dimensions we noticed that the GDPR regulations are a challenge that often requires the help of experts. This work is reflecting on the observation of eight projects and is collecting lessons learned to help future projects and to learn from previous work.

Differences in the Optimal Motion of Android Robots for the Ease of Communications Among Individuals With Autism Spectrum Disorders.

Android robots are employed in various fields. Many individuals with autism spectrum disorders (ASD) have the motivation and aptitude for using such robots. Interactions with these robots are structured to resemble social situations in which certain social behaviors can occur and to simulate daily life. Considering that individuals with ASD have strong likes and dislikes, ensuring not only the optimal appearance but also the optimal motion of robots is important to achieve smooth interaction and to draw out the potential of robotic interventions. We investigated whether individuals with ASD found it easier to talk to an android robot with little motion (i.e., only opening and closing its mouth during speech) or an android robot with much motion (i.e., in addition to opening and closing its mouth during speech, moving its eyes from side to side and up and down, blinking, deeply breathing, and turning or moving its head or body at random). This was a crossover study in which a total of 25 participants with ASD experienced mock interviews conducted by an android robot with much spontaneous facial and bodily motion and an android robot with little motion. We compared demographic data between participants who answered that the android robot with much motion was easier to talk to than android robot with little motion and those who answered the opposite. In addition, we investigated how each type of demographic data was related to participants' feeling of comfort in an interview setting with an android robot. Fourteen participants indicated that the android robot with little motion was easier to talk to than the robot with much motion, whereas 11 participants answered the opposite. There were significant differences between these two groups in the sensory sensitivity score, which reflects the tendency to show a low neurological threshold. In addition, we found correlations between the sensation seeking score, which reflects the tendency to show a high neurological threshold, and self-report ratings of comfort in each condition. These results provide preliminary support for the importance of setting the motion of an android robot considering the sensory traits of ASD.

Influence of Teacher-Student Interaction on Course Learning Effect in Distance Education

Comprehensive integration of 5G, artificial intelligence and other technologies into education has fully demonstrated openness and flexibility of distance education, which attracts a large number of learners to study. Good teacher-student interaction in distance teaching plays a significant role in improving the quality of course teaching and teachers’ career development. Based on the Classroom Assessment Scoring System (CLASS) questionnaire, the influence of emotional support, classroom organization and teaching support of teacher-student interaction on course teaching effect in distance education was analyzed, the difference of learning effect of whether students like distance education were analyzed. Results show that the reliability coefficient of the questionnaire is 0.938, and the KMO value is 0.892. The reliability and validity of the questionnaire are very good. Two aspects of teacher-student interaction (classroom organization and teaching support) can improve the learning effect. Whether samples like distance education have a significant effect on learning effect (p<0.05). The learning effect of learners who like distance education is significantly higher than those who do not. Conclusions have important reference value in clarifying the main types and contents of teacher-student interaction, improving students’ subjective feeling ability of curriculum education, promoting learners’ active participation in classroom teaching activities, and maintaining smooth interaction with teachers.

Human–machine interaction in self-driving vehicles: a perspective on product liability

Abstract Cars are increasingly being automated, with the ultimate goal of creating a completely self-driving car. The interaction between the human driver or user of an automated vehicle and the driving automation will radically change from the interaction drivers now have with their vehicles. This article classifies the various new interactions that will occur as automation progresses through the six levels of automation discerned by the Society of Automotive Engineers. Smooth interaction between man and machine is critical for safety. A breakdown in interaction can easily give rise to accidents. The ensuing liability questions are difficult to solve: who is responsible for a breakdown in interaction? This article looks through the lens of EU product liability law as harmonized in directive 85/374/EC and asks whether failed man–machine interactions may be qualified as defects.

Continuous and simultaneous estimation of lower limb multi-joint angles from sEMG signals based on stacked convolutional and LSTM models

The smooth and natural interaction between human and lower limb exoskeleton is important. However, one of the challenges is that obtaining the joint rotation angles in time and accurately is difficult. In this paper, we propose the stacked convolutional and long–short term memory networks (Conv-LSTM) to estimate the hip, knee, and ankle joint angles from sEMG signals in locomotion modes including walk, run, stair descent, stair ascent, stand-to-sit, sit-to-stand, and jump. The joint angles are calculated from the kinematic models using the Euler angle signals measured by IMUs. The sEMG and joint angles are segmented according to the gait cycles measured by footswitch signals. Time–frequency analysis of sEMG signals is carried out using continuous wavelet transform. The Conv-LSTM model can extract the spatiotemporal information from the input to establish the mapping from sEMG sequences to multi-joint angle sequences. The evaluation effects of coefficient of determination (R2), root mean squared error, and Dynamic Time Warping on estimation performance are compared. The time domain (TD) features of sEMG perform better on joint angle estimation than the frequency domain and time–frequency domain features (p<0.05). The Conv-LSTM model with TD features as input outperforms the BP and state-of-the-art machine learning algorithms (kernel ridge, random forest, and support vector regression) on multi-joint angle estimation (R2: 0.9334, 0.9110, 0.9236, 0.9238, 0.8999, 0.9430, 0.9351, p<0.05). The estimation results are simulated in V-REP for exoskeleton control.

The Effect of eHMI Malfunctions on Younger and Elderly Pedestrians' Trust and Acceptance of Automated Vehicle Communication Signals.

To ensure traffic flow and road safety in automated driving, external human–machine interfaces (eHMIs) could prospectively support the interaction between automated vehicles (AVs; SAE Level 3 or higher) and pedestrians if implicit communication is insufficient. Particularly elderly pedestrians (≥65 years) who are notably vulnerable in terms of traffic safety might benefit of the advantages of additional signals provided by eHMIs. Previous research showed that eHMIs were assessed as useful means of communication in AVs and were preferred over exclusively implicit communication signals. However, the attitudes of elderly users regarding technology usage and acceptance are ambiguous (i.e., less intention to use technology vs. a tendency toward overreliance on technology compared to younger users). Considering potential eHMI malfunctions, an appropriate level of trust in eHMIs is required to ensure traffic safety. So far, little research respected the impact of multiple eHMI malfunctions on participants’ assessment of the system. Moreover, age effects were rarely investigated in eHMIs. In the current monitor-based study, N = 36 participants (19 younger, 17 elderly) repeatedly assessed an eHMI: During an initial measurement, when encountering a valid system and after experiencing eHMI malfunctions. Participants indicated their trust and acceptance in the eHMI, feeling of safety during the interaction and vigilance toward the eHMI. The results showed a positive effect of interacting with a valid system that acted consistently to the vehicle’s movements compared to an initial assessment of the system. After experiencing eHMI malfunctions, participants’ assessment of the system declined significantly. Moreover, elderly participants assessed the eHMI more positive across all conditions than younger participants did. The findings imply that participants considered the vehicle’s movements as implicit communication cues in addition to the provided eHMI signals during the encounters. To support traffic safety and smooth interactions, eHMI signals are required to be in line with vehicle’s movements as implicit communication cues. Moreover, the results underline the importance of calibrating an appropriate level of trust in eHMI signals. An adequate understanding of eHMI signals needs to be developed. Thereby, the requirements of different user groups should be specifically considered.

Cationic N,N-Dimethylglycine Ester Prodrug of 2R-α-Tocotrienol Promotes Intestinal Absorption via Efficient Self-Micellization with Intrinsic Bile Acid Anion.

The intestinal absorption of hydrophobic compounds is severely influenced by their transportation rate through the unstirred water layer in the intestinal lumen. A member of the vitamin E family, α-Tocotrienol (α-T3) has remarkable pharmacological effects, but its intestinal absorption is hampered due to its hydrophobicity. Here, we prepared three ester derivatives of 2R-α-T3, and we selected a suitable prodrug compound using rat plasma and liver microsomes. The micellization profile of the selected compound in the presence of taurocholic acid (TCA) was evaluated. After gastrostomy administration of the prodrug candidate or α-T3 solution containing TCA, AUC values were determined for α-T3 in plasma obtained from bile duct-ligated rats. Among the three types in the efficiency of the reconversion to the parent drug, α-T3 N,N-dimethylglycinate (α-T3DMG) was the best prodrug; α-T3DMG formed mixed micelles via ion pairs with anionic TCA. The solubility of α-T3DMG in n-octanol/water depended on its ratio to TCA. The AUC after α-T3DMG administration to ligated rats was 2-fold higher than that after α-T3 administration, suggesting a smooth interaction with intrinsic bile acids. In conclusion, utilization of the prodrug synthesized using N,N-dimethylglycine ester may be a beneficial approach to promote intestinal absorption of α-T3 via self-micellization with intrinsic bile acid.