# IIAI AAI 2021-Winter: Papers with Abstracts

Papers
Abstract. This study focuses on the subset selection problem of computational statistics and de- ploys the rank-biserial correlation (RBSC) based deck generation algorithm (RBSC-SubGen) [1] in solving it. RBSC-SubGen is originally designed for automatically building a desired number of vocabulary decks (out of a large corpus) with a desired level of word frequency relation, which shares many common aspects with the generic subset selection problem. In this article, we consider applying it not only on word corpora but any set of ranked items and study its resilience against various hyper-parameters, which are not treated in previ- ous studies. Namely, based on simulations we test RBSC-SubGen under various constraints and indicate the vulnerable aspects in terms of rate of saturation, computational cost and accuracy of obtained solution.
Abstract. With the development of the times, use the electrical devices is essential for our daily live. For using these devices, we need cables to charge or connect them. So, for people, the cables can be found almost everywhere. The cables also bring new problems, like the cables always appear in a messy form with crosses and knots. We have to tidy up the cables before using them and this is a time-consuming and tedious task. And in colleges and companies where have a large number of cables, when we clean the room or laboratory, we can always find these cables are annoying. For this reason we think that it would make our daily live more convenient to use robots to manipulate and untie the cables. Therefore, for manipulating and untying the cables, this paper proposes a method which can convert the 2D cable data from image into 3D cable data in Unity3D, where the 3D cable model is movable and can simulate the real cable, we call this 3D cable model the “Simulatable Cable Model”. In our approach, we use 2D and 3D neural networks to recover the 3D position information of the cable from the input image, then adjust this 3D position information to increase it's accuracy, and finally create the “simulatable cable model” in Unity3D. The “Simulatable Cable Model” provides a new way to manipulate the cables, that is, to simulate the actions in the virtual environment and then apply it in the real world. Such a method can be used not only to support people daily life with robots, but also can be used to arrange cables in the workplace like factories and so on. We believe that our research is applicable and helpful to the recognition and manipulation of all cord-like objects, and will also be useful in the field of recognizing and manipulating soft objects.
Abstract. The present paper aims to reduce unnecessary information obtained through inputs, supposed to be inappropriately encoded, for producing easily interpretable networks with better generalization. The proposed method lies mainly in forced reduction of selective information even at the expense of a larger cost to eliminate unnecessary information coming from the inputs in the initial stage of learning. Then, in the later stage of learning, selective information is increased to produce a small number of really important connection weights for learning. The method was preliminarily applied to two business data sets: the bankruptcy and the mission statement data sets, in which the interpretation is considered as important as generalization performance. The results show that selective information could be decreased, though the cost to realize this reduction became larger. However, the accompa- nying selective information increase could be used to compensate for the expensive cost to produce simpler and interpretable internal representations with better generalization performance.
Abstract. The demand for automatic summarization of newspaper headlines and article sum- maries has increasing with various studies on automatic summarization being currently conducted. However, there are only a few studies on Japanese documents as compared English documents.
In this paper, wheter existing summarization methods can be effective for academic pa- pers written in Japanese is verified. First, we demonstrate the effectiveness of topic-based extractive summarization methods Latent Semantic Analysis (LSA). Then, a more effec- tive topic-based extractive summarization is possible by using Latent Dirichlet Allocation (LDA) is demonstrated.
Abstract. The research is aimed at the development of an ontology that classifies the users into user types based on which personalized decisions are recommended. A user type represents a category of users distinguished by common preferences and decision-making behaviours. The ontology is intended to be used in a decision support system implemented following an earlier proposed conceptual framework of intelligent decision support based on user digital life. The paper briefly introduces this framework and provides the formalization for main framework components. The major research result is a multi-aspect user ontology that models a user via three aspects: user profile, user segment, and user digital life model. Users’ digital traces is the framework’s component that provides information about the users to determine their types. Suggestions on ontology usage for intelligent decision recommendation are provided.
Abstract. This paper introduces a new modification of the Possibilistic Fuzzy multiclass Novelty Detector for data streams (PFuzzND). Mentioned modification is based on the implementation of the automated adjustment of the number of clusters for each class (determined beforehand or during the novelty detection procedure) to improve algorithm’s ability to divide objects into small groups. As result, the proposed approach generates models with flexible class boundaries, which are capable to identify new classes or extensions of the ones that are already known as well as the outliers. Proposed possibilistic fuzzy algorithm for novelty detection was used to solve various benchmark problems with synthetically generated datasets. In order to show the workability and efficiency of the introduced modification its results were also compared with the results obtained by the original PFuzzND algorithm. Thus, it was established that the PFuzzND technique with automatically adjusted number of clusters allows achieving better results in regards to the accuracy, the Macro F-score metric and the unknown rate measure. Comparison to the original algorithm showed that the proposed modification outperforms it but is sensitive to the parameter settings, which can be also said about the PFuzzND method. Therefore, the MPFuzzND approach can be used instead of the original PFuzzND algorithm for other classification problems.
Abstract. With the introduction of the Digital Transformation (DX) era, It is now feasible to obtain digital data not only on the shop floor of the manufacturing facility but also across the whole supply chain (SC) network for improved management. The Bottleneck (BN) is the first tackling point to gain more throughput. By getting the accumulated Lead time (LT) data on the SC network map using simulations, we could identify the SC bottleneck regardless of the production policies such as push or pull: using a simulator that imitates the production of the entire SC network by assembling the materials; using the simple Key Performance Indicators (KPIs) that are the average lead time and the standard deviation of lead time on the simulator; identifying the BN from the remaining quantities of work in processes (WIP) between the nodes in a high-demand situation; identifying the BN based on the use of nodes at the low-demand situation virtually. In addition, our last method can depict the degree how each node is close to the BN, by sorting the rate of the utilization of the nodes.
Abstract. In this paper, we present an emotion estimation method using heart rate variability parameters of vital data. Recently, as sensors have become more precise and smaller, it has been possible to obtain users' vital data in real-time quickly. In our method, ECG (electrocardiogram) data are measured beforehand while listening to a story with voice narration that evokes emotions and based on the trends obtained through the measurement, the emotions that have a high correlation with the newly acquired ECG data are estimated to be the emotions expressed in the ECG data. With the implementation of our method, it is possible to estimate the user's emotions based on ECG data. In this paper, we also represent the application of our method to chat icons that see users' emotions in real-time. By realizing this application, users will see the changes in their emotions and control their mental health.
Abstract. In recent years, accidents and damages caused by wild animals have been serious prob- lems. It has become important to detect wild animals accurately at an early stage. A sufficient number of training infrared images is required to detect wild animals taking various postures at night time using deep learning techniques. In this study, we propose a method to increase appropriate training samples for night wild animal detection using annotated daytime images. We employ a model based on Cycle Generative Adversarial Network (CycleGAN) to be able to generate pseudo infrared images from daytime images. In our experiments, we apply the proposed method to bear and boar detection. The exper- imental results show that the proposed method achieves significant improvements in bear detection accuracy taking various postures.
Abstract. Since the end of 2019, a respiratory disease called COVID-19 caused by SARS- COV2 has been spread around the world. The disease has similar symptoms with influenza. The common symptoms are cough, fever and fatigue. The human-to human transmission occurs primarily through droplets spread by coughing or sneezing from infected people directly and indirectly. In this paper a system based on embedded devices that can be used to help prevent the spread of COVID-19 between humans through face mask detection and a contactless thermal sensor is proposed. CNN based deep learning for the facemask detection and IR thermal sensor for non-contact human temperature measurement are used. The system is implemented locally on the Raspberry Pi platform. The training result shows the accuracy of the face mask detector is higher than 90% and stable after epoch 2. The thermal sensor shows the stable input with 0.25 deviation.
Abstract. Sarcasm is generally characterized as ironic or satirical that is intended to blame, mock, or amuse in an implied way. Recently, pre-trained language models, such as BERT, have achieved remarkable success in sarcasm detection. However, there are many problems that cannot be solved by using such state-of-the-art models. One problem is attribute infor- mation of entities in sentences. This work investigates the potential of external knowledge about entities in knowledge bases to improve BERT for sarcasm detection. We apply em- bedded knowledge graph from Wikipedia to the task. We generate vector representations from entities of knowledge graph. Then we incorporate them with BERT by a mechanism based on self-attention. Experimental results indicate that our approach improves the accuracy as compared with the BERT model without external knowledge.
Abstract. To solve the problem of low navigation accuracy of traditional geomagnetic matching navigation algorithm, a geomagnetic navigation and positioning algorithm based on long-term and short-term memory neural network (LSTM) is proposed in this paper. In this algorithm, the corresponding geodetic coordinates are derived from geomagnetic measurements based on least-square linear fitting. Therefore, the geomagnetic matching is implemented. Then the position of the aircraft at the next time is predicted by the LSTM algorithm. Furthermore, the corresponding geodetic coordinates derived from the geomagnetic sensor are modified to complete the geomagnetic navigation and positioning. In this paper, the geomagnetic field data of a certain region are obtained by IGRF-13. The multi-time simulated flight trajectory is used for simulation experiments. The results show that the proposed methods are reliable to transform the geomagnetic measurements to geodetic coordinates. Also, the artificial intelligent method is to make up for the measurement error of the geomagnetic sensor and improve the accuracy of the geomagnetic navigation.
Abstract. Generalized Mutual Assignment Problem (GMAP) is a multi-agent based distributed optimization where the agents try to obtain the most profitable job assignment. Since it is NP-hard and even a problem of judging the existence of a feasible solution is NP-complete, it is a challenging issue to solve GMAP. In this paper, a consensus based distributed subgradient method is considered to obtain feasible solutions of GMAP as good as possible. Adaptive step size which is calculated by the lower and estimated upper bounds is proposed for the step size in the subgradient method. In addition, a protocol how to estimate the upper bound is also proposed, where each agent do not have to synchronize it.
Abstract. In the era of digital, social media is highly used, and many businesses are using this opportunity to promote their product online massively using promotions from many different social media influencers or endorsement to famous people. Many promoters also need a great representation of their product in the shape of images and pictures to make them look great. However, finding a great quality photographer is quite hard right now, because everything is done manually from mouth to mouth, and there are no applications or websites in Indonesia that can provide a service of renting great photographers. There are also many bad photographers that’s not capable of doing professional photography. Mobile Application has been a part of our everyday life since it first came out on smartphones. Many applications helps our daily life such as uber, Gojek, and grab. Those aforementioned applications helps with transport, logistics, and payment. Although there are platforms like Airbnb that listed entertainment / experiences from their user to be rented, It doesn't focuses on photographers and such. This paper proposes the idea of an application that connects photography related peoples such as a professional photographer, hobbyist, or someone who loves to be a model in one platform. The application can also become a platform of incomes to them and idea sharing for all groups.
Abstract. In this Digital Era, we are facing a lot of threats to protect our data. One of the latest technology on the short raneg communication is Near-Field Communication (NFC) with so many implications of technology that ranging from Non-physical access control to digital payments. These applications are frequently proclaimed as being more secure, as they require near physical vicinity and don't include Wi-Fi or versatile systems. In any case, these frameworks are still defenseless to security assaults at the time of the exchange, as they require small to no extra confirmation from the user’s end. The problem that is the main concern of our paper is about NFC Data Stealing. Not everyone realized that their data get stolen by the Cyber Criminal. A lot of people complacent by NFC Technology that makes data transmission a lot easier, but they only see the good side and close their eyes on the bad side. The problem with NFC is that the data becomes a lot more accessible, and this opens wide the windows for the cyber criminals to steal any data as they like. This opens a new window for them to steal any personal data in no time. Our research method is a survey paper that is based on a real-life case, this method can help us identify a lot of case types. These findings may help all of us to understand more about the problem that we don't even realize.
Abstract. This paper intends to develop a model of Big Data Analytics (BDA) utilization in Indonesian context. This is important due to the lack of related research on what factors influencing company to adopt BDA as their strategic and somehow secret weapon to win in nowadays intensified competition among companies in industries. By the model, this paper aims to contribute additional knowledge on what factors influence company to adopt this emerging technology as part of their strategic action in winning the market. Thus, intended questionnaires are distributed to about 206 companies. However, only 124 responses can be gathered and proceed using Part-Least Square (PLS) Structural Equation Modeling (SEM) and TOE Framework by adopting SmartPLS 3.0. By processing those data, two significant insights can be generated. First, BDA adoption in Indonesia is mainly encouraged degree of technology savviness, organizational readiness, and better anticipating environmental changes. Second, Organization readiness is also influenced by technology savviness and environmental changes anticipation. the company needs to master its technology which in Indonesia, compatibility and relative advantage could be significant issue. Thus, for those who want to adopt this emerging technology need to develop technology savviness and organization readiness while anticipate environmental changes.
Abstract. This paper describes how ABC company has successfully increased its Process Cycle Efficiency (PCE) to win market competition through Lean Production initiative. By adopting Value Stream Mapping, an in-depth study towards its production process of product A is carefully conducted. This results in careful waste identification and elimination. After the implementation, the company can achieve an improved process cycle efficiency from 15,60% to 29,60% with product cost reduction about 56%. This gives insight for any manufacturing systems that the adoption of lean production especially value stream mapping may help to reduce product cost instead of Product Cycle Efficiency.
Abstract. This study aims to clarify the differences in psychological, social, and physical characteristics that influence the preferences for nursing care by Japanese and Chinese people. A questionnaire was conducted with Japanese and Chinese seniors who were living at homes and capable of independent living and self-care. At that time, changes in the mental state before and after the spread of COVID- 19 were also examined. The participants were divided into two groups based on their nursing care preferences, “family care” or “public care” with Fisher’s exact test and ANOVA was being used in the analysis. These results showed only a significant difference between these two groups in the responses regarding exercise habits before COVID-19 for both Japanese and Chinese participants. Doing sports or exercise frequency was higher for those who preferred family care before COVID-19. This suggests that the physical factor of exercise habits influences the choice to care for the elderly at home.
Abstract. The number of courses offered online by universities has been increasing in the recent years. To assure that students can engage appropriately with those courses, many universities have been implementing a bring-your-own-device (BYOD) policy. Due to the COVID-19 outbreak, most courses in Japanese universities shifted to online education. In the present study, two aspects of student behavior after this shift towards online education were analyzed: the usage of computers versus mobile phones and other devices to watch videos; length of video watched at one time. Results show that students under the BYOD policy used computers to watch educational videos more often than other devices, while students not under this policy used computers and other devices to roughly the same extent. Following previous research, shorter videos were watched in higher proportions than longer videos. Students watching videos using computers tended to watch a higher proportion of videos than those using other devices. Overall, students watched videos more often during the morning and the afternoon (school time), followed by the evening. Thus, there was no clear change of routine, despite those videos being available at any time. Implications were discussed.
Abstract. Despite global trends in quality assurance emphasizing degree-specific learning outcomes, Japanese higher education has yet to develop a comprehensive evaluation system at the program level. This paper argues that defining program-level learning outcomes is a necessary step in advancing education quality in Japan. This paper analyzes recent policy trends and survey results related to Japanese quality assurance. It explores the development and implementation of program-level evaluation practices, internal quality enhancement processes and external quality assurance mechanisms. In a potentially important shift within the country’s overall approach to quality assurance, this paper examines the parallels between its recent reforms and the policies implemented by the United Kingdom. These comparative analyses will elucidate the benefits and challenges of articulating program-level internal and external quality assurance frameworks.
Abstract. This preliminary study visualizes the characteristics of the medium-term plan of ten universities that were transferred from private to public ones. The analysis tool is KH Coder version 3. Drawing 2-D maps in three ways: Co-occurrence network, Correspondence analysis, Self-organizing map make it to interpret the whole picture.
Abstract. An environmental problem is in a serious situation. In order to suppress and advance environmental discharge, the measure which grasps the quantity of the substance of the environmental impact which affects various kinds of environment is advanced. The PRTR system was enacted in order to grasp the quantity of discharge and transfers in industry. The unification evaluation which grasps the environment impact of category, and the technique of evaluating influence using the quantity of discharge of an environmental impact are proposed. Moreover, this study has grasped it as various kinds of transfers and the tendency of the quantity of discharge by PRTR system, and clarified the quantity of discharge using the characterization factor to the carcinogen which is the environmental impact in PRTR.
Abstract. The environment surrounding companies is changing rapidly, such as entering an advanced information society, intensifying competition between companies on a daily basis, and creating new management forms such as fabless companies. Innovation is important for sustainable management of companies, and much research has been done. Individual creativity is important for creating innovation within an organization. Therefore, in this study, we focused on the individuals who belong to the company, and summarized the characteristics of creation by industry in the manufacturing industry based on the creation that is carried out every day.
Abstract. In the current state of the world, the issue of identifying spammers has received escalating attention due to its influence towards social network security. The popularity of social networking sites made them unsurprisingly easy target for most spammers due to the ease of information sharing they provide. While having important information shared easily is a good thing, the extra bits of harmful objects including viruses or malwares are not. Not to mention the irrelevant information found across almost everywhere in the social media shared by said spammers. Spamming does not only affect social media but could also affect most websites and e-mails. Thus, an extensive action is needed to detect and counter the act of spamming, and this study attempts to review them.
Abstract. In recent years Indonesia is struggling with their waste. Every day, Indonesia generates around 175,000 tons of waste. Some waste takes a lot of time to decompose normally and even though many people know this fact, there are still a lot of people still throwing their waste without giving a second thought. This problem has not been solved yet and it’s because people in Indonesia don’t know how to recycle their waste properly. In order to solve this problem, a platform is needed to provide information on how to recycle waste, for example Recycle Helper (a web application that provides guides on how to make useful items out of waste to reduce the amount of waste thrown and let users create and share their own guides with their own recycle idea). The questionnaire result that has been collected proves that people are still having a recycling motivation, hence Recycle Helper application is compatible with the current situation.
Abstract. The new generation of distance learning online education, established with the help of multimedia computer technology and network technology, is gaining growing attention around the world with the advancement of information technology. The purpose of this paper is to provide information about the effectiveness of online learning from a summary of 12 published research.
Abstract. This paper describes an automated grading system for MS-Excel files and MS-Word files for information technology education. The system can relieve teachers’ workloads to grade many exercises of MS-Excel/MS-Word files. It can also provide immediate feedback and has a mechanism to prevent students from submitting copied files.
In addition, we discuss the system’s effectiveness from both perspectives: the time to grade MS-Excel/MS-Word files and the average normalized gain computed by the operation records of the system in our university.
Abstract. The concept of “production effect” from experimental psychology suggests that produc- ing a word aloud during study improves explicit memory as compared to reading the word silently. In this study, we investigate the effect of the different vocal production behav- iors on recollection rates concerning varying content types delivered through an e-learning platform and inquire whether there is any possibility of improving the e-learning system by integrating vocal production instructions. As for different sorts of vocal production behaviors, we considered as the usual depiction (uttering) as well as lack (free view) and suppression (mouthing) of vocal production. As for content types, one numerical content and two verbal contents with varying levels of pronunciation difficulty are considered. Our results indicate that there is no statistically significant difference on recollection rates be- tween various vocal production behaviors. However, it is observed that by uttering, the content which is relatively harder to pronounce, can be recalled better than the others in a statistically significant way. This unexpected result indicates that there is a potential to increase the performance of learners, who study unfamiliar verbal content (e.g. foreign vocabulary) by integrating vocal production into e-learning systems.
Abstract. Immersive virtual reality (IVR) technology has a great potentiality in providing high presence and in-time interactions to simulate real learning situations by presenting 3D visualization to enhance the effectiveness of learning about biology, especially genetics topics which on a submicroscopic level including genes, chromosomes, and DNAs are abstract and cannot be directly perceived or touched. In this study, different types of media learning environments, including traditional PC-slides and IVR, such as VR-game, which were employed for experiential learning of science courses with 109 students in the middle school. The purpose of this study was to investigate the effects of reflection strategy and type of media on participants’ cognitive outcomes. Significant interaction between media and methods illustrated the reflection strategy enhanced learners' cognitive performance through immersive VR learning environments (IVREs), but not traditional PC-slides. By using the drawing method, the VR-game made students the most engaged in learning and focus on the key points of important concepts; non-reflection learners focused on games and their learning was easily disturbed. It was concluded that the immersive virtual reality with the specific reflection method was effective in increasing learning performance and the drawing as a generative learning strategy indeed reduced the external cognitive load of learning and promoted the effectiveness of cognitive processing.
Abstract. The COVID-19 pandemic made it difficult to conduct the face-to-face contact-based DRR (disaster risk reduction) delivery lesson we had been giving in an elementary school. To overcome this challenge, we developed a video tool and practiced delivery lessons by using ICT in schools. This paper reports on three cases. In study 1, we conducted a delivery lesson by connecting the school broadcasting room to the classroom in a one- way manner. In study 2, we practiced with connecting the laboratory in a university to individual student’s computers. In study 3, we visited the school and carried out the practice in connecting the school computer room with the classroom teacher’s computer in classroom. We summarized the differences among these three practices, as well as their various characteristics, and discussed the future directions of ICT-based DRR delivery lessons. The ICT-based DRR delivery lesson could bring new educational effects that have never been generated by the traditional delivery lessons.
Abstract. An AI Virtual Teaching Assistant with Smart Search and Feedback has been developed and is being evaluated. It supplements the tuition from the teachers with a Q&A system with higher accuracy of question mapping based on elimination and involvement of stop words in a two-step searching algorithm. An effective and efficient method is applied to estimate the level of students, providing feedback on teaching performance.
Abstract. The pandemic that is happening in this world greatly affects many outdoor activities. Especially in the sector of education, where all activities are carried out online. Almost all educational institutions ranging from elementary schools to lectures use video conferencing applications as a support for learning. Zoom is a web application and an application that is being used. Zoom really helps users to meet fellow users virtually. Even in a relatively young way and there is no time limit when we use a Pro account. however, this Zoom application has several security-related issues as well as audio and video displays. The security problem is a serious problem, therefore this matter is quickly handled by the Zoom. And quickly, even this application is developing very well. Then the problem Display audio and video. Sometimes, while Zooming is running, the sound volume produced is not stable. And also, there are often delays that can disrupt communication during meetings. This is certainly very important to handle because it involves the smooth running of the meeting, which certainly affects the quality of the application itself. We use the qualitative research methods such as Google Form for asking people online.
Abstract. What we should do with service robots to attract people’s attention and communicate more smoothly? We are proceeding with the robot OSONO project, which is referring to Japanese Joruri puppets, with the theme of utilizing expressions that incorporate the "Performing arts and technology" that has been passed down through the ages. In this paper, we propose the associative model that clarifies the correspondence between Ningyo Joruri’s acting script of the performance, and the choreography, and its meaning. And using this method, we discover a number of choreographies that can be used for service robots from the performance record video. Then we will prototype robot OSONO2 and implement this choreography on it so that we confirm that it is possible to express typical poses and typical choreography comfortably by mainly static evaluation. As a result, a series of flows for extracting the choreography for service robots from the acting script / acting video will be established.
Abstract. In this paper, we present a realization method of discovery for burst topic transition using the topic change point detection method for time-series text data. In our method, we focus on the topic change point detection method for time-series text data. By similarity measure using the topic change point detection method for time-series text data, we can discover for burst topic transition. In general, when we would like to understand the outline or main points of an event, we often read articles written by people who know information about the event or ask others who are aware of the event to tell us about it. However, the information obtained by these means is hearsay from others and subject to third-party bias, it is difficult to comprehend the events objectively. In our paper, we focus on the topic change and extract the topic change point detection It enables us to discover burst topic transitions. In this paper, we describe an evaluation experiment of a prototype system using our discovery for burst topic transition to verify the effectiveness of our method. We also implement an application by the user interface that provides some crews of a trendy word.
Abstract. In recent years, the importance of E-services incorporating concepts such as IoT (Internet of Things), digital twin, CPS (Cyber-Physical System) and so forth has increased. There, in addition to cloud computing, edge computing on the terminal equipment is becoming essential. For semiconductor companies, this situation might be a business opportunity to transform or transit from the traditional business model to a business model suitable for the edge computing device business. There, it is necessary to form a healthy business ecosystem with various stakeholders. In this article, we briefly illustrate our proposed business ecosystem analysis methods that are (1) business boundary analysis method and (2) business ecosystem stakeholder analysis method. Then we apply them to an actual business case of edge computing device business, in order to confirm effectiveness of them.
Abstract. The demand for elderly care services has increased owing to the aging society. Daytime care facilities provide rehabilitation services to the elderly, such as massage and training, which use machines. In these facilities, rehabilitation equipment is used by staff to take care and assist the elderly, particularly in walkable activities. Accordingly, the service productivity of the staffs can be improved by reducing the total flow. The total flow among the staffs can be reduced by placing the equipment closer. However, equipment should be placed separately to avoid injuries caused by tripping on the rehabilitation equipment. Two goals are considered for minimizing the total flow of the staff and maximizing the remoteness of equipment. This paper proposes a layout planning business model in a daytime care service for rehabilitation equipment with the two goals for the total flow of the staff and the remoteness of equipment by the quadratic assignment problem (QAP). First, the QAP problem is formulated to integrate the minimization of the total flow and maximization of the value of remoteness by weighting. Next, an actual rehabilitation facility and its staff are surveyed. Finally, numerical experiments are conducted, and the effects of the total flow and remoteness of the equipment are discussed. Key words: Elderly Care Service, Quadratic Assignment Problem, Rehabilitation Equipment, Multi-Goal, Healthcare Business
Abstract. According to research firms, employee engagement in Japan is extremely low compared with that in other countries. This is a major problem for Japanese companies, and they are implementing various measures to improve their employee engagement. However, this is a relatively new concept with no clear definition, and it is also unclear whether the concept of employee engagement fits the corporate culture of Japanese companies and the characteristics of Japanese people. Taking this point as a problem, and based on previous research on employee engagement and the current study, the authors concluded that a theoretical system suitable for Japan, different from the Western concept of social exchange theory, might be necessary to define employee engagement in Japan.
Abstract. Information technology continues to evolve unceasingly. In line with the evolvement, agricultural sciences also transform the sense of technology utilization in its information systems to improve its quality and service. The Government of Indonesia strongly supports the use of information system technology in agriculture. DutaTani research team has consistently developed Agricultural Information System (AIS) technology since 2016 to achieve precision agriculture. These developments must be followed by continuous improvement of information systems carried out sustainably following changes and developments in the technology used. Testing is sorely needed in the system repair phase so that changes or improvements do not cause conflicts or problems in any pre-existing functions. The number of technologies that are tried to be applied in the repair phase tends to cause high system failures when they are tested on users. Based on these problems, this study aims to implement Blackbox testing to increase the system's success rate before general users utilize it. Blackbox testing is considered capable of bridging the development team and random respondents representing general users later. This research also added iterations to increase the success rate of the system. Respondents are invited to use the system through several main scenarios, but they have to fill in the input with variables that they have never filled in before. Through several iterations and following a test scenario created by an independent test team with ten random respondents, this study increased the system's success rate by 11.79%.
Abstract. Machine learning and data mining from tree structured data are studied intensively. In this paper, as tree structured patterns we use tag tree patterns with vertex and edge labels and wildcards in order to represent label connecting relation of vertices and edges in tree structured data. We propose an evolutionary learning method based on Genetic Programming for acquiring characteristic tag tree patterns with vertex and edge labels and wildcards from positive and negative tree structured data. By using label information, that is, label connecting relation of positive examples, as inappropriate individuals we can exclude tag tree patterns that do not satisfy label connecting relation of positive examples. We report experimental results on our evolutionary learning method and show the effectiveness of using label connecting relation of positive examples.
Abstract. Tourism industry is vulnerable to external shock such as natural and human-caused disasters. Covid-19 shows an example of vulnerability and threat for tourism industry. In the future, the possibility of the risk like these threats cannot be denied. This study employs a quantitative approach, conducting an online survey on risk perception of Japanese, Chinese, and Taiwanese. Respondents are asked about degree of risk perception when going on an oversea trip. To measure the degree of risk perception, Steel-Dwass test will be used to analyze the multiple comparisons of each respondents’ evaluation. The results of this study clarify that there are significant differences among Japanese, Chinese, and Taiwanese respondents in some items of the questionnaire survey. It is important to discuss risk management plan considered characteristics of the people of country or region.
Abstract. This paper's principal objective is to analyze and design an attainable model of action to comprehend a recognized mental issue: emotional well-being mindfulness and maintainable profitability improvement; the solutions of personal development in this study refers to Cognitive Behavioral Therapy (CBT), as a work to make a proactive methodology toward psychological well-being and its relationship with efficiency. Analysis and configuration in this study use Enterprise Design Thinking, to make the investigation and plan as persuasive and pragmatic as conceivable to the users. From the plan thinking measure, it is concluded that the convenience and reasonableness of the application are yet the fundamental inclinations, combining with the competitive advantage of engaging both instructors and customers to be more proactive in their approaches on emotional wellness and productivity.
Abstract. The most common failure from sports organizations was caused by improper sports organizations to manage their resources. Sports science generally refers to model intended to improve sports organizations' performance for general and the athlete for specific. Currently, it is important to implement sports science because it can be promoted as competitive strategies to win from any sport competition. The purpose of this research is to identify the dimensional success factor for sport science systems that become an important part of sports organizations before they build the system. This study focuses to examine many articles using systematic literature reviews in sports journals and conferences as supplementary materials alongside published articles, while the topic is a relatively recent sports science phenomenon to support sport organizations. The selected papers were screened and extracted to formulate the core dimensional success factor. The result of this study is a fact-finding dimensional success factor for sports organizations based on previous research that can be considered as the mainstream foundation for sports organizations to build their system, and also it can be applied in multiple sports organizations field as a competitive strategy.
Abstract. This research discusses the collaboration tool system that can be used for work from home activities. The form of this collaboration tool can be in the form of software or applications. This study aims to collect and analyze data about collaboration tools, as well as find out the usefulness of collaboration tools. This research is using the Systematic Literature Review method because this method is very useful for explaining the topic in detail. This collaboration tool is also flexible because it can be used effectively and efficiently anywhere. Therefore, this research was applied to find out the answers to the effect of the collaboration tools. Based on the analysis that has been done, the result is that this collaboration tool can support work from home activities. This research is also conducted to help workers and individuals to determine suitable collaboration tools to assist them in their task or organization.
Abstract. Optimal monitoring of athletes is conducted by up-to-date information at the individual and sports organization. Technology to accommodate these data can be varied. One of the trends in the millennial generation is to use wearable technology, such as smartwatches. Deployment of wearable in sport organization setting for the monitoring of athlete performance. A recent innovation in wearable technology can support sports organizations to collect athlete data that come from kinetic and kinematic activity. Besides, the utilization of wearable technology can protect the athlete from several potential injuries. However, this adoption needs behavior analysis from the user who uses this device. Therefore, this research focus to identify the variable that has a significant impact on the athlete to decide to wear this application. To analysis the data, this study uses some technical statistical. The result shows that the decision to buy or to use the wearable technology is not decided by the hedonic factor, but the awareness of the person to monitor their health performance. It will be an opportunity for sports organizations to explore more this wearable technology in the future.
Abstract. One of the difficulties to create stock control is the way to deal with the stockroom and organize stock to satisfy both on the web and offline (retailer) orders. Mostly, the current improvement of stock administration by the garment industry is yet running physically utilizing paper and notes. It causes miscalculation and loss of stock by the piece of clothing industry happened when recording the stock information. Additionally, it influences shrinkage and quality fall flat reduces which prompts the inconsistency between the recorded stock and the actual stock. The fundamental motivation behind this theory is to assemble an answer for stock administration for Garment Industry and encourages the piece of clothing industry with the Buka Gudang – Inventory Management System. Advantage from Buka Gudang – Inventory Management System for an article of the clothing industry is to improve for eliminating bottlenecks and disposal of repetitive advances can without much of a stretch be accomplished, encourage Garment Industry for a mechanized report of stock by checking stock rundown that will be refreshed electronically each time a deal is made and print out the report featuring the stock to be restocked, and Help business for keeping up the stock rundown naturally and give an exactness to each refreshed information, for example, a precise numerical estimation on Buka Gudang – Inventory Management System. Investigation measure for this postulation is finished by Data Gathering through Interview with a few dealers around Tanah Abang Jakarta who possessed a centerpiece of the clothing industry, at that point doing some perception on the stock framework and current piece of clothing industry circumstance that requirements stock administration to have the option to control the stockroom of an article of the clothing industry. Inventory, Control, Garment, Stock, Online