• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1317-1341
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• 2021

Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.

• Journal of the Daesoon Academy of Sciences
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• v.28
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• pp.165-206
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• 2017

In Daesoon Jinrihoe (The Society of Daesoon Truth), pilgrimages can serve as a medium to experience and spread Daesoon Thought. The purpose of this study is to gauge the empirical impact that the motive of a pilgrimage has on the satisfaction level of the participant and the participant's willingness to revisit the holy place. This study further suggests a variety of propositions to promote pilgrimages and thereby Daesoon Thought. This study employs hierarchical analysis for measuring the correlation between all factors the pilgrimage can entail and also the moderator variables (holy places) in the pilgrimage. The study reveals that empirical motive is one of the most influential factors in determining a given participant's level of satisfaction and willingness to revisit said holy place. It is also revealed also that the religious significance of a holy place plays an important role in satisfaction and future revisitation. This study claims pilgrimages are a form of learning and cultural exchange which promotes Daesoon Thought that enables maturity of religious faith. Thereby, all stake holders in the Daesoon Jinrihoe community including clergy should increase their efforts to raise awareness and recognition of Daesoon Truth.

• Safety and Health at Work
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• v.15 no.1
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• pp.24-32
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• 2024

Background: Learning from incidents for accident prevention is a two-stage process, involving the investigation of past accidents to identify the causal factors, followed by the identification and implementation of remedial measures to address the identified causal factors. The focus of past research has been on the identification of causal factors, with limited focus on the identification and implementation of remedial measures. This research begins to contribute to this gap. The motivation for the research is twofold. First, previous analyses show the recurring nature of accidents within the Ghanaian mining industry, and the causal factors also remain the same. This raises questions on the nature and effectiveness of remedial measures identified to address the causes of past accidents. Secondly, without identifying and implementing remedial measures, the full benefits of accident investigations will not be achieved. Hence, this study aims to assess the nature of remedial measures proposed to address investigation causal factors. Method: The study adopted SMARTER from business studies with the addition of HMW (H - Hierarchical, M - Mapping, and W - Weighting of causal factors) to analyse the recommendations from 500 individual investigation reports across seven different mines in Ghana. Results: The individual and the work environment (79%) were mostly the focused during the search for causes, with limited focus on organisational factors (21%). Forty eight percentage of the recommendations were administrative, focussing on fixing the problem in the immediate affected area or department of the victim(s). Most recommendations (70.4%) were support activities that only enhance the effectiveness of control but do not prevent/mitigate the failure directly. Across all the mines, there was no focus on evaluating the performance of remedial measures after their implementation. Conclusion: Identifying sharp-end causes leads to proposing weak recommendations which fail to address latent organisational conditions. The study proposed a guide for effective planning and implementation of remedial actions.

• Journal of Educational Research in Mathematics
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• v.26 no.2
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• pp.189-204
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• 2016

As compared with the gender differences in the achievement of mathematics of the PISA 2009, the results of this study on the PISA 2012 show that the achievement of male students sharply increased, while that of female students maintained the status quo. Based on the premise that this result is derived from the ratio differences between male and female students of high level, this study analyzed the educational context variable effects on the achievements of gender differences observed between male and female students of high level. In particular, this study inquired into the factors which influence the gender difference, by analyzing the identical variables regarding Singapore and Finland of which the achievement of female students registers high among other top high-ranking countries of the PISA 2012. Hence, the binominal logistic multi-level analysis was conducted in order to consider the characteristics of hierarchical structure of PISA, and to compare the features of the educational context variable effects between the high level (above level 5) by country and the highest level (above level 6) by group. The analysis results are as follows: in terms of after-school learning time realized either in private lessons and private institutes, no significant effects were shown in any of the students of these three countries. In terms of after-school homework time, the students of Korea and Singapore gave significant influences on the probability which would be included in the group of high level or the highest level. In particular, regarding the variables which influence the probability of inclusion of Korean female students in the group of high level or the highest level, they correspond to "Homework set by teacher", "Attitude toward school: learning activities", "ESCS of School" and "Teacher-student relations". And "Cultural possessions at home" gave main influences on the probability of inclusion of the female students of Korea, Singapore and Finland in the group of the highest level.

• Journal of Gifted/Talented Education
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• v.24 no.5
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• pp.877-892
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• 2014

This Study was to examine whether high school students' autonomy support and beliefs of intelligence ability influence their self-regulated strategies. Of the 600 high school students surveyed from 3 high schools in two metropolitan cities, Korea, 478 completed and returned the questionnaires yielding a total response rate of 79.7%. Among the final sample consisted of 109 gifted students (22.8%), 190 high-achieving non-gifted students (39.7%), and low-achieving non-gifted students (37.4%). Measures of students' perceived autonomy support (i.e. from parents, teacher, peer), beliefs of intelligence ability (i.e. incremental, entity) and self-regulated strategies (i.e. managing environment and behavior, seeking and learning information, maladaptive regulatory behavior). Spearman's rho(${\rho}$) indicated that students' achieving level was positively associated with autonomy support (i.e. parents, teacher), beliefs of intelligence ability (i.e. incremental) and self-regulated strategies (i.e. managing environment and behavior, seeking and learning information). However, students' achieving level was negatively associated with beliefs of intelligence ability (i.e. entity) and self-regulated strategies (i.e. maladaptive regulatory behavior). Hierarchical multiple regression analyses showed that students' perceived autonomy support (i.e. from teacher) and beliefs of intelligence ability (i.e. incremental) were the crucial contributors for enhancing students' self-regulated strategies. Results are discussed in relation to theoretical implications and school settings.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.95-110
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• 2013

This paper presents a novel feature engineering technique that can improve the conventional machine learning-based text classification systems. The proposed method extends the initial set of features by using hyperlink relationships in order to effectively categorize hypertext web documents. Web documents are connected to each other through hyperlinks, and in many cases hyperlinks exist among highly related documents. Such hyperlink relationships can be used to enhance the quality of features which consist of classification models. The basic idea of the proposed method is to generate a sort of ed concept feature which consists of a few raw feature words; for this, the method computes the semantic similarity between a target document and its neighbor documents by utilizing hierarchical relationships in the WordNet ontology. In developing classification models, the ed concept features are equated with other raw features, and they can play a great role in developing more accurate classification models. Through the extensive experiments with the Web-KB test collection, we prove that the proposed methods outperform the conventional ones.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.221-228
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• 2017

With the recent development of IoT technology, medical services using IoT technology are increasing in many medical institutions providing health care services. However, as the number of IoT sensors attached to the user body increases, the healthcare information transmitted to the server becomes complicated, thereby increasing the time required for analyzing the user's healthcare information in the server. In this paper, we propose a deep learning based health care information management method to collect and process healthcare information in a server for a large amount of healthcare information delivered through a user - attached IoT device. The proposed scheme constructs a subnet according to the attribute value by assigning an attribute value to the healthcare information transmitted to the server, and extracts the association information between the subnets as a seed and groups them into a hierarchical structure. The server extracts optimized information that can improve the observation speed and accuracy of user's treatment and prescription by using deep running of grouped healthcare information. As a result of the performance evaluation, the proposed method shows that the processing speed of the medical service operated in the healthcare service model is improved by 14.1% on average and the server overhead is 6.7% lower than the conventional technique. The accuracy of healthcare information extraction was 10.1% higher than the conventional method.

• Journal of the Korean School Mathematics Society
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• v.22 no.2
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• pp.163-182
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• 2019

The purpose of this study is to investigate the effects of educational context variables on achievement and interest in mathematics in high and low achieving students in Korea. Students participated in TIMSS 2015 in Korea were divided into two groups according to their achievement in mathematics. And the effects of educational context variables on achievement and interest in mathematics were analyzed in each group using the Hierarchical Linear Model(HLM). Main findings of this study are as follows. First, variables which influence achievement also influence interest but any variables which influence interest don't influence achievement in upper-group students. Number of Books and Students' Perceived Mathematics Lessons have strong influence on achievement and interest in both fourth and eighth grade students. Second, variables which influence achievement or interest in mathematics in lower-group also influence achievement or interest in mathematics in upper-group students. But any variables which influence achievement or interest in upper-group students don't influence achievement or interest in lower-group students. For examples, Parents' Education, Students' Perceived Mathematics Lessons have effects on upper-group students' achievement. Number of Books, Home Learning Environment, and Numeracy Activities Before School have significant effects on the achievement of fourth grade students. Students' Perceived Mathematics Lessons is the variable that influence on the interest of both fourth grade and eighth grade students. This study suggests the ways to improve mathematics teaching and learning based on these results.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.17-25
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• 2021

Population aging is an inevitable problem in our society nowadays, and the current aging trend in Asia is prominent and the number of elderly people is huge, among which the World Health Organization predicts that by 2050, 35% of China's population will be over 60 years old, making it the most serious aging country in the world. According to actual reports and surveys, there is a clear digital divide between a large proportion of the elderly and ICT technology, which has had a negative impact on the quality of life and mentality of the elderly living in cities due to the rapid development of technology and the dramatic changes that have occurred in urban life in recent years. The author chose Chinese urban elderly as the main research topic, the research method through the collation of existing literature and information combined with the actual data research, narrative collation of the current situation of ICT use among the Chinese urban elderly and the causes of the difficulties, summarize the ability of the Chinese urban elderly as the representative of the elderly users to master and learn ICT. The study concluded that the needs of the elderly for ICT are multi-layered and there is a gradation in the ability of the elderly users to master various ICT services, so that the elderly can better use and enjoy ICT services and provide teaching and services in a hierarchical and targeted manner can be the next research direction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.157-167
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• 2019

This study empirically analyzed the effects of the use of a single human resource development system in the enterprise on corporate performance using the Human Capital Enterprise Panel (HCCP) data. The results of the hierarchical regression analysis on the sales per log of job analysis use, The use of job analysis confirms that $R^2=.294$ and ${\beta}=.165$ can have a positive effect on sales per log, and Hypothesis 1 is supported. The participation in the work parallelism participation was negatively influenced by the sales per log in $R^2=.283$ and ${\beta}=-.129$, and Hypothesis 2 was rejected. This is attributed to the lack of data of 66, and it was judged that there were 45 new companies entering the company. In addition, we conducted a hierarchical regression analysis that confirms the moderating effect of the training and training obligation by using interaction variables of job analysis use and education and training obligation. It was confirmed that the use of job analysis could have a negative impact on the sales per log, and Hypothesis 3 was rejected. As the labor productivity increases, firms have supported the previous study that productivity effect is not significant because they do not want to invest in education and training. In addition, it was confirmed that the participation of the training system in the job training system could strengthen the positive sales (+). Therefore, Hypothesis 4 was supported. In order to reflect the effective aspects of job analysis, the voluntary activation of enterprises should be premised. In addition, if employing talented people with diverse backgrounds such as academic backgrounds, gender, religion, nationality, etc. and investing in human resources development through education and training focused on job analysis, recruitment of learning workers in parallel with work- It will be possible to contribute to the creation of performance.