• The KIPS Transactions:PartC
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• v.14C no.4
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• pp.331-340
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• 2007

Mobile network environments are the environments where mobile devices are distributed invisible in our daily lives so that we can conventionally use mobile services at my time and place. The fact that we can work with mobile devices regardless of time and place, however, means that we are also in security threat of leaking or forging the information. In particular, without solving privacy concern, the mobile network environments which serve convenience to use, harmonized without daily lives, on the contrary, will cause a serious malfunction of establishing mobile network surveillance infrastructure. On the other hand, as the mobile devices with various sizes and figures, public key cryptography techniques requiring heavy computation are difficult to be applied to the computational constrained mobile devices. In this paper, we propose efficient PKI-based user authentication and java-based cryptography module for the privacy-preserving in mobile network environments. Proposed system is support a authentication and digital signature to minimize encrypting and decrypting operation by compounding session key and public key based on Korean standard cryptography algorithm(SEED, KCDSA, HAS160) and certificate in mobile network environment. Also, it has been found that session key distribution and user authentication is safety done on PDA.

• Korean Parent-Child Health Journal
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• v.6 no.2
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• pp.147-158
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• 2003

The purpose of this study was to investigate the situation of occurrence of disease and accidence of child care center. The subjects of this study were 17 public district child care centers, but only one center kept their health diary. Therefore, it became finally the only subject for this study. The data were collected through the analysis it's health diary and case reports for emergency. The collected data were analyzed by the number of cases, age and sex, types of case, and the emergency case were analyzed by age, background, types of accidents and follow up. The number of cases of disease and accident in 2002 were 572. In sexual difference, boys more have accident than girls. The teachers and the outsiders also frequently use the health care service. Smallpox and epidemic conjunctivitis were spreaded during winter and summer. In causes of accidents, 'accident by other child' were 98%. In emergency cases, 1 pierced wound, 1 dislocation, 2 dental emergencies, 4 eyeball contusion and bleedings and 2 burns were occurred. all the cases of emergency were performed follow up education. On the basis of above data, there will be needed to intensify health and safety subjects in curriculum for the teacher of child care, and health and safety education for child. Each child care centers must have health care manager and the network for emergency. To enhance the quality of child care service, government have to offer financial and systematical support.

• Safety and Health at Work
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• v.15 no.2
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• pp.220-227
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• 2024

Background: Though the artificial neural network (ANN) technique has been used to predict noise-induced hearing loss (NIHL), the established prediction models have primarily relied on cross-sectional datasets, and hence, they may not comprehensively capture the chronic nature of NIHL as a disease linked to long-term noise exposure among workers. Methods: A comprehensive dataset was utilized, encompassing eight-year longitudinal personal hearing threshold levels (HTLs) as well as information on seven personal variables and two environmental variables to establish NIHL predicting models through the ANN technique. Three subdatasets were extracted from the afirementioned comprehensive dataset to assess the advantages of the present study in NIHL predictions. Results: The dataset was gathered from 170 workers employed in a steel-making industry, with a median cumulative noise exposure and HTL of 88.40 dBA-year and 19.58 dB, respectively. Utilizing the longitudinal dataset demonstrated superior prediction capabilities compared to cross-sectional datasets. Incorporating the more comprehensive dataset led to improved NIHL predictions, particularly when considering variables such as noise pattern and use of personal protective equipment. Despite fluctuations observed in the measured HTLs, the ANN predicting models consistently revealed a discernible trend. Conclusions: A consistent correlation was observed between the measured HTLs and the results obtained from the predicting models. However, it is essential to exercise caution when utilizing the model-predicted NIHLs for individual workers due to inherent personal fluctuations in HTLs. Nonetheless, these ANN models can serve as a valuable reference for the industry in effectively managing its hearing conservation program.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.92-104
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• 2021

This study aims to analyze online news articles to identify social issues related to patient safety and compare the changes in these issues before and after the implementation of the Patient Safety Act. This study performed text mining through the R program, wherein 7,600 online news articles were collected from January 1, 2010, to March 5, 2020, and examined using keyword analysis, topic modeling, and word co-occurrence network analysis. A total of 2,609 keywords were categorized into 8 topics: "medical practice", "medical personnel", "infection and facilities", "comprehensive nursing service", "medicine and medical supplies", "system development and establishment for improvement", "Patient Safety Act" and "healthcare accreditation". The study revealed that keywords such as "patient safety awareness", "infection control" and "healthcare accreditation" appeared before the implementation of the Patient Safety Act. Meanwhile, keywords such as "patient safety culture". and "administration and injection" appeared after the act's implementation with improved ranking of importance pertaining to nursing-related terminology. Interest in patient safety has increased in the medical community as well as among the public. In particular, nursing plays an important role in improving patient safety. Therefore, the recognition of patient safety as a core competency of nursing and the persistent education of the public are vital and inevitable.

• Journal of the Korean Institute of Educational Facilities
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• v.13 no.3
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• pp.56-65
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• 2006

The multipurpose auditoriums in schools are the center of local community and the places of their life-long education. The multipurpose auditoriums are to be open and made available for use by local public as far as it does not interfere with the education of the schools. However, most of them are not open to public on the pretext of management problems while demands of local communities for the opening of the facility is rising. The role of the multipurpose auditorium as the place of physical training and its maximum availability to local community have be taken into account of from its design stage. The location of the auditorium itself has to be close to the main entrance of the school for easy access, its facilities located in one common area, their management and maintenance scheme adopted appropriately but legally, and then security and safety measurement have to be devised. Also, more studies are necessary to propose detail regulations for local sports facilities and to develop their interrelationship and network, in connection with sophistication of school facilities and BTL system.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.30-40
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• 2024

Building an accurate 3-D spatial road network model has become an active area of research now-a-days that profess to be a new paradigm in developing Smart roads and intelligent transportation system (ITS) which will help the public and private road impresario for better road mobility and eco-routing so that better road traffic, less carbon emission and road safety may be ensured. Dealing with such a large scale 3-D road network data poses challenges in getting accurate elevation information of a road network to better estimate the CO₂ emission and accurate routing for the vehicles in Internet of Vehicle (IoV) scenario. Clustering and regression techniques are found suitable in discovering the missing elevation information in 3-D spatial road network dataset for some points in the road network which is envisaged of helping the public a better eco-routing experience. Further, recently Explainable Artificial Intelligence (xAI) draws attention of the researchers to better interprete, transparent and comprehensible, thus enabling to design efficient choice based models choices depending upon users requirements. The 3-D road network dataset, comprising of spatial attributes (longitude, latitude, altitude) of North Jutland, Denmark, collected from publicly available UCI repositories is preprocessed through feature engineering and scaling to ensure optimal accuracy for clustering and regression tasks. K-Means clustering and regression using Support Vector Machine (SVM) with radial basis function (RBF) kernel are employed for 3-D road network analysis. Silhouette scores and number of clusters are chosen for measuring cluster quality whereas error metric such as MAE ( Mean Absolute Error) and RMSE (Root Mean Square Error) are considered for evaluating the regression method. To have better interpretability of the Clustering and regression models, SHAP (Shapley Additive Explanations), a powerful xAI technique is employed in this research. From extensive experiments , it is observed that SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions with an accuracy of 97.22% and strong performance metrics across all classes having MAE of 0.0346, and MSE of 0.0018. On the other hand, the ten-cluster setup, while faster in SHAP analysis, presented challenges in interpretability due to increased clustering complexity. Hence, K-Means clustering with K=4 and SVM hybrid models demonstrated superior performance and interpretability, highlighting the importance of careful cluster selection to balance model complexity and predictive accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.668-675
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• 2017

In Korea, natural disasters such as earthquakes and floods continue to occur, but it is difficult to respond and provide relief effectively and promptly. Due to the Circulation Position and administrative characteristics, soft and physical systems for basic disasters, such as private cooperation and disaster response bases, have not yet been built organically. This is mainly due to the job rotation of the responsible persons and bureaucratic problems limiting cooperation between the public and private sectors. Japan is responding to disasters through a mutual cooperation network between the public and private sectors (NGOs), but in Korea the public sector still manages disasters entirely by itself. However, in modern society, the ability of the public sector to effectively manage disasters is limited due to the large number of natural disasters and their wide-ranging consequences. This situation makes it difficult to respond quickly and effectively to the various crises that arise. In this paper, we review the disaster response bases in the cases of Japan and the United States, and propose the establishment of a disaster response base system that supports disaster countermeasures together with a cooperative network incorporating the private and business sectors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1357-1366
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• 2022

It is important to quickly and accurately build a disaster network or tactical mobile communication network adapting to the field. In configuring the traditional wireless communication systems, the parameters of the base station are set through cell planning. However, for cell planning, information on the environment must be established in advance. If parameters which are not appropriate for the field are used, because they are not reflected in cell planning, additional optimization must be carried out to solve problems and improve performance after network construction. In this paper, we present a rapid mobile communication network construction and optimization method using artificial intelligence and SON technologies in mobile communication base stations. After automatically setting the base station parameters using the CNN model that classifies the terrain with path loss prediction through the DNN model from the location of the base station and the measurement information, the path loss model enables continuous overage/capacity optimization.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.51-58
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• 2010

SIP is a flexible and extensible call setup protocol that may be combined with other protocols used in the Internet to make various services like voice communication. Voice communication can be classified into normal calls used for communication between common users and emergency calls for 112, 119 and other services through public safety networks. It is required to research to process effectively these normal calls and emergency calls through public networks such as the Internet. In this paper, we propose a bypass scheme for emergency calls by giving priority to INVITE messages for them and processing them with priority in the SIP proxy queue. We perform simulation studies using the network simulator ns-2 for the performance evaluation. Simulation results show that the proposed scheme processes emergency calls faster than normal calls and thus it is expected to make a special purpose network like the national disaster network efficiently by using the existing Internet.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.168-173
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• 2024

This paper proposes a solution for innovating crime prevention and real-time response through the development of the Smart Drone Police System. The system integrates big data, artificial intelligence (AI), the Internet of Things (IoT), and autonomous drone driving technologies [2][5]. It stores and analyzes crime statistics from the Statistics Office and the Public Prosecutor's Office, as well as real-time data collected by drones, including location, video, and audio, in a cloud-based database [6][7]. By predicting high-risk areas and peak times for crimes, drones autonomously patrol these identified zones using a self-driving algorithm [5][8]. Equipped with video and voice recognition technologies, the drones detect dangerous situations in real-time and recognize threats using deep learning-based analysis, sending immediate alerts to the police control center [3][9]. When necessary, drones form an ad-hoc network to coordinate efforts in tracking suspects and blocking escape routes, providing crucial support for police dispatch and arrest operations [2][11]. To ensure sustained operation, solar and wireless charging technologies were introduced, enabling prolonged patrols that reduce operational costs while maintaining continuous surveillance and crime prevention [8][10]. Research confirms that the Smart Drone Police System is significantly more cost-effective than CCTV or patrol car-based systems, showing a 40% improvement in real-time response speed and a 25% increase in crime prevention effectiveness over traditional CCTV setups [1][2][14]. This system addresses police staffing shortages and contributes to building safer urban environments by enhancing response times and crime prevention capabilities [4].