• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.10 no.2
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• pp.145-157
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• 1999

This study was performed by the children and adolescents who were abused or neglected physically, emotionally that were selected in child & adolescents psychiatric ward. We investigated the number of these case in admitted children & adolescents, and also observed characteristics of symptoms, developmental history, characteristics of abuse style, characteristics of abusers, family dynamics and psychopathology. We hypothesized that all kinds of abuse will influnced to emotional, behavioral problems, developmental courses on victims, interactive effects on family dynamics and psychopathology. That subjects were 22 persons of victims who be determined by clinical observation and clinical note. The results of the study were as follows：1) Demographic characteristics of victims：ratio of sex was 1：6.3(male：female), mean age was $11.1{\pm}2.5$. According to birth order, lst was 12(54.5%), 2nd was 5(23%), 3rd was 2(9%) and only child was 3(13.5%). 2) Characteristics of family：According to socioeconomic status, middle to high class was 3(13.5%), middle one was 9(41.% ), middle to low one was 9(41%), low one was 1(0.5%). according to number of family, under the 3 person was 3(13.5%), 4-5 was 17(77.5%), 6-7 was 2(9%). according to marital status of parents, divorce or seperation were 5(23%), remarriage 2(9%), severe marital discord was 19(86.5%). In father, antisocial behavior was 7(32%), alcohol dependence was 10(45.5%). In mother, alcohol abuse was 5(23%), depression was 17(77.3%), history of psychiatric management was 6(27%). 3) Characteristics of abuse：Physical abuse was 18(81.8%), physical and emotional abuse and neglect were 4(18.2%). according to onset of abuse, before 3 years was 15(54.5%), 3-6 years was 5(27.5%), schooler was 1(15%). Only father offender was 2(19%), only mother offender was 8(35.4%), both offender was 8(35.4%), accompaning with spouse abuse was 7(27%), and accompaning with other sibling abuse was 4(18.2%). 4) General characteristics and developmental history of victims：Unwanted baby was 12(54.5%), developmental delay before abuse was9(41%), comorbid developmental disorder was 15(68%). there were 6(27.5%) who didn‘t show definite sign of developmental delay before abuse. 5) Main diagnosis and comorbid diagnosis：According to main diagnosis, conduct disorder 6(27.3%), borderline child 5(23%), depression4(18%), attention deficit hyperactivity disorder(ADHD) 4(18%), pervasive developmental disorder not otherwise specified 2(9%), selective mutism 1(5%). According to comorbid diagnosis, ADHD, borderline intelligence, mental retardation, learning disorder, developmental language disorder, oppositional defiant disorder, chronic tic disorder, functional enuresis and encoporesis, anxiety disorder, dissociative disorder, personality disorder due to medical condition. 5) Course of treatment：A mean duration of admission was $2.4{\pm}1.5$ months. 11(15%) showed improvement of symtoms, however 11(50%) was not changed of symtoms.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.35-52
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• 2019

As public services are provided in various forms, including e-government, the level of public demand for public service quality is increasing. Although continuous measurement and improvement of the quality of public services is needed to improve the quality of public services, traditional surveys are costly and time-consuming and have limitations. Therefore, there is a need for an analytical technique that can measure the quality of public services quickly and accurately at any time based on the data generated from public services. In this study, we analyzed the quality of public services based on data using process mining techniques for civil licensing services in N city. It is because the N city's building license complaint service can secure data necessary for analysis and can be spread to other institutions through public service quality management. This study conducted process mining on a total of 3678 building license complaint services in N city for two years from January 2014, and identified process maps and departments with high frequency and long processing time. According to the analysis results, there was a case where a department was crowded or relatively few at a certain point in time. In addition, there was a reasonable doubt that the increase in the number of complaints would increase the time required to complete the complaints. According to the analysis results, the time required to complete the complaint was varied from the same day to a year and 146 days. The cumulative frequency of the top four departments of the Sewage Treatment Division, the Waterworks Division, the Urban Design Division, and the Green Growth Division exceeded 50% and the cumulative frequency of the top nine departments exceeded 70%. Higher departments were limited and there was a great deal of unbalanced load among departments. Most complaint services have a variety of different patterns of processes. Research shows that the number of 'complementary' decisions has the greatest impact on the length of a complaint. This is interpreted as a lengthy period until the completion of the entire complaint is required because the 'complement' decision requires a physical period in which the complainant supplements and submits the documents again. In order to solve these problems, it is possible to drastically reduce the overall processing time of the complaints by preparing thoroughly before the filing of the complaints or in the preparation of the complaints, or the 'complementary' decision of other complaints. By clarifying and disclosing the cause and solution of one of the important data in the system, it helps the complainant to prepare in advance and convinces that the documents prepared by the public information will be passed. The transparency of complaints can be sufficiently predictable. Documents prepared by pre-disclosed information are likely to be processed without problems, which not only shortens the processing period but also improves work efficiency by eliminating the need for renegotiation or multiple tasks from the point of view of the processor. The results of this study can be used to find departments with high burdens of civil complaints at certain points of time and to flexibly manage the workforce allocation between departments. In addition, as a result of analyzing the pattern of the departments participating in the consultation by the characteristics of the complaints, it is possible to use it for automation or recommendation when requesting the consultation department. In addition, by using various data generated during the complaint process and using machine learning techniques, the pattern of the complaint process can be found. It can be used for automation / intelligence of civil complaint processing by making this algorithm and applying it to the system. This study is expected to be used to suggest future public service quality improvement through process mining analysis on civil service.