• Title/Summary/Keyword: discipline bias

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Discipline Bias of Document Citation Impact Indicators: Analyzing Articles in Korean Citation Index (논문 인용 영향력 측정 지수의 편향성에 대한 연구: KCI 수록 논문을 대상으로)

  • Lee, Jae Yun;Choi, Sanghee
    • Journal of the Korean Society for information Management
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    • v.32 no.4
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    • pp.205-221
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    • 2015
  • The impact of a journal is commonly used as the impact of an individual paper within that journal. It is problematic to interpret a journal's impact as a single paper's impact of the journal, so there are several researches to measure a single paper's impact with its own citation counts. This study applied 8 impact indicators to Korean Citation Index database and examined discipline bias of each indicator. Analyzed indicators are simple citation counts, PageRank, f-value, CCI, c-index, single publication h-index, single publication hs-index, and cl-index. PageRank has the least discipline bias at highly ranked papers and journal bias in a discipline. On the contrary, simple citation counts showed strongly biased results toward a certain discipline or a journal. KCI database provides only simple citation counts. It needs to show PageRank (global indicator) to discover influential papers in diverse areas. Furthermore it needs to consider to provide the best of local indicators. Local indicators can be calculated only with papers in users' search results because they uses citation counts of citing papers and the number of references. They are more efficient than global indicators which explore the whole database. KCI should also consider to provide Cl-index (local indicator).

Three-Stage Strati ed Randomize Response Model (3단계 층화확률화응답모형)

  • Kim, Jong-Min;Chae, Seong-S.
    • The Korean Journal of Applied Statistics
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    • v.23 no.3
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    • pp.533-543
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    • 2010
  • Asking sensitive questions by a direct survey method causes non-response bias and response bias. Non-response bias arises from interviewees refusal to respond and response bias arises from giving incorrect responses. To rectify these biases, Warner (1965) introduced a randomized response model which is an alternative survey method for socially undesirable or incriminating behavior questions. The randomized response model is a procedure for collecting the information on sensitive characteristics without exposing the identity of the respondent. Many survey researchers have proposed diverse variants of the Warner randomized response model and applied their model to collect the information of sensitive questions. Using an optimal allocation, we proposed three-stage stratified randomized response technique which is an extension of the Kim and Elam (2005) two-stage stratified randomized response technique. In this study, we showed that the estimator based on the proposed response model is more efficient than Kim and Elam (2005). But by adding one more survey step to the Kim and Elam (2005), our proposed model may have relatively less privacy protection compared to the Kim and Elam (2005) model.

Families of Estimators of Finite Population Variance using a Random Non-Response in Survey Sampling

  • Singh, Housila P.;Tailor, Rajesh;Kim, Jong-Min;Singh, Sarjinder
    • The Korean Journal of Applied Statistics
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    • v.25 no.4
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    • pp.681-695
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    • 2012
  • In this paper, a family of estimators for the finite population variance investigated by Srivastava and Jhajj (1980) is studied under two different situations of random non-response considered by Tracy and Osahan (1994). Asymptotic expressions for the biases and mean squared errors of members of the proposed family are obtained; in addition, an asymptotic optimum estimator(AOE) is also identified. Estimators suggested by Singh and Joarder (1998) are shown to be members of the proposed family. A correction to the Singh and Joarder (1998) results is also presented.

Efficient Use of Auxiliary Variables in Estimating Finite Population Variance in Two-Phase Sampling

  • Singh, Housila P.;Singh, Sarjinder;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • v.17 no.2
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    • pp.165-181
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    • 2010
  • This paper presents some chain ratio-type estimators for estimating finite population variance using two auxiliary variables in two phase sampling set up. The expressions for biases and mean squared errors of the suggested c1asses of estimators are given. Asymptotic optimum estimators(AOE's) in each class are identified with their approximate mean squared error formulae. The theoretical and empirical properties of the suggested classes of estimators are investigated. In the simulation study, we took a real dataset related to pulmonary disease available on the CD with the book by Rosner, (2005).

Construction Cost-Schedule Integration Management Methodolgy by using Progress Integration Unit (성과측정유닛을 활용한 건설 비용 - 일정 통합관리 방안)

  • Kang, Namhee;Choi, Jaehyun
    • Korean Journal of Construction Engineering and Management
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    • v.18 no.3
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    • pp.42-51
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    • 2017
  • Measuring and evaluating project progress and performance are the key element of the construction project success. Construction progress is typically measured quantitatively by evaluating cost and time allocated to the project deliverable, and thus properly integrating cost and time is essential to the project management. This research was performed to propose an alternative methodology to integrate the cost and time and provide a framework for the progress measurement. The researchers developed a typical work process for the cost and schedule planning and also developed an alternative cost-schedule integration method by using progress integration units (PIU). A discipline of a construction phase served as a common level for WBS and CBS integration, so the PIUs'were defined under discipline. A case study project was selected to validate the developed methodology. The result showed the proposed method improved efficiency of cost and time integration. The result also showed the excluding material for the progress measurement purpose significantly reduced the bias of progress measurement.

Conflict of Interests and Analysts' Forecast (이해상충과 애널리스트 예측)

  • Park, Chang-Gyun;Youn, Taehoon
    • KDI Journal of Economic Policy
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    • v.31 no.1
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    • pp.239-276
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    • 2009
  • The paper investigates the possible relationship between earnings prediction by security analysts and special ownership ties that link security companies those analysts belong to and firms under analysis. "Security analysts" are known best for their role as information producers in stock markets where imperfect information is prevalent and transaction costs are high. In such a market, changes in the fundamental value of a company are not spontaneously reflected in the stock price, and the security analysts actively produce and distribute the relevant information crucial for the price mechanism to operate efficiently. Therefore, securing the fairness and accuracy of information they provide is very important for efficiencyof resource allocation as well as protection of investors who are excluded from the special relationship. Evidence of systematic distortion of information by the special tie naturally calls for regulatory intervention, if found. However, one cannot presuppose the existence of distorted information based on the common ownership between the appraiser and the appraisee. Reputation effect is especially cherished by security firms and among analysts as indispensable intangible asset in the industry, and the incentive to maintain good reputation by providing accurate earnings prediction may overweigh the incentive to offer favorable rating or stock recommendation for the firms that are affiliated by common ownership. This study shares the theme of existing literature concerning the effect of conflict of interests on the accuracy of analyst's predictions. This study, however, focuses on the potential conflict of interest situation that may originate from the Korea-specific ownership structure of large conglomerates. Utilizing an extensive database of analysts' reports provided by WiseFn(R) in Korea, we perform empirical analysis of potential relationship between earnings prediction and common ownership. We first analyzed the prediction bias index which tells how optimistic or friendly the analyst's prediction is compared to the realized earnings. It is shown that there exists no statistically significant relationship between the prediction bias and common ownership. This is a rather surprising result since it is observed that the frequency of positive prediction bias is higher with such ownership tie. Next, we analyzed the prediction accuracy index which shows how accurate the analyst's prediction is compared to the realized earnings regardless of its sign. It is also concluded that there is no significant association between the accuracy ofearnings prediction and special relationship. We interpret the results implying that market discipline based on reputation effect is working in Korean stock market in the sense that security companies do not seem to be influenced by an incentive to offer distorted information on affiliated firms. While many of the existing studies confirm the relationship between the ability of the analystand the accuracy of the analyst's prediction, these factors cannot be controlled in the above analysis due to the lack of relevant data. As an indirect way to examine the possibility that such relationship might have distorted the result, we perform an additional but identical analysis based on a sub-sample consisting only of reports by best analysts. The result also confirms the earlier conclusion that the common ownership structure does not affect the accuracy and bias of earnings prediction by the analyst.

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The Implications of Feminist Epistemology for Knowledge Production in Social Welfare (사회복지연구를 위한 페미니스트 인식론의 비평과 함의)

  • Sung, Jung-Suk;Lee, Na-Young
    • Korean Journal of Social Welfare
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    • v.62 no.2
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    • pp.349-373
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    • 2010
  • The purpose of this paper is to critically analyze the way of knowledge production in social welfare and to graft feminist epistemology to the discipline of social welfare. To put it more concretely, as analyzing the epistemological and methodological issues appeared in the articles in "orean Journal of Social Welfare", this study examines the meanings of feminist epistemology and its implications to research and practice in social welfare. From its onset, feminist research criticized the 'mainstream' ways of conceptualizing knowledge construction via research conducted upon a positivist epistemological position. Particularly, western feminists have problematized the androcentric bias embedded within the so-called 'social sciences' that we have taken for granted as 'scientific,' 'objective,' and 'neutral,' and attempted to redirect and reformulate the way of knowledge production with new concepts of 'strong objectivity,' 'partial/situated knowledge,' and 'strong reflection.' We believe that the implications of feminist epistemology to enable us to reflect the power relationship between subject and object, I and Other, and the researcher and the researched will contribute to recover the original vision of social welfare as critical theory and liberating practice in social work.

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Regulation of autonomic functions following two high frequency yogic breathing techniques

  • Mondal, Joydeb;Balakrishnan, Ragavendrasamy;Krishnamurthy, Manjunath Nandi
    • CELLMED
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    • v.5 no.1
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    • pp.4.1-4.4
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    • 2015
  • Yoga is an ancient Indian system of life, encompassing various practices including practices for self-discipline and also for regulating the health states of the individual, being practiced for thousands of years. The present study aims at understanding the effect of two high frequency breathing practices over autonomic nervous system. Forty healthy male volunteers of age $21{\pm}2$ years with $9{\pm}3$ months of Yoga practice experience were recruited. The two high frequency Yoga breathing practices, kapalabhati (KB) and bhastrika (BH) were given as interventions randomly on either of the two days to minimise laboratory bias. They were assessed before and immediately after the interventions for heart rate, respiratory rate, heart rate variability (HRV), blood pressure and peripheral oxygen saturation. There was a significant increase in heart rate (p<0.01; p<0.001), systolic blood pressure (p<0.01; p<0.001), NN50 (p<0.01; p<0.001) component of HRV for both KB and BH groups respectively. There was a significant reduction in respiratory rate in both the groups (p<0.001, and p<0.05, BH and KB respectively) immediately following intervention. A significant increase in LF component of HRV and reduction in Diastolic blood pressure and high frequency (HF)component following KB was also observed (p<0.05, for all comparisons). The Mean peripheral oxygen saturation remained unaltered in both the groups (p>0.05).The results suggest that high frequency yoga breathing practices induce physiological arousal immediately as evidenced by increased blood pressure and heart rate. The sympathetic arousal was more following KB session as evidenced by an increased diastolic blood pressure, LF power and a decrease in HF power of HRV as compared to the BH session.

The Comparison of Sphere Fitting Methods for Estimating the Center of Rotation on a Human Joint (인체관절의 회전중심 추정을 위한 구적합법의 비교)

  • Kim, Jin-Uk
    • Korean Journal of Applied Biomechanics
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    • v.23 no.1
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    • pp.53-62
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    • 2013
  • The methods of fitting a circle to measured data, geometric fit and algebraic fit, have been studied profoundly in various areas of science. However, they have not been applied exactly to a biomechanics discipline for locating the center of rotation of a human joint. The purpose of this study was to generalize the methods to fitting spheres to the points in 3-dimension, and to estimate the center of rotation of a hip joint by three of geometric fit methods(Levenberg-Marquardt, Landau, and Sp$\ddot{a}$th) and four of algebraic fit methods(Delogne-K${\aa}$sa, Pratt, Taubin, and Hyper). 1000 times of simulation experiments for flexion/extension and ad/abduction at an artificial hip joint with four levels of range of motion(10, 15, 30, and $60^{\circ}$) and three levels of angular velocity(30, 60, and $90^{\circ}$/s) were executed to analyze the responses of the estimated center of rotation. The results showed that the Sp$\ddot{a}$th estimate was very sensitive to the marker near the center of rotation. The bias of Delogne-K${\aa}$sa estimate existed in an even larger range of motion. The Levenberg-Marquardt algorithm of geometric fit and the Pratt of algebraic fit showed the best results. The combination of two methods, using the Pratt's estimate as initial values of the Levenberg-Marquardt algorithm, could be a candidate of more valid estimator.

Evaluation of deep learning and convolutional neural network algorithms for mandibular fracture detection using radiographic images: A systematic review and meta-analysis

  • Mahmood Dashti;Sahar Ghaedsharaf;Shohreh Ghasemi;Niusha Zare;Elena-Florentina Constantin;Amir Fahimipour;Neda Tajbakhsh;Niloofar Ghadimi
    • Imaging Science in Dentistry
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    • v.54 no.3
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    • pp.232-239
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    • 2024
  • Purpose: The use of artificial intelligence (AI) and deep learning algorithms in dentistry, especially for processing radiographic images, has markedly increased. However, detailed information remains limited regarding the accuracy of these algorithms in detecting mandibular fractures. Materials and Methods: This meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Specific keywords were generated regarding the accuracy of AI algorithms in detecting mandibular fractures on radiographic images. Then, the PubMed/Medline, Scopus, Embase, and Web of Science databases were searched. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool was employed to evaluate potential bias in the selected studies. A pooled analysis of the relevant parameters was conducted using STATA version 17 (StataCorp, College Station, TX, USA), utilizing the metandi command. Results: Of the 49 studies reviewed, 5 met the inclusion criteria. All of the selected studies utilized convolutional neural network algorithms, albeit with varying backbone structures, and all evaluated panoramic radiography images. The pooled analysis yielded a sensitivity of 0.971 (95% confidence interval [CI]: 0.881-0.949), a specificity of 0.813 (95% CI: 0.797-0.824), and a diagnostic odds ratio of 7.109 (95% CI: 5.27-8.913). Conclusion: This review suggests that deep learning algorithms show potential for detecting mandibular fractures on panoramic radiography images. However, their effectiveness is currently limited by the small size and narrow scope of available datasets. Further research with larger and more diverse datasets is crucial to verify the accuracy of these tools in in practical dental settings.