• Geophysics and Geophysical Exploration
• /
• v.13 no.1
• /
• pp.40-50
• /
• 2010

The building process of any geological map involves linking sparse lithological outcrop information with equally sparse geometrical measurements, all in a single entity which is the preferred interpretation of the field geologist. The actual veracity of this interpretative map is partially dependent upon the frequency and distribution of geological outcrops compounded by the complexity of the local geology. Geophysics is commonly used as a tool to augment the distribution of data points, however it normally does not have sufficient geometrical constraints due to: a) all geophysical inversion models being inherently non-unique; and b) the lack of knowledge of the physical property contrasts associated with specific lithologies. This contribution proposes the combined use of geophysical edge detection routines and 'three point' solutions from topographic data as a possible approach to obtaining geological contact geometry information (strike and dip), which can be used in the construction of a preliminary geological model. This derived geological information should first be assessed for its compatibility with the scale of the problem, and any directly observed geological data. Once verified it can be used to help constrain the preferred geological map interpretation being developed by the field geologist. The method models the contacts as planar surfaces. Therefore, it must be ensured that this assumption fits the scale and geometry of the problem. Two examples are shown from folded sequences at the Bathurst Mining Camp, New Brunswick, Canada.

• Geophysics and Geophysical Exploration
• /
• v.5 no.3
• /
• pp.157-168
• /
• 2002

Improved procedures were implemented in the production of the lithospheric magnetic anomaly map from Magsat satellite magnetometer data of East Asia between $90^{\circ}E-150^{\circ}E$ and $10^{\circ}S-50^{\circ}N$. Procedures included more effective selection of the do·it and dawn tracks, ring current correction, and separation of core field and external field effects. External field reductions included an ionospheric correction and pass-by-pass correlation analysis. Track-line noise effects were reduced by spectral reconstruction of the dusk and dawn data sets. The total field magnetic anomalies were differentially-reduced-to-the-pole to minimize distortion s between satellite magnetic anomalies and their geological sources caused by corefield variations over the study area. Aeromagnetic anomalies were correlated with Magsat magnetic anomalies at the satellite altitude to test the lithospheric veracity of anomalies in these two data sets. The aeromagnetic anomalies were low-pass filtered to eliminate high frequency components that may not be shown at the satellite altitude. Although the two maps have a low CC of 0.243, there are many features that are directly correlated (peak-to-peak and trough-to-trough). The low CC between the two maps was generated by the combination of directly- and inversely-correlative anomaly features between them. It is very difficult to discriminate directly, inversely, and nully correlative features in these two anomaly maps because features are complicatedly correlated due to the depth and superposition of the anomaly sources. In general, the lithospheric magnetic components were recovered successfully from satellite magnetometer observations and correlated well with aeromagnetic anomalies in the study area.

• Journal of Science and Technology Studies
• /
• v.20 no.1
• /
• pp.39-85
• /
• 2020

With the development of information technology, fake news is becoming a serious social problem. Individual measures to manage the problem, such as fact-checking by the media, legal regulation, or technical solutions, have not been successful. The flood of fake news has undermined not only trust in the media but also the general credibility of social institutions, and is even threatening the foundations of democracy. This is why one cannot leave fake news unchecked, though it is certainly a difficult task to accomplish. The problem of fake news is not about simply judging its veracity, as no news is completely fake or unquestionably real and there is much uncertainty. Therefore, managing fake news does not mean removing them completely. Nor can the problem be left to individuals' capacity for rational judgment. Recurring fake news can easily disrupt individual decision making, which raises the need for socio-technical measures and multidisciplinary collaboration. In this study, we introduce a new public online platform for fake news management, which incorporates a multidimensional and multidisciplinary approach based on citizen science. Our proposed platform will fundamentally redesign the existing process for collecting and analyzing fake news and engaging with user reactions. People in various fields would be able to participate in and contribute to this platform by mobilizing their own expertise and capability.

• Journal of Internet Computing and Services
• /
• v.20 no.1
• /
• pp.87-96
• /
• 2019

In this paper, we propose a MapReduce-supported clustering technique for collecting and classifying distributed workflow enactment event logs as a preprocessing tool. Especially, we would call the distributed workflow enactment event logs as Workflow BIG-Logs, because they are satisfied with as well as well-fitted to the 5V properties of BIG-Data like Volume, Velocity, Variety, Veracity and Value. The clustering technique we develop in this paper is intentionally devised for the preprocessing phase of a specific workflow process mining and analysis algorithm based upon the workflow BIG-Logs. In other words, It uses the Map-Reduce framework as a Workflow BIG-Logs processing platform, it supports the IEEE XES standard data format, and it is eventually dedicated for the preprocessing phase of the ${\rho}$-Algorithm that is a typical workflow process mining algorithm based on the structured information control nets. More precisely, The Workflow BIG-Logs can be classified into two types: of activity-based clustering patterns and performer-based clustering patterns, and we try to implement an activity-based clustering pattern algorithm based upon the Map-Reduce framework. Finally, we try to verify the proposed clustering technique by carrying out an experimental study on the workflow enactment event log dataset released by the BPI Challenges.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.6
• /
• pp.1013-1024
• /
• 2022

In addition to the assessment measure of electric quality levels, load loss are also a factor in hindering the financial profits of electrical sales companies. Therefore, accurate analysis of load losses generated from distributed power networks is very important. The accurate calculation of load losses in the distribution line has been carried out for a long time in many research institutes as well as power utilities around the world. But it is increasingly difficult to calculate the exact amount of loss due to the increase in the congestion of distribution power network due to the linkage of distributed energy resources(DER). In this paper, we develop smart grid big data infrastructure in order to accurately analyze the load loss of the distribution power network due to the connection of DERs. Through the preprocess of data selected from the smart grid big data, we develop a load loss analysis model that eliminated 'veracity' which is one of the characteristics of smart grid big data. Our analysis results can be used for facility investment plans or network operation plans to maintain stable supply reliability and power quality.

• Korean Journal of Forensic Psychology
• /
• v.11 no.3
• /
• pp.349-370
• /
• 2020

This study was to test the effects of unanticipated questions on the number of general and verifiable details. In addition, the number of verifiable details would discriminate truth-tellers and liars more accurately than the number of general details. In a 2(Veracity: truth vs. lie) X 2(Question type: Expected questions vs. Unexpected questions) mixed-design study, truth tellers(N=40) were asked to visit a cafe on campus and liars(N=40) were told to fabricated a story as if they visited the cafe. Then, participants were interviewed about their trip to the cafe and asked four questions(two anticipated questions: 'report the trip in detail', 'describe the place'; two unanticipated questions: 'recall in reverse order', 'report verifiable details'). Each participant's statements were transcribed and coded by trained graduate students for the number of general details and verifiable details. The results showed that truth-tellers mentioned significantly more general details than liars regardless of the question type. On the contrary, there was no significant difference between liars and truth-tellers in the number of verifiable details. High percentages of truth-tellers(62.5%) and liars(80.0%) were classified correctly based on the number of general details whereas only 45.0% of truth tellers and 62.5% of liars were accurately classified by the number of verifiable details. Liars were found to speak more words when asked to provide verifiable details compared to a general open question, but the number of general details did not seem to increase accordingly. The limitations of this study and future research directions were discussed.

• 한국체육학회지인문사회과학편
• /
• v.55 no.3
• /
• pp.43-57
• /
• 2016

This narrative study aims to describe the experience of P.E. assessment that was conducted by P.E. teachers of Korea Science Academy of KAIST, and interpret the educational significance that was found in the process. The study participants were two P.E. teachers who were selected by decisive case sampling method. Data were collected mainly through official interviews with study participants, and through researcher's field notes, informal interviews, various minutes, students' evaluation of teaching, and emails between the researcher and study participants. Data were analyzed through inductive categorization, and to gain veracity of the study, there were integration of diverse materials, advice and suggestions of fellow researchers, continuous confirmation of study texts by study participants. Study participants, while conducting P.E. assessment in Korea Science Academy of KAIST, experienced effectiveness of evaluation such as qualitative development of P,E. classes in accordance with the simplified assessment, freedom from the chores of handling assessment results, students' improved perceptions of P.E. class, realization of safe classes without excessive competition, and the possibility of giving alternative evaluations to pass/fail system but at the same time experienced limitations such as concerns over gaining validity and reliability of P.E. evaluation, the students' attitude who take lightly of P.E. class, and the reality that teachers cannot fail students. The evaluation experiences of the two P.E teachers were educationally interpreted as encounter with good P.E. classes, invitation to P.E. class criticism, and the start of school P.E. culture that is led by students.

• Journal of the Daesoon Academy of Sciences
• /
• v.32
• /
• pp.137-173
• /
• 2019

Modern scientists are trying to find the basic unit of order, fractal geometry, in the complex systems of the universe. Fractal is a term often used in mathematics or physics, it is appropriate as a principle to explain why some models of ultimate reality are represented as multifaceted. Fractals are already widely used in the field of computer graphics and as a commercial principle in the world of science. In this paper, using observations from fractal geometry, I present the embodiment of ultimate reality as understood in Daesoon Thought. There are various models of ultimate reality such as Dao (道, the way), Sangje (上帝, supreme god), Sinmyeong (神明, Gods), Mugeuk (無極, limitlessness), Taegeuk (太極, the Great Ultimate), and Cheonji (天地, heaven and earth) all of which exist in Daesoon Thought, and these concepts are mutually interrelated. In other words, by revealing the fact that ultimate reality is embodied within fractal geometry, it can be shown that concordance and transformation of various models of ultimate reality are supported by modern science. But when the major religions of the world were divided along lines of personality (personal gods) and non-personality (impersonal deities), most religions came to assume that ultimate reality was either transcendental or personal, and they could not postulate a relationship between God and humanity as Yin Yang (陰陽) fractals (Holon). In addition, religions, which assume ultimate reality as an intrinsic and impersonal being, are somewhat different in terms of their degree of Holon realization - all parts and whole restitution. Daesoon Thought most directly states that gods (deities) and human beings are in a relationship of Yin Yang fractals. In essence, "deities are Yin, and humanity is Yang" and furthermore, "human beings are divine beings." Additionally, in the Daesoon Thought, these models of ultimate reality are presented through various concepts from various viewpoints, and they are revealed as mutually interrelated concepts. As such, point of view regarding the universe wherein Holarchy becomes a models in a key idea within perennial philosophy. According to a universalized view of religious phenomena, perennial philosophy was adopted by the world's great spiritual teachers, thinkers, philosophers, and scientists. From this viewpoint, when ultimate reality coincides, human beings and God are no longer different. In other words, the veracity of the theory of ultimate reality that has appeared in Daesoon Thought can find support in both modern science and perennial philosophy.

• The Korean Society of Law and Medicine
• /
• v.24 no.4
• /
• pp.67-101
• /
• 2023

The utilization of generative AI in the medical field is also being rapidly researched. Access to vast data sets reduces the time and energy spent in selecting information. However, as the effort put into content creation decreases, there is a greater likelihood of associated issues arising. For example, with generative AI, users must discern the accuracy of results themselves, as these AIs learn from data within a set period and generate outcomes. While the answers may appear plausible, their sources are often unclear, making it challenging to determine their veracity. Additionally, the possibility of presenting results from a biased or distorted perspective cannot be discounted at present on ethical grounds. Despite these concerns, the field of generative AI is continually advancing, with an increasing number of users leveraging it in various sectors, including biomedical and life sciences. This raises important legal considerations regarding who bears responsibility and to what extent for any damages caused by these high-performance AI algorithms. A general overview of issues with generative AI includes those discussed above, but another perspective arises from its fundamental nature as a large-scale language model ('LLM') AI. There is a civil law concern regarding "the memorization of training data within artificial neural networks and its subsequent reproduction". Medical data, by nature, often reflects personal characteristics of patients, potentially leading to issues such as the regeneration of personal information. The extensive application of generative AI in scenarios beyond traditional AI brings forth the possibility of legal challenges that cannot be ignored. Upon examining the technical characteristics of generative AI and focusing on legal issues, especially concerning the protection of personal information, it's evident that current laws regarding personal information protection, particularly in the context of health and medical data utilization, are inadequate. These laws provide processes for anonymizing and de-identification, specific personal information but fall short when generative AI is applied as software in medical devices. To address the functionalities of generative AI in clinical software, a reevaluation and adjustment of existing laws for the protection of personal information are imperative.