Earticle

Microdosimetry does not simply refer to dosimetry with small targets, but rather to dosimetry that accounts for the stochastic nature of energy deposition. The International Commission on Radiation Units and Measurements has proposed using the probability densities of microdosimetric quantities such as lineal energy (y) and specific energy (z) to characterize the radiation fields instead of relying solely on linear energy transfer (LET) and absorbed dose. However, the practical application of microdosimetry remains limited due to significant computational costs associated with evaluating these stochastic quantities in macroscopic contexts such as the human body. To bridge the gap between microdosimetry and macrodosimetry, three approaches have been proposed and implemented: direct integration of track-structure and macroscopic radiation transport codes; integration of a database containing dose-mean values of microdosimetric quantities into macroscopic radiation transport codes; and integration of the analytical microdosimetric function for instantaneously calculating the probability densities of microdosimetric quantities within macroscopic radiation transport codes. This paper comprehensively reviews the conceptual and practical differences between LET and microdosimetric quantities, including their respective computational methodologies. The advantages and limitations of the three approaches are then discussed, followed by a summary of previous research efforts and suggestions for future research directions.

Perspective taking, one’s knowledge of their own mental and emotional states and inferences about others’ mental and emotional states, is an important higher order cognitive skill required in successful writing. However, there has not been much research on the identification and examiantion of the psychometrics of perspective taking. To fill in this gap, I reviewed the psychological and cognitive frameworks of perspective taking including theory of mind, audience awareness, development of epistemological understanding, and argumentation schema. I also reviewed various methods of examining the psychometric properties of perspective taking in written composition, including both manual and computational approaches. The review of literature yielded suggestions on the development of manual coding scheme for perspective taking as well as the selection of indexes to draw from natural language processing tools. Challenges and affordances of combining the manual and computational approach are discussed along with future research directions to advance the field of psycholinguistics.

Foot-and-Mouth Disease (FMD) is a highly contagious trans-boundary viral disease caused by FMD virus, which causes huge economic losses. FMDV infects cloven hoofed (two-toed) mammals such as cattle, sheep, goats, pigs and various wildlife species. To control the FMDV, it is necessary to understand the life cycle and the pathogenesis of FMDV in host. Especially, the protein-protein interaction between FMDV and host will help to understand the survival cycle of viruses in host cell and establish new therapeutic strategies. However, the computational approach for protein-protein interaction between FMDV and pig hosts have not been applied to studies of the onset mechanism of FMDV. In the present work, we have performed the prediction of the pig's proteins which interact with FMDV based on RNA-Seq data, protein sequence, and structure information. After identifying the virus-host interaction, we looked for meaningful pathways and anticipated changes in the host caused by infection with FMDV. A total of 78 proteins of pig were predicted as interacting with FMDV. The 156 interactions include 94 interactions predicted by sequence-based method and the 62 interactions predicted by structure-based method using domain information. The protein interaction network contained integrin as well as STYK1, VTCN1, IDO1, CDH3, SLA-DQB1, FER, and FGFR2 which were related to the up-regulation of inflammation and the down-regulation of cell adhesion and host defense systems such as macrophage and leukocytes. These results provide clues to the knowledge and mechanism of how FMDV affects the host cell.

The problems associated with gene identification and the prediction of gene structure in DNA sequences have been the focus of increased attention over the past few years with the recent acquisition by large-scale sequencing projects of an immense amount of genome data. A variety of prediction programs have been developed in order to address these problems. This paper presents a review of the computational approaches and gene-finders used commonly for gene prediction in eukaryotic genomes. Two approaches, in general, have been adopted for this purpose: similarity-based and ab initio techniques. The information gleaned from these methods is then combined via a variety of algorithms, including Dynamic Programming (DP) or the Hidden Markov Model (HMM), and then used for gene prediction from the genomic sequences.

Computational approaches for the aerodynamic design and optimization are introduced. In this paper the aerodynamic design methods and applications, which have been applied to various aerospace vehicles at Konkuk University, are introduced. It is shown that system approximation technique reduces computational cost for CFD analysis and improves efficiency for the design optimization process.

Structural genomics aims to provide a good experimental structure or computational model of every tractable protein in a complete genome. Underlying this goal is the immense value of protein structure, especially in permitting recognition of distant evolutionary relationships for proteins whose sequence analysis has failed to find any significant homolog. A considerable fraction of the genes in all sequenced genomes have no known function, and structure determination provides a direct means of revealing homology that may be used to infer their putative molecular function. The solved structures will be similarly useful for elucidating the biochemical or biophysical role of proteins that have been previously ascribed only phenotypic functions. More generally, knowledge of an increasingly complete repertoire of protein structures will aid structure prediction methods, improve understanding of protein structure, and ultimately lend insight into molecular interactions and pathways. We use computational methods to select families whose structures cannot be predicted and which are likely to be amenable to experimental characterization. Methods to be employed included modern sequence analysis and clustering algorithms. A critical component is consultation of the presage database for structural genomics, which records the community's experimental work underway and computational predictions. The protein families are ranked according to several criteria including taxonomic diversity and known functional information. Individual proteins, often homologs from hyperthermophiles, are selected from these families as targets for structure determination. The solved structures are examined for structural similarity to other proteins of known structure. Homologous proteins in sequence databases are computationally modeled, to provide a resource of protein structure models complementing the experimentally solved protein structures.

The compound 3-(2-Mercaptopyridine)phthalonitrile has been synthesized and characterized by IR, UV-vis, and X-ray single-crystal determination. The molecular geometry from X-ray determination of the title compound in the ground state has been compared using the Hartree-Fock (HF) and density functional theory (DFT) with the 6-31G(d) basis set. The calculated results show that the DFT and HF can well reproduce the structure of the title compound. The energetic behavior of the title compound in solvent media was examined using the B3LYP method with the 6-31G(d) basis set by applying the Onsager and polarizable continuum model. Using the TD-DFT and TD-HF methods, electronic absorption spectra of the title compound have been predicted and good agreement with the TD-DFT method and the experimental determination was found. The predicted nonlinear optical properties of the title compound are much greater than those of urea. Besides, molecular electrostatic potential of the title compound were investigated by theoretical calculations. The thermodynamic properties of the compound at different temperatures have been calculated and corresponding relations between the properties and temperature have also been obtained.

An auxiliary device, called Post Cyclone (PoC). had been introduced and primarily examined in earlier works which proved the reduction of the emission of fine dust from the gas-solid cyclones without incurring significant increase of cost and pressure drop. It has been known that the PoC has some advantages over other secondary dust treatment devices such as (a) simple design, (b) low cost of manufacture, (c) minimum additional pressure drop, (d) high recoverbility of the product dust, and (e) simplicity of operation. Despite the potential advantage, however, lack of practical data confined its plausible application in wide areas. Thus, in this work, a few serial experiments were conducted in terms of a few operation conditions, and the particle trajectories throughout the cyclone set-up were visually analyzed by using a commercial computer simulation program (FLUENT).

This study investigates how immigrants are represented in The New York Times by applying text mining techniques and critical discourse analysis to a corpus of 1,000 immigration-related news articles. Combining methods such as word frequency analysis, word embeddings, and clustering, the study identifies major thematic domains within immigration discourse, including political and legal processes, border control, socio-economic impacts, and urban life. The analysis reveals that while overtly negative terms are largely absent, linguistic choices frequently foreground immigrants’ legal status, framing them in ways that implicitly reinforce institutional ideologies and marginalization. The study further argues that such delicate ideological representations often elude large-scale quantitative approaches, highlighting the limitations of automated, frequency-based text analysis. The absence of explicitly negative language is attributed to both methodological constraints and data bias, including sampling limitations and a narrow source base. As such, the findings emphasize the need for “smart big data”, datasets that combine volume with contextual richness, and call for the integration of qualitative discourse analysis to reflect the pragmatic and ideological complexity of media language. By connecting computational and interpretive approaches, this research contributes to interdisciplinary scholarship on critical discourse analysis, immigration studies, and data methodologies.

A thermophilic Bacillus stearothermophilus F1 produces an extremely thermostable serine protease. The F1 protease sequence was used to predict its three-dimensional (3D) structure to provide better insights into the relationship between the protein structure and biological function and to identify opportunities for protein engineering. The final model was evaluated to ensure its accuracy using three independent methods: Procheck, Verify3D, and Errat. The predicted 3D structure of F1 protease was compared with the crystal structure of serine proteases from mesophilic bacteria and archaea, and led to the identification of features that were related to protein stabilization. Higher thermostability correlated with an increased number of residues that were involved in ion pairs or networks of ion pairs. Therefore, the mutants W200R and D58S were designed using site-directed mutagenesis to investigate F1 protease stability. The effects of addition and disruption of ion pair networks on the activity and various stabilities of mutant F1 proteases were compared with those of the wild-type F1 protease.

사회 복잡성이 계속해서 증가함에 따라, 이를 연구하기 위한 도구로서 사회학적 시스템 이론의 중요성이 강조되어 왔다. 그러나 기존의 사회학적 시스템 이론들은 메타-, 거대이론적 논의에 머무르며, 충분한 분석 역량을 발휘하지 못한다는 한계가 지적되어 왔다. 이러한 문제의식을 바탕으로, 본 연구는 사회학적 시스템 이론의 분석 역량을 재고하기 위해 사회적 시스템의 시뮬레이션에 적용가능한 일부 전산적(computational) 모델들의 사회학적 활용 가능성을 탐색한다. 먼저, 시뮬레이션의 일반적 의의를 개괄한 후, 에이전트 기반 모델(Agent-Based Model)과 소프트 컴퓨팅(Soft Computing)의 사회학적 의미를 논의한다. 이어서 유전 알고리즘(Genetic Algorithm)과 소시오닉스(Socionics)와 같은 전산적 접근법의 핵심 내용과 특징을 조망할 뿐만 아니라, 경험적 사회 연구에서의 활용 가능성과 적용 시 고려해야 할 사항들을 면밀히 검토한다. 아울러, ‘사회학과 복잡성 과학(Sociology and Complexity Science, SACS)’ 연구자 커뮤니티의 기본 지향과 한계 또한 간략히 논의한다.

With the increasing complexity of society, the importance of sociological systems theory as a tool for studying such complexity has been emphasized. However, existing sociological systems theories have been criticized for remaining at the level of meta-theoretical and grand-theoretical discussions, lacking sufficient analytical capacity. Based on this concern, this study explores the sociological applicability of certain computational models that can be used for simulating social systems to enhance the analytical capabilities of sociological systems theory. First, the general significance of simulation is outlined, followed by a discussion on the sociological implications of Agent-Based Models (ABM) and Soft Computing. Subsequently, the core concepts and characteristics of computational approaches such as Genetic Algorithms and Socionics are examined, along with a detailed review of their applicability in empirical social research and key considerations for their implementation. Additionally, the fundamental orientations and limitations of the research community in Sociology and Complexity Science (SACS) are briefly discussed.

본 연구에서는 퍼즐 기반 학습에서 이루어지는 초등정보영재의 컴퓨팅적 문제 해결 접근법을 분석함으로써 퍼즐 기반 학습의 체계적 개선을 위한 시사점을 도출하고자 하였다. 이를 위해, 제약조건, 최적화, 확률, 통계, 패턴인식, 전략의 6가지 유형별 교육용 퍼즐을 구성하고 초등정보영재를 대상으로 퍼즐 기반 학습을 수행하였다. 또한 각 퍼즐 유형에 따른 학습자의 문제 해결 접근법을 확인하기 위해 사전 사후검사 결과의 정답률 및 정답자와 오답자의 문제 해결 접근법을 비교 분석하였다. 연구 결과, 각 퍼즐 유형별 빈번한 오류 발생의 원인인 몇 가지 양식 오류와 다양한 직관들을 확인하였으며, 오답자들은 '백트래킹', '동적 프로그래밍', '추상화', '모델링', '문제 축소'와 같은 컴퓨팅적 전략을 적용하지 못함으로 인해 완전한 해법에 도달하지 못한다는 것을 확인하였다. 이러한 분석 결과를 토대로 퍼즐 문제 표현 방식의 개선, 인지적 피드백의 적시 제공, 퍼즐 기반 학습 지원을 위한 웹 기반 시스템 개발 등 퍼즐 기반 학습 개선 방안을 제안하였다.

The purpose of this study is to propose strategies of puzzle-based learning for Informatics gifted education through analyzing Informatics gifted elementary students' computational problem solving approaches in puzzle-based learning contexts. Six types of educational puzzles, which are constraints, optimization, probability, statistically speaking, pattern recognition, and strategy, were used in teaching 14 Informatics gifted students for 8 sessions. The results of pre and post test and each students' answers were analyzed to identify why students were not able to solve the puzzles. We also analysed what essential computational strategies are needed to solve each type of puzzles, and what students did not know in solving puzzle problems. We identified some problems caused by puzzle representation methods, and various students' intuitions that disturb puzzle solving. Also, we identified essential computational strategies to solve puzzles: backtracking, dynamic programming, abstraction, modeling, and reduction of big problem. However, students had difficulties in applying these strategies to solve their puzzle problems. We proposed the revised puzzle-based learning strategies, which is based on the improved problem representation, just-in-time cognitive feedbacks, and web-based learning system.

에코 챔버는 필터 버블과 더불어 최근 미디어·정치 상황에서 많이 등장하는 가설적 개념이다. 그러나 많은 유행 개념들이 그렇듯이 에코 챔버 역시 개념에 대한 정의도, 실재 여부에 대한 증명도, 병폐성에 대한 합의도 그렇게 확고하지 않다. 이를 이론이라 한다면 이렇게 허술한 이론도 찾아보기 어려울 것이다. 그러나 연구의 양은 ‘체계적 문헌 리뷰’가 여러 차례 쓰일 정도로 엄청나게 많다. 연구자들의 출신도 다양하고, 방법도 새롭다. 컴퓨터·데이터과학의 다양한 기법들이 동원되는 컴퓨테이션은 에코 챔버를 지금의 지위로 만들었다. 개념·증명여부·방법론을 분석한 이 글의 전반부는 이 과정을 추적한다. 결과는 컴퓨테이션이 증명한 네트워크 효과는 에코 챔버의 전제인 군집화를 확인하는 데 그쳤고, 일부 수용자를 과잉 대표하게 만들었다. 또 많은 연구는 특정 플랫폼에 집중해 소셜 미디어 전체로 일반화하는 데 문제가 있었고, 측정 방식 또한 일관되지않거나 범위가 협소했다. 마지막 미국이라는 공간적 한계 역시 일반화된 이론으로 발전하는 데는 문제가 있었다. 그러나 그렇다고 해서 이런 비판론이 에코 챔버의 가정 자체를 완전히 부정하는 경우도 거의 없었다. 이는 에코 챔버론이 최근 들어 더욱 심화된 대립을 보이는 보수와 진보 진영의 정보와 의견 편향을 적시하는 직관적 타당성을 갖기 때문일 것이다. 후반부는 이런 에코 챔버의 논의구도를 보다 폭넓게, 또 비판적으로 조망하는 ‘대안적 컴퓨테이션 사회과학’을살펴보고, 이의 일환인 질적·혼합적 방법의 대안적 가치와 한계를 제시한다. 질적·혼합적 방법은 가치에 비해 사례는 희귀할 만큼 적다. 그러나 에코 챔버의 병폐로 꼽히는 양극화나 적대적 음모론이 강해질수록 사회적 맥락과 정체성에 주목하는 이 방법의 필요성도 커질 것이다.

Echo chambers, alongside filter bubbles, have gained prominence as theoretical constructs in contemporary media and political discourse. However, as with many buzzwords, the definition of echo chambers remains contested, empirical validation is inconclusive, and scholarly consensus on their societal implications is lacking. If echo chambers were to be classified as an established theory, its conceptual foundation would appear notably unstable. Nevertheless, the volume of research on this subject is extensive and well-documented, to the extent that several systematic literature reviews have been undertaken. Scholars from diverse disciplinary backgrounds have engaged with this phenomenon, employing an array of methodological innovations. Computational approaches, drawing on techniques from computer and data science, have been instrumental in shaping the prominence of echo chambers studies. The first section of this paper critically examines this trajectory by analyzing the conceptual foundations, empirical validation, and methodological frameworks in echo chambers research. The findings indicate that computational methods have predominantly identified network clustering effects(homophily), which merely confirm the preconditions of echo chambers rather than validating their full theoretical implications. Moreover, these methodologies have often resulted in an overrepresentation of highly engaged and ideologically motivated user groups. Many studies have also been constrained by their focus on specific digital platforms(Twitter, Facebook), raising concerns about the extent to which their findings can be extrapolated tothe broader social media ecosystem. Additionally, inconsistencies in measurement and the predominant emphasis on the United States pose further challenges to the global theoretical framework. However, despite these limitations, few studies completely reject the foundational premises of echo chambers theory. This persistence likely stems from its intuitive validity, given the increasing polarization of information consumption patterns and the growing ideological confrontation between conservatives and progressives. The latter part of this paper expands the discourse on echo chambers by engaging with critical perspectives from heterodox computational social science. It explores the epistemological and methodological contributions of qualitative and mixed-method approaches as alternative frameworks. Despite their analytical significance, these approaches remain significantly underexplored. However, as the societal concerns frequently associated with echo chambers － such as ideological polarization and antagonistic conspiracy theories － continue to intensify, the necessity of methodologies that emphasize social context and cultural identity will become increasingly evident.

본 논문은 목적 함수가 분수로 표현되고 제약 조건의 모든 함수가 선형이며 모든 변수가 이산형인 정수 선형 분수 계획법(Integer Linear Fractional Programming) 문제를 다룬다. 최적해를 도출하기 위해 새로운 파라메트릭(Parametric) 알고리즘을 제안하고 이를 실증적(empirical)으로 분석하였다. 기존의 파라메트릭 알고리즘(예., 뉴턴 알고리즘)은 분수 계획법 문제의 최적 함수 값에 접근하는 한 방향의 (하한) 수열 값을 생성하는 반면, 제안한 파라메트릭 알고리즘은 최적 함수 값에 수렴하는 하한과 상한 수열 값을 같이 생성하는 차이점이 있다. 또한 본 연구에서 제안한 알고리즘이 다양한 생산 및 운영 관리 문제에 효과적으로 적용할 수 있음을 보여주기 위해 잘 알려진 분수 배낭 문제(fractional knapsack problem)를 대상으로 수치적 성능과 그 효율성을 분석했다. 여러 조건을 고려한 실험 환경을 무작위로 생성하고 이러한 다양한 시나리오의 분수 배낭 문제에서 알고리즘의 성능을 뉴턴 알고리즘과 비교했다. 성능 지표로 보조 함수(auxililary function)의 평가 횟수를 측정한 결과, 본 연구에서 제안한 알고리즘이 정수 선형 분수 계획법 문제를 더 빠르고(fast) 안정적(robust)으로 푼다는 것을 알 수 있다. 이러한 알고리즘을 이용해 기존의 생산 및 운영 문제에서 비분수 형태의 목적식이 고려할 수 없었던 상황을 극복하고 새로운 결과와 의미를 도출할 수 있을 것으로 기대한다.

In this paper, we focus on the integer linear fractional optimization problem, a special case of fractional programming where all functions in the objective function and constraints are linear and all variables are bounded and discrete. To derive the optimal solution, the parametric algorithms are considered, and the efficiency of the algorithms is investigated computationally. Unlike traditional parametric algorithms such as Newton's method, which create a unidirectional sequence approaching the optimal function value, our proposed algorithm generates both upper and lower bounds converging to this value. To demonstrate its effectiveness across various production and operations management problems, the suggested algorithms are used to solve the fractional knapsack problem by comparison to other algorithms (e.g., Newton’s method) under the randomized experimental conditions. The relative practical performance measured by the number of function calls demonstrates that the proposed algorithms are fast and robust for solving the linear fractional programs with discrete variables. Leveraging this algorithm holds the potential to overcome situations in traditional production and operations problems where non-fractional objective functions were previously unconsidered, thereby expecting to derive new outcomes and significance.