Earticle

This With the expansion of information and communication technology, the term ubiquitous computing is a known concept used to describe the current era of interconnected digital systems, which is silently posing a new threat to private information leakage through encryption applications. This work aims to acquaint individuals with the privacy information forms of expression in networking technology and then proposes secure multi-party computation to achieve personal information protection. This work emphasizes that, for the time being, homomorphic computing research approaches privacy in ubiquitous environments without considering the various aspects and fundamental principles of privacy. Finally, this work highlights the need for multidisciplinary research in the area and the importance that homomorphic computing algorithm research receives input from other related disciplines, such as law and psychology. This research aims to contribute to the ongoing discourse on the nature of privacy and its role in ubiquitous environments, providing insights for future research. Although research on privacy in the area of ubiquitous computing expands in many different directions and covers various topics, privacy issues are still open, and it appears that feasible and effective solutions are still quite far from being realized. A critical analysis of this research on privacy in ubiquitous environments reveals a significant shift: up to now, it has been the government's role to provide the framework for privacy protection. Homomorphic encryption is an encryption scheme that allows operations on encrypted data, and it can be applied in any system using various public key algorithms. When data is transferred to the public area, various encryption algorithms are used to secure both the operations and storage of the data. However, to process data located on a remote proxy server while preserving privacy, homomorphic encryption is crucial, especially for network-based operations.

Due to the simplicity of the k-nearest neighbor classification algorithm, it has been widely used in many fields. Until now, when the sample size is enormous and the feature attributes are outsized, the productivity of the k-nearest neighbor algorithm classification has also significantly increased. This work demonstrates that a k-nearest neighbor-based data mining technique has been utilized for data index to gather data and analyze an outpatient facility's clinical data set. Therefore, the investigational results show that the suggested algorithm can effectively improve the classification effectiveness of the KNN algorithm in processing a large set of data. Data extraction and fetching techniques can classify possible user/customer behavior using the k-nearest neighbor algorithm based on the user or consumer's impression, entailing prospects, responders, active entities, and different entities. Data mining methods have been utilized to uncover undisclosed patterns and relations. Undoubtedly, the information in a novel manner is reasonable to the healthcare stakeholders and to anticipate future patterns and practices in health-related practices. Many examinations and work have focused on various data mining strategies and approaches. The advanced growth of data science, information, and communication technology has directed the progress of medical-based details toward new artificial intelligence-based processes and data sciences.

Note that k-anonymity algorithm has been widely discussed in the area of privacy protection. In this paper, a new search algorithm to achieve k-anonymity for database application is introduced. A lattice is introduced to form a solution space for a k-anonymity problem and then a hybrid search method composed of tabu search and genetic algorithm is proposed. In this algorithm, the tabu search plays the role of mutation in the genetic algorithm. The hybrid method with independent tabu search and genetic algorithm is compared, and the hybrid approach performs the best in average case.

This study examines how the core contents of “Daniel,” “Revelation,” God’s Grace, and Snow Crash, which remind us that humanity can be destroyed by uncontrollable pride and selfishness, are interconnected as simulacra, forming an algorithmic relationship with one another. Like “Daniel,” “Revelation,” and God’s Grace which are apocalyptic literature, Snow Crash shows humanity’s constant craving for a higher dimension to overcome an absurd world, which becomes the driving force to lead the metaverse. In this process, it is revealed that the fundamental contents of “Daniel,” “Revelation,” God’s Grace, and Snow Crash are closely correlated through their simulation relationship, forming an algorithmic structure. While “Daniel,” “Revelation,” and God’s Grace superficially depict a dystopian society that may occur in the future, Snow Crash specifically challenges itself to manifest a new dimension beyond human control. Neal Stephenson’s experimental writing, driven by the hope of subverting the limitations of humanity, visualizes a virtual world that is the metaverse in Snow Crash. In conclusion, Snow Crash which leads people to higher dimension has an algorithmic relationship with apocalyptic literature, driving the emergence of the metaverse while embodying a cyberpunk “Revelation.”

Shimming, active and/or passive, is indispensable for most MR (magnetic resonance) magnets where homogeneous magnetic fields are required within target spaces. Generally, shimming consists of two steps, field mapping and correcting of fields, and they are recursively repeated until the target field homogeneity is reached. Thus, accuracy of the field mapping is crucial for fast and efficient shimming of MR magnets. For an accurate shimming, a "magnetic" center, which is a mathematical origin for harmonic analysis, must be carefully defined, Although the magnetic center is in general identical to the physical center of a magnet, it is not rare that both centers are different particularly in HTS (high temperature superconducting) magnets of which harmonic field errors, especially high orders, are significantly dependent on a location of the magnetic center. This paper presents a new algorithm, based on a field mapping theory with harmonic analysis, to define the best magnetic center of an MR magnet in terms of minimization of pre-shimming field errors. And the proposed algorithm is tested with simulation under gaussian noise environment.

이 논문에서는 고정된 개수를 가진 bin들을 이용하여 실행 복잡도가 p(n).2o() 인 알고리즘을 제시한다, 여기서 x는 ⑤n개의 객체들에 대한 리스트의 길이에 대한 총 비트 수를 나타낸다. 이러한 방법은 수치적 크기나 비중의 합 의 리스트를 이용하는 여러 가지 최적화 알고리즘이나 결정 문제등에 적용할 수 있다. 이 논문에서 제시한 알고리즘은 의사-다항식(pseudo-polynomial) 시간을 갖는 NP-Complete의 많은 문제들을 결정적인 서브-지수 시간에 해결할 수 있은 가능성을 제시한다. 여기서 제시한 알고리즘을 이용하여 생명공학의 유전자 분석에 적용하려고 한다.

We investigate p(n).2o() algorithm for 0/1 knapsack problem where x is the total bit length of a list of sizes of n objects. The algorithm is adaptable of method that achieves a similar complexity for the partition and Subset Sum problem. The method can be applied to other optimization or decision problem based on a list of numerics sizes or weights. 0/1 knapsack problem can be used to solve NP-Complete Problems with pseudo-polynomial time algorithm. We try to apply this technique to bio-informatics problem which has pseudo-polynomial time complexity.

컴퓨터과학의 원리를 교육의 기반이 되는 알고리즘 교육이 초등학교에서부터 강조되고 있다. 그러나 초등학생에 적합한 알고리즘을 교육시키고 초등학생들이 이해하기는 어렵다. 본 연구에서는 초등학생들이 알고리즘에 대해 쉽게 배울 수 있도록 검증되어진 컴퓨터과학 언플러그드의 프로그램을 기반으로 교육과정 및 학습자료를 개발하였다. 학습방법은 활동중심학습으로 구성 하였으며, 학습내용은 해싱기법을 사용하여 주어진 자료를 정렬하고, 요구되는 자료를 찾는 교육과정을 제시하였다. 본 연구에서 제시한 교육과정과 학습자료는 전문가 집단의 검증 및 정보담당 선생님의 설문 분석을 통해 적절하다는 결론을 얻었다.

Algorithm education that become at the base of computational thinking is emphasized as an instrument for teaching the basic principles of Computer Science. We’ll present ‘the sorting teaching contents for algorithm in the elementary student. And they will successfully guide the student to understand sorting using algorithm. The activity-based learning is provided for the contents, and the data will be found out in everyday life. To check the adequacy of these materials they were tested to the elementary classroom, and the results can help to enhance the problem solving ability and the creativity.

본 연구의 목적은 생활 속에서 알고리즘 개념을 포함하는 사례들을 이용한 알고리즘 학습이 초등학생들의 논리적 사고력에 어떤 영향을 미치는가에 대해 알아 보는 것이다. 이를 위해 사전 GALT 검사, 생활 속에서 알고리즘을 지도할 수 있는 사례 선정 및 지도안 작성후 실험처치, 사후 GALT 검사, 그리고 사전, 사후 GALT 검사 결과 간의 대응 표본 t 검증 순으로 실험을 실시하였다. 그 결과 논리적 사고력의 변화 정도와 논리적 사고력을 구성하는 하위 5 개 영역(보존논리, 비례논리, 조합논리, 확률논리, 변인통제논리)의 변화 정도는 유의수준 .05에서 통계적으로 유의미한 결과를 얻었지만 상관논리 변화 정도는 유의 수준 .05에서 통계적으로 유의미한 결과를 얻지 못하였다.

The purpose of this study is to investigate the effect of learning algorithm which uses real-life examples including the concept of algorithm on the logical thinking of elementary school students. For this purpose, the experiment was performed by pre-GALT test, a case selection of algorithm which can be taught in real-life, experiment treatment after completing teaching plan, post-GALT test, and paired sample t-test on the results of pre and post GALT in order. As a result, changes in the degree of logical thinking ability and in five sub-regions(conservative logic, proportional logic, combinatorial logic, probabilistic logic, controlling variables) composing of logical thinking obtained statistically significant results in .05 significance level but changes in the correlational logic couldn't obtain the significant results.

본 논문은 저 전력 설계 자동화를 위한 새로운 최소 자원 상위 레벨 합성 알고리즘을 제안한다. 제안된 알고리즘은 상위 레벨 합성 동안에 기능 연산자의 소비 전력 최소화를 위해 효율적인 접근 방식을 실행한다. 본 논문에서는 CDFG의 스위칭 활동을 감소시키기 위해 모든 제어 스텝을 하나씩 차례로 방문한다. 레지스터 공유 알고리즘은 모든 변수들의 생명 주기를 분석 한 후, 최소의 레지스터들을 결정한다. 또한 기능 단위의 입력 신호의 특성에 따라 모든 제어 스텝을 하나씩 차례로 방문하고, 갈망 방법에 따라 각 제어 스텝의 소비 전력을 최소화하여 자원 할당을 수행한다. 제안된 저 전력설계 자동화를 위한 최소 자원 상위 레벨 합성 알고리즘은 다양한 벤치마크들의 예를 통해 효율성을 입증한다.

This paper proposes a new minimal resource high-level synthesis algorithm for low power design automation. The proposed algorithm executes an efficient approach to minimize the power consumption of the functional units in a circuit during the high level synthesis. In this paper, we visit all control steps one by one to reduce the switching activity in CDFG. The register sharing algorithm determines the minimum register after the life time analysis of all variable. According to property of input signal for functional unit, the proposed method visits all control step one by one and determines the resource allocation with minimal power consumption at each control step in a greedy fashion. The effect of the proposed algorithm has been proved through various filter benchmark to adopt a new scheduling and allocation algorithm considering the low rover.

본 연구는 정신장애인의 신체적, 심리적, 사회ㆍ환경적 상황을 종합적으로 평가하여 그에 적합한 서비스를 제공하기 위한 욕구 중심의 사정도구를 개발하고, 개발된 도구를 활용하여 정신장애인 379명의 사정 데이터를 수집한후 데이터마이닝의 의사결정 나무분석 기법을 활용하여 욕구에 적합한 서비스제공을 위한 욕구추출 알고리즘을 구성하였다. 연구기간은 2007년 3월부터 2009년 3월까지 약 2년에 걸쳐 이루어졌으며, 크게 사정도구 개발과 개발된 도구를 활용한 욕구추출 과정으로 나뉠 수 있다. 도구개발은 문헌고찰을 통하여 기본적인 틀을 구성하였고, 포커스 집단과 전문가들을 통하여 사정도구의 주관적 호소와 욕구 문항을 개발하였으며, 도구의 타당도를 확인하기 위해 통계적인 검증과정을 거쳤다. 검증결과 본 도구의 내적 신뢰도의 평균은 .805이었고 이 도구를 활용하여 정신장애인 사례관리의 욕구추출 알고리즘을 제시하였다. 본 연구의 결과로 제시한 사정도구와 알고리즘은 정신장애인의 객관적 욕구를 사정하고 확인함으로써 체계적인 사례관리를 수행하는 자료로 활용될 수 있다.

The study aims to develop a assessment tool to develop an assessment tool to provide the sufferers of mental disorders in local communities with appropriate services with consideration for physical, emotional, social and environmental circumstances. After collection of assesment data of 379 mental disorders through use of the tool, an algorithm to determine needs was developed to provide a service to real needs through the use of decision tree analysis on data mining. The study was conducted for two years from March 2007 through March 2009, and it is divided into development of an assessment tool and extraction of real needs through the use of the tool. The basic framework of the development of the tool was established through the examination of related literature, while the subjective satisfaction of the assessment tool and items were developed through the use of a focus group and experts. Finally, verification was implemented through the use of statistics to confirm the validity of the tool. As a result of the verification, the tool secured following reliability α = .805. In addition to this, a real needs-extraction algorithm was established through the use of the assessment tool, and the an algorithm according to each desire was suggested. The assessment tool and algorithm suggested as a result of the study can be used as data to conduct systematic management of examples through the confirmation of the objective needs of each mental disorder.

The purpose of this study is to analyze fractal geometry and to apply modeling-principal, form-organization in archiecture design. There are self-similarity, random, irregularity, unpredictable in fractal geometry that can be applied to architectural design analysis and modeling-principal. And there are scaling, superimposition, and repetition in the fractal formative elements that can be applied to design concept and process in architecture. Form-organization algorithm is composed of, form-originator, form-creater, and Form-organization algorithm, three steps. This study shows fractal geometry can be reflected on the architectural action and logical process.

본 논문은 윷놀이를 활용한 SW융합교육이 초등학생의 지식정보처리역량에 미치는 효과를 분석하고자 하였 다. 전라남도 도서지역 초등학생을 대상으로 연구를 실시하였다. 윷놀이를 활용한 SW융합교육 수업을 개발하여 실험집단에 적용하여 보았다. 지식정보처리역량 사전검사를 실시하고 윷놀이를 활용한 SW융합교육을 진행한 후 지식정보처리역량 사후검사를 실시하였다. 지식정보처리역량 검사도구로는 초등학교 고학년 지식정보처리역량 측정도구를 사용하여 분석하였다. 분석한 결과에 따르면 윷놀이를 활용한 SW융합교육이 초등학생이 학습상황 속에서 문제를 해결하기 위하여 지식정보와 자료를 수집하고 분석하여 평가, 선택한 지식과 정보를 활용하여 효 율적으로 문제를 해결할 수 있는 능력인 지식정보처리역량 향상에 효과적인 것으로 나타났다.

This paper aimed to analyze the effect of SW convergence education applying Yut-nori on the knowledge information processing ability of elementary school students. A study was conducted targeting elementary school students in the islands of Jeollanam-do. A SW convergence education applying Yut-nori was developed and applied to the experimental group. A pre-test for knowledge and information processing competency was conducted, SW convergence education applying Yut-nori was conducted, and a post-test for knowledge and information processing competency was conducted. As a knowledge information processing capability test tool, the upper elementary school knowledge information processing competency measurement tool was used for analysis. According to the analysis, SW convergence education using Yut-nori is effective in improving knowledge and information processing competency, which is the ability of elementary school students to collect, analyze, evaluate, and use selected knowledge and information to solve problems efficiently. It was found to be effective in improving knowledge and information processing competency.

본 연구는 4차 산업 대응 옴니채널 유통 환경 속에서, 중소기업 대상의 범용 솔루션 라스트마일 딜리버리 시스템 을 개발 구축함으로서 중소기업에 배송효율 극대화 및 운송 서비스 향상으로 물류경쟁력 강화를 달성할 수 있는 클라우드 기반 사용료 방식의 초기투자비용 및 운영비를 절감할 수 있도록 하여 중소기업이 쉽게 접근 가능한 범용 솔루션 개발 및 구축하여 활용하고 배포되어 범용화를 실현하는 것이 그 목적이다. 라스트마일 딜리버리 시스템을 구축한 중소기업은 시뮬레이션을 통한 운영전략 수립, 물량변동에 대응하여 효율적인 노선 운영이 가능하고 배차계 획 수립 소요시간이 단축되며 최적화된 배송 경로를 통한 고객 만족 및 브랜드 이미지 제고를 통해 고객 서비스에서 도 우위를 선점할 수 있다. 본 연구의 라스트마일 딜리버리 시스템이 구축되고 범용화를 실현한다면 적은 비용으로 중소기업들의 배송 경쟁력을 강화시키고 고객들의 니즈에 맞는 서비스를 제공할 수 있어 물류와 유통 산업의 전반적 인 성장의 기여가 기대되어진다.

In this research, we developed and built a universal solution last mile delivery system for small and medium sized enterprises in the quaternary omni-channel distribution environment. The objective is to develop, utilize, and even distribute and generalize general-purpose solutions that small and medium sized enterprises can easily access by reducing initial investment and operating costs. Small and medium sized enterprises that have built a last delivery system can efficiently operate routes in response to simulation and volume changes, reduce the time required for dispatching plans, and improve customer satisfaction and brand image through optimized delivery routes. You can dominate the service. By setting up regional areas, centralizing capacity management, and by realizing integrated dispatch of orders from other customers, the customer order acceptance rate can be improved. By using optimal transportation plans, you can increase the satisfaction of the courier, efficiently operate the vehicle, and reduce fuel costs by reducing the mileage. Even if stores and centers and added, it is easy to expand and apply, improving the logistics operation efficiency.

이 연구는 미국 경찰의 빅 데이터 경찰활동 도입・운영 현황을 분석하여, 한국 경찰 의 추진현황과 비교한 후 정책적 함의를 끌어내고자 함에 그 목적이 있다. 미국에서는 주 혹은 대도시 경찰기관 위주로 예측적 경찰활동과 실시간 감시 체계를 운영하고 있다. 이러한 빅 데이터 경찰활동을 추진하는 데에는 기술 발전, 경찰권 남용 제한 및 테러에 대한 우려라는 사회적 목소리가 그 배경이 되고 있다. 추진동력은 연방정부의 리드가 큰 요소이고, 실제적인 도입은 경찰・학계・기업이 협업하여 분업적인 참여를 통해 이루어 지고 있다. 한국 경찰도 빅 데이터 경찰활동을 위해 전략적 접근을 시도하고 있으며, 기능별로 수요에 맞는 빅 데이터 분석이 실시되고 있다. 비교경찰학적 측면에서 볼 때, 빅 데이터 분석 형태가 미국 경찰은 장소기반형, 사람기반형, 실시간 감시형으로 다양하고 이루어지고 있으나, 한국 경찰은 장소기반형 중심으로 이루어지고 있다. 또한, 활용 분 야에서 미국은 가해자 및 범행 장소를 예측하는데 초점을 맞추는 반면, 한국 경찰은 피 의자 특정 및 수사 분야에서 주로 활용되고 있다. 빅 데이터 경찰활동이 미국과 같이 현 장에까지 도입이 될 경우 알고리즘과 데이터의 소유권 분쟁, 법집행현장에서 판단근거 로 활용 가능성, 의사결정에 대한 책임소재와 같은 법적 쟁점이 예상된다.

The purpose of this study was to analyze the introduction and operation of big data policing by some US police forces, and to compare them with the progress by the Korean police. In the US, predictive policing and real-time surveillance are run by state or city police agencies. Technological advancement, restriction on power abuse by police, and fear of terrorism were the background for promoting such big data policing activities. The federal government led the initiative and the actual introduction was made via the cooperation among police, academia, and corporations. The Korean police was attempting a strategic approach to big data policing activities, and some big data analyses were being conducted to meet the demands by subordinate functions. In terms of comparative policing, analytic forms of big data, in the US, were diversified into place-based, people-based, and real-time surveillance approaches, while the Korean police primarily took the place-based approach. In addition, the US focused on predicting perpetrators and criminogenic places, while the Korean police mainly used the big data analysis for investigative purposes. If big data policing is introduced in Korea like the US, legal issues such as algorithmic and data ownership disputes, the possibility of using algorithmic results as judgment grounds by field officers, and the responsibility for decision making are expected.

소프트웨어 교육과 관련된 교육과정이나 운영지침에 포함된 Computational Thinking(CT)의 개념과 구성 요 소가 서로 달라서 학교 현장에서 CT를 기반으로 한 소프트웨어 교육을 정착시키는 데 어려움을 겪고 있다. 따 라서 본 연구에서는 전문가 델파이 조사 결과를 토대로, CT에 대한 용어를 ‘컴퓨팅 사고력’으로 통일하였고, CT 의 구성 요소를 문제 정의, 자료 분석, 추상화, 자동화, 일반화 등 5가지로 구분하였다. 또한, 한국정보교육학회에 서 개발한 정보과 교육과정 표준 모델에서 컴퓨팅 사고력과 관련성이 높은 소프트웨어 영역을 선정하여, 하위 영역별 성취 기준과 관련성이 높은 컴퓨팅 사고력이 무엇인지를 조사하여 제시하였다.

Because the concepts and components of computational thinking included in the Information Education Curriculum and the Software Education Guidelines are different, it has been difficult to establish computational thinking-based software education in schools. Therefore, this study, which is based on the Delphi survey results from 39 experts, we defined computational thinking as 'computing thinking' and separated the components of computational thinking into five main categories: (1) problem definition, (2) data analysis, (3) abstraction, (4) automation, and (5) generalization. In addition, we selected software areas that are strongly related to computational thinking in the KAIE's information Curriculum Standard Model and surveyed experts to decide which computing thinking components are related to the achievement criteria of the software areas.