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A Combat Effectiveness Evaluation Algorithm Considering Technical and Human Factors in C4I System (NCW 환경에서 C4I 체계 전투력 상승효과 평가 알고리즘 : 기술 및 인적 요소 고려)

  • Jung, Whan-Sik;Park, Gun-Woo;Lee, Jae-Yeong;Lee, Sang-Hoon
    • Journal of Intelligence and Information Systems
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    • v.16 no.2
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    • pp.55-72
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    • 2010
  • Recently, the battlefield environment has changed from platform-centric warfare(PCW) which focuses on maneuvering forces into network-centric warfare(NCW) which is based on the connectivity of each asset through the warfare information system as information technology increases. In particular, C4I(Command, Control, Communication, Computer and Intelligence) system can be an important factor in achieving NCW. It is generally used to provide direction across distributed forces and status feedback from thoseforces. It can provide the important information, more quickly and in the correct format to the friendly units. And it can achieve the information superiority through SA(Situational Awareness). Most of the advanced countries have been developed and already applied these systems in military operations. Therefore, ROK forces also have been developing C4I systems such as KJCCS(Korea Joint Command Control System). And, ours are increasing the budgets in the establishment of warfare information systems. However, it is difficult to evaluate the C4I effectiveness properly by deficiency of methods. We need to develop a new combat effectiveness evaluation method that is suitable for NCW. Existing evaluation methods lay disproportionate emphasis on technical factors with leaving something to be desired in human factors. Therefore, it is necessary to consider technical and human factors to evaluate combat effectiveness. In this study, we proposed a new Combat Effectiveness evaluation algorithm called E-TechMan(A Combat Effectiveness Evaluation Algorithm Considering Technical and Human Factors in C4I System). This algorithm uses the rule of Newton's second law($F=(m{\Delta}{\upsilon})/{\Delta}t{\Rightarrow}\frac{V{\upsilon}I}{T}{\times}C$). Five factors considered in combat effectiveness evaluation are network power(M), movement velocity(v), information accuracy(I), command and control time(T) and collaboration level(C). Previous researches did not consider the value of the node and arc in evaluating the network power after the C4I system has been established. In addition, collaboration level which could be a major factor in combat effectiveness was not considered. E-TechMan algorithm is applied to JFOS-K(Joint Fire Operating System-Korea) system that can connect KJCCS of Korea armed forces with JADOCS(Joint Automated Deep Operations Coordination System) of U.S. armed forces and achieve sensor to shooter system in real time in JCS(Joint Chiefs of Staff) level. We compared the result of evaluation of Combat Effectiveness by E-TechMan with those by other algorithms(e.g., C2 Theory, Newton's second Law). We can evaluate combat effectiveness more effectively and substantially by E-TechMan algorithm. This study is meaningful because we improved the description level of reality in calculation of combat effectiveness in C4I system. Part 2 will describe the changes of war paradigm and the previous combat effectiveness evaluation methods such as C2 theory while Part 3 will explain E-TechMan algorithm specifically. Part 4 will present the application to JFOS-K and analyze the result with other algorithms. Part 5 is the conclusions provided in the final part.

A Study on the Blood-Letting Therapy in Elementary Questions (("황제내경소문(黃帝內經素問)" 중(中) 사혈(瀉血)에 관한 연구(硏究))

  • Lee, Jun-Geun
    • Journal of the Korean Institute of Oriental Medical Informatics
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    • v.14 no.1
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    • pp.19-42
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    • 2008
  • Blood-Letting Therapy is a rational and ecological medical treatment by which we can heal most of the diseases by removing the static blood which precipitates in the blood vessel and blocks the flowing of blood. And the static blood is the generic term for the injurious, bad, dead and precipitated blood which is blocked the capillary vessel. The Yellow Emperor's Canon of Internal Medicine says that "the patient is treated with drugs internally and stone acupuncture externally. "In the old texts, the blood-letting therapy is mentioned as blood-letting, network vessel pricking, bloodletting, pricking, and arousing pulses etc and it is noted down as the method of network vessel pricking in 'On the Application of Needles' of Spiritual Pivot. Nine-pricking therapy, twelve-pricking therapy and five-pricking therapy are recorded in the methods of network vessel pricking and among them, the method of squeezing blood after pricking the affected part is explained as the network vessel pricking. There are four methods of network vessel pricking, pricking, picking, cluster needling and scatter-pricking and they are fluidly applied to the various symptoms of diseases. In 'On Discriminative Treating for Patients of Different Regions' in Elementary Questions, Ki-baek emphasizes "most of the local people, there are black in skin and loose in striate, and their diseases are mostly of carbuncle kind. It is suitable to treat the disease with stone therapy to prick with stone, so the stone therapy is transmitted from the east. "And in 'On the Corresponding Relation Between the Eum and Yang of Man and All Things' in Elementary Questions, when the Emperor asked Ki-Back, he answered "sthenia means the sthenia of evil, and deficiency means the deficiency of healthy energy. When the blood is sthenic, the evil should be discharged by pricking when out letting the blood; deficiency of vital energy is the asthenia of channels and network vessels, so the energy should drain from the channel which is not deficient, to replenish. "And in this case we can use the methods of 'Breaking out the static bloods', 'driving out the static bloods', blood-letting'. With this we can infer that the blood-letting therapy is made use of the important medical treatments from the ancient times. Especially in referring to the principles of treatment in The Yellow Emperor's Canon of Internal Medicine, it mostly alluded to acupuncture therapies and only eleven times to medicinal treatments. This is to verify that the blood-letting therapy formed the foundation of the medical art. In Dong's Therapy of Acupuncture-Moxibustion and Bloodletting, Dong Kyeong-Chang gave emphasis on the points that there must be extravasated bloods without exception in the serious illnesses which is old, unnatural, accompanying acute pains and so we can revive our body‘s sprit by circulating 'gi' and static blood piled up in the network vessel, regulating the weakness and strength, and controling the disharmony of the internal organs. The blood-letting therapy has effect on the orifice in emergency, such as fore draining, freeing network vessels, harmonizing gi and blood, relieving pain, dispersing swelling and concretion, sedation, resolving toxin as well as strengthening the heart, relieving itching. So it has distinguished effect on all kinds of medical treatment to the modern people. But by the change of social customs and the confucianism of confucius - it is widely spread on the period of North and South Dynasties, 'Wi' and 'Jin' in china and the period of the Three States in korea - The blood-letting therapy which was regarded as the most important medicinal treatment withered rapidly. And Confucius accentuated the importance of our body and all its members, loyalty and filial piety and banned any damage of our body under no circumstances. As a result of it, the therapy of blood-letting had a rapid decrease and barely kept itself in existence in both countries. What is worse, at the period of Japanese colonial rule of korea and our nation's founding of early stage, it has been withered by the high-handed policy to change Oriental Medicine into modern medical science. So the therapy of blood-letting barely kept itself in existence in some Buddhist temples. Another case, it has handed down as a old-fashioned quick fix in folk remedies. But all kinds of the contamination of heavy metals and the misuses of antibiotics are widely spread nowadays, which increased diseases of adult people and incurable diseases as modern society unavoidably made its way into a highly industrial society. To make us more miserable, the western medical science - the antibiotics and surgical operation medical science - already reveals itself into a limit. The necessity of a new medical science which can give a security to the patients who are suffering from the diseases of adult people and the incurable diseases is especially come into the force nowadays. In view of the results after bibliographically studying on the blood-letting Therapy in Elementary Questions of the Yellow Emperor's Canon of Internal Medicine, the blood-letting therapy has acted for the important Oriental medicinal science and has been clarified the prominent effects on the diseases of adult people and the incurable diseases. So it is regarded as an appropriate thing that we lay out a determined theory of the blood-letting therapy and of course prevent the unwanted side effects from inappropriate medicinal treatments, and make full use of clinic by elevating the curative value and that we win back our self-respect of medical treatment which is dominated from the western medical science and ultimately contribute to national medical welfare.

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Development and Application of Scientific Model Co-construction Program about Image Formation by Convex Lens (볼록렌즈가 상을 만드는 원리에 대한 과학적 모형의 사회적 구성 프로그램 개발 및 적용)

  • Park, Jeongwoo
    • Korean Journal of Optics and Photonics
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    • v.28 no.5
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    • pp.203-212
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    • 2017
  • A scientific model refers to a conceptual system that can describe, explain, and predict a particular physical phenomenon. The co-construction of the scientific model is attracting attention as a new teaching and learning strategy in the field of science education and various studies. The evaluation and modification of models compared with the predicted models of data from the real world is the core of modeling strategy. However, there were only a limited data provided by the teacher in many studies of modeling comparing the students' predictions of their own models. Most of the students were not given the opportunity to evaluate the suitability of the model with the data in the real world. The purpose of this study was to develop a scientific model co-construction program that can evaluate the model by directly comparing the predicted models with the observed data from the real world. Through a collaborative discussion between teachers and researchers for 6 months, a 5-session scientific model co-construction program on the subject 'image formation by convex lenses' for second grade middle school students was developed. Eighty (80) students in 3 classes and a science teacher with 20 years of service from general public co-educational middle school in Gyeonggi-do participated in this 2-week program. After the class, students were asked about the helpfulness and difficulty of the class, and whether they would like to recommend this class to a friend. After the class, 95.8% of the students constructed the scientific model more than the model using the construction rule. Students had difficulties to identify principles or understand their friends, but the result showed that they could understand through model evaluation experiment. 92.5% of the students said that they would be more than willing to recommend this program to their friends. It is expected that the developed program will be applied to the school and contribute to the improvement of students' modeling ability and co-construction ability.

Clustering Method based on Genre Interest for Cold-Start Problem in Movie Recommendation (영화 추천 시스템의 초기 사용자 문제를 위한 장르 선호 기반의 클러스터링 기법)

  • You, Tithrottanak;Rosli, Ahmad Nurzid;Ha, Inay;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.19 no.1
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    • pp.57-77
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    • 2013
  • Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.