• Title/Summary/Keyword: Memory Problem

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A Proposal for Archives securing Community Memory The Achievements and Limitations of GPH Archives (공동체의 기억을 담는 아카이브를 지향하며 20세기민중생활사연구단 아카이브의 성과와 과제)

  • Kim, Joo-Kwan
    • The Korean Journal of Archival Studies
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    • no.33
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    • pp.85-112
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    • 2012
  • Group for the People without History(GPH) was launched at September 2002 and had worked for around five years with the following purposes; Firstly, GPH collects first-hand data on people's everyday lives based on fieldworks. Secondly, GPH constructs digital archives of the collected data. Thirdly, GPH guarantees the accessibility to the archives for people. And lastly, GPH promotes users to utilize the archived data for the various levels. GPH has influenced on the construction of archives on everyday life history as well as the research areas such as anthropology and social history. What is important is that GPH tried to construct digital archives even before the awareness on archives was not widely spreaded in Korea other than formal sectors. Furthermore, the GPH archives proposed a model of open archives which encouraged the people's participation in and utilization of the archives. GPH also showed the ways in which archived data were used. It had published forty seven books of people's life histories and five photographic books, and held six photographic exhibitions on the basis of the archived data. Though GPH archives had contributed to the ignition of the discussions on archives in various areas as leading civilian archives, it has a few limitations. The most important problem is that the data are vanishing too fast for researchers to collect. It is impossible for researchers to collect the whole data. Secondly, the physical space and hardware for the data storage should be ensured. One of the alternatives to solve the problems revealed in the works of GPH is to construct community archives. Community archives are decentralized archives run by people themselves to preserve their own voices and history. It will guarantee the democratization of archives.

A Comparison of the Metanarrative and East Timor's Local Narrative in Indonesia under the Suharto's Regime (인도네시아의 메타내러티브와 동티모르의 로칼내러티브의 서술구조 비교)

  • Song, Seung-Won
    • Journal of International Area Studies (JIAS)
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    • v.15 no.1
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    • pp.155-180
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    • 2011
  • This paper aims at comparing the metanarrative and East Timor's local narrative in Indonesia during the Suharto's regime. Although these history writings have different political goals, the patterns of writings are ironically similar. Both of the history writings show strong nationalistic history writing patterns. Yet, in the writings, these histories place different interpretations on the historical events. In the metanarrative, local dynamics are seen through the diagrams of the nation and nationhood. This narrative finds the roots of the "ethnie" from some kingdoms in Java and Sumatra. These kingdoms, which throve based on the Hindu-Buddhist culture, achieved a territorial unity to a degree, covering some parts of Java and Sumatra. The glorious past disappeared with the advent of the colonial rule. The metanarrative then emphasizes the unity of the ethnic groups in the archipelago, which fiercely resisted against the colonial exploitation and oppression. By this, these ethnic groups were defined as "the masses," the collective identity, which had a same goal to achieve the national independence. In addition, some local histories, which took positive attitudes toward the European forces, were simply left out from the metanarrative. All the separatist movements taking place in the republic were also described as the anti-unifying forces. On the other hand, the goal of the history-writing in East Timor was to enhance the sense of nationalism and create the perception of the "East Timorese." The fundamental aim was the separation from Indonesia. In the narrative, the nationalist politicians overcame the problem of the non-existence of any memories of the glorious past with the awakening of the idea of "the imagined gloriousness of the past if there was no colonial rule." In addition, the narrative overemphasizes the memory of the colonial rule for 450 years under the Portuguese rule in order to stress the fact that it was the colony of Portugal, not of the Netherlands. Finally, the narrative shows how the East Timorese collectively fell to the status of slaves. By this, the political leaders of East Timor evoked the notion that it was recolonized by Indonesia, under which the East Timorese were demoted to the status of slaves. This notion of "slave-master" relationship then became the motives for the independence struggles in East Timor.

The Effect of Consumers' Value Motives on the Perception of Blog Reviews Credibility: the Moderation Effect of Tie Strength (소비자의 가치 추구 동인이 블로그 리뷰의 신뢰성 지각에 미치는 영향: 유대강도에 따른 조절효과를 중심으로)

  • Chu, Wujin;Roh, Min Jung
    • Asia Marketing Journal
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    • v.13 no.4
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    • pp.159-189
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    • 2012
  • What attracts consumers to bloggers' reviews? Consumers would be attracted both by the Bloggers' expertise (i.e., knowledge and experience) and by his/her unbiased manner of delivering information. Expertise and trustworthiness are both virtues of information sources, particularly when there is uncertainty in decision-making. Noting this point, we postulate that consumers' motives determine the relative weights they place on expertise and trustworthiness. In addition, our hypotheses assume that tie strength moderates consumers' expectation on bloggers' expertise and trustworthiness: with expectation on expertise enhanced for power-blog user-group (weak-ties), and an expectation on trustworthiness elevated for personal-blog user-group (strong-ties). Finally, we theorize that the effect of credibility on willingness to accept a review is moderated by tie strength; the predictive power of credibility is more prominent for the personal-blog user-groups than for the power-blog user groups. To support these assumptions, we conducted a field survey with blog users, collecting retrospective self-report data. The "gourmet shop" was chosen as a target product category, and obtained data analyzed by structural equations modeling. Findings from these data provide empirical support for our theoretical predictions. First, we found that the purposive motive aimed at satisfying instrumental information needs increases reliance on bloggers' expertise, but interpersonal connectivity value for alleviating loneliness elevates reliance on bloggers' trustworthiness. Second, expertise-based credibility is more prominent for power-blog user-groups than for personal-blog user-groups. While strong ties attract consumers with trustworthiness based on close emotional bonds, weak ties gain consumers' attention with new, non-redundant information (Levin & Cross, 2004). Thus, when the existing knowledge system, used in strong ties, does not work as smoothly for addressing an impending problem, the weak-tie source can be utilized as a handy reference. Thus, we can anticipate that power bloggers secure credibility by virtue of their expertise while personal bloggers trade off on their trustworthiness. Our analysis demonstrates that power bloggers appeal more strongly to consumers than do personal bloggers in the area of expertise-based credibility. Finally, the effect of review credibility on willingness to accept a review is higher for the personal-blog user-group than for the power-blog user-group. Actually, the inference that review credibility is a potent predictor of assessing willingness to accept a review is grounded on the analogy that attitude is an effective indicator of purchase intention. However, if memory about established attitudes is blocked, the predictive power of attitude on purchase intention is considerably diminished. Likewise, the effect of credibility on willingness to accept a review can be affected by certain moderators. Inspired by this analogy, we introduced tie strength as a possible moderator and demonstrated that tie strength moderated the effect of credibility on willingness to accept a review. Previously, Levin and Cross (2004) showed that credibility mediates strong-ties through receipt of knowledge, but this credibility mediation is not observed for weak-ties, where a direct path to it is activated. Thus, the predictive power of credibility on behavioral intention - that is, willingness to accept a review - is expected to be higher for strong-ties.

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A STUDY ON THE TEMPERATURE CHANGES OF BONE TISSUES DURING IMPLANT SITE PREPARATION (임플랜트 식립부위 형성시 골조직의 온도변화에 관한 연구)

  • Kim Pyung-Il;Kim Yung-Soo;Jang Kyung-Soo;Kim Chang-Whe
    • The Journal of Korean Academy of Prosthodontics
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    • v.40 no.1
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    • pp.1-17
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    • 2002
  • The purpose of this study is to examine the possibility of thermal injury to bone tissues during an implant site preparation under the same condition as a typical clinical practice of $Br{\aa}nemark$ implant system. All the burs for $Br{\aa}nemark$ implant system were studied except the round bur The experiments involved 880 drilling cases : 50 cases for each of the 5 steps of NP, 5 steps of RP, and 7 steps of WP, all including srew tap, and 30 cases of 2mm twist drill. For precision drilling, a precision handpiece restraining system was developed (Eungyong Machinery Co., Korea). The system kept the drill parallel to the drilling path and allowed horizontal adjustment of the drill with as little as $1{\mu}m$ increment. The thermocouple insertion hole. that is 0.9mm in diameter and 8mm in depth, was prepared 0.2mm away from the tapping bur the last drilling step. The temperatures due to countersink, pilot drill, and other drills were measured at the surface of the bone, at the depths of 4mm and 8mm respectively. Countersink drilling temperature was measured by attaching the tip of a thermocouple at the rim of the countersink. To assure temperature measurement at the desired depths, 'bent-thermocouples' with their tips of 4 and 8mm bent at $120^{\circ}$ were used. The profiles of temperature variation were recorded continuously at one second interval using a thermometer with memory function (Fluke Co. U.S.A.) and 0.7mm thermocouples (Omega Co., U.S.A.). To simulate typical clinical conditions, 35mm square samples of bovine scapular bone were utilized. The samples were approximately 20mm thick with the cortical thickness on the drilling side ranging from 1 to 2mm. A sample was placed in a container of saline solution so that its lower half is submerged into the solution and the upper half exposed to the room air, which averaged $24.9^{\circ}C$. The temperature of the saline solution was maintained at $36.5^{\circ}C$ using an electric heater (J. O Tech Co., Korea). This experimental condition was similar to that of a patient s opened mouth. The study revealed that a 2mm twist drill required greatest attention. As a guide drill, a twist drill is required to bore through a 'virgin bone,' rather than merely enlarging an already drilled hole as is the case with other drills. This typically generates greater amount of heat. Furthermore, one tends to apply a greater pressure to overcome drilling difficulty, thus producing even greater amount heat. 150 experiments were conducted for 2mm twist drill. For 140 cases, drill pressure of 750g was sufficient, and 10 cases required additional 500 or 100g of drilling pressure. In case of the former. 3 of the 140 cases produced the temperature greater than $47^{\circ}C$, the threshold temperature of degeneration of bone tissue (1983. Eriksson et al.) which is also the reference temperature in this study. In each of the 10 cases requiring extra pressure, the temperature exceeded the reference temperature. More significantly, a surge of heat was observed in each of these cases This observations led to addtional 20 drilling experiments on dense bones. For 10 of these cases, the pressure of 1,250g was applied. For the other 10, 1.750g were applied. In each of these cases, it was also observed that the temperature rose abruptly far above the thresh old temperature of $47^{\circ}C$, sometimes even to 70 or $80^{\circ}C$. It was also observed that the increased drilling pressure influenced the shortening of drilling time more than the rise of drilling temperature. This suggests the desirability of clinically reconsidering application of extra pressures to prevent possible injury to bone tissues. An analysis of these two extra pressure groups of 1,250g and 1,750g revealed that the t-statistics for reduced amount of drilling time due to extra pressure and increased peak temperature due to the same were 10.80 and 2.08 respectively suggesting that drilling time was more influenced than temperature. All the subsequent drillings after the drilling with a 2mm twist drill did not produce excessive heat, i.e. the heat generation is at the same or below the body temperature level. Some of screw tap, pilot, and countersink showed negative correlation coefficients between the generated heat and the drilling time. indicating the more the drilling time, the lower the temperature. The study also revealed that the drilling time was increased as a function of frequency of the use of the drill. Under the drilling pressure of 750g, it was revealed that the drilling time for an old twist drill that has already drilled 40 times was 4.5 times longer than a new drill The measurement was taken for the first 10 drillings of a new drill and 10 drillings of an old drill that has already been used for 40 drillings. 'Test Statistics' of small samples t-test was 3.49, confirming that the used twist drills require longer drilling time than new ones. On the other hand, it was revealed that there was no significant difference in drilling temperature between the new drill and the old twist drill. Finally, the following conclusions were reached from this study : 1 Used drilling bur causes almost no change in drilling temperature but increase in drilling time through 50 drillings under the manufacturer-recommended cooling conditions and the drilling pressure of 750g. 2. The heat that is generated through drilling mattered only in the case of 2mm twist drills, the first drill to be used in bone drilling process for all the other drills there is no significant problem. 3. If the drilling pressure is increased when a 2mm twist drill reaches a dense bone, the temperature rises abruptly even under the manufacturer-recommended cooling conditions. 4. Drilling heat was the highest at the final moment of the drilling process.

Performance analysis of Frequent Itemset Mining Technique based on Transaction Weight Constraints (트랜잭션 가중치 기반의 빈발 아이템셋 마이닝 기법의 성능분석)

  • Yun, Unil;Pyun, Gwangbum
    • Journal of Internet Computing and Services
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    • v.16 no.1
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    • pp.67-74
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    • 2015
  • In recent years, frequent itemset mining for considering the importance of each item has been intensively studied as one of important issues in the data mining field. According to strategies utilizing the item importance, itemset mining approaches for discovering itemsets based on the item importance are classified as follows: weighted frequent itemset mining, frequent itemset mining using transactional weights, and utility itemset mining. In this paper, we perform empirical analysis with respect to frequent itemset mining algorithms based on transactional weights. The mining algorithms compute transactional weights by utilizing the weight for each item in large databases. In addition, these algorithms discover weighted frequent itemsets on the basis of the item frequency and weight of each transaction. Consequently, we can see the importance of a certain transaction through the database analysis because the weight for the transaction has higher value if it contains many items with high values. We not only analyze the advantages and disadvantages but also compare the performance of the most famous algorithms in the frequent itemset mining field based on the transactional weights. As a representative of the frequent itemset mining using transactional weights, WIS introduces the concept and strategies of transactional weights. In addition, there are various other state-of-the-art algorithms, WIT-FWIs, WIT-FWIs-MODIFY, and WIT-FWIs-DIFF, for extracting itemsets with the weight information. To efficiently conduct processes for mining weighted frequent itemsets, three algorithms use the special Lattice-like data structure, called WIT-tree. The algorithms do not need to an additional database scanning operation after the construction of WIT-tree is finished since each node of WIT-tree has item information such as item and transaction IDs. In particular, the traditional algorithms conduct a number of database scanning operations to mine weighted itemsets, whereas the algorithms based on WIT-tree solve the overhead problem that can occur in the mining processes by reading databases only one time. Additionally, the algorithms use the technique for generating each new itemset of length N+1 on the basis of two different itemsets of length N. To discover new weighted itemsets, WIT-FWIs performs the itemset combination processes by using the information of transactions that contain all the itemsets. WIT-FWIs-MODIFY has a unique feature decreasing operations for calculating the frequency of the new itemset. WIT-FWIs-DIFF utilizes a technique using the difference of two itemsets. To compare and analyze the performance of the algorithms in various environments, we use real datasets of two types (i.e., dense and sparse) in terms of the runtime and maximum memory usage. Moreover, a scalability test is conducted to evaluate the stability for each algorithm when the size of a database is changed. As a result, WIT-FWIs and WIT-FWIs-MODIFY show the best performance in the dense dataset, and in sparse dataset, WIT-FWI-DIFF has mining efficiency better than the other algorithms. Compared to the algorithms using WIT-tree, WIS based on the Apriori technique has the worst efficiency because it requires a large number of computations more than the others on average.

KNU Korean Sentiment Lexicon: Bi-LSTM-based Method for Building a Korean Sentiment Lexicon (Bi-LSTM 기반의 한국어 감성사전 구축 방안)

  • Park, Sang-Min;Na, Chul-Won;Choi, Min-Seong;Lee, Da-Hee;On, Byung-Won
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.219-240
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    • 2018
  • Sentiment analysis, which is one of the text mining techniques, is a method for extracting subjective content embedded in text documents. Recently, the sentiment analysis methods have been widely used in many fields. As good examples, data-driven surveys are based on analyzing the subjectivity of text data posted by users and market researches are conducted by analyzing users' review posts to quantify users' reputation on a target product. The basic method of sentiment analysis is to use sentiment dictionary (or lexicon), a list of sentiment vocabularies with positive, neutral, or negative semantics. In general, the meaning of many sentiment words is likely to be different across domains. For example, a sentiment word, 'sad' indicates negative meaning in many fields but a movie. In order to perform accurate sentiment analysis, we need to build the sentiment dictionary for a given domain. However, such a method of building the sentiment lexicon is time-consuming and various sentiment vocabularies are not included without the use of general-purpose sentiment lexicon. In order to address this problem, several studies have been carried out to construct the sentiment lexicon suitable for a specific domain based on 'OPEN HANGUL' and 'SentiWordNet', which are general-purpose sentiment lexicons. However, OPEN HANGUL is no longer being serviced and SentiWordNet does not work well because of language difference in the process of converting Korean word into English word. There are restrictions on the use of such general-purpose sentiment lexicons as seed data for building the sentiment lexicon for a specific domain. In this article, we construct 'KNU Korean Sentiment Lexicon (KNU-KSL)', a new general-purpose Korean sentiment dictionary that is more advanced than existing general-purpose lexicons. The proposed dictionary, which is a list of domain-independent sentiment words such as 'thank you', 'worthy', and 'impressed', is built to quickly construct the sentiment dictionary for a target domain. Especially, it constructs sentiment vocabularies by analyzing the glosses contained in Standard Korean Language Dictionary (SKLD) by the following procedures: First, we propose a sentiment classification model based on Bidirectional Long Short-Term Memory (Bi-LSTM). Second, the proposed deep learning model automatically classifies each of glosses to either positive or negative meaning. Third, positive words and phrases are extracted from the glosses classified as positive meaning, while negative words and phrases are extracted from the glosses classified as negative meaning. Our experimental results show that the average accuracy of the proposed sentiment classification model is up to 89.45%. In addition, the sentiment dictionary is more extended using various external sources including SentiWordNet, SenticNet, Emotional Verbs, and Sentiment Lexicon 0603. Furthermore, we add sentiment information about frequently used coined words and emoticons that are used mainly on the Web. The KNU-KSL contains a total of 14,843 sentiment vocabularies, each of which is one of 1-grams, 2-grams, phrases, and sentence patterns. Unlike existing sentiment dictionaries, it is composed of words that are not affected by particular domains. The recent trend on sentiment analysis is to use deep learning technique without sentiment dictionaries. The importance of developing sentiment dictionaries is declined gradually. However, one of recent studies shows that the words in the sentiment dictionary can be used as features of deep learning models, resulting in the sentiment analysis performed with higher accuracy (Teng, Z., 2016). This result indicates that the sentiment dictionary is used not only for sentiment analysis but also as features of deep learning models for improving accuracy. The proposed dictionary can be used as a basic data for constructing the sentiment lexicon of a particular domain and as features of deep learning models. It is also useful to automatically and quickly build large training sets for deep learning models.