• 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.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.6
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• pp.155-164
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• 2018

Many malicious programs have been compressed or encrypted using various commercial packers to prevent reverse engineering, So malicious code analysts must decompress or decrypt them first. The OEP (Original Entry Point) is the address of the first instruction executed after returning the encrypted or compressed executable file back to the original binary state. Several unpackers, including PinDemonium, execute the packed file and keep tracks of the addresses until the OEP appears and find the OEP among the addresses. However, instead of finding exact one OEP, unpackers provide a relatively large set of OEP candidates and sometimes OEP is missing among candidates. In other words, existing unpackers have difficulty in finding the correct OEP. We have developed new tool which provides fewer OEP candidate sets by adding two methods based on the property of the OEP. In this paper, we propose two methods to provide fewer OEP candidate sets by using the property that the function call sequence and parameters are same between packed program and original program. First way is based on a function call. Programs written in the C/C++ language are compiled to translate languages into binary code. Compiler-specific system functions are added to the compiled program. After examining these functions, we have added a method that we suggest to PinDemonium to detect the unpacking work by matching the patterns of system functions that are called in packed programs and unpacked programs. Second way is based on parameters. The parameters include not only the user-entered inputs, but also the system inputs. We have added a method that we suggest to PinDemonium to find the OEP using the system parameters of a particular function in stack memory. OEP detection experiments were performed on sample programs packed by 16 commercial packers. We can reduce the OEP candidate by more than 40% on average compared to PinDemonium except 2 commercial packers which are can not be executed due to the anti-debugging technique.

• Archives of design research
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• v.18 no.3 s.61
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• pp.85-94
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• 2005

Most of product designers use 3D CAD system as a inevitable design tool nowadays and many new products are developed through a concurrent engineering process. However, it is very difficult for novice designers to get the sense of reality from modeling objects shown in the computer screens. Such a intangibility problem comes from the lack of haptic interactions and contextual information about the real space because designers tend to do 3D modeling works only in a virtual space of 3D CAD system. To address this problem, this research investigate the possibility of a interactive quantified structure simulation for product design using AR(augmented reality) which can register a 3D CAD modeling object on the real space. We built a quantified structure simulation system based on AR and conducted a series of experiments to measure how accurately human perceive and adjust the size of virtual objects under varied experimental conditions in the AR environment. The experiment participants adjusted a virtual cube to a reference real cube within 1.3% relative error(5.3% relative StDev). The results gave the strong evidence that the participants can perceive the size of a virtual object very accurately. Furthermore, we found that it is easier to perceive the size of a virtual object in the condition of presenting plenty of real reference objects than few reference objects, and using LCD panel than HMD. We tried to apply the simulation system to identify preference characteristics for the appearance design of a home-service robot as a case study which explores the potential application of the system. There were significant variances in participants' preferred characteristics about robot appearance and that was supposed to come from the lack of typicality of robot image. Then, several characteristic groups were segmented by duster analysis. On the other hand, it was interesting finding that participants have significantly different preference characteristics between robot with arm and armless robot and there was a very strong correlation between the height of robot and arm length as a human body.

• 재활복지
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• v.22 no.2
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• pp.1-30
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• 2018

This paper attempts to explore the place of human and disability rights from the perspective of Social Welfare within the context of the UN Disability Rights Convention of 2006. The overall discussion is focused especially upon the situations of human and disability rights in the Democratic People's Republic of Korea (North Korea) as it is being challenged to drastically address the issues of human rights in general, and disability rights in particular. The UN Disability Rights Convention challenges every ratified State party to commence legal reforms, legal harmonization, and policy and program developments to implement the Convention. Both North and South Korea are not exceptions to this. Even without drawing upon the UN's the Commission of Inquiry on Human Rights in the Democratic People's Republic of Korea, the dire situation of human rights in North Korea is well documented. However, this paper does not assume South Korea's human rights are any way superior to that of North Korea. This paper spells out areas for further action common to two Koreas and to any other nations for that matter. Apart from the general discussion on disability rights, the distinctive contribution of this paper lies in the fact that it has endeavored to draw upon any latest information and data on North Korea. It relied on various sources from UN and also from North Korea itself. One can note that North Korean disability authorities are making strenuous efforts to improve human rights of persons with disabilities in their desires to seek assistance from outside. It also shows an enormous need for international cooperation in seeking financial and material supports. This paper notes the latest political development between North and South Korea in taking "phased" steps for peace and stability as a positive sign for North and South Koreans' DPOs collaboration under the banner of International Cooperation of the article 32 of the UN Disability Rights Convention. More critically, this paper points to the further need to improve the overall data bases to ensure balanced legal reforms, policy developments and sharpen the areas of international collaboration.

• Clinical and Experimental Reproductive Medicine
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• v.36 no.3
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• pp.187-197
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• 2009

Objective: Phosphorylation and dephosphorylation of proteins are important in regulating cellular signaling pathways. Bead-based multiplex phosphorylation assay was conducted to detect the phosphorylation of seven proteins to maximize the information obtained from a single lysate of stage-specific mouse oocytes at a time. Methods: Cumulus-oocyte complexes (COCs) were cultured for 2 h, 8 h, and 16 h, respectively to address phosphorylation status of seven target proteins during oocyte maturation process. We analyzed the changes in phosphorylation at germinal vesicle (GV, 0 h), germinal vesicle breakdown (GVBD, 2 h), metaphase I (MI, 8 h), and metaphase II (MII, 16 h in vitro or in vivo) mouse oocytes by using Bio-Plex phosphoprotein assay system. We chose seven target proteins, namely, three mitogen-activated protein kinases (MAPKs), ERK1/2, JNK, and p38 MAPK, and other 4 well known signaling molecules, Akt, GSK-$3{\alpha}/{\beta}$, $I{\kappa}B{\alpha}$, and STAT3 to measure their phosphorylation status. Western blot analysis and kinase inhibitor treatment for ERK1/2, JNK, and Akt during in vitro maturation of oocytes were conducted for the confirmation. Results: Phosphorylation of ERK1/2, JNK, p38 MAPK and STAT3 was increased over 3 folds up to 20 folds, while phosphorylation of the other three signal molecules, Akt, GSK-$3{\alpha}/{\beta}$, and $I{\kapa}B{\alpha}$ was less than 3 folds. All of these results except for Akt were statistically significant (p<0.05). Conclusion: This is the first report on the new and valuable method measuring many phosphoproteins simultaneously in one minute sample such as oocyte lysates. All of the three MAPKs, ERK1/2, JNK, and p38 MAPK are involved in the process of mouse oocyte maturation. In addition, STAT3 might be important regulator of oocyte maturation, while Akt phosphorylation at Serine 473 may not be involved in the regulation of oocyte maturation.

• Cross-Cultural Studies
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• v.52
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• pp.277-312
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• 2018

First-order cybernetics during the 1940s and 1950s aimed for control of an observed system, while second-order cybernetics during the mid-1970s aspired to address the mechanism of an observing system. The former pursues an objective, subjectless, approach to a system, whereas the latter prefers a subjective, personal approach to a system. Second-order observation must be noted since a human observer is a living system that has its unique cognition. Maturana and Varela place the autopoiesis of this biological system at the core of second-order cybernetics. They contend that an autpoietic system maintains, transforms and produces itself. Technoscientific recreation of biological autopoiesis opens up to a new step in cybernetics: what I describe as third-order cybernetics. The formation of technoscientific autopoiesis overlaps with the Fourth Industrial Revolution or what Erik Brynjolfsson and Andrew McAfee call the Second Machine Age. It leads to a radical shift from human centrism to posthumanity whereby humanity is mechanized, and machinery is biologized. In two versions of the novel Demon Seed, American novelist Dean Koontz explores the significance of technoscientific autopoiesis. The 1973 version dramatizes two kinds of observers: the technophobic human observer and the technology-friendly machine observer Proteus. As the story concludes, the former dominates the latter with the result that an anthropocentric position still works. The 1997 version, however, reveals the victory of the techno-friendly narrator Proteus over the anthropocentric narrator. Losing his narrational position, the technophobic human narrator of the story disappears. In the 1997 version, Proteus becomes the subject of desire in luring divorcee Susan. He longs to flaunt his male egomaniac. His achievement of male identity is a sign of technological autopoiesis characteristic of third-order cybernetics. To display self-producing capabilities integral to the autonomy of machinery, Koontz's novel demonstrates that Proteus manipulates Susan's egg to produce a human-machine mixture. Koontz's demon child, problematically enough, implicates the future of eugenics in an era of technological autopoiesis. Proteus creates a crossbreed of humanity and machinery to engineer a perfect body and mind. He fixes incurable or intractable diseases through genetic modifications. Proteus transfers a vast amount of digital information to his offspring's brain, which enables the demon child to achieve state-of-the-art intelligence. His technological editing of human genes and consciousness leads to digital standardization through unanimous spread of the best qualities of humanity. He gathers distinguished human genes and mental status much like collecting luxury brands. Accordingly, Proteus's child-making project ultimately moves towards technologically-controlled eugenics. Pointedly, it disturbs the classical ideal of liberal humanism celebrating a human being as the master of his or her nature.