• Cross-Cultural Studies
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• v.40
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• pp.111-131
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• 2015

An unusual success engendering loyalty among cult fans in the United States, Mamoru Oshii's 1995 cyberpunk anime, Ghost in the Shell (GITS) revolves around a female cyborg assassin named Motoko Kusanagi, a.k.a. "the Major." When the news came out last year that Scarlett Johansson was offered 10 million dollars for the role of the Major in the live action remake of GITS, the frustrated fans accused DreamWorks of "whitewashing" the classic Japanimation and turning it into a PG-13 film. While it would be premature to judge a film yet to be released, it appears timely to revisit the core achievement of Oshii's film untranslatable into the Hollywood formula. That is, unlike ultimately heteronormative and humanist sci-fi films produced in Hollywood, such as the Matrix trilogy or Cloud Atlas, GITS defies a Hollywoodization by evoking much bafflement in relation to its queer, posthuman characters and settings. This essay homes in on Major Kusanagi's body in order to update prior criticism from the perspectives of posthumanism and queer theory. If the Major's voluptuous cyborg body has been read as a liberating or as a commodified feminine body, latest critical work of posthumanism and queer theory causes us to move beyond the moralistic binaries of human/non-human and male/female. This deconstruction of binaries leads to a radical rethinking of "reality" and "identity" in an image-saturated, hypermediated age. Viewed from this perspective, Major Kusanagi's body can be better understood less as a reflection of "real" women than as an embodiment of our anxieties on the loss of self and interiority in the SNS-dominated society. As is warned by many posthumanist and queer critics, queer and posthuman components are too often used to reinforce the human. I argue that the Major's hybrid body is neither a mere amalgam of human and machine nor a superficial postmodern blurring of boundaries. Rather, the compelling combination of individuality, animality, and technology embodied in the Major redefines the human as always, already posthuman. This ethical act of revision-its shifting focus from oppressive humanism to a queer coexistence-evinces the lasting power of GITS.

• Journal of the Korean Wood Science and Technology
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• v.13 no.4
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• pp.3-57
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• 1985

This research was conducted to examine the feasibility of developing fire retardant particleboard and complyboard. Particleboard were manufactured using meranti particle(Shorea spp.)made with Pallmann chipper, and complyboard meranti particle and apitong veneer (Dipterocarpus spp.). Particles were passed through 4mm (6 mesh) and retained on 1mm (25 mesh). Urea formaldehyde resin was added 10 percent on ovendry weight of particle. Face veneer for complyboard was 0.9, 1.6 and 2.3mm in thickness and spread with 36 g/(30.48 cm)$^2$ glue on one side. Veneers were soaked with 10 percent solution of five fire retardant chemicals (diammonium phosphate, ammonium sulfate, monoammonium phosphate, Pyresote and Minalith), and particles with 5, 10, 15 and 20 percent solution of five chemicals. Particleboard and complyboard were evaluated on physical and mechanical properties, and fire retardancy. The results obtained were summarized as follows. 1. Among five fire retardant chemicals treated to particleboard and complyboard, the retention of ammonium sulfate in 5 percent solution showed the lowest as 1.39 kg/(30.48 cm)$^3$ exceeding the minimum retention of 1.125 kg/(30.48 cm)$^3$ recommended by Forest Products Laboratory and Koch. 2. Particleboard and complyboard treated with diammonium phosphate showed higher modulus of rupture (MOR), modulus of elasticity (MOE), internal bond strength and screw holding power than those with the other chemicals. 3. MOR and MOE of complyboard treated with fire retardant chemicals were greater than those of fire retardant particleboard. 4. Thickness swelling of fire retardant complyboard was lower than that of fire retardant particleboard. 5. The moisture content of the boards treated with Pyresote and Minalith increased and with monoammonium phosphate reduced. 6. Fire retardant particleboard showed no ignition, and fire retardant complyboard started ignition, but time required to ignite was prolonged comparing the controlboard. Complyboard with only shell veneer treated showed ignition and lingering flame, but lingering flame time was shorter than controlboard. Complyboard with treated both core and veneer showed ignition but not lingering flame. 7. Flame length, carbonized area and weight loss were smaller than controlboard but had no significant difference among chemicals treated. 8. Temperature of unexposed surface of fire retardant particleboard was lowered with the increasing concentration of five chemicals. 9. Temperature of unexposed surface of fire retardant particleboard was lowered with the highest in Pyresote and the lowest in Minalith. 10. Temperature of unexposed surface of fire retardant complyboard was lower than that of controlboard.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.