• Title/Summary/Keyword: Existence of Solution

검색결과 943건 처리시간 0.024초

Electrochemical Characteristics of LiNi0.5Mn1.5O4 Spinel as 5 V Class Cathode Material for Lithium Secondary Batteries (5V급 고전압 양극 LiNi0.5Mn1.5O4 Spinel의 제조와 전기화학적 특성에 관한 연구)

  • Jeon, Sang-Hoon;Oh, Si-Hyoung;Lee, Byung-Jo;Cho, Won-Il;Cho, Byung-Won
    • Journal of the Korean Electrochemical Society
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    • 제8권4호
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    • pp.172-176
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    • 2005
  • Recently, many researches on the high-voltage 5 V class cathode material have focused on $LiNi_{0.5}Mn_{1.5}O_4$, where $Mn^{3+}$ in the existing $LiMn_2O_4 (Li[Mn^{3+}][Mn^{4+}]O_4)$ is replaced by $Ni^{2+}(Li[Ni^{2+}]_{0.5}[Mn^{4+}]_{1.5}O_4)$ in order to utilize $Ni^{2+}/Ni^{4+}$ redox reaction in the 5V region. The partial substitution of Mn in $LiMn_2O_4$ for other transition metal element, $LiM_yMn_{1-y}O_4$(M=Cr, Al, Ni, Fe, Co, Cu, Ga etc) is known as a good solution to overcome the problems associated with $LiMn_2O_4$ like the gradual capacity fading. In this study, we synthesized $LiNi_{0.5}Mn_{1.5}O_4$ through a mechanochemical process and investigated its morphological, crystallographic and electrochemical characteristics. The results showed that 4 V peaks had been found in the cyclic volammograms of the synthesized powders due to the existence of $Mn^{3+}$ from the incomplete substitution of $Ni^{2+}$ for $Mn^{3+}$ implying that the mechanochemical activation alone was not good enough to synthesize an exact stoichiometric compound of $LiNi_{0.5}Mn_{1.5}O_4$. The synthetic condition of mechanochemical process, such as type of starting materials, ball-mill and calcination condition was optimized for the best electrochemical performance.

A Study on Practical Curriculum Development of the Education for Love based on the Understanding of Psychoanalytic 'Desire of Subject' (정신분석학적 '욕망의 주체' 이해에 기초한 사랑의 교육 교육과정 개발)

  • Kim, Sun Ah
    • Journal of Christian Education in Korea
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    • 제68권
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    • pp.77-112
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    • 2021
  • This study is based on the research of the first year, which is the National Research Foundation of Korea's R&D subject for middle-grade researchers. In this study, the practical curriculum development of the education for love - an according to the psychoanalytic perspectives of F. Dolto(1908-1988) - is suggested as follows. The first is 'the reconstruction of the directions of curriculum and its specific aims in accordance with such directions.' The reconstruction of the directions of curriculum aims at leading our future generation to live as a subject of desire through the mutual-communication of love. The second is 'the reconstruction of the tasks of curriculum and its specific contents in accordance with such tasks.' The reconstruction of the tasks of curriculum pursuit to help our future generation through the converting the education for love into the paradigm of desire of Agape to live as a subject of desire forming a whole personality and practicing the desire of Agape in daily life. as a source of desire. According to these aims, the reconstruction of directions of curriculum are presented as following: firstly, 'curriculum for the mutual-communication between subjects of love' and secondly, 'curriculum for the subject of desire'. The reconstruction of tasks of curriculum are like these: firstly, 'converting the education for love into the paradigm of desire of Agape', and secondly, 'forming a whole personality through the education for love'. Thus, with respect to two specific aims in accordance with the reconstruction of directions are suggested like these: Firstly, 'constructing a subject as a speaking existence' and secondly, 'realizing the subject as the autonomous source of desire'. In the two specific contents in accordance with the reconstruction of tasks are presented as following: Firstly, 'realizing the truth of the desire of Agape'.' Secondly, 'practicing the desire of Agape in daily life.' The third is 'the reconstruction of curriculum by life cycle' are suggested. They include the fetal life, infants and preschool children life, and childhood life. In further study, it is required to contain adolescent period. It will be useful to help them to recover their self-esteem with the experience of true love, especially, out-of-school young generation overcome negative perspectives and prejudice in the society, and challenges to their dreams and future through proper utilization of the study outcome. The outcome of this study, which presented practical curriculum development of the education for love based on the understanding of psychoanalytic 'desire of subject' can be used as basic teaching materials for our future generations. Furthermore, the results can be used as a resource for educating ministers and lay leaders in the religious world to build capabilities to heal their inner side as well as the society that is tainted with various forms of conflict. These include general conflicts, anger, pleasure and addiction, depression and suicide, violence and murder, etc. The study outcome can contribute to the prevention of antisocial incidents against humanity that have recently been occurring in our free-semester system implemented in all middle schools across the country to be operated effectively. For example, it is possible to provide the study results as lecture and teaching materials for 'character camp' (self-examination and self-esteem improvement training) and 'family healing camp' (solution of a communication gap between family members and love communication training), which help students participate in field trip activities and career exploration activities voluntarily, independently, and creatively. Ultimately, it can visibly present the convergent research performance by providing the study outcome as preliminary data for the development of lecture videos and materials including infant care and preschool education, parental education, family consultation education, and holistic healing education. Support from the religious world, including the central government and local governments, are urgently required in order for such educational possibilities to be fulfilled both in the society and the fields of church education and to be actively linked to follow-up studies.

The way to make training data for deep learning model to recognize keywords in product catalog image at E-commerce (온라인 쇼핑몰에서 상품 설명 이미지 내의 키워드 인식을 위한 딥러닝 훈련 데이터 자동 생성 방안)

  • Kim, Kitae;Oh, Wonseok;Lim, Geunwon;Cha, Eunwoo;Shin, Minyoung;Kim, Jongwoo
    • Journal of Intelligence and Information Systems
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    • 제24권1호
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    • pp.1-23
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    • 2018
  • From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.