• Journal of the Korean Geographical Society
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• v.39 no.1
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• pp.153-168
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• 2004

This study begins with the interests of the problems in learning a region under the Korean National Curriculum in geography field and the perceptions on the region which affects students 'formation of regional concept. The purposes of this study are to find problems in learning a region and to construct a new content for learning a region to improve the current problems. This study suggests that it is necessary for student to establish a clear concept on a region in order to effectively learn a region. Therefore, this study reviews how concepts on a region have changed and selects important elements in learning a region by considering a level of students' understanding. The important elements selected in this study are the definition of a region, the formation of a region, and the system of a region. By learning a real region established as a 'region for instruction' of a medium scale, students can reach an appropriate level of meaningful understanding of a region. This study found that an appropriate selection of scale in choosing the extent of a region was critical in success of effective organization of learning contents.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.13-16
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• 2023

This study aims to explore the status of e-learning in the public sector institutes of the Sukkur region in Pakistan. A survey was conducted to collect data from students and teachers regarding their awareness, access, and use of e-learning resources. The results showed that although there is a widespread use of the internet and mobile devices for accessing information, there is a lack of awareness and access to e-learning resources. Barriers to accessing e-learning content and a lack of familiarity with e-learning content development technologies were also identified. The study concludes that there is a need for improved e-learning facilities and curriculum in the public sector institutes of the Sukkur region in Pakistan. Recommendations are provided for developing a correctness-centered e-learning based curriculum that is tailored to the specific needs of the students in the region. It is hoped that the findings of this study will inform efforts to improve the teaching and learning process in the region and provide students with greater flexibility and access to study materials.

• Journal of the Korean Regional Science Association
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• v.15 no.1
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• pp.93-116
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• 1999

Recently the concept of learning has become very fashionable among academics from different economic disciplines. Economic geographers and spatial planners joined this fashion by increasingly speaking about the 'learning region'. This paper makes clear that this learning region'. This paper makes clear that this learning region concept has been launched from three angles; as spatial outcome of grand societal changes, as spatial concentration of entrepreneurial learning for innovation and as regional development concept. Despite the deficits and flaws such a young concept is faced with, such as vague definitions, the lack of empirical research and an insufficiently clear separation from existing concepts, the learning region concept might provide economic geography with more insight in agglomeration effects, stronger links with policy-making and more knowledge on path dependency and thus on unravelling the distinction between 'good' and 'bad' industrial agglomerations.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.174-174
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• 2000

Q-learning, based on discrete state and action space, is a most widely used reinforcement Learning. However, this requires a lot of memory and much time for learning all actions of each state when it is applied to a real mobile robot navigation using continuous state and action space Region-based Q-learning is a reinforcement learning method that estimates action values of real state by using triangular-type action distribution model and relationship with its neighboring state which was defined and learned before. This paper proposes a new Region-based Q-learning which uses a reward assigned only when the agent reached the target, and get out of the Local optimal path with adjustment of random action rate. If this is applied to mobile robot navigation, less memory can be used and robot can move smoothly, and optimal solution can be learned fast. To show the validity of our method, computer simulations are illusrated.

• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.138-148
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• 2015

Object detection methods based on background learning are widely used in video surveillance. However, when a car runs with headlights on, these methods are likely to detect the car region and the area illuminated by the headlights as one connected change region. This paper describes a method of separating the car region from the area illuminated by the headlights. First, we detect change regions with a background learning method, and extract blobs, connected components in the detected change region. If a blob is larger than the maximum object size, we extract candidate object regions from the blob by clustering the intensity histogram of the frame difference between the mean of background images and an input image. Finally, we compute the similarity between the mean of background images and the input image within each candidate region and select a candidate region with weak similarity as an object region.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.175-182
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• 1994

In this study, we present unvoiced consonant recognition system using characteristic parameters of the phoneme of the each syllable. For the recognition, the characteristic parameters on the time domain such as ZCR, total energy of the consonant region and half region energy of the consonant region, and those on the frequency domain such as the frequency spectrum of the transition region are used. The objective unvoiced consonants in this study are /ㄱ/,/ㄷ/,/ㅂ/,/ㅈ/,/ㅋ/,/ㅌ/,/ㅍ/ and /ㅊ/. Each characteristic parameter of two regions extracted from these segmented unvoiced consonants are used for each recognition system of the region, independently, And complementing two outputs of each other system, the final output is to be produced. The recognition system is implemented using MLP which has learning ability. The recognition simulation results for 112 unvoiced consonant samples are that average recognition rates are 96.4$\%$ under 80$\%$ learning rates and 93.7$\%$ under 60$\%$ learning rates.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3333-3350
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• 2019

The smart jammer launches jamming attacks which degrade the transmission reliability. In this paper, smart jamming attacks based on the communication probability over different channels is considered, and an anti-jamming Q learning algorithm (AQLA) is developed to obtain anti-jamming knowledge for the local region. To accelerate the learning process across multiple regions, a multi-regional intelligent anti-jamming learning algorithm (MIALA) which utilizes transferred knowledge from neighboring regions is proposed. The MIALA algorithm is evaluated through simulations, and the results show that the it is capable of learning the jamming rules and effectively speed up the learning rate of the whole communication region when the jamming rules are similar in the neighboring regions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2127-2134
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• 2007

The electronic learning helped a learner to overcome the time restriction by providing mobility, instantly and flexibility but the restriction in connection with space on cable computer remained unsolved. Accordingly, the electronic learning has tendency to change into mobile learning environment which allows a learner to overcome time and spatial restriction. However, these mobile devices have a limitation to awareness of learning contents provided over the realtime video movie due to its small display size. Therefore, this paper suggests a technique according to the following priority: for a real time learning image, extract region of study for region of interest, rescale the real time image to its proper size suitable for the display device, and then make it displayed on a wireless PDA. As a result of the experiment, we reduced the calculating time by sampling the field centering on learning contents adaptively and computing the field best suited for device size of the user effectively.

• Journal of the Korean association of regional geographers
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• v.13 no.2
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• pp.220-233
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• 2007

In the context of region reconceptualized as a learning framework, using the Seoul region as an example, this paper focused on the debate and the condition of regional social studies curriculum in elementary schools, It means that regionalization of curriculum is the decentralization of power to develop and manage curriculum In that case, region is understood to he a resource used to connect the subject matter to children's experience, Furthermore, region is interpreted as Heimat, community and world around, Heimat is intended to be understood, loved and belonged to, Community is the resource for learning and the space of communication, participation and action, World around is the typical example to be searched, compared and explained by the concept and theory. On the base of the regionalization debate and the classification of learning a region, I analysed the local textbook, Social Studies Inquiry: Life in Seoul and suggested the framework of learning a region. In this paper, I tried to pick out the spatial demension of Seoul. It is classified into the space of experience, participation and inquiry, In conclusion, the region-specific materials and approach laying stress on the issue and topic in the geographical context of the region will determine that a proper regionalization occurs through not only methods hut also content.

• Journal of Digital Convergence
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• v.13 no.8
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• pp.289-294
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• 2015

This paper proposes an autonomous machine learning method applicable to the BCI(Brain-Computer Interface) is based on the self-organizing Kohonen method, one of the exemplary method of unsupervised learning. In addition we propose control method of learning region and self machine learning rule using an interactive function. The learning region control and machine learning was used to control the side effects caused by interaction function that is based on the self-organizing Kohonen method. After determining the winner neuron, we decided to adjust the connection weights based on the learning rules, and learning region is gradually decreased as the number of learning is increased by the learning. So we proposed the autonomous machine learning to reach to the network equilibrium state by reducing the flow toward the input to weights of output layer neurons.