• Journal of Broadcast Engineering
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• 제26권2호
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• pp.155-166
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• 2021

Most object detection algorithms are studied based on RGB images. Because the RGB cameras are capturing images based on light, however, the object detection performance is poor when the light condition is not good, e.g., at night or foggy days. On the other hand, high-quality infrared(IR) images regardless of weather condition and light can be acquired because IR images are captured by an IR sensor that makes images with heat information. In this paper, we performed the object detection algorithm based on the compression ratio in RGB and IR images to show the detection capabilities. We selected RGB and IR images that were taken at night from the Free FLIR Thermal dataset for the ADAS(Advanced Driver Assistance Systems) research. We used the pre-trained object detection network for RGB images and a fine-tuned network that is tuned based on night RGB and IR images. Experimental results show that higher object detection performance can be acquired using IR images than using RGB images in both networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권7호
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

• Journal of Internet Computing and Services
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• 제15권3호
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• pp.71-77
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• 2014

The equalization algorithm based on the cross-information potential concept and Dirac-delta functions (CIPD) has outstanding ISI elimination performance even under impulsive noise environments. The main drawback of the CIPD algorithm is a heavy computational burden caused by the use of a block processing method for its weight update process. In this paper, for the purpose of reducing the computational complexity, a new method of the gradient calculation is proposed that can replace the double summation with a single summation for the weight update of the CIPD algorithm. In the simulation results, the proposed method produces the same gradient learning curves as the CIPD algorithm. Even under strong impulsive noise, the proposed method yields the same results while having significantly reduced computational complexity regardless of the number of block data, to which that of the e conventional algorithm is proportional.

• Communications of Mathematical Education
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• 제28권1호
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• pp.81-96
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• 2014

Now, most of programs developed were presented as form of item pool by dividing problems by section and level for the level differentiated course, so the utilization is decreasing at the field caused by unconsidered school underachievement elements by achievement. Especially, the study on teaching materials and effective measures map for mid-low level students with low utilization is more urgent. Therefore, in this study we will promote teaching method for improving learning achievement at high school. The development teaching materials(the performance evaluation and diagnostic assessment, reconstruction of textbooks) will be applied to classes for the underachieving students directly, and the achievement in the experimental class was significantly improved compared to the comparative class and the meaningful conclusions could be drawn as results of conducting same assessment based on the experimental class and the comparative class.

• The Journal of the Korea Contents Association
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• 제9권1호
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• pp.465-474
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• 2009

The emergence of the digital age has changed the paradigm of education. Recently, the new paradigm needs new digital books that contain more interactive contents. Our goal is to design the digital textbook with convenient interfaces and cutting effects for interactive and effective education. To achieve these goals, we propose interfaces and contents which are designed after a lot of discussion with educational experts. In the implementation step, cutting algorithm is proposed to generate the cut planes of the 3D objects, based on the free strokes specified by the users. In order to test the performance of the contents, the testbed was implemented so that students try our digital book and present their evaluation results on the convenience and the effectiveness.

• Knowledge Management Research
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• 제10권3호
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• pp.51-80
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• 2009

The purpose of this study is to empirically analyze the impact that occurs when Korean organizations make practical use of various information technology tools and systems in the knowledge management process, such as sharing, learning and creating knowledge. Such a process is usually made through online and offline knowledge management activities. This paper also verifies how the externalization of tacit knowledge, and the internalization of explicit knowledge via the Internet and offline socialization activities have altered the mechanisms of knowledge transfers inside organizations. For the research, a survey was conducted on the satisfaction and usability levels of information technology, and the impact of IT usage on the results of knowledge management activities and knowledge transfers. 622 Korean organizations were surveyed, including major listed firms and public organizations. The results were examined as an online/offline integration process using SECI's Model proposed by Nonaka (1994, 1995). The analysis shows that information technology satisfaction and the usage of information technology help accelerate the pace of the knowledge flow and amplify the volume of the knowledge transfer by boosting the externalization and internalization processes-also known as knowledge management activities. However. there is no distinct correlation between information technology and socialization, an offline knowledge transferal activity. In particular, the quality of knowledge-an end result of knowledge transfer-does not improve merely by the externalization of online knowledge and instead requires the internalization of knowledge processes. Above all, the research reveals that offline socialization processes vastly contribute to the improvement of knowledge quality. This paper suggests that in order to ensure a transfer of quality knowledge, an organization or a company should focus on the use of information technology rather than the satisfaction level of information technology, and that knowledge transfers via the Internet has limitations in creating high quality of knowledge. For an organization to ensure the transfer of high-quality knowledge, the organization should not entirely hinge the transfer of knowledge online, as it is essential to have an offline method-a form of socialization such as a 'community of practice.'

• Journal of Physiology & Pathology in Korean Medicine
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• 제30권1호
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• pp.61-65
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• 2016

The purpose of this study is to examine the relationship between Myers-Briggs Type Indicator(MBTI) personality type and academic achievement of Korean medical students. A total of 97 (57 men, 40 women; ages 24 to 36) fourth-year Korean medical students participated in this study. The MBTI questionnaire was administered to all the students for identification of their personality type and academic performance. The results are as follows. First, the proportions of Personality type of Korean medical students were Extroversion (E) 33.0% - Introversion (I) 67.0%, Sensing (S) 70.1%- Intuition (N) 29.9%, Thinking (T) 58.8%- Feeling (F) 41.2%, and Judging (J) 54.6% - Perceiving (P) 45.3%. Second, the most common personality type was ISTJ (22.7%), followed by ISTP (13.4%), ISFJ (12.3%). Third, according to the analysis of this study, academic achievement was significantly related with their personality type in the preference : Sensing (S) - Intuition (N) and Judging (J)-Perceiving (P). In analysis of Sensing (S) - Intuition (N) and Judging (J)-Perceiving (P) index, Sensing (S) and Judging (J) type students had higher academic achievement than Intuition (N) and Perceiving (P) type students. This is the study to identify the characteristics of MBTI in Korean Medical students. The findings indicate that academic achievement was significantly related to their personality type in the preference. Using the results of MBTI in Korean medical students, is helpful in selection of appropriate teaching and learning strategies to provide better education.

• Journal of the Institute of Electronics Engineers of Korea CI
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• 제49권4호
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• pp.42-53
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• 2012

In pattern recognition and machine learning society, classification has been a classical problem and the most widely researched area. Adaptive boosting also known as Adaboost has been successfully applied to binary classification problems. It is a kind of boosting algorithm capable of constructing a strong classifier through a weighted combination of weak classifiers. On the other hand, the PCA and LDA algorithms are the most popular linear feature extraction methods used mainly for dimensionality reduction. In this paper, the combination of Adaboost and feature extraction methods is proposed for efficient classification of two class data. Conventionally, in classification problems, the roles of feature extraction and classification have been distinct, i.e., a feature extraction method and a classifier are applied sequentially to classify input variable into several categories. In this paper, these two steps are combined into one resulting in a good classification performance. More specifically, each projection vector is treated as a weak classifier in Adaboost algorithm to constitute a strong classifier for binary classification problems. The proposed algorithm is applied to UCI dataset and FRGC dataset and showed better recognition rates than sequential application of feature extraction and classification methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 한국방송공학회 2009년도 IWAIT
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• pp.547-550
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• 2009

The object recognition mechanism of human being is not well understood yet. On research of animal experiment using an ape, however, neurons that respond to simple shape (e.g. circle, triangle, square and so on) were found. And Hypothesis has been set up as human being may recognize object as combination of such simple shapes. That mechanism is called Figure Alphabet Hypothesis, and those simple shapes are called Figure Alphabet. As one way to research object recognition algorithm, we focused attention to this Figure Alphabet Hypothesis. Getting idea from it, we proposed the feature extraction algorithm for object recognition. In this paper, we described recognition of binarized images of multifont alphabet characters by the recognition model which combined three-layered neural network in the feature extraction algorithm. First of all, we calculated the difference between the learning image data set and the template by the feature extraction algorithm. The computed finite difference is a feature quantity of the feature extraction algorithm. We had it input the feature quantity to the neural network model and learn by backpropagation (BP method). We had the recognition model recognize the unknown image data set and found the correct answer rate. To estimate the performance of the contriving recognition model, we had the unknown image data set recognized by a conventional neural network. As a result, the contriving recognition model showed a higher correct answer rate than a conventional neural network model. Therefore the validity of the contriving recognition model could be proved. We'll plan the research a recognition of natural image by the contriving recognition model in the future.

• Communications of Mathematical Education
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• 제25권4호
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• pp.629-639
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• 2011

Currently science and technology are changing so fast and college mathematics becomes more and more important. But the downturn of freshmen's scholastic performance has been intensified and this phenomenon leads to serious problems in managing college curriculums. During the recent years at a middle level engineering college, many freshmen had a lot of difficulties in their mathematics courses. In consequence, many of them had hard time to survive at their major curriculums. In this point of view, we analyse the situation of mathematical scholastic ability among engineering majored freshmen through the research on the actual state of mathematical background, mathematical scholastic ability test, college mathematics scores, and scholastic aptitude test scores. We study the relation between the mathematics score of scholastic aptitude test for the college entrance and mathematical scholastic ability of freshmen of a middle level engineering college. From this study we conclude that the essential reasons for the above situations are the curriculum of middle school mathematics and the system of scholastic aptitude test and the entrance examination of university. In order for improving mathematical accomplishment. we give suggestions such as a learning ability improvement program in mathematics.