• The Journal of the Korea Contents Association
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• v.6 no.3
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• pp.38-45
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• 2006

A dual-level low voltage differential signalling (DLVDS) circuit is proposed aiming at reducing transmission lines for a LCD driver IC. We apply two data to the proposed DLVDS circuit as inputs. Then, the transmitter converts two inputs to two kinds of fully differential signals. In this circuit, two transmission lines are sufficient to transfer two inputs while keeping the LVDS feature. However, the circuit has a common mode bias fluctuation due to difference of the input bias and the reference bias. We compensate the common mode bias fluctuation using a feedback circuit of the current source bias. The receiver recovers the original input data through a level decoding circuit. We fabricated the proposed circuit using $0.25{\mu}m$ CMOS technology. The simulation results of proposed circuit shows 1-Gbps/2-line data rate and 35mW power consumption at 2.5V supply voltage, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.209-219
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• 2011

Most of the computer-based distance learning systems are asynchronous ones that allow students to download from the server the lecture previously given by a lecturer. While these asynchronous systems has the advantage that enable students to view the lecture with no time restriction, the study may not be effective due to the lack of support for real-time interaction between students and lecturers. Based on the student-lecturer-collaboration session model, this paper presents a collaboration session-centric synchronous distance learning system that supports real-time interaction between students and teachers, awareness information during lecture, and feedback from students. Basic feature of the proposed system include audio and video conferencing, text-based chat, and shared slide with annotation support.

• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.699-704
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• 2001

ABSTRACT In this paper, a new hybrid modular recurrent TDNN (time-delay neural network)-HMM (hidden Markov model) architecture for speech recognition has been studied. In TDNN, the recognition rate could be increased if the signal window is extended. To obtain this effect in the neural network, a high-level memory generated through a feedback within the first hidden layer of the neural network unit has been used. To increase the ability to deal with the temporal structure of phonemic features, the input layer of the network has been divided into multiple states in time sequence and has feature detector for each states. To expand the network from small recognition task to the full speech recognition system, modular construction method has been also used. Furthermore, the neural network and HMM are integrated by feeding output vectors from the neural network to HMM, and a new parameter smoothing method which can be applied to this hybrid system has been suggested.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.507-513
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• 2020

This paper aims to design and implement a robot that will help teach children living habits and English conversation education in dual-income families using the open platform robot Q.bo one based on raspberry pi3 of a single board computer. The first function of life habit formation is to help children to wash their hands, to brush their teeth, homework and sleep regularly. The child is then photographed listening to the notification and acting so that the parent can identify and provide feedback. The second basic conversation education feature uses Google's DialogFlow to help children learn English naturally through simple English conversation through the robot. The two-functioning robot allows children from working families to feel secure by printing their parents' voices even when they are not at home. At the same time, it allows them to get into basic lifestyle, to have basic English conversation with robots, and to be interested in English early.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.634-640
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• 2018

In this paper, we propose an automatic extraction algorithm of region of interest(ROI) based on medical x-ray images. The proposed algorithm uses segmentation, feature extraction, and reference image matching to detect lesion sites in the input image. The extracted region is searched for matching lesion images in the reference DB, and the matched results are automatically extracted using the Kalman filter based fitness feedback. The proposed algorithm is extracts the contour of the left hand image for extract growth plate based on the left x-ray input image. It creates a candidate region using multi scale Hessian-matrix based sessionization. As a result, the proposed algorithm was able to split rapidly in 0.02 seconds during the ROI segmentation phase, also when extracting ROI based on segmented image 0.53, the reinforcement phase was able to perform very accurate image segmentation in 0.49 seconds.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.2
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• pp.81-86
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• 2006

In this paper, a new process detection circuit is proposed. The proposed process detection circuit compares a long channel MOS transistor (L > 0.4um) to a short channel MOS transistor which uses lowest feature size of the process. The circuit generates the differential current proportional to the deviation of carrier mobilities according to the process variation. This method keep the two transistor's drain voltage same by implementing the feedback using a high gain OPAMP. This paper also shows the new design of the simple high gam self-biased rail-to-rail OPAMP using a proposed self-biased super MOS composite circuit. The gain of designed OPAMP is measured over 100dB with $0.2{\sim}1.6V$ wide range CMR in single stage. Finally, the proposed process detection circuit is applied to a differential VCO and the VCO showed that the proposed process detection circuit compensates the process corners successfully and ensures the wide rage operation.

• The KIPS Transactions:PartA
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• v.14A no.6
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• pp.383-390
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• 2007

This paper describes the e-learning system for science and engineering mathematics using computer algebra system and Bayesian inference network. The best feature of this system is using one of the most recent mathematical dynamic web content authoring model which is called client independent dynamic web content authoring model and using the Bayesian inference network for diagnosing student's learning. The authoring module using computer algebra system provides teacher-user with easy way to make dynamic mathematical web contents. The diagnosis module using Bayesian inference network helps students know the weaker parts of their learning, in this way our system determines appropriate next learning sequences in order to provide supplementary learning feedback.

• Nuclear Engineering and Technology
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• v.47 no.7
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• pp.791-803
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• 2015

The effective cross sections (XSs) in the direct whole core calculation code nTRACER are evaluated by the equivalence theory-based resonance-integral-table method using the WIMS-based library as an alternative to the subgroup method. The background XSs, as well as the Dancoff correction factors, were evaluated by the enhanced neutron-current method. A method, with pointwise microscopic XSs on a union-lethargy grid, was used for the generation of resonance-interference factors (RIFs) for mixed resonant absorbers. This method was modified by the intermediate-resonance approximation by replacing the potential XSs for the non-absorbing moderator nuclides with the background XSs and neglecting the resonance-elastic scattering. The resonance-escape probability was implemented to incorporate the energy self-shielding effect in the spectrum. The XSs were improved using the proposed method as compared to the narrow resonance infinite massbased method. The RIFs were improved by 1% in $^{235}U$, 7% in $^{239}Pu$, and >2% in $^{240}Pu$. To account for thermal feedback, a new feature was incorporated with the interpolation of pre-generated RIFs at the multigroup level and the results compared with the conventional resonance-interference model. This method provided adequate results in terms of XSs and k-eff. The results were verified first by the comparison of RIFs with the exact RIFs, and then comparing the XSs with the McCARD calculations for the homogeneous configurations, with burned fuel containing a mixture of resonant nuclides at different burnups and temperatures. The RIFs and XSs for the mixture showed good agreement, which verified the accuracy of the RIF evaluation using the proposed method. The method was then verified by comparing the XSs for the virtual environment for reactor applicationbenchmark pin-cell problem, as well as the heterogeneous pin cell containing burned fuel with McCARD. The method works well for homogeneous, as well as heterogeneous configurations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.8
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• pp.637-648
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• 2021

This paper aims to propose new reentry guidance for Korean Space plane (KSP). Similar to the Space Shuttle guidance concept, a reference drag profile is first determined to satisfy several flight path constraints and boundary conditions, and the proposed guidance commands are realized in a way to track the predetermined reference drag profile. To this end, the drag dynamics is examined. The investigation uncovers that the dynamics characteristics of the drag and the flight path angle are considerably different. Based on this fact, the proposed guidance commands are determined using the time-scale separation technique and the feedback linearization methodology. The key feature of the proposed guidance lies in its simple structure and a clear working mechanism. Therefore, the proposed method is simple to implement compared to existing methods. Numerical simulations are performed to investigate the performance of the proposed method.

• Journal of The Korean Association of Information Education
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• v.24 no.1
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• pp.49-57
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• 2020

The society we are living in has being changed to the age of the intelligent information society after passing through the knowledge-based information society in the early 21st century. In this study, we have developed the instructional model for software education based on the machine learning which is a field of artificial intelligence(AI) to enhance the core competencies of learners required in the intelligent information society. This model is focusing on enhancing the core competencies through the process of problem-solving as well as reducing the burden of learning about AI itself. The specific stages of the developed model are consisted of seven levels which are 'Problem Recognition and Analysis', 'Data Collection', 'Data Processing and Feature Extraction', 'ML Model Training and Evaluation', 'ML Programming', 'Application and Problem Solving', and 'Share and Feedback'. As a result of applying the developed model in this study, we were able to observe the positive response about learning from the students and parents. We hope that this research could suggest the future direction of not only the instructional design but also operation of software education program based on machine learning.