• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.1
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• pp.105-111
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• 2003

Wheel for passenger car support the car weight with tires, and they transmit rolling and braking power into the ground. Whittling away at wheel weight is more effective to boost fuel economy than lighting vehicle body structure. A shape of hole in disk is optimized for minimizing the weight of steel wheel. Pro/ENGINEER program is used for formulating the design model, and ANSYS package is selected for analyzing the design model. It has difficulties to interface these commercial software directly. For Combining both programs, response surface methodology is applied to construct approximation functions for maximum stresses and maximum displacements are obtained by full factorial design of five levels. This steel wheel is modeled in 14-inch diameter of rim, and wide parameter of hole in disk is only selected as design variable for reducing the weight of steel whee. PLBA(Pshenichny-Lim-Belegundu-Arora) algorithm, which used the second-order information in the direction finding problem and uses the active set strategy, is used for solving optimization problems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.103-108
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• 2011

The modern society with the wide spread recognition of the importance of informatics and for the development of information and communication technology is rapidly processing. Especially the rapid development in mobile technology boost up the general expectation that one can get the information he wants anytime anywhere. Accordingly image search for the convenient information retrieval is becoming common. However general image search has difficulties because inexactitude extracting character in the image and getting the detail information in extracted character. Therefore these paper make character recognition through the images that I photographed a sightseeing resort, a signboard of a lot of stores to a smart phone camera, so information offer to be convenient to users is a purpose. A user can get detailed information, by character extraction way called top-hat algorithm and connect to a server.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.328-338
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• 2017

In this paper, a zero torque control scheme adopting current sharing function (CSF) used in integrated Switched Reluctance Motor (SRM) drive with DC battery charger is proposed. The proposed control scheme is able to achieve the keeping position (KP), zero torque (ZT) and power factor correction (PFC) at the same time with a simple novel current sharing function algorithm. The proposed CSF makes the proper reference for each phase windings of SRM to satisfy the total charging current of the battery with zero torque output to hold still position with power factor correction, and the copper loss minimization during of battery charging is also achieved during this process. Based on these, CSFs can be used without any recalculation of the optimal current at every sampling time. In this proposed integrated battery charger system, the cost effective, volume and weight reduction and power enlargement is realized by function multiplexing of the motor winding and asymmetric SR converter. By using the phase winding as large inductors for charging process, and taking the asymmetric SR converter as an interleaved converter with boost mode operation, the EV can be charged effectively and successfully with minimum integral system. In this integral system, there is a position sliding mode controller used to overcome any uncertainty such as mutual inductance or DC offset current sensor. Power factor correction and voltage adaption are obtained with three-phase buck type converter (or current source rectifier) that is cascaded with conventional SRM, one for wide input and output voltage range. The practicability is validated by the simulation and experimental results by using a laboratory 3-hp SRM setup based on TI TMS320F28335 platform.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.11
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• pp.155-162
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• 2019

The construction industry is the highest safety accident causing industry as 28.55% portion of all industries' accidents in Korea. In particular, falling is the highest accidents type composed of 60.16% among the construction field accidents. Therefore, we analyzed the factors of major disaster affecting the fall accident and then derived feature importances by considering various variables. We used data collected from Korea Occupational Safety & Health Agency (KOSHA) for learning and predicting in the proposed model. We have an effort to predict the degree of occupational fall accidents by using the machine learning model, i.e., Adaboost, short for Adaptive Boosting. Adaboost is a machine learning meta-algorithm which can be used in conjunction with many other types of learning algorithms to improve performance. Decision trees were combined with AdaBoost in this model to predict and classify the degree of occupational fall accidents. HyOperpt was also used to optimize hyperparameters and to combine k-fold cross validation by hierarchy. We extracted and analyzed feature importances and affecting fall disaster by permutation technique. In this study, we verified the degree of fall accidents with predictive accuracy. The machine learning model was also confirmed to be applicable to the safety accident analysis in construction site. In the future, if the safety accident data is accumulated automatically in the network system using IoT(Internet of things) technology in real time in the construction site, it will be possible to analyze the factors and types of accidents according to the site conditions from the real time data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1478-1499
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• 2024

Coronavirus disease (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. COVID-19 become an active epidemic disease due to its spread around the globe. The main causes of the spread are through interaction and transmission of the droplets through coughing and sneezing. The spread can be minimized by isolating the susceptible patients. However, it necessitates remote monitoring to check the breathing issues of the patient remotely to minimize the interactions for spread minimization. Thus, in this article, we offer a wearable-IoTs-centered framework for remote monitoring and recognition of the breathing pattern and abnormal breath detection for timely providing the proper oxygen level required. We propose wearable sensors accelerometer and gyroscope-based breathing time-series data acquisition, temporal features extraction, and machine learning algorithms for pattern detection and abnormality identification. The sensors provide the data through Bluetooth and receive it at the server for further processing and recognition. We collect the six breathing patterns from the twenty subjects and each pattern is recorded for about five minutes. We match prediction accuracies of all machine learning models under study (i.e. Random forest, Gradient boosting tree, Decision tree, and K-nearest neighbor. Our results show that normal breathing and Bradypnea are the most correctly recognized breathing patterns. However, in some cases, algorithm recognizes kussmaul well also. Collectively, the classification outcomes of Random Forest and Gradient Boost Trees are better than the other two algorithms.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.361-368
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• 2014

The LPR(License plate recognition) system has been developed to efficient control for complex traffic environment and currently be used in many places. However, because of light, noise, background changes, environmental changes, damaged plate, it only works limited environment, so it is difficult to use in real-time. This paper presents a heuristic segmentation algorithm for robust to noise and illumination changes and introduce a real-time license plate recognition system using it. In first step, We detect the plate utilized Haar-like feature and Adaboost. This method is possible to rapid detection used integral image and cascade structure. Second step, we determine the type of license plate with adaptive histogram equalization, bilateral filtering for denoise and segment accurate character based on adaptive threshold, pixel projection and associated with the prior knowledge. The last step is character recognition that used histogram of oriented gradients (HOG) and multi-layer perceptron(MLP) for number recognition and support vector machine(SVM) for number and Korean character classifier respectively. The experimental results show license plate detection rate of 94.29%, license plate false alarm rate of 2.94%. In character segmentation method, character hit rate is 97.23% and character false alarm rate is 1.37%. And in character recognition, the average character recognition rate is 98.38%. Total average running time in our proposed method is 140ms. It is possible to be real-time system with efficiency and robustness.

• The Journal of Korean Society for Radiation Therapy
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• v.27 no.2
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• pp.145-156
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• 2015

Purpose : The purpose of this study is to evaluate the efficiency of Split VMAT planning(Contouring rectum divided into an upper and a lower for reduce rectum dose) compare to Conventional VMAT planning(Contouring whole rectum) for prostate cancer radiotherapy involving pelvic lymph nodes. Materials and Methods : A total of 9 cases were enrolled. Each case received radiotherapy with Split VMAT planning to the prostate involving pelvic lymph nodes. Treatment was delivered using TrueBeam STX(Varian Medical Systems, USA) and planned on Eclipse(Ver. 10.0.42, Varian, USA), PRO3(Progressive Resolution Optimizer 10.0.28), AAA(Anisotropic Analytic Algorithm Ver. 10.0.28). Lower rectum contour was defined as starting 1cm superior and ending 1cm inferior to the prostate PTV, upper rectum is a part, except lower rectum from the whole rectum. Split VMAT plan parameters consisted of 10MV coplanar $360^{\circ}$ arcs. Each arc had $30^{\circ}$ and $30^{\circ}$ collimator angle, respectively. An SIB(Simultaneous Integrated Boost) treatment prescription was employed delivering 50.4Gy to pelvic lymph nodes and 63~70Gy to the prostate in 28 fractions. $D_{mean}$ of whole rectum on Split VMAT plan was applied for DVC(Dose Volume Constraint) of the whole rectum for Conventional VMAT plan. In addition, all parameters were set to be the same of existing treatment plans. To minimize the dose difference that shows up randomly on optimizing, all plans were optimized and calculated twice respectively using a 0.2cm grid. All plans were normalized to the prostate $PTV_{100%}$ = 90% or 95%. A comparison of $D_{mean}$ of whole rectum, upperr ectum, lower rectum, and bladder, $V_{50%}$ of upper rectum, total MU and H.I.(Homogeneity Index) and C.I.(Conformity Index) of the PTV was used for technique evaluation. All Split VMAT plans were verified by gamma test with portal dosimetry using EPID. Results : Using DVH analysis, a difference between the Conventional and the Split VMAT plans was demonstrated. The Split VMAT plan demonstrated better in the $D_{mean}$ of whole rectum, Up to 134.4 cGy, at least 43.5 cGy, the average difference was 75.6 cGy and in the $D_{mean}$ of upper rectum, Up to 1113.5 cGy, at least 87.2 cGy, the average difference was 550.5 cGy and in the $D_{mean}$ of lower rectum, Up to 100.5 cGy, at least -34.6 cGy, the average difference was 34.3 cGy and in the $D_{mean}$ of bladder, Up to 271 cGy, at least -55.5 cGy, the average difference was 117.8 cGy and in $V_{50%}$ of upper rectum, Up to 63.4%, at least 3.2%, the average difference was 23.2%. There was no significant difference on H.I., and C.I. of the PTV among two plans. The Split VMAT plan is average 77 MU more than another. All IMRT verification gamma test results for the Split VMAT plan passed over 90.0% at 2 mm / 2%. Conclusion : As a result, the Split VMAT plan appeared to be more favorable in most cases than the Conventional VMAT plan for prostate cancer radiotherapy involving pelvic lymph nodes. By using the split VMAT planning technique it was possible to reduce the upper rectum dose, thus reducing whole rectal dose when compared to conventional VMAT planning. Also using the split VMAT planning technique increase the treatment efficiency.

• Journal of KIISE:Software and Applications
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• v.33 no.4
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• pp.365-377
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• 2006

Proteins are known to perform a biological function by interacting with other proteins or compounds. Since protein interaction is intrinsic to most cellular processes, prediction of protein interaction is an important issue in post-genomic biology where abundant interaction data have been produced by many research groups. In this paper, we present an associative feature mining method to predict implicit protein-protein interactions of Saccharomyces cerevisiae from public protein interaction data. We discretized continuous-valued features by maximal interdependence-based discretization approach. We also employed feature dimension reduction filter (FDRF) method which is based on the information theory to select optimal informative features, to boost prediction accuracy and overall mining speed, and to overcome the dimensionality problem of conventional data mining approaches. We used association rule discovery algorithm for associative feature and rule mining to predict protein interaction. Using the discovered associative feature we predicted implicit protein interactions which have not been observed in training data. According to the experimental results, the proposed method accomplished about 96.5% prediction accuracy with reduced computation time which is about 29.4% faster than conventional method with no feature filter in association rule mining.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.4
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• pp.43-54
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• 2007

This paper presents design and verification of a face detection hardware for real time application. Face detection algorithm detects rough face position based on already acquired feature parameter data. The hardware is composed of five main modules: Integral Image Calculator, Feature Coordinate Calculator, Feature Difference Calculator, Cascade Calculator, and Window Detection. It also includes on-chip Integral Image memory and Feature Parameter memory. The face detection hardware was verified by using S3C2440A CPU of Samsung Electronics, Virtex4LX100 FPGA of Xilinx, and a CCD Camera module. Our design uses 3,251 LUTs of Xilinx FPGA and takes about 1.96${\sim}$0.13 sec for face detection depending on sliding-window step size, when synthesized for Virtex4LX100 FPGA. When synthesized on Magnachip 0.25um ASIC library, it uses about 410,000 gates (Combinational area about 345,000 gates, Noncombinational area about 65,000 gates) and takes less than 0.5 sec for face realtime detection. This size and performance shows that it is adequate to use for embedded system applications. It has been fabricated as a real chip as a part of XF1201 chip and proven to work.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.11-21
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• 2010

To aim at improving performance and reflecting user's needs of retrieval, the number of researches has been actively conducted in recent year as the quantity of information and generation of the web pages exceedingly increase. One of alternative approaches can be a tagging system. It makes users be able to provide a representation of metadata including writings, pictures, and movies etc. called tag and be convenient in use of retrieval of internet resources. Tags similar to keywords play a critical role in maintaining target pages. However, they still needs time consuming labors to annotate tags, which sometimes are found to be a hinderance caused by overuse of tagging. In this paper, we present an automatic tagging scheme for a solution of current tagging system conveying drawbacks and inconveniences. To realize the approach, face recognition-based tagging system on SNS is proposed by building a face area detection procedure, linear-based classification and boosting algorithm. The proposed novel approach of tagging service can increase possibilities that utilized SNS more efficiently. Experimental results and performance analysis are shown as well.