• Journal of Electrical Engineering and Technology
• /
• v.12 no.1
• /
• pp.402-410
• /
• 2017

For many years, researchers in face description area have been representing and recognizing faces based on different methods that include subspace discriminant analysis, statistical learning and non-statistics based approach etc. But still automatic face recognition remains an interesting but challenging problem. This paper presents a novel and efficient face image representation method based on Optimized Local Ternary Pattern (OLTP) texture features. The face image is divided into several regions from which the OLTP texture feature distributions are extracted and concatenated into a feature vector that can act as face descriptor. The recognition is performed using nearest neighbor classification method with Chi-square distance as a similarity measure. Extensive experimental results on Yale B, ORL and AR face databases show that OLTP consistently performs much better than other well recognized texture models for face recognition.

• Journal of the Economic Geographical Society of Korea
• /
• v.16 no.1
• /
• pp.1-16
• /
• 2013

This study investigates the spatial distribution characteristics of Korean fashion industries during the last decade, in which the economic geography of fashion industries has changed dynamically with economic globalization and "thus resulted in increased" demand "of" diversification. In particular, this study examines the spatial distribution patterns of fashion industries in the Seoul metropolitan area where fashion industries are highly agglomerated. For the purpose, this study applies Moran's I Index of spatial autocorrelation analysis for seven functional sectors of fashion industries related to fashion production. The global and local agglomeration patterns are examined for each functional sector. The results clarify the distinction in the spatial agglomeration patterns among the seven functional sectors of fashion industries in the Seoul Metropolitan area. Logit models are developed to examine the interrelationships among functional sectors in their spatial agglomeration distribution patterns. By conducting binary logistic regression analysis, we find out how the spatial agglomeration of each functional sector is related to the others.

• Journal of Oriental Neuropsychiatry
• /
• v.16 no.1
• /
• pp.185-192
• /
• 2005

Objectives : This study is for discovering the clinical Features of the sleep in ordinary symptoms based on the Sasang Constitution. The result of this study could be helpful to understand and to identify the patients as Soeumin in contrast with the other constitutions-Soyangin, Taeumin and Taeyangin. Methods : There were 1,229 patients(700 female), who answered the questionnaire about their ordinary sleeping patterns. They had been diagnosed, including their clinical Sasang Constitution, by the Sasang Constitution specialist at Bundang Oriental Hospital of Dongguk University. By applying the binary logistic regression analysis, we can measure the characteristics and the influence of ordinary sleeping patterns to the dependent variable(Sasang Constitution). Results : As a result of the binary logistic analysis on the observed questionnaire, we found the characteristics of the ordinary sleeping patterns on Soeumin in contrast the other constitutions. Firstly, Soeumin has a tendency that he wouldn't snore well in comparison with the others. Secondly, Soeumin has a tendency that he will dreams more, when he sleeps in contrast with the others. Thirthly, Soeumin has a tendency that he will sleep longer than 6-7hours. Fourthly, Soeumin has a tendency that he will struggle during sleeping in contrast with the others. Conclustion : This study will be used to identify patients as Soeumin in contrast with the others-Soyangin, Taeumin and Taeyangin.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.11 no.2
• /
• pp.97-105
• /
• 2016

Microcontrollers (MCUs) for endpoint smart sensor devices of internet-of-thing (IoT) are being implemented as system-on-chip (SoC) with on-chip instruction flash memory, in which user firmware is embedded. MCUs directly fetch binary code-based instructions through bit-line sense amplifier (S/A) integrated with on-chip flash memory. The S/A compares bit cell current with reference current to identify which data are programmed. The S/A in reading '0' (erased) cell data consumes a large sink current, which is greater than off-current for '1' (programmed) cell data. The main motivation of our approach is to reduce the number of accesses of erased cells by binary code level transformation. This paper proposes a built-in write/read path architecture using binary code inversion method based on hot-spot region detection of instruction code access to reduce sensing current in S/A. From the profiling result of instruction access patterns, hot-spot region of an original compiled binary code is conditionally inverted with the proposed bit-inversion techniques. The de-inversion hardware only consumes small logic current instead of analog sink current in S/A and it is integrated with the conventional S/A to restore original binary instructions. The proposed techniques are applied to the fully-custom designed MCU with ARM Cortex-M0$^{TM}$ using 0.18um Magnachip Flash-embedded CMOS process and the benefits in terms of power consumption reduction are evaluated for Dhrystone$^{TM}$ benchmark. The profiling environment of instruction code executions is implemented by extending commercial ARM KEIL$^{TM}$ MDK (MCU Development Kit) with our custom-designed access analyzer.

• 제어로봇시스템학회:학술대회논문집
• /
• 1999.10a
• /
• pp.278-280
• /
• 1999

This paper proposes controlling of temperature in an oven by using 4 bits Integral - Cycle Binary Rate Modulation (IBRM) method and ac line with frequency 50 Hz. Microcontroller MCS-51 controls IBRM according to Proportional Integral controller (PI) function. Discrete signals are used in the system modeled by using Ziegler Nichols principle for analyzing the stability before designing the system. This procedure makes it easy to investigate system response. The system is implemented by 4 bits digital circuit which gives 320 patterns of ac signal fur controlling the generation of energy for 3,000 watts thermal coil every 20 ms of each cycle. We divide scan time (Ts$\sub$n/) in to 20 intervals, 1 ms interval is selected to generate 16 patterns IBRM. Because of this method gives the ripple lower than 2% it generates less noise fur system. Moreover, we can consider whole system from the time model of control procedure and IBRM algorithm at 40-200$^{\circ}C$ with ${\pm}$ 1$^{\circ}C$ error in the 1 cubic meter oven.

• Communications for Statistical Applications and Methods
• /
• v.25 no.3
• /
• pp.321-328
• /
• 2018

In clinical trials with repeated measurements, the time-averaged difference (TAD) may provide a more powerful evaluation of treatment efficacy than the rate of changes over time when the treatment effect has rapid onset and repeated measurements continue across an extended period after a maximum effect is achieved (Overall and Doyle, Controlled Clinical Trials, 15, 100-123, 1994). The sample size formula has been investigated by many researchers for the evaluation of TAD in two treatment groups. For the evaluation of TAD in multi-arm trials, Zhang and Ahn (Computational Statistics & Data Analysis, 58, 283-291, 2013) and Lou et al. (Communications in Statistics-Theory and Methods, 46, 11204-11213, 2017b) developed the sample size formulas for continuous outcomes and count outcomes, respectively. In this paper, we derive a sample size formula to evaluate the TAD of the repeated binary outcomes in multi-arm trials using the generalized estimating equation approach. This proposed sample size formula accounts for various correlation structures and missing patterns (including a mixture of independent missing and monotone missing patterns) that are frequently encountered by practitioners in clinical trials. We conduct simulation studies to assess the performance of the proposed sample size formula under a wide range of design parameters. The results show that the empirical powers and the empirical Type I errors are close to nominal levels. We illustrate our proposed method using a clinical trial example.

• Journal of the Korean Solar Energy Society
• /
• v.22 no.2
• /
• pp.39-47
• /
• 2002

The thermosyphon SDHWS and the loop type thermosyphon systems are widely used for domestic hot water system. The loop type thermosyphon is a circulation device for transferring the heat produced at the evaporator to the condenser area in the loop. In this study, the operating characteristics of various working fluids being used have been identified. The working fluids employed in the study were ethanol. water, and a binary mixture of ethanol and water. The volume of working fluid used in this study were 30%, 40%, 50%, 60% and 70% of evaporator volume. It is observed that, in the thermosyphon with low volume of working fluid, such as 30% or 40%, the fluid was dried out. The flow pattern and mechanism of the heat transfer were identified through this study. Flow patterns of the binary mixture working fluid were also investigated, and the patterns were recorded in the camera. The system parameters were calculated using the thermal performance data. Modelling of the system was carried out using PSTAR method and TRNSYS program.

• Journal of Information Processing Systems
• /
• v.14 no.2
• /
• pp.469-486
• /
• 2018

We propose an enhanced version of the local binary pattern (LBP) operator for texture extraction in images in the context of image retrieval. The novelty of our proposal is based on the observation that the LBP exploits only the lowest kind of local information through the global histogram. However, such global Histograms reflect only the statistical distribution of the various LBP codes in the image. The block based LBP, which uses local histograms of the LBP, was one of few tentative to catch higher level textural information. We believe that important local and useful information in between the two levels is just ignored by the two schemas. The newly developed method: gradual locality integration of binary patterns (GLIBP) is a novel attempt to catch as much local information as possible, in a gradual fashion. Indeed, GLIBP aggregates the texture features present in grayscale images extracted by LBP through a complex structure. The used framework is comprised of a multitude of ellipse-shaped regions that are arranged in circular-concentric forms of increasing size. The framework of ellipses is in fact derived from a simple parameterized generator. In addition, the elliptic forms allow targeting texture directionality, which is a very useful property in texture characterization. In addition, the general framework of ellipses allows for taking into account the spatial information (specifically rotation). The effectiveness of GLIBP was investigated on the Corel-1K (Wang) dataset. It was also compared to published works including the very effective DLEP. Results show significant higher or comparable performance of GLIBP with regard to the other methods, which qualifies it as a good tool for scene images retrieval.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.4
• /
• pp.1807-1823
• /
• 2016

Local Binary Pattern (LBP) and its variants have powerful discriminative capabilities but most of them just consider each LBP code independently. In this paper, we propose sub oriented histograms of LBP for smoke detection and image classification. We first extract LBP codes from an image, compute the gradient of LBP codes, and then calculate sub oriented histograms to capture spatial relations of LBP codes. Since an LBP code is just a label without any numerical meaning, we use Hamming distance to estimate the gradient of LBP codes instead of Euclidean distance. We propose to use two coordinates systems to compute two orientations, which are quantized into discrete bins. For each pair of the two discrete orientations, we generate a sub LBP code map from the original LBP code map, and compute sub oriented histograms for all sub LBP code maps. Finally, all the sub oriented histograms are concatenated together to form a robust feature vector, which is input into SVM for training and classifying. Experiments show that our approach not only has better performance than existing methods in smoke detection, but also has good performance in texture classification.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.3
• /
• pp.11-25
• /
• 2012

We present the method to infer Context-Free Grammars by applying genetic algorithm to the Binary Third-order Recurrent Neural Networks(BTRNN). BTRNN is a multiple-layered architecture of recurrent neural networks, each of which is corresponding to an input symbol, and is combined with external stack. All parameters of BTRNN are represented as binary numbers and each state transition is performed with any stack operation simultaneously. We apply Genetic Algorithm to BTRNN chromosomes and obtain the optimal BTRNN inferring context-free grammar of positive and negative input patterns. This proposed method infers BTRNN, which includes the number of its states equal to or less than those of existing methods of Discrete Recurrent Neural Networks, with less examples and less learning trials. Also BTRNN is superior to the recent method of chromosomes representing grammars at recognition time complexity because of performing deterministic state transitions and stack operations at parsing process. If the number of non-terminals is p, the number of terminals q, the length of an input string k, and the max number of BTRNN states m, the parallel processing time is O(k) and the sequential processing time is O(km).