• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.145-156
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• 2015

Incorporation of individual learning and forgetting behaviors within worker-task assignment models produces a mixed integer nonlinear program (MINLP) problem, which is difficult to solve as a NP hard due to its nonlinearity in the objective function. Previous studies commonly assume homogeneity among workers in workforce scheduling that takes account of learning and forgetting characteristics. This paper expands previous researches by considering heterogeneous individual learning/forgetting, and investigates the impact of worker heterogeneity in initial expertise, steady-state productivity, learning and forgetting on system performance to assist manager's decision-making in worker-task assignments without tackling complex MINLP models. In order to understand the performance implications of workforce heterogeneity, this paper examines analytically how heterogeneity in each of the four parameters of the exponential learning and forgetting (L/F) model affects system performance in three cases : consecutive assignments with no break, n breaks of s-length each, and total b break-periods occurred over T periods. The study presents the direction of change in worker performance under different assignment schedules as the variance in initial expertise, steady-state productivity, learning or forgetting increases. Thus, it implies whether having more heterogenous workforce in terms of each of four parameters in the L/F model is desired or not in different schedules from the perspective of system productivity measurement.

• Bulletin of the Korean Chemical Society
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• v.29 no.1
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• pp.197-201
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• 2008

Conformational heterogeneity of directly linked multiporphyrin arrays with larger molecular length retards their utilities in practical applications such as two-photon absorption and molecular photonic wire. In this regard, here we adopted a way to overcome the conformational heterogeneity through hydrogen bonding by selective binding of meso aryl substituents of porphyrins (host) with urea (guest) to form helical structure. Using steady-state and time-resolved spectroscopy, we observed the enhanced fluorescence quantum yield by ~1.8 to 2.4 times, enhanced anisotropy values and the disappearance of fast fluorescence decay component in the host-guest helical forms. In addition, the enhanced nonlinear optical responses of helical arrays infer the extended inter-porphyrin electronic coupling due to a significant change in dihedral angle between the neighboring porphyrin moieties. The current host-guest strategy will provide a guideline to improve the structural homogeneity of the photonic wire.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.105-115
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• 2021

The purpose of this study is to present the effect of differences in individual coping and organizational homogeneity culture on information security compliance from an exploratory perspective. The study divided groups into individual coping (task-oriented, emotion-oriented) and organizational homogeneity culture (homogeneity, heterogeneity), confirms the difference in information security for each group through cross-design and presents a multiple mediation model between information security factors. As a result of the study, in the coping dimension, the average of the security compliance factors was higher in the emotion-oriented than the task-oriented, and in the homogeneity culture dimension, the average of the security compliance factors was higher in the homogeneity than the heterogeneity. Additionally, social influence and involvement had a multiple mediation effect on the relationship between information security awareness and compliance intention. The implications of this study were to confirm the difference in the effect of individual decision-making styles on security compliance according to the organizational culture differences. The results suggest the necessity of applying a customized information security compliance model for each organization and individual characteristics.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1776-1784
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• 2017

There are two types of WSN(wireless sensor networks) in terms of sensor node's capability, that is, homogeneous or heterogeneous WSN. Even though the latter has better performance than the former, it requires some overhead for deploying nodes or clustering the network. In this paper, we propose a new scheme, called VHS(Virtual Heterogenous Sensor-Network), which uses a homogeneous WSN regarding energy in a heterogeneous way. The proposed scheme's performance has been evaluated and compared with other homogeneous schemes by simulation. The results are shown to be better than the other existing homogeneous schemes used in a sample sensor network application.

• Journal of applied mathematics & informatics
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• v.4 no.2
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• pp.501-512
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• 1997

In multiple linear regression model we have presupposed assumptions (independence normality variance homogeneity and so on) on error term. When case weights are given because of variance heterogeneity we can estimate efficiently regression parameter using weighted least squares estimator. Unfortunately this estimator is sen-sitive to outliers like ordinary least squares estimator. Thus in this paper we proposed some statistics for detection of outliers in weighted least squares regression.

• Geomechanics and Engineering
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• v.34 no.6
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• pp.683-696
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• 2023

The destruction and fracture of rock masses are crucial components in engineering and there is an increasing demand for the study of the influence of rock mass heterogeneity on the safety of engineering projects. The numerical manifold method (NMM) has a unified solution format for continuous and discontinuous problems. In most NMM studies, material homogeneity has been assumed and despite this simplification, fracture mechanics remain complex and simulations are inefficient because of the complicated topology updating operations that are needed after crack propagation. These operations become computationally expensive especially in the cases of heterogeneous materials. In this study, a heterogeneous model algorithm based on stochastic theory was developed and introduced into the NMM. A new fracture algorithm was developed to simulate the rupture zone. The algorithm was validated for the examples of the four-point shear beam and semi-circular bend. Results show that the algorithm can efficiently simulate the rupture zone of heterogeneous rock masses. Heterogeneity has a powerful effect on the macroscopic failure characteristics and uniaxial compressive strength of rock masses. The peak strength of homogeneous material (with heterogeneity or standard deviation of 0) is 2.4 times that of heterogeneous material (with heterogeneity of 11.0). Moreover, the local distribution of parameter values can affect the configuration of rupture zones in rock masses. The local distribution also influences the peak value on the stress-strain curve and the residual strength. The post-peak stress-strain curve envelope from 60 random calculations can be used as an estimate of the strength of engineering rock masses.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Structural Engineering and Mechanics
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• v.37 no.2
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• pp.215-231
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• 2011

As a brittle and heterogeneous material, concrete behaves differently under different stress conditions and its bulk strength is loading rate dependent. To a large extent, the varying behavioural properties of concrete can be explained by the mechanical failure processes at a mesoscopic level. The development of a computational mesoscale model in a general finite element environment, as presented in the preceding companion paper (Part 1), makes it possible to investigate into the underlying mechanisms governing the bulk-scale behaviour of concrete under a variety of loading conditions and to characterise the variation in quantitative terms. In this paper, we first present a series of parametric studies on the behaviour of concrete material under quasi-static compression and tension conditions. The loading-face friction effect, the possible influences of the non-homogeneity within the mortar and ITZ phases, and the effect of randomness of coarse aggregates are examined. The mesoscale model is then applied to analyze the dynamic behaviour of concrete under high rate loading conditions. The potential contribution of the mesoscopic heterogeneity towards the generally recognized rate enhancement of the material compressive strength is discussed.

• International Journal of Safety
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• v.6 no.2
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• pp.22-26
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• 2007

An episode of corona is a heterogeneity-caused electric discharge that occurs when electric fields are formed layer on layer and concentrated on an electrode. Electric wires built at the tip of 154kV private facilities use dead end clamp spawns corona from homogeneity caused by field concentration. Corona induces power loss, noise, insulator failure and more. In this research, we've studied the characteristics of coronas that take place in porcelain insulators and terminal electric wires of supporting hard wares (dead end clamp) that are set up as spares in the 154kV private facilities use hydroelectricity installations to support electric wires. Corona, which cannot be identified by regular methods, was measured utilizing UV image camera. As the result of measuring corona via UV image camera, we've confirmed that the depletion of insulators was accelerated following the wire end treatment method and validated the stress intensity of insulators at various lengths of bare wires caused by electric fields via FEMLAB. We have also proposed a new model for relieving homogeneity-caused field concentration, and after analyzing the proposed model via FEMLAB, we've confirmed that the concentration of field distribution was indeed reduced. Such results are exploited in installation of private facilities use equipments, maintenance of insulators and hard wares as well as safety enhancement, and are anticipated to be effectively utilized in corona prevention measures.

• Journal of Information Technology Applications and Management
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• v.19 no.1
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• pp.85-100
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• 2012

The development of technology causes a lot of change. Many researchers have insisted that the proliferation of cyber space changes the physical space. Their insistences have been accumulated into three aspects. Firstly, the proliferation of cyber space brings out the concentration in the physical space, secondly the decentralization and lastly both at the same time. In Korea, the concentration of plastic surgery clinics has taken place in Kangnam-gu area at similar period of the Internet proliferation. In this research, we execute empirical study of whether the concentration of plastic surgery in specific areas correlates with the proliferation of cyber space or not. In order to do this, we verified homogeneity of plastic surgery websites between Kangnam-gu and Non-Kangnam-gu areas. Also, we used three statistical and data-mining techniques which are Multi-discriminant analysis, Decision tree analysis and artificial neural network analysis. As a result, there was homogeneity between two different area plastic surgery clinics websites, but there was not big heterogeneity as well. Therefore, in this case of concentration of plastic surgery in Korea, the proliferation of cyber space restrictively correlates with the concentration of physical space.