• Title/Summary/Keyword: Key Performance Index

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A Comparative Study on the Management Performance of General Retail Companies in Korea: For Department store, TV home­shopping, Internet & Mobile shopping (우리나라 종합소매업의 경영성과에 관한 비교 연구 - 백화점, TV홈쇼핑, 온라인쇼핑몰 업태를 대상으로 -)

  • Koo, Kyoungmo
    • Journal of Korea Port Economic Association
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    • v.35 no.4
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    • pp.31-50
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    • 2019
  • The retail industry has been coping with changes in the retail market environment for the past decade or so. Using a total of 14 companies, this study aims to reveal the effect of differences in sales channels and retail business styles on the management performance of retail companies. The financial statements of these companies were used to analyze the five key indicators of their management performance. As research variables, sales channels, retail business style and business period were used as factors affecting their management performance. ANOVA or MANOVA was performed to test differences in management performance between groups according to the number of factors. The effect of three factors on the management performance of retail companies was found to be significant. The multi-comparison test revealed significant differences among retail business styles in terms of the five key indicators. TV home-shopping performed better than others in terms of stability and profitability. Internet and mobile shopping companies performed poorly in terms of profitability compared to others and performed higher than department stores in terms of growth, activity, and productivity.

Improved Gauss Pseudospectral Method for UAV Trajectory Planning with Terminal Position Constraints

  • Qingquan Hu;Ping Liu;Jinfeng Yang
    • Journal of Information Processing Systems
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    • v.19 no.5
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    • pp.563-575
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    • 2023
  • Trajectory planning is a key technology for unmanned aerial vehicles (UAVs) to achieve complex flight missions. In this paper, a terminal constraints conversion-based Gauss pseudospectral trajectory planning optimization method is proposed. Firstly, the UAV trajectory planning mathematical model is established with considering the boundary conditions and dynamic constraints of UAV. Then, a terminal constraint handling strategy is presented to tackle terminal constraints by introducing new penalty parameters so as to improve the performance index. Combined with Gauss-Legendre collocation discretization, the improved Gauss pseudospectral method is given in detail. Finally, simulation tests are carried out on a four-quadrotor UAV model with different terminal constraints to verify the performance of the proposed method. Test studies indicate that the proposed method performances well in handling complex terminal constraints and the improvements are efficient to obtain better performance indexes when compared with the traditional Gauss pseudospectral method.

Development and Application of a Performance Prediction Model for Home Care Nursing Based on a Balanced Scorecard using the Bayesian Belief Network (Bayesian Belief Network 활용한 균형성과표 기반 가정간호사업 성과예측모델 구축 및 적용)

  • Noh, Wonjung;Seomun, GyeongAe
    • Journal of Korean Academy of Nursing
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    • v.45 no.3
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    • pp.429-438
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    • 2015
  • Purpose: This study was conducted to develop key performance indicators (KPIs) for home care nursing (HCN) based on a balanced scorecard, and to construct a performance prediction model of strategic objectives using the Bayesian Belief Network (BBN). Methods: This methodological study included four steps: establishment of KPIs, performance prediction modeling, development of a performance prediction model using BBN, and simulation of a suggested nursing management strategy. An HCN expert group and a staff group participated. The content validity index was analyzed using STATA 13.0, and BBN was analyzed using HUGIN 8.0. Results: We generated a list of KPIs composed of 4 perspectives, 10 strategic objectives, and 31 KPIs. In the validity test of the performance prediction model, the factor with the greatest variance for increasing profit was maximum cost reduction of HCN services. The factor with the smallest variance for increasing profit was a minimum image improvement for HCN. During sensitivity analysis, the probability of the expert group did not affect the sensitivity. Furthermore, simulation of a 10% image improvement predicted the most effective way to increase profit. Conclusion: KPIs of HCN can estimate financial and non-financial performance. The performance prediction model for HCN will be useful to improve performance.

Development of Data Warehouse for Construction Material Management (건설공사 자재 관리를 위한 데이터 웨어하우스 개발)

  • Ryu, Han-Guk
    • Journal of the Korea Institute of Building Construction
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    • v.11 no.3
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    • pp.319-325
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    • 2011
  • During a construction project, construction managers must be provided with material information to help them to make decisions more efficiently without delaying the delivery of material. Construction work can be smoothly performed with the proper material supply. Construction duration depends on several material-related decisions, including the order, delivery, and allocation of material to the correct work location. Hence, it is worthwhile to introduce data warehouse techniques that generate subject-oriented and integrated data to construction material management. The data warehouse for construction material management can perform multidimensional analysis and then define KPIs (Key Performance Index) in order to provide construction managers with construction material information such as lead time, material delivery rate, material installation rate and so on. This research proposes a method of effectively facilitating large amounts of data in the operating systems during the construction management process. In other words, the proposed method can supply structured and multi-perspective material-related information using data warehouse techniques.

Extended Fitts' Law for Dual Task : Pointing on IVIS during Simulated Driving (다중작업에의 적용을 위한 Fitts' Law 확장 : 운전 중 IVIS 조작 작업을 대상으로)

  • Lee, Mingyu;Kim, Heejin;Chung, Min K.
    • Journal of Korean Institute of Industrial Engineers
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    • v.40 no.3
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    • pp.267-274
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    • 2014
  • The purpose of this study is to identify a relationship between the time taken and the characteristics of touch key for touch-screen-based in-vehicle information system (IVIS) and to suggest a new Fitts' law formula that is added a driving speed parameter. Many studies already have shown that Fitts' law is well fitted in various devices for primary tasks, but there is no study of Fitts' law for secondary task in dual-task situation. Fitts' law may not be applied to the secondary task as it is, because the secondary task performance can be affected by the amount of attention for the primary task. To verify this, we carried out an experiment that showed whether pointing task to touch-screen-based IVIS during driving is affected by driving speeds or not. In the experiment, 30 people were volunteered for participants and the participants carried out driving task and pointing task on the screen of IVIS simultaneously. We measured the time to point a touch key on IVIS for every condition (3 driving speeds${\times}5$ touch key sizes${\times}7$ distances between steering wheel and touch key). As a result, there was an effect of driving speed on the pointing time. As we extended the index of difficulty of the conventional Fitts' law formula by incorporating driving speed, we established an extended Fitts' law formula for pointing on IVIS, which showed better accordance with dual task situation. This study can be evidence that secondary task performance is affected by degree of concentration on primary task, and the extended Fitts' law formula can be useful to design interfaces of IVIS.

An Efficient Video Clip Matching Algorithm Using the Cauchy Function (커쉬함수를 이용한 효율적인 비디오 클립 정합 알고리즘)

  • Kim Sang-Hyul
    • Journal of the Institute of Convergence Signal Processing
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    • v.5 no.4
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    • pp.294-300
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    • 2004
  • According to the development of digital media technologies various algorithms for video clip matching have been proposed to match the video sequences efficiently. A large number of video search methods have focused on frame-wise query, whereas a relatively few algorithms have been presented for video clip matching or video shot matching. In this paper, we propose an efficient algorithm to index the video sequences and to retrieve the sequences for video clip query. To improve the accuracy and performance of video sequence matching, we employ the Cauchy function as a similarity measure between histograms of consecutive frames, which yields a high performance compared with conventional measures. The key frames extracted from segmented video shots can be used not only for video shot clustering but also for video sequence matching or browsing, where the key frame is defined by the frame that is significantly different from the previous frames. Experimental results with color video sequences show that the proposed method yields the high matching performance and accuracy with a low computational load compared with conventional algorithms.

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Enhancement of HCB Tree for Improving Retrieval Performance and Dynamic Environments (검색 성능 향상과 동적 환경을 위한 HCB 트리의 개선)

  • Kim, Sung Wan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.2
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    • pp.365-371
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    • 2015
  • CB tree represents the binary trie by a compact binary sequence. However, retrieval time grows fast since the more keys stored in the trie, longer the binary sequences are. In addition it is inefficient for frequent key insertion/deletion. HCB tree is a hierarchical CB tree consisting of small binary tries. However it can not avoid shift operations and have to scan an additional table to refer child or parent trie. In order to improve retrieval performance and avoid shift operations when keys are inserted or deleted, we in this paper represent each separated trie by a full binary trie and then assign the unique identifier to it. Finally the theoretical evaluations show that both the proposed approach and HCB tree provides better than CB tree for key retrieval. The proposed approach shows the highest performance in case of key insertion/deletion and moreover requires only 71%~89% of storage as compared with CB tree.

A Study on the Development Model and Establishment of KPIs for the Realization of Social Value in Port Authority (항만공사의 사회적 가치 실현을 위한 추진모델과 평가지표 구축연구)

  • Kim, Seung-Chul;Pyo, Hee-Dong
    • Korea Trade Review
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    • v.43 no.6
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    • pp.193-214
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    • 2018
  • The role of social value in public institutions has recently been emphasized. The purpose of this paper is to present key performance indicators(KPIs) and a development model for the realization of social value for port authorities. KPIs that could be quantitatively measured are presented with the five social value assessment indicators of the government management evaluation system for public institutions. Through the analysis of vision, mission and social value promotion strategies and stakeholders for each port authority, the concept of a customer-specific social value model is presented.

Correlations of Genic Heterozygosity and Variances with Heterosis in a Pig Population Revealed by Microsatellite DNA Marker

  • Zhang, J.H.;Xiong, Y.Z.;Deng, C.Y.
    • Asian-Australasian Journal of Animal Sciences
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    • v.18 no.5
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    • pp.620-625
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    • 2005
  • Correlation of microsatellite heterozygosity with performance or heterosis was reported in wild animal populations and domestic animal populations, but the correlation with heterosis in a crossbreeding F$_1$ pig population remained uncertain. To explore this, we had random selected and mated Yorkshire${\times}$Meishan (F, n = 82) and their reciprocal (G, n = 47) to F$_1$, and used the two straightbreds as control groups (Yorkshire = 34, Meishan = 55), and observed the heterosis of birth weight (BWT), average daily gain (ADG) and feed and meat ratio (FMR). Two Kinds of measurement-individual heterozygosity (IH) and individual mean d$^2$ (lg value, ID) were used as index of heterozygosity and variance from 39 microsatellite marker loci to perform univariate regression analysis against heterosis. We detected significant correlation of IH with BWT in all of F$_1$ (F+G) and in F. We observed significant correlation of ID with ADG in all of F$_1$ (F+G), and with FMR in all of F$_1$ (F+G) and in F. There was significant maternal effect on heterosis, which was indicated by significant difference of means and distribution of heterosis between F and G. This difference was consistent with distributions of IH and ID, and with difference of means in F and G. From this study, it would be suggested that the two kinds of genetic index could be used to explore the genetic basis of heterosis in crossbreeding populations but could not determine which is better.

Real-time prediction on the slurry concentration of cutter suction dredgers using an ensemble learning algorithm

  • Han, Shuai;Li, Mingchao;Li, Heng;Tian, Huijing;Qin, Liang;Li, Jinfeng
    • International conference on construction engineering and project management
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    • 2020.12a
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    • pp.463-481
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    • 2020
  • Cutter suction dredgers (CSDs) are widely used in various dredging constructions such as channel excavation, wharf construction, and reef construction. During a CSD construction, the main operation is to control the swing speed of cutter to keep the slurry concentration in a proper range. However, the slurry concentration cannot be monitored in real-time, i.e., there is a "time-lag effect" in the log of slurry concentration, making it difficult for operators to make the optimal decision on controlling. Concerning this issue, a solution scheme that using real-time monitored indicators to predict current slurry concentration is proposed in this research. The characteristics of the CSD monitoring data are first studied, and a set of preprocessing methods are presented. Then we put forward the concept of "index class" to select the important indices. Finally, an ensemble learning algorithm is set up to fit the relationship between the slurry concentration and the indices of the index classes. In the experiment, log data over seven days of a practical dredging construction is collected. For comparison, the Deep Neural Network (DNN), Long Short Time Memory (LSTM), Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and the Bayesian Ridge algorithm are tried. The results show that our method has the best performance with an R2 of 0.886 and a mean square error (MSE) of 5.538. This research provides an effective way for real-time predicting the slurry concentration of CSDs and can help to improve the stationarity and production efficiency of dredging construction.

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