• Title/Summary/Keyword: run probability

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Performance Improvement for Tracking Small Targets (고기동 표적 추적 성능 개선을 위한 연구)

  • Jung, Yun-Sik;Kim, Kyung-Su;Song, Taek-Lyul
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.11
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    • pp.1044-1052
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    • 2010
  • In this paper, a new realtime algorithm called the RTPBTD-HPDAF (Recursive Temporal Profile Base Target Detection with Highest Probability Data Association Filter) is presented for tracking fast moving small targets with IIR (Imaging Infrared) sensor systems. Spatial filter algorithms are mainly used for target in IIR sensor system detection and tracking however they often generate high density clutter due to various shapes of cloud. The TPBTD (Temporal Profile Base Target Detection) algorithm based on the analysis of temporal behavior of individual pixels is known to have good performance for detection and tracking of fast moving target with suppressing clutter. However it is not suitable to detect stationary and abruptly maneuvering targets. Moreover its computational load may not be negligible. The PTPBTD-HPDAF algorithm proposed in this paper for real-time target detection and tracking is shown to be computationally cheap while it has benefit of tracking targets with abrupt maneuvers. The performance of the proposed RTPBTD-HPDAF algorithm is tested and compared with the spatial filter with HPDAF algorithm for run-time and track initiation at real IIR video.

The Effect of Bribery on Firm Innovation: An Analysis of Small and Medium Firms in Vietnam

  • NGUYEN, Toan Ngoc
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.5
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    • pp.259-268
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    • 2020
  • This study aims to provide empirical evidence on the causal relationship between bribery and firm innovation. To this end, we use a micro-dataset of small and medium firms in Vietnam surveyed in 2015. Given the binary nature of the dependent variable, a simple probit regression model is employed. However, as bribery variable is potentially endogenous, a simple probit regression may give biased estimates. We deal with the potential endogeneity by making use of the bivariate probit model. A property of the bivariate probit model is that it can produce efficient estimates of a typical probit model with endogenous binary explanatory variable. A Hausman-like likelihood ratio test is implemented following the estimation to test the existence of endogeneity. We find that bribery significantly undermines firm innovation. Also, firms run by household appear less innovative. The probability of innovation diminishes significantly if firm owners or managers have previous experience in firm products. As expected, larger firms seem to be more innovative. Exporters tend to be more innovative compared to non-exporters. Our findings provide support to the hypothesis that bribery is detrimental to firm innovation and, thus, innovation may be a mediating channel, through which, bribery impedes firm long-term performance.

A Study on the Rail Pone of Transition Curve Track to Speed Up of Tilting train (틸팅차량 완화곡선 증속 주행시 궤도작용력 검토)

  • Shin, Tae-Hyoung;Choi, Jung-Youl;Eum, Ki-Young;Park, Yong-Gul
    • Proceedings of the KSR Conference
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    • 2009.05a
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    • pp.529-538
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    • 2009
  • A trial run of locally-developed tilting train has been in process on Chungbuk line since the test vehicle was first produced. For the system stabilization, interface verification among the systems including track, structure, catenary and signaling system, not to mention the rolling stock, is very crucial. Therefore, in this study, the dynamic rail force of the tilting (Hanvit 200), high-speed (KTX) and general (Mugunghwa) vehicle caused by driving in transition curve track was measured. And, it compared the tilting response with the other by using the measured wheel load data in transition curve track, and then evaluated probability the range of wheel load fluctuation for the variable dynamic vertical and lateral wheel load. As a result, a range of wheel load by occured a change of cant from the high-speed and general vehicle which had fixed bogie structure was distributed throughout small deviation (${\Delta}8{\sim}13kN$). Otherwise, in case of the tilting train which was consisted of the pendulum bogie structure was distributed wide range about large deviation (${\Delta}25{\sim}28kN$) by changed of cant.

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Paradox in collective history-dependent Parrondo games (집단 과거 의존 파론도 게임의 역설)

  • Lee, Ji-Yeon
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.4
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    • pp.631-641
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    • 2011
  • We consider a history-dependent Parrondo game in which the winning probability of the present trial depends on the results of the last two trials in the past. When a fraction of an infinite number of players are allowed to choose between two fair Parrondo games at each turn, we compare the blind strategy such as a random sequence of choices with the short-range optimization strategy. In this paper, we show that the random sequence of choices yields a steady increase of average profit. However, if we choose the game that gives the higher expected profit at each turn, surprisingly we are not supposed to get a long-run positive profit for some parameter values.

Maritime radar display unit based on PC for safe ship navigation

  • Bae, Jin-Ho;Lee, Chong-Hyun;Hwang, Chang-Ku
    • International Journal of Ocean System Engineering
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    • v.1 no.1
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    • pp.52-59
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    • 2011
  • A prototype radar display unit was implemented using inexpensive off-the-shelf components, including a nonlinear estimation algorithm for the target tracking in a clutter environment. Two custom designed boards; an analog signal processing board and a DSP board, can be plugged into an expansion slot of a personal computer (PC) to form a maritime radar display unit. Our system provided all the functionality specified in the International Maritime Organization (IMO) resolution A422(XI). The analog signal processing board was used for A/D conversion as well as rain and sea clutter suppression. The main functions of the DSP board were scan conversion and video overlay operations. A host PC was used to run the tracking algorithm of targets in clutter, using the discrete-time Bayes optimal (nonlinear, and non-Gaussian) estimation method, and the graphic user interface (GUI) software for Automatic Radar Plotting Aid (ARPA). The proposed tracking method recursively found the entire probability density function of the target position and velocity by converting into linear convolution operations.

A Study on the Adjustment Synthetic Control Chart Pattern for Detecting Shifts using Individual Observations in Start-Up Process (초기공정에서 공정변화에 대한 개별 관측치를 이용한 수정된 합성 관리도 연구)

  • 지선수
    • Journal of Korea Society of Industrial Information Systems
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    • v.7 no.4
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    • pp.53-58
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    • 2002
  • This paper presents a adjustment synthetic control chart that is an integration of the Shewhart X chart and the conforming run length(CRL) chart. The application of the adjustment synthetic control chart my therefore substantially enhance the effectiveness process control for manufacturing. In the synthetic control chart, denotes the average number of the X sample required to detect a process shift. The synthetic control chart outperforms the EWM chart and the X chart when σ is greater than 0.75σ. And the X-CRL charts suggested above evaluate using the conditional probability.

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Do Risk-Taking, Innovativeness, and Proactivity Affect Business Performance of SMEs? A Case Study in Bangladesh

  • RAHAMAN, Md. Atikur;LUNA, Kaniz Fatema;PING, Zhao Lin;ISLAM, Mohammad Saiyedul;KARIM, Md. Mobarak
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.5
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    • pp.689-695
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    • 2021
  • In the current technology-driven era, Small and medium enterprises (SMEs) have been deemed as one of the leading and prominent drivers of sustainable economic progress in emerging and developing economies such as in the Bangladesh context. Hence, it is of significance to understand what might fuel accelerating performance of SME business as increased SME performance will bring about more sustainability and strong development of SME sector within the country, through which more employment is anticipated to be generated. Therefore, the current study examines the impact of three factors: risk-taking, innovativeness, and proactiveness on SME performance in Bangladesh. The study has gathered data from SME entities in Dhaka city of Bangladesh, by applying a non-probability sampling strategy. 250 SME owners were contacted to act as respondents and finally, 180 SME owners fully completed the survey questionnaire, indicating that the final sample size is n=180. SPSS is used as a purpose of testing the hypotheses by considering a 5% significance level as acceptance criteria of the hypothesis. Hierarchical regression analysis was run to understand the impact of control variables and independent variables on SME performance and found that age of business, risk-taking, innovativeness, and proactiveness have an important impact on SME performance in Bangladesh.

Inter-clustering Cooperative Relay Selection Schemes for 5G Device-to-device Communication Networks

  • Nasaruddin, Nasaruddin;Yunida, Yunida;Adriman, Ramzi
    • Journal of information and communication convergence engineering
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    • v.20 no.3
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    • pp.143-152
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    • 2022
  • The ongoing adoption of 5G will increase the data traffic, throughput, multimedia services, and power consumption for future wireless applications and services, including sensor and mobile networks. Multipath fading on wireless channels also reduces the system performance and increases energy consumption. To address these issues, device-to-device (D2D) and cooperative communications have been proposed. In this study, we propose two inter-clustering models using the relay selection method to improve system performance and increase energy efficiency in cooperative D2D networks. We develop two inter-clustering models and present their respective algorithms. Subsequently, we run a computer simulation to evaluate each model's outage probability (OP) performance, throughput, and energy efficiency. The simulation results show that inter-clustering model II has the lowest OP, highest throughput, and highest energy efficiency compared with inter-clustering model I and the conventional inter-clustering-based multirelay method. These results demonstrate that inter-clustering model II is well-suited for use in 5G overlay D2D and cellular communications.

Development of a GIS-based Computer Program to Design Countermeasures against Debris Flows (GIS기반 토석류 산사태 대응공법 설계 프로그램 개발)

  • Song, Young-Suk;Chae, Byung-Gon
    • The Journal of Engineering Geology
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    • v.23 no.1
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    • pp.57-65
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    • 2013
  • We developed a computer program (CDFlow v. 1.0) to design countermeasures against debris flows in natural terrain. The program can predict the probability of landslides occurring in natural terrain and can estimate the zone of damage caused by a debris flow. It can also be used to design the location and size of countermeasures against the debris flow. The program is run using the ArcGIS Engine, which is one of the most well-known Geographic Information System (GIS) tools for developers. The quasi-dynamic wetness index and the infinite slope stability equation were applied to predict landslide probability as a type of slope safety factor. The calculated safety factor was compared with the required safety factor, and areas of high probable potential for landslides were then selected and represented on the digital map. The volume of debris flow was estimated using these areas of high probable potential for landslides and soil depth. The accumulated volume of debris flow can be calculated along the flow channel. To assess the accuracy of the program, it was applied to a real landslide site at Deoksan-ri, Inje-gun, Kangwon-Province, where four debris barriers have been installed in the watershed of the site. The results of soil tests and a field survey indicate that the program has great potential for estimating probable landslide areas and the trajectory of debris flows. Calculation of the capacity volume of existing debris barriers revealed that they had insufficient capacity to store the calculated amount of debris flow. Therefore, this program enables a rational estimation of the optimal location and size of debris barriers.

Recurrent Neural Network Modeling of Etch Tool Data: a Preliminary for Fault Inference via Bayesian Networks

  • Nawaz, Javeria;Arshad, Muhammad Zeeshan;Park, Jin-Su;Shin, Sung-Won;Hong, Sang-Jeen
    • Proceedings of the Korean Vacuum Society Conference
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    • 2012.02a
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    • pp.239-240
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    • 2012
  • With advancements in semiconductor device technologies, manufacturing processes are getting more complex and it became more difficult to maintain tighter process control. As the number of processing step increased for fabricating complex chip structure, potential fault inducing factors are prevail and their allowable margins are continuously reduced. Therefore, one of the key to success in semiconductor manufacturing is highly accurate and fast fault detection and classification at each stage to reduce any undesired variation and identify the cause of the fault. Sensors in the equipment are used to monitor the state of the process. The idea is that whenever there is a fault in the process, it appears as some variation in the output from any of the sensors monitoring the process. These sensors may refer to information about pressure, RF power or gas flow and etc. in the equipment. By relating the data from these sensors to the process condition, any abnormality in the process can be identified, but it still holds some degree of certainty. Our hypothesis in this research is to capture the features of equipment condition data from healthy process library. We can use the health data as a reference for upcoming processes and this is made possible by mathematically modeling of the acquired data. In this work we demonstrate the use of recurrent neural network (RNN) has been used. RNN is a dynamic neural network that makes the output as a function of previous inputs. In our case we have etch equipment tool set data, consisting of 22 parameters and 9 runs. This data was first synchronized using the Dynamic Time Warping (DTW) algorithm. The synchronized data from the sensors in the form of time series is then provided to RNN which trains and restructures itself according to the input and then predicts a value, one step ahead in time, which depends on the past values of data. Eight runs of process data were used to train the network, while in order to check the performance of the network, one run was used as a test input. Next, a mean squared error based probability generating function was used to assign probability of fault in each parameter by comparing the predicted and actual values of the data. In the future we will make use of the Bayesian Networks to classify the detected faults. Bayesian Networks use directed acyclic graphs that relate different parameters through their conditional dependencies in order to find inference among them. The relationships between parameters from the data will be used to generate the structure of Bayesian Network and then posterior probability of different faults will be calculated using inference algorithms.

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