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An Interplay of Wigner–Ville Distribution and 2D Hyper-Complex Quadratic-Phase Fourier Transform
(2023-02-01)
Bhat, Mohammad Younus
;
Dar, Aamir Hamid
;
Nurhidayat, Irfan
;
Pinelas, Sandra
Two-dimensional hyper-complex (Quaternion) quadratic-phase Fourier transforms (Q-QPFT) have gained much popularity in recent years because of their applications in many areas, including color image and signal processing. At the same time, the applications of Wigner–Ville distribution (WVD) in signal analysis and image processing cannot be ruled out. In this paper, we study the two-dimensional hyper-complex (Quaternion) Wigner–Ville distribution associated with the quadratic-phase Fourier transform (WVD-QQPFT) by employing the advantages of quaternion quadratic-phase Fourier transforms (Q-QPFT) and Wigner–Ville distribution (WVD). First, we propose the definition of the WVD-QQPFT and its relationship with the classical Wigner–Ville distribution in the quaternion setting. Next, we investigate the general properties of the newly defined WVD-QQPFT, including complex conjugate, symmetry-conjugation, nonlinearity, boundedness, reconstruction formula, Moyal’s formula, and Plancherel formula. Finally, we propose the convolution and correlation theorems associated with WVD-QQPFT.
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Forecasting Commercial Vehicle Demand Using a Multiple Linear Regression Model
(2023-01-01)
Aungkulanon, Pasura
;
Hirunwat, Anucha
;
Atthirawong, Walailak
;
Luangpaiboon, Pongchanun
The purpose of this study was to develop predictive equations and explore the elements that are having an effect on the demand for commercial vehicles in Thailand. The Consumer Price Index (CPI), the Business Sentiment Index (BSI), the price of diesel fuel, and the desire for electric cars were all factors that were considered while compiling this information from a database of newly registered automobiles. Multiple regression analysis, consisting of a linear model and a quadratic model, was utilized to investigate how the presence of a variety of influences influenced the demand for commercial cars. Both the Consumer Price Index and the relationship between the CPI and diesel fuel costs were shown to have a considerable impact on the demand for commercial vehicles. This was the case regardless of which factor was considered first. It was determined that there was a connection between these two parameters of 74.96% after doing the necessary calculations.
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Correlation of Reverse Logistics Performance to Solutions Using Structural Equation Modeling
(2019-12-01)
Sirisawat, Pornwasin
;
Kiatcharoenpol, Tossapol
Nowadays, reverse logistics (RL) is one of the key strategies in many industries, especially in the electronics industry due to increasing environmental awareness and sustainable management. The main aim of this research is to investigate the correlation of RL performance to solutions for RL practice of the electronics industry in Thailand. In this research, questionnaires were distributed to 417 companies in the electronics industry of Thailand. A conceptual model was developed and the model examined by using structural equation modeling (SEM). Both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used in this study. The hypotheses were tested in which RL performance was directly positively associated with the overall solutions for RL practices. RL performance was also indirectly positively associated with management & organization solutions, legal & technology solutions and collaboration and support solutions of the various solutions for RL practices. Empirical data was tested by using SEM and it was found that the proposed model could fit with the empirical data. The proposed results of this study will help to understand more about RL practices and could provide further direction for researchers and practitioners in the electronics industry and other related industries.
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Reliability indices estimation in PEA distribution system using ANNs
(2017-05-10)
Jiriwibhakorn, Somchat
;
Kaewmanee, Keattisak
The purpose of this paper is to present the methodology of SAIFI, SAIDI and CAIDI estimation of Provincial Electricity Authority (PEA) distribution network in Thailand using Artificial Neural Networks (ANNs). The data used in this study was obtained from the Reliability Program of PEA. The feeder data from Singburi substation was used as the samples of ANNs in this research from January 2010 to October 2012. The three inputs of ANNs for reliability indices (SAIFI, SAIDI and CAIDI) consist of the number of customers behind the protective equipment, the interruption frequency of protective equipment per month and the total time interruption per month. ANNs gave the outputs (SAIFI, SAIDI and CAIDI) faster with accurate results.
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Clustering Top-10 malware/bots based on download behavior
(2013-01-01)
Yukonhiatou, Chaxiong
;
Kittitornkun, Surin
;
Kikuchi, Hiroaki
;
Sisaat, Khamphao
;
Terada, Masato
Malware can be spread over the Internet via especially download mechanism to the victim computers. This work tries to cluster malware/bots download behavior of Top-10 malware based on 2010 and 2011 CCC (Cyber Clean Center) datasets. The datasets contain more than one million download logs collected from several independent honeypots in Japan to observe malware/bot traffic and activities. Although the daily and hourly patterns are quite similar in 2010, those of 2011 are quite different. As a result, the proposed Integral Correlation Coefficient can cluster 3 and 4 groups of Top-10 malware/bots in 2010 and 2011, respectively. © 2013 IEEE.
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