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Calculating AGC and C/N0 thresholds of mobile for jamming detection
(2021-05-19)
Sakorn, Chotipong
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Supnithi, Pornchai
GNSS jamming poses a serious threat to GNSS users by interrupting the signal reception and may cause outages. Alleviation and detection of jamming are therefore important issues for real-world users. In this work, we propose the entropy-based detector for mobile phones to detect the jamming occurrence in GPS, Galileo, and Beidou systems. The computed entropy values of the carrier to noise (C/N0) and auto gain control (AGC) are considered as the thresholds. We found that the false alarm of the entropy-based detector is lower than the likelihood ratio test (LRT) by about 4% to 9%.
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Measuring icon recognization mapping with automated decision making system
(2019-07-01)
Tangtisanon, Pikulkaew
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Khongtrakan, Yanaphat
Nowadays, mobile technology has been rapidly improved in both hardware and software aspects. Thus, many applications have been built and install in a smartphone. To find an application in the smartphone, a user has to search through various icons that design based on functions of the application. The purpose of this research is to build an automatic system that helps software designers to decide if the designed-icon is a proper icon that could be recognized by the user easily or not using entropy, Canny edge detection, and decision tree. Two experiments are reported in this research. 100 icons in both Android and iPhone operation system were used in both experiments. The sample included undergraduate students and workers in Thailand (n=90) ages ranged from 18 to 57. The first experiment was made in order to find a relationship among edge, entropy and human visual processing and use it as a training and testing dataset for the proposed system. The second experiment shows that the proposed system can be used to judge for a proper icon property with 73.33% accuracy rate.
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Differential effects of gender on entropy perception
(2017-01-01)
Satcharoen, Kleddao
The purpose of this research is to examine differences in perception of entropy (color intensity) between male and female computer users. The objectives include identifying gender-based differences in entropy intention and exploring the potential effects of these differences (if any) on user interface design. The research is an effort to contribute to an emerging field of interest in gender as it relates to science, engineering and technology (SET), particularly user interface design. Currently, there is limited evidence on the role of gender in user interface design and in use of technology generally, with most efforts at gender-differentiated or customized design based on stereotypes and assumptions about female use of technology or the assumption of a default position based on male preferences. Image entropy was selected as a potential characteristic where gender could be a factor in perception because of known differences in color perception acuity between male and female individuals, even where there is no known color perception abnormality (which is more common with males). Although the literature review suggested that training could offset differences in color perception and identification, tests in untrained subject groups routinely show that females are more able to identify, match, and differentiate colors, and that there is a stronger emotional and psychosocial association of color for females. Since image entropy is associated with information content and image salience, the ability to identify areas of high entropy could make a difference in user perception and technological capabilities.
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Sensitivity analysis ofwelfare, equity, and acceptability level of transport policies
(2015-01-01)
Connors, R.
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Patriksson, M.
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Rydergren, C.
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Sumalee, A.
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Watling, D.
Transport planners face a major challenge to devise policies to meet multiple expectations and objectives. While we know that transport networks are complex, multi-modal, and spatially distributed systems, there is now a long history of mathematical tools which assist planners in understanding travel movements. However, the objectives that they are asked to achieve do not always admit such a quantification, and so there is a potential mismatch between seemingly qualitatively driven objectives and quantitatively expressed models of the transport system. In the present chapter we address this mismatch, by focusing on three objectives that we believe represent the typical interests of a planner. These are namely: is the policy economically justifiable (efficient), is it “fair” (equitable), and is it justifiable to a democratic society (acceptable)? We provide mathematical representations of these three objectives and link them to mathematical theory of transport networks, in which we may explore the sensitivity of travel behaviour (and hence the objectives) to various multi-modal transport policies. The detailed steps for representing the policy objectives and sensitivities in the network are set out, and the results of a case study reported in which road tolls, road capacities, and bus fares are the policy variables. Overall, the chapter sets out a systematic method for planners to choose between multi-modal policies based on these three objectives.
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Thermodynamic models for determination of the solubility of 2,5-bis(2-furylmethylidene)cyclopentan-1-one in different solvents at temperatures ranging from 308.15 to 403.15K
(2014-04-15)
Prapasawat, Tatchanok
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Hronec, Milan
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Štolcová, Magdaléna
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Lothongkum, Anchaleeporn Waritswat
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Pancharoen, Ura
The solubility data of 2,5-bis(2-furylmethylidene)cyclopentan-1-one (F<inf>2</inf>C) in solid-liquid equilibrium in alternative solvents are vital for a preliminary study of industrial applications aimed at producing sustainable and renewable materials and fuels. The solubility behavior of F<inf>2</inf>C in different solvents, such as tetrahydrofuran, mixed water-tetrahydrofuran (1:1, v/v), methanol, and water at temperatures ranging from 308.15 to 403.15K was investigated. An isothermal method was employed to measure the solubility data of F<inf>2</inf>C. The experimental data showed that the solubility of F<inf>2</inf>C increased as the temperature increased and was strongly affected by the surface tension and polarity index. The solubility of F<inf>2</inf>C in the studied solvents increased in the following order: H<inf>2</inf>O<methanol<H<inf>2</inf>O-THF mixture<THF. The thermodynamic models, such as the polynomial empirical equation, the Van't Hoff, and the modified Apelblat models were investigated to describe the experimental data. It was found that the modified Apelblat model was the most suitable for predicting the solubility behavior of F<inf>2</inf>C with a temperature increment. The calculated thermodynamic parameters indicated that in each studied solvent the dissolution process of F<inf>2</inf>C is endothermic and spontaneous. © 2014 Elsevier B.V.
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Enhancing K-means algorithm for solving classification problems
(2013-11-25)
Thammano, Arit
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Kesisung, Pannee
K-means is the most popular clustering algorithm because of its efficiency and superior performance. However, the performance of K-means algorithm depends heavily on the selection of initial centroids. This paper proposes an extension to the original K-means algorithm enabling it to solve classification problems. First, the entropy concept is employed to adapt the traditional K-means algorithm to be used as a classification technique. Then, to improve the performance of K-means algorithm, a new scheme to select the initial cluster centers is proposed. The proposed models are tested on seven benchmark data sets from the UCI machine learning repository. Experimental results have shown that the proposed models outperform the learning vector quantization network in most of the tested data sets. © 2013 IEEE.
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Entropy measures of flow graphs with applications to decision trees
(2009-08-27)
Pattaraintakorn, Puntip
Entropy is a fundamental principle in many disciplines such as information theory, thermodynamics, and more recently, artificial intelligence. In this article, a measure of entropy on Pawlak's mathematical flow graph is introduced. The predictability and quality of a flow graph can be derived directly from the entropy. An application to decision tree generation from a flow graph is examined. In particular, entropy measures on flow graphs lead to a new methodology of reasoning from data and shows rigorous relationships between flow graphs, entropy and decision trees. © 2009 Springer Berlin Heidelberg.

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