Search results for: adaptive behaviours

Authors: Isaac Dery

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Masculinity studies have gained much purchase globally in recent decades, especially the sense in which they have produced discursive space for interdisciplinary investigations. In the light of this, there is increasing consensus among commentators that different masculinities co-exist within a particular social space. There is also a growing recognition and awareness of the merits in examining the conceptual underpinnings of masculinity (especially hegemonic masculinity) its variously contested meanings, and values, and how it contributes to violent behaviours by men. The consequences of hegemonic masculinity and its violent and traumatic impacts on men and women have been evident. The emerging call to imagine more egalitarian and complex masculinities among men has been at the centre of various discussions on the fight against violence. Some theorists argue that this violence emanates from men’s drive to live up to impossible ideals of “masculinity.” Seeking to make the connections between masculinity and gender-based violence, this paper discusses the imperative and possibilities of engaging men/boys as key actors in the campaign against violence. It is worth re-examining the ways in which men’s embodiment and performance of dangerous masculinities contribute towards violence. This paper therefore argues that empowering men to understand the implications of certain behaviours is the key in an attempt to arrest violence and its traumatic cost. This paper is situated within the thesis that there is a relationship between men’s embodiment and performance of dominant forms of masculinities, on the one hand, and violence against women and other men, on the other. Based on research conducted in northern Ghana on domestic violence, it is the argument of this paper that in order to contain violence against women, conditions of gender construction need to be problematized in a manner that will transform fundamental understandings of gender relations in society.

Keywords: violence against women, masculinities, Ghana, gender

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Authors: Jun Xu, Haiyan Xiao

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The Analects (Lunyu) is one of the most recognized Confucian classics and one of the earliest Chinese classics that have been translated into English and known to the West. Research on the translation of The Analects has witnessed a transfer from the comparison of the text and language to a wider description of social and cultural contexts. Mainly on the basis of Legge and Waley’s translations of The Analects, this paper integrates Lefevere’s theory of rewriting and Verschueren’s theory of adaptation and explores the influence of ideology and poetics on the translation. It analyses how translators make adaptive decisions in the manipulation of ideology and poetics. It is proved that the English translation of The Analects is the translators’ initiative rewriting of the original work, which is a selective and adaptive process in the multi-layered contexts of the target language. The research on the translation of classics should include both the manipulative factors and translator’s initiative as well.

Keywords: The Analects, ideology, poetics, rewriting, adaptation

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Authors: Seyed Sadegh Naseralavi, Najmeh Bemani

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In this paper, different concrete codes including America, New Zealand, Mexico, Italy, India, Canada, Hong Kong, Euro Code and Britain are compared with the Iranian concrete design code. First, by using Adaptive Neuro Fuzzy Inference System (ANFIS), the codes having the most correlation with the Iranian ninth issue of the national regulation are determined. Consequently, two anticipated methods are used for comparing the codes: Artificial Neural Network (ANN) and Multi-variable regression. The results show that ANN performs better. Predicting is done by using only tensile steel ratio and with ignoring the compression steel ratio.

Keywords: adaptive neuro fuzzy inference system, anticipate method, artificial neural network, concrete design code, multi-variable regression

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Authors: Yu Li, Dongyao Wang, Xiaobao Sun, Wei Ni

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In long-term evolution (LTE), the carriers around 5GHz are planned to be utilized without licenses to further enlarge system capacity. This feature is termed licensed assisted access (LAA). The channel sensing (clean channel assessment, CCA) is required before any transmission on these unlicensed carriers, in order to make sure the harmonious co-existence of LAA with other radio access technology in the unlicensed band. Obviously, the CCA threshold is very critical, which decides whether the transmission right following CCA is delivered in time and without collisions. An improper CCA threshold may cause buffer overflow of some eNodeBs if the eNodeBs are heavily loaded with the traffic. Thus, to solve these problems, we propose an adaptive threshold adjustment method for CCA in the LAA downlink. Both the load and transmission opportunities are concerned. The trend of the LAA throughput as the threshold varies is obtained, which guides the threshold adjustment. The co-existing between LAA and Wi-Fi is particularly tested. The results from system-level simulation confirm the merits of our design, especially in heavy traffic cases.

Keywords: LTE, LAA, CCA, threshold adjustment

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Authors: Sara Namdarian, Hafez Salleh

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This paper scrutinizes the circumstances of the application of Augmented Reality (AR) technology to enhance the adaptability of architecture classrooms in private Malaysian university classrooms. This study aims to indicate the constraints of mono-functional classrooms in comparison to the potentials of multi-functional classrooms derived from AR application through an exploratory mixed method strategy. This paper expects to contribute towards recognition of suitable AR techniques which can be applied in the development of Adaptive-AR-Classroom-Systems (AARCS) in architecture classrooms. The findings, derived from the analysis, show current classrooms have limited functional spaces, and concludes that AR application can be used in design classrooms to provide a variety of visuals and virtual objects that are required in conducting architecture projects in higher educational centers.

Keywords: design activity, space enhancement, design education, architectural design augmented reality

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Authors: Soumya Bhattacharjya, Avinandan Sahoo, Gaurav Datta

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Wind fragility analysis of chimney is often carried out disregarding temperature effect. However, the combined effect of wind and temperature is the most critical limit state for chimney design. Hence, in the present paper, an efficient fragility analysis for concrete chimney is explored under combined wind and temperature effect. Wind time histories are generated by Davenports Power Spectral Density Function and using Weighed Amplitude Wave Superposition Technique. Fragility analysis is often carried out in full Monte Carlo Simulation framework, which requires extensive computational time. Thus, in the present paper, an efficient adaptive metamodelling technique is adopted to judiciously approximate limit state function, which will be subsequently used in the simulation framework. This will save substantial computational time and make the approach computationally efficient. Uncertainty in wind speed, wind load related parameters, and resistance-related parameters is considered. The results by the full simulation approach, conventional metamodelling approach and proposed adaptive metamodelling approach will be compared. Effect of disregarding temperature in wind fragility analysis will be highlighted.

Keywords: adaptive metamodelling technique, concrete chimney, fragility analysis, stochastic extreme wind load, temperature effect

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Authors: Shaomei Li, Yawen Wang, Chao Gao

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To improve tracking drift which often occurs in adaptive tracking, an algorithm based on the fusion of tracking and detection is proposed in this paper. Firstly, object tracking is posed as a binary classification problem and is modeled by partial least squares (PLS) analysis. Secondly, tracking object frame by frame via particle filtering. Thirdly, validating the tracking reliability based on both positive and negative models matching. Finally, relocating the object based on SIFT features matching and voting when drift occurs. Object appearance model is updated at the same time. The algorithm cannot only sense tracking drift but also relocate the object whenever needed. Experimental results demonstrate that this algorithm outperforms state-of-the-art algorithms on many challenging sequences.

Keywords: object tracking, tracking drift, partial least squares analysis, positive and negative models matching

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Authors: Chidozie C. Nwobi-Okoye, Basil Q. Ochieze, Stanley Okiy

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This research reports on the modeling of age hardening process using adaptive neuro-fuzzy inference system (ANFIS). The age hardening output (Hardness) was predicted using ANFIS. The input parameters were ageing time, temperature and percentage composition of cow horn particles (CHp%). The results show the correlation coefficient (R) of the predicted hardness values versus the measured values was of 0.9985. Subsequently, values outside the experimental data points were predicted. When the temperature was kept constant, and other input parameters were varied, the average relative error of the predicted values was 0.0931%. When the temperature was varied, and other input parameters kept constant, the average relative error of the hardness values predictions was 80%. The results show that ANFIS with coarse experimental data points for learning is not very effective in predicting process outputs in the age hardening operation of A356 alloy/CHp particulate composite. The fine experimental data requirements by ANFIS make it more expensive in modeling and optimization of age hardening operations of A356 alloy/CHp particulate composite.

Keywords: adaptive neuro-fuzzy inference system (ANFIS), age hardening, aluminum alloy, metal matrix composite

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Authors: Chia-Hau Liu, Tai-Yue Wang

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Traditional multivariate control charts assume that measurement from manufacturing processes follows a multivariate normal distribution. However, this assumption may not hold or may be difficult to verify because not all the measurement from manufacturing processes are normal distributed in practice. This study develops a new multivariate control chart for monitoring the processes with non-normal data. We propose a mechanism based on integrating the one-class classification method and the adaptive technique. The adaptive technique is used to improve the sensitivity to small shift on one-class classification in statistical process control. In addition, this design provides an easy way to allocate the value of type I error so it is easier to be implemented. Finally, the simulation study and the real data from industry are used to demonstrate the effectiveness of the propose control charts.

Keywords: multivariate control chart, statistical process control, one-class classification method, non-normal data

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: James Boylan, Denny Meyer, Won Sun Chen

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Background: Globally, there is an increasing trend of road traffic deaths, reaching 1.35 million in 2016 in comparison to 1.3 million a decade ago, and overall, road traffic injuries are ranked as the eighth leading cause of death for all age groups. The reported death rate for younger drivers aged 16-19 years is almost twice the rate reported for older drivers aged 25 and above, with a rate of 3.5 road traffic fatalities per annum for every 10,000 licenses held. Telematics refers to a system with the ability to capture real-time data about vehicle usage. The data collected from telematics can be used to better assess a driver's risk. It is typically used to measure acceleration, turn, braking, and speed, as well as to provide locational information. With the Australian government creating the National Telematics Framework, there has been an increase in the government's focus on using telematics data to improve road safety outcomes. The purpose of this study is to test the hypothesis that improvements in telematics measured driving behaviour to relate to improvements in road safety attitudes measured by the Driving Behaviour Questionnaire (DBQ). Methodology: 28 participants were recruited and given a telematics device to insert into their vehicles for the duration of the study. The participant's driving behaviour over the course of the first month will be compared to their driving behaviour in the second month to determine whether feedback from telematics devices improves driving behaviour. Participants completed the DBQ, evaluated using a 6-point Likert scale (0 = never, 5 = nearly all the time) at the beginning, after the first month, and after the second month of the study. This is a well-established instrument used worldwide. Trends in the telematics data will be captured and correlated with the changes in the DBQ using regression models in SAS. Results: The DBQ has provided a reliable measure (alpha = .823) of driving behaviour based on a sample of 23 participants, with an average of 50.5 and a standard deviation of 11.36, and a range of 29 to 76, with higher scores, indicating worse driving behaviours. This initial sample is well stratified in terms of gender and age (range 19-27). It is expected that in the next six weeks, a larger sample of around 40 will have completed the DBQ after experiencing in-vehicle telematics for 30 days, allowing a comparison with baseline levels. The trends in the telematics data over the first 30 days will be compared with the changes observed in the DBQ. Conclusions: It is expected that there will be a significant relationship between the improvements in the DBQ and the trends in reduced telematics measured aggressive driving behaviours supporting the hypothesis.

Keywords: telematics, driving behavior, young drivers, driving behaviour questionnaire

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Authors: D. Venu, N. V. Koteswara Rao

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Space – time adaptive processing (STAP) is an effective tool for detecting a moving target in spaceborne or airborne radar systems. Since airborne passive radar systems utilize broadcast, navigation and excellent communication signals to perform various surveillance tasks and also has attracted significant interest from the distinct past, therefore the need of the hour is to have cost effective systems as compared to conventional active radar systems. Moreover, requirements of small number of secondary samples for effective clutter suppression in bi-static passive radar offer abundant illuminator resources for passive surveillance radar systems. This paper presents a framework for incorporating knowledge sources directly in the space-time beam former of airborne adaptive radars. STAP algorithm for clutter mitigation for passive bi-static radar has better quantitation of the reduction in sample size thereby amalgamating the earlier data bank with existing radar data sets. Also, we proposed a novel method to estimate the clutter matrix and perform STAP for efficient clutter suppression based on small sample size. Furthermore, the effectiveness of the proposed algorithm is verified using MATLAB simulations in order to validate STAP algorithm for passive bi-static radar. In conclusion, this study highlights the importance for various applications which augments traditional active radars using cost-effective measures.

Keywords: bistatic radar, clutter, covariance matrix passive radar, STAP

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Authors: K. Larysz, E. Grochowska-Niedworok, M. Kardas, K. Brukalo, B. Calyniuk, R. Polaniak

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Eating behaviours and habits are one of the main factors affecting health. Abnormal nutritional status is a growing problem related to nutritional errors. The number of adolescents presenting excess body weight is also rising. The body's demand for all nutrients increases in the period of intensive development, i.e., during puberty. A varied, well-balanced diet and elimination of unhealthy habits are two of the key factors that contribute to the proper development of a young body. The aim of the study was to assess the nutritional status and selected eating behaviours/habits in adolescents attending middle school. An original questionnaire including 24 questions was conducted. A total of 401 correctly completed questionnaires were qualified for the assessment. Body mass index (BMI) was calculated. Furthermore, the frequency of breakfast consumption, the number of meals per day, types of snacks and sweetened beverages, as well as the frequency of consuming fruit and vegetables, dairy products and fast-foods were assessed. The obtained results were analysed statistically. The study showed that malnutrition was more of a problem than overweight or obesity among middle school students. More than 71% of middle school students have breakfast, whereas almost 30% of adolescents skip this meal. Up to 57.6% of respondents most often consume sweets at school. A total of 37% of adolescents consume sweetened beverages daily or almost every day. Most of the respondents consume an optimal number of meals daily. Only 24.7% of respondents consume fruit and vegetables more than once daily. The majority of respondents (49.40%) declared that they consumed fast food several times a month. Satisfactory frequency of consuming dairy products was reported by 32.7% of middle school students. Conclusions of our study: 1. Malnutrition is more of a problem than overweight or obesity among middle school students. They consume excessive amounts of sweets, sweetened beverages, and fast foods. 2. The consumption of fruit and vegetables was too low in the study group. The intake of dairy products was also low in some cases. 3. A statistically significant correlation was found between the frequency of fast food consumption and the intake of sweetened beverages. A low correlation was found between nutritional status and the number of meals per day. The number of meals consumed by these individuals decreased with increasing nutritional status.

Keywords: adolescent, malnutrition, nutrition, nutritional status, obesity

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Authors: Wafa’ Alma'Aitah, Khaled Almakadmeh

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this study presents an information retrieval system of using genetic algorithm to increase information retrieval efficiency. Using vector space model, information retrieval is based on the similarity measurement between query and documents. Documents with high similarity to query are judge more relevant to the query and should be retrieved first. Using genetic algorithms, each query is represented by a chromosome; these chromosomes are fed into genetic operator process: selection, crossover, and mutation until an optimized query chromosome is obtained for document retrieval. Results show that information retrieval with adaptive crossover probability and single point type crossover and roulette wheel as selection type give the highest recall. The proposed approach is verified using (242) proceedings abstracts collected from the Saudi Arabian national conference.

Keywords: genetic algorithm, information retrieval, optimal queries, crossover

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Authors: Baladitya Swaika, Rahul Khatry

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Computer Adaptive Tests (CATs) is one of the most efficient ways for testing the cognitive abilities of students. CATs are based on Item Response Theory (IRT) which is based on item selection and ability estimation using statistical methods of maximum information selection/selection from posterior and maximum-likelihood (ML)/maximum a posteriori (MAP) estimators respectively. This study aims at combining both classical and Bayesian approaches to IRT to create a dataset which is then fed to a neural network which automates the process of ability estimation and then comparing it to traditional CAT models designed using IRT. This study uses python as the base coding language, pymc for statistical modelling of the IRT and scikit-learn for neural network implementations. On creation of the model and on comparison, it is found that the Neural Network based model performs 7-10% worse than the IRT model for score estimations. Although performing poorly, compared to the IRT model, the neural network model can be beneficially used in back-ends for reducing time complexity as the IRT model would have to re-calculate the ability every-time it gets a request whereas the prediction from a neural network could be done in a single step for an existing trained Regressor. This study also proposes a new kind of framework whereby the neural network model could be used to incorporate feature sets, other than the normal IRT feature set and use a neural network’s capacity of learning unknown functions to give rise to better CAT models. Categorical features like test type, etc. could be learnt and incorporated in IRT functions with the help of techniques like logistic regression and can be used to learn functions and expressed as models which may not be trivial to be expressed via equations. This kind of a framework, when implemented would be highly advantageous in psychometrics and cognitive assessments. This study gives a brief overview as to how neural networks can be used in adaptive testing, not only by reducing time-complexity but also by being able to incorporate newer and better datasets which would eventually lead to higher quality testing.

Keywords: computer adaptive tests, item response theory, machine learning, neural networks

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Authors: Hamza Nejib, Okba Taouali

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This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS

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Authors: Yanqun Li, Hong Geng

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The rapid urbanization process taking big cities as the main body leads to the unequal configuration of urban and rural areas in the aspects of land supply, industrial division of labor, service supply and space allocation, and induces the shrinking characterization of service energy, industrial system and population vitality in small towns. As an important spatial unit in the spectrum of urbanization that serves, connects and couples urban and rural areas, the shrinking phenomenon faced by small towns has an important influence on the healthy development of urbanization. Based on the census of small towns in Wuhan metropolitan area, we have found that the shrinking of small towns is a passive contraction of elastic tension under the squeeze in cities. Once affected by the external forces such as policy regulation, planning guidance, and population return, small towns will achieve expansion and growth. Based on the theory of complex adaptive systems, this paper comprehensively constructs the development index evaluation system of small towns from five aspects of population, economy, space, society and ecology, measures the shrinking level of small towns, further analyzes the shrinking characteristics of small towns, and identifies whether the shrinking is elastic or not. And then this paper measures the resilience ability index of small town contract from the above-mentioned five aspects. Finally, this paper proposes an adaptive mechanism of urban-rural interaction evolution under fine division of labor to response the passive shrinking in small towns of Wuhan. Based on the above, the paper creatively puts forward the planning response measures of the small towns on the aspects of spatial layout, function orientation and service support, which can provide reference for other regions.

Keywords: complex adaptive systems, resiliency shrinking, adaptation mechanism, planning response

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Authors: Wei Wang, Martin Chen

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The reconstitution behaviours of nutritional products could impact user experience. Reconstitution issues such as lump formation and white flecks sticking to bottles surfaces could be very unappealing for the consumers in milk preparation. The controlling steps in dissolving instant milk powders include wetting, swelling, sinking, dispersing, and dissolution as in the literature. Each stage happens simultaneously with the others during milk preparation, and it is challenging to isolate and measure each step individually. This study characterized three adult nutritional products for different properties including particle size, density, dispersibility, stickiness, and capillary wetting to understand the relationship between powder physical properties and their reconstitution behaviours. From the results, the formation of clumps can be caused by different factors limiting the critical steps of powder reconstitution. It can be caused by small particle size distribution, light particle density limiting powder wetting, or the rapid swelling and dissolving of particle surface materials to impede water penetration in the capillary channels formed by powder agglomerates. For the grain or white flecks formation in milk preparation, it was believed to be controlled by dissolution speed of the particles after dispersion into water. By understanding those relationship between fundamental powder structure and their user experience in reconstitution, this information provides us new and multiple perspectives on how to improve the powder characteristics in the commercial manufacturing.

Keywords: characterization, dairy nutritional powder, physical property, reconstitution

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Authors: Ju-Hong Lee, Ching-Wei Liao

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Owing to close antenna spacing between antenna sensors within a compact space, a part of data in one antenna sensor would outflow to other antenna sensors when the antenna sensors in an antenna array operate simultaneously. This phenomenon is called mutual coupling effect (MCE). It has been shown that the performance of antenna array systems can be degraded when the antenna sensors are in close proximity. Especially, in a systems equipped with massive antenna sensors, the degradation of beamforming performance due to the MCE is significantly inevitable. Moreover, it has been shown that even a small angle error between the true direction angle of the desired signal and the steering angle deteriorates the effectiveness of an array beamforming system. However, the true direction vector of the desired signal may not be exactly known in some applications, e.g., the application in land mobile-cellular wireless systems. Therefore, it is worth developing robust techniques to deal with the problem due to the MCE and steering angle error for array beamforming systems. In this paper, we present an efficient technique for performing adaptive beamforming with robust capabilities against the MCE and the steering angle error. Only the data vector received by an antenna array is required by the proposed technique. By using the received array data vector, a correlation matrix is constructed to replace the original correlation matrix associated with the received array data vector. Then, the mutual coupling matrix due to the MCE on the antenna array is estimated through a recursive algorithm. An appropriate estimate of the direction angle of the desired signal can also be obtained during the recursive process. Based on the estimated mutual coupling matrix, the estimated direction angle, and the reconstructed correlation matrix, the proposed technique can effectively cure the performance degradation due to steering angle error and MCE. The novelty of the proposed technique is that the implementation procedure is very simple and the resulting adaptive beamforming performance is satisfactory. Simulation results show that the proposed technique provides much better beamforming performance without requiring complicated complexity as compared with the existing robust techniques.

Keywords: adaptive beamforming, mutual coupling effect, recursive algorithm, steering angle error

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Authors: G. Schuh, S. Woelk, D. Schraknepper, A. Such

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The systematic evaluation of manufacturing technologies with regard to the potential for product designing constitutes a major challenge. Until now, conventional evaluation methods primarily consider the costs of manufacturing technologies. Thus, the potential of manufacturing technologies for achieving additional product design features is not completely captured. To compensate this deficit, final evaluations of new technologies are mainly intuitive in practice. Therefore, an additional evaluation dimension is needed which takes the potential of manufacturing technologies for specific realizable product designs into account. In this paper, we present the approach of an evaluation method for selecting manufacturing technologies with regard to their potential for product designing. This research is done within the Fraunhofer innovation cluster »AdaM« (Adaptive Manufacturing) which targets the development of resource efficient and adaptive manufacturing technology processes for complex turbo machinery components.

Keywords: manufacturing, product design, production, technology assessment, technology management

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Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

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The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

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Authors: H. Mahdjoub, B. Hamaidi, B. Zerouali, S. Rouabhia

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The issue of fault detection and diagnosis (FDD) has gained widespread industrial interest in process condition monitoring applications. Accordingly, the use of neuro-fuzzy technic seems very promising. This paper treats a diagnosis modeling a strategic equipment of an industrial installation. We propose a diagnostic tool based on adaptive neuro-fuzzy inference system (ANFIS). The neuro-fuzzy network provides an abductive diagnosis. Moreover, it takes into account the uncertainties on the maintenance knowledge by giving a fuzzy characterization of each cause. This work was carried out with real data of a lubrication circuit from the gas turbine. The machine of interest is a gas turbine placed in a gas compressor station at South Industrial Centre (SIC Hassi Messaoud Ouargla, Algeria). We have defined the zones of good and bad functioning, and the results are presented to demonstrate the advantages of the proposed method.

Keywords: fault detection and diagnosis, lubrication system, turbine, ANFIS, training, pattern recognition

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Authors: Arfan Ali Nagra, Tariq Shahzad, Meshal Alharbi, Khalid Masood Khan, Muhammad Mugees Asif, Taher M. Ghazal, Khmaies Ouahada

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Gene selection is an essential step for the classification of microarray cancer data. Gene expression cancer data (DNA microarray) facilitates computing the robust and concurrent expression of various genes. Particle swarm optimization (PSO) requires simple operators and less number of parameters for tuning the model in gene selection. The selection of a prognostic gene with small redundancy is a great challenge for the researcher as there are a few complications in PSO based selection method. In this research, a new variant of PSO (Self-inertia weight adaptive PSO) has been proposed. In the proposed algorithm, SIW-APSO-ELM is explored to achieve gene selection prediction accuracies. This new algorithm balances the exploration capabilities of the improved inertia weight adaptive particle swarm optimization and the exploitation. The self-inertia weight adaptive particle swarm optimization (SIW-APSO) is used to search the solution. The SIW-APSO is updated with an evolutionary process in such a way that each particle iteratively improves its velocities and positions. The extreme learning machine (ELM) has been designed for the selection procedure. The proposed method has been to identify a number of genes in the cancer dataset. The classification algorithm contains ELM, K- centroid nearest neighbor (KCNN), and support vector machine (SVM) to attain high forecast accuracy as compared to the start-of-the-art methods on microarray cancer datasets that show the effectiveness of the proposed method.

Keywords: microarray cancer, improved PSO, ELM, SVM, evolutionary algorithms

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Authors: Jenn-Yih Chen, Bean-Yin Lee, Yuan-Chuan Hsu, Jui-Cheng Lin, Kuang-Chyi Lee

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In this paper, a sliding mode control method based on the passivity approach is proposed to control the position of surface-mounted permanent magnet synchronous motors (PMSMs). Firstly, the dynamics of a PMSM was proved to be strictly passive. The position controller with an adaptive law was used to estimate the load torque to eliminate the chattering effects associated with the conventional sliding mode controller. The stability analysis of the overall position control system was carried out by adopting the passivity theorem instead of Lyapunov-type arguments. Finally, experimental results were provided to show that the good position tracking can be obtained, and exhibit robustness in the variations of the motor parameters and load torque disturbances.

Keywords: adaptive law, passivity theorem, permanent magnet synchronous motor, sliding mode control

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Authors: B. M. M. D. Mendis, L. I. Rajapaksa, P. S. K. Gunathunga, R. C. Fernando, M. Jayalath

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Background / introduction: During the year 2011, 8511 males received services from the sexual health clinics island wide. At present there is only limited information on the risk behaviours of male attendees. Information on risk behaviours related to STI /HIV transmission is helpful in planning suitable prevention interventions. Aim(s)/objectives: The objectives were to determines the sexual partners (other than the marital partner and regular partners) responsible for transmitting STI( Sexually transmitted infections)/ HIV and to understand the practice of safer sex. Methods: Study was a clinic based prospective study conducted for a one year period using an interviewer administered questionnaire. Results: 983 attendees were interviewed. . Mean age was 34.02 years. 75% of the sample had completed GCE O/L (ordinary level examination). Skilled labourers, drivers and forces/police comprised 40% of the sample. 50% admitted sex with a casual female, 12% with a casual male, and 13% with CSW (commercial sex workers) while MSW (male sex workers) exposures were minimal. It was identified that younger males had more contacts with males, and regular female partners while more older males with CSW. Anal sex among males was reported by 11.5%. 20.5% used alcohol frequently and 5.9% used drugs and 1.4% injected. Common STI were genital herpes (7.9%), Non gonococcal urethritis (6.2%) and gonorrhoea (6.2%). Among those who had contacts with FSW 6.7% gonorrhoea (GC), 8.2% non gonococcal urethritis (NGU), 7.5% genital herpes and 0.7% HIV. Non regular partner exposures 3.7% had gonorrhoea, 8.3% NGU, 6.6% genital herpes and 0.8% HIV. Among MSM contacts 10.6% had GC, 4.5% NGU, 5.3% genital herpes, 5.3% secondary syphilis and 0.8% HIV. Only 9.0% used condoms correctly. Friends, doctors, newspapers, internet, and forces were important sources of information on condoms. Non use of condoms were due to worry about satisfaction (24.6%) and faith in the partner (25.6%). Discussion/conclusion: Casual partners for unsafe sex is a concern. MSM and CSW are remained as an important source of infection. Early Syphilis and gonorrhoea infections were mostly seen among MSM exposures. The findings indicate that the male population in the sample had satisfactory education. However, still the unsafe sexual contacts are common. . Newspapers, internet were more important sources of information on condoms. Low condom use remains another concern.. More males contracted STI through casual partners. Therefore strategies used for prevention need to be revisited also emphasizing on general population where casual partners represent. . Increasing awareness of men and women through mass media and primary health care teams may be important strategies that can be used to keep the HIV epidemic in a low level.

Keywords: STI, HIV, Males, safe sex practices

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Authors: Hamed Azad, Azadeh M. Ardakani

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Visual content, as an integral part of social media marketing, is growing dramatically. They are, in different technological usage categories (i.e., photos, graphics, animation IGTV, Stories, Livestreams, and Reels), associated with improving customer engagement behaviours (CEBs) in social commerce (SC). However, few researchers have explored the impact of specific and occasional contents that respect green products, gender equality, religious freedom, and LGBTs' rights. This study aims to compare and analyse how the ten best global brands (Interbrand's) in different categories communicate with customers on Instagram. Netnography approach and method used to conduct the data collection and data analysis of 1072 Instagram posts and 10494 comments. The results show that brands in fashion, sport, and homeware categories (H&M, Nike, and Ikea) emerge to use more effective content with the above global values elements than other brand categories. Findings also indicate that some different themes such as celebrities, models, pets, kids, aged and disabled people are part of visual management strategies on Instagram brands' pages. This research aims to inform researchers to consider all aspects of visual elements in content quality and marketing managers to increase brand optimisation, awareness, and authenticity by promoting contemporary world values on Instagram.

Keywords: green products, gender equality, religious freedom, LGBTs, Instagram, netnography

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Authors: M. Ramesh Kanthan, S. Naga Nandini Sujatha

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The goal of haze removal algorithms is to enhance and recover details of scene from foggy image. In enhancement the proposed method focus into two main categories: (i) image enhancement based on Adaptive contrast Histogram equalization, and (ii) image edge strengthened Gradient model. Many circumstances accurate haze removal algorithms are needed. The de-fog feature works through a complex algorithm which first determines the fog destiny of the scene, then analyses the obscured image before applying contrast and sharpness adjustments to the video in real-time to produce image the fusion strategy is driven by the intrinsic properties of the original image and is highly dependent on the choice of the inputs and the weights. Then the output haze free image has reconstructed using fusion methodology. In order to increase the accuracy, interpolation method has used in the output reconstruction. A promising retrieval performance is achieved especially in particular examples.

Keywords: single image, fusion, dehazing, multi-scale fusion, per-pixel, weight map

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Authors: Leja Salciute

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Mental health difficulties are one of the reasons for abnormal feeding behaviour. This is especially evident in a crisis situation. Abnormal feeding behaviour occurs when individuals use food as a method to provide relief for these negative emotions. The study aimed to discover an association between emotional regulation, mental health difficulties and disruption in feeding behaviours in the UK in times of crisis. A mixed-methods design was used. Abnormal feeding behaviour was measured using the Binge Eating Disorder Screener-7, SCOFF scale, Crisis impact scale, Difficulties in Emotion Regulation Scale and demographics. The sample comprised 342 participants with a history of excessive overeating. The participants (male= 198, female= 141 and other= 3) came from the general population and they were aged 16 and over. Participants ranged in age from 16 to 89. Findings from the survey concluded that difficulties with emotion regulation were found to be associated with abnormal feeding behaviours. Mental health difficulties correlated significantly with changes in individuals’ lives, such as work or routines. Individuals differed in their abnormal feeding behaviour in terms of their age, that is, younger individuals showed less struggle with their eating patterns while older individuals faced greater struggles with their abnormal feeding behaviour. Emotion regulation significantly influenced abnormal feeding behaviour. Results from qualitative data suggest four common themes that were identified: demonstration of gratitude, negative emotions, disruptions to social life, and financial loss. For example, participants developed and gained an awareness of being grateful for the simple things in life even when participants experienced hardships. The results also suggested that emotional eating acted like a sedative that allowed the participant to run away from their painful reality. Crisis situation negatively affected relationships among participants and induced negativity related to social interaction. Finally, the respondents highlighted that the presence of uncertainty made it hard to plan ahead and look forward to the future. Although respondents experienced negative emotions and financial losses, some of them still managed to allocate time for themselves and enjoy their time off during crisis. However, majority of respondents referred to their inability to control their external circumstances and turned to and relied upon food overconsumption instead. This had a negative effect on their mental health and presented disruptions in feeding behaviour. It was recommended for individuals in times of crisis to seek psychological support in the form of Cognitive Behavioural Therapy (CBT).

Keywords: binge eating, maladaptive eating behaviours, mental health, negative emotions in crisis

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Authors: Sandra Figueiredo, Alexandra Pereira, Ana Oliveira, Idia Brito, Ivaniltan Jones, Joana Moreira, Madalena Silva, Maria Paraíba, Milene Silva, Tânia Pinho

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In the present society, we are facing behaviours mainly in young individuals that might be considered trends of culture or psychopathology. Both contexts are challenges for Education, Psychology and Health. This paper examines nine case studies specifically in Educational Psychology with the main goal to identify and define phenomena contexts in school culture, the psychopathology involved and to present a psychological intervention for each case. The research was conducted by university students in the period of March 2017-June 2017, in Portugal, and the childhood was focused. The case studies explored the cyberbullying; the bullying - victims and bullies’ perspectives; the obsessive compulsive disorder; perception and inclusion of children from homoparental families; inclusion of foreign students in the higher education system; blindness and the inclusion in physical curricular activities; influence of doc-reality and media in attitudes and self-esteem; and the morningness and eveningness types learning in the same school timetables. The university students were supervised during their research analysis and two methods were available for the intervention research study: the meta-analysis and the empirical study. In the second phase, the pedagogical intervention was designed for the different educational contexts in analysis, especially concerning the school environments. The evidence of literature and the empirical studies showed new trends of school’ behaviours and educational disturbances that require further research and effective (and adequate to age, gender, nationality and culture) pedagogical instruments. Respecting the instruments, on the one hand, to identify behaviors, habits or pathologies and highlight the role and training of teachers, psychologists and health professionals, on the other hand, to promote the early intervention and to enhance healthy child development and orientation of the families. To respond to both milestones, this paper present nine pedagogical techniques and measures that will be discussed on their impact concerning advances for the psychological and educational intervention, centered in the individual and in the new generations of family’ cultures.

Keywords: behaviour, culture trends, educational intervention, psychopathology, obsessive compulsive disorder, cyberbullying, bullying, homoparental families, sleep influence, blindness and sports at school, inclusion of foreign students, media influence in behaviour

Procedia PDF Downloads 186

Authors: A. Sewell

Abstract:

The paper reports a research project which investigated the social interactions of nine to ten-year-olds in a mainstream primary school. The project implemented an adaption of a whole class, behavioural intervention known as 'The Good Behaviour Game (TGBG)'. TGBG is an evidence-based intervention traditionally used to reduce low-level disruptive behaviours in a classroom setting. TGBG was adapted to encourage pupil’s engagement in pro-social behaviour during lessons. A mixed methods research design was employed to evaluate intervention effects and pupil’s perceptions of their social interactions and relationships with others. Single-case research design was used to evaluate behaviour change, and Personal Construct Psychology (PCP) repertory grids were used to explore pupil’s perceptions. The findings demonstrated that TGBG could be successfully adapted to positively influence pupil’s engagement in pro-social behaviours. The findings from the PCP repertory grid interviews revealed the complexities of how children construct their social interactions and relationships with others, and how an understanding of these could be used to design better social skills interventions. It is concluded that TGBG is a cost-effective, simple to implement intervention for promoting positive social interactions and relationships at the whole class level. The paper presents the aims, design, findings, and conclusions of the study in further detail and relates limitations and potential future extensions of the research. The outcomes have direct application and relevance for practitioners interested in children’s social development and how to promote positive outcomes in this critical aspect of childhood.

Keywords: social skills, social development, social competency, the good behaviour game

Procedia PDF Downloads 147