Search results for: premises selection

Authors: Zhehao Zhang

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Walking has become an indispensable and sustainable way of travel for college students in their daily lives; campus street is an important carrier for students to walk and take part in a variety of activities, improving the walkability of campus streets plays an important role in optimizing the quality of campus space environment, promoting the campus walking system and inducing multiple walking behaviors. The purpose of this paper is to explore the effect of campus layout, facility distribution, and location site selection on the walkability of campus streets, and assess the street design qualities from the elements of imageability, enclosure, complexity, transparency, and human scale, and further examines the relationship between street-level urban design perceptual qualities and walkability and its effect on walking behavior in the campus. Taking Tianjin University as the research object, this paper uses the optimized walk score method based on walking frequency, variety, and distance to evaluate the walkability of streets from a macro perspective and measures the urban design qualities in terms of the calculation of street physical environment characteristics, as well as uses behavior annotation and street image data to establish temporal and spatial behavior database to analyze walking activity from the microscopic view. In addition, based on the conclusions, the improvement and design strategy will be presented from the aspects of the built walking environment, street vitality, and walking behavior.

Keywords: walkability, streetscapes, pedestrian activity, walk score

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Authors: Vidishaa Jali, Amit Sinha, Kameshwar Prasad

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Background and Objective: Cerebral microbleeds are frequently found in healthy elderly individuals. We performed a meta- analysis to determine the prevalence of cerebral microbleeds in apparently healthy, elderly population and to determine the effect of age, smoking and hypertension on the occurrence of cerebral microbleeds. Methods: Relevant literature was searched using electronic databases such as MEDLINE, EMBASE, PubMed, Cochrane database, Google scholar to identify studies on the prevalence of cerebral microbleeds in general elderly population till March 2016. STATA version 13 software was used for analysis. Fixed effect model was used if heterogeneity was less than 50%. Otherwise, random effect model was used. Meta- regression analysis was performed to check any effect of important variables such as age, smoking, hypertension. Selection Criteria: We included cross-sectional studies performed in apparently healthy elderly population, who had age more than 50 years. Results: The pooled proportion of cerebral microbleeds in healthy population is 12% (95% CI, 0.11 to 0.13). No significant effect of age was found on the prevalence of cerebral microbleeds (p= 0.99). A linear relationship between increase in hypertension and the prevalence of cerebral microbleeds was found, however, this linear relationship was not statistically significant (p=0.16). Similarly, A linear relationship between increase in smoking and the prevalence of cerebral microbleeds was found, however, this linear relationship was also not statistically significant (p=0.21). Conclusion: Presence of cerebral microbleeds is evident in apparently healthy, elderly population, in more than 10% of individuals.

Keywords: apparently healthy, elderly, prevalence, cerebral microbleeds

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Authors: Clement Ndoricimpa

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The expression of stance is highly expected in writing at tertiary level. Through a selection of linguistic and rhetorical elements, writers express commitment, critical distance and build a critically discerning reader in texts. Despite many studies on patterns of stance in students’ academic writing, little may not be known about how English as a Foreign Language students learns to build a critically discerning reader in their texts. Therefore, this study examines patterns of stance in essays written by students majoring in business administration at English-medium University in Burundi as part of classroom assignments. It draws on systemic functional linguistics to analyze qualitatively and quantitatively the data. The quantitative analysis is used to identify the differences in frequency of stance patterns in the essays. The results show a significant difference in the use of boosters by lower- and upper-level students. Lower-level students’ writing contains more boosters and many idiosyncratic sentence structures than do upper-level students’ writing, and upper-level students’ essays contain more hedging and few grammatical mistakes than do lower-level students’ essays. No significant difference in the use of attitude markers and concessive and contrastive expressions. Students in lower- and upper-level do not use attitude markers and disclaimer markers appropriately and accurately. These findings suggest that students should be taught the use of stance patterns in academic writing.

Keywords: academic writing, metadiscourse, stance, student corpora

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Authors: Jehnming Lin

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The effects of the contact ball-lens on the soda lime glass in laser thermal cleavage with a cw Nd-YAG laser were investigated in this study. A contact ball-lens was adopted to generate a bending force on the crack formation of the soda-lime glass in the laser cutting process. The Nd-YAG laser beam (wavelength of 1064 nm) was focused through the ball-lens and transmitted to the soda-lime glass, which was coated with a carbon film on the surface with a bending force from a ball-lens to generate a tensile stress state on the surface cracking. The fracture was controlled by the contact ball-lens and a straight cutting was tested to demonstrate the feasibility. Experimental observations on the crack propagation from the leading edge, main section and trailing edge of the glass sheet were compared with various mechanical and thermal loadings. Further analyses on the stress under various laser powers and contact ball loadings were made to characterize the innovative technology. The results show that the distributions of the side crack at the leading and trailing edges are mainly dependent on the boundary condition, contact force, cutting speed and laser power. With the increase of the mechanical and thermal loadings, the region of the side cracks might be dramatically reduced with proper selection of the geometrical constraints. Therefore, the application of the contact ball-lens is a possible way to control the fracture in laser cleavage with improved cutting qualities.

Keywords: laser cleavage, stress analysis, crack visualization, laser

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Authors: Stelios A. Mitilineos, Nicolas-Alexander Tatlas, Georgia Korompili, Lampros Kokkalas, Stelios M. Potirakis

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Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a widespread chronic disease that mostly remains undetected, mainly due to the fact that it is diagnosed via polysomnography which is a time and resource-intensive procedure. Screening the disease’s symptoms at home could be used as an alternative approach in order to alert individuals that potentially suffer from OSAHS without compromising their everyday routine. Since snoring is usually linked to OSAHS, developing a snore detector is appealing as an enabling technology for screening OSAHS at home using ubiquitous equipment like commodity microphones (included in, e.g., smartphones). In this context, this study developed a snore detection tool and herein present the approach and selection of specific sound features that discriminate snoring vs. environmental sounds, as well as the performance of the proposed tool. Furthermore, a Real-Time Snore Detector (RTSD) is built upon the snore detection tool and employed in whole-night sleep sound recordings resulting to a large dataset of snoring sound excerpts that are made freely available to the public. The RTSD may be used either as a stand-alone tool that offers insight to an individual’s sleep quality or as an independent component of OSAHS screening applications in future developments.

Keywords: obstructive sleep apnea hypopnea syndrome, apnea screening, snoring detection, machine learning, neural networks

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Authors: Mst. Tuhina-Khatun, Mohamed Hanafi Musa, Mohd Rafii Yosup, Wong Mui Yun, Md. Aktar-Uz-Zaman, Mahbod Sahebi

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Rice is a staple crop of economic importance of most Asian people, and blast is the major constraints for its higher yield. Heritability of plants traits helps plant breeders to make an appropriate selection and to assess the magnitude of genetic improvement through hybridization. Diversity of crop plants is necessary to manage the continuing genetic erosion and address the issues of genetic conservation for successfully meet the future food requirements. Therefore, an experiment was conducted to estimate heritability and to determine the diversity of 27 blast resistant upland rice genotypes based on 18 quantitative traits using randomized complete block design. Heritability value was found to vary from 38 to 93%. The lowest heritability belonged to the character total number of tillers/plant (38%). In contrast, number of filled grains/panicle, and yield/plant (g) was recorded for their highest heritability value viz. 93 and 91% correspondingly. Cluster analysis based on 18 traits grouped 27 rice genotypes into six clusters. Cluster I was the biggest, which comprised 17 genotypes, accounted for about 62.96% of total population. The multivariate analysis suggested that the genotype ‘Chokoto 14’ could be hybridized with ‘IR 5533-55-1-11’ and ‘IR 5533-PP 854-1’ for broadening the gene pool of blast resistant upland rice germplasms for yield and other favorable characters.

Keywords: blast resistant, diversity analysis, heritability, upland rice

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Authors: Abhishek Agarwal, Manoj Sarda, Juhi Kaushik, Vatsal Sanjay, Arup Kumar Das

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Propagation of fire through a non-air conditioned railway compartment is studied by virtue of numerical simulations. Simultaneous computational fire dynamics equations, such as Navier-Stokes, lumped species continuity, overall mass and energy conservation, and heat transfer are solved using finite volume based (for radiation) and finite difference based (for all other equations) solver, Fire Dynamics Simulator (FDS). A single coupe with an eight berth occupancy is used to establish the numerical model, followed by the selection of a three coupe system as the fundamental unit of the locomotive compartment. Heat Release Rate Per Unit Area (HRRPUA) of the initial fire is varied to consider a wide range of compartmental fires. Parameters, such as air inlet velocity relative to the locomotive at the windows, the level of interaction with the ambiance and closure of middle berth are studied through a wide range of numerical simulations. Almost all the loss of lives and properties due to fire breakout can be attributed to the direct or indirect exposure to flames or to the inhalation of toxic gases and resultant suffocation due to smoke and soot. Therefore, the temporal stature of fire and smoke are reported for each of the considered cases which can be used in the present or extended form to develop guidelines to be followed in case of a fire breakout.

Keywords: fire dynamics, flame propagation, locomotive fire, soot flow pattern, non-air-conditioned coaches

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Authors: Shaleni Bajpai, Nancy Stephan

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Various designs of women’s kurtis with different styles, motifs and prints were available in market but none of the kurtis was found in army print. Mostly army prints are used for men’s wear like jackets, trousers, caps, bags. The main colours available in military prints were beige, parrot green, red, dark blue, light blue, orange, bottle green, pink and the original military green colour. As the original camouflage is banned in civil wears so the different variety and colours were used in this study to popularize army prints in women’s wear. The aim of this project was to construct different styles of women kurti’s with various colours of different military prints. Mood board, inspiration and colour board was prepared to design the kurtis. The fabric used for construction was army printed poplin and crepe. The designing and construction of kurti’s were divided into two categories such as - casual and party wear. Casual wear had simple silhouette like a-line, high-low and waist coat style whereas party wear included princess line, panelled and bandhani style. Structured questionnaire was prepared to assess the acceptance of newly designed kurtis with respect to colour combination, overall appearance and cost. Purposively sampling method was adopted for selection of respondents. Opinion was taken from 100 women of various age groups. The result and analysis was presented through graph and percentage. Kurtis in army print of both the categories were appreciated by the respondents.

Keywords: army, kurti, casual wear, party wear

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Authors: Sergejs Kolesovs, Armands Vigants

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The use of dairy industry by-products and wastewater as a cheap substrate for microalgal growth is gaining recognition. However, the mechanisms of lactose utilization remain understudied, limiting the potential of successful microalgal biomass production using various dairy by-products, such as whey and permeate. The necessity for microalgae to produce a specific enzyme, β-galactosidase, requires the selection of suitable strains. This study focuses on a freshwater microalgal isolate's ability to grow on a semi-synthetic medium supplemented with lactose. After 10 days of agitated cultivation, an axenic microalgal isolate achieved significantly higher biomass production under mixotrophic growth conditions (0.86 ± 0.07 g/L, dry weight) than heterotrophic growth (0.46 ± 0.04 g/L). Moreover, mixotrophic cultivation had significantly higher biomass production compared to photoautotrophic growth (0.67 ± 0.05 g/L). The activity of β-galactosidase was detected in both supernatant and microalgal biomass under mixotrophic and heterotrophic growth conditions, showing the potential of extracellular and intracellular mechanisms of enzyme production. However, the main limiting factor in this study was the increase of pH values during the cultivation, significantly reducing the activity of the β-galactosidase enzyme after 3rd day of cultivation. It highlights the need for stricter control of growth parameters to ensure the enzyme's activity. Further research will assess the isolate's suitability for dairy by-product bioconversion and biomass composition.

Keywords: microalgae, lactose, whey, permeate, beta-galactosidase, mixotrophy, heterotrophy

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Authors: Azeem Alphonce

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In Pakistan, there is a variety of skin tones and colors across all provinces. However, a fair complexion is one of the standards of beauty among females in Pakistan, which creates insecurities in dark-complexioned females. This research is a critical discourse analysis of the language used on beauty products for females in Pakistan. The purpose was to analyze the language used on female beauty products using Van Dijk's three-stage socio-cognitive model to understand what message is received from the few words written and repeated across the packaging of various facial products, why such language is used and what are its wider socio-cognitive effects? The criterion for the selection of beauty products was skin whitening terminologies and the language used on these products. The results showed that over 57 per cent of products utilized skin-whitening terms. The adjectives written on the package indicate that fairer skin is the ultimate beauty goal of females. The analysis explored how the language reinforces unfair beauty standards and perpetuates colorism. It was concluded that female beauty products utilize discriminatory discourse by marginalizing individuals of darker skin tones. Fairer skin is promoted, whereas darker skin is referred to as a problem, flaw or imperfection. Socially shared mental models seem to have caused beauty companies to exploit and promote perceptions of colorism in society. Therefore, such discourse should be prevented, and beauty companies should utilize their discourse to promote acceptance of various skin tones.

Keywords: language, skin whitening products, beauty standards, social mental models

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Authors: Reza Moslemi, Sebastien Perrier

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Water infrastructure deterioration can result in increased operational costs owing to increased repair needs and non-revenue water and consequently cause a reduced level of service and customer service satisfaction. Various water main condition assessment technologies have been introduced to the market in order to evaluate the level of pipe deterioration and to develop appropriate asset management and pipe renewal plans. One of the challenges for any condition assessment and inspection program is to determine the percentage of the water network and the combination of pipe segments to be inspected in order to obtain a meaningful representation of the status of the entire water network with a desirable level of accuracy. Traditionally, condition assessment has been conducted by selecting pipes based on age or location. However, this may not necessarily offer the best approach, and it is believed that by using a smart sampling methodology, a better and more reliable estimate of the condition of a water network can be achieved. This research investigates three different sampling methodologies, including random, stratified, and systematic. It is demonstrated that selecting pipes based on the proposed clustering and sampling scheme can considerably improve the ability of the inspected subset to represent the condition of a wider network. With a smart sampling methodology, a smaller data sample can provide the same insight as a larger sample. This methodology offers increased efficiency and cost savings for condition assessment processes and projects.

Keywords: condition assessment, pipe degradation, sampling, water main

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Authors: Neha Ahirwar

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In the contemporary digital era, the rise of credit card fraud poses a significant threat to both financial institutions and consumers. As fraudulent activities become more sophisticated, there is an escalating demand for robust and effective fraud detection mechanisms. Advanced machine learning algorithms have become crucial tools in addressing this challenge. This paper conducts a thorough examination of the design and evaluation of a credit card fraud detection system, utilizing four prominent machine learning algorithms: random forest, logistic regression, decision tree, and XGBoost. The surge in digital transactions has opened avenues for fraudsters to exploit vulnerabilities within payment systems. Consequently, there is an urgent need for proactive and adaptable fraud detection systems. This study addresses this imperative by exploring the efficacy of machine learning algorithms in identifying fraudulent credit card transactions. The selection of random forest, logistic regression, decision tree, and XGBoost for scrutiny in this study is based on their documented effectiveness in diverse domains, particularly in credit card fraud detection. These algorithms are renowned for their capability to model intricate patterns and provide accurate predictions. Each algorithm is implemented and evaluated for its performance in a controlled environment, utilizing a diverse dataset comprising both genuine and fraudulent credit card transactions.

Keywords: efficient credit card fraud detection, random forest, logistic regression, XGBoost, decision tree

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Authors: Kei Okubo, Yosuke Kurihara, Takashi Kaburagi, Kajiro Watanabe

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Many of the ever-growing elderly population require exercise, such as running, for health management. One important element of a runner’s training is the choice of shoes for exercise; shoes are important because they provide the interface between the feet and road. When we purchase shoes, we may instinctively choose a pair after trying on many different pairs of shoes. Selecting the shoes instinctively may work, but it does not guarantee a suitable fit for running activities. Therefore, if we could select suitable shoes for each runner from the viewpoint of brain activities, it would be helpful for validating shoe selection. In this paper, we describe how brain activities show different characteristics during particular task, corresponding to different properties of shoes. Using five subjects, we performed a verification experiment, applying weight, softness, and flexibility as shoe properties. In order to affect the shoe property’s differences to the brain, subjects run for ten min. Before and after running, subjects conducted a paced auditory serial addition task (PASAT) as the particular task; and the subjects’ brain activities during the PASAT are evaluated based on oxyhemoglobin and deoxyhemoglobin relative concentration changes, measured by near-infrared spectroscopy (NIRS). When the brain works actively, oxihemoglobin and deoxyhemoglobin concentration drastically changes; therefore, we calculate the maximum values of concentration changes. In order to normalize relative concentration changes after running, the maximum value are divided by before running maximum value as evaluation parameters. The classification of the groups of shoes is expressed on a self-organizing map (SOM). As a result, deoxyhemoglobin can make clusters for two of the three types of shoes.

Keywords: brain activities, NIRS, PASAT, running shoes

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Authors: Behailu Bezabih Ayele

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Illustrative expressions in art education and in overall learning are being given increasing attention in the transmission of knowledge. The objective of this paper, therefore, is to present an analysis of graffiti on school desks-a way of smuggling knowledge on the edge of classroom education and learning. The methodological approach focuses on the systematic collection and selection of desk graffiti. Four schools are chosen to reflect socioeconomic status and gender composition. The analysis focused on the categorization of graffiti by genre. This was followed by an analysis of the style, intensity as well as content of the messages in terms of overall social impacts. The paper grounds the analysis by reviewing the literature on modern education and art education in the Ethiopian context, as well as the place of desk graffiti. The findings generally show that the school desks and the school environment, by and large, have managed to serve as vessels through which formal and informal knowledge is acquired, transmitted, engrained into the students and transformed into messages by the students. The desks have also apparently served as a springboard to maximize the interfaces between several ideas and disciplines and communications. However, the very fact that the desks serve as massive channels of expression and knowledge transmission also points to a lack of breadth availability of channels of expression, perhaps confounding the ability of classrooms as means of outlet of expression and documentation for the students. This points to the need for efforts in education policy and funding of artistic endeavors for young students.

Keywords: artistic expression, desk graffiti, education, school children, Ethiopia

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Authors: Olatokunbo Shoyemi, Mario Brito, Ian Dawson

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In recent times, the Nigerian motor insurers have experienced high volume of motor insurance claim pay-outs and insignificant contribution to the net premium income of the Nigerian insurance market, which has been a major concern for the shareholders/stakeholders. It has been argued that there are many factors that have brought about these concerns. However, anecdotal evidence (ongoing debates among industry practitioners) suggests prevalence of fraud due to poor practices in motor insurance business in Nigeria. This study is therefore aimed to carry out an assessment of fraud in motor insurance claims as perceived by experts in the Nigerian insurance market. This study adopted a descriptive research design, and the analysis was built on a survey among insurance experts in Nigeria using a designed questionnaire. A purposive and snowball sampling were used to select our sample (N = 120) - representing a selection of all professionally qualified insurance experts in Nigeria insurance industry. The study found that Nigerian insurance experts (i) largely agree that there is a problematic level of fraud in the Nigerian motor insurance industry; (ii) perceive soft fraud to be about 3 times more common than hard fraud in the Nigerian motor insurance industry, and (iii) strongly agree there are problematic impacts from fraud on the solvency of the Nigerian motor insurers. This paper has provided an empirical understanding of the existence, extent, and impact of fraud risks within the Nigerian insurance market based on expert knowledge and insights rather than, as has often been the case, a reliance on individual anecdotes.

Keywords: claims, net premium income, motor insurance, soft fraud, hard fraud

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Authors: David Calderon Villegas, Thomas Kaltizky

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Run-of-river (RoR) hydropower projects represent a viable, clean, and cost-effective alternative to dam-based plants and provide decentralized power production. However, RoR schemes cost-effectiveness depends on the proper selection of site and design flow, which is a challenging task because it requires multivariate analysis. In this respect, this study presents the development of an investment decision support tool for assessing the optimal size of an RoR scheme considering the technical, environmental, and cost constraints. The net present value (NPV) from a project perspective is used as an objective function for supporting the investment decision. The tool has been tested by applying it to an actual RoR project recently proposed in Colombia. The obtained results show that the optimum point in financial terms does not match the flow that maximizes energy generation from exploiting the river's available flow. For the case study, the flow that maximizes energy corresponds to a value of 5.1 m3/s. In comparison, an amount of 2.1 m3/s maximizes the investors NPV. Finally, a sensitivity analysis is performed to determine the NPV as a function of the debt rate changes and the electricity prices and the CapEx. Even for the worst-case scenario, the optimal size represents a positive business case with an NPV of 2.2 USD million and an IRR 1.5 times higher than the discount rate.

Keywords: small hydropower, renewable energy, RoR schemes, optimal sizing, objective function

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Authors: Saifullah Khalid

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Governance and good governance are among the main topics in international discussions about the success factors for social and economic development. The image of developing countries as for example Pakistan in this respect is bad (in TI Corruption Index nr. among countries). Additionally, the police are among the sectors and organizations which are seen as most corrupt in many countries. However, in case of Pakistan there seem to be exceptions to the rule, and improvement can be brought in specific police departments. This paper represents the findings of Islamabad traffic police (ITP). In Pakistan, the police, in general, have been stigmatized for being the most corrupt department in the country. However, the few recent examples of Motorway police and its replicated model of Islamabad traffic police changed the perception about police and policing. These police forces have shown that Policing in Pakistan can be changed for better. In this paper, the research question that is addressed is: How corrupt are (traffic) police forces in Pakistan and what factors influence corruption within that police force? And What lessons can be learned from that to improve police integrity? Both qualitative and quantitative tools are utilized for data collection. The overall picture of the factors is not so easy to interpret and summarise. Nevertheless paying a better salary does not seem to limit integrity violations, neither does recruitment and selection and leadership, while supervision and control, training and stimulating the positive and limiting the negative elements of culture appear to be important in curbing (sometimes specific) integrity violations in the context of Pakistani police forces. The study also leads to a number of suggestions for curbing corruption and other integrity violations in the Pakistan police.

Keywords: corruption control, governance, integrity violations, Islamabad traffic police, Pakistan

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Authors: Saeed Karimi, Ali Behbahaninia

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In this study, the design and optimization of combined cooling, heating, and power system (CCHP) for a sustainable building are dealt with. Sustainable buildings are environmentally responsible and help us to save energy also reducing waste, pollution and environmental degradation. CCHP systems are widely used to save energy sources. In these systems, electricity, cooling, and heating are generating using just one primary energy source. The selection of the size of components based on the maximum demand of users will lead to an increase in the total cost of energy and equipment for the building complex. For this purpose, a system was designed in which the prime mover (gas turbine), heat recovery boiler, and absorption chiller are lower than the needed maximum. The difference in months with peak consumption is supplied with the help of electrical absorption chiller and auxiliary boiler (and the national electricity network). In this study, the optimum capacities of each of the equipment are determined based on Thermo economic method, in a way that the annual capital cost and energy consumption will be the lowest. The design was done for a gas turbine prime mover, and finally, the optimum designs were investigated using exergy analysis and were compared with a traditional energy supply system.

Keywords: sustainable building, CCHP, energy optimization, gas turbine, exergy, thermo-economic

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Authors: Ting Li Liu

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‘Leftover woman’ or ‘3S’ woman is the term used to describe a well-educated, high income, independent woman who is single and never married around 30 years in Chinese society. With the naming of this demographic of ‘leftover women’, their family, dating culture, mate selection and marriage attract public concern. Massive media representations of ‘leftover women’ occur daily; the research aims to present several media representations of women’s anxiety about their singlehood and related marital issues around thirty. The research triangulates two areas of media representation of ‘leftover women’: films and audience reviews on ‘Douban Movie’ website. Drawing on traditional media studies, Fairclough’s critical discourse analysis combined with multimodal techniques is applied to the research to analyze the representations of ‘leftover women’ and their implications for marital culture in China, in conjunction with a feminist perspective. The conference paper will discuss two case studies: the film ‘The last woman standing’ and ‘I Do’. Paying attention to different aspects of ‘leftover women’, the research aims to re-examine the representations of ‘leftover women’ in selected scenes, such as their age anxiety, family, marriage, dating process, careers, etc. The paper also includes public beliefs about ‘leftover women’ from online audience reviews. In conclusion, the emergence of ‘leftover women’ is a reflection of Chinese tradition’s impact on people’s lives and new changes in Chinese families and their attitude to marriage.

Keywords: leftover women, marriage, family, media culture, China

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Authors: Y. H. Wang, C. C. Hsieh

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Good service design can increase organization revenue and consumer satisfaction while reducing labor and time costs. The problems facing consumers in the original serve model for eyewear and optical industry includes the following issues: 1. Insufficient information on eyewear products 2. Passively dependent on recommendations, insufficient selection 3. Incomplete records on progression of vision conditions 4. Lack of complete customer records. This study investigates the case of Kobayashi Optical, applying the Theory of Inventive Problem Solving (TRIZ) to develop innovative solutions for eyewear and optical industry. Analysis results raise the following conclusions and management implications: In order to provide customers with improved professional information and recommendations, Kobayashi Optical is suggested to establish customer purchasing records. Overall service efficiency can be enhanced by applying data mining techniques to analyze past consumer preferences and purchase histories. Furthermore, Kobayashi Optical should continue to develop a 3D virtual trial service which can allow customers for easy browsing of different frame styles and colors. This 3D virtual trial service will save customer waiting times in during peak service times at stores.

Keywords: theory of inventive problem solving (TRIZ), service design, augmented reality (AR), eyewear and optical industry

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: S. J. M. Mohd Saleh, S. Guo

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Composite materials have become an important option for the primary structure of aircraft due to their design flexibility and ability to improve the overall performance. At present, the option for composite usage in aircraft component is largely based on experience, knowledge, benchmarking and partly market driven. An inevitable iterative design during the design stage and validation process will increase the development time and cost. This paper aims at presenting the correlation between laminate and composite thin-wall beam structure, which contains the theoretical and numerical investigations on stiffness estimation of composite aerostructures with applications to aircraft wings. Classical laminate theory and thin-walled beam theory were applied to define the correlation between 1-dimensional composite laminate and 2-dimensional composite beam structure, respectively. Then FE model was created to represent the 3-dimensional structure. A detailed study on stiffness matrix of composite laminates has been carried out to understand the effects of stacking sequence on the coupling between extension, shear, bending and torsional deformation of wing box structures for 1-dimensional, 2-dimensional and 3-dimensional structures. Relationships amongst composite laminates and composite wing box structures of the same material have been developed in this study. These correlations will be guidelines for the design engineers to predict the stiffness of the wing box structure during the material selection process and laminate design stage.

Keywords: aircraft design, aircraft structures, classical lamination theory, composite structures, laminate theory, structural design, thin-walled beam theory, wing box design

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Authors: Kemka Ihemelandu, Chukwuemeka Ihemelandu

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Melanoma remains a public health crisis, with incidence rates increasing rapidly in the past decades. Improving diagnostic accuracy to decrease misdiagnosis using Artificial intelligence (AI) continues to be documented. Unfortunately, unintended racially biased outcomes, a product of lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone, have increasingly been recognized as a problem.Resulting in noted limitations of the accuracy of the Convolutional neural network (CNN)models. CNN models are prone to biased output due to biases in the dataset used to train them. Our aim in this study was the optimization of convolutional neural network algorithms to mitigate bias in the automated diagnosis of melanoma. We hypothesized that our proposed training algorithms based on a data augmentation method to optimize the diagnostic accuracy of a CNN classifier by generating new training samples from the original ones will reduce bias in the automated diagnosis of melanoma. We applied geometric transformation, including; rotations, translations, scale change, flipping, and shearing. Resulting in a CNN model that provided a modifiedinput data making for a model that could learn subtle racial features. Optimal selection of the momentum and batch hyperparameter increased our model accuracy. We show that our augmented model reduces bias while maintaining accuracy in the automated diagnosis of melanoma.

Keywords: bias, augmentation, melanoma, convolutional neural network

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Authors: Anjela Koblischka-Veneva, Michael R. Koblischka

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In this contribution, the Transmission-Kikuchi Diffraction (TKD, or sometimes called t-EBSD) is applied to bulk, melt-grown YBa₂Cu₃O₇ (YBCO) superconductors prepared by the MTMG (melt-textured melt-grown) technique and the infiltration growth (IG) technique. TEM slices required for the analysis were prepared by means of Focused Ion-Beam (FIB) milling using mechanically polished sample surfaces, which enable a proper selection of the interesting regions for investigations. The required optical transparency was reached by an additional polishing step of the resulting surfaces using FIB-Ga-ion and Ar-ion milling. The improved spatial resolution of TKD enabled the investigation of the tiny YBa₂Cu₃O₅ (Y-211) particles having a diameter of about 50-100 nm embedded within the YBCO matrix and of other added secondary phase particles. With the TKD technique, the microstructural properties of the YBCO matrix are studied in detail. It is observed that the matrix shows the effects of stress/strain, depending on the size and distribution of the embedded particles, which are important for providing additional flux pinning centers in such superconducting bulk samples. Using the Kernel Average Misorientation (KAM) maps, the strain induced in the superconducting matrix around the particles, which increases the flux pinning effectivity, can be clearly revealed. This type of analysis of the EBSD/TKD data is, therefore, also important for other material systems, where nanoparticles are embedded in a matrix.

Keywords: transmission Kikuchi diffraction, EBSD, TKD, embedded particles, superconductors YBa₂Cu₃O₇

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Authors: Syed Ahsan, Saleh Alshomrani, Ishtiaq Rasool, Ali Hassan

Abstract:

In this oral presentation, we will provide an overview of the technical and semantic architecture of a desert border security and critical infrastructure protection security system. Modern border security systems are designed to reduce the dependability and intrusion of human operators. To achieve this, different types of sensors are use along with video surveillance technologies. Application of these technologies in a harsh desert environment of Saudi Arabia poses unique challenges. Environmental and geographical factors including high temperatures, desert storms, temperature variations and remoteness adversely affect the reliability of surveillance systems. To successfully implement a reliable, effective system in a harsh desert environment, the following must be achieved: i) Selection of technology including sensors, video cameras, and communication infrastructure that suit desert environments. ii) Reduced power consumption and efficient usage of equipment to increase the battery life of the equipment. iii) A reliable and robust communication network with efficient usage of bandwidth. Also, to reduce the expert bottleneck, an ontology-based intelligent information systems needs to be developed. Domain knowledge unique and peculiar to Saudi Arabia needs to be formalized to develop an expert system that can detect abnormal activities and any intrusion.

Keywords: border security, sensors, abnormal activity detection, ontologies

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Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

Abstract:

In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: brain-computer interface, speech recognition, artificial neural network, electroencephalography, EEG, wernicke area

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Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

Abstract:

Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: android, API Calls, machine learning, permissions combination

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Authors: Warunpun Kongsom, Chaiwat Kongsom

Abstract:

The objective of this study was to investigate the awareness, knowledge and consumer behavior towards organic products in Thailand. For this study, a purposive sampling technique was used to identify a sample group of 2,575 consumers over the age of 20 years who intended or made purchases from 1) green shops; 2) supermarkets with branches; and, 3) green markets. A questionnaire was used for data collection across the country. Descriptive statistics were used for data analysis. The results showed that more than 92% of consumers were aware of organic agriculture, but had less knowledge about it. More than 60% of consumers knew that organic agriculture production and processing did not allow the use of chemicals. And about 40% of consumers were confused between the food safety logo and the certified organic logo, and whether GMO was allowed in organic agriculture practice or not. In addition, most consumers perceived that organic agricultural products, good agricultural practice (GAP) products, agricultural chemicals free products, and hydroponic vegetable products had the same standard. In the view of organic consumers, the organic Thailand label was the most seen and reliable among various organic labels. Less than 3% of consumers thought that the International Federation of Organic Agriculture Movements (IFOAM) Global Organic Mark (GOM) was the most seen and reliable. For the behaviors of organic consumers, they purchased organic products mainly at the supermarket and green shop (55.4%), one to two times per month, and with a total expenditure of about 200 to 400 baht each time. The main reason for buying organic products was safety and free from agricultural chemicals. The considered factors in organic product selection were price (29.5%), convenience (22.4%), and a reliable certification system (21.3%). The demands for organic products were mainly rice, vegetables and fruits. Processed organic products were relatively small in quantity.

Keywords: consumer behavior, consumer knowledge, organic products, Thailand

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Authors: Rajkumar Kolangarakandy

Abstract:

Feature extraction and selection is the primary part of any mammogram classification algorithms. The choice of feature, attribute or measurements have an important influence in any classification system. Discrete Wavelet Transformation (DWT) coefficients are one of the prominent features for representing images in frequency domain. The features obtained after the decomposition of the mammogram images using wavelet transformations have higher dimension. Even though the features are higher in dimension, they were highly correlated and redundant in nature. The dimensionality reduction techniques play an important role in selecting the optimum number of features from the higher dimension data, which are highly correlated. PCA is a mathematical tool that reduces the dimensionality of the data while retaining most of the variation in the dataset. In this paper, a multilevel classification of mammogram images using reduced discrete wavelet transformation coefficients and lazy classifiers is proposed. The classification is accomplished in two different levels. In the first level, mammogram ROIs extracted from the dataset is classified as normal and abnormal types. In the second level, all the abnormal mammogram ROIs is classified into benign and malignant too. A further classification is also accomplished based on the variation in structure and intensity distribution of the images in the dataset. The Lazy classifiers called Kstar, IBL and LWL are used for classification. The classification results obtained with the reduced feature set is highly promising and the result is also compared with the performance obtained without dimension reduction.

Keywords: PCA, wavelet transformation, lazy classifiers, Kstar, IBL, LWL

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Authors: Kazuma Mizukoshi

Abstract:

Are electoral politics in contemporary Brazil still local in organization and focus? The importance of this question lies in its paradoxical trajectories. First, often coupled with institutional and sociological ‘barriers’ (e.g. the selection and election of candidates relatively loyal to the local party leadership, the predominance of territorialized electoral campaigns, and the resilience of political clientelism), the regionalization of electoral politics has been a viable and practical solution especially for pragmatic politicians in some Latin American countries. On the other hand, some leftist parties that once served as minor opposition forces at the time of foundational or initial elections have certainly expanded vote shares. Some were eventually capable of holding most (if not a majority) legislative seats since the 1990s. Though not yet rigorously demonstrated, theoretically implicit in the rise of leftist parties in legislative elections is the gradual (if not complete) nationalization of electoral support—meaning the growing equality of a party’s vote share across electoral districts and its change over time. This study will develop four hypotheses to explain the dynamics of party nationalization in contemporary Brazil: district magnitude, ethnic and class fractionalization of each district, voting intentions in federal and state executive elections, and finally the left-right stances of electorates. The study will demonstrate these hypotheses by closely working with the Brazilian Electoral Study (2002-2014).

Keywords: party nationalization, presidential coattails, Left, Brazil

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