Search results for: multiple deprivation

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: Yakubu Suleiman, S. A. Musa

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Nigeria is the largest cowpea producer in the world, accounting for about 45%, followed by Brazil with about 17%. Cowpea is grown in Kano, Bauchi, Katsina, Borno in the north, Oyo in the west, and to the lesser extent in Enugu in the east. This study was conducted to determine the input–output relationship of Cowpea production in Kano, Katsina, and Jigawa states of Nigeria. The data were collected with the aid of 1000 structured questionnaires that were randomly distributed to Cowpea farmers in the three states mentioned above of the study area. The data collected were analyzed using regression analysis (Cobb–Douglass production function model). The result of the regression analysis revealed the coefficient of multiple determinations, R2, to be 72.5% and the F ration to be 106.20 and was found to be significant (P < 0.01). The regression coefficient of constant is 0.5382 and is significant (P < 0.01). The regression coefficient with respect to labor and seeds were 0.65554 and 0.4336, respectively, and they are highly significant (P < 0.01). The regression coefficient with respect to fertilizer is 0.26341 which is significant (P < 0.05). This implies that a unit increase of any one of the variable inputs used while holding all other variables inputs constants, will significantly increase the total Cowpea output by their corresponding coefficient. This indicated that farmers in the study area are operating in stage II of the production function. The result revealed that Cowpea farmer in Kano, Jigawa and Katsina States realized a profit of N15,997, N34,016 and N19,788 per hectare respectively. It is hereby recommended that more attention should be given to Cowpea production by government and research institutions.

Keywords: coefficient, constant, inputs, regression

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Authors: A. A. Ghanim

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The Kingdom of Saudi Arabia (KSA) is heading towards a severe and rapidly expanding water crisis, which can have negative impacts on the country’s environment and economy. Of the total water consumption in KSA, the agricultural sector accounts for nearly 87% of the total water use and, therefore, any attempt that overlooks this sector will not help in improving the sustainability of the country’s water resources. KSA Vision 2030 gives priority of water use in the agriculture sector for the regions that have natural renewable water resources. It means that there is little concern for making reuse of municipal wastewater for irrigation purposes in any region in general and in water-scarce regions in particular. The use of treated wastewater is very limited in Saudi Arabia, but it has very considerable potential for future expansion due its numerous beneficial uses. This study reviews the current situation of water resources in Saudi Arabia, providing more highlights on agriculture and wastewater reuse. The reviewed study is proposing some corrective measures for development and better management of water resources in the Kingdom. Suggestions also include consideration of treated water as an alternative source for irrigation in some regions of the country. The study concluded that a sustainable solution for the water crisis in KSA requires implementation of multiple measures in an integrated manner. The integrated solution plan should focus on two main directions: first, improving the current management practices of the existing water resources; second, developing new water supplies from both conventional and non-conventional sources.

Keywords: Saudia Arabia, water resources, water crises, wastewater reuse

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Authors: Rana Praween Kumar

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Preterm-low birth weight delivery is a major cause of infant morbidity and mortality in developing countries and has been linked to poor periodontal health during pregnancy. Gingivitis and chronic periodontitis are highly prevalent chronic inflammatory oral diseases. The detection and diagnosis of these common diseases is a fundamentally important component of oral health care. This study is intended to investigate predisposing and enabling factors as determinants of oral health indicators in pregnancy as well as the association between periodontal problems during pregnancy with age and socio economic status of the individual. A community –based prospective cohort study will be conducted in Jamshedpur, Jharkhand, India among pregnant women using completed interviews and a full mouth oral clinical examination using the CPITN (Community Periodontal Index of Treatment Need) and OHI-S (Simplified Oral Hygiene) indices with adequate sample size and informed consent to the patient following proper inclusion and exclusion criteria. Multiple logistic regression analyses will be used to identify independent determinants of periodontal problems and use of dental services during pregnancy. Analysis of covariance (ANCOVA) will be used to investigate the relationship between periodontal problems with the age and socioeconomic status. The result will help in proper monitoring of periodontal health during pregnancy encouraging the delivery of healthy child and the maintenance of proper health of the mother.

Keywords: infant, periodontal problems, pregnancy, pre-term-low birth weight delivery

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Authors: Ahmad Mohsin, Syda Fatima, Falak Nawaz, Aman Ullah Khan

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Selection of an appropriate architectural style is vital to the success of target web service under development. The nature of architecture design and selection for service-oriented computing applications is quite different as compared to traditional software. Web Services have complex and rigorous architectural styles to choose. Due to this, selection for accurate architectural style for web services development has become a more complex decision to be made by architects. Architectural style selection is a multi-criteria decision and demands lots of experience in service oriented computing. Decision support systems are good solutions to simplify the selection process of a particular architectural style. Our research suggests a new approach using DSS for selection of architectural styles while developing a web service to cater FRs and NFRs. Our proposed DSS helps architects to select right web service architectural pattern according to the domain and non-functional requirements. In this paper, a rule base DSS has been developed using CLIPS (C Language Integrated Production System) to support decisions using multi-criteria requirements. This DSS takes architectural characteristics, domain requirements and software architect preferences for NFRs as input for different architectural styles in use today in service-oriented computing. Weighted sum model has been applied to prioritize quality attributes and domain requirements. Scores are calculated using multiple criterions to choose the final architecture style.

Keywords: software architecture, web-service, rule-based, DSS, multi-criteria requirements, quality attributes

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Authors: Ahmed A. Freewan

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The current research explored the quality of daylight and classroom visual environments and their impact on human performance and visual comfort in hot climates like Jordan. The research used multiple methods, including real experiments, simulation, focus groups and questionnaires. Therefore, seven different designs and visual environments have been implemented in south-facing classrooms with high WWR in recently constructed modern schools in Jordan. These visual environments have been created by applying various innovative shading systems in the seven classrooms to enable real interaction with the users of these spaces: students and teachers. The main aims of the research were to introduce distinct measures for daylight quality and to expand the scope of daylight studies in schools by connecting directly with students and teachers through focus groups or questionnaires. The main findings of this research showed the importance of studying uniformity not only across the entire classroom but also in different zones in relation to the windows and the front wall where the whiteboard is located, and the teacher stands. Moreover, it has been found that uniformity analysis in classrooms extends beyond just the horizontal plane, encompassing the relationship with the illuminance level on the front wall as well. Study the fenestration design impact on critical function requirements in addition to studying the dynamic of daylight over time, especially glare, uniformity and veiling reflection.

Keywords: daylight, uniformity, WWR, innovative shading systems

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Authors: Ines Vieira, Luisa Faria

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Globally, half of all mental disorders begin by age 14 and the current gap of poorly addressed adolescent mental health has future consequences in adulthood. Schoolwork pressure to achieve good performance in secondary education might lead to lower levels of life satisfaction in youth and individual emotional competencies are crucial in this life stage. The present study aimed to determine how mindfulness relates to school achievements and well-being in adolescence and whether such a relationship might be mediated by emotional intelligence. We also studied the moderation interaction effects of gender and the involvement in non-curricular activities. A sample of 597 Portuguese adolescents aged 15 to 17 years old (N=597; 292 girls; 298 boys), enrolled in secondary education completed self-report measures of mindfulness (CAMM), emotional intelligence (TEIQue-ASF) and well-being (SWLS) in their Portuguese versions. Using SPSS and AMOS, the results were obtained through path analyses and multiple linear regression. A Confirmatory Factor Analysis was also conducted. The correlation coefficients reported a positive and statistically significant relationship between mindfulness, emotional intelligence and well-being. Regression analysis indicated that mindfulness reduced its influence on well-being and on school results when emotional intelligence was added to the model. Overall, our results provided further evidence supporting the development of robust hypotheses by perceiving the relevance of mindfulness and individual emotional competencies to school achievements and well-being in a way of improving adolescents’ health, wellness, and school success.

Keywords: mindfulness, emotional intelligence, well-being, adolescence, school

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Authors: Sushma Ghogale

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With a surge in user-generated content or feedback or reviews on the internet, it has become possible and important to know consumers' opinions about products and services. This data is important for both potential customers and businesses providing the services. Data from social media is attracting significant attention and has become the most prominent channel of expressing an unregulated opinion. Prospective customers look for reviews from experienced customers before deciding to buy a product or service. Several websites provide a platform for users to post their feedback for the provider and potential customers. However, the biggest challenge in analyzing such data is in extracting latent features and providing term-level analysis of the data. This paper proposes an approach to use topic modeling to classify the reviews into topics and conduct sentiment analysis to mine the opinions. This approach can analyse and classify latent topics mentioned by reviewers on business sites or review sites, or social media using topic modeling to identify the importance of each topic. It is followed by sentiment analysis to assess the satisfaction level of each topic. This approach provides a classification of hotel reviews using multiple machine learning techniques and comparing different classifiers to mine the opinions of user reviews through sentiment analysis. This experiment concludes that Multinomial Naïve Bayes classifier produces higher accuracy than other classifiers.

Keywords: latent Dirichlet allocation, topic modeling, text classification, sentiment analysis

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Authors: Abdullah Abdulsalam, Adamu Balami, Olajide Olubanji Olowe, Maryam Abdu Abdulkadir

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The development and persistence of low back pain may be influenced by several factors which include lifestyle factors, previous pain symptoms, psychological factors, workplace factors as well as socio-demographic variables. The focus of this study was to determine the socio-demographic and work related variables as a predictor of persistence of back pain and disability among civil servants receiving physiotherapy in tertiary health institutions in Kano, Nigeria. One hundred and twenty nine newly referred low back pain patients for physiotherapy participated in the study. This study was a cross sectional study involving patients that were newly diagnosed of back pain, referred and received physiotherapy. The convenience sampling technique was used to select the patients based on the inclusion criteria. The data obtained was analysed using simple percentage and multiple regression for stated hypothesis at 0.05 level of significance. The findings reveal that all the variables are not significant predictor of persistence of back pain and disability. The study recommended that determinants of low back pain recovery by clinician should include other clinical factors not only reduction in pain intensity.

Keywords: socio-demographic, work related variables, Kano state, back pain and disability

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Authors: Huawei Bai, Jianguo Yao, Fellow, IEEE

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Atrial fibrillation (AF) is the most common form of heart arrhythmia and is closely associated with mortality and morbidity in heart failure, stroke, and coronary artery disease. The development of single spot optical sensors enables widespread photoplethysmography (PPG) screening, especially for AF, since it represents a more convenient and noninvasive approach. To our knowledge, most existing studies based on public and unbalanced datasets can barely handle the multiple noises sources in the real world and, also, lack interpretability. In this paper, we construct a large- scale PPG dataset using measurements collected from PPG wrist- watch devices worn by volunteers and propose an attention-based two-stream heterogeneous neural network (TSHNN). The first stream is a hybrid neural network consisting of a three-layer one-dimensional convolutional neural network (1D-CNN) and two-layer attention- based bidirectional long short-term memory (Bi-LSTM) network to learn representations from temporally sampled signals. The second stream extracts latent representations from the PPG time-frequency spectrogram using a five-layer CNN. The outputs from both streams are fed into a fusion layer for the outcome. Visualization of the attention weights learned demonstrates the effectiveness of the attention mechanism against noise. The experimental results show that the TSHNN outperforms all the competitive baseline approaches and with 98.09% accuracy, achieves state-of-the-art performance.

Keywords: PPG wearables, atrial fibrillation, feature fusion, attention mechanism, hyber network

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Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

Procedia PDF Downloads 138

Authors: Muhammedamin Hussen Saad, Geoffrey Haagler, Onno Omta, Gerben Van Der Velde

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Unfolding chaos and persistent disruptions pose threats to companies’ performance especially in vulnerable settings of SME’s particularly in developing countries. Attention for resilience research in the academic world has increased considerably during the last decade looking at the number of papers published. As we are interested in adding to the understanding of the foundation and development of the concept of resilience, we focus especially on structuring the literature of business resilience in those vulnerable settings. A well-structured systematic search & review procedure was deployed. First, we defined key search terms and applied these to multiple databases (Scopus, Web of Science, Google Scholar, Emerald, and Science Direct). To make our literature search more encompassing, we augmented with co-citation, reference checking including hand searching techniques. The paper offers (1) an overview of SMEs resilience literature from 2000 up to March 2017 comprising 88 articles, and (2) special attention, within that overview, to developing countries. This review concludes that resilience literature is very much diverse in definitions and its measurements, and is inconclusive about its influencing factors. Furthermore, resilience literature is based predominantly on research in the developed world. On the bases of how the concept resilience emerges from the literature we describe distinct features of resilience, give options to extend the theoretical bases of research into resilience and describe concrete ideas for further research.

Keywords: business resilience, systematic review, SMEs, developing countries

Procedia PDF Downloads 172

Authors: Masoud Rabbani, Majede Smizadeh, Hamed Farrokhi-Asl

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We study jointly determining prices and production in a multiple period horizon under a general non-stationary stochastic demand with continuous prices. In some periods we need to increase capacity of production to satisfy demand. This paper presents a model to aid multi-period production capacity planning by quantifying the trade-off between product quality and production cost. The product quality is estimated as the statistical variation from the target performances obtained from the output tolerances of the production machines that manufacture the components. We consider different tolerance for different machines that use to increase capacity. The production cost is estimated as the total cost of owning and operating a production facility during the planning horizon.so capacity planning has cost that impact on price. Pricing products often turns out to be difficult to measure them because customers have a reservation price to pay that impact on price and demand. We decide to determine prices and production for periods after enhance capacity and consider reservation price to determine price. First we use an algorithm base on fuzzy set of the optimal objective function values to determine capacity planning by determine maximize interval from upper bound in minimum objectives and define weight for objectives. Then we try to determine inventory and pricing policies. We can use a lemma to solve a problem in MATLAB and find exact answer.

Keywords: price policy, inventory policy, capacity planning, product quality, epsilon -constraint

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Authors: Theresa N. Uzor

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The word cardiovascular fitness is a topic of much interest to people of Nigeria, especially during this time, some heart diseases run in families. Cardiovascular fitness is the ability of the heart and lungs to supply-rich blood to the working muscle tissues. This type of fitness is a health-related component of physical fitness that is brought about by sustained physical activity such as plyometric training. Plyometric is a form of advanced fitness training that uses fast muscular contractions to improve power and speed in the sports performance by coaches and athletes. Plyometric training involves a rapid stretching of muscle (eccentric phase) immediately followed by a concentric or shortening action of the same muscle and connective tissue. However, the most basic example of true plyometric training is running and can be safe for a wide variety of populations. This paper focused on building cardiovascular health through Plyometric Training. The centre focus of the article is cardiovascular fitness and plyometric training with factors of cardiovascular fitness. Plyometric training at any age provides multiple benefits even beyond weight control and weight loss, decrease the risk of cardiovascular diseases, stroke, high blood pressure, diabetes, and other diseases, among other benefits of plyometric training to cardiovascular fitness. Participation in plyometric training will increase metabolism of an individual, thereby burning more calories even when at rest and reduces weight is also among the benefits of plyometric training. Some guidelines were recommended for planning plyometric training programme to minimise the chance of injury. With plyometric training in Nigeria, fortune can change for good, especially now that there has been an increase in cardiovascular diseases within the society for great savings would be saved.

Keywords: aerobic, cardiovascular, concentric, stretch-shortening cycle, plyometric

Procedia PDF Downloads 139

Authors: Mirvat Shamseddine, Issam Lakkis

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We present an efficient, three-dimensional parallel multi-scale Direct Simulation Monte Carlo (DSMC) algorithm for the simulation of unsteady rarefied gas flows in micro/nanosystems. The algorithm employs a novel spatiotemporal adaptivity scheme. The scheme performs a fully dynamic multi-level grid adaption based on the gradients of flow macro-parameters and an automatic temporal adaptation. The computational domain consists of a hierarchical octree-based Cartesian grid representation of the flow domain and a triangular mesh for the solid object surfaces. The hybrid mesh, combined with the spatiotemporal adaptivity scheme, allows for increased flexibility and efficient data management, rendering the framework suitable for efficient particle-tracing and dynamic grid refinement and coarsening. The parallel algorithm is optimized to run DSMC simulations of strongly unsteady, non-equilibrium flows over multiple cores. The presented method is validated by comparing with benchmark studies and then employed to improve the design of micro-scale hotwire thermal sensors in rarefied gas flows.

Keywords: DSMC, oct-tree hierarchical grid, ray tracing, spatial-temporal adaptivity scheme, unsteady rarefied gas flows

Procedia PDF Downloads 299

Authors: K. A. Bindu, T. V. Raja, P. M. Rojan, A. Siby

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The multivariate path coefficient approach was employed to study the effects of various production and reproduction traits on the slaughter body weight of rabbits. Information on 562 rabbits maintained at the university rabbit farm attached to the Centre for Advanced Studies in Animal Genetics, and Breeding, Kerala Veterinary and Animal Sciences University, Kerala State, India was utilized. The manifest variables used in the study were age and weight of dam, birth weight, litter size at birth and weaning, weight at first, second and third months. The linear multiple regression analysis was performed by keeping the slaughter weight as the dependent variable and the remaining as independent variables. The model explained 48.60 percentage of the total variation present in the market weight of the rabbits. Even though the model used was significant, the standardized beta coefficients for the independent variables viz., age and weight of the dam, birth weight and litter sizes at birth and weaning were less than one indicating their negligible influence on the slaughter weight. However, the standardized beta coefficient of the second-month body weight was maximum followed by the first-month weight indicating their major role on the market weight. All the other factors influence indirectly only through these two variables. Hence it was concluded that the slaughter body weight can be predicted using the first and second-month body weights. The principal components were also developed so as to achieve more accuracy in the prediction of market weight of rabbits.

Keywords: component analysis, multivariate, slaughter, regression

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Authors: Yoseph Gela Ali

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Inadequate quality and quantity diet is one of the major reasons for high levels of malnutrition in pregnant women. Across-sectional survey was conducted in Shashemene District, Southern Oromia Region. A two-stage cluster sampling technique was used to select a representative sample of 15190 pregnant women aged 20-50 years from four rural villages Energy and nutrient intakes from foods were calculated from one-day weighed food records on a sub-sample (n = 83). The result of the study showed that the intakes of most nutrients were lower than the recommended intake. The energy intake of the study participants both in 2nd and 3rd trimesters of pregnancy were 2,308 kcal and 1,420.5 kcal compared to the recommended 2,340 kcal and 2,452 kcal, respectively. Except iron, almost all micronutrient intakes were lower than the recommended intake. Vitamin A intake was 3 µg compared with the recommended 800 µg, while protein intake of the study respondents in 2nd and 3rd trimester of pregnancy was 45.9 g and 31.5 g, respectively, compared with the recommended 71 g. Risk factors for under nutrition were multiple pregnancy and no consumption of cereal-based foods. This study revealed that the energy and nutrient intake of the pregnant women in the study area was below the recommended intakes. Furthermore, the situation might be aggravated by the high phytate content food consumption reported. Nutritional status of pregnant women in the study area was not adequate to support the increased energy and nutrient requirement of the participants.

Keywords: nutrition, pregnancy, protein, vitamin, energy

Procedia PDF Downloads 140

Authors: Nasrin Badrkhani

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The increasing use of educational technologies has created a tremendous transformation in all fields and most importantly, in the field of education and learning. In recent decades, traditional learning approaches have undergone fundamental changes with the emergence of new learning technologies. Research shows that suitable educational tools play an effective role in the transmission, comprehension, and impact of educational concepts. These tools provide a tangible basis for thinking and constructing concepts, resulting in an increased interest in learning. They provide real and true experiences to students and convey educational meanings and concepts more quickly and clearly. It can be said that educational technology, as an active and modern teaching method, with capabilities such as engaging multiple senses in the educational process and involving the learner, makes the learning environment more flexible. It effectively impacts the skills of children with special needs by addressing their specific needs. Teachers are no longer the sole source of information, and students are not mere recipients of information. They are considered the main actors in the field of education and learning. Since education is one of the basic rights of every human being and children with special needs face unique challenges and obstacles in education, these challenges can negatively affect their abilities and learning. To combat these challenges, one of the ways is to use educational technologies for more diverse, effective learning. Also, the use of educational technology for students with special needs has increasingly proven effective in boosting their self-confidence and helping them overcome learning challenges, enhancing their learning outcomes.

Keywords: communication technology, students with special needs, self-confidence, raising the expectations and progress

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Authors: Azzeddine Abdelalim, Fatiha Rogti

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The degradation phenomenon in polymer solar cells (PCSs) has not been clearly explained yet. In fact, there are many causes that show up and influence these cells in a variety of ways. Also, there has been a growing concern over this degradation in the photovoltaic community. One of the main variables deciding PSCs photovoltaic output is defect states. In this research, devices modeling is carried out to analyze the multiple effects of degradation by applying high defect states (HDS) on ideal PSCs, mainly poly(3-hexylthiophene) (P3HT) absorber layer. Besides, a comparative study is conducted between P3HT and other PSCs by a simulation program called Solar Cell Capacitance Simulator (SCAPS). The adjustments to the defect parameters in several absorber layers explain the effect of HDS on the total output properties of PSCs. The performance parameters for HDS, quantum efficiency, and energy band were therefore examined. This research attempts to explain the degradation process of PSCs and the causes of their low efficiency. It was found that the defects often affect PSCs performance, but defect states have a little effect on output when the defect level is less than 1014cm-3, which gives similar performance values with P3HT cells when these defects is about 1019cm-3. The high defect states can cause up to 11% relative reduction in conversion efficiency of ideal P3HT. In the center of the band gap, defect states become more noxious. This approach is for one of the degradation processes potential of PSCs especially that use fullerene derivative acceptors.

Keywords: degradation, high defect states, polymer solar cells, SCAPS-1D

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Authors: Abu Salim Mustafa

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The comparisons of mycobacterial genomes have identified several Mycobacterium tuberculosis-specific genomic regions that are absent in other mycobacteria and are known as regions of differences. Due to M. tuberculosis-specificity, the peptides encoded by these regions could be useful in the specific diagnosis of tuberculosis. To explore this possibility, overlapping synthetic peptides corresponding to 39 proteins predicted to be encoded by genes present in regions of differences were tested for antibody-reactivity with sera from tuberculosis patients and healthy subjects. The results identified four immunodominant peptides corresponding to four different proteins, with three of the peptides showing significantly stronger antibody reactivity and rate of positivity with sera from tuberculosis patients than healthy subjects. The fourth peptide was recognized equally well by the sera of tuberculosis patients as well as healthy subjects. Predication of antibody epitopes by bioinformatics analyses using ABCpred server predicted multiple linear epitopes in each peptide. Furthermore, peptide sequence analysis for sequence identity using BLAST suggested M. tuberculosis-specificity for the three peptides that had preferential reactivity with sera from tuberculosis patients, but the peptide with equal reactivity with sera of TB patients and healthy subjects showed significant identity with sequences present in nob-tuberculous mycobacteria. The three identified M. tuberculosis-specific immunodominant peptides may be useful in the serological diagnosis of tuberculosis.

Keywords: genomic regions of differences, Mycobacterium tuberculossis, peptides, serodiagnosis

Procedia PDF Downloads 183

Authors: Mariam Shah

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‘Honour’ crime has commonly been perceived in the UK as being a ‘domestic violence’ related issue due to incidents perceived to take place within a domestic context, and commonly by familial perpetrators. The lack of differentiation between domestic violence and ‘honour’ related incidents has several negative implications. Firstly, the prevalence and extent of ‘honour’ related crime within the UK cannot be accurately quantified due to ‘honour’ incidents being classed statistically as domestic violence incidents. Secondly, lack of differentiation means that the negative stereotypical attitudes ascribed to domestic violence which has resulted in lower criminal conviction rates that are also impacting the conviction of perpetrators of ‘honour’ crime. Thirdly, ‘honour’ related crime is innately distinct from domestic violence due to the perpetrator’s resolute intent of cleansing perceived ‘shame’ in any way possible, often with the involvement and collusion of multiple perpetrators from within the family and/or community. Domestic violence is typically restricted to the ‘home’, but ‘honour’ crime can operate between national and international boundaries. This paper critically examines the current academic literature and concludes that the few similarities between domestic violence and ‘honour’ related crime are not sufficient to warrant identical treatment under UK criminal law. ‘Honour’ related crime is a distinct and stand-alone offence which should be recognised as such. The appropriate identification and treatment of ‘honour’ crime are crucial, particularly in light of the UK’s first ‘white’ honour killing which saw a young English woman murdered after being deemed to have brought ‘shame’ on her ex-boyfriend’s family. This incident highlights the possibility of ‘honour’ crime extending beyond its perceived ‘ethnic minority’ roots and becoming more of a ‘mainstream’ issue for the multi-cultural and multi-racial UK.

Keywords: differentiation, domestic violence, honour crime, United Kingdom

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Authors: Rouag N., Khalifa M. W., Bencheikh A., Abed H.

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The behavior study of forty-two varieties and genotypes of chickpeas regarding root wilt disease induced by Fusarium oxysporum under the natural conditions of infection was conducted at the ITGC experimental station in Sétif. The infected plants of the different chickpea genotypes have shown multiple symptoms in the field caused by the local strain of Fusarium oxysporum f.sp.cecris belonging to race II of the pathogen. These symptoms ranged from lateral or partial wilting of some ramifications to total desiccation of the plant, sometimes combined with the very slow growth of symptomatic plants. The results of the search for sources of resistance to Fusarium wilt of chickpeas in the 42 genotypes tested revealed that in terms of infection rate, the presence of 7 groups and no genotype showed absolute resistance. While in terms of severity, the results revealed the presence of three homogeneous groups. The first group formed by the most resistant genotypes, in this case, Flip10-368C; Flip11-77C; Flip11-186C; Flip11-124C; Flip11-142C, Flip11-152C; Flip11-69C; Ghab 05; Flip11-159C; Flip11-90C; Flip10-357C and Flip11-37C while the second group is the FLIP genotype 10-382C which was found to be the most sensitive for the natural infection test. Thus, the genotypes of Cicer arietinum L., which have shown significant levels of resistance to Fusarium wilt, can be integrated into breeding and improvement programs.

Keywords: chickpea, Cicer arietinum, Fusarium oxysporum, genotype resistance

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Authors: Dani Sukkar, Ali Kanso, Philippe Laval-Gilly, Jairo Falla-Angel

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The honeybees' immune system is challenged by different risk factors that induce various responses. However, complex scenarios where bees are exposed to different pesticides simultaneously with immune activation are not well evaluated. The Toll pathway is one of the main signaling pathways studied in invertebrate immune responses, and it is a good indicator of the effect of such complex interactions in addition to key signaling elements of other pathways like Relish of the immune deficiency (IMD) pathway or Eater, the phagocytosis receptor or vitellogenin levels. Honeybee hemocytes extracted from 5th instar larvae were exposed to imidacloprid and/or amitraz with or without the presence of the zymosan a as an immune activator. The gene expression of multiple immune related genes were studied, including spaetzle, Toll, myD88, relish, eater and vitellogenin, by real-time polymerase chain reaction after RNA extraction. The results demonstrated that the Toll pathway is mainly affected by the pesticides; imidacloprid and amitraz, especially by their different combinations. Furthermore, immune activation by zymosan A, a fungal cell-wall component, acts to mitigate to some extent the effect of pesticides on the different levels of the Toll pathway. In addition, imidacloprid, amitraz, and zymosan A have complex and context-specific interactions depending on the levels of immune activation and the pathway evaluated affecting immune-gene expression differently.

Keywords: toll pathway, immune modulation, β-glucan, imidacloprid, amitraz, honeybees, immune genes

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Authors: Marjan Javanmard

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The rheological properties of dairy products critically depend on the underlying organisation of proteins at multiple length scales. When heated and acidified, milk proteins form particle gel that is viscoelastic, solvent rich, ‘soft’ material. In this work recent developments on the rheology of soft particles suspensions were used to interpret and potentially define the properties of dairy gel structures. It is discovered that at volume fractions below random close packing (RCP), the Maron-Pierce-Quemada (MPQ) model accurately predicts the viscosity of the dairy gel suspensions without fitting parameters; the MPQ model has been shown previously to provide reasonable predictions of the viscosity of hard sphere suspensions from the volume fraction, solvent viscosity and RCP. This surprising finding demonstrates that up to RCP, the dairy gel system behaves as a hard sphere suspension and that the structural aggregates behave as discrete particulates akin to what is observed for microgel suspensions. At effective phase volumes well above RCP, the system is a soft solid. In this region, it is discovered that the storage modulus of the sheared AMG scales with the storage modulus of the set gel. The storage modulus in this regime is reasonably well described as a function of effective phase volume by the Evans and Lips model. Findings of this work has potential to aid in rational design and control of dairy food structure-properties.

Keywords: dairy suspensions, rheology-structure, Maron-Pierce-Quemada Model, Evans and Lips Model

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Authors: Tahmina Sultana, Yasser Hassan

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Vehicle technologies rapidly evolving due to their multifaceted advantages. Adapted different vehicle technologies like connectivity and automation on the same roads with conventional vehicles controlled by human drivers may increase speed disparity in mixed vehicle technologies. Identifying relationships between speed distribution measures of different vehicles and road geometry can be an indicator of speed disparity in mixed technologies. Previous studies proved that speed disparity measures and traffic accidents are inextricably related. Horizontal curves from three geographic areas were selected based on relevant criteria, and speed data were collected at the midpoint of the preceding tangent and starting, ending, and middle point of the curve. Multiple linear mixed effect models (LME) were developed using the instantaneous speed measures representing the speed of vehicles at different points of horizontal curves to recognize relationships between speed variance (standard deviation) and road geometry. A simulation-based framework (Monte Carlo) was introduced to check the speed disparity on horizontal curves in mixed vehicle technologies when consideration is given to the interactions among connected vehicles (CVs), autonomous vehicles (AVs), and non-connected vehicles (NCVs) on horizontal curves. The Monte Carlo method was used in the simulation to randomly sample values for the various parameters from their respective distributions. Theresults show that NCVs had higher speed variation than CVs and AVs. In addition, AVs and CVs contributed to reduce speed disparity in the mixed vehicle technologies in any penetration rates.

Keywords: autonomous vehicles, connected vehicles, non-connected vehicles, speed variance

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Authors: Sabitha Rahim

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In the context of teaching vocabulary of English as Foreign Language (EFL), the confluence of memory and retention is one of the most significant factors in students' language acquisition. The progress of students engaged in foreign language acquisition is often stymied by vocabulary attrition, which leads to learners' lack of confidence and motivation. However, among other factors, little research has investigated the importance of neuroplasticity in Foreign Language acquisition and how underused neural pathways lead to the loss of plasticity, thereby affecting the learners’ vocabulary retention and motivation. This research explored the effect of enhancing vocabulary acquisition of EFL students in the Foundation Year at King Abdulaziz University through various methods and neuroplasticity exercises that reinforced their attention, motivation, and engagement. It analyzed the results to determine if stimulating the brain of EFL learners by various physical and mental activities led to the improvement in short and long term memory in vocabulary retention. The main data collection methods were student surveys, assessment records of teachers, student achievement test results, and students' follow-up interviews. A key implication of this research is for the institutions to consider having multiple varieties of student activities promoting brain plasticity within the classrooms as an effective tool for foreign language acquisition. Building awareness among the faculty and adapting the curriculum to include activities that promote brain plasticity ensures an enhanced learning environment and effective language acquisition in EFL classrooms.

Keywords: language acquisition, neural paths, neuroplasticity, vocabulary attrition

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Authors: Weerakarj Dokchan

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The purposes of this research are to find out the factors for developing trainers in the auto part manufacturing factories (AMF) in Amata Nakon Industrial Estate Cholburi. Population in this study included 148 operators to complete the questionnaires and 10 trainers to provide the information on the interview. The research statistics consisted of percentage, mean, standard deviation and step-wise multiple linear regression analysis.The analysis of the training model revealed that: The research result showed that the development factors of trainers in AMF consisted of 3 main factors and 8 sub-factors: 1) knowledge competency consisting of 4 sub-factors; arrangement of critical thinking, organizational loyalty, working experience of the trainers, analysis of behavior, and work and organization loyalty which could predict the success of the trainers at 55.60%. 2) Skill competency consisted of 4 sub-factors, arrangement of critical thinking, organizational loyalty and analysis of behavior and work and the development of emotional quotient. These 4 sub-factors could predict the success of the trainers in skill aspect 55.90%. 3) The attitude competency consisted of 4 sub-factors, arrangement of critical thinking, intention of trainee computer competency and teaching psychology. In conclusion, these 4 sub-factors could predict the success of the trainers in attitude aspect 58.50%.

Keywords: the development factors, trainers development, trainer competencies, auto part manufacturing factory (AMF), AmataNakon Industrial Estate Cholburi

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Authors: Jonathan D. Moore, Mark G. Reith, David S. Long

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Serious games (SGs) have been shown to be an effective teaching tool in many contexts. Because of the success of SGs, several design frameworks have been created to expedite the process of making original serious games to teach specific learning objectives (LOs). Even with these frameworks, the time required to create a custom SG from conception to implementation can range from months to years. Furthermore, it is even more difficult to design a game framework that allows an instructor to create customized game variants supporting multiple LOs within the same field. This paper proposes a refactoring methodology to apply the theoretical principles from well-established design frameworks to a pre-existing serious game. The expected result is a generalized game that can be quickly customized to teach LOs not originally targeted by the game. This methodology begins by describing the general components in a game, then uses a combination of two SG design frameworks to extract the teaching elements present in the game. The identified teaching elements are then used as the theoretical basis to determine the range of LOs that can be taught by the game. This paper evaluates the proposed methodology by presenting a case study of refactoring the serious game Battlespace Next (BSN) to teach joint military capabilities. The range of LOs that can be taught by the generalized BSN are identified, and examples of creating custom LOs are given. Survey results from users of the generalized game are also provided. Lastly, the expected impact of this work is discussed and a road map for future work and evaluation is presented.

Keywords: serious games, learning objectives, game design, learning theory, game framework

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Authors: Amah Nnachi Lofty, Oyefeso Olufemi, Ibiam Udu Ama

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New and more powerful communications technologies continue to emerge at a rapid pace and their uses in education are widespread and the impact remarkable in the developing societies. This study investigates Mobile Collaboration Learning Technique (MCLT) on learners’ outcome among students in tertiary institutions of developing nations (a case of Nigeria students). It examines the significance of retention achievement scores of students taught using mobile collaboration and conventional method. The sample consisted of 120 students using Stratified random sampling method. Three research questions and hypotheses were formulated, and tested at a 0.05 level of significance. A student achievement test (SAT) was made of 40 items of multiple-choice objective type, developed and validated for data collection by professionals. The SAT was administered to students as pre-test and post-test. The data were analyzed using t-test statistic to test the hypotheses. The result indicated that students taught using MCLT performed significantly better than their counterparts using the conventional method of instruction. Also, there was no significant difference in the post-test performance scores of male and female students taught using MCLT. Based on the findings, the following recommendations was made that: Mobile collaboration system be encouraged in the institutions to boost knowledge sharing among learners, workshop and trainings should be organized to train teachers on the use of this technique and that schools and government should formulate policies and procedures towards responsible use of MCLT.

Keywords: education, communication, learning, mobile collaboration, technology

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Authors: Ali Akyar, Osman Serdar Gedik

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Depth estimation is a challenging computer vision task that involves estimating the distance between objects in a scene and the camera. It predicts how far each pixel in the 2D image is from the capturing point. There are some important Monocular Depth Estimation (MDE) studies that are based on Vision Transformers (ViT). We benchmark three major studies. The first work aims to build a simple and powerful foundation model that deals with any images under any condition. The second work proposes a method by mixing multiple datasets during training and a robust training objective. The third work combines generalization performance and state-of-the-art results on specific datasets. Although there are studies with thermal images too, we wanted to benchmark these three non-thermal, state-of-the-art studies with a hybrid image dataset which is taken by Multi-Spectral Dynamic Imaging (MSX) technology. MSX technology produces detailed thermal images by bringing together the thermal and visual spectrums. Using this technology, our dataset images are not blur and poorly detailed as the normal thermal images. On the other hand, they are not taken at the perfect light conditions as RGB images. We compared three methods under test with our thermal dataset which was not done before. Additionally, we propose an image enhancement deep learning model for thermal data. This model helps extract the features required for monocular depth estimation. The experimental results demonstrate that, after using our proposed model, the performance of these three methods under test increased significantly for thermal image depth prediction.

Keywords: monocular depth estimation, thermal dataset, benchmarking, vision transformers

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