Search results for: variable neighbourhood search

Authors: Nor Diana Ahmad, Eric Atwell, Brandon Bennett

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Text processing techniques for English have been developed for several decades. But for the Malay language, text processing methods are still far behind. Moreover, there are limited resources, tools for computational linguistic analysis available for the Malay language. Therefore, this research presents the use of natural language processing (NLP) in processing Malay translated Qur’an text. As the result, a new language resource for Malay translated Qur’an was created. This resource will help other researchers to build the necessary processing tools for the Malay language. This research also develops a simple question-answer prototype to demonstrate the use of the Malay Qur’an resource for text processing. This prototype has been developed using Python. The prototype pre-processes the Malay Qur’an and an input query using a stemming algorithm and then searches for occurrences of the query word stem. The result produced shows improved matching likelihood between user query and its answer. A POS-tagging algorithm has also been produced. The stemming and tagging algorithms can be used as tools for research related to other Malay texts and can be used to support applications such as information retrieval, question answering systems, ontology-based search and other text analysis tasks.

Keywords: language resource, Malay translated Qur'an, natural language processing (NLP), text processing

Procedia PDF Downloads 311

Authors: Tessa Heeren

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The following proposal pertains to the complex process of successfully implementing health policies that are based on public health research. A systematic review was conducted by myself and faculty at the Cluj School of Public Health in Romania. The reviewed articles covered a wide range of topics, such as barriers and facilitators to multi-sector collaboration, differences in professional cultures, and systemic obstacles. The reviewed literature identified communication, collaboration, user-friendly dissemination, and documentation of processes in the execution of applied research as important themes for the promotion of evidence in the public health decision-making process. This proposal fits into the Academy Health National Health Policy conference because it identifies and examines differences between the worlds of research and politics. Implications and new insights for federal and/or state health policy: Recommendations made based on the findings of this research include using politically relevant levers to promote research (e.g. campaign donors, lobbies, established parties, etc.), modernizing dissemination practices, and reforms in which the involvement of external stakeholders is facilitated without relying on invitations from individual policy makers. Description of how evidence and/or data was or could be used: The reviewed articles illustrated shortcomings and areas for improvement in policy research processes and collaborative development. In general, the evidence base in the field of integrating research into policy lacks critical details of the actual process of developing evidence based policy. This shortcoming in logistical details creates a barrier for potential replication of collaborative efforts described in studies. Potential impact of the presentation for health policy: The reviewed articles focused on identifying barriers and facilitators that arise in cross sector collaboration, rather than the process and impact of integrating evidence into policy. In addition, the type of evidence used in policy was rarely specified, and widely varying interpretations of the definition of evidence complicated overall conclusions. Background: Using evidence to inform public health decision making processes has been proven effective; however, it is not clear how research is applied in practice. Aims: The objectives of the current study were to assess the extent to which evidence is used in public health decision-making process. Methods: To identify eligible studies, seven bibliographic databases, specifically, PubMed, Scopus, Cochrane Library, Science Direct, Web of Science, ClinicalKey, Health and Safety Science Abstract were screened (search dates: 1990 – September 2015); a general internet search was also conducted. Primary research and systematic reviews about the use of evidence in public health policy in Europe were included. The studies considered for inclusion were assessed by two reviewers, along with extracted data on objective, methods, population, and results. Data were synthetized as a narrative review. Results: Of 2564 articles initially identified, 2525 titles and abstracts were screened. Ultimately, 30 articles fit the research criteria by describing how or why evidence is used/not used in public health policy. The majority of included studies involved interviews and surveys (N=17). Study participants were policy makers, health care professionals, researchers, community members, service users, experts in public health.

Keywords: cross-sector, dissemination, health policy, policy implementation

Procedia PDF Downloads 217

Authors: Bib Paruhum Silalahi, Djihad Wungguli, Sugi Guritman

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Steepest descent method is a simple gradient method for optimization. This method has a slow convergence in heading to the optimal solution, which occurs because of the zigzag form of the steps. Barzilai and Borwein modified this algorithm so that it performs well for problems with large dimensions. Barzilai and Borwein method results have sparked a lot of research on the method of steepest descent, including alternate minimization gradient method and Yuan method. Inspired by previous works, we modified the step size of the steepest descent method. We then compare the modification results against the Barzilai and Borwein method, alternate minimization gradient method and Yuan method for quadratic function cases in terms of the iterations number and the running time. The average results indicate that the steepest descent method with the new step sizes provide good results for small dimensions and able to compete with the results of Barzilai and Borwein method and the alternate minimization gradient method for large dimensions. The new step sizes have faster convergence compared to the other methods, especially for cases with large dimensions.

Keywords: steepest descent, line search, iteration, running time, unconstrained optimization, convergence

Procedia PDF Downloads 537

Authors: Camila da Silva, Simone Belorte de Andrade, Vitor Augusto dos Santos Garcia, Vladimir Ferreira Cabral, J. Vladimir Oliveira Lúcio Cardozo-Filho

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In the present study, the non-catalytic transesterification of soybean oil in continuous mode using supercritical ethanol were investigated. Experiments were performed in a packed-bed tubular reactor (PBTR) and variable studied were reaction temperature (523 K to 598 K), pressure (10 MPa to 20 MPa), oil to ethanol molar ratio (1:10 to 1:40) and water concentration (0 wt% to 10 wt% in ethanol). Results showed that ethyl esters yields obtained in the PBTR were higher (> 20 wt%) than those verified in a tubular reactor (TR), due to improved mass transfer conditions attained in the PBTR. Results demonstrated that temperature, pressure, oil to ethanol molar ratio and water concentration had a positive effect on fatty acid ethyl esters (FAEE) production in the experimental range investigated, with appreciable reaction yields (90 wt%) achieved at 598 K, 20 MPa, oil to ethanol molar ratio of 1:40 and 10 wt% of water concentration.

Keywords: packed bed reactor, ethyl esters, continuous process, catalyst-free process

Procedia PDF Downloads 518

Authors: B. Makhlouf, O. Bouchhida, M. Nibouche, K. Laidi

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A variety of methods for selective harmonics elimination pulse width modulation have been developed, the most frequently used for real-time implementation based on look-up tables method. To address real-time requirements based in modified carrier signal is proposed in the presented work, with a general formulation to real-time harmonics control/elimination in switched inverters. Firstly, the proposed method has been demonstrated for a single value of the modulation index. However, in reality, this parameter is variable as a consequence of the voltage (amplitude) variability. In this context, a simple interpolation method for calculating the modified sine carrier signal is proposed. The method allows a continuous adjustment in both amplitude and frequency of the fundamental. To assess the performance of the proposed method, software simulations and hardware experiments have been carried out in the case of a single-phase inverter. Obtained results are very satisfactory.

Keywords: harmonic elimination, Particle Swarm Optimisation (PSO), polynomial interpolation, pulse width modulation, real-time harmonics control, voltage inverter

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Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

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The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

Procedia PDF Downloads 133

Authors: F. Uriel, M. M. Fernandez Liporace

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In the last decade, academic achievement in higher education has become a topic of agenda in Argentina, regarding the high figures of adjustment problems, academic failure and dropout, and the low graduation rates in the context of massive classes and traditional teaching methods. Psychological variables, such as perceived social support, academic motivation and learning styles and strategies have much to offer since their measurement by tests allows a proper diagnose of their influence on academic achievement. Framed in a major research, several studies analysed multiple samples, totalizing 5135 students attending Argentinean public universities. The first goal was aimed at the identification of statistically significant differences in psychological variables -perceived social support, learning styles, learning strategies, and academic motivation- by age, gender, and degree of academic advance (freshmen versus sophomores). Thus, an inferential group differences study for each psychological dependent variable was developed by means of student’s T tests, given the features of data distribution. The second goal, aimed at examining associations between the four psychological variables on the one hand, and academic achievement on the other, was responded by correlational studies, calculating Pearson’s coefficients, employing grades as the quantitative indicator of academic achievement. The positive and significant results that were obtained led to the formulation of different predictive models of academic achievement which had to be tested in terms of adjustment and predictive power. These models took the four psychological variables above mentioned as predictors, using regression equations, examining predictors individually, in groups of two, and together, analysing indirect effects as well, and adding the degree of academic advance and gender, which had shown their importance within the first goal’s findings. The most relevant results were: first, gender showed no influence on any dependent variable. Second, only good achievers perceived high social support from teachers, and male students were prone to perceive less social support. Third, freshmen exhibited a pragmatic learning style, preferring unstructured environments, the use of examples and simultaneous-visual processing in learning, whereas sophomores manifest an assimilative learning style, choosing sequential and analytic processing modes. Despite these features, freshmen have to deal with abstract contents and sophomores, with practical learning situations due to study programs in force. Fifth, no differences in academic motivation were found between freshmen and sophomores. However, the latter employ a higher number of more efficient learning strategies. Sixth, freshmen low achievers lack intrinsic motivation. Seventh, models testing showed that social support, learning styles and academic motivation influence learning strategies, which affect academic achievement in freshmen, particularly males; only learning styles influence achievement in sophomores of both genders with direct effects. These findings led to conclude that educational psychologists, education specialists, teachers, and universities must plan urgent and major changes. These must be applied in renewed and better study programs, syllabi and classes, as well as tutoring and training systems. Such developments should be targeted to the support and empowerment of students in their academic pathways, and therefore to the upgrade of learning quality, especially in the case of freshmen, male freshmen, and low achievers.

Keywords: academic achievement, academic motivation, coping, learning strategies, learning styles, perceived social support

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Authors: Sanjay Kumar, Saikat Dutta, Devendra S. Rawat, Jitendra K. Pandey, Pankaj Kumar

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Exploding demand for various types of fuels and gradually growing impacts of atmospheric carbon dioxide have forced the researchers to search biofuels in general and algae-based biofuels in particular. However, strain identification in terms of fuel productivity and over all economics of fuel generation remains a debatable challenge. Utilization of marine biomass, especially the ones important in the Indian subcontinent, in forming furanic fuels and specialty chemicals would likely to be a better value-addition pathway. Seaweed species e.g. Ulva, Sarconema, and Gracilaria species have been found more productive than land-based biomass sources due to their higher growth rate. Additionally, non-recalcitrant nature of marine biomass unlike lignocellulosics has attracted much attention in recent years towards producing bioethanol. Here we report the production of renewable, biomass-derived platform molecules such as furfural and 5-(chloromethyl) furfural (CMF) from a seaweed species which are abundant marine biomass. These products have high potential for synthetic upgradation into various classes of value-added compounds such as fuels, fuel-additives, and monomers for polymers, solvents, agrochemicals, and pharmaceuticals.

Keywords: seaweeds, Ulva, CMF, furan

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Authors: E. Behmanesh, J. Pannek

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Logistics network design is known as one of the strategic decision problems. As these kinds of problems belong to the category of NP-hard problems, traditional ways are failed to find an optimal solution in short time. In this study, we attempt to involve reverse flow through an integrated design of forward/reverse supply chain network that formulated into a mixed integer linear programming. This Integrated, multi-stages model is enriched by three different delivery path which makes the problem more complex. To tackle with such an NP-hard problem a revised random path direct encoding method based memetic algorithm is considered as the solution methodology. Each algorithm has some parameters that need to be investigate to reveal the best performance. In this regard, Taguchi method is adapted to identify the optimum operating condition of the proposed memetic algorithm to improve the results. In this study, four factors namely, population size, crossover rate, local search iteration and a number of iteration are considered. Analyzing the parameters and improvement in results are the outlook of this research.

Keywords: integrated logistics network, flexible path, memetic algorithm, Taguchi method

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Authors: Karin Schakib-Ekbatan, Annette Roser

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According to the Federal Government’s plans, the German building stock should be virtually climate neutral by 2050. Thus, the “EnEff.Gebäude.2050” funding initiative was launched, complementing the projects of the Energy Transition Construction research initiative. Beyond the construction and renovation of individual buildings, solutions must be found at the neighborhood level. The subject of the presented pilot project is a building ensemble from the Wilhelminian period in Munich, which is planned to be refurbished based on a socially compatible, energy-saving, innovative-technical modernization concept. The building ensemble, with about 200 apartments, is part of the building cooperative. To create an optimized network and possible synergies between researchers and projects of the funding initiative, a Scientific Accompanying Research was established for cross-project analyses of findings and results in order to identify further research needs and trends. Thus, the project is characterized by an interdisciplinary approach that combines constructional, technical, and socio-scientific expertise based on a participatory understanding of research by involving the tenants at an early stage. The research focus is on getting insights into the tenants’ comfort requirements, attitudes, and energy-related behaviour. Both qualitative and quantitative methods are applied based on the Technology-Acceptance-Model (TAM). The core of the refurbishment strategy is a wall heating system intended to replace conventional radiators. A wall heating provides comfortable and consistent radiant heat instead of convection heat, which often causes drafts and dust turbulence. Besides comfort and health, the advantage of wall heating systems is an energy-saving operation. All apartments would be supplied by a uniform basic temperature control system (around perceived room temperature of 18 °C resp. 64,4 °F), which could be adapted to individual preferences via individual heating options (e. g. infrared heating). The new heating system would affect the furnishing of the walls, in terms of not allowing the wall surface to be covered too much with cupboards or pictures. Measurements and simulations of the energy consumption of an installed wall heating system are currently being carried out in a show apartment in this neighborhood to investigate energy-related, economical aspects as well as thermal comfort. In March, interviews were conducted with a total of 12 people in 10 households. The interviews were analyzed by MAXQDA. The main issue of the interview was the fear of reduced self-efficacy within their own walls (not having sufficient individual control over the room temperature or being very limited in furnishing). Other issues concerned the impact that the construction works might have on their daily life, such as noise or dirt. Despite their basically positive attitude towards a climate-friendly refurbishment concept, tenants were very concerned about the further development of the project and they expressed a great need for information events. The results of the interviews will be used for project-internal discussions on technical and psychological aspects of the refurbishment strategy in order to design accompanying workshops with the tenants as well as to prepare a written survey involving all households of the neighbourhood.

Keywords: energy efficiency, interviews, participation, refurbishment, residential buildings

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Authors: Lynndee Kemmet

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The U.S. military plays an increasing role in supporting political stability efforts, and this includes efforts to prevent the food insecurity that can trigger political and social instability. This paper presents a model that assists military commanders in identifying variables that impact food production and distribution in their areas of operation (AO), in identifying connections between variables and in assessing the impacts of those variables on food production and distribution. Through use of the model, military units can better target their data collection efforts and can categorize and analyze data within the data categorization framework most widely-used by military forces—PMESII-PT (Political, Military, Economic, Infrastructure, Information, Physical Environment and Time). The model provides flexibility of analysis in that commanders can target analysis to be highly focused on a specific PMESII-PT domain or variable or conduct analysis across multiple PMESII-PT domains. The model is also designed to assist commanders in mapping food systems in their AOs and then identifying components of those systems that must be strengthened or protected.

Keywords: food security, food system model, political stability, US Military

Procedia PDF Downloads 187

Authors: Rashmi D. G., Aishwarya G., Niharika M. K.

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Purpose: Free recall tasks target cognitive and linguistic processes like episodic memory, lexical access and retrieval. Consequently, the free recall paradigm is suitable for assessing memory deterioration caused by aging; this also depends on linguistic factors, including the use of first and second languages and their relative ability. Hence, the present study aimed to determine if aging has an effect on visual and auditory recall abilities. Method: Twenty young adults (mean age: 25.4±0.99) and older adults (mean age: 63.3±3.51) participated in the study. Participants performed a free recall task under two conditions – related and unrelated and two modalities - visual and auditory where they were instructed to recall as many items as possible with no specific order and time limit. Results: Free recall performance was calculated as the mean number of correctly recalled items. Although younger participants recalled a higher number of items, the performance across conditions and modality was variable. Conclusion: In summary, the findings of the present study revealed an age-related decline in the efficiency of episodic memory, which is crucial to remember recent events.

Keywords: recall, episodic memory, aging, modality

Procedia PDF Downloads 89

Authors: S. Forughi, A. De Zoysa, S. Bhati

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The present study focuses on the environmental performance of the companies in the electricity-producing sector and its relationship with their financial performance. We will review the major studies that examined the relationship between the environmental and financial performance of firms in various industries. While the classical economic debates consider the environmental friendly activities costly and harmful to a firm’s profitability, it is claimed that firms will be rewarded with higher profitability in long run through the investments in environmental friendly activities. In this context, prior studies have examined the relationship between the environmental and financial performance of firms operating in different industry sectors. Our study will employ an environmental indicator to increase the accuracy of the results and be employed as an independent variable in our developed econometric model to evaluate the impact of the financial performance of the firms on their environmental friendly activities in the context of companies operating in the Australian electricity-producing sector. As a result, we expect our methodology to contribute to the literature and the findings of the study will help us to provide recommendations and policy implications to the electricity producers.

Keywords: Australian electricity sector, efficiency measurement, environmental-financial performance interaction, environmental index

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Authors: Adnan A. Y. Mustafa

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Image matching is a fundamental problem that arises frequently in many aspects of robot and computer vision. It can become a time-consuming process when matching images to a database consisting of hundreds of images, especially if the images are big. One approach to reducing the time complexity of the matching process is to reduce the search space in a pre-matching stage, by simply removing dissimilar images quickly. The Probabilistic Matching Model for Binary Images (PMMBI) showed that dissimilarity detection between binary images can be accomplished quickly by random pixel mapping and is size invariant. The model is based on the gamma binary similarity distance that recognizes an image and its inverse as containing the same scene and hence considers them to be the same image. However, in many applications, an image and its inverse are not treated as being the same but rather dissimilar. In this paper, we present a comparative analysis of dissimilarity detection between PMMBI based on the gamma binary similarity distance and a modified PMMBI model based on a similarity distance that does distinguish between an image and its inverse as being dissimilar.

Keywords: binary image, dissimilarity detection, probabilistic matching model for binary images, image mapping

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Authors: Magda Cepeda, Frances Hodgson, Ann Jopson

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There are different barriers people face when choosing to cycle for commuting purposes. This study examined the role of psycho-social factors predicting the intention to cycle to commute in Mexico City. An extended version of the theory of planned behaviour was developed and utilized with a simple random sample of 401 road users. We applied exploratory and confirmatory factor analysis and after identifying five factors, a structural equation model was estimated to find the relationships among the variables. The results indicated that cycling attributes, attitudes to cycling, social comparison and social image and prestige were the most important factors influencing intention to cycle. Although the results from this study are specific to Mexico City, they indicate areas of interest to transportation planners in other regions especially in those cities where intention to cycle its linked to its perceived image and there is political ambition to instigate positive cycling cultures. Moreover, this study contributes to the current literature developing applications of the Theory of Planned Behaviour.

Keywords: cycling, latent variable model, perception, theory of planned behaviour

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Authors: Ren Moses

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The process of classifying vehicles on a highway is hereby viewed as a pattern recognition problem in which connectionist techniques such as artificial neural networks (ANN) can be used to assign vehicles to their correct classes and hence to establish optimum axle spacing thresholds. In the United States, vehicles are typically classified into 13 classes using a methodology commonly referred to as “Scheme F”. In this research, the ANN model was developed, trained, and applied to field data of vehicles. The data comprised of three vehicular features—axle spacing, number of axles per vehicle, and overall vehicle weight. The ANN reduced the classification error rate from 9.5 percent to 6.2 percent when compared to an existing classification algorithm that is not ANN-based and which uses two vehicular features for classification, that is, axle spacing and number of axles. The inclusion of overall vehicle weight as a third classification variable further reduced the error rate from 6.2 percent to only 3.0 percent. The promising results from the neural networks were used to set up new thresholds that reduce classification error rate.

Keywords: artificial neural networks, vehicle classification, traffic flow, traffic analysis, and highway opera-tions

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Authors: Ghada M. R. Koura, Ahmed M. F. El Shiwi

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Background: structural scoliosis is a twisting deformity in the curve of vertebral column to the lateral side with simultaneous rotation of the vertebrae, which occurs during the growing years from 10 years to the puberty. Purpose: Studies investigating balance problems specific to scoliotic patients showed that those patients reveal variable balance abnormalities. In this study we evaluated the difference in postural stability responses between female patients (students, office worker and shish weapon players) with structural scoliosis and normal subjects. Methods: sixty subjects participated in this study. Thirty female patients with structural scoliosis with a mean age of (19.5 ± 3.26) years, with Cobb's angle ranged from 20º to 40° in the major curves, and thirty healthy female subjects with a mean age of (19.36 ± 2.41) years. Postural stability of both groups were evaluated by the Biodex Stability System. Results: There was no significant difference between both groups in dynamic balance test. Interpretation/Conclusion: As there was no significant difference between both groups in balance response, it is not recommended to add balance training as an extra physical therapy program for AIS female patients.

Keywords: structural scoliosis, postural stability, female patients, evaluation

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Authors: Mahta Eskandarnejad

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The aim of this paper was to compare physical activity and mental toughness in the staff and students of the University of Tabriz. 615 people participated in this study and filled demographic questionnaire, mental thoughness48 (MTQ48) questionnaire and habitual physical activity questionnaire (Baecke physical activity questionnaire). The research sample included 355 students and 260 staff (615 questionnaires). For analyzing hypotheses MANOVA, correlation and independent t-test were used. Based on the result; some subscales of mental toughness and physical activity were significantly related. The result showed the significant correlation between mental toughness and physical activity in student and no significant correlation in staff. Students were significantly physically more active than staff, and mental toughness was higher in staff. There was no difference in mental toughness variable between active participants (active staff and student). The results of this study showed that mental toughness could influence the way a person cope with living conditions. It is expected that mental toughness changes can lead to changing in levels of physical activity. It should be noted that the other variables should not be ignored.

Keywords: Baecke physical activity questionnaire, mental toughness, physical activity, university staff, university student

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Authors: Izdihar Ismail, Alona C. Linatoc, Maryati Mohamed

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The tropical rainforest of Malaysia is known for its rich biological diversity and high endemicity. The potential for these forests to hold the cure for many diseases and illnesses is high and much is yet to be discovered. This study explores the richness of the tropical rainforest of Endau-Rompin National Park in Johor, Malaysia in search of plants traditionally used by the indigenous people in the treatment of malaria and malaria-like symptoms. Seven species of plants were evaluated and tested for antiplasmodial activities. Different plant parts were subjected to methanolic and aqueous extractions. A total of 24 extracts were evaluated by histidine-rich protein II (HRP2) assay against K1 strain of Plasmodium falciparum chloroquine-resistant. Ten extracts showed significant inhibition of the growth of P. falciparum. Phytochemical screening of the same extracts revealed the presence of alkaloids, flavonoids, terpenoids and anthraquinones. This study affirms that tropical rainforests may still hold undiscovered cures for many diseases and illnesses that have inflicted millions of people worldwide. The species studied herein have not known to have been studied elsewhere before.

Keywords: Endau-Rompin, malaria, Malaysia, tropical rainforest, traditional knowledge

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Authors: Ahmed Bellakhdhar

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This paper aims to test the impact of various variables-namely, investment in physical capital, investment in human capital, openness to trade and foreign direct investments, and distance from the technology frontier-on economic growth in the Tunisian context during the period 1976-2010. Empirical results identify that the impact of human capital is significantly positive. This finding confirms the hypothesis that human capital is a main driver of economic performance through its role of improving the internal productive capacity and the absorption of foreign technology especially via foreign direct investments. The effect of FDI is significantly positive in all alternative regressions and the coefficient associated to physical capital variable is positive, but not significant overall. Concerning the import of technologically advanced equipments, our estimates show the absence of a significant direct impact on economic growth in Tunisia. Our empirical results also support the assumption of a non linear relationship between tax and growth and demonstrate the existence of an inverted-U curve between the two variables, in the spirit of the “Laffer curve”.

Keywords: Endogenous growth, Human capital, Technology transfer, Absorptive capacity

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Authors: Yungtai Lo

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The current study follows an educational intervention on bottle-weaning to simultaneously evaluate the effect of the bottle-weaning intervention on reducing bottle use, daily milk intake from bottles, and daily energy intake in toddlers aged 11 to 13 months. A shared parameter model and a random effects model are used to jointly model bottle use, daily milk intake from bottles, and daily energy intake. We show in the two joint models that the bottle-weaning intervention promotes bottleweaning, and reduces daily milk intake from bottles in toddlers not off bottles and daily energy intake. We also show that the odds of drinking from a bottle were positively associated with the amount of milk intake from bottles and increased daily milk intake from bottles was associated with increased daily energy intake. The effect of bottle use on daily energy intake is through its effect on increasing daily milk intake from bottles that in turn increases daily energy intake.

Keywords: two-part model, semi-continuous variable, joint model, gamma regression, shared parameter model, random effects model

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Mai Ashraf Talaat

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Objectives: The aim of this review article is to assess the success of dental implants in breast cancer patients receiving bisphosphonate therapy and to evaluate the risk of developing bisphosphonate-related osteonecrosis of the jaw following dental implant surgery. Materials and Methods: A thorough search was conducted, with no time or language restriction, using: PubMed, PubMed Central, Web of Science, and ResearchGate electronic databases. Medical Subject Headings (MeSH) terms such as “bisphosphonate”, “dental implant”, “bisphosphonate-related osteonecrosis of the jaw (BRONJ)”, “osteonecrosis”, “breast cancer, MRONJ”, and their related entry terms were used. Eligibility criteria included studies and clinical trials that evaluated the impact of bisphosphonates on dental implants. Conclusion: Breast cancer patients undergoing bisphosphonate therapy may receive dental implants. However, the risk of developing BRONJ and implant failure is high. Risk factors such as the type of BP received, the route of administration, and the length of treatment prior to surgery should be considered. More randomized controlled trials with long-term follow-ups are needed to draw more evidence-based conclusions.

Keywords: dental implants, breast cancer, bisphosphonates, osteonecrosis, bisphosphonate-related osteonecrosis of the jaw

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Authors: R. Shamsi, F. Sharifi

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In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose a multi-objective DEA-R model because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduce the efficiency score), an efficient decision-making unit (DMU) is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other cases, only the ratio of stochastic data may be available (e.g., the ratio of stochastic inputs to stochastic outputs). Thus, we provide a multi-objective DEA model without explicit outputs and prove that the input-oriented MOP DEA-R model in the invariable return to scale case can be replaced by the MOP-DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided.

Keywords: DEA-R, multi-objective programming, stochastic data, data envelopment analysis

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Authors: E. Accomando, L. Delle Rose, S. Moretti, E. Olaiya, C. Shepherd-Themistocleous

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Heavy sterile neutrinos are almost ubiquitous in the class of Beyond Standard Model scenarios aimed at addressing the puzzle that emerged from the discovery of neutrino flavour oscillations, hence the need to explain their masses. In particular, they are necessary in a U(1)’ enlarged Standard Model (SM). We show that these heavy neutrinos can be rather long-lived producing distinctive displaced vertices and tracks. Indeed, depending on the actual decay length, they can decay inside a Large Hadron Collider (LHC) detector far from the main interaction point and can be identified in the inner tracking system or the muon chambers, emulated here through the Compact Muon Solenoid (CMS) detector parameters. Among the possible production modes of such heavy neutrino, we focus on their pair production mechanism in the SM Higgs decay, eventually yielding displaced lepton signatures following the heavy neutrino decays into weak gauge bosons. By employing well-established triggers available for the CMS detector and using the data collected by the end of the LHC Run 2, these signatures would prove to be accessible with negligibly small background. Finally, we highlight the importance that the exploitation of new triggers, specifically, displaced tri-lepton ones, could have for this displaced vertex search.

Keywords: beyond the standard model, displaced vertex, Higgs physics, neutrino physics

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Authors: Usriatur Rohma, Adji Achmad Rinaldo Fernandes

Abstract:

Nonparametric path analysis is a statistical method that does not rely on the assumption that the curve is known. The purpose of this study is to determine the best nonparametric truncated spline path function between linear and quadratic polynomial degrees with 1, 2, and 3-knot points and to determine the significance of estimating the best nonparametric truncated spline path function in the model of the effect of population migration and agricultural economic growth on rural poverty through the variable unemployment rate using the t-test statistic at the jackknife resampling stage. The data used in this study are secondary data obtained from statistical publications. The results showed that the best model of nonparametric truncated spline path analysis is quadratic polynomial degree with 3-knot points. In addition, the significance of the best-truncated spline nonparametric path function estimation using jackknife resampling shows that all exogenous variables have a significant influence on the endogenous variables.

Keywords: nonparametric path analysis, truncated spline, linear, quadratic, rural poverty, jackknife resampling

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Authors: Christina Surmei

Abstract:

Autism Spectrum Disorder (ASD) is defined as a diverse range of developmental conditions that affect an individual’s functionality. ASD is not linear, and individuals can present with deficits in social interaction, communication, and demonstrate limited, repetitive patterns of behaviour, interests, or activities. These characteristics may be observed in a variety of ways and range from mild to severe. ASD may include autism disorder, pervasive developmental disorder not otherwise specified, Asperger’s, or other related pervasive developmental disorders. Modern slavery is defined as 'situations of exploitation that a person cannot refuse or leave because of threats, violence, coercion, and abuse of power or deception'. A review of the literature investigated the prevalence of research regarding ASD and modern slavery. Two universal search engines and five online journals were used as the apparatuses of inquiry. The results revealed two editorials, one study, and one act, totaling four publications attesting to ASD and modern slavery as a joint entity. This is representative of a vast absence of research. However, as individual entities research on autism and modern slavery is in a general high occurrence. This paper has identified a significant gap in research on ASD and modern slavery, and initiates the dialogue to unpack a significant global issue in society today.

Keywords: autism spectrum, education, modern slavery, support

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Authors: Hammad Majeed, Hanna Knuutila, Magne Hillestad, Hallvard F. Svendsen

Abstract:

Formation of aerosols can cause serious complications in industrial exhaust gas cleaning processes. Small mist droplets and fog formed can normally not be removed in conventional demisting equipment because their submicron size allows the particles or droplets to follow the gas flow. As a consequence of this, aerosol based emissions in the order of grams per Nm³ have been identified from PCCC plants. The model predicts the droplet size, the droplet internal variable profiles, and the mass transfer fluxes as function of position in the absorber. The Matlab model is based on a subclass method of weighted residuals for boundary value problems named, orthogonal collocation method. This paper presents results describing the basic simulation tool for the characterization of aerosols formed in CO₂ absorption columns and describes how various entering droplets grow or shrink through an absorber and how their composition changes with respect to time. Below are given some preliminary simulation results for an aerosol droplet composition and temperature profiles.

Keywords: absorption columns, aerosol formation, amine emissions, internal droplet profiles, monoethanolamine (MEA), post combustion CO2 capture, simulation

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Authors: Hema Lattupalli

Abstract:

Introduction: The palate forms a partition between the oral cavity and nasal cavity. The palate is made up of two parts hard palate and soft palate. The Hard palate forms the anterior part of the palate, the soft palate forms a movable muscular fold covered by mucous membrane that is suspended from the posterior border of a hard palate. Aim and Objectives: Soft palate morphological variations have a great paucity in the literature. It’s also believed that the soft palate has no such important anatomical variations. There is a variable presentation of the soft palate morphology in the lateral cephalograms. The aim of this study is to identify the velar morphology. Materials and Methods: 100 normal subjects between the age group of 20 – 35 were taken for the study. Method: Lateral Cephalogram (radiologic study). Results: Different shapes of the soft palate were observed in the lateral cephalograms. The morphology of soft palate was classified into six types 1.Leaf like (50 cases) most common type, 2.Straight line (20 cases), 3.S shaped (4 cases) very rare, 4.Butt like (10 cases), 5. Rat tail (6 cases), 6. Hook shaped (10 cases). Conclusion: This classification helps us to understand the better diversity of the velar morphology in mid-sagittal plane. These findings help us to understand the etiology of OSAS.

Keywords: soft palate, cephalometric radiographs, morphology, cleft palate, obstructive sleep apnoea syndrome

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Authors: Wiwat Kittinaraporn, Napat Harnpornchai, Sutja Boonyachut

Abstract:

This paper deals with the application of a novel neural network technique, so-called Support Vector Machine (SVM). The objective of this study is to explore the variable and parameter of forecasting factors in the construction industry to build up forecasting model for construction quantity in Thailand. The scope of the research is to study the non-residential construction quantity in Thailand. There are 44 sets of yearly data available, ranging from 1965 to 2009. The correlation between economic indicators and construction demand with the lag of one year was developed by Apichat Buakla. The selected variables are used to develop SVM models to forecast the non-residential construction quantity in Thailand. The parameters are selected by using ten-fold cross-validation method. The results are indicated in term of Mean Absolute Percentage Error (MAPE). The MAPE value for the non-residential construction quantity predicted by Epsilon-SVR in corporation with Radial Basis Function (RBF) of kernel function type is 5.90. Analysis of the experimental results show that the support vector machine modelling technique can be applied to forecast construction quantity time series which is useful for decision planning and management purpose.

Keywords: forecasting, non-residential, construction, support vector machines

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