Search results for: multiple input multiple output

Authors: Waleed Maqableh, Ahmad Al-Hamad, Manjit Sidhu

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Augmented reality (AR) technology has the capability to provide many benefits in the field of education as a modern technology which aided learning and improved the learning experience. This paper evaluates AR based application with multiple markers interaction technique (touch-to-print) which is designed for analyzing the kinematics of 4BL mechanism in mechanical engineering. The application is termed as AR-4BL-MAST and it allows the users to touch the symbols on a paper in natural way of interaction. The evaluation of this application was performed with mechanical engineering students and human–computer interaction (HCI) experts to test its effectiveness as a tangible user interface application where the statistical results show its ability as an interaction technique, and it gives the users more freedom in interaction with the virtual mechanical objects.

Keywords: augmented reality, multimedia, user interface, engineering, education technology

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Authors: Kadam Bhambri, Neena Gupta

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All optical wavelength conversion is essential in present day optical networks for transparent interoperability, contention resolution, and wavelength routing. The incorporation of all optical wavelength convertors leads to better utilization of the network resources and hence improves the efficiency of optical networks. Wavelength convertors that can work with Dispersion Managed (DM) solitons are attractive due to their superior transmission capabilities. In this paper, wavelength conversion for dispersion managed soliton signals was demonstrated at 100 Gbps through semiconductor optical amplifier and an optical filter. The wavelength conversion was achieved for a 1550 nm input signal to1555nm output signal. The output signal was measured in terms of BER, Q factor and system margin.    

Keywords: all optical wavelength conversion, dispersion managed solitons, semiconductor optical amplifier, cross gain modultation

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Authors: Yanshuang Zhang, Byungho Jeong

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In many cases, there is a time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in evaluating the performance of organizations. Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. Multi-periods input(MpI) and Multi-periods output(MpO) models are integrated models to calculate simple efficiency considering time lag effect. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. That is, efficient DMUs can’t be discriminated because their efficiency scores are same. Thus, this paper suggests a super-efficiency model for efficiency evaluation under the consideration of time lag effect based on the MpO model. A case example using a long-term research project is given to compare the suggested model with the MpO model.

Keywords: DEA, super-efficiency, time lag, multi-periods input

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Authors: Esmat Noroozi, Elahe Sarfi, Farha Hosseinzadeh Lotfi

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Examining the impacts of data modification is considered as sensitivity analysis. A lot of studies have considered the data modification of inputs and outputs in DEA. The issues which has not heretofore been considered in DEA sensitivity analysis is modification in the number of inputs and (or) outputs and determining the impacts of this modification in the status of efficiency of DMUs. This paper is going to present systems that show the impacts of adding one or multiple inputs or outputs on the status of efficiency of DMUs and furthermore a model is presented for recognizing the minimum number of inputs and (or) outputs from among specified inputs and outputs which can be added whereas an inefficient DMU will become efficient. Finally the presented systems and model have been utilized for a set of real data and the results have been reported.

Keywords: data envelopment analysis, efficiency, sensitivity analysis, input, out put

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Authors: Sima Aznavi, Poria Fajri, Hanif Livani

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Smart homes are small energy systems which may be equipped with renewable energy sources, storage devices, and loads. Energy management strategy plays a main role in the efficient operation of smart homes. Effective energy scheduling of the renewable energy sources and storage devices guarantees efficient energy management in households while reducing the energy imports from the grid. Nevertheless, despite such strategies, independently day ahead energy schedules for multiple households can cause undesired effects such as high power exchange with the grid at certain times of the day. Therefore, the interactions between multiple smart home day ahead energy projections is a challenging issue in a smart grid system and if not managed appropriately, the imported energy from the power network can impose additional burden on the distribution grid. In this paper, a central energy management strategy for a network consisting of multiple households each equipped with renewable energy sources, storage devices, and Plug-in Electric Vehicles (PEV) is proposed. The decision-making strategy alongside the smart home energy management system, minimizes the energy purchase cost of the end users, while at the same time reducing the stress on the utility grid. In this approach, the smart home energy management system determines different operating scenarios based on the forecasted household daily load and the components connected to the household with the objective of minimizing the end user overall cost. Then, selected projections for each household that are within the same cost range are sent to the central decision-making system. The central controller then organizes the schedules to reduce the overall peak to average ratio of the total imported energy from the grid. To validate this approach simulations are carried out for a network of five smart homes with different load requirements and the results confirm that by applying the proposed central energy management strategy, the overall power demand from the grid can be significantly flattened. This is an effective approach to alleviate the stress on the network by distributing its energy to a network of multiple households over a 24- hour period.

Keywords: energy management, renewable energy sources, smart grid, smart home

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Authors: Hadi Molaei, Yasavoli Davoud, Keshavarz, Mozhde Poordana

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The present study aimed was to prediction the academic performance based on academic motivation, self-efficacy and Resiliency in the students. The present study was descriptive and correlational. Population of the study consisted of all students in Arak schools in year 1393-94. For this purpose, the number of 304 schools students in Arak was selected using multi-stage cluster sampling. They all questionnaires, self-efficacy, Resiliency and academic motivation Questionnaire completed. Data were analyzed using Pearson correlation and multiple regressions. Pearson correlation showed academic motivation, self-efficacy, and Resiliency with academic performance had a positive and significant relationship. In addition, multiple regression analysis showed that the academic motivation, self-efficacy and Resiliency were predicted academic performance. Based on the findings could be conclude that in order to increase the academic performance and further progress of students must provide the ground to strengthen academic motivation, self-efficacy and Resiliency act on them.

Keywords: academic motivation, self-efficacy, resiliency, academic performance

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Authors: Ronghui (Kevin) Zhou

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This research intends to explore the enactment of Education for Sustainable Development (ESD), in term of the ESD concept, in primary schools in China, and investigate the factors that have positively or negatively impacted the outcome of ESD in urban primary schools in China. The proposed research question is: how is the ESD concept perceived and enacted by the local education stakeholders. This research is conducted in multiple primary schools in China and has questionnaired and interviewed multiple education stakeholders, including school principals, school teachers, and bureau from the municipal Ministry of Education. Factor analysis, regression analysis, and critical discourse analysis are adopted to interpret and analyze the data. The preliminary findings suggest that contested ESD definition, education system pressures, education policy enforcement, and power dynamics between stakeholders are the key factors that have determined to what degree is ESD enacted, and to what extent is ESD practiced in primary schools in China.

Keywords: education for sustainable development, China, primary education, case study

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Authors: Fatemeh Abbasi, Sahand Daneshvar

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Productivity is one of the essential goals of companies to improve performance, which as a strategy-oriented method, determines the basis of the company's economic growth. The history of productivity goes back centuries, but most researchers defined productivity as the relationship between a product and the factors used in production in the early twentieth century. Productivity as the optimal use of available resources means that "more output using less input" can increase companies' economic growth and prosperity capacity. Also, having a quality life based on economic progress depends on productivity growth in that society. Therefore, productivity is a national priority for any developed country. There are several methods for calculating productivity growth measurements that can be divided into parametric and non-parametric methods. Parametric methods rely on the existence of a function in their hypotheses, while non-parametric methods do not require a function based on empirical evidence. One of the most popular non-parametric methods is Data Envelopment Analysis (DEA), which measures changes in productivity over time. The DEA evaluates the productivity of decision-making units (DMUs) based on mathematical models. This method uses multiple inputs and outputs to compare the productivity of similar DMUs such as banks, government agencies, companies, airports, Etc. Non-parametric methods are themselves divided into the frontier and non frontier approaches. The Malmquist productivity index (MPI) proposed by Caves, Christensen, and Diewert (1982), the Hicks–Moorsteen productivity index (HMPI) proposed by Bjurek (1996), or the Luenberger productivity indicator (LPI) proposed by Chambers (2002) are powerful tools for measuring productivity changes over time. This study will compare the Malmquist, Hicks–Moorsteen, and Luenberger indices theoretically and empirically based on DEA models and review their strengths and weaknesses.

Keywords: data envelopment analysis, Hicks–Moorsteen productivity index, Leuenberger productivity indicator, malmquist productivity index

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Authors: Cynthia Sau Chun Yip, Richard Fielding

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High meat and especially red meat intakes are significantly and positively associated with a multiple burden of diseases and also high greenhouse gas (GHG) emissions. This study investigated population meat intake patterns in Hong Kong. It quantified the burden of disease and GHG emission outcomes by modeling to adjust Hong Kong population meat intakes to recommended healthy levels. It compared age- and sex-specific population meat, fruit and vegetable intakes obtained from a population survey among adults aged 20 years and over in Hong Kong in 2005-2007, against intake recommendations suggested in the Modelling System to Inform the Revision of the Australian Guide to Healthy Eating (AGHE-2011-MS) technical document. This study found that meat and meat alternatives, especially red meat intakes among Hong Kong males aged 20+ years and over are significantly higher than recommended. Red meat intakes among females aged 50-69 years and other meat and alternatives intakes among aged 20-59 years are also higher than recommended. Taking the 2005-07 age- and sex-specific population meat intake as baselines, three counterfactual scenarios of adjusting Hong Kong adult population meat intakes to AGHE-2011-MS and Pre-2011 AGHE recommendations by the year 2030 were established. Consequent energy intake gaps were substituted with additional legume, fruit and vegetable intakes. To quantify the consequent GHG emission outcomes associated with Hong Kong meat intakes, Cradle-to-ready-to-eat lifecycle assessment emission outcome modelling was used. Comparative risk assessment of burden of disease model was used to quantify the health outcomes. This study found adjusting meat intakes to recommended levels could reduce Hong Kong GHG emission by 17%-44% when compared against baseline meat intake emissions, and prevent 2,519 to 7,012 premature deaths in males and 53 to 1,342 in females, as well as multiple burden of diseases when compared to the baseline meat intake scenario. Comparing lump sum meat intake reduction and outcome measures across the entire population, and using emission factors, and relative risks from individual studies in previous co-benefit studies, this study used age- and sex-specific input and output measures, emission factors and relative risks obtained from high quality meta-analysis and meta-review respectively, and has taken government dietary recommendations into account. Hence evaluations in this study are of better quality and more reflective of real life practices. Further to previous co-benefit studies, this study pinpointed age- and sex-specific population and meat-type-specific intervention points and leverages. When compared with similar studies in Australia, this study also showed that intervention points and leverages among populations in different geographic and cultural background could be different, and that globalization also globalizes meat consumption emission effects. More regional and cultural specific evaluations are recommended to promote more sustainable meat consumption and enhance global food security.

Keywords: burden of diseases, greenhouse gas emissions, Hong Kong diet, sustainable meat consumption

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Authors: A. Bolaji Adesoye, Alimi Olorunfemi

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This paper examines the impact of small and medium-scale enterprises (SMEs) credit financing and financial market development and their shocks on the output growth of Nigeria. The study estimated a VAR model for Nigeria using 1970-2013 annual data series. Unit root tests and cointegration are carried out. The study also explores IRFs and FEVDs in a system that includes output, commercial bank loan to SMEs, domestic credit to private sector by banks, money supply, lending rate and investment. Findings suggest that shocks in commercial bank credit to SMEs has a major impact on the output changes of Nigeria. Money supply shocks also have a sizeable impact on output growth variations amidst other financial instruments. Lastly, neutrality of investment does not hold in Nigeria as it also has impact on output fluctuations.

Keywords: SMEs financing, financial development, investment, output, Nigeria

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Authors: Abhinav Purohit, Shruthi S. Pradeep

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In today’s world, aviation industries are using turbofan engines (permutation of turboprop and turbojet) which meet the obligatory requirements to be fuel competent and to produce enough thrust to propel an aircraft. But one can imagine increasing the work output of this particular machine by reducing the input power. In striving to improve technologies, especially to augment the efficiency of the engine with some adaptations, which can be crooked to new concepts by introducing a step change in the turbofan engine development. One hopeful concept is, to de-couple the fan with the help of reduction gear box in a two spool shaft engine from the rest of the machinery to get more work output with maximum efficiency by reducing the load on the turbine shaft. By adapting this configuration we can get an additional degree of freedom to better optimize each component at different speeds. Since the components are running at different speeds we can get hold of preferable efficiency. Introducing water alcohol mixture to this concept would really help to get better results.

Keywords: emissions, fuel consumption, more power, turbofan

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Authors: Bardia Khafaf, Mehrdad Ghaffari, Amir Hussein Samakar

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It is currently desirable to use Hollow Square Sections (HSS) in moment resistant structures in construction of building because they offer fewer restrictions for designing and more useful space while adhering to build design codes. This paper present a through bolt connection in HSS column. This connection meets building code standards that require the moment resistant connections to deflect and absorb energy resulting from gravity and seismic loads. Connection through bolts is installed and pretension to provide the connection strength needed to make a beam–column moment rigid zone. A rigid joint is typically used to resist lateral forces by holding columns and beams fixed in relation to one another. With bolted moment frames using HSS columns, a through–bolt connection could be used to secure the beam and end plate to the column. However, when multiple columns and beams are used to span a length of building, the use of through-bolts would necessities aligning multiple beams simultaneously to the columns. In the case of a linear span, the assembly process requires the holes of a first beam end plate to be aligned with through bolt holes in a column and aligning the holes of a second, opposing beam plate with the column through bolt, then inserting the through bolts in each hole for tightening with nuts and washers. In moment resistant building, a problem arises when assembling beams to columns where multiple beams and columns are required. Through bolt, moment connections are among the economical, practical and not difficult rigid steel connection for HSS column building. In this paper, the results of numerous analytical studies performed for moment structures with HSS columns with through bolt based on AISC standard codes are shown.

Keywords: through bolt, moment resistant connection, HSS columns section, construction engineering

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Authors: Arpit K. Shrivastava, Nirmal K. Mohakud, Subrat Kumar, Priyadarshi S. Sahu

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Acute diarrhea is one of the major causes of morbidity and mortality among children less than five years of age. Multiple etiologies have been implicated for infectious gastroenteritis causing acute diarrhea. In our study fecal samples (n=165) were collected from children (<5 years) presenting with symptoms of acute diarrhea. Samples were screened for viral, bacterial, and parasitic etiologies such as Rotavirus, Adenovirus, Diarrhoeagenic Escherichia coli (EPEC, EHEC, STEC, O157, O111), Shigella spp., Salmonella spp., Vibrio cholera, Cryptosporidium spp., and Giardia spp. The overall results from our study showed that 57% of children below 5 years of age with acute diarrhea were positive for at least one infectious etiology. Diarrhoeagenic Escherichia coli was detected to be the major etiological agent (29.09%) followed by Rotavirus (24.24%), Shigella (21.21%), Adenovirus (5.45%), Cryptosporidium (2.42%), and Giardia (0.60%). Among the different DEC strains, EPEC was detected significantly higher in <2 years children in comparison to >2 years age group (p =0.001). Concurrent infections with two or more pathogens were observed in 47 of 160 (28.48%) cases with a predominant incidence particularly in <2-year-old children (66.66%) compared to children of 2 to 5 years age group. Co-infection of Rotavirus with Shigella was the most frequent combination, which was detected in 17.94% cases, followed by Rotavirus with EPEC (15.38%) and Shigella with STEC (12.82%). Detection of multiple infectious etiologies and diagnosis of the right causative agent(s) can immensely help in better management of acute childhood diarrhea. In future more studies focusing on the detection of cases with concurrent infections must be carried out, as we believe that the etiological agents might be complementing each other’s strategies of pathogenesis resulting in severe diarrhea.

Keywords: children, co-infection, infectious diarrhea, Odisha

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Authors: G. I. Onwuka, A. Danbaba, S. U. Gulumbe

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This study investigated of Infant Mortality Rate as observed at a general hospital in Kaduna-South, Kaduna State, North West Nigeria. The causes of infant Mortality were examined. The data used for this analysis were collected at the statistics unit of the Hospital. The analysis was carried out on the data using Multiple Linear regression Technique and this showed that there is linear relationship between the dependent variable (death) and the independent variables (malaria, measles, anaemia, and coronary heart disease). The resultant model also revealed that a unit increment in each of these diseases would result to a unit increment in death recorded, 98.7% of the total variation in mortality is explained by the given model. The highest number of mortality was recorded in July, 2005 and the lowest mortality recorded in October, 2009.Recommendations were however made based on the results of the study.

Keywords: infant mortality rate, multiple linear regression, diseases, serial correlation

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Authors: Mostafa Sarabzadeh, Masoumeh Helalizadeh, Seyyed Mahmoud Hejazi

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Multiple Sclerosis is considered as diseases related to central nerve system, the chronic and progressive disease impress on sensory and motor function of people. Due to equilibrium problems in this patients that related to disorder of nerve conduction transmission from central nerve system to organs and the nature of elastic bands that can make changes in neuromuscular junctions and momentary actions, the aim of this research is evaluate elastic training effect by reactionary ropes on nerve conduction velocity (in lower and upper limb) and functional balance in female patients with Multiple Sclerosis. The study was a semi-experimental study that was performed based on pre and post-test method, The statistical community consisted of 16 women with MS in the age mean 25-40yrs, at low and intermediate levels of disease EDSS 1-4 (Expanded Disability Status Scale) that were divided randomly into elastic and control groups, so the training program of experimental group lasted six weeks, 3 sessions per week of elastic exercises with reactionary ropes. Electroneurography parameters (nerve conduction velocity- latency) of Upper and lower nerves (Median, Tibial, Sural, Peroneal) along with balance were investigated respectively by the Electroneurography system (ENG) and Timed up and go (TUG) functional test two times in before and after the training period. After that, To analyze the data were used of Dependent and Independent T-test (with sig level p<0.05). The results showed significant increase in nerve conduction velocity of Sural (p=0.001), Peroneal (p=0.01), Median (p=0.03) except Tibial and also development Latency Time of Tibial (p= 0), Peroneal (p=0), Median (p=0) except Sural. The TUG test showed significant decreases in execution time too (p=0.001). Generally, based on what the obtained data can indicate, modern training with elastic bands can contribute to enhanced nerve conduction velocity and balance in neurosis patients (MS) so lead to reduce problems, promotion of mobility and finally more life expectancy in these patients.

Keywords: balance, elastic bands, multiple sclerosis, nerve conduction, velocity

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Authors: Henry Lau, Dilupa Nakandala, Li Zhao

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All along the length of the supply chain, fresh food firms face the challenge of managing both product quality, due to the perishable nature of the products, and product cost. This paper develops a method to assist logistics managers upstream in the fresh food supply chain in making cost optimized decisions regarding transportation, with the objective of minimizing the total cost while maintaining the quality of food products above acceptable levels. Considering the case of multiple fresh food products collected from multiple farms being transported to a warehouse or a retailer, this study develops a total cost model that includes various costs incurred during transportation. The practical application of the model is illustrated by using several computational intelligence approaches including Genetic Algorithms (GA), Fuzzy Genetic Algorithms (FGA) as well as an improved Simulated Annealing (SA) procedure applied with a repair mechanism for efficiency benchmarking. We demonstrate the practical viability of these approaches by using a simulation study based on pertinent data and evaluate the simulation outcomes. The application of the proposed total cost model was demonstrated using three approaches of GA, FGA and SA with a repair mechanism. All three approaches are adoptable; however, based on the performance evaluation, it was evident that the FGA is more likely to produce a better performance than the other two approaches of GA and SA. This study provides a pragmatic approach for supporting logistics and supply chain practitioners in fresh food industry in making important decisions on the arrangements and procedures related to the transportation of multiple fresh food products to a warehouse from multiple farms in a cost-effective way without compromising product quality. This study extends the literature on cold supply chain management by investigating cost and quality optimization in a multi-product scenario from farms to a retailer and, minimizing cost by managing the quality above expected quality levels at delivery. The scalability of the proposed generic function enables the application to alternative situations in practice such as different storage environments and transportation conditions.

Keywords: cost optimization, food supply chain, fuzzy sets, genetic algorithms, product quality, transportation

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Authors: Minttu Laukkanen, Janne Huiskonen

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This study investigates the sharing economy business models as examples of the sustainable business models. The aim is to contribute to the limited literature on sharing economy in connection with sustainable business models by explaining sharing economy business models value capturing. Specifically, this research answers the following question: How business model choices affect captured sustainable value? A multiple case study approach is applied in this study. Twenty different successful sharing economy business models focusing on consumer business and covering four main areas, accommodation, mobility, food, and consumer goods, are selected for analysis. The secondary data available on companies’ websites, previous research, reports, and other public documents are used. All twenty cases are analyzed through the sharing economy business model framework and sustainable value analysis framework using qualitative data analysis. This study represents general sharing economy business model value attributes and their specifications, i.e. sustainable value propositions for different stakeholders, and further explains the sustainability impacts of different sharing economy business models through captured and uncaptured value. In conclusion, this study represents how business model choices affect sustainable value capturing through eight business model attributes identified in this study. This paper contributes to the research on sustainable business models and sharing economy by examining how business model choices affect captured sustainable value. This study highlights the importance of careful business model and sustainability impacts analyses including the triple bottom line, multiple stakeholders and value captured and uncaptured perspectives as well as sustainability trade-offs. It is not self-evident that sharing economy business models advance sustainability, and business model choices does matter.

Keywords: sharing economy, sustainable business model innovation, sustainable value, value capturing

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Authors: Luong A. Nguyen, Elihu Deneke, Thomas L. Harman

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This paper describes a multibody dynamics algorithm formulated for parallel implementation on multiprocessor computing platforms using the divide-and-conquer approach. The system of interest is a general topology of rigid and elastic articulated bodies with or without loops. The algorithm is an extension of Featherstone’s divide and conquer approach to include the flexible-body dynamics formulation. The equations of motion, configured for the International Space Station (ISS) with its robotic manipulator arm as a system of articulated flexible bodies, are implemented in separate computer processors. The performance of this divide-and-conquer algorithm implementation in multiple processors is compared with an existing method implemented on a single processor.

Keywords: multibody dynamics, multiple processors, multithreading, divide-and-conquer algorithm, computational efficiency, flexible body dynamics

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Authors: Jairson Barbosa Rodrigues, Paulo Romero Martins Maciel, Germano Crispim Vasconcelos

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This paper presents an investigation of the performance impacts regarding the variation of five factors (input data size, node number, cores, memory, and disks) when applying a distributed implementation of Naïve Bayes for text classification of a large Corpus on the Spark big data processing framework. Problem: The algorithm's performance depends on multiple factors, and knowing before-hand the effects of each factor becomes especially critical as hardware is priced by time slice in cloud environments. Objectives: To explain the functional relationship between factors and performance and to develop linear predictor models for time and cost. Methods: the solid statistical principles of Design of Experiments (DoE), particularly the randomized two-level fractional factorial design with replications. This research involved 48 real clusters with different hardware arrangements. The metrics were analyzed using linear models for screening, ranking, and measurement of each factor's impact. Results: Our findings include prediction models and show some non-intuitive results about the small influence of cores and the neutrality of memory and disks on total execution time, and the non-significant impact of data input scale on costs, although notably impacts the execution time.

Keywords: big data, design of experiments, distributed machine learning, natural language processing, spark

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Authors: Muzammil Dar

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The confluence of trans-national interests and divergent approaches followed by multiple actors has surrounded the Indo-Pacific region with myriad of strategic complexes- Geo-Political, Geo-economic, and security. This paper has thus made a humble attempt to understand the Indo-Pacific strategic predicament from Asia-Pacific perspective. The portmanteau of Indo-Pacific strategic gamble has multiple actors from global powers to regional actors. On the indo-pacific waters, not only flow trade relations, but the tides of conflicts and controversies are striking these actors against each other. The alliance formation and infrastructure building has built-in threat perceptions from rivals vice-versa. The assertiveness of China as a reality and India’s ideological doctrine of peace and friendship, as well as American rebalancing against China, could be seen as clear and bright on the Indo-Pacific strategic portmanteau. ASEAN and Japan, too, have oscillating posturing in the strategic dilemma. The aim and objective of the paper are to sketch out the prospectus and prejudices of Indo-pacific strategic complex.

Keywords: Indo Pacific, Asia Pacific, security and growth for all in the region, SAGAR, ASEAN China

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Authors: Jason Gica, Yi-Hsieng Samuel Wu, Deng-Jye Yang, Yi-Chen Chen

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Mycotoxins, harmful secondary metabolites produced by certain fungi species, pose significant risks to animals and humans worldwide. Their stable properties lead to contamination during grain harvesting, transportation, and storage, as well as in processed food products. The prevalence of mycotoxin contamination has attracted significant attention due to its adverse impact on food safety and global trade. The secondary contamination pathway from animal products has been identified as an important route of exposure, posing health risks for livestock and humans consuming contaminated products. Pork, one of the highly consumed meat products in Taiwan according to the National Food Consumption Database, plays a critical role in the nation's diet and economy. Given its substantial consumption, pork processing products are a significant component of the food supply chain and a potential source of mycotoxin contamination. This study is paramount for formulating effective regulations and strategies to mitigate mycotoxin-related risks in the food supply chain. By establishing a reliable analytical method, this research contributes to safeguarding public health and enhancing the quality of pork processing products. The findings will serve as valuable guidance for policymakers, food industries, and consumers to ensure a safer food supply chain in the face of emerging mycotoxin challenges. An innovative and efficient analytical approach is proposed using Ultra-High Performance Liquid Chromatography coupled with Temperature Control Fluorescence Detector Light (UHPLC-TCFLD) to determine multiple mycotoxins in pork meat samples due to its exceptional capacity to detect multiple mycotoxins at the lowest levels of concentration, making it highly sensitive and reliable for comprehensive mycotoxin analysis. Additionally, its ability to simultaneously detect multiple mycotoxins in a single run significantly reduces the time and resources required for analysis, making it a cost-effective solution for monitoring mycotoxin contamination in pork processing products. The research aims to optimize the efficient mycotoxin QuEChERs extraction method and rigorously validate its accuracy and precision. The results will provide crucial insights into mycotoxin levels in pork processing products.

Keywords: multiple-mycotoxin analysis, pork processing products, QuEChERs, UHPLC-TCFLD, validation

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Authors: Wenlong Feng, Zhenchun Du, Jianguo Yang

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To decrease the grating scale thermal expansion error, a novel method which based on multiple temperature detections is proposed. Several temperature sensors are installed on the grating scale and the temperatures of these sensors are recorded. The temperatures of every point on the grating scale are calculated by interpolating between adjacent sensors. According to the thermal expansion principle, the grating scale thermal expansion error model can be established by doing the integral for the variations of position and temperature. A novel compensation method is proposed in this paper. By applying the established error model, the grating scale thermal expansion error is decreased by 90% compared with no compensation. The residual positioning error of the grating scale is less than 15um/10m and the accuracy of the machine tool is significant improved.

Keywords: thermal expansion error of grating scale, error compensation, machine tools, integral method

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Authors: Sikiru Ademola Adewale, Joe Thomas, Bolanle Hafiz Matti, Tosin Ige

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This project demonstrates the implementation and use of an encoder-decoder model to perform a many-to-many mapping of video data to text captions. The many-to-many mapping occurs via an input temporal sequence of video frames to an output sequence of words to form a caption sentence. Data preprocessing, model construction, and model training are discussed. Caption correctness is evaluated using 2-gram BLEU scores across the different splits of the dataset. Specific examples of output captions were shown to demonstrate model generality over the video temporal dimension. Predicted captions were shown to generalize over video action, even in instances where the video scene changed dramatically. Model architecture changes are discussed to improve sentence grammar and correctness.

Keywords: decoder, encoder, many-to-many mapping, video captioning, 2-gram BLEU

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Authors: Sherry Ann Ganase, Sandra Sookram

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This study examines adaptation measures and factors that influence adaptation decisions in Bequia by using multiple linear regression and a structural equation model. Using survey data, the results suggest that households are knowledgeable and concerned about climate change but lack knowledge about the measures needed to adapt. The findings from the SEM suggest that a positive relationship exist between vulnerability and adaptation, vulnerability and perception, along with a negative relationship between perception and adaptation. This suggests that being aware of the terms associated with climate change and knowledge about climate change is insufficient for implementing adaptation measures; instead the risk and importance placed on climate change, vulnerability experienced with household flooding, drainage and expected threat of future sea level are the main factors that influence the adaptation decision. The results obtained in this study are beneficial to all as adaptation requires a collective effort by stakeholders.

Keywords: adaptation, Bequia, multiple linear regression, structural equation model

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Authors: Farzaneh Rajabighamchi, Stan van Hoesel, Christof Defryn

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The generalized traveling salesman problem (GTSP) is an extension of the traveling salesman problem (TSP) where the set of nodes is partitioned into clusters, and the salesman must visit exactly one node per cluster. In this research, we apply the definition of the GTSP to an order picker routing problem with multiple locations per product. As such, each product represents a cluster and its corresponding nodes are the locations at which the product can be retrieved. To pick a certain product item from the warehouse, the picker needs to visit one of these locations during its pick tour. As all products are scattered throughout the warehouse, the product clusters not separated geographically. We propose an exact LP model as well as heuristic and meta-heuristic solution algorithms for the order picking problem with multiple product locations.

Keywords: warehouse optimization, order picking problem, generalised travelling salesman problem, heuristic algorithm

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Authors: Devika Nair, Sean Bellairs, Ken Evans

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Flow and erosion modeling provides an avenue for simulating the fine suspended sediment in surface water systems like streams and creeks. Fine suspended sediment is highly mobile, and many contaminants that may have been released by any sort of catchment disturbance attach themselves to these sediments. Therefore, a knowledge of fine suspended sediment transport is important in assessing contaminant transport. The CAESAR-Lisflood Landform Evolution Model, which includes a hydrologic model (TOPMODEL) and a hydraulic model (Lisflood), is being used to assess the sediment movement in tropical streams on account of a disturbance in the catchment of the creek and to determine the dynamics of sediment quantity in the creek through the years by simulating the model for future years. The accuracy of future simulations depends on the calibration and validation of the model to the past and present events. Calibration and validation of the model involve finding a combination of parameters of the model, which, when applied and simulated, gives model outputs similar to those observed for the real site scenario for corresponding input data. Calibrating the sediment output of the CAESAR-Lisflood model at the catchment level and using it for studying the equilibrium conditions of the landform is an area yet to be explored. Therefore, the aim of the study was to calibrate the CAESAR-Lisflood model and then validate it so that it could be run for future simulations to study how the landform evolves over time. To achieve this, the model was run for a rainfall event with a set of parameters, plus discharge and sediment data for the input point of the catchment, to analyze how similar the model output would behave when compared with the discharge and sediment data for the output point of the catchment. The model parameters were then adjusted until the model closely approximated the real site values of the catchment. It was then validated by running the model for a different set of events and checking that the model gave similar results to the real site values. The outcomes demonstrated that while the model can be calibrated to a greater extent for hydrology (discharge output) throughout the year, the sediment output calibration may be slightly improved by having the ability to change parameters to take into account the seasonal vegetation growth during the start and end of the wet season. This study is important to assess hydrology and sediment movement in seasonal biomes. The understanding of sediment-associated metal dispersion processes in rivers can be used in a practical way to help river basin managers more effectively control and remediate catchments affected by present and historical metal mining.

Keywords: erosion modelling, fine suspended sediments, hydrology, surface water systems

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Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

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Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feed-forward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on self organizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: classification, SOFM algorithm, neural network, neighborhood, RGB image

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Authors: Fally Titikpina, Abderafi Charki, Antoine Caucheteux, David Bigaud

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The building sector is one of the largest energy consumer with about 40% of the final energy consumption in the European Union. Ensuring building energy performance is of scientific, technological and sociological matter. To assess a building energy performance, the consumption being predicted or estimated during the design stage is compared with the measured consumption when the building is operational. When valuing this performance, many buildings show significant differences between the calculated and measured consumption. In order to assess the performance accurately and ensure the thermal efficiency of the building, it is necessary to evaluate the uncertainties involved not only in measurement but also those induced by the propagation of dynamic and static input data in the model being used. The evaluation of measurement uncertainty is based on both the knowledge about the measurement process and the input quantities which influence the result of measurement. Measurement uncertainty can be evaluated within the framework of conventional statistics presented in the \textit{Guide to the Expression of Measurement Uncertainty (GUM)} as well as by Bayesian Statistical Theory (BST). Another choice is the use of numerical methods like Monte Carlo Simulation (MCS). In this paper, we proposed to evaluate the uncertainty associated to the use of a simplified model for the estimation of the energy consumption of a given building. A detailed review and discussion of these three approaches (GUM, MCS and BST) is given. Therefore, an office building has been monitored and multiple sensors have been mounted on candidate locations to get required data. The monitored zone is composed of six offices and has an overall surface of 102 $m^2$. Temperature data, electrical and heating consumption, windows opening and occupancy rate are the features for our research work.

Keywords: building energy performance, uncertainty evaluation, GUM, bayesian approach, monte carlo method

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Authors: José Carlos Rodríguez, Mario Gómez

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This paper analyses innovation trends in Latin America countries by means of the number of patent applications filed by residents and non-residents during the period 1965 to 2012. Making use of patent data released by the World Intellectual Property Organization (WIPO), we search for the presence of multiple structural changes in patent application series in Argentina, Brazil Chile, and Mexico. These changes may suggest that firms’ innovative activity has been modified as a result of implementing a particular science, technology and innovation (STI) policy. Accordingly, the new regulations implemented in these countries during 1980s and 1990s have influenced their intellectual property regimes. The question conducting this research is thus how STI policies in these countries have affected their innovation activity? The results achieved in this research confirm the existence of multiple structural changes in the series of patent applications resulting from STI policies implemented in these countries.

Keywords: econometric methods, innovation activity, Latin America countries, patents, science, technology and innovation policy

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Authors: Uttam Aryal, Shekhar Thapaliya

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This research paper presents a comprehensive analysis of the factors contributing to student dropout at Makawanpur Multiple Campus, utilizing primary data collected directly from dropped out as well as regular students and academic staff. Employing a mixed-method approach, combining qualitative and quantitative methods, this study examines into the complicated issue of student dropout. Data collection methods included surveys, interviews, and a thorough examination of academic records covering multiple academic years. The study focused on students who left their programs prematurely, as well as current students and academic staff, providing a well-rounded perspective on the issue. The analysis reveals a shaded understanding of the factors influencing student dropout, encompassing both academic and non-academic dimensions. These factors include academic challenges, personal choices, socioeconomic barriers, peer influences, and institutional-related issues. Importantly, the study highlights the most influential factors for dropout, such as the pursuit of education abroad, financial restrictions, and employment opportunities, shedding light on the complex web of circumstances that lead students to discontinue their education. The insights derived from this study offer actionable recommendations for campus administrators, policymakers, and educators to develop targeted interventions aimed at reducing dropout rates and improving student retention. The study underscores the importance of addressing the diverse needs and challenges faced by students, with the ultimate goal of fostering a supportive academic environment that encourages student success and program completion.

Keywords: drop out, students, factors, opportunities, challenges

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