Search results for: autoregressive integrate moving average model selection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 22993

Search results for: autoregressive integrate moving average model selection

12223 A Collaborative Learning Model in Engineering Science Based on a Cyber-Physical Production Line

Authors: Yosr Ghozzi

Abstract:

The Cyber-Physical Systems terminology has been well received by the industrial community and specifically appropriated in educational settings. Indeed, our latest educational activities are based on the development of experimental platforms on an industrial scale. In fact, we built a collaborative learning model because of an international market study that led us to place ourselves at the heart of this technology. To align with these findings, a competency-based approach study was conducted, and program content was revised by reflecting the projectbased approach. Thus, this article deals with the development of educational devices according to a generated curriculum and specific educational activities while respecting the repository of skills adopted from what constitutes the educational cyber-physical production systems and the laboratories that are compliant and adapted to them. The implementation of these platforms was systematically carried out in the school's workshops spaces. The objective has been twofold, both research and teaching for the students in mechatronics and logistics of the electromechanical department. We act as trainers and industrial experts to involve students in the implementation of possible extension systems around multidisciplinary projects and reconnect with industrial projects for better professional integration.

Keywords: education 4.0, competency-based learning, teaching factory, project-based learning, cyber-physical systems, industry 4.0

Procedia PDF Downloads 82
12222 Social Media Idea Ontology: A Concept for Semantic Search of Product Ideas in Customer Knowledge through User-Centered Metrics and Natural Language Processing

Authors: Martin H¨ausl, Maximilian Auch, Johannes Forster, Peter Mandl, Alexander Schill

Abstract:

In order to survive on the market, companies must constantly develop improved and new products. These products are designed to serve the needs of their customers in the best possible way. The creation of new products is also called innovation and is primarily driven by a company’s internal research and development department. However, a new approach has been taking place for some years now, involving external knowledge in the innovation process. This approach is called open innovation and identifies customer knowledge as the most important source in the innovation process. This paper presents a concept of using social media posts as an external source to support the open innovation approach in its initial phase, the Ideation phase. For this purpose, the social media posts are semantically structured with the help of an ontology and the authors are evaluated using graph-theoretical metrics such as density. For the structuring and evaluation of relevant social media posts, we also use the findings of Natural Language Processing, e. g. Named Entity Recognition, specific dictionaries, Triple Tagger and Part-of-Speech-Tagger. The selection and evaluation of the tools used are discussed in this paper. Using our ontology and metrics to structure social media posts enables users to semantically search these posts for new product ideas and thus gain an improved insight into the external sources such as customer needs.

Keywords: idea ontology, innovation management, semantic search, open information extraction

Procedia PDF Downloads 175
12221 Investigation of the Physical Computing in Computational Thinking Practices, Computer Programming Concepts and Self-Efficacy for Crosscutting Ideas in STEM Content Environments

Authors: Sarantos Psycharis

Abstract:

Physical Computing, as an instructional model, is applied in the framework of the Engineering Pedagogy to teach “transversal/cross-cutting ideas” in a STEM content approach. Labview and Arduino were used in order to connect the physical world with real data in the framework of the so called Computational Experiment. Tertiary prospective engineering educators were engaged during their course and Computational Thinking (CT) concepts were registered before and after the intervention across didactic activities using validated questionnaires for the relationship between self-efficacy, computer programming, and CT concepts when STEM content epistemology is implemented in alignment with the Computational Pedagogy model. Results show a significant change in students’ responses for self-efficacy for CT before and after the instruction. Results also indicate a significant relation between the responses in the different CT concepts/practices. According to the findings, STEM content epistemology combined with Physical Computing should be a good candidate as a learning and teaching approach in university settings that enhances students’ engagement in CT concepts/practices.

Keywords: arduino, computational thinking, computer programming, Labview, self-efficacy, STEM

Procedia PDF Downloads 100
12220 Architectural Robotics in Micro Living Spaces: An Approach to Enhancing Wellbeing

Authors: Timothy Antoniuk

Abstract:

This paper will demonstrate why the most successful and livable cities in the future will require multi-disciplinary designers to develop a deep understanding of peoples’ changing lifestyles, and why new generations of deeply integrated products, services and experiences need to be created. Disseminating research from the UNEP Creative Economy Reports and through a variety of other consumption and economic-based statistics, a compelling argument will be made that it is peoples’ living spaces that offer the easiest and most significant affordances for inducing positive changes to their wellbeing, and to a city’s economic and environmental prosperity. This idea, that leveraging happiness, wellbeing and prosperity through creating new concepts and typologies of ‘home’, puts people and their needs, wants, desires, aspirations and lifestyles at the beginning of the design process, not at the end, as so often occurs with current-day multi-unit housing construction. As an important part of the creative-reflective and statistical comparisons that are necessary for this on-going body of research and practice, Professor Antoniuk created the Micro Habitation Lab (mHabLab) in 2016. By focusing on testing the functional and economic feasibility of activating small spaces with different types of architectural robotics, a variety of movable, expandable and interactive objects have been hybridized and integrated into the architectural structure of the Lab. Allowing the team to test new ideas continually and accumulate thousands of points of feedback from everyday consumers, a series of on-going open houses is allowing the public-at-large to see, physically engage with, and give feedback on the items they find most and least valuable. This iterative approach of testing has exposed two key findings: Firstly, that there is a clear opportunity to improve the macro and micro functionality of small living spaces; and secondly, that allowing people to physically alter smaller elements of their living space lessens feelings of frustration and enhances feelings of pride and a deeper perception of “home”. Equally interesting to these findings is a grouping of new research questions that are being exposed which relate to: The duality of space; how people can be in two living spaces at one time; and how small living spaces is moving the Extended Home into the public realm.

Keywords: architectural robotics, extended home, interactivity, micro living spaces

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12219 Using Deep Learning Neural Networks and Candlestick Chart Representation to Predict Stock Market

Authors: Rosdyana Mangir Irawan Kusuma, Wei-Chun Kao, Ho-Thi Trang, Yu-Yen Ou, Kai-Lung Hua

Abstract:

Stock market prediction is still a challenging problem because there are many factors that affect the stock market price such as company news and performance, industry performance, investor sentiment, social media sentiment, and economic factors. This work explores the predictability in the stock market using deep convolutional network and candlestick charts. The outcome is utilized to design a decision support framework that can be used by traders to provide suggested indications of future stock price direction. We perform this work using various types of neural networks like convolutional neural network, residual network and visual geometry group network. From stock market historical data, we converted it to candlestick charts. Finally, these candlestick charts will be feed as input for training a convolutional neural network model. This convolutional neural network model will help us to analyze the patterns inside the candlestick chart and predict the future movements of the stock market. The effectiveness of our method is evaluated in stock market prediction with promising results; 92.2% and 92.1 % accuracy for Taiwan and Indonesian stock market dataset respectively.

Keywords: candlestick chart, deep learning, neural network, stock market prediction

Procedia PDF Downloads 423
12218 A Fuzzy TOPSIS Based Model for Safety Risk Assessment of Operational Flight Data

Authors: N. Borjalilu, P. Rabiei, A. Enjoo

Abstract:

Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained.

Keywords: F-topsis, fuzzy set, flight data monitoring (FDM), flight safety

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12217 The Effect of Sowing Time on Phytopathogenic Characteristics and Yield of Sunflower Hybrids

Authors: Adrienn Novák

Abstract:

The field research was carried out at the Látókép AGTC KIT research area of the University of Debrecen in Eastern-Hungary, on the area of the aeolain loess of the Hajdúság. We examined the effects of the sowing time on the phytopathogenic characteristics and yield production by applying various fertilizer treatments on two different sunflower genotypes (NK Ferti, PR64H42) in 2012 and 2013. We applied three different sowing times (early, optimal, late) and two different treatment levels of fungicides (control = no fungicides applied, double fungicide protection). During our investigations, the studied cropyears were of different sowing time optimum in terms of yield amount (2012: early, 2013: average). By Pearson’s correlation analysis, we have found that delaying the sowing time pronouncedly decreased the extent of infection in both crop years (Diaporthe: r=0.663**, r=0.681**, Sclerotinia: r=0.465**, r=0.622**). The fungicide treatment not only decreased the extent of infection, but had yield increasing effect too (2012: r=0.498**, 2013: r=0.603**). In 2012, delaying of the sowing time increased (r=0.600**), but in 2013, it decreased (r= 0.356*) the yield amount.

Keywords: fungicide treatment, genotypes, sowing time, yield, sunflower

Procedia PDF Downloads 196
12216 Parental Involvement Among Host Community and Refugees in Iraqi Kurdistan

Authors: Peshawa Jalal Mohammed

Abstract:

Following the recent political conflict in the Middle East, the number of refugees and internally displaced people increased in the last decades. The flood of displaced people became a big issue for the host communities in the neighbouring countries and Europe. The need for research about the education and integration of the refugees became urgent. After the appearance of the Islamic State and displacing millions of Syrian people, the Kurdistan Region of Iraq became a safe shelter for hundreds of thousands of Syrians and international organisations helping the refugees. This study focuses on the factors of parental involvement among the host community and refugee parents and its role in the academic success of children. The setting is the three provinces of Iraqi Kurdistan (Erbil, Sulaimani, and Dohuk), including the refugee camps in the three provinces. Based on the purpose of the study, the study was designed as a descriptive survey study with a mixed approach, qualitative (open-ended), and quantitative (questionnaire) questions and both forms of data were integrated and analysed. The current study participants were 8th and 9th graders at the basic school level, studying at public schools and their parents. The sampling design was the selection of local schools and schools in the refugee camps in the region's three provinces. The number of participants for each of the two groups was 250 students and 250 parents. The results showed that parents' socioeconomic status, gender, and place of residency have significant roles in students' parental involvement and academic success of their students. The results also show the characteristics of parental inspiration to their children's future and their expectations from education.

Keywords: refugee, education, parental involvement, socioeconomic

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12215 Concentration of Droplets in a Transient Gas Flow

Authors: Timur S. Zaripov, Artur K. Gilfanov, Sergei S. Sazhin, Steven M. Begg, Morgan R. Heikal

Abstract:

The calculation of the concentration of inertial droplets in complex flows is encountered in the modelling of numerous engineering and environmental phenomena; for example, fuel droplets in internal combustion engines and airborne pollutant particles. The results of recent research, focused on the development of methods for calculating concentration and their implementation in the commercial CFD code, ANSYS Fluent, is presented here. The study is motivated by the investigation of the mixture preparation processes in internal combustion engines with direct injection of fuel sprays. Two methods are used in our analysis; the Fully Lagrangian method (also known as the Osiptsov method) and the Eulerian approach. The Osiptsov method predicts droplet concentrations along path lines by solving the equations for the components of the Jacobian of the Eulerian-Lagrangian transformation. This method significantly decreases the computational requirements as it does not require counting of large numbers of tracked droplets as in the case of the conventional Lagrangian approach. In the Eulerian approach the average droplet velocity is expressed as a function of the carrier phase velocity as an expansion over the droplet response time and transport equation can be solved in the Eulerian form. The advantage of the method is that droplet velocity can be found without solving additional partial differential equations for the droplet velocity field. The predictions from the two approaches were compared in the analysis of the problem of a dilute gas-droplet flow around an infinitely long, circular cylinder. The concentrations of inertial droplets, with Stokes numbers of 0.05, 0.1, 0.2, in steady-state and transient laminar flow conditions, were determined at various Reynolds numbers. In the steady-state case, flows with Reynolds numbers of 1, 10, and 100 were investigated. It has been shown that the results predicted using both methods are almost identical at small Reynolds and Stokes numbers. For larger values of these numbers (Stokes — 0.1, 0.2; Reynolds — 10, 100) the Eulerian approach predicted a wider spread in concentration in the perturbations caused by the cylinder that can be attributed to the averaged droplet velocity field. The transient droplet flow case was investigated for a Reynolds number of 200. Both methods predicted a high droplet concentration in the zones of high strain rate and low concentrations in zones of high vorticity. The maxima of droplet concentration predicted by the Osiptsov method was up to two orders of magnitude greater than that predicted by the Eulerian method; a significant variation for an approach widely used in engineering applications. Based on the results of these comparisons, the Osiptsov method has resulted in a more precise description of the local properties of the inertial droplet flow. The method has been applied to the analysis of the results of experimental observations of a liquid gasoline spray at representative fuel injection pressure conditions. The preliminary results show good qualitative agreement between the predictions of the model and experimental data.

Keywords: internal combustion engines, Eulerian approach, fully Lagrangian approach, gasoline fuel sprays, droplets and particle concentrations

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12214 One-Shot Text Classification with Multilingual-BERT

Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao

Abstract:

Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.

Keywords: OSML, BERT, text classification, one shot

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12213 Optimization of Thermopile Sensor Performance of Polycrystalline Silicon Film

Authors: Li Long, Thomas Ortlepp

Abstract:

A theoretical model for the optimization of thermopile sensor performance is developed for thermoelectric-based infrared radiation detection. It is shown that the performance of polycrystalline silicon film thermopile sensor can be optimized according to the thermoelectric quality factor, sensor layer structure factor, and sensor layout geometrical form factor. Based on the properties of electrons, phonons, grain boundaries, and their interactions, the thermoelectric quality factor of polycrystalline silicon is analyzed with the relaxation time approximation of the Boltzmann transport equation. The model includes the effect of grain structure, grain boundary trap properties, and doping concentration. The layer structure factor is analyzed with respect to the infrared absorption coefficient. The optimization of layout design is characterized by the form factor, which is calculated for different sensor designs. A double-layer polycrystalline silicon thermopile infrared sensor on a suspended membrane has been designed and fabricated with a CMOS-compatible process. The theoretical approach is confirmed by measurement results.

Keywords: polycrystalline silicon, relaxation time approximation, specific detectivity, thermal conductivity, thermopile infrared sensor

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12212 Sun-Driven Evaporation Enhanced Forward Osmosis Process for Application in Wastewater Treatment and Pure Water Regeneration

Authors: Dina Magdy Abdo, Ayat N. El-Shazly, E. A. Abdel-Aal

Abstract:

Forward osmosis (FO) is one of the important processes during the wastewater treatment system for environmental remediation and fresh water regeneration. Both Egypt and China are troubled by over millions of tons of wastewater every year, including domestic and industrial wastewater. However, the traditional FO process in wastewater treatment usually suffers low efficiency and high energy consumption because of the continuously diluted draw solution. An additional concentration process is necessary to keep running of FO separation, causing energy waste. Based on the previous study on photothermal membrane, a sun-driven evaporation process is integrated into the draw solution side of FO system. During the sun-driven evaporation, not only the draw solution can be concentrated to maintain a stable and sustainable FO system, but fresh water can be directly separated for regeneration. Solar energy is the ultimate energy source of everything we have on Earth and is, without any doubt, the most renewable and sustainable energy source available to us. Additionally, the FO membrane process is rationally designed to limit the concentration polarization and fouling. The FO membrane’s structure and surface property will be further optimized by the adjustment of doping ratio of controllable nano-materials, membrane formation conditions, and selection of functional groups. A novel kind of nano-composite functional separation membrane with bi-interception layers and high hydrophilicity will be developed for the application in wastewater treatment. So, herein we aim to design a new wastewater treatment system include forward osmosis with high-efficiency energy recovery via the integration of photothermal membrane.

Keywords: forward osmosis, membrane, solar, water treatement

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12211 Investigation of Green Dye-Sensitized Solar Cells Based on Natural Dyes

Authors: M. Hosseinnezhad, K. Gharanjig

Abstract:

Natural dyes, extracted from black carrot and bramble, were utilized as photosensitizers to prepare dye-sensitized solar cells (DSSCs). Spectrophotometric studies of the natural dyes in solution and on a titanium dioxide substrate were carried out in order to assess changes in the status of the dyes. The results show that the bathochromic shift is seen on the photo-electrode substrate. The chemical binding of the natural dyes at the surface photo-electrode were increased by the chelating effect of the Ti(IV) ions. The cyclic voltammetry results showed that all extracts are suitable to be performed in DSSCs. Finally, photochemical performance and stability of DSSCs based on natural dyes were studied. The DSSCs sensitized by black carrot extract have been reported to achieve up to Jsc=1.17 mAcm-2, Voc= 0.55 V, FF= 0.52, η=0.34%, whereas Bramble extract can obtain up to Jsc=2.24 mAcm-2, Voc= 0.54 V, FF= 0.57, η=0.71%. The power conversion efficiency was obtained from the mixed dyes in DSSCs. The power conversion efficiency of dye-sensitized solar cells using mixed Black carrot and Bramble dye is the average of the their efficiency in single DSSCs.

Keywords: anthocyanin, dye-sensitized solar cells, green energy, optical materials

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12210 Three-Dimensional, Non-Linear Finite Element Analysis of Bullet Penetration through Thin AISI 4340 Steel Target Plate

Authors: Abhishek Soni, A. Kumaraswamy, M. S. Mahesh

Abstract:

Bullet penetration in steel plate is investigated with the help of three-dimensional, non-linear, transient, dynamic, finite elements analysis using explicit time integration code LSDYNA. The effect of large strain, strain-rate and temperature at very high velocity regime was studied from number of simulations of semi-spherical nose shape bullet penetration through single layered circular plate with 2 mm thickness at impact velocities of 500, 1000, and 1500 m/s with the help of Johnson Cook material model. Mie-Gruneisen equation of state is used in conjunction with Johnson Cook material model to determine pressure-volume relationship at various points of interests. Two material models viz. Plastic-Kinematic and Johnson- Cook resulted in different deformation patterns in steel plate. It is observed from the simulation results that the velocity drop and loss of kinetic energy occurred very quickly up to perforation of plate, after that the change in velocity and changes in kinetic energy are negligibly small. The physics behind this kind of behaviour is presented in the paper.

Keywords: AISI 4340 steel, ballistic impact simulation, bullet penetration, non-linear FEM

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12209 Designing Stochastic Non-Invasively Applied DC Pulses to Suppress Tremors in Multiple Sclerosis by Computational Modeling

Authors: Aamna Lawrence, Ashutosh Mishra

Abstract:

Tremors occur in 60% of the patients who have Multiple Sclerosis (MS), the most common demyelinating disease that affects the central and peripheral nervous system, and are the primary cause of disability in young adults. While pharmacological agents provide minimal benefits, surgical interventions like Deep Brain Stimulation and Thalamotomy are riddled with dangerous complications which make non-invasive electrical stimulation an appealing treatment of choice for dealing with tremors. Hence, we hypothesized that if the non-invasive electrical stimulation parameters (mainly frequency) can be computed by mathematically modeling the nerve fibre to take into consideration the minutest details of the axon morphologies, tremors due to demyelination can be optimally alleviated. In this computational study, we have modeled the random demyelination pattern in a nerve fibre that typically manifests in MS using the High-Density Hodgkin-Huxley model with suitable modifications to account for the myelin. The internode of the nerve fibre in our model could have up to ten demyelinated regions each having random length and myelin thickness. The arrival time of action potentials traveling the demyelinated and the normally myelinated nerve fibre between two fixed points in space was noted, and its relationship with the nerve fibre radius ranging from 5µm to 12µm was analyzed. It was interesting to note that there were no overlaps between the arrival time for action potentials traversing the demyelinated and normally myelinated nerve fibres even when a single internode of the nerve fibre was demyelinated. The study gave us an opportunity to design DC pulses whose frequency of application would be a function of the random demyelination pattern to block only the delayed tremor-causing action potentials. The DC pulses could be delivered to the peripheral nervous system non-invasively by an electrode bracelet that would suppress any shakiness beyond it thus paving the way for wearable neuro-rehabilitative technologies.

Keywords: demyelination, Hodgkin-Huxley model, non-invasive electrical stimulation, tremor

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12208 Comparing Performance of Neural Network and Decision Tree in Prediction of Myocardial Infarction

Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

Abstract:

Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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12207 Determination of the Optimum Size of Building Stone Blocks: Case Study of Delichai Travertine Mine

Authors: Hesam Sedaghat Nejad, Navid Hosseini, Arash Nikvar Hassani

Abstract:

Determination of the optimum block size with high profitability is one of the significant parameters in designation of the building stone mines. The aim of this study was to determine the optimum dimensions of building stone blocks in Delichai travertine mine of Damavand in Tehran province through combining the effective parameters proven in determination of the optimum dimensions in building stones such as the spacing of joints and gaps, extraction tools constraints with the help of modeling by Gemcom software. To this end, following simulation of the topography of the mine, the block model was prepared and then in order to use spacing joints and discontinuities as a limiting factor, the existing joints set was added to the model. Since only one almost horizontal joint set with a slope of 5 degrees was available, this factor was effective only in determining the optimum height of the block, and thus to determine the longitudinal and transverse optimum dimensions of the extracted block, the power of available loader in the mine was considered as the secondary limiting factor. According to the aforementioned factors, the optimal block size in this mine was measured as 3.4×4×7 meter.

Keywords: building stone, optimum block size, Delichay travertine mine, loader power

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12206 Measuring Output Multipliers of Energy Consumption and Manufacturing Sectors in Malaysia during the Global Financial Crisis

Authors: Hussain Ali Bekhet, Tuan Ab. Rashid Bin Tuan Abdullah, Tahira Yasmin

Abstract:

The strong relationship between energy consumption and economic growth is widely recognised. Most countries’ energy demand declined during the economic depression known as the Global Financial Crisis (GFC) of 2008–2009. The objective of the current study is to investigate the energy consumption and performance of Malaysia’s manufacturing sectors during the GFC. We applied the output multiplier approach, which is based on the input-output model. Two input-output tables of Malaysia covering 2005 and 2010 were used. The results indicate significant changes in the output multipliers of the manufacturing sectors between 2005 and 2010. Moreover, the energy-to-manufacturing sectors’ output multipliers also decreased during the GFC due to a decline in export-oriented industries during the crisis. The increasing importance of the manufacturing sector to the development of Malaysian trade resulted in a noticeable decrease in the consumption of each energy sector’s output, especially the electricity and gas sector. Based on the research findings, the Malaysian government released several policy implementations in the form of stimulus packages to enhance these sectors’ performance and generally improve the Malaysian economy.

Keywords: global financial crisis, input-output model, manufacturing, output multipliers, energy, Malaysia

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12205 Assessment of Proximate Composition and Heavy Metal in Vigna unguculata (White Beans) Sold in Kazaure Market, Jigawa State, Nigeria

Authors: Abdu Umar Adamu, Saidu Akun Abdullahi, Al-Hassan Muhammed, Hamisu Abdu

Abstract:

Leguminous plants such as beans have been considered as a source of protein in this present work. The proximate analysis on beans (Vigna unguiculata) were determined in order to identify the nutritional content as well as presence of some heavy metals accumulation in washed and unwashed beans (white Beans) sold in Kazaure market Jigawa State Nigeria. On the average comparative analysis, the result has indicated that, the Vigna unguiculata had protein content of 61.1%, fibre 4.5%, ash 10.4%, moisture 5%, carbohydrate 15.8% and total lipid 4.9%, therefore it could be suggested that beans has enough nutritional content that helps the people health. The heavy metal analysis of unwashed white beans showed that Fe (17.37 ± 6.71)mg/kg had the highest concentration followed by Zn (6.41 ± 3.09), Cu (5.69 ± 2.42), Cd (0.46 ± 0.65) and Pb (0.57 ± 0.94)mg/kg , while the washed beans shows that Zn (0.11 ± 0.17), Fe (0.01 ± 0.006), Cd (0.02 ± 0.01), Cu (0.03 ± 0.021), Pb (0.01 ± 0.006)mg/kg. The washed white beans are safe for consumption and also the concentration of heavy metal are negligible and of nontoxic effect to human health.

Keywords: white beans, protein, proximate composition, heavy metal

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12204 Short-Term Operation Planning for Energy Management of Exhibition Hall

Authors: Yooncheol Lee, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

This paper deals with the establishment of a short-term operational plan for an air conditioner for efficient energy management of exhibition hall. The short-term operational plan is composed of a time series of operational schedules, which we have searched using genetic algorithms. Establishing operational schedule should be considered the future trends of the variables affecting the exhibition hall environment. To reflect continuously changing factors such as external temperature and occupant, short-term operational plans should be updated in real time. But it takes too much time to evaluate a short-term operational plan using EnergyPlus, a building emulation tool. For that reason, it is difficult to update the operational plan in real time. To evaluate the short-term operational plan, we designed prediction models based on machine learning with fast evaluation speed. This model, which was created by learning the past operational data, is accurate and fast. The collection of operational data and the verification of operational plans were made using EnergyPlus. Experimental results show that the proposed method can save energy compared to the reactive control method.

Keywords: exhibition hall, energy management, predictive model, simulation-based optimization

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12203 The Impact of Sustainable Packaging on Customers’ Willingness to Buy: A Study Based in Rwanda

Authors: Nirere Martine

Abstract:

Purpose –The purpose of this study aims to understand the intention of customers to adopt sustainable packaging and the impact of sustainable packaging on customers’ willingness to buy a product using sustainable packaging. Design/methodology/approach – A new research model based on the technology acceptance model (TAM) and structural equation modeling are used to examine causality and test relationship based on the data collected from 251 Rwanda samples. Findings – The findings indicated that perceived ease of use positively affects perceived usefulness. However, perceived usefulness and perceived ease of use positively affect the intention to adopt sustainable packaging. However, perceived risk and perceived cost negatively affect the intention to adopt sustainable packaging. The intention to adopt sustainable packaging positively affects the willingness to buy a product using sustainable packaging. Originality/value – Many researchers have investigated the issue of a consumers’ behavior to purchase a product. In particular, they have examined whether customers are willing to pay extra for a packaging product. There has been no study that has examined the impact of sustainable packaging on customers’ willingness to buy. The results of this study can help manufacturers form a better understanding of customers’ willingness to purchase a product using sustainable packaging.

Keywords: consumers’ behavioral, sustainable packaging, TAM, Rwanda

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12202 Nutritive Potential of Mealworm (Tenebrio molitor) in the Diet of Olive Flounder (Paralichthys olivaceus)

Authors: Joo-min Kim, Gi-wook Shin, Tae-ho Chung, Chul Park, Seong-hyun Kim, Namjung Kim

Abstract:

Mealworm (Tenebrio molitor) was evaluated to investigate the effect of partial or total replacement of fish meal in diets for olive flounder, Paralichthys olivaceus. Experimental groups of fish with average initial body weight (287.5 ± 7.24 g) were fed each with 4 isonitrogeneous (52% crude protein) diets formulated to include 0, 7, 17 and 27% (diets 1 to 4, respectively) of fish meal substituted with mealworm. After six weeks of feeding trials, fish fed with diet 3 revealed the highest values for live weight gain(42.10), specific growth rates (0.445 ± 0.089) as well as better feed conversion ratio (12.08) compared to the other group with statistically significant manner (p<0.05). Hepatosomatic index was showed no significant difference in diet 3 compared to the control group. An increase in weight gain and other growth associated parameters was observed in diet 3. These results clearly indicate that 17% of fish meal protein in bastard halibut diet can be replaced by mealworm not only without any adverse effect but also the effect of promoting growth performance.

Keywords: mealworm, olive flounder, Paralichthys olivaceus, Tenebrio molitor

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12201 Modelling Dengue Disease With Climate Variables Using Geospatial Data For Mekong River Delta Region of Vietnam

Authors: Thi Thanh Nga Pham, Damien Philippon, Alexis Drogoul, Thi Thu Thuy Nguyen, Tien Cong Nguyen

Abstract:

Mekong River Delta region of Vietnam is recognized as one of the most vulnerable to climate change due to flooding and seawater rise and therefore an increased burden of climate change-related diseases. Changes in temperature and precipitation are likely to alter the incidence and distribution of vector-borne diseases such as dengue fever. In this region, the peak of the dengue epidemic period is around July to September during the rainy season. It is believed that climate is an important factor for dengue transmission. This study aims to enhance the capacity of dengue prediction by the relationship of dengue incidences with climate and environmental variables for Mekong River Delta of Vietnam during 2005-2015. Mathematical models for vector-host infectious disease, including larva, mosquito, and human being were used to calculate the impacts of climate to the dengue transmission with incorporating geospatial data for model input. Monthly dengue incidence data were collected at provincial level. Precipitation data were extracted from satellite observations of GSMaP (Global Satellite Mapping of Precipitation), land surface temperature and land cover data were from MODIS. The value of seasonal reproduction number was estimated to evaluate the potential, severity and persistence of dengue infection, while the final infected number was derived to check the outbreak of dengue. The result shows that the dengue infection depends on the seasonal variation of climate variables with the peak during the rainy season and predicted dengue incidence follows well with this dynamic for the whole studied region. However, the highest outbreak of 2007 dengue was not captured by the model reflecting nonlinear dependences of transmission on climate. Other possible effects will be discussed to address the limitation of the model. This suggested the need of considering of both climate variables and another variability across temporal and spatial scales.

Keywords: infectious disease, dengue, geospatial data, climate

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12200 Model of Learning Center on OTOP Production Process Based on Sufficiency Economic Philosophy

Authors: Chutikarn Sriviboon, Witthaya Mekhum

Abstract:

The purposes of this research were to analyze and evaluate successful factors in OTOP production process for the developing of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The research has been designed as a qualitative study to gather information from 30 OTOP producers in Bangkontee District, Samudsongkram Province. They were all interviewed on 3 main parts. Part 1 was about the production process including 1) production 2) product development 3) the community strength 4) marketing possibility and 5) product quality. Part 2 evaluated appropriate successful factors including 1) the analysis of the successful factors 2) evaluate the strategy based on Sufficiency Economic Philosophy and 3) the model of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The results showed that the production did not affect the environment with potential in continuing standard quality production. They used the raw materials in the country. On the aspect of product and community strength in the past 1 year, it was found that there was no appropriate packaging showing product identity according to global market standard. They needed the training on packaging especially for food and drink products. On the aspect of product quality and product specification, it was found that the products were certified by the local OTOP standard. There should be a responsible organization to help the uncertified producers pass the standard. However, there was a problem on food contamination which was hazardous to the consumers. The producers should cooperate with the government sector or educational institutes involving with food processing to reach FDA standard. The results from small group discussion showed that the community expected high education and better standard living. Some problems reported by the community included informal debt and drugs in the community. There were 8 steps in developing the model of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality.

Keywords: production process, OTOP, sufficiency economic philosophy, learning center

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12199 Influence of Fermentation Conditions on Humic Acids Production by Trichoderma viride Using an Oil Palm Empty Fruit Bunch as the Substrate

Authors: F. L. Motta, M. H. A. Santana

Abstract:

Humic Acids (HA) were produced by a Trichoderma viride strain under submerged fermentation in a medium based on the oil palm Empty Fruit Bunch (EFB) and the main variables of the process were optimized by using response surface methodology. A temperature of 40°C and concentrations of 50g/L EFB, 5.7g/L potato peptone and 0.11g/L (NH4)2SO4 were the optimum levels of the variables that maximize the HA production, within the physicochemical and biological limits of the process. The optimized conditions led to an experimental HA concentration of 428.4±17.5 mg/L, which validated the prediction from the statistical model of 412.0mg/L. This optimization increased about 7–fold the HA production previously reported in the literature. Additionally, the time profiles of HA production and fungal growth confirmed our previous findings that HA production preferably occurs during fungal sporulation. The present study demonstrated that T. viride successfully produced HA via the submerged fermentation of EFB and the process parameters were successfully optimized using a statistics-based response surface model. To the best of our knowledge, the present work is the first report on the optimization of HA production from EFB by a biotechnological process, whose feasibility was only pointed out in previous works.

Keywords: empty fruit bunch, humic acids, submerged fermentation, Trichoderma viride

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12198 A Conv-Long Short-term Memory Deep Learning Model for Traffic Flow Prediction

Authors: Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh

Abstract:

Traffic congestion has become a severe worldwide problem, affecting everyday life, fuel consumption, time, and air pollution. The primary causes of these issues are inadequate transportation infrastructure, poor traffic signal management, and rising population. Traffic flow forecasting is one of the essential and effective methods in urban congestion and traffic management, which has attracted the attention of researchers. With the development of technology, undeniable progress has been achieved in existing methods. However, there is a possibility of improvement in the extraction of temporal and spatial features to determine the importance of traffic flow sequences and extraction features. In the proposed model, we implement the convolutional neural network (CNN) and long short-term memory (LSTM) deep learning models for mining nonlinear correlations and their effectiveness in increasing the accuracy of traffic flow prediction in the real dataset. According to the experiments, the results indicate that implementing Conv-LSTM networks increases the productivity and accuracy of deep learning models for traffic flow prediction.

Keywords: deep learning algorithms, intelligent transportation systems, spatiotemporal features, traffic flow prediction

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12197 The Effects of Separating Inferior Alveolar Neurovascular Bundles on Osteogenesis of Tissue-Engineered Bone and Vascularization

Authors: Lin Feng, E. Lingling, Hongchen Liu

Abstract:

In order to evaluate the effects of autologous blood vessels and nerves on vascularization. A dog model of tissue-engineered bone vascularization was established by constructing inferior alveolar neurovascular bundles through the mandibular canal. Sixteen 12-month-old healthy beagles were randomly divided into two groups (n=8). Group A retained inferior alveolar neurovascular bundles, and Group B retained inferior alveolar nerves. Bone marrow mesenchymal stem cells were injected into β-tricalcium phosphate to prepare internal tissue-engineered bone scaffold. A personalized titanium mesh was then prepared by rapid prototyping and fixed by external titanium scaffold. Two dogs in each group were sacrificed on the 30th, 45th, 60th, and 90th postoperative days respectively. The bone was visually examined, scanned by CT, and subjected to HE staining, immunohistochemical staining, vascular casting and PCR to detect the changes in osteogenesis and vascularization.The two groups had similar outcomes in regard to osteogenesis and vascularization (P>0.05) both showed remarkable regenerative capacities. The model of tissue-engineered bone vascularization is potentially applicable in clinical practice to allow satisfactory osteogenesis and vascularization.

Keywords: inferior alveolar neurovascular bundle, osteogenesis, tissue-engineered bone, vascularization

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12196 Horizontal and Vertical Illuminance Correlations in a Case Study for Shaded South Facing Surfaces

Authors: S. Matour, M. Mahdavinejad, R. Fayaz

Abstract:

Daylight utilization is a key factor in achieving visual and thermal comfort, and energy savings in integrated building design. However, lack of measured data related to this topic has become a major challenge with the increasing need for integrating lighting concepts and simulations in the early stages of design procedures. The current paper deals with the values of daylight illuminance on horizontal and south facing vertical surfaces; the data are estimated using IESNA model and measured values of the horizontal and vertical illuminance, and a regression model with an acceptable linear correlation is obtained. The resultant illuminance frequency curves are useful for estimating daylight availability on south facing surfaces in Tehran. In addition, the relationship between indirect vertical illuminance and the corresponding global horizontal illuminance is analyzed. A simple parametric equation is proposed in order to predict the vertical illumination on a shaded south facing surface. The equation correlates the ratio between the vertical and horizontal illuminance to the solar altitude and is used with another relationship for prediction of the vertical illuminance. Both equations show good agreement, which allows for calculation of indirect vertical illuminance on a south facing surface at any time throughout the year.

Keywords: Tehran daylight availability, horizontal illuminance, vertical illuminance, diffuse illuminance

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12195 Influence of Social, Economic, Political and Legal Environment of Sport Organizations on Sport Development in Zone Ten (10) of National Zonal Sport Offices in Nigeria

Authors: Ejeh Benjamin Ijuo

Abstract:

The purpose of this study was to investigate the influence of social, economic, political, and legal environment of sport organizations on sport development in zone ten (10) national zonal sport offices in Nigeria (Plateau, Nasarawa, Benue and F.C.T Abuja). To achieve this purpose, a structured 26 item questionnaire (ISEPLESOQ) designed by the researcher was used for this study. Related literature to this study was reviewed. 311 copies of questionnaire were administered to randomly selected respondents. Out of this number, 306 was dully completed and returned representing 98.4%. The respondents included: Athletes, games masters/ mistresses, coaches in state sport councils, zonal sport coordinators, team managers, directors of state sports council. Four research questions were answered using the mean and standard deviation, while the inferential statistics of chi-square(x2) test of goodness of fit was used to test the four hypotheses at 0.05 alpha levels. The findings of this study revealed that the social, economic, political and legal environment of sport organizations significantly influenced sport development in zone ten (10) national zonal sport offices in Nigeria. It was also established that the general environment of sport organizations influences people’s participation in sport, funding and sponsorship of sports, sitting of equipment and facilities at different locations, selection of athletes. It was therefore, recommended among other things that government should privatize and commercialized sport programmes to enable corporate organizations and individuals participation. Lt was further suggested that the federal government should harness her social, economic, political and legal environment to improve sport development in Nigeria.

Keywords: sport organization, sport development, sport environment, zonal sport offices

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12194 Assessment of Surface Water Quality in Belarus

Authors: Anastasiya Vouchak, Aliaksandr Volchak

Abstract:

Belarus is not short of water. However, there is a problem of water quality. Its pollution has both natural and man-made origin. This research is based on data from State Water Cadastre of the Republic of Belarus registered from 1994 to 2014. We analyzed changes in such hydro-chemical criteria as concentration of ammonium ions, suspended matter, dissolved oxygen, oil-products, nitrites, phosphates in water, dichromate value, water impurity index, 5-day biochemical oxygen demand (BOD). Pollution of water with ammonium ions was observed in Belarus rivers of the Western Dvina, Polota, Schara, Usha, Muhavets, Berzina, Plissa, Svisloch, Pripiat, Yaselda in 2006-2014. The threshold limit value (TLV) was 1.5-3 times as much. Concentration of ammonia in the Berezina exceeded 3 – 5 times the TLVs in 2006-2010. Maximum excess of TLV was registered in the Svisloch (10 km downstream of Minsk) in 2006-2007. It was over 4 mg/dm³ whereas the norm is 0.39 mg/dm³. In 1997 there were ammonia pollution spots in the Dnieper, the Berezina, and the Svisloch Rivers. Since 2006 we have observed pollution spots in the Neman, Ross, Vilia, Sozh, Gorin Rivers, the Osipovichi and Soligorsk reservoirs. Dichromate value exceeds the TLVs in 40% cases. The most polluted waters are the Muhavets, Berezina, Pripiat, Yaselda, Gorin Rivers, the Vileyka and Soligorsk reservoirs. The Western Dvina, Neman, Viliya, Schara, Svisloch, and Plissa Rivers are less polluted. The Dnieper is the cleanest in this respect. In terms of BOD, water is polluted in the Neman, Muhavets, Svisloch, Yaselda, Gorin Rivers, the Osipovichi, Zaslavl, and Soligorsk reservoirs. The Western Dvina, Polota, Sozh, Iputs Rivers and Lake Naroch are not polluted in this respect. This criterion has been decreasing in 33 out of 42 cases. The least suspended matter is in the Berezina, Sozh, Iputs Rivers and Lake Naroch. The muddiest water is in the Neman, Usha, Svisloch, Pripyat, Yaselda Rivers, the Osipovichi and Soligorsk reservoirs. Water impurity index shows reduction of this criterion at all gauge stations. Multi-year average values predominantly (66.6%) correspond to the third class of water quality, i.e. moderately polluted. They include the Western Dvina, Ross, Usha, Muhavets, Dnieper, Berezina, Plissa, Iputs, Pripyat, Yaselda, Gorin Rivers, the Osipovichi and Soligorsk reservoirs. Water in the Svisloch River downstream of Minsk is of the forth quality class, i.e. most polluted. In the rest cases (33.3%) water is relatively clean. They include the Lidea, Schara, Viliya, Sozh Rivers, Lake Lukoml, Lake Naroch, Vileyka and Zaslavl reservoirs. Multi-year average values range from 7.0 to 9.5 mg О₂/dm³. The Yaselda has the least value - 6.7 mg О₂/dm³. A shortage of dissolved oxygen was found in the Berezina (2010), the Yaselda (2007), the Plissa (2011-2014), the Soligorsk reservoir (1996). Contamination of water with oil-products was observed everywhere in 1994-1999. Some spots were found in the Western Dvina, Vilia, Usha, Dnieper in 2003-2006, in the Svisloch in 2002-2012. We are observing gradual decrease of oil pollutants in surface water. The quality of 67 % surface water is referred to as moderately polluted.

Keywords: belarus, hydro-chemical criteria, water pollution, water quality

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