Search results for: statistical simulation

Authors: Selfa Johnson Zwalnan, Nanchen Nimyel Caleb, Gideon Duvuna Ayuba

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Air conditioning accounts for a significant share of the overall energy consumed in residential buildings. Solar thermal gains in buildings account for a significant component of the air conditioning load in buildings. This study compares the solar thermal gain and air conditioning load of a proposed building design with a typical conventional building in the climatic conditions of Jos, Nigeria, using a combined experimental and computational method using TRNSYS software. According to the findings of this study, the proposed design building's annual average solar thermal gains are lower compared to the reference building's average solar heat gains. The study case building's decreased solar heat gain is mostly attributable to the somewhat lower temperature of the building zones because of the greater building volume and lower fenestration ratio (ratio of external opening area to the area of the external walls). This result shows that the innovative building design adjusts to the local climate better than the standard conventional construction in Jos to maintain a suitable temperature within the building. This finding means that the air-conditioning electrical energy consumption per volume of the proposed building design will be lower than that of a conventional building design.

Keywords: building simulation, solar gain, comfort temperature, temperature, carbon foot print

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Authors: Thandeka Y. S. Jwara, Paul Musonge

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Traditionally, the complexity associated with implementing and controlling biological nutrient removal (BNR) in wastewater works (WWW) has been primarily in terms of balancing competing requirements for nitrogen and phosphorus removal, particularly with respect to the use of influent chemical oxygen demand (COD) as a carbon source for the microorganisms. Successful BNR optimization and modelling using WEST (Worldwide Engine for Simulation and Training) depend largely on the accurate fractionation of the influent COD. The different COD fractions have differing effects on the BNR process, and therefore, the influent characteristics need to be well understood. This study presents the fractionation results of primary wastewater effluent COD at one of South Africa’s wastewater works treating 65ML/day of mixed industrial and domestic effluent. The method used for COD fractionation was the oxygen uptake rate/respirometry method. The breakdown of the results of the analysis is as follows: 70.5% biodegradable COD (bCOD) and 29.5% of non-biodegradable COD (iCOD) in terms of the total COD. Further fractionation led to a readily biodegradable soluble fraction (SS) of 75%, a slowly degradable particulate fraction (XS) of 24%, a particulate non-biodegradable fraction (XI) of 50.8% and a non-biodegradable soluble fraction (SI) of 49.2%. The fractionation results demonstrate that the primary effluent has good COD characteristics, as shown by the high level of the bCOD fraction with Ss being higher than Xs. This means that the microorganisms have sufficient substrate for the BNR process and that these components can now serve as inputs to the WEST Model for the plant under study.

Keywords: chemical oxygen demand, COD fractionation, wastewater modelling, wastewater optimization

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Authors: Martins Y. Otache, John J. Musa, Abayomi I. Kuti, Mustapha Mohammed

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The performance of an artificial neural network (ANN) is contingent on a host of factors, for instance, the network optimisation scheme. In view of this, the study examined the general implications of the ANN training optimisation algorithm on its forecast performance. To this end, the Bayesian regularisation (Br), Levenberg-Marquardt (LM), and the adaptive learning gradient descent: GDM (with momentum) algorithms were employed under different ANN structural configurations: (1) single-hidden layer, and (2) double-hidden layer feedforward back propagation network. Results obtained revealed generally that the gradient descent with momentum (GDM) optimisation algorithm, with its adaptive learning capability, used a relatively shorter time in both training and validation phases as compared to the Levenberg- Marquardt (LM) and Bayesian Regularisation (Br) algorithms though learning may not be consummated; i.e., in all instances considering also the prediction of extreme flow conditions for 1-day and 5-day ahead, respectively especially using the ANN model. In specific statistical terms on the average, model performance efficiency using the coefficient of efficiency (CE) statistic were Br: 98%, 94%; LM: 98 %, 95 %, and GDM: 96 %, 96% respectively for training and validation phases. However, on the basis of relative error distribution statistics (MAE, MAPE, and MSRE), GDM performed better than the others overall. Based on the findings, it is imperative to state that the adoption of ANN for real-time forecasting should employ training algorithms that do not have computational overhead like the case of LM that requires the computation of the Hessian matrix, protracted time, and sensitivity to initial conditions; to this end, Br and other forms of the gradient descent with momentum should be adopted considering overall time expenditure and quality of the forecast as well as mitigation of network overfitting. On the whole, it is recommended that evaluation should consider implications of (i) data quality and quantity and (ii) transfer functions on the overall network forecast performance.

Keywords: streamflow, neural network, optimisation, algorithm

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Authors: M. Baldini, H. K. Jacobsen, M. Jaccard

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In light of the international efforts to comply with the Paris agreement and emission targets for future energy systems, Denmark and Canada are among the front-runner countries dealing with climate change. The experiences in the energy sector have seen both countries coping with trade-offs between investments in renewable energy technologies and energy efficiency, thus tackling the climate issue from the supply and demand side respectively. On the demand side, the industrial sector is going through a remarkable transformation, with implementation of energy efficiency measures, change of input fuel for end-use processes and forecasted electrification as main features under the spotlight. By looking at Canada and Denmark's experiences as pathfinders on the demand and supply approach to climate change, it is possible to obtain valuable experience that may be applied to other countries aiming at the same goal. This paper presents a comparative study on industrial energy efficiency between Canada and Denmark. The study focuses on technologies and system options, policy design and implementation and modelling methodologies when implementing industrial energy savings in optimization models in comparison to simulation models. The study identifies gaps and junctures in the approach towards climate change actions and, learning from each other, lessen the differences to further foster the adoption of energy efficiency measurements in the industrial sector, aiming at reducing energy consumption and, consequently, CO₂ emissions.

Keywords: industrial energy efficiency, comparative study, CO₂ reduction, energy system modelling

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Authors: Saeid Haghjoo, Ebrahim Reyhani, Fahimeh Kolahdouz

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The present study aimed to evaluate the understanding of the students in Tehran universities (Iran) about the numerical representation of the average rate of change based on the Structure of Observed Learning Outcomes (SOLO). In the present descriptive-survey research, the statistical population included undergraduate students (basic sciences and engineering) in the universities of Tehran. The samples were 604 students selected by random multi-stage clustering. The measurement tool was a task whose face and content validity was confirmed by math and mathematics education professors. Using Cronbach's Alpha criterion, the reliability coefficient of the task was obtained 0.95, which verified its reliability. The collected data were analyzed by descriptive statistics and inferential statistics (chi-squared and independent t-tests) under SPSS-24 software. According to the SOLO model in the prestructural, unistructural, and multistructural levels, basic science students had a higher percentage of understanding than that of engineering students, although the outcome was inverse at the relational level. However, there was no significant difference in the average understanding of both groups. The results indicated that students failed to have a proper understanding of the numerical representation of the average rate of change, in addition to missconceptions when using physics formulas in solving the problem. In addition, multiple solutions were derived along with their dominant methods during the qualitative analysis. The current research proposed to focus on the context problems with approximate calculations and numerical representation, using software and connection common relations between math and physics in the teaching process of teachers and professors.

Keywords: average rate of change, context problems, derivative, numerical representation, SOLO taxonomy

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Authors: Salman Piri

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In this study, a two-dimensional lattice Boltzmann method (LBM) was considered for the numerical simulation of fluid flow in a channel. Also, the Lagrangian method was used for particle tracking in one-way coupling. Three hundred spherical particles with specific diameters were released in the channel entry and an elliptical object was placed in the channel for flow obstruction. The effect of gravity, the drag force, the Saffman lift and the Brownian forces were evaluated in the particle motion trajectories. Also, the effect of the geometrical parameter, ellipse aspect ratio, and the flow characteristic or Reynolds number was surveyed for the transport and deposition of particles. Moreover, the influence of particle diameter between 0.01 and 10 µm was investigated. Results indicated that in small Reynolds, more inertial and gravitational trapping occurred on the obstacle surface for particles with larger diameters. Whereas, for nano-particles, influenced by Brownian diffusion and vortices behind the obstacle, the inertial and gravitational mechanisms were insignificant and diffusion was the dominant deposition mechanism. In addition, in Reynolds numbers larger than 400, there was no significant difference between the deposition of finer and larger particles. Also, in higher aspect ratios of the ellipse, more inertial trapping occurred for particles of larger diameter (10 micrometers), while in lower cases, interception and gravitational mechanisms were dominant.

Keywords: ellipse aspect elito, particle tracking diffusion, lattice boltzman method, larangain particle tracking

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Authors: Raghunandan Gurumurthy, Aricson Pereira, Sandeep Patil

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The escalating adoption of electric vehicles (EVs) across the globe has underscored the critical importance of advancing battery system technologies. This has catalyzed a shift towards the design and development of battery systems that not only exhibit higher energy efficiency but also boast enhanced thermal performance and sophisticated multi-material enclosures. A significant leap in this domain has been the incorporation of simulation-based design optimization for battery packs and Battery Management Systems (BMS), a move further enriched by integrating artificial intelligence/machine learning (AI/ML) approaches. These strategies are pivotal in refining the design, manufacturing, and operational processes for electric vehicles and energy storage systems. By leveraging AI/ML, stakeholders can now predict battery performance metrics—such as State of Health, State of Charge, and State of Power—with unprecedented accuracy. Furthermore, as Li-ion batteries (LIBs) become more prevalent in urban settings, the imperative for bolstering thermal and fire resilience has intensified. This has propelled Battery Thermal Management Systems (BTMs) to the forefront of energy storage research, highlighting the role of machine learning and AI not just as tools for enhanced safety management through accurate temperature forecasts and diagnostics but also as indispensable allies in the early detection and warning of potential battery fires.

Keywords: electric vehicles, battery thermal management, industrial engineering, machine learning, artificial intelligence, manufacturing

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Authors: Olajumoke Adetoun Ojeleye

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The study assessed the safety culture, mindfulness and safe behaviors of students residing in the halls of residence of Obafemi Awolowo University (OAU), Ile Ife, Nigeria. The objectives of the study were to assess the level of safety mindfulness of students residing in the halls of residence of OAU, examine their safety culture and establish whether these students are involved in unsafe practices. The study employed a cross-sectional research design and instrument used for data collection was a self-structured, self-administered questionnaire. The questionnaire was tested for validity and reliability with its reliability coefficient at 0.71 before being used for data collection. Respondents were selected by multi-stage sampling technique and the sample size was 530. Data collection took 2 weeks and analysed using descriptive statistical techniques. Results showed that about half of the respondents’ population (49.8%) was between the ages of 20-24 years. There were more males (56.2%) than females (43.8%). Although data demonstrated that majority (91.7%) of the respondents are highly safety minded and the safety culture of an equally high proportion (83.4%) was adjudged fair, a lot of improvement is needed in the area of alerting or informing management of impending dangers and studying the hall handbook to internalize its contents. The study further showed that only 43.6% of respondents had good safety practices and behaviors and majority (56.4%) had fair safety practices and behaviors. One accidental discovery of the study is the finding that not a few of the students squat their counterparts. The study recommended the establishment of clearly written out complaint procedure that is accessible and available to all hall residents, building more hostels with adequate facilities to address the issue of overcrowding and also putting systems in place in order to encourage residents to report incidences/accidents.

Keywords: safe behaviours, safety culture, safety mindfulness, student

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Authors: Zainab Fadhil Al Toki, Nader Ghareeb

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This study investigates how lightweight a fire resistance door will perform with under types of insulation materials. Data is initially collected from various websites, scientific books and research papers. Results show that different layers of insulation in a single door can perform better than one insulator. Furthermore, insulation materials that are lightweight, high strength and low thermal conductivity are the most preferred for fire-rated doors. Whereas heavy weight, low strength, and high thermal conductivity are least preferred for fire resistance doors. Fire-rated door specifications, theoretical test methodology, structural analysis, and comparison between five different models with diverse layers insulations are presented. Five different door models are being investigated with different insulation materials and arrangements. Model 1 contains an air gap between door layers. Model 2 includes phenolic foam, mild steel and polyurethane. Model 3 includes phenolic foam and glass wool. Model 4 includes polyurethane and glass wool. Model 5 includes only rock wool between the door layers. It is noticed that model 5 is the most efficient model, and its design is simple compared to other models. For this model, numerical calculations are performed to check its efficiency and the results are compared to data from experiments for validation. Good agreement was noticed.

Keywords: fire resistance, insulation, strength, thermal conductivity, lightweight, layers

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Authors: H. Shokouhmand, A. Ghanami

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A heat pipe is simple heat transfer device which combines the conduction and phase change phenomena to control the heat transfer without any need for external power source. At a hot surface of the heat pipe, the liquid phase absorbs heat and changes to the vapor phase. The vapor phase flows to condenser region and with the loss of heat changes to the liquid phase. Due to gravitational force the liquid phase flows to the evaporator section. In HVAC systems, the working fluid is chosen based on the operating temperature. The heat pipe has significant capability to reduce the humidity in HVAC systems. Each HVAC system which uses the heater, humidifier, or dryer is a suitable nominate for the utilization of heat pipes. Generally, heat pipes have three main sections: condenser, adiabatic region, and evaporator. Performance investigation and optimization of heat pipes operation in order to increase their efficiency is crucial. In the present article, a parametric study is performed to improve the heat pipe performance. Therefore, the heat capacity of the heat pipe with respect to geometrical and confining parameters is investigated. For the better observation of heat pipe operation in HVAC systems, a CFD simulation in Eulerian-Eulerian multiphase approach is also performed. The results show that heat pipe heat transfer capacity is higher for water as working fluid with the operating temperature of 340 K. It is also showed that the vertical orientation of heat pipe enhances its heat transfer capacity.

Keywords: heat pipe, HVAC system, grooved heat pipe, heat pipe limits

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Authors: Nabil Hameed Al-Farsi

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This study’s main goal is to develop a model and a maintenance strategy for a cement factory called Arabian Cement Company, Rabigh Plant. The proposed work here depends on Reliability centric maintenance approach to develop a strategy and maintenance schedule that ensures increasing the reliability of the production system components, thus ensuring continuous productivity. The cost-effective maintenance of the plant’s dependability performance is the key goal of durability-based maintenance is. The cement plant consists of 7 important steps, so, developing a maintenance plan based on Reliability centric maintenance (RCM) method is made up of 10 steps accordingly starting from selecting units and data until performing and updating the model. The processing unit chosen for the analysis of this case is the calcinatory unit regarding model’s validation and the Travancore Titanium Products Ltd (TTP) using the claimed data history acquired from the maintenance department maintenance from the mentioned company. After applying the proposed model, the results of the maintenance simulation justified the plant's existing scheduled maintenance policy being reconsidered. Results represent the need for preventive maintenance for all Class A criticality equipment instead of the planned maintenance and the breakdown one for all other equipment depends on its criticality and an FMEA report. Consequently, the additional cost of preventive maintenance would be offset by the cost savings from breakdown maintenance for the remaining equipment.

Keywords: engineering, reliability, strategy, maintenance, failure modes, effects and criticality analysis (FMEA)

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Authors: Moon Moon Devi, Ran Budnik

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The current large area cosmic ray detector surface arrays typically measure only the net flux and arrival-time of the charged particles produced in an extensive air shower (EAS). Measurement of the individual charged particles at a surface array will provide additional distinguishing parameters to identify the primary and to map the very high energy interactions in the upper layers of the atmosphere. In turn, these may probe anomalies in QCD interactions at energies beyond the reach of current accelerators. The recent attempts of studying the individual muon tracks are limited in their expandability to larger arrays and can only probe primary particles with energy up to about 10^15.5 eV. New developments in detector technology allow for a realistic cost of large area detectors, however with limitations on energy resolutions, directional information, and dynamic range. In this study, we perform a simulation study using CORSIKA to combine the energy spectrum and lateral spread of the muons with the longitudinal depth (Xmax) of an EAS initiated by a primary at ultra high energies (10¹⁶ – 10¹⁹) eV. Using proton and iron as the shower primaries, we show that the muon observables and Xmax together can be used to distinguish the primary. This study can be used to design a future detector for the surface array, which will be able to enhance our knowledge of primaries and QCD interactions.

Keywords: ultra high energy extensive air shower, muon tracking, air shower primaries, QCD interactions

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Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

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Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

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Authors: Adeyinka Adeniran, Omowunmi Bakare, Esther Oluwole, Florence Chieme, Temitope Durojaiye, Modupe Akinyinka, Omobola Ojo, Babatunde Olujobi, Marcus Ilesanmi, Akintunde Ogunsakin

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Introduction: Globally, COVID-19 has greatly impacted the human race physically, socially, mentally, and economically. However, healthcare workers seemed to bear the greatest impact. The study, therefore, sought to assess the impact of COVID-19 on the primary healthcare workers in Ekiti, South-west Nigeria. Methods: The study was a cross-sectional descriptive study using a quantitative data collection method of 716 primary healthcare workers in Ekiti state. Respondents were selected using an online convenience sampling method via their social media platforms. Data was collected, collated, and analyzed using SPSS version 25 software and presented as frequency tables, mean and standard deviation. Bivariate and multivariate analyses were conducted using a t-test, and the level of statistical significance was set at p<0.05. Results: Less than half (47.1%) of respondents were between 41-50 age group and a mean age of 44.4+6.4SD. A majority (89.4%) were female, and almost all (96.2%) were married. More than (90%) had ever heard of Coronavirus, and (85.8%) had to spend more money on activities of daily living such as transportation (90.1%), groceries (80.6%), assisting relations (95.8%) and sanitary measures (disinfection) at home (95.0%). COVID-19 had a huge negative impact on about (89.7%) of healthcare workers, with a mean score of 22+4.8. Conclusion: COVID-19 negatively impacted the daily living and professional duties of primary healthcare workers, which reflected their psychological, physical, social, and economic well-being. Disease outbreaks are unlikely to disappear in the near future. Hence, global proactive interventions and homegrown measures should be adopted to protect healthcare workers and save lives.

Keywords: Covid-19, health workforce, primary health care, health systems, depression

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Authors: Hamidreza Joudaki, Yousefali Ziari

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The appearance of city and urbanism is one of the important processes which have affected social communities. Being industrialized urbanism developed along with each other in the history. In addition, they have had simple relationship for more than six thousand years, that is, from the appearance of the first cities. In 18th century by coming out of industrial capitalism, progressive development took place in urbanism in the world. In Iran, the city of each region made its decision by itself and the capital of region (downtown) was the only central part and also the regional city without any hierarchy, controlled its realm. However, this method of ruling during these three decays, because of changing in political, social and economic issues that have caused changes in rural and urban relationship. Moreover, it has changed the variety of performance of cities and systematic urban network in Iran. Today, urban system has very vast imbalanced apace and performance. In Isfahan, the trend of urbanism is like the other part of Iran and systematic urban hierarchy is not suitable and normal. This article is a quantitative and analytical. The statistical communities are Isfahan Province cities and the changes in urban network and its hierarchy during the period of fifty years (1956 -2006) has been surveyed. In addition, those data have been analyzed by model of Rank and size and Entropy index. In this article Iran cities and also the factor of entropy of primate city and urban hierarchy of Isfahan Province have been introduced. Urban residents of this Province have been reached from 55 percent to 83% (2006). As we see the analytical data reflects that there is mismatching and imbalance between cities. Because the entropy index was.91 in 1956.And it decreased to.63 in 2006. Isfahan city is the primate city in the whole of these periods. Moreover, the second and the third cities have population gap with regard to the other cities and finally, they do not follow the system of rank-size.

Keywords: urban network, urban hierarchy, primate city, Isfahan province, urbanism, first cities

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Authors: Mahshid Asadollahi, Mohammad Akbari Asl

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The restaurant industry is highly competitive, and restaurants are constantly looking for ways to attract new customers and retain their existing ones. Nonverbal communication is an important factor in creating a positive customer experience and can play a significant role in attracting customers to restaurants. Nonverbal communication can include body language, facial expressions, tone of voice, and physical proximity, among other things. The present study aimed to investigate the impact of nonverbal communication between restaurant employees and customers on attracting customers in food courts in Tehran. The research method was descriptive-correlational, and the statistical population of this study included all customers of food court restaurants in Tehran, which was about 30 restaurants. The research sample was selected through probability sampling, and 440 customers completed emotional response, customer satisfaction, and nonverbal communication questionnaires in person. The data obtained were analyzed using multiple regression analysis. The results showed that vocal language, employee proximity, physical appearance, and speech movements, as components of nonverbal communication of restaurant employees, had an impact on attracting customers. Additionally, positive and negative emotions of customers have a significant relationship with customer attraction in Food Court restaurants. The study shows that various nonverbal communication factors can play a significant role in attracting customers, and that positive and negative customer emotions can affect customer satisfaction. Therefore, restaurant owners and managers should pay attention to nonverbal communication and train their employees accordingly to create a positive and welcoming atmosphere for customers.

Keywords: verbal language, proximity of employees, physical appearance, speech gestures, nonverbal communication, customer emotions, customer attraction

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Authors: Babak Nemat Shahrbabaki, Arezo Fallahi, Masoomeh Hashemian

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Introduction: Health and safety are basic components of civil right. Health care systems in different countries were influenced by political, economic and cultural circumstances. In order to health services to people, these systems are organized with different forms, methods such as: prevention, treatment and rehabilitation and in this among, public satisfaction with the services provided is important. This study aimed to determine client satisfaction with family physician and relationship with physician’ demographic variables in health care centers of Jiroft county, Iran. Methods: This is a descriptive-analytical study. The collective data tool was a self-made questionnaire with two parts. The first part comprised demographic characteristics, and the second part contained 11 items for the assessment of satisfaction with family physician from different aspects. In addition, questionnaire, reliability and validity were confirmed. Random simple sampling method was used to determine samples. 234 people referred to the health centers filled questionnaire. The data were analyzed using SPSS software, and inferential statistical analysis was performed. Findings: The majority of the study population were women, married, and aged between 18 and 62 years (mean= 30.09±10.71). Total average satisfaction score was 42.63±3.68. Overall satisfaction averages were 9.47% very high, 30.04% high, 33.09% moderate, 15.12% low, and 12.28% very low. Except lodge on of family physician none of physician’ demographic variables did not effect on satisfaction index. Discussion & Conclusion: The Results showed that mean of satisfaction indexes of family physicians was high and lodge on of family physician effected on this index. Informing people about the main goals of family-doctor program will help to promote the quality of program and increase people satisfaction.

Keywords: family physician program, satisfaction, health-care centers, client

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Authors: Hengki Eko Putra, Dennish Ari Putro, Tri Wahyu Hadi, Edi Riawan, Junnaedhi Dewa Gede, Aditia Rojali, Fariza Dian Prasetyo, Yudhistira Satya Pribadi, Dita Fatria Andarini, Mila Khaerunisa, Raditya Hanung Prakoswa

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Catastrophe risk management can only be done if we are able to calculate the exposed risks. Jakarta is an important city economically, socially, and politically and in the same time exposed to severe floods. On the other hand, flood risk calculation is still very limited in the area. This study has calculated the risk of flooding for Jakarta using 2-Dimensional Model ANUGA. 2-Dimensional model ANUGA and 1-Dimensional Model HEC-RAS are used to calculate the risk of flooding from 13 major rivers in Jakarta. ANUGA can simulate physical and dynamical processes between the streamflow against river geometry and land cover to produce a 1-meter resolution inundation map. The value of streamflow as an input for the model obtained from hydrological analysis on rainfall data using hydrologic model HEC-HMS. The probabilistic streamflow derived from probabilistic rainfall using statistical distribution Log-Pearson III, Normal and Gumbel, through compatibility test using Chi Square and Smirnov-Kolmogorov. Flood event on 2007 is used as a comparison to evaluate the accuracy of model output. Property damage estimations were calculated based on flood depth for 1, 5, 10, 25, 50, and 100 years return period against housing value data from the BPS-Statistics Indonesia, Centre for Research and Development of Housing and Settlements, Ministry of Public Work Indonesia. The vulnerability factor was derived from flood insurance claim. Jakarta's flood loss estimation for the return period of 1, 5, 10, 25, 50, and 100 years, respectively are Rp 1.30 t; Rp 16.18 t; Rp 16.85 t; Rp 21.21 t; Rp 24.32 t; and Rp 24.67 t of the total value of building Rp 434.43 t.

Keywords: 2D hydrodynamic model, ANUGA, flood, flood modeling

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Authors: Strahinja Kovačević, Sanja Podunavac-Kuzmanović, Lidija Jevrić, Cristina Prandi, Piermichele Kobauri

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The present study is based on molecular modeling of a series of twelve 5-(4-substituent-phenoxy)-3-methylfuran-2(5H)-one derivatives which have potential of strigolactones mimics toward Striga hermonthica. The first step of the analysis included the calculation of molecular descriptors which numerically describe the structures of the analyzed compounds. The descriptors ALOGP (lipophilicity), AClogS (water solubility) and BBB (blood-brain barrier penetration), served as the input variables in multiple linear regression (MLR) modeling of germination activity toward S. hermonthica. Two MLR models were obtained. The first MLR model contains ALOGP and AClogS descriptors, while the second one is based on these two descriptors plus BBB descriptor. Despite the braking Topliss-Costello rule in the second MLR model, it has much better statistical and cross-validation characteristics than the first one. The ALOGP and AClogS descriptors are often very suitable predictors of the biological activity of many compounds. They are very important descriptors of the biological behavior and availability of a compound in any biological system (i.e. the ability to pass through the cell membranes). BBB descriptor defines the ability of a molecule to pass through the blood-brain barrier. Besides the lipophilicity of a compound, this descriptor carries the information of the molecular bulkiness (its value strongly depends on molecular bulkiness). According to the obtained results of MLR modeling, these three descriptors are considered as very good predictors of germination activity of the analyzed compounds toward S. hermonthica seeds. This article is based upon work from COST Action (FA1206), supported by COST (European Cooperation in Science and Technology).

Keywords: chemometrics, germination activity, molecular modeling, QSAR analysis, strigolactones

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Authors: Enlin Lo, Ioannis Dogaris, George Philippidis

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Succinic acid is a compound used for manufacturing lacquers, resins, and other coating chemicals. It is also used in the food and beverage industry as a flavor additive. It is predominantly manufactured from petrochemicals, but it can also be produced by fermentation of sugars from renewable feedstocks, such as plant biomass. Bio-based succinic acid has great potential in becoming a platform chemical (building block) for commodity and high-value chemicals. In this study, the production of bio-based succinic acid from sweet sorghum was investigated. Sweet sorghum has high fermentable sugar content and can be cultivated in a variety of climates. In order to avoid competition with food feedstocks, its non-edible ‘bagasse’ (the fiber part after extracting the juice) was targeted. Initially, various conditions of pretreating sweet sorghum bagasse (SSB) were studied in an effort to remove most of the non-fermentable components and expose the cellulosic fiber containing the fermentable sugars (glucose). Concentrated (83%) phosphoric acid was utilized at temperatures 50-80 oC for 30-60 min at various SSB loadings (10-15%), coupled with enzymatic hydrolysis using commercial cellulase (Ctec2, Novozymes) enzyme, to identify the conditions that lead to the highest glucose yields for subsequent fermentation to succinic acid. As the pretreatment temperature and duration increased, the bagasse color changed from light brown to dark brown-black, indicating decomposition, which ranged from 15% to 72%, while the theoretical glucose yield is 91%. With Minitab software statistical analysis, a model was built to identify the optimal pretreatment condition for maximum glucose released. The projected theoretical bio-based succinic acid production is 23g per 100g of SSB, which will be confirmed with fermentation experiments using the bacterium Actinobacillus succinogenes.

Keywords: biomass, cellulose, enzymatic hydrolysis, fermentation, pretreatment, succinic acid

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Authors: Milad Mirzaei Aminiyan, Abdolreza Akhgar, Farzad Mirzaei Aminiyan

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Water quality is the critical factor that influence on human health and quantity and quality of grain production in semi-humid and semi-arid area. Pistachio is a main crop that accounts for a considerable portion of Iranian agricultural exports. Give that pistachio tree is a tolerant type of tree to saline and alkaline soil and water conditions, but groundwater and irrigation water quality play important roles in main production this crop. For this purpose, 94 well water samples were taken from 25 wells and samples were analyzed. The results showed give that region’s geological, climatic characteristics, statistical analysis, and based on dominant cations and anions in well water samples (piper diagram); four main types of water were found: Na-Cl, K-Cl, Na-SO4, and K-SO4. It seems that most wells in terms of water quality (salinity and alkalinity) and based on Wilcox diagram have critical status. The analysis suggested that more than eighty-seven percentage of the well water samples have high values of EC that these values are higher than into critical limit EC value for irrigation water, which may be due to the sandy soils in this area. Most groundwater were relatively unsuitable for irrigation but it could be used by application of correct management such as removing and reducing the ion concentrations of Cl‾, SO42‾, Na+ and total hardness in groundwater and also the concentrated deep groundwater was required treatment to reduce the salinity and sodium hazard. Given that irrigation water quality in this area was relatively unsuitable for most agriculture production but pistachio tree was adapted to this area conditions. The integrated management of groundwater for irrigation is the way to solve water quality issues not only in Rafsanjan area, but also in other arid and semi-arid areas.

Keywords: groundwater quality, irrigation water quality, salinity, alkalinity, Rafsanjan plain, pistachio

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Authors: Rumesh Liyanage, S. B. Nawaratne, K. K. D. S. Ranaweera, Indira Wickramasinghe, K. G. S. C. Katukurunda

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Study it was attempted to identify an effect of food habits and publics’ attitudes on micro-sleepiness and preventive measures to develop a food product to combat. Statistical data pertaining to road accidents were collected from, Sri Lanka Police Traffic Division and a pre-tested questionnaire was used to collect data from 250 respondents. They were selected representing drivers (especially highway drivers), private and public sector workers (shift based) and cramming students (university and school). Questionnaires were directed to fill independently and personally and collected data were analyzed statistically. Results revealed that 76.84, 96.39 and 80.93% out of total respondents consumed rice for all three meals which lead to ingesting higher glycemic meals. Taking two hyper glycemic meals before 14.00h was identified as a cause of micro-sleepiness within these respondents. Peak level of road accidents were observed at 14.00 - 20.00h (38.2%)and intensity of micro-sleepiness falls at the same time period (37.36%) while 14.00 to 16.00h was the peak time, 16.00 to 18.00h was the least; again 18.00 to 20.00h it reappears slightly. Even though respondents of the survey expressed that peak hours of micro- sleepiness is 14.00-16.00h, according to police reports, peak hours fall in between 18.00-20.00h. Out of the interviewees, 69.27% strongly wanted to avoid micro-sleepiness and intend to spend LKR 10-20 on a commercial product to combat micro sleepiness. As age-old practices to suppress micro-sleepiness are time taken, modern day respondents (51.64%) like to have a quick solution through a drink. Therefore, food habits of morning and noon may cause for micro- sleepiness while dinner may cause for both, natural and micro-sleepiness due to the heavy glycemic load of food. According to the study micro-sleepiness, can be categorized into three zones such as low-risk zone (08.00-10.00h and 18.00-20.00h), manageable zone (10.00-12.00h), and high- risk zone (14.00-16.00h).

Keywords: food habits, glycemic load, micro-sleepiness, road accidents

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Authors: P. J. Kagosi, M. Mndolwa, E. Japhate

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The study was conducted to communities adjacent MNR, Lushoto district, Tanzania. The MNR is one of the nine nature reserves in the Eastern Arc Mountains of Tanzania with an area of 8,700ha with high biological diversity. However, biodiversity in MNR have been threatened by increasing human activities for livelihood in 1970s. The AF systems in the study area was practised since 1980s however, no study was conducted on AF impacts. This paper presents the influence of AF on livelihood of communities adjacent MNR and biodiversity conservation. Qualitative and quantitative data were collected using socio-economic survey and botanical surveys. Data were analysed using Statistical Packages for Social Sciences and content analysis. The study found that in 1970s free livestock grazing caused considerable surface runoff, soil erosion and reduction of crop production. Since 1980s, the study area received various interventions based on the land conservations and improved livelihood through practising AF systems. It was further found that the AF farming improved crop productivity, reduced soil erosion, increased firewood (80.2%) and other forest products availability and AF encouraged community members practicing indoor livestock keeping.The dominant agroforestry tree found in the study area is grevillea reported by 74.1% of respondents planting an average of 40 trees. The study found that the AF reduced pressure to MNR as forest products and fodders were obtained from community's farms in turn, currently water flow from MNR has been increased. Thus AF products support livelihood needs and conserve biodiversity. The study recommends continuity education on new AF technology packages.

Keywords: impact of agroforestry, biodiversity management, communities’ livelihoods, Magamba nature reserve

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Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

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Authors: Dawei Cai, Yuya Tokuda

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The market of localization based service (LBS) is expanding. The acquisition of physical location is the fundamental basis for LBS. GPS, the de facto standard for outdoor localization, does not work well in indoor environment due to the blocking of signals by walls and ceiling. To acquire high accurate localization in an indoor environment, many techniques have been developed. Triangulation approach is often used for identifying the location, but a heavy and complex computation is necessary to calculate the location of the distances between the object and several source points. This computation is also time and power consumption, and not favorable to a mobile device that needs a long action life with battery. To provide a low power consumption approach for a mobile device, this paper presents a fast calculation approach to identify the location of the object without online solving solutions to simultaneous quadratic equations. In our approach, we divide the location identification into two parts, one is offline, and other is online. In offline mode, we make a mapping process that maps the location area to distance space and find a simple formula that can be used to identify the location of the object online with very light computation. The characteristic of the approach is a good tradeoff between the accuracy and computational amount. Therefore, this approach can be used in smartphone and other mobile devices that need a long work time. To show the performance, some simulation experimental results are provided also in the paper.

Keywords: indoor localization, location based service, triangulation, fast calculation, mobile device

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Authors: Ali Ashraf, Ghazaleh Aghaee, Sedigheh Samimian, Mohaya Farzin

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Objectives: Previous studies have indicated the positive effect of physical activity and sports on different aspects of health, such as muscle endurance and sleep cycle. However, in university students, particularly medical students, who have limited time and a stressful lifestyle, there have been limited studies exploring this matter with proven statistical results. In this regard, this study aims to find out how regular physical activity can influence the academic performance of medical students during their internship period. Methods: This was a descriptive-analytical study. Overall, 160 medical students (including 80 women and 88 men) voluntarily participated in the study. The Baecke Physical Activity Questionnaire was applied to determine the student’s physical activity levels. The student's academic performance was determined based on their total average academic scores. The data were analyzed in SPSS version 16 software using the independent t-test, Pearson correlation, and linear regression. Results: The average age of the students was 26.0±1.5 years. Eighty-eight students (52.4%) were male, and 142 (84.5%) were single. The student's mean total average academic score was 16.2±1.2, and their average physical activity score was 8.3±1.1. The student's average academic score was not associated with their gender (P=0.427), marital status (P=0.645), and age (P=0.320). However, married students had a significantly lower physical activity level compared to single students (P=0.020). The results indicated a significant positive correlation between student's physical activity levels and average academic scores (r=+0.410 and P<0.001). This correlation was independent of the student’s age, gender, and marital status based on the regression analysis. Conclusion: The results of the current study suggested that the physical activity level in medical students was low to moderate in most cases, and there was a significant direct relationship between student’s physical activity level and academic performance, independent of age, gender, and marital status.

Keywords: exercise, education, physical activity, academic performance

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Authors: Sudhanshu Kumar

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Electrical discharge machining, also known as EDM, process is one of the most applicable machining process for removal of material in hard to machine materials like superalloy metals. EDM process utilizes electrical energy into sparks to erode the metals in presence of dielectric medium. In the present investigation, superalloy, Inconel 718 has been selected as workpiece and electrolytic copper as tool electrode. Attempt has been made to understand the effect of size of tool with varying cavity depth during drilling of hole through EDM process. In order to systematic investigate, tool size in terms of tool diameter and cavity depth along with other important electrical parameters namely, peak current, pulse-on time and servo voltage have been varied at three different values and the experiments has been designed using fractional factorial (Taguchi) method. Each experiment has been repeated twice under the same condition in order to understand the variability within the experiments. The effect of variations in parameters has been evaluated in terms of material removal rate, tool wear rate and surface roughness. Results revel that change in tool diameter during machining affects the response characteristics significantly. Larger tool diameter yielded 13% more material removal rate than smaller tool diameter. Analysis of the effect of variation in cavity depth is notable. There is no significant effect of cavity depth on material removal rate, tool wear rate and surface quality. This indicates that number of experiments can be performed to analyze other parameters effect even at smaller depth of cavity which can reduce the cost and time of experiments. Further, statistical analysis has been carried out to identify the interaction effect between parameters.

Keywords: EDM, Inconel 718, material removal rate, roughness, tool wear, tool size

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Authors: Sergio Curilef, Boris Atenas

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Systems with long-range interactions are very common in nature. They are observed from the atomic scale to the astronomical scale and exhibit anomalies, such as inequivalence of ensembles, negative heat capacity, ergodicity breaking, nonequilibrium phase transitions, quasistationary states, and anomalous diffusion. These anomalies are exacerbated when special initial conditions are imposed; in particular, we use the so-called water bag initial conditions that stand for a uniform distribution. Several theoretical and practical implications are discussed here. A potential energy inspired by dipole-dipole interactions is proposed to build the dipole-type Hamiltonian mean-field model. As expected, the dynamics is novel and general to the behavior of systems with long-range interactions, which is obtained through molecular dynamics technique. Two plateaus sequentially emerge before arriving at equilibrium, which are corresponding to two different quasistationary states. The first plateau is a type of quasistationary state the lifetime of which depends on a power law of N and the second plateau seems to be a true quasistationary state as reported in the literature. The general behavior of the model according to its dynamics and thermodynamics is described. Using numerical simulation we characterize the mean kinetic energy, caloric curve, and the diffusion law through the mean square of displacement. The present challenge is to characterize the distributions in phase space. Certainly, the equilibrium state is well characterized by the Gaussian distribution, but quasistationary states in general depart from any Gaussian function.

Keywords: dipole-type interactions, dynamics and thermodynamics, mean field model, quasistationary states

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Authors: Ehsan Asgari, Meisam Afazeli, Nezhla Attarchian

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Post-earthquake fire is considered as a major threat in seismic areas. After an earthquake, fire is possible in structures. In this research, the effect of post-earthquake fire on steel moment frames with and without fireproofing coating is investigated. For this purpose, finite element method is employed. For the verification of finite element results, the results of an experimental study carried out by previous researchers are used, and the predicted FE results are compared with the test results, and good agreement is observed. After ensuring the accuracy of the predictions of finite element models, the effect of post-earthquake fire on the frames is investigated taking into account the parameters including the presence or absence of fire protection, frame design assumptions, earthquake type and different fire scenario. Ordinary fire and post-earthquake fire effect on the frames is also studied. The plastic hinges induced by earthquake in the structure are determined in the beam to the column connection and in panel zone. These areas should be accurately considered when providing fireproofing coatings. The results of the study show that the occurrence of fire beside corner columns is the most damaging scenario that results in progressive collapse of structure. It was also concluded that the behavior of structure in fire after a strong ground motion is significantly different from that in a normal fire.

Keywords: post earthquake fire, moment frame, finite element simulation, coupled temperature-displacement analysis, fire scenario

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Authors: Yves Lacroix, Van Van Than, Didier Léandri, Pierre Liardet

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The western Tombolo of the Giens peninsula in southern France, known as Almanarre beach, is subject to coastal erosion. We are trying to use computer simulation in order to propose solutions to stop this erosion. Our aim was first to determine the main factors for this erosion and successfully apply a coupled hydro-sedimentological numerical model based on observations and measurements that have been performed on the site for decades. We have gathered all available information and data about waves, winds, currents, tides, bathymetry, coastal line, and sediments concerning the site. These have been divided into two sets: one devoted to calibrating a numerical model using Mike 21 software, the other to serve as a reference in order to numerically compare the present situation to what it could be if we implemented different types of underwater constructions. This paper presents the first part of the study: selecting and melting different sources into a coherent data basis, identifying the main erosion factors, and calibrating the coupled software model against the selected reference period. Our results bring calibration of the numerical model with good fitting coefficients. They also show that the winter South-Western storm events conjugated to depressive weather conditions constitute a major factor of erosion, mainly due to wave impact in the northern part of the Almanarre beach. Together, current and wind impact is shown negligible.

Keywords: Almanarre beach, coastal erosion, hydro-sedimentological, numerical model

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