Search results for: seismic performance

Authors: Rachelle M. Johnson, Jenna E. Finch

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Motivation, persistence, and learning disability status are all associated with academic performance, but to the author's knowledge, little research has been done on how these variables interact with one another and how that interaction looks different within children with and without learning disabilities. The present study's goal was to examine the role motivation and persistence play in the academic success of children with learning disabilities and how these variables interact. Measurements were made using surveys and direct cognitive assessments on each child. Analyses were run on student's scores in motivation, persistence, and ability to learn compared to other fifth grade students. In this study, learning ability was intended as a proxy for learning disabilities (LDs). This study included a nationally representative sample of over 8,000 fifth-grade children from across the United States. Multiple interactions were found among these variables of motivation, persistence, and motivation as they relate to academic achievement. The major finding of the study was the significant role motivation played in academic achievement. This study shows the importance of measuring the within-group. One key finding was that motivation was associated with academic success and was moderated by the other variables. The interaction results were different for math and reading outcomes, suggesting that reading and math success are different and should be addressed differently. This study shows the importance of measuring the within-group differences in levels of motivation to better understand the academic success of children with and without learning disabilities. This study's findings call for further investigation into motivation and the possible need for motivational intervention for students, especially those with learning disabilities

Keywords: academic achievement, learning disabilities, motivation, persistence

Procedia PDF Downloads 121

Authors: Ahmed Moulay, Mariia Zhuldybina, Mirko Torres, Mike Rozel, Ngoc Duc Trinh, Chloé Bois

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Hybrid printed electronics technology (HPE) provides innovative opportunities to enhance conventional electronics applications, which are often based on printed circuit boards (PCB). By combining the best of both performance from conventional electronic components and the flexibility from printed circuits makes it possible to manufacture HPE at high volumes using roll-to-roll printing processes. However, several challenges must be overcome in order to accurately integrate an electronic component on a printed circuit. In this presentation, we will demonstrate the integration process of electronic components from the lab scale to the industrialization. Both the printing quality and the integration technique must be studied to define the optimal conditions. To cover the parameters that influence the print quality of the printed circuit, different printing processes, flexible substrates, and conductive inks will be used to determine the optimized printing process/ink/substrate system. After the systems is selected, an electronic component of 2.5 mm2 chip size will be integrated to validate the functionality of the printed, electronic circuit. Critical information such as the conductive adhesive, the curing conditions, and the chip encapsulation will be determined. Thanks to these preliminary results, we are able to demonstrate the chip integration on a printed circuit using industrial equipment, showing the potential of industrialization, compatible using roll-to-roll printing and integrating processes.

Keywords: flat bed screen-printing, hybrid printed electronics, integration, large-scale production, roll-to-roll printing, rotary screen printing

Procedia PDF Downloads 177

Authors: Mateen Abbas, Abdul Muqeet Khan, Sadia Bashir, Muhammad Awais Khalid, Aamir Ghafoor, Zara Hussain, Mashal Shahid

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The irrational use of insecticides in everyday life has drawn attention worldwide towards its harmful effects. To mitigate the toxic effects of insecticides to humans, present study was planned on the degradation/detoxification of the neonicotinoid insecticides including imidacloprid and acetamiprid. Biocarbon of fruit peels (Banana & Watermelon) and biochar (activated or non-activated) of rice husk was utilized as adsorbents for degradation of selected pesticides. Both activated and non-activated biochar were prepared for treatment and then applied in different concentrations (0.5 to 2.0 ppm) and dosage (1.0 to 2.5g) to insecticides (Acetamiprid & Imidacloprid) as well as studied at different times (30-120 minutes). Reverse Phase-High Performance Liquid Chromatography (RP-HPLC) coupled with Photodiode array detector was used to quantify the insecticides. Results depicted that activated biochar of rice husk minimized the 73% concentrations of both insecticides however, watermelon activated biocarbon degraded 72% of imidacloprid and 56% of acetamiprid. Results proved the efficiency of the method employed and it was also inferred that high concentration of biocarbon resulted in larger percentage of degradation. The applied method is cheaper, easy and accessible that can be used to minimize the pesticide residues in animal feed. Degradation using biochar proved significant degradation, eco-friendly and economic method to reduce toxicity of insecticides.

Keywords: insecticides, acetamiprid, imidacloprid, biochar, HPLC

Procedia PDF Downloads 153

Authors: Umar Bello

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Literature has become an invaluable subject which has added a great value and contribution to the teaching of English language and the discovery of many other developed ideas. Literature produces an exhilarating impulse that imprints a lasting picture on the mind of a learner. Many researchers have devised various means and approaches to language Teaching methods which remain unconvinging and which yield little result, but it has remained unconvincing because it has only produced little results. Devicing a method that eliminates monotony and boredome to learners is a good factor that enhances students’ motivation to learning. In this sense, literature and language become unavoidable components that aid intellectual development. This study examines the indispensability of literature as a means of English Language teaching to secondary school classes. The researcher has developed many instructive activities which are believed will help students to improve their study in grammar and vocabulary. The researcher has used quasi-experimental approach using experimental group and control group to find out how literature enhances the students grammar as well as their vocabulary. The findings revealed a positive performance in the experimental group doing better than the control group using simple percentage. The results make it clear that literature allows learners to pay more attention and develop more interest to their studies. In giving a perspicacious linguistic development, literature therefore remains an essential tool for language teaching classrooms, thereby enhancing their grammatical and vocabulary usage.

Keywords: teaching vocabulary, integration, poetry, classroom

Procedia PDF Downloads 104

Authors: Raja Arslan Ahmad Khan

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Audience feedback and data play an increasingly crucial role, particularly in the digital age. The advent of digital media and the digitalization of news have given rise to novel forms of audience feedback, markedly different from traditional channels. The engagement of online audiences challenges the conventional role of journalists, introducing a dynamic where audiences can wield both direct and indirect influence. This struggle between the audience and journalists is evident in their contributions and interactions. Media professionals are grappling with challenges such as derogatory remarks, hate speech, online harassment, audience hostility, and attacks from online audiences. The influence of online audiences extends to shaping journalists' daily routines and work practices. Consequently, this study seeks to analyze the impact of online audience feedback on journalists at a routine level within the Malaysian context. Employing a Hierarchy of Influence model as a theoretical framework, the study will utilize a quantitative approach with a snowball survey method. The study's findings aim to enhance our understanding of how online audiences influence journalists and their work practices, encompassing aspects like journalists' autonomy and integrity, editorial decision-making, performance and accountability, daily routines, work practices, as well as the psychological and emotional costs they bear. It's important to note that the study has limitations due to the use of the snowball survey method and its focus within the specific context of Malaysia, making it relatively small in scale.

Keywords: online audiences, feedback, influence, journalists, Malaysia

Procedia PDF Downloads 69

Authors: Reza Mohammadzadeh

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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

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Authors: Mamadou Sileye Niang

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The study is a contribution to the development of a feed for juvenile tilapia Oreochromis niloticus, from local raw materials in order to reduce the cost of feeding farmed tilapia in Senegal. Three feeds were formulated from local raw materials. The basic composition of the tested feeds is as follows: A1 (peanut meal, rice bran, millet bran, maize meal and no fish meal); A2 (peanut meal, rice bran, millet bran, maize meal and 10% fish meal) and A3 (peanut meal, rice bran, millet bran, maize meal and 25% fish meal). All feeds contain 31% protein. The trial compared three batches, in 2 replicates, with different diets. The initial weight of the juveniles was 0.37± 0.5g. The daily ration was distributed at 9 am and 4 pm. After 90 days of the experiment, the final mean weights were 2.45 ± 0.5g; 2.75±0.5g; and 4.67 ± 0.5g for A1, A2, and A3, respectively. A performance test, of which the objective was to compare growth parameters, was conducted. The results of the growth parameters of juveniles fed A3 were significantly higher (p < 0.05) than those fed A1 and A2. The weight growth study shows similar growth during the first month. However, from this date onwards, juveniles fed A3 show a faster growth, which is maintained throughout the experiment. On the other hand, the Protein Efficiency Coefficient and the Survival Rate showed no significant difference. The zootechnical parameters are not significantly different (p > 0.05) between the two tanks for the same feed treatment.

Keywords: nutrition, feed, fingerlings, Oreochromis, local raw materials, feed cost

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Authors: Jacky Hau

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The prevalence of emerging technologies disrupts various industries as well as consumer behavior. Data collection has been in the fingertip and inherited through enabled Internet-of-things (IOT) devices. Big data analytics (BDA) becomes possible and allows real-time demand network management (DNM) through leagile supply chain. To enhance further on its resilience and predictability, governance is going to be examined to promote supply chain transparency and trust in an efficient manner. Leagility combines lean thinking and agile techniques in supply chain management. It aims at reducing costs and waste, as well as maintaining responsiveness to any volatile consumer demand by means of adjusting the decoupling point where the product flow changes from push to pull. Leagility would only be successful when collaborative planning, forecasting, and replenishment (CPFR) process or alike is in place throughout the supply chain business entities. Governance and procurement of the supply chain, however, is crucial and challenging for the execution of CPFR as every entity has to walk-the-talk generously for the sake of overall benefits of supply chain performance, not to mention the complexity of exercising the polices at both of within across various supply chain business entities on account of organizational behavior and mutual trust. Empirical survey results showed that the effective timespan on demand forecasting had been drastically shortening in the magnitude of months to weeks planning horizon, thus agility shall come first and preferably following by lean approach in a timely manner.

Keywords: governance, leagility, procure-to-pay, source-to-contract

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Authors: M. Dhana Lakshmi, S. Sakthivel Murugan

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As light passes from source to observer in the water medium, it is scattered by the suspended particulate matter. This scattering effect will plague the captured images with non-uniform illumination, blurring details, halo artefacts, weak edges, etc. To overcome this, pixel normalization with an Amended Unsharp Mask (AUM) filter is proposed to enhance the degraded image. To validate the robustness of the proposed technique irrespective of atmospheric light, the considered datasets are collected on dual locations. For those images, the maxima and minima pixel intensity value is computed and normalized; then the AUM filter is applied to strengthen the blurred edges. Finally, the enhanced image is obtained with good illumination and contrast. Thus, the proposed technique removes the effect of scattering called de-hazing and restores the perceptual information with enhanced edge detail. Both qualitative and quantitative analyses are done on considering the standard non-reference metric called underwater image sharpness measure (UISM), and underwater image quality measure (UIQM) is used to measure color, sharpness, and contrast for both of the location images. It is observed that the proposed technique has shown overwhelming performance compared to other deep-based enhancement networks and traditional techniques in an adaptive manner.

Keywords: underwater drone imagery, pixel normalization, thresholding, masking, unsharp mask filter

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Authors: Khalid S. Hashim, Andy Shaw, Rafid Alkhaddar

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Dissolved oxygen concentration (DO) plays a key role in the electrocoagulation process (EC) as it oxidizes the heavy metals, ammonia, and cyanide into other forms that can be removed easily from water. For instance, the DO oxidises Fe (II) to Fe (III), As (III) to As (V), and cyanide to cyanate and then to ammonia. As well as, removal of nitrogenous compounds accomplishes by the presence of DO. Hence, many of the previous investigations used external aerators to provide the required DO inside EC reactors especially when the water being treated has low DO (such as leachate and highly polluted waters with organic matter); or when the DO depleted during the EC treatment. Although the external aeration process effectively enhances the DO concentration, it has a significant impact on energy consumption. Where, the presence of air bubbles increases the electrical resistance of the EC cell that increase the energy consumption in consequence. Thus, the present project aims to fill this gap by an innovative use of perforated flow columns in the designing of a new EC reactor (ECR1). The new reactor (ECR1) consisted of a Perspex made cylinder container having a controllable working volume of 0.5 to 1 L. It supplied with a flow column that consisted of perorated discoid electrodes that made from aluminium. In order to investigate the performance of ECR1; water samples with a controlled DO concentration were pumped at different flow rates (110, 220, and 440 ml/min) to the ECR1 for 10 min. The obtained results demonstrated that the ECR1 increased the DO concentration from 5.0 to 9.54, 10.53, and 11.0 mg/L which equivalent to 90.8%, 110.6%, and 120% at flow rates of 110, 220, and 440 mL/min respectively.

Keywords: dissolved oxygen, flow column, electrocoagulation, aluminium electrodes

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Authors: Woosuk Lee

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We controlled the electron injection rate in inverted quantum dot light-emitting diode (QLED) by inserting PEIE layer between ZnO electron transport layer(ETL) and quantum dots(QDs) layer and successfully demonstrated high efficiency of QLEDs. The inverted QLED has the layer structure of ITO(cathode)/ ZnO NPs/PEIE/QDs/PEIE/P-TPD/MoO3/Al(anode). The PEIE between poly-TPD hole transport layer (HTL) and quantum dot emitting layer protects QD EML during HTL coating process and improves the surface morphology. In addition, the hole injection barrier is reduced by upshifting the valence band maximum (VBM) of QDs. An additional layer of PEIE was introduced between ZnO and QD to balance charge within QD emissive layer in device, which serves as an effective electron blocking layer without changing device operating condition such as turn-on voltage and emissive spectra. As a result, the optimized QLED with 5nm PEIE shows a ~36% improved current efficiency and external quantum efficiency (EQE) compared to the QLED without PEIE.(maximum current efficiency, and EQE are achieved 70cd/A and 17.3%, respectively). In particular, the maximum brightness of the optimized QLED dramatically improved by a factor of 2.3 relative to the QLED without PEIE. The main reasons for these QLED performance improvement are due to the suppressing the leakage current across the device and well confined exciton by inserting PEIE layers.

Keywords: quantum dot light-emitting diodes, interfacial layer, charge-injection balance, suppressing QD charging

Procedia PDF Downloads 184

Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

Procedia PDF Downloads 330

Authors: Farah Ali, Laeeq Akbar Lodhi, Riaz Hussain, Muhammad Sufyan

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The present study was conducted to determine the macro mineral profile and biomarkers of oxidative stress in Cholistani cattle kept at a public farm and various villages in district Bahawalpur. For this purpose 90 blood samples were collected each from estrual, anestrous and repeat breeding cattle having different age and lactation number. Reproductive tract examination of all the cattle was carried out to determine the reproductive status. Blood samples without EDTA were collected for serum separation at day of estrus (normal cyclic), repeat breeder and anestrous cows. The serum calcium levels were significantly decreased (P<0.05) in anestrous (7.31±0.02 mg/dl) cattle as compared to estrus. However, these values were non-significantly different between repeat breeder and cattle having estrus phase. The concentrations of serum phosphorus were significantly higher (P<0.01) in normal estrual (4.99±0.08 mg/dl) as compared torepeat breeder (3.90±0.06 mg/dl) and anestrous (3.82±0.04 mg/dl) Cholistani cattle. Mean serum MDA (nmol/ml) levels of repeat breeder (2.68±0.18) and anestrous (2.54±0.22) were significantly(P<0.01) higher than the estrous (1.71±0.03) cattle. Moreover, the serum nitric oxide levels(µmol/L) were also increased significantly (P<0.01) in repeat breeder(58.28±4.01)and anestrous (61.40±9.40) than the normalestrous (31.67±6.71) cattle. The ratio of Ca: P in normal cyclic animals was lower (1.73:1) as compared to the anestrous animals (1.92:1). It can be concluded from the present study that the level of Ca: P should also be near to 1.5:1 for better reproductive performance.

Keywords: anestrus, cholistani cattle, minerals, oxidative stress, repeat breeder

Procedia PDF Downloads 606

Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

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This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

Procedia PDF Downloads 128

Authors: Ajai Singh

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Simulation of hydrological processes at the watershed outlet through modelling approach is essential for proper planning and implementation of appropriate soil conservation measures in Damodar Barakar catchment, Hazaribagh, India where soil erosion is a dominant problem. This study quantifies the parametric uncertainty involved in simulation of stream flow using Soil and Water Assessment Tool (SWAT), a watershed scale model and Radial Basis Neural Network (RBNN), an artificial neural network model. Both the models were calibrated and validated based on measured stream flow and quantification of the uncertainty in SWAT model output was assessed using ‘‘Sequential Uncertainty Fitting Algorithm’’ (SUFI-2). Though both the model predicted satisfactorily, but RBNN model performed better than SWAT with R2 and NSE values of 0.92 and 0.92 during training, and 0.71 and 0.70 during validation period, respectively. Comparison of the results of the two models also indicates a wider prediction interval for the results of the SWAT model. The values of P-factor related to each model shows that the percentage of observed stream flow values bracketed by the 95PPU in the RBNN model as 91% is higher than the P-factor in SWAT as 87%. In other words the RBNN model estimates the stream flow values more accurately and with less uncertainty. It could be stated that RBNN model based on simple input could be used for estimation of monthly stream flow, missing data, and testing the accuracy and performance of other models.

Keywords: SWAT, RBNN, SUFI 2, bootstrap technique, stream flow, simulation

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Authors: A. E. Kobryn

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We present both descriptive and predictive modeling of structural properties of blends of PCBM or organic-inorganic hybrid perovskites of the type CH3NH3PbX3 (X=Cl, Br, I) with P3HT, P3BT or squaraine SQ2 dye sensitizer, including adsorption on TiO2 clusters having rutile (110) surface. In our study, we use a methodology that allows computing the microscopic structure of blends on the nanometer scale and getting insight on miscibility of its components at various thermodynamic conditions. The methodology is based on the integral equation theory of molecular liquids in the reference interaction site representation/model (RISM) and uses the universal force field. Input parameters for RISM, such as optimized molecular geometries and charge distribution of interaction sites, are derived with the use of the density functional theory methods. To compare the diffusivity of the PCBM in binary blends with P3HT and P3BT, respectively, the study is complemented with MD simulation. A very good agreement with experiment and the reports of alternative modeling or simulation is observed for PCBM in P3HT system. The performance of P3BT with perovskites, however, seems as expected. The calculated nanoscale morphologies of blends of P3HT, P3BT or SQ2 with perovskites, including adsorption on TiO2, are all new and serve as an instrument in rational design of organic/hybrid photovoltaics. They are used in collaboration with experts who actually make prototypes or devices for practical applications.

Keywords: multiscale theory and modeling, nanoscale morphology, organic-inorganic halide perovskites, three dimensional distribution

Procedia PDF Downloads 156

Authors: El Sayed A. Sharara, A. Tsuji, K. Terada

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Call centers have been expanding and they have influence on activation in various markets increasingly. A call center’s work is known as one of the most demanding and stressful jobs. In this paper, we propose the fatigue detection system in order to detect burnout of call center agents in the case of a neck pain and upper back pain. Our proposed system is based on the computer vision technique combined skin color detection with the Viola-Jones object detector. To recognize the gesture of hand poses caused by stress sign, the YCbCr color space is used to detect the skin color region including face and hand poses around the area related to neck ache and upper back pain. A cascade of clarifiers by Viola-Jones is used for face recognition to extract from the skin color region. The detection of hand poses is given by the evaluation of neck pain and upper back pain by using skin color detection and face recognition method. The system performance is evaluated using two groups of dataset created in the laboratory to simulate call center environment. Our call center agent burnout detection system has been implemented by using a web camera and has been processed by MATLAB. From the experimental results, our system achieved 96.3% for upper back pain detection and 94.2% for neck pain detection.

Keywords: call center agents, fatigue, skin color detection, face recognition

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Authors: Mehdi Bakhtiarzadeh, Reza Efatnejad, Kambiz Rezapour Rezapour

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Due to the limited resources of fossil fuels and their harmful effects on the environment and human health, research on renewable energy applications in industrial and scientific communities has become particularly important. Only one percent of freshwater resources are available for use in the domestic, agricultural, and industrial sectors. On the other hand, the rapid growth of industry and the increase of population in most countries of the world, including Iran, have led to an increase in demand for freshwater. Among renewable energies, there is the potential of solar energy in Iran. As a result, solar distillation systems can be used as a solution to supply fresh water in remote rural areas. Therefore, in the present study, a solar water desalination device was designed and manufactured using two heat exchangers and a photovoltaic system. Its evaluation was done during September and October of 2020. During the evaluation of the device, environmental variables such as total solar radiation, ambient temperature and cooling tower temperature were recorded at intervals of one hour from 9 am to 5 pm. The effect of these variables on solar concentrator performance, heat exchanger, and daily freshwater production was evaluated. The results showed that using two heat exchangers and a photovoltaic system has led to the daily production of 5 liters of fresh water and 46% economic efficiency.

Keywords: solar water desalination, heat exchanger, photovoltaic system, technical and economic evaluation

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Authors: Khalidou Ba, Abdelkrim Chahine, Mohamed Ebn Touhami

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A strong industrial interest is focused on the development of coatings for anticorrosion protection. In this context, phosphate composite materials are expanding strongly due to their chemical characteristics and their interesting physicochemical properties. Sol-gel coatings offer high homogeneity and purity that may lead to obtain coating presenting good adhesion to metal surface. The goal behind this work is to develop efficient coatings for corrosion protection of steel to extend its life. In this context, a sol gel process allowing to obtain thin film coatings on carbon steel with high resistance to corrosion has been developed. The optimization of several experimental parameters such as the hydrolysis time, the temperature, the coating technique, the molar ratio between precursors, the number of layers and the drying mode has been realized in order to obtain a coating showing the best anti-corrosion properties. The effect of these parameters on the microstructure and anticorrosion performance of the films sol gel coating has been investigated using different characterization methods (FTIR, XRD, Raman, XPS, SEM, Profilometer, Salt Spray Test, etc.). An optimized coating presenting good adhesion and very stable anticorrosion properties in salt spray test, which consists of a corrosive attack accelerated by an artificial salt spray consisting of a solution of 5% NaCl, pH neutral, under precise conditions of temperature (35 °C) and pressure has been obtained.

Keywords: sol gel, coating, corrosion, XPS

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Authors: Kwok W. Mui, Ling T. Wong, F. Xiao, Chin T. Cheung, Ho C. Yu

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This study addresses a concept of the Sustainable Building Environmental Model (SBEM) developed to optimize energy consumption in air conditioning and ventilation (ACV) systems without any deterioration of indoor environmental quality (IEQ). The SBEM incorporates two main components: an adaptive comfort temperature control module (ACT) and a new carbon dioxide demand control module (nDCV). These two modules take an innovative approach to maintain satisfaction of the Indoor Environmental Quality (IEQ) with optimum energy consumption, they provide a rational basis of effective control. A total of 2133 sets of measurement data of indoor air temperature (Ta), relative humidity (Rh) and carbon dioxide concentration (CO2) were conducted in some Hong Kong offices to investigate the potential of integrating the SBEM. A simulation was used to evaluate the dynamic performance of the energy and air conditioning system with the integration of the SBEM in an air-conditioned building. It allows us make a clear picture of the control strategies and performed any pre-tuned of controllers before utilized in real systems. With the integration of SBEM, it was able to save up to 12.3% in simulation and 15% in field measurement of overall electricity consumption, and maintain the average carbon dioxide concentration within 1000ppm and occupant dissatisfaction in 20%.

Keywords: sustainable building environmental model (SBEM), adaptive comfort temperature (ACT), new demand control ventilation (nDCV), energy saving

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Authors: Hamed Movahedizadeh, Annuar Md Nassir, Mehdi Karimimalayer, Navid Samimi Sedeh, Ehsan Bagherpour

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The aim of this paper is to evaluate Tehran’s Stock Exchange (TSE) performance regarding with impact of four macroeconomic factors including world crude Oil Price (OP), World Gold Price (GP), Consumer Price Index (CPI) and total Supplied Oil by Iran (SO) from January 2006 to December 2012 that Iran faced with economic and oil sanctions. Iran's exports of crude oil and lease condensate reduced to roughly 1.5 million barrels per day (bbl/d) in 2012, compared to 2.5 million bbl/d in 2011 due to hard sanctions. Monthly data are collected and subjected to a battery of tests through ordinary least square by EViews7. This study found that gold price and oil price are positively correlated with stock returns while total oil supplied and consumer price index have negative relationship with stock index, however, consumer price index tends to become insignificant in stock index. While gold price and consumer price index have short run relationship with TSE index at 10% of significance level this amount for oil price is significant at 5% and there is no significant short run relationship between supplied oil and Tehran stock returns. Moreover, this study found that all macroeconomic factors have long-run relationship with Tehran Stock Exchange Index.

Keywords: consumer price index, gold price, macroeconomic, oil price, sanction, stock market, supplied oil

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Authors: Evy Latifah, Eli Korlina, Hanik Anggraeni, Kuntoro Boga, Joko Mariyono

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During the rainy season, the tomato plants are vulnerable to various diseases. A disease that attacks the leaves of tomato plants (foliar diseases) such as late blight (Phytophtora infestans) and spotting bacteria (bacterial spot / Xanthomonas sp.) In addition, there is a disease that attacks the roots such as fusarium and bacterial wilt. If not immediately anticipated, it will decrease the quality and quantity of crop yields. In fact, it can lead to crop failure. The aim of this research is to know the production of tomato grafting by using Timoty and CLN 3024 tomatoes at rain shelter during rainy season in lowland. Data were analyzed using analysis of variance and tested further by Least Significant Difference (LSD) level of 5 %. The parameters measured were plant height (cm), stem diameter (cm), number of fruit space, canopy extended, number of branches, number of productive branches, and the number of stem segments. The results show at the beginning of growth until the end of the treatment without grafting with relative rain shelter displays the highest plant height. This was followed by extensive crop canopy. For tomato grafting and non-grafting using rain shelter able to produce the number of branches and number of productive branches at most. While at the end of the growth in the number of productive branches generated as much. Highest production of tomatoes produced by tomato dig rafting to use the shelter.

Keywords: field trail, wet and dry season, production, diseases, rain shelter

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Authors: Tarang Varmora, Krupa Shah, Karan Patel

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Environmental pollution and shortage of conventional fuel are the main concerns in the transportation sector. Most of the vehicles use an internal combustion engine (ICE), powered by gasoline fuels. This results into emission of toxic gases. Hybrid electric vehicle (HEV) powered by electric machine and ICE is capable of reducing emission of toxic gases and fuel consumption. However to build HEV, it is required to accommodate motor and batteries in the vehicle along with engine and fuel tank. Thus, overall weight of the vehicle increases. To improve the fuel economy and acceleration, the weight of the HEV can be minimized. In this paper, the design methodology to reduce the weight of the hybrid racing car is proposed. To this end, the chassis design is optimized. Further, attempt is made to obtain the maximum strength with minimum material weight. The best configuration out of the three main configurations such as series, parallel and the dual-mode (series-parallel) is chosen. Moreover, the most suitable type of motor, battery, braking system, steering system and suspension system are identified. The racing car is designed and analyzed in the simulating software. The safety of the vehicle is assured by performing static and dynamic analysis on the chassis frame. From the results, it is observed that, the weight of the racing car is reduced by 11 % without compromising on safety and cost. It is believed that the proposed design and specifications can be implemented practically for manufacturing hybrid racing car.

Keywords: design optimization, hybrid racing car, simulation, vehicle, weight reduction

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Authors: Duong Cong Chinh, Shiao-Shing Chen, Le Quang Huy

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Membrane distillation (MD) is actually claimed to be a cost-effective separation process when waste heat, alternative energy sources, or wastewater are used. To the best of our knowledge, this is the first study that a thermophilic anaerobic granular bioreactor is integrated with membrane distillation (ThAnMDB) was investigated. In this study, the laboratory scale anaerobic bioreactor (1.2 litter) was set-up. The bioreactor was maintained at temperature 55 ± 2°C, hydraulic retention time = 0.5 days, organic loading rates of 7 and 10 kg chemical oxygen demand (COD) m³/day. Side-stream direct contact membrane distillation with the polytetrafluoroethylene membrane area was 150 cm². The temperature of the distillate was kept at 25°C. Results show that distillate flux was 19.6 LMH (Liters per square meter per hour) on the first day and gradually decreased to 6.9 LMH after 10 days, and the membrane was not wet. Notably, by directly using the heat from the thermophilic anaerobic for MD separation process, all distilled water from wastewater was reuse as fresh water (electrical conductivity < 120 µs/cm). The ThAnMDB system showed its high pollutant removal performance: chemical oxygen demand (COD) from 99.6 to 99.9%, NH₄⁺ from 60 to 95%, and PO₄³⁻ complete removal. In addition, methane yield was from 0.28 to 0.34 lit CH₄/gram COD removal (80 – 97% of the theoretical) demonstrated that the ThAnMDB system was quite stable. The achievement of the ThAnMDB is not only in removing pollutants and reusing wastewater but also in absolutely unnecessarily adding alkaline to the anaerobic bioreactor system.

Keywords: high rate anaerobic digestion, membrane distillation, thermophilic anaerobic, wastewater reuse

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Authors: Jin Ho Kim, Yujeong Shin, Seong-Jin Cho, Dong-Jin Kim, U-Syn Ha

Abstract:

Due to the development of the information industry and technologies, cellular phones have must not only function to communicate, but also have functions such as the Internet, e-banking, entertainment, etc. These phones are called smartphones. The performance of smartphones has improved, because of the various functions of smartphones, and the capacity of the battery has been increased gradually. Recently, linear generators have been embedded in smartphones in order to recharge the smartphone's battery. In this study, optimization is performed and an array change of permanent magnets is examined in order to increase efficiency. We propose an optimal design using design of experiments (DOE) to maximize the generated induced voltage. The thickness of the poleshoe and permanent magnet (PM), the height of the poleshoe and PM, and the thickness of the coil are determined to be design variables. We made 25 sampling points using an orthogonal array according to four design variables. We performed electromagnetic finite element analysis to predict the generated induced voltage using the commercial electromagnetic analysis software ANSYS Maxwell. Then, we made an approximate model using the Kriging algorithm, and derived optimal values of the design variables using an evolutionary algorithm. The commercial optimization software PIAnO (Process Integration, Automation, and Optimization) was used with these algorithms. The result of the optimization shows that the generated induced voltage is improved.

Keywords: smartphone, linear generator, design of experiment, approximate model, optimal design

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Authors: Athira Babu, M. Nazeer

Abstract:

Concrete is the most common and versatile construction material used in any type of civil engineering structure. The durability and strength characteristics of concrete make it more desirable among any other construction materials. The manufacture and use of concrete produces wide range of environmental and social consequences. The major component in concrete, cement accounts for roughly 5 % of global CO2 emissions. In order to improve the environmental friendliness of concrete, suitable substitutes are added to concrete. The present study deals with GGBS and silica fume as supplementary cementitious materials. The strength and durability studies were conducted in this ternary blended concrete. Several mixes were adopted with varying percentages of Silica Fume i.e., 5%, 10% and 15%. Binary mix with 50% GGBS was also prepared. GGBS content has been kept constant for the rest of mixes. There is an improvement in compressive strength with addition of Silica Fume.Maximum workability, split tensile strength, modulus of elasticity, flexural strength and impact resistance are obtained for GGBS binary blend. For durability studies, maximum sulphate resistance,carbonation resistance andresistance to chloride ion penetration are obtained for ternary blended concrete. Partial replacement of GGBS and Silica Fume reduces the environmental effects, produces economical and eco-friendly concrete. The study showed that for strength characteristics, binary blended concrete showed better performance while for durability study ternary blend performed better.

Keywords: concrete, GGBS, silica fume, ternary blend

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Authors: Sang-Yoon Lee, Jae-Joon Song

Abstract:

Precast decked bulb-tee girder or precast deck generally adopts in-situ connections of loop joints. Loop joint could be an effective method to connect precast concrete members where the width of joint is not wide sufficiently to allow the lap splice length of reinforcing bars. However, the regulation for the minimum bend diameter of looped rebar gives limitation not to reduce the thickness of precast concrete member; thus, in-situ connection adopting loop joint place a constraint on improving the structural efficiency of precast concrete member. Ultra high strength concrete (UHSC) is effective on reduce the development and lap splice length of reinforcing bar. In-situ connection with UHSC gives a merit to reduce connection width. This study intends to investigate the details of the longitudinal joint to be applied in the precast modular bridge using decked bulb-tee girder that has been recently developed in Korea. This paper presents the details applying UHSC and lap splices of straight reinforcement and results of tests. Several tests were performed on flexural specimens with longitudinal joints to verify the length of the lap splices and amount of transverse reinforcement, and to examine the flexural strength of the longitudinal joint.

Keywords: precast structure, decked bulb-tee girder, in-situ connection, UHSC, modular bridge

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Authors: Naruemon Phongaksorn

Abstract:

The biofuel consumption has increased significantly over the decade resulting in the increasing request on agricultural land for biofuel feedstocks. However, the biofuel feedstocks are already stressed of having low productivity owing to inappropriate agricultural practices without considering suitability of crop land. This research evaluates the land suitability using GIS-integrated Analytic Hierarchy Processing (AHP) of biofuel crops: cassava, at Chachoengsao province, in Thailand. AHP method that has been widely accepted for land use planning. The objective of this study is compared between AHP method and the most limiting group of land characteristics method (classical approach). The reliable results of the land evaluation were tested against the crop performance assessed by the field investigation in 2015. In addition to the socio-economic land suitability, the expected availability of raw materials for biofuel production to meet the local biofuel demand, are also estimated. The results showed that the AHP could classify and map the physical land suitability with 10% higher overall accuracy than the classical approach. The Chachoengsao province showed high and moderate socio-economic land suitability for cassava. Conditions in the Chachoengsao province were also favorable for cassava plantation, as the expected raw material needed to support ethanol production matched that of ethanol plant capacity of this province. The GIS integrated AHP for biofuel crops land suitability evaluation appears to be a practical way of sustainably meeting biofuel production demand.

Keywords: Analytic Hierarchy Processing (AHP), Cassava, Geographic Information Systems, Land suitability

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Authors: Shryas Bhurat, Aryan Vashistha, Sampreet Dinakar Nayak, Ayush Gupta

Abstract:

As the technology is advancing more towards high computational resources, there is a paradigm shift in the usage of these resources to optimize the design process. This paper discusses the usage of ‘Generative Design using Artificial Intelligence’ to build better models that adapt the operations like selection, mutation, and crossover to generate results. The human mind thinks of the simplest approach while designing an object, but the intelligence learns from the past & designs the complex optimized CAD Models. Generative Design takes the boundary conditions and comes up with multiple solutions with iterations to come up with a sturdy design with the most optimal parameter that is given, saving huge amounts of time & resources. The new production techniques that are at our disposal allow us to use additive manufacturing, 3D printing, and other innovative manufacturing techniques to save resources and design artistically engineered CAD Models. Also, this paper discusses the Genetic Algorithm, the Non-Domination technique to choose the right results using biomimicry that has evolved for current habitation for millions of years. The computer uses parametric models to generate newer models using an iterative approach & uses cloud computing to store these iterative designs. The later part of the paper compares the topology optimization technology with Generative Design that is previously being used to generate CAD Models. Finally, this paper shows the performance of algorithms and how these algorithms help in designing resource-efficient models.

Keywords: genetic algorithm, bio mimicry, generative modeling, non-dominant techniques

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Authors: Hameed Rukayat Opeyemi, Pericles Pilidis, Pagone Emanuele

Abstract:

An infinitesimal increase in performance can have immense reduction in operating and capital expenses in a power generation system. Therefore, constant studies are being carried out to improve both conventional and novel power cycles. Globally, power producers are constantly researching on ways to minimize emission and to collectively downsize the total cost rate of power plants. A substantial spurt of developmental technologies of low carbon cycles have been suggested and studied, however they all have their limitations and financial implication. In the area of carbon abatement in power plants, three major objectives conflict: The cost rate of the plant, Power output and Environmental impact. Since, an increase in one of this parameter directly affects the other. This poses a multi-objective problem. It is paramount to be able to discern the point where improving one objective affects the other. Hence, the need for a Pareto-based optimization algorithm. Pareto-based optimization algorithm helps to find those points where improving one objective influences another objective negatively and stops there. The application of Pareto-based optimization algorithm helps the user/operator/designer make an informed decision. This paper sheds more light on areas that multi-objective optimization has been applied in carbon abatement technologies in the last five years, developments and prospects.

Keywords: gas turbine, low carbon technology, pareto optimal, multi-objective optimization

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