Search results for: experimental results

Authors: Ewa Rak

Abstract:

This paper utilises literature studies and author’s research conducted in small enterprises using survey. The purpose of the study is to identify conditions of employee development in small enterprises. More specifically, it will be barriers to employee development, needs for development expressed by interested employees themselves and the attitude of the company to employee development. Moreover, the enterprises participation in funding and initiating development activities will be presented. Paper presents the results of comparative studies conducted with employees of small enterprises in Poland and Finland in 2015-2016.

Keywords: employee development, Finland, human resources development, Poland, small enterprises

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Authors: Anabel Fernandez, Leandro Rodriguez-Ortiz, Rosa RodríGuez

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Due to the negative impact of fossil fuels, renewable energies are promising sources to limit global temperature rise and damage to the environment. Also, the development of technology is focused on obtaining energetic products from renewable sources. In this study, a thermodynamic model including Exergy balance and a subsequent Life Cycle Assessment (LCA) were carried out for four subsystems of the integrated gasification-combustion of pinewood. Results of exergy analysis and LCA showed the process feasibility in terms of exergy efficiency and global energy efficiency of the life cycle (GEELC). Moreover, the energy return on investment (EROI) index was calculated. The global exergy efficiency resulted in 67 %. For pretreatment, reaction, cleaning, and electric generation subsystems, the results were 85, 59, 87, and 29 %, respectively. Results of LCA indicated that the emissions from the electric generation caused the most damage to the atmosphere, water, and soil. GEELC resulted in 31.09 % for the global process. This result suggested the environmental feasibility of an integrated gasification-combustion system. EROI resulted in 3.15, which determinates the sustainability of the process.

Keywords: exergy analysis, life cycle assessment (LCA), renewability, sustainability

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Authors: Thohidul Islam, Md. Hamidul Haque, Robin Kumar Biswas

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Floods are one of the deadliest natural disasters which are very complex to model; however, machine learning is opening the door for more reliable and accurate flood prediction. In this research, a multilayer perceptron neural network (MLP) is developed to model the rainfall-water level relation, in a subtropical monsoon climatic region of the Bangladesh-India border. Our experiments show promising empirical results to forecast the water level for 1 day lead time. Our best performing MLP model achieves 98.7% coefficient of determination with lower model complexity which surpasses previously reported results on similar forecasting problems.

Keywords: flood forecasting, machine learning, multilayer perceptron network, regression

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Authors: H. S. S Abou El-Mal, A. S. Sherbini, H. E. M. Sallam

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Mode II fracture toughness (KIIc) of fiber reinforced concrete has been widely investigated under various patterns of testing geometries. The effect of fiber type, concrete matrix properties, and testing mechanisms were extensively studied. The area of hybrid fiber addition shows a lake of reported research data. In this paper an experimental investigation of hybrid fiber embedded in high strength concrete matrix is reported. Three different types of fibers; namely steel (S), glass (G), and polypropylene (PP) fibers were mixed together in four hybridization patterns, (S/G), (S/PP), (G/PP), (S/G/PP) with constant cumulative volume fraction (Vf) of 1.5%. The concrete matrix properties were kept the same for all hybrid fiber reinforced concrete patterns. In an attempt to estimate a fairly accepted value of fracture toughness KIIc, four testing geometries and loading types are employed in this investigation. Four point shear, Brazilian notched disc, double notched cube, and double edge notched specimens are investigated in a trial to avoid the limitations and sensitivity of each test regarding geometry, size effect, constraint condition, and the crack length to specimen width ratio a/w. The addition of all hybridization patterns of fiber reduced the compressive strength and increased mode II fracture toughness in pure mode II tests. Mode II fracture toughness of concrete KIIc decreased with the increment of a/w ratio for all concretes and test geometries. Mode II fracture toughness KIIc is found to be sensitive to the hybridization patterns of fiber. The (S/PP) hybridization pattern showed higher values than all other patterns, while the (S/G/PP) showed insignificant enhancement on mode II fracture toughness (KIIc). Four point shear (4PS) test set up reflects the most reliable values of mode II fracture toughness KIIc of concrete. Mode II fracture toughness KIIc of concrete couldn’t be assumed as a real material property.

Keywords: fiber reinforced concrete, Hybrid fiber, Mode II fracture toughness, testing geometry

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Authors: Alhaji Musa Abdullahi, Usman Abdullahi, Adamu Lawan, Aminu Maidala

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Abstract 16 healthy lactating cows will be randomly selected for the trial and will be randomly divided in to 4 groups with 4 cows in each. They will be kept under similar management condition (conventional management system). Animals of relatively same weight and age will be used. After 11days for adaptation, feed intake and performance of the experimental animals will be determine. Milk sample will be collected at each milking in the morning and afternoon to determine; Milk yield, Milk fat percentage, Solid not fat percentage, Total solid percentage of milk. Cows dung will be observe to determine; Score 1 very loose watery stool, Score 2 semi solid with undigested raw material, Score 3 semi solid with less undigested raw material, Score 4 solid with very less undigested raw material, Score 5 good dung no undigested raw material. At the end of the experiment, blood samples will be analyzed for full blood counts and differentials {White Blood Cells (WBC), Red Blood Cells (RBC), Hemoglobin (Hb), Packed Cell Volume (PCV), Mean Corpuscular Volume (MCV), Mean Corpuscular Hemoglobin (MCH), Mean Corpuscular Hemoglobin Concentration (MCHC), Platelets (PLT), Lymphocytes (LYM), Basophils, Eosinophils and Monocytes Proportion (MXD) and Neutrophils (NEUT)} using automated hematology analyzer. Serum samples will be analyzed for heat shock transcription factors, heat shock proteins and hormones (Serum glucocorticoid, prolactin and cortisol). Moreover, biochemical analysis will also be conducted to check for Total protein (TP), Albumen (ALB), Globulin (GBL), Total cholesterol (TCH), glucose (G), sodium (Na+), potassium (K+), chloride (Cl-) and pH. Keywords: Lactating cows, milk composition, dung score and blood parameters.

Keywords: Lactating cows , Milk yield , Dung score , Blood parameters

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Authors: Muneeb Ullah, Daishihan, Xiadong Young

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Deep learning plays a crucial role in identifying COVID-19 and preventing its spread. To improve the accuracy of COVID-19 diagnoses, it is important to have access to a sufficient number of training images of CXRs (chest X-rays) depicting the disease. However, there is currently a shortage of such images. To address this issue, this paper introduces COVID-19 GAN, a model that uses generative adversarial networks (GANs) to generate realistic CXR images of COVID-19, which can be used to train identification models. Initially, a generator model is created that uses digressive channels to generate images of CXR scans for COVID-19. To differentiate between real and fake disease images, an efficient discriminator is developed by combining the dense connectivity strategy and instance normalization. This approach makes use of their feature extraction capabilities on CXR hazy areas. Lastly, the deep regret gradient penalty technique is utilized to ensure stable training of the model. With the use of 4,062 grape leaf disease images, the Leaf GAN model successfully produces 8,124 COVID-19 CXR images. The COVID-19 GAN model produces COVID-19 CXR images that outperform DCGAN and WGAN in terms of the Fréchet inception distance. Experimental findings suggest that the COVID-19 GAN-generated CXR images possess noticeable haziness, offering a promising approach to address the limited training data available for COVID-19 model training. When the dataset was expanded, CNN-based classification models outperformed other models, yielding higher accuracy rates than those of the initial dataset and other augmentation techniques. Among these models, ImagNet exhibited the best recognition accuracy of 99.70% on the testing set. These findings suggest that the proposed augmentation method is a solution to address overfitting issues in disease identification and can enhance identification accuracy effectively.

Keywords: classification, deep learning, medical images, CXR, GAN.

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Authors: Morteza Raei Dehaghi, Seyed Mohammad Mirhashemi

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The current study explored the effect of economic development, financial development and institutional quality on environmental destruction in upper-middle income countries during the time period of 1999-2011. The dependent variable is logarithm of carbon dioxide emissions that can be considered as an index for destruction or quality of the environment given to its effects on the environment. Financial development and institutional development variables as well as some control variables were considered. In order to study cross-sectional correlation among the countries under study, Pesaran and Friz test was used. Since the results of both tests show cross-sectional correlation in the countries under study, seemingly unrelated regression method was utilized for model estimation. The results disclosed that Kuznets’ environmental curve hypothesis is confirmed in upper-middle income countries and also, financial development and institutional quality have a significant effect on environmental quality. The results of this study can be considered by policy makers in countries with different income groups to have access to a growth accompanied by improved environmental quality.

Keywords: economic development, environmental destruction, financial development, institutional development, seemingly unrelated regression

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Authors: Mohammed Kafaji

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This paper aims to investigate the influence of quality of education and quality of research, provided by local educational institutions, on the adoption of Information and Communication Technology (ICT) in managing business operations for companies in Saudi market. A model was developed and tested using data collected from 138 CEO’s of foreign companies in diverse business sectors. The data is analysed and managed using multivariate approaches through standard statistical packages. The results showed that educational quality has little contribution to the ICT adoption while research quality seems to play a more prominent role. These results are analysed in terms of business environment and market constraints and further extended to the perceived effectiveness of applied pedagogical approaches in schools and universities.

Keywords: quality of education, quality of research, mediation, domestic competition, ICT adoption

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Authors: Parker Townes, Aisouda Savadlou, Shoshana Weiss, Marina Jarenova, Suzzane Ferris, Dan Devoe, Russel Schachar, Scott Patten, Tomas Lange, Marlena Colasanto, Holly McGinn, Paul Arnold

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Some research suggests obsessive-compulsive disorder (OCD) is associated with impaired executive functioning: higher-level mental processes involved in carrying out tasks and solving problems. Relevant literature was identified systematically through online databases. Meta-analyses were conducted for task performance metrics reported by at least two articles. Results were synthesized by the executive functioning domain measured through each performance metric. Heterogeneous literature was identified, typically involving few studies using consistent measures. From 29 included studies, analyses were conducted on 33 performance metrics from 12 tasks. Results suggest moderate associations of working memory (two out of five tasks presented significant findings), planning (one out of two tasks presented significant findings), and visuospatial abilities (one out of two tasks presented significant findings) with OCD in youth. There was inadequate literature or contradictory findings for other executive functioning domains. These findings suggest working memory, planning, and visuospatial abilities are impaired in pediatric OCD, with mixed results. More work is needed to identify the effect of age and sex on these results. Acknowledgment: This work was supported by the Alberta Innovates Translational Health Chair in Child and Youth Mental Health. The funders had no role in the design, conducting, writing, or decision to submit this article for publication.

Keywords: obsessive-compulsive disorder, neurocognition, executive functioning, adolescents, children

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Authors: Abbas Al-Refaie

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The research examines the factors that affect customer churn (CC) in the Jordanian telecom industry. A total of 700 surveys were distributed. Cluster analysis revealed three main clusters. Results showed that CC and customer satisfaction (CS) were the key determinants in forming the three clusters. In two clusters, the center values of CC were high, indicating that the customers were loyal and SC was expensive and time- and energy-consuming. Still, the mobile service provider (MSP) should enhance its communication (COM), and value added services (VASs), as well as customer complaint management systems (CCMS). Finally, for the third cluster the center of the CC indicates a poor level of loyalty, which facilitates customers churn to another MSP. The results of this study provide valuable feedback for MSP decision makers regarding approaches to improving their performance and reducing CC.

Keywords: cluster analysis, telecom industry, switching cost, customer churn

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Authors: Chodidjah, Edi Dharmana, Hardhono, Sarjadi

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Breast cancer treatment options including surgery, radiation therapy, chemotherapy, and immunotherapy have not been effective. Besides, they have side effects. Keladi Tikus (Typhonium flagelliforme) has been shown to improve immune system, suppress tumor growth and induce apoptosis. One of the parameters for immune system, tumor growth and apoptosis is IFNγ (Interferon γ), VEGF (Vascular Endothelial Growth Factor) and Caspase 3 respectively. The aim of this study was to examine the effect of the administration of Keladi Tikus tuber extract at the dose of 200 mg/kgBW, 400 mg/KgBW, and 800 mg/kgBW on the level of IFNγ, VEGF and caspase 3 expression. In this experimental study using post test randomized control group design, 24 CH3 mice with tumor were randomly divided into 4 groups including control group and treated groups: Treated with 0.2 cc extract of Keladi Tikus at the dose of 200 mg/kgBW, 400 mg/kgBW, 800 mg/kgBW, respectively for 30 days. On day 31 the lymphatic tissue was taken and evaluated for its level of IFNγ, using ELISA. The tumor tissue was taken and subjected to immunohistochemistry staining for VEGF and caspase 3 expression evaluation. The data on IFNγ, VEGF and Caspase 3 expression were analyzed using One Way Anova with significant level of 0.05. One Way Anova resulted in p<0.05. LSD test showed that the level of IFNγ and Caspase 3 for control group was different from that of treated groups. There was no significant different between the treated group of 400 mg/KgBW and 800mg/KgBW. VEGF expressions for all the treated groups were significant. In conclusion, the oral administration of ethanolic extract of Keladi Tikus (Typhonium flagelliforme) at the dose of 200mg/kgBW, 400 mg/kgBW,800 mg/kgBW increases IFNγ, Caspase 3 and decreases VEGF expression in C3H mice with adenocarsinoma mamma.

Keywords: Typhonium flagelliforme, IFNγ, caspase 3, VEGF

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Authors: Lameck Zetu Khonje, Mulala Danny Simatele

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Malawi’s economy is agriculture based. Recently the government earmarked the tourism sector as an important economic sector which could support the agriculture sector to bring about sustainable economic development and help socioeconomic wellbeing of the local people. Greening of the hotel industry is one of the proven ideal ways of creating a sustainable tourism industry which brings about sustainable economic development in a country like Malawi. This study uses qualitative methodology to examine the efficacy of the governance and policing tools that Malawi uses to guide the development and general practices of the hotel sector to ascertain whether these tools are for greening or not. Grounded Theory method is used whereby semi-structured interviews and field visits were conducted to collect data for the study. The results of the study show that there are loopholes in the governance system in Malawi. The results also reveal gaps within the policing tools such that the hotel industry is not properly guided on green issues. Furthermore, the results show that there is a lack of collaboration for the enforcement of the green practices in the hotel industry. It is also revealed that there is a lack of knowledge of green issues within the governance structures. Awareness campaigns and capacity building would improve greening of the hotel industry in Malawi.

Keywords: governance, greening, Grounded Theory, Malawi

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Authors: John Odo Ogah

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The study investigated ways of fostering students’ interest in senior secondary two Biology, using prior knowledge of behavioural objectives and assertive questioning strategies in Benue State of Nigeria. A quasi-experimental research design was adopted; the population comprised 8,571 senior Secondary two students. The sample consisted of 265 SSII biology students selected from six government schools in the study area using a multi-staged sampling technique. Data was generated using the Biology Interest Inventory (BII). The instrument was validated and subjected to reliability analysis using Cronbach’s Alpha formula, which yielded a coefficient of 0.73. Three research questions guided the study, while three hypotheses were formulated and tested. Data collected were analyzed using means, bar graphs, and standard deviations to answer the research questions, while analysis of covariance (ANCOVA) was employed in testing the hypotheses at 0.05 level of significance. The finding revealed that there is a significant difference in the mean interest ratings of students taught cellular respiration and excretory system using assertive questioning strategy, prior knowledge of behavioural objectives strategy and lecture method (p=0.000˂0.05). There is no significant difference in the mean interest ratings of male and female students taught cellular respiration and excretory systems using an assertive questioning strategy (p=0.790>0.05). There is significant difference in the mean interest ratings of male and female students taught cellular respiration and execratory system using prior knowledge of behavioural objectives strategy (p=0.028˂0.05). It was recommended, among others, that teachers should endeavor to utilize prior knowledge of behavioral objectives strategy in teaching biology in order to harness its benefits as it enhances students’ interest.

Keywords: interest, assertive, questioning, prior, knowledge

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Authors: Jaroslav Krutil, Simona Fialová, , František Pochylý

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A nonlinear mathematical model of mutual fluid-structure interaction is presented in the work. The model is applicable to the general shape of sealing gaps. An in compressible fluid and turbulent flow is assumed. The shaft carries a rotational and procession motion, the gap is axially flowed through. The achieved results of the additional mass, damping and stiffness matrices may be used in the solution of the rotor dynamics. The usage of this mathematical model is expected particularly in hydraulic machines. The method of control volumes in the ANSYS Fluent was used for the simulation. The obtained results of the pressure and velocity fields are used in the mathematical model of additional effects.

Keywords: nonlinear mathematical model, CFD modeling, hydrodynamic sealing gap, matrices of mass, stiffness, damping

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Authors: M.R Asghari Bejestani, Gh. R. Mohammad Khani, V.R. Nafisi

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Imagined speech recognition is one of the most interesting approaches to BCI development and a lot of works have been done in this area. Many different experiments have been designed and hundreds of combinations of feature extraction methods and classifiers have been examined. Reported classification accuracies range from the chance level to more than 90%. Based on non-stationary nature of brain signals, we have introduced 3 classification modes according to time difference in inter and intra-class samples. The modes can explain the diversity of reported results and predict the range of expected classification accuracies from the brain signal accusation procedure. In this paper, a few samples are illustrated by inspecting results of some previous works.

Keywords: brain computer interface, silent talk, imagined speech, classification, signal processing

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Authors: Zubda Zia, Zainab Masood

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This study has investigated the relationship between renewable energy, urbanization, industrialization, and economic growth in Pakistan, through the years 1990-2016. All the three explanatory variables play a pivotal role in their contribution to growth in any economy, especially a developing one such as Pakistan. Auto-regressive distributive lag (ARDL) model has been used to determine the co-integration and relationship between the variables. The empirical results indicate that there exists a positive and significant relationship between all the three variables and economic growth and that there is a stable, long-run relationship among them. Policy suggestions that incorporate the results include having a larger share of renewable energy in the energy sector, using urbanization as a means to remove the big city trend and move towards, smaller sustainable cities, etc.

Keywords: economic growth, energy crisis, industrialization, renewable energy, SGDs, urbanization

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Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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Authors: Morteza Hadi

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This research investigates the potential enhancement of the rollability of Cu-Ge-Ni alloy through the mitigation of microstructural and compositional inhomogeneities via two distinct heat treatment methods: homogenization and solution treatment. To achieve this objective, the alloy with the desired composition was fabricated using a vacuum arc remelting furnace (VAR), followed by sample preparation for microstructural, compositional, and heat treatment analyses at varying temperatures and durations. Characterization was conducted employing optical and scanning electron microscopy (SEM), X-ray diffraction (XRD), and Vickers hardness testing. The results obtained indicate that a minimum duration of 10 hours is necessary for adequate homogenization of the alloy at 750°C. This heat treatment effectively removes coarse dendrites from the casting microstructure and significantly reduces elemental separations. However, despite these improvements, the presence of a second phase with markedly different hardness from the matrix results in poor rolling ability for the alloy. The optimal time for solution treatment at various temperatures was determined, with the most effective cycle identified as 750°C for 2 hours, followed by rapid quenching in water. This process induces the formation of a single-phase microstructure and complete elimination of the second  phase, as confirmed by X-ray diffraction analysis. Results demonstrate a reduction in hardness by 30 Vickers, and the elimination of microstructural unevenness enables successful thickness reduction by up to 50% through rolling without encountering cracking.

Keywords: Cu-Ge-Ni alloy, homogenization. solution treatment, rollability

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Authors: B. Chetti, W. A. Crosby

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The work described in this paper is an investigation of the static and dynamic characteristics of two-lobe journal bearings taking into consideration the thermal effects. A thermo-hydrodynamic solution of a finite two-lobe journal bearing is performed by solving the generalized form Reynolds equation with the energy equation, taking into consideration viscosity variation across the film thickness. The static and dynamic characteristics were numerically obtained. The results are evaluated for different values of viscosity-temperature coefficient and Peclet number. The results show that considering the thermal effects in the solution of the two-lobe journal bearing has a marked on the study of its stability.

Keywords: two-lobe bearing, thermal effect, static, dynamic characteristics

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Authors: Farajallah Adibhashemi

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A retrospective study on causes, surgery findings, results and the follow up of 30 horses with colic in Tehran, Iran. Colic is the main problem horse industry.The causes of colic are related to management like food, sport and medical care. In this study that has been done between 2012-2015 for 30 horses referred to teaching hospital of veterinary medicine faculty of the University of Tehran. Seventy percent of causes was related to management of feeding and twenty percent was for malsporting. The rest of causes was from the anti parasite in bad root. The surgery findings were as follows: 60% displacement of dorsal right and left colon, 20% in impaction of pelvic flexure,10% impaction of the cecum, and 10% impaction of the stomach.

Keywords: horse, colic, Tehran, Iran

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Authors: Aulon Shabani, Denis Panxhi, Orion Zavalani

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This paper presents the modelling and development of a simulator for residential electrical appliances. The simulator is developed on MATLAB providing the possibility to analyze and simulate energy consumption of frequently used home appliances in Albania. Modelling of devices considers the impact of different factors, mentioning occupant behavior and climacteric conditions. Most devices are modeled as an electric circuit, and the electric energy consumption is estimated by the solutions of the guiding differential equations. The provided models refer to devices like a dishwasher, oven, water heater, air conditioners, light bulbs, television, refrigerator water, and pump. The proposed model allows us to simulate beforehand the energetic behavior of the largest consumption home devices to estimate peak consumption and improving its reduction. Simulated home prototype results are compared to real measurement of a considered typical home. Obtained results from simulator framework compared to monitored typical household using EmonTxV3 show the effectiveness of the proposed simulation. This conclusion will help for future simulation of a large group of typical household for a better understanding of peak consumption.

Keywords: electrical appliances, energy management, modelling, peak estimation, simulation, smart home

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Authors: Marianna Maiaru, Gregory M. Odegard

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During the processing of high-performance thermoset polymer matrix composites, chemical reactions occur during elevated pressure and temperature cycles, causing the constituent monomers to crosslink and form a molecular network that gradually can sustain stress. As the crosslinking process progresses, the material naturally experiences a gradual shrinkage due to the increase in covalent bonds in the network. Once the cured composite completes the cure cycle and is brought to room temperature, the thermal expansion mismatch of the fibers and matrix cause additional residual stresses to form. These compounded residual stresses can compromise the reliability of the composite material and affect the composite strength. Composite process modeling is greatly complicated by the multiscale nature of the composite architecture. At the molecular level, the degree of cure controls the local shrinkage and thermal-mechanical properties of the thermoset. At the microscopic level, the local fiber architecture and packing affect the magnitudes and locations of residual stress concentrations. At the macroscopic level, the layup sequence controls the nature of crack initiation and propagation due to residual stresses. The goal of this research is use molecular dynamics (MD) and finite element analysis (FEA) to predict the residual stresses in composite laminates and the corresponding effect on composite failure. MD is used to predict the polymer shrinkage and thermomechanical properties as a function of degree of cure. This information is used as input into FEA to predict the residual stresses on the microscopic level resulting from the complete cure process. Virtual testing is subsequently conducted to predict strength allowables. Experimental characterization is used to validate the modeling.

Keywords: molecular dynamics, finite element analysis, processing modeling, multiscale modeling

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Authors: Vytautas Galvanauskas, Rimvydas Simutis, Donatas Levisauskas, Vykantas Grincas, Renaldas Urniezius

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The paper deals with model-based development and implementation of efficient control strategies for recombinant protein synthesis in fed-batch E.coli cultivation processes. Based on experimental data, a kinetic dynamic model for cultivation process was developed. This model was used to determine substrate feeding strategies during the cultivation. The proposed feeding strategy consists of two phases – biomass growth phase and recombinant protein production phase. In the first process phase, substrate-limited process is recommended when the specific growth rate of biomass is about 90-95% of its maximum value. This ensures reduction of glucose concentration in the medium, improves process repeatability, reduces the development of secondary metabolites and other unwanted by-products. The substrate limitation can be enhanced to satisfy restriction on maximum oxygen transfer rate in the bioreactor and to guarantee necessary dissolved carbon dioxide concentration in culture media. In the recombinant protein production phase, the level of substrate limitation and specific growth rate are selected within the range to enable optimal target protein synthesis rate. To account for complex process dynamics, to efficiently exploit the oxygen transfer capability of the bioreactor, and to maintain the required dissolved oxygen concentration, adaptive control algorithms for dissolved oxygen control have been proposed. The developed model-based control strategies are useful in scale-up of cultivation processes and accelerate implementation of innovative biotechnological processes for industrial applications.

Keywords: adaptive algorithms, model-based control, recombinant E. coli, scale-up of bioprocesses

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Authors: Wipada Chaiwchan, Patcharee Klinhom

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This research is aimed to develop the online-class scheduling management system and improve as a complex problem solution, this must take into consideration in various conditions and factors. In addition to the number of courses, the number of students and a timetable to study, the physical characteristics of each class room and regulations used in the class scheduling must also be taken into consideration. This system is developed to assist management in the class scheduling for convenience and efficiency. It can provide several instructors to schedule simultaneously. Both lecturers and students can check and publish a timetable and other documents associated with the system online immediately. It is developed in a web-based application. PHP is used as a developing tool. The database management system was MySQL. The tool that is used for efficiency testing of the system is questionnaire. The system was evaluated by using a Black-Box testing. The sample was composed of 2 groups: 5 experts and 100 general users. The average and the standard deviation of results from the experts were 3.50 and 0.67. The average and the standard deviation of results from the general users were 3.54 and 0.54. In summary, the results from the research indicated that the satisfaction of users was in a good level. Therefore, this system could be implemented in an actual workplace and satisfy the users’ requirement effectively

Keywords: timetable, schedule, management system, online

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Authors: Valeriu Mihai But, Sorana Daniela Bolboacă, Adriana Elena Bulboacă

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The nutraceutical compound Curcumin (Curcuma longa L.) is known for its anti-inflammatory, anti-cancer, and antioxidant effects. This study aimed to evaluate the antioxidative and analgesic effects of Curcumin (CC) compared to Tramadol (T) in chemical-induced nociceptive pain in rats. Thirty-five rats were randomly divided into five groups of seven rats each and were treated as follows: C group (control group): treated with saline solution 0.9%, (1 ml, i.p. administration), ethanoic acid (EA) group: pretreated with saline solution 0.9% - 30 min before EA nociceptive pain induction, (1 ml, i.p. administration), T group: pretreated with Tramadol, 10 mg/kg body weight (bw), i.p. administration - 30 min before EA nociceptive pain induction, CC1-group: pretreated with 1 mg/100g bw Curcumin i.p. administration - 2 days before EA pain induction and CC2-group: pretreated with Curcumin 2 mg/100g bw i.p. administration - 2 days before EA nociceptive pain induction. The following oxidative stress parameters were assessed: malondialdehyde (MDA), nitric oxide (NOx), total oxidative status (TOS), total antioxidative capacity (TAC), and thiol (Th). The antalgic activity was measured by the ethanoic acid writhing test. Treatment with Curcumin, both 1 mg/100g bw, and 2 mg/100g bw, showed significant differences as compared with the control group (p<0.001) regarding malondialdehyde (MDA), nitric oxide (NOx), and total oxidative status (TOS) oxidative biomarkers. Pretreatment with 2 mg/100g bw of Curcumin presented a significant decrease in MDA values compared with Tramadol (p<0.001). The TAC significantly increased in pretreatment with Curcumin compared with group control. (p<0.001) The nociceptive response to EA was significantly reduced in Curcumin and Tramadol groups. Treatment with Curcumin at a higher concentration was more effective. In an experimental pain model, this study demonstrates an important antioxidant and antinociceptive activity of Curcumin comparable with Tramadol treatment.

Keywords: curcumin, nociception, oxidative stress, pain

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Authors: M. Sandeep Kumar, Vasu Velagapudi, A. Venugopal

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When machining is carried out on a workpiece, residual stresses are induced in the workpiece due to nonuniform thermal and mechanical loads. These stresses play a vital role in the surface integrity of the final product or the output. Inconel 718 is commonly used in critical structural components of aircraft engines due to its properties at high temperatures. Therefore it is important to keep down the stresses induced due to machining. This can be achieved through proper lubricating conditions. In this work, experiments were carried out to check the influence of the developed nanofluid as cutting fluids on residual stresses developed during the course of machining. The results of MQL/Nanofluids were compared with MQL/Vegetable oil and dry machining lubricating condition. Results indicate the reduction in residual stress with the use of MQL/Nanofluid.

Keywords: nanofluids, MQL, residual stress, Inconel-718

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Authors: Mahmud Gungor, Ali Aydin, Erdal Akyol, Suat Tasdelen

Abstract:

The understanding of geotechnical characteristics of near-surface material and the effects of the groundwater is very important problem in such as site studies. For showing the relations between seismic data and groundwater we selected about 25 km2 as the study area. It has been presented which is a detailed work of seismic data and groundwater depths of Gokpinar Damp area. Seismic waves velocity (Vp and Vs) are very important parameters showing the soil properties. The seismic records were used the method of the multichannel analysis of surface waves near area of Gokpinar Damp area. Sixty sites in this area have been investigated with survey lines about 60 m in length. MASW (Multichannel analysis of surface wave) method has been used to generate one-dimensional shear wave velocity profile at locations. These shear wave velocities are used to estimate equivalent shear wave velocity in the study area at every 2 and 5 m intervals up to a depth of 45 m. Levels of equivalent shear wave velocity of soil are used the classified of the study area. After the results of the study, it must be considered as components of urban planning and building design of Gokpinar Damp area, Denizli and the application and use of these results should be required and enforced by municipal authorities.

Keywords: seismic data, Gokpinar Damp, urban planning, Denizli

Procedia PDF Downloads 288

Authors: Azadeh Golshan, Craig Evans, Phillip Geary, Abigail Morrow, Zoe Rogers, Marcel Maeder

Abstract:

22 physicochemical variables have been determined in water samples collected weekly from January to December in 2013 from three sampling stations located within a major drinking water reservoir. Classical Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) analysis was used to investigate the environmental factors associated with the physico-chemical variability of the water samples at each of the sampling stations. Matrix augmentation MCR-ALS (MA-MCR-ALS) was also applied, and the two sets of results were compared for interpretative clarity. Links between these factors, reservoir inflows and catchment land-uses were investigated and interpreted in relation to chemical composition of the water and their resolved geographical distribution profiles. The results suggested that the major factors affecting reservoir water quality were those associated with agricultural runoff, with evidence of influence on algal photosynthesis within the water column. Water quality variability within the reservoir was also found to be strongly linked to physical parameters such as water temperature and the occurrence of thermal stratification. The two methods applied (MCR-ALS and MA-MCR-ALS) led to similar conclusions; however, MA-MCR-ALS appeared to provide results more amenable to interpretation of temporal and geological variation than those obtained through classical MCR-ALS.

Keywords: drinking water reservoir, multivariate analysis, physico-chemical parameters, water quality

Procedia PDF Downloads 291

Authors: Marwa Ben Khalifa, Zeineb Ben Salem, Wissem Frikha

Abstract:

This paper presents a case study of “Radès la Goulette” bridge project using the technique of prefabricated vertical drains (PVD) associated with step by step construction of preloading embankments with averaged height of about 6 m. These embankments are founded on a highly compressible layer of Tunis soft soil. The construction steps included extensive soil instrumentation such as piezometers and settlement plates for monitoring the dissipation of excess pore water pressures and settlement during the consolidation of Tunis soft soil. An axisymmetric numerical model using the 2D finite difference code FLAC was developed and calibrated using laboratory tests to predict the soil behavior and consolidation settlements. The constitutive model impact for simulating the soft soil behavior is investigated. The results of analyses show that numerical analysis provided satisfactory predictions for the field performance during the construction of Radès la Goulette embankment. The obtained results show the effectiveness of PVD in the acceleration of the consolidation time. A comparison of numerical results with theoretical analysis was presented.

Keywords: tunis soft soil, radès bridge project, prefabricated vertical drains, FLAC, acceleration of consolidation

Procedia PDF Downloads 123

Authors: Kishor T. Zingre, Seshadhri Srinivasan

Abstract:

Energy consumption by the building sector is increasing at an alarming rate throughout the world and leading to more building-related CO₂ emissions into the environment. In buildings, the main contributors to energy consumption are heating, ventilation, and air-conditioning (HVAC) systems, lighting, and electrical appliances. It is hypothesised that the energy efficiency in buildings can be achieved by implementing sustainable technologies such as i) enhancing the thermal resistance of fabric materials for reducing heat gain (in hotter climates) and heat loss (in colder climates), ii) enhancing daylight and lighting system, iii) HVAC system and iv) occupant localization. Energy performance of various sustainable technologies is highly dependent on climatic conditions. This paper investigated the use of machine learning techniques for accurate prediction of air-conditioning energy in seasonal climates. The data required to train the machine learning techniques is obtained using the computational simulations performed on a 3-story commercial building using EnergyPlus program plugged-in with OpenStudio and Google SketchUp. The EnergyPlus model was calibrated against experimental measurements of surface temperatures and heat flux prior to employing for the simulations. It has been observed from the simulations that the performance of sustainable fabric materials (for walls, roof, and windows) such as phase change materials, insulation, cool roof, etc. vary with the climate conditions. Various renewable technologies were also used for the building flat roofs in various climates to investigate the potential for electricity generation. It has been observed that the proposed technique overcomes the shortcomings of existing approaches, such as local linearization or over-simplifying assumptions. In addition, the proposed method can be used for real-time estimation of building air-conditioning energy.

Keywords: building energy efficiency, energyplus, machine learning techniques, seasonal climates

Procedia PDF Downloads 114