Search results for: system performance

Authors: Abdulmajeed Almansour

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Learning a foreign language with the assistant of technological tools has become an interest of learners and educators. Increased use of smartphones among undergraduate students has made them popular for not only social communication but also for entertainment and educational purposes. Smartphones have provided remarkable advantages in language learning process. Learning vocabulary is an important part of learning a language. The use of smartphone applications for English vocabulary learning provides an opportunity for learners to improve vocabulary knowledge beyond the classroom wall anytime anywhere. Recently, various smartphone applications were created specifically for vocabulary learning. This paper aims to explore the use of smartphone application Memrise designed for vocabulary learning to enhance academic vocabulary among undergraduate students. It examines whether the use of a Memrise smartphone application designed course enhances the academic vocabulary learning among ESL learners. The research paradigm used in this paper followed a mixed research model combining quantitative and qualitative research. The study included two hundred undergraduate students randomly assigned to the experimental and controlled group during the first academic year at the Faculty of English Language, Imam University. The research instruments included an attitudinal questionnaire and an English vocabulary pre-test administered to students at the beginning of the semester whereas post-test and semi-structured interviews administered at the end of the semester. The findings of the attitudinal questionnaire revealed a positive attitude towards using smartphones in learning vocabulary. The post-test scores showed a significant difference in the experimental group performance. The results from the semi-structure interviews showed that there were positive attitudes towards Memrise smartphone application. The students found the application enjoyable, convenient and efficient learning tool. From the study, the use of the Memrise application is seen to have long-term and motivational benefits to students. For this reason, there is a need for further research to identify the long-term optimal effects of learning a language using smartphone applications.

Keywords: second language vocabulary learning, academic vocabulary, mobile learning technologies, smartphone applications

Procedia PDF Downloads 146

Authors: Nyaris Pambudiyatno, Asto Buditjahjanto, Eppy Yundra, Arie Wardhono, Eko Hariadi

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Vocational education is part of the national education system that is prepared to produce graduates who have the skills and knowledge according to the needs and requirements required by the job. Vocational Education is a secondary education that prepares students to work in a particular field. The purpose of this study was to analyze and find out the effect of industrial work practice experience and career information on work readiness through work motivation. This type of research is causal research with a quantitative approach. The population in this study was 359 cadets of Aviation Polytechnic Surabaya. While the number of samples calculates using slovin calculations obtained by 189 cadets of Surabaya Aviation Polytechnic. The type of data used is quantitative data with the primary data source. Data collection techniques are by distributing questionnaires. Analysis of this study is with Lisrel. The findings prove that: (1) Industrial Work Experience experience has a positive and significant effect on work motivation; (2) Industrial Work Experience has a positive and significant impact on work readiness; (3) Career information has a positive and significant effect on job readiness; (4) Career information has a positive and significant impact on job readiness; Dan (5) Work motivation has a positive and significant effect on work readiness.

Keywords: career information, increase work readiness, industrial work experience, work motivation

Procedia PDF Downloads 122

Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

Procedia PDF Downloads 391

Authors: Ravi Kumar

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Agricultural wastes are the non-product outcomes of agricultural processing whose monetary value is less as compared to its collection cost, transportation, and processing. When such agricultural waste is not properly disposed of, it may damage the natural environment and cause detrimental pollution in the atmosphere. Agricultural development and intensive farming methods usually result in wastes that remarkably affect the rural environments in particular and the global environment in general. Agricultural waste has toxicity latent to human beings, animals, and plants through various indirect and direct outlets. The present paper explores the various activities that result in agricultural waste and the routes that can utilize the agricultural waste in a manageable manner to reduce its adverse impact on the environment. Presently, the agricultural waste management system for ecological agriculture and sustainable development has emerged as a crucial issue for policymakers. There is an urgent need to consider agricultural wastes as prospective resources rather than undesirable in order to avoid the transmission and contamination of water, land, and air resources. Waste management includes the disposal and treatment of waste with a view to eliminate threats of waste by modifying the waste to condense the microbial load. The study concludes that proper waste utilization and management will facilitate the purification and development of the ecosystem and provide feasible biofuel resources. This proper utilization and management of these wastes for agricultural production may reduce their accumulation and further reduce environmental pollution by improving environmental health.

Keywords: agricultural waste, utilization, management, environment, health

Procedia PDF Downloads 74

Authors: M. Ghosh, A. Miroux, L. A. I. Kestens

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At molecular or micrometre scale, practically all materials are neither homogeneous nor isotropic. The concept of texture is used to identify the structural features that cause the properties of a material to be anisotropic. For metallic materials, the anisotropy of the mechanical behaviour originates from the crystallographic nature of plastic deformation, and is therefore controlled by the crystallographic texture. Anisotropy in mechanical properties often constitutes a disadvantage in the application of materials, as it is often illustrated by the earing phenomena during drawing. However, advantages may also be attained when considering other properties (e.g. optimization of magnetic behaviour to a specific direction) by controlling texture through thermo-mechanical processing). Nevertheless, in order to have better control over the final properties it is essential to relate texture with materials processing route and subsequently optimise their performance. However, up to date, few studies have been reported about the evolution of texture in 6061 aluminium alloy during warm processing (from room temperature to 250ºC). In present investigation, recrystallized 6061 aluminium alloy samples were subjected to tensile and plane strain compression (PSC) at room and warm temperatures. The gradual change of texture following both deformation modes were measured and discussed. Tensile tests demonstrate the mechanism at low strain while PSC does the same at high strain and eventually simulate the condition of rolling. Cube dominated texture of the initial rolled and recrystallized AA6061 sheets were replaced by domination of S and R components after PSC at room temperature, warm temperature (250ºC) though did not reflect any noticeable deviation from room temperature observation. It was also noticed that temperature has no significant effect on the evolution of grain morphology during PSC. The band contrast map revealed that after 30% deformation the substructure inside the grain is mainly made of series of parallel bands. A tendency for decrease of Cube and increase of Goss was noticed after tensile deformation compared to as-received material. Like PSC, texture does not change after deformation at warm temperature though. n-fibre was noticed for all the three textures from Goss to Cube.

Keywords: AA 6061, deformation, temperature, tensile, PSC, texture

Procedia PDF Downloads 472

Authors: Vahid Bayrami Rad

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In this research, common methods and techniques have been investigated with a focus on intelligent fault finding and monitoring systems in the oil industry. In fact, remote and intelligent control methods are considered a necessity for implementing various operations in the oil industry, but benefiting from the knowledge extracted from countless data generated with the help of data mining algorithms. It is a avoid way to speed up the operational process for monitoring and troubleshooting in today's big oil companies. Therefore, by comparing data mining algorithms and checking the efficiency and structure and how these algorithms respond in different conditions, The proposed (Bayesian) algorithm using data clustering and their analysis and data evaluation using a colored Petri net has provided an applicable and dynamic model from the point of view of reliability and response time. Therefore, by using this method, it is possible to achieve a dynamic and consistent model of the remote control system and prevent the occurrence of leakage in oil pipelines and refineries and reduce costs and human and financial errors. Statistical data The data obtained from the evaluation process shows an increase in reliability, availability and high speed compared to other previous methods in this proposed method.

Keywords: wireless sensors, petroleum equipment troubleshooting, Bayesian algorithm, colored Petri net, rapid miner, data mining-reliability

Procedia PDF Downloads 48

Authors: Dimitriya A. Mihaylova, Zlatka V. Valkova-Jarvis, Georgi L. Iliev

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One possible approach for maintaining the security of communication systems relies on Physical Layer Security mechanisms. However, in wireless time division duplex systems, where uplink and downlink channels are reciprocal, the channel estimate procedure is exposed to attacks known as pilot contamination, with the aim of having an enhanced data signal sent to the malicious user. The Shifted 2-N-PSK method involves two random legitimate pilots in the training phase, each of which belongs to a constellation, shifted from the original N-PSK symbols by certain degrees. In this paper, legitimate pilots’ offset values and their influence on the detection capabilities of the Shifted 2-N-PSK method are investigated. As the implementation of the technique depends on the relation between the shift angles rather than their specific values, the optimal interconnection between the two legitimate constellations is investigated. The results show that no regularity exists in the relation between the pilot contamination attacks (PCA) detection probability and the choice of offset values. Therefore, an adversary who aims to obtain the exact offset values can only employ a brute-force attack but the large number of possible combinations for the shifted constellations makes such a type of attack difficult to successfully mount. For this reason, the number of optimal shift value pairs is also studied for both 100% and 98% probabilities of detecting pilot contamination attacks. Although the Shifted 2-N-PSK method has been broadly studied in different signal-to-noise ratio scenarios, in multi-cell systems the interference from the signals in other cells should be also taken into account. Therefore, the inter-cell interference impact on the performance of the method is investigated by means of a large number of simulations. The results show that the detection probability of the Shifted 2-N-PSK decreases inversely to the signal-to-interference-plus-noise ratio.

Keywords: channel estimation, inter-cell interference, pilot contamination attacks, wireless communications

Procedia PDF Downloads 199

Authors: M. Kamil, Rahber Husain Khan

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In the present study, the Interaction of anionic polymer, sodium carboxymethylcellulose (NaCMC), with cationic gemini surfactants 2,2[(oxybis(ethane-1,2-diyl))bis(oxy)]bis(N-hexadecyl1-N,N-[di(E2)/tri(E3)]methyl1-2-oxoethanaminium)chloride (16-E2-16 and 16-E3-16) and conventional surfactant (CTAC) in aqueous solutions have been studied by surface tension measurement of binary mixtures (0.0- 0.5 wt% NaCMC and 1 mM gemini surfactant/10 mM CTAC solution). Surface tension measurements were used to determine critical aggregation concentration (CAC) and critical micelle concentration (CMC). The maximum surface excess concentration (Ґmax) at the air-water interface was evaluated by the Gibbs adsorption equation. The minimum area per surfactant molecule was evaluated, which indicates the surfactant-polymer Interaction in a mixed system. The effect of changing surfactant chain length on CAC and CMC values of mixed polymer-surfactant systems was examined. From the results, it was found that the gemini surfactant interacts strongly with NaCMC as compared to its corresponding monomeric counterpart CTAC. In these systems, electrostatic interactions predominate. The lowering of surface tension with an increase in the concentration of surfactants is higher in the case of gemini surfactants almost 10-15 times. The measurements indicated that the Interaction between NaCMC-CTAC resulted in complex formation. The volume of coacervate increases with an increase in CTAC concentration; however, above 0.1 wt. % concentration coacervate vanishes.

Keywords: anionic polymer, gemni surfactants, tensiometer, CMC, interaction

Procedia PDF Downloads 73

Authors: Sao-Jeng Chao, Wen-Cheng Chen, Wei-Humg Lu

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In order to prevent encountering unpredictable factors, geotechnical engineers always conduct numerical analysis for braced excavation design. Simulation work in advance can predict the response of subsequent excavation and thus will be designed to increase the security coefficient of construction. The parameters that are considered include geological conditions, soil properties, soil distributions, loading types, and the analysis and design methods. National Ilan University is located on the LanYang plain, mainly deposited by clayey soil and loose sand, and thus is vulnerable to external influence displacement. National Ilan University experienced a construction of braced excavation with a complete program of monitoring excavation. This study takes advantage of a one-dimensional finite element method RIDO to simulate the excavation process. The predicted results from numerical simulation analysis are compared with the monitored results of construction to explore the differences between them. Numerical simulation analysis of the excavation process can be used to analyze retaining structures for the purpose of understanding the relationship between the displacement and supporting system. The resulting deformation and stress distribution from the braced excavation cab then be understand in advance. The problems can be prevented prior to the construction process, and thus acquire all the affected important factors during design and construction.

Keywords: excavation, numerical simulation, RIDO, retaining structure

Procedia PDF Downloads 244

Authors: Bliss Singhal

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Epilepsy is a prevalent neurological disorder affecting approximately 50 million individuals worldwide and 1.2 million Americans. There exist millions of pediatric patients with intractable epilepsy, a condition in which seizures fail to come under control. The occurrence of seizures can result in physical injury, disorientation, unconsciousness, and additional symptoms that could impede children's ability to participate in everyday tasks. Predicting seizures can help parents and healthcare providers take precautions, prevent risky situations, and mentally prepare children to minimize anxiety and nervousness associated with the uncertainty of a seizure. This research proposes a comprehensive framework to predict seizures in pediatric patients by evaluating machine learning algorithms on unimodal neuroimaging data consisting of electroencephalogram signals. The bandpass filtering and independent component analysis proved to be effective in reducing the noise and artifacts from the dataset. Various machine learning algorithms’ performance is evaluated on important metrics such as accuracy, precision, specificity, sensitivity, F1 score and MCC. The results show that the deep learning algorithms are more successful in predicting seizures than logistic Regression, and k nearest neighbors. The recurrent neural network (RNN) gave the highest precision and F1 Score, long short-term memory (LSTM) outperformed RNN in accuracy and convolutional neural network (CNN) resulted in the highest Specificity. This research has significant implications for healthcare providers in proactively managing seizure occurrence in pediatric patients, potentially transforming clinical practices, and improving pediatric care.

Keywords: intractable epilepsy, seizure, deep learning, prediction, electroencephalogram channels

Procedia PDF Downloads 69

Authors: J. Omer, H. Haroglu

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Base enlargement in piles was invented to enhance pile resistance in downward loading, but the contribution of an enlarged base to the lateral load resistance of a pile has not been fully exploited or understood. This paper presents a laboratory investigation of the lateral capacity and deformation response of small-scale steel piles with enlarged bases installed in dry sand. Static loading tests were performed on 24 model piles having different base-to-shaft diameter ratios. The piles were installed in a box filled with dry sand, and lateral loads were applied to the pile tops using a pulley system. The test piles had shaft diameters of 20 mm, 16 mm, and 10 mm; base diameters of 900 mm, 700 mm, and 500 mm. As a control, a pile without base enlargement was tested to allow comparisons with the enlarged base piles. Incremental maintained loads were applied until pile failure approached while recording pile head deflections with high-precision dial gauges. The results showed that the lateral capacity increased with an increase in base diameter, albeit by different percentages depending on the shaft diameters and embedment length in the sand. There was always an increase in lateral capacity with increasing embedment length. Also, it was observed that an enlarged pile base had deflected less at a given load when compared to the control pile. Therefore, the research demonstrated the benefits of lateral capacity and stability of enlarging a pile base.

Keywords: pile foundations, enlarged base, lateral loading

Procedia PDF Downloads 124

Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

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Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

Procedia PDF Downloads 227

Authors: Rosemary Anibogwu, Kavita Sharma, Karl De Jesus

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Sagebrush is an abundant and naturally occurring plant in the Intermountain West region of the United States. The plant contains an array of bioactive compounds such as flavonoids, terpenoids, sterols, and phenolic acids. It is important to identify and characterize these compounds because Native Americans use sagebrush as herbal medicine. These compounds are also utilized for preventing infection in wounds, treating headaches and colds, and possess antitumor properties. This research is an exploratory study on the sesquiterpene present in the leaves of sagebrush. The leaf foliage was extracted with 100 % chloroform and 100 % methanol. The percentage yield for the crude was considerably higher in chloroform. The Thin Layer Chromatography (TLC) analysis of the crude extracted unveiled a brown band at Rf = 0.25 and a dark brown band at Rf = 0.74, along with three unknown faint bands the 254 nm UV lamp. Furthermore, the two distinct brown (Achillin) and dark brown band (Hydroxyachillin) in TLC were further utilized in the isolation of pure compounds with column chromatography. The structures of Achillin and Hydroxyachillin were elucidated based on extensive spectroscopic analysis, including TLC, High-Performance Liquid Chromatography (HPLC), 1D- and 2D-Nuclear Magnetic Resonance (NMR), and Mass Spectroscopy (MS). The antioxidant activities of crude extract and three pure compounds were evaluated in terms of their peroxyl radical scavenging by Ferric Reducing Ability of Plasma (FRAP) and 1,1-Diphenyl-2-picryl-hydrazyl (DPPH) methods. The crude extract showed the antioxidant activity of 18.99 ± 0.51 µmol TEg -1 FW for FRAP and 11.59 ± 0.38 µmol TEg -1 FW for DPPH. The activities of Achillin, Hydroxyachillin, and Quercetagetin trimethyl ether were 13.03, 15.90 and 14.02 µmol TEg -1 FW respectively for the FRAP assay. The three purified compounds have been submitted to the National Cancer Institute 60 cancer cell line for further study.

Keywords: HPLC, nuclear magnetic resonance spectroscopy, sagebrush, sesquiterpene lactones

Procedia PDF Downloads 111

Authors: Bhavini Patel, Aslihan Ugun-Klusek, Ellen Billet

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The two main contributing factors to familial and idiopathic form of Parkinson’s disease (PD) are oxidative stress and altered proteolysis. Monoamine oxidase-A (MAO-A) plays a significant role in redox homeostasis by producing reactive oxygen species (ROS) via deamination of for example, dopamine. The ROS generated induces chemical modification of proteins resulting in altered biological function. The ubiquitin-proteasome system, which consists of three different types or proteolytic activity, namely “chymotrypsin-like” activity (CLA), “trypsin-like” activity (TLA) and “post acidic-like” activity (PLA), is responsible for the degradation of ubiquitinated proteins. Defects in UPS are known to be strongly correlated to PD. Herein, the effect of ROS generated by MAO-A on proteasome activity and the effects of proteasome inhibition on MAO-A protein levels in WT, mock and MAO-A overexpressed (MAO-A+) SHSY5Y neuroblastoma cell lines were investigated. The data in this study report increased proteolytic activity when MAO-A protein levels are significantly increased, in particular CLA and PLA. Additionally, 20S proteasome inhibition induced a decrease in MAO-A levels in WT and mock cells in comparison to MAO-A+ cells in which 20S proteasome inhibition induced increased MAO-A levels to be further increased at 48 hours of inhibition. This study supports the fact that MAO-A could be a potential pharmaceutical target for neuronal protection as data suggests that endogenous MAO-A levels may be essential for modulating cell death and survival.

Keywords: monoamine oxidase, neurodegeneration, Parkinson's disease, proteasome

Procedia PDF Downloads 116

Authors: Samuel Quashie

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Ph.D. Construction Management methodology and mixed methods are organized to guide the researcher to assemble and assess data in the research activities. Construction management research is close to business management and social science research. It also contributes to researching the phenomenon and answering the research question, generating an integrated management system for post-disaster reconstruction in construction and related industries. Research methodology and methods drive the research to achieve the goal or goals, contribute to knowledge, or increase knowledge. This statement means the research methodology, mixed methods, aim, objectives, and processes address the research question, facilitate its achievement and foundation to conduct the study. Mixed methods use project-based case studies, interviews, observations, literature and archival document reviews, research questionnaires, and surveys, and evaluation of integrated systems used in the construction industry and related industries to address the research work. The research mixed methods (qualitative, quantitative) define the research topic and establish a more in-depth study. The research methodology is action research, which involves the collaboration of participants and service users to collect and evaluate data, studying the phenomenon, research question(s) to improve the situation in post-disaster reconstruction phase management.

Keywords: methodology, Ph.D. research, post-disaster reconstruction, mixed-methods qualitative and quantitative

Procedia PDF Downloads 210

Authors: Sue Lynn Kim, Sang-Gyun Lee, Joan P. Yoo

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Although adolescents in low socioeconomic status (SES) have been reported to less engage in health promoting behaviors (HPB), the specific mechanism between their SES and HPB has not been extensively studied. Considering the Korean education system which focuses only on college entrance exams while lacking of interest in students’ health, and unique traits of adolescents, such as ego-centric thinking, family members can significantly contribute to develop and enhance adolescents’ HPB. Based on the review of related literature and previous researches, this study examined the mediating effect of family-based activities on the relationship between SES and adolescents' HPB. 636 adolescents (4th graders in elementary and 1st graders in middle school) and their parents from the 1st year survey of Seoul Education & Health Welfare Panel were analyzed by AMOS 19.0 utilizing structural equation modeling. Analytic results show that adolescents in low SES were less likely to engage in family-based activities as well as HPB. This association between SES and HPB was partially mediated by family-based activities. Based on the findings, we suggest that special education programs to enhance HPB should be required in schools and community organizations especially for adolescents in low SES who may have difficulties in doing family-based activities due to parents’ low income and insufficient leisure time. In addition, family-based activities should be encouraged to enhance HPB by raising parents' awareness about the importance of family-based activities on their children's HPB.

Keywords: family-based activity, health promoting behaviors, socioeconomic status, HPB

Procedia PDF Downloads 365

Authors: A. F. Agboola, B. R. O. Omidiwura, A. Oyeyemi, E. A. Iyayi, A. S. Adelani

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Dietary cholesterol has elicited the most public interest as it relates with coronary heart disease. Thus, humans have been paying more attention to health, thereby reducing consumption of cholesterol enriched food. Egg is considered as one of the major sources of human dietary cholesterol. However, an alternative way to reduce the potential cholesterolemic effect of eggs is to modify the fatty acid composition of the yolk. The effect of palm oil (PO), soybean oil (SO), sesame seed oil (SSO) and fish oil (FO) supplementation in the diets of layers on egg yolk fatty acid, cholesterol, egg production and egg quality parameters were evaluated in a 42-day feeding trial. One hundred and five Isa Brown laying hens of 34 weeks of age were randomly distributed into seven groups of five replicates and three birds per replicate in a completely randomized design. Seven corn-soybean basal diets (BD) were formulated: BD+No oil (T1), BD+1.5% PO (T2), BD+1.5% SO (T3), BD+1.5% SSO (T4), BD+1.5% FO (T5), BD+0.75% SO+0.75% FO (T6) and BD+0.75% SSO+0.75% FO (T7). Five eggs were randomly sampled at day 42 from each replicate to assay for the cholesterol, fatty acid profile of egg yolk and egg quality assessment. Results showed that there were no significant (P>0.05) differences observed in production performance, egg cholesterol and egg quality parameters except for yolk height, albumen height, yolk index, egg shape index, haugh unit, and yolk colour. There were no significant differences (P>0.05) observed in total cholesterol, high density lipoprotein and low density lipoprotein levels of egg yolk across the treatments. However, diets had effect (P<0.05) on TAG (triacylglycerol) and VLDL (very low density lipoprotein) of the egg yolk. The highest TAG (603.78 mg/dl) and VLDL values (120.76 mg/dl) were recorded in eggs of hens on T4 (1.5% sesame seed oil) and was similar to those on T3 (1.5% soybean oil), T5 (1.5% fish oil) and T6 (0.75% soybean oil + 0.75% fish oil). However, results revealed a significant (P<0.05) variations on eggs’ summation of polyunsaturated fatty acid (PUFA). In conclusion, it is suggested that dietary oils could be included in layers’ diets to produce designer eggs low in cholesterol and high in PUFA especially omega-3 fatty acids.

Keywords: dietary oils, egg cholesterol, egg fatty acid profile, egg quality parameters

Procedia PDF Downloads 293

Authors: Ulriikka Savela-Huovinen, Hanni Muukkonen, Auli Toom

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The development of workplace as a learning environment has been emphasized in research field of workplace learning. The prior literature on sensory performance emphasized the individual’s competences as assessor, while the competences in the collaborative interactional and knowledge creation practices as workplace learning method are not often mentioned. In the present study aims to find out what kinds of competences and contexts are central when assessor conducts food sensory evaluation in authentic professional context. The aim was to answer the following questions: first, what kinds of competences does sensory evaluation require according to assessors? And second, what kinds of contexts for sensory evaluation do assessors report? Altogether thirteen assessors from three Finnish food companies were interviewed by using semi-structural thematic interviews to map practices and development intentions as well as to explicate already established practices. The qualitative data were analyzed by following the principles of abductive and inductive content analysis. Analysis phases were combined and their results were considered together as a cross-analysis. When evaluated independently required competences were perception, knowledge of specific domains and methods and cognitive skills e.g. memory. Altogether, 42% of analysis units described individual evaluation contexts, 53% of analysis units described collaborative interactional contexts, and 5% of analysis units described collaborative knowledge creation contexts. Related to collaboration, analysis reviewed learning, sharing and reviewing both external and in-house consumer feedback, developing methods to moderate small-panel evaluation and developing product vocabulary collectively between the assessors. Knowledge creation contexts individualized from daily practices especially in cases product defects were sought and discussed. The study findings contribute to the explanation that sensory assessors learn extensively from one another in the collaborative interactional and knowledge creation context. Assessors learning and abilities to work collaboratively in the interactional and knowledge creation contexts need to be ensured in the development of the expertise.

Keywords: assessor, collaboration, competences, contexts, learning and practices, sensory evaluation

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Authors: Tina Melkoshvili

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Drastic development of information and communication technologies in Georgia has led to the necessity of launching conceptually new, effective, flexible, transparent and society oriented form of government that is e-government. Through applying information technologies, the electronic system enables to raise the efficacy of state governance and increase citizens’ participation in the process. Focusing on the topic of e-government allows us to analyze success stories, attributed benefits and, at the same time, observes challenges hampering the government development process. There are number of methodologies elaborated to study the conditions in the field of electronic governance. They enable us to find out if the government is ready to apply broad opportunities of information and communication technologies and if the government is apt to improve the accessibility and quality of delivering mainly social services. This article seeks to provide comparative analysis of widely spread methodologies used for Electronic government projects’ assessment. It has been concluded that applying current methods of assessment in Georgia is related to difficulties due to inaccessible data and the necessity of involving number of experts. The article presents new indicators for e-government development assessment that reflect efficacy of e-government conception realization in the regions of Georgia and enables to provide quantitative evaluation of regional e-government projects including all significant aspects of development.

Keywords: development methodology, e-government in Georgia, information and communication technologies, regional government

Procedia PDF Downloads 257

Authors: Moet Moet Myint lay

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Professional learning communities provide ongoing professional development for teachers, where they become learning leaders and actively participate in school improvement. The development of professional knowledge requires a significant focus on professional competence in the work of teachers, and a solid foundation of professional knowledge and skills is necessary for members of society to become intelligent members. Continuing professional development (CPD) plays a vital role in improving educational outcomes, as its importance has been proven over the years. This article explores the need for CPD for teachers in Myanmar and the utility of professional learning communities in improving teacher quality. This study aims to explore a comprehensive understanding of professional learning communities to support the continuing professional development of teacher educators in improving the quality of education. The research questions are: (1) How do teacher educators in Myanmar understand the concept of professional learning communities for continuing professional development? (2) What CPD training is required for all teachers in teachers' colleges? Quantitative research methods were used in this study. Survey data were collected from 50 participants (teacher trainers) from five educational institutions. The analysis shows that professional learning communities when done well, can have a lasting impact on teacher quality. Furthermore, the creation of professional learning communities is the best indicator of professional development in existing education systems. Some research suggests that teacher professional development is closely related to teacher professional skills and school improvement. As a result of the collective learning process, teachers gain a deeper understanding of the subject matter, increase their knowledge, and develop their professional teaching skills. This will help improve student performance and school quality in the future. The lack of clear understanding and knowledge about PLC among school leaders and leads teachers to believe that PLC activities are not beneficial. Lack of time, teacher accountability, leadership skills, and negative attitudes of participating teachers were the most frequently cited challenges in implementing PLCs. As a result of these findings, educators and stakeholders can use them to implement professional learning communities.

Keywords: professional learning communities, continuing professional development, teacher education, competence, school improvement

Procedia PDF Downloads 38

Authors: Berat Krasniqi, Shpëtim Thaçi, Miribane Dërmaku-Sopjani, Sokol Abazi, Mentor Sopjani

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The Mediterranean native plant, Sideritis raeseri Boiss. & Heldr. (Lamiaceae), also known as "mountain tea," has a long history of use in traditional medicine. The effects of an ethanol extract of Sideritis raeseri (SR) on uterus smooth muscle activity are evaluated in this study, and the underlying mechanism is identified. S. raeseri extract (SRE) was made from air-dried components of the SR shoot system. At 37°C, the SRE (0.5-2 mg/mL) was tested on isolated rabbit uterus rings that were suspended in a Krebs solution-filled organ bath and bubbled with a mixture of 95% O₂ and 5% CO₂. The SRE alone relaxed the muscle contraction in a concentration-dependent manner in uterine rings in in vitro tests. SRE also decreased Ca²⁺-induced contractions in the uterus by a large amount when the uterus was depolarized with carbachol (CCh, 1µM), K⁺ (80 mM), or contracted by oxytocin (5 nM). The potential involvement of NO-dependent or independent cGMP mechanisms in the uterine actions of SR was investigated. For this purpose, L-NAME (NO synthase inhibitor, 100 M) or bradykinin (NO synthase stimulator, 100 nM), or indomethacin (cyclooxygenase inhibitor, 10µM) decreased the impact of SRE. These results suggest that NO-dependent signaling is involved in SRE's mediated uterine relaxant effect. Data suggests that SRE could be a powerful tocolytic agent that reduces uterine activity and could be used to treat a number of uterine conditions.

Keywords: Sideritis raeseri, uterus, alternative medicine, intracellular mechanisms

Procedia PDF Downloads 99

Authors: Mohsin Ejaz, Shiao-Wei Kuo

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The growing production and exploitation of fossil fuels have placed human society in serious environmental issues. As a result, it's critical to design efficient and eco-friendly energy production and storage techniques. Porous organic polymers (POPs) are multi-dimensional porous network materials developed through the formation of covalent bonds between different organic building blocks that possess distinct geometries and topologies. POPs have tunable porosities and high surface area making them a good candidate for an effective electrode material in energy storage applications. Herein, we prepared a fully benzoxazine-based porous organic polymers (TPA–DHTP–BZ POP) through sonogashira coupling of dihydroxyterephthalaldehyde (DHPT) and triphenylamine (TPA) containing benzoxazine (BZ) monomers. Firstly, both BZ monomers (TPA-BZ-Br and DHTP-BZ-Ea) were synthesized by three steps, including Schiff base, reduction, and mannich condensation reaction. Finally, the TPA–DHTP–BZ POP was prepared through the sonogashira coupling reaction of brominated monomer (TPA-BZ-Br) and ethynyl monomer (DHTP-BZ-Ea). Fourier transform infrared (FTIR) and solid-state nuclear magnetic resonance (NMR) spectroscopy confirmed the successful synthesis of monomers as well as POP. The porosity of TPA–DHTP–BZ POP was investigated by the N₂ absorption technique and showed a Brunauer–Emmett–Teller (BET) surface area of 196 m² g−¹, pore size 2.13 nm and pore volume of 0.54 cm³ g−¹, respectively. The TPA–DHTP–BZ POP experienced thermal ring-opening polymerization, resulting in poly (TPA–DHTP–BZ) POP having strong inter and intramolecular hydrogen bonds formed by phenolic groups and Mannich bridges, thereby enhancing CO₂ capture and supercapacitive performance. The poly(TPA–DHTP–BZ) POP demonstrated a remarkable CO₂ capture of 3.28 mmol g−¹ and a specific capacitance of 67 F g−¹ at 0.5 A g−¹. Thus, poly(TPA–DHTP–BZ) POP could potentially be used for energy storage and CO₂ capture applications.

Keywords: porous organic polymer, benzoxazine, sonogashira coupling, CO₂, supercapacitor

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Authors: Ashok Kalagura

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This paper presents a data-mining model for fault-zone identification of flexible AC transmission systems (FACTS)-based transmission line including a thyristor-controlled series compensator (TCSC) and unified power-flow controller (UPFC), using ensemble decision trees. Given the randomness in the ensemble of decision trees stacked inside the random forests model, it provides an effective decision on the fault-zone identification. Half-cycle post-fault current and voltage samples from the fault inception are used as an input vector against target output ‘1’ for the fault after TCSC/UPFC and ‘1’ for the fault before TCSC/UPFC for fault-zone identification. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network, including noisy environment providing a reliability measure of 99% with faster response time (3/4th cycle from fault inception). The results of the presented approach using the RF model indicate the reliable identification of the fault zone in FACTS-based transmission lines.

Keywords: distance relaying, fault-zone identification, random forests, RFs, support vector machine, SVM, thyristor-controlled series compensator, TCSC, unified power-flow controller, UPFC

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Authors: I. A. Landa-Fernandez, I. Monje-Ramirez, M. T. Orta-Ledesma

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Every year plant-parasitic nematodes diminish the yield of high-value crops worldwide causing important economic losses. Currently, Meloidogyne enterolobii has increased its importance due to its high aggressiveness, increasing geographical distribution and host range. Root-knot nematodes inhabit the rhizosphere soil around plant roots. However, they can come into contact with irrigation water. Thus, plant-parasitic nematodes can be transported by water, as eggs or juveniles. Due to their high resistance, common water disinfection methods are not effective for inactivating these parasites. Ozone is the most effective disinfectant for microbial inactivation. The objective of this study is to demonstrate that ozone treatment is an alternative method control in irrigation water of the root-knot nematode M. enterolobii. It has been shown that ozonation is an effective treatment for the inactivation of protozoan cysts and oocysts (Giardia and Cryptosporidium) and for other species of the genus Meloidogyne (M. incognita), but not for the enterolobii specie. In this study, the strain of M. enterolobii was isolated from tomatoes roots. For the tests, eggs were used and were inoculated in water with similar characteristics of irrigation water. Subsequently, the disinfection process was carried out in an ozonation unit. The performance of the treatments was evaluated through the egg's viability by assessing its structure by optical microscopy. As a result of exposure to ozone, the viability of the nematode eggs was reduced practically in its entirety; with dissolved ozone levels in water close to the standard concentration (equal to 0.4 mgO₃/L), but with high contact times (greater than 4 min): 0.2 mgO₃/L for 15 minutes or 0.55 mgO₃/L for 10 minutes. Additionally, the effect of temperature, alkalinity and organic matter of the water was evaluated. Ozonation is effective and a promising alternative for the inactivation of nematodes in irrigation water, which could contribute to diminish the agricultural losses caused by these organisms.

Keywords: inactivation process, irrigation water treatment, ozonation, plant-parasite nematodes

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Authors: S. Chandrasekaran, P. A. Kiran

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Increasing demand for large-sized Floating, Storage and Regasification Units (FSRUs) for oil and gas industries led to the development of novel geometric form of Buoyant Leg Storage and Regasification Platform (BLSRP). BLSRP consists of a circular deck supported by six buoyant legs placed symmetrically with respect to wave direction. Circular deck is connected to buoyant legs using hinged joints, which restrain transfer of rotational response from the legs to deck and vice-versa. Buoyant legs are connected to seabed using taut moored system with high initial pretension, enabling rigid body motion in vertical plane. Encountered environmental loads induce dynamic tether tension variations, which in turn affect stability of the platform. The present study investigates Mathieu stability of BLSRP under the postulated tether pullout cases by inducing additional tension in the tethers. From the numerical studies carried out, it is seen that postulated tether pullout on any one of the buoyant legs does not result in Mathieu type instability even under excessive tether tension. This is due to the presence of hinged joints, which are capable of dissipating the unbalanced loads to other legs. However, under tether pullout of consecutive buoyant legs, Mathieu-type instability is observed.

Keywords: offshore platforms, stability, postulated failure, dynamic tether tension

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Authors: Amir Hossein Hejazi, Nima Amjady

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In recent years, due to environmental issues traditional energy sources had been replaced by renewable ones. Wind energy as the fastest growing renewable energy shares a considerable percent of energy in power electricity markets. With this fast growth of wind energy worldwide, owners and operators of wind farms, transmission system operators, and energy traders need reliable and secure forecasts of wind energy production. In this paper, a new forecasting strategy is proposed for short-term wind power prediction based on Echo State Networks (ESN). The forecast engine utilizes state-of-the-art training process including dynamical reservoir with high capability to learn complex dynamics of wind power or wind vector signals. The study becomes more interesting by incorporating prediction of wind direction into forecast strategy. The Big Bang-Big Crunch (BB-BC) evolutionary optimization algorithm is adopted for adjusting free parameters of ESN-based forecaster. The proposed method is tested by real-world hourly data to show the efficiency of the forecasting engine for prediction of both wind vector and wind power output of aggregated wind power production.

Keywords: wind power forecasting, echo state network, big bang-big crunch, evolutionary optimization algorithm

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Authors: Nasser A. Al-Shabib

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Food allergens are most common non-native form when exposed to the immune system. Most food proteins undergo various treatments (e.g. thermal or proteolytic processing) during food manufacturing. Such treatments have the potential to impact the chemical structure of food allergens so as to convert them to more denatured or unfolded forms. The conformational changes in the proteins may affect the allergenicity of treated-allergens. However, most allergenic proteins possess high resistance against thermal modification or digestive enzymes. In the present study, ovomucoid (a major allergenic protein of egg white) was heated in phosphate-buffered saline (pH 7.4) at different temperatures, aqueous solutions and on different surfaces for various times. The results indicated that different antibody-based methods had different sensitivities in detecting the heated ovomucoid. When using one particular immunoassay‚ the immunoreactivity of ovomucoid increased rapidly after heating in water whereas immunoreactivity declined after heating in alkaline buffer (pH 10). Ovomucoid appeared more immunoreactive when dissolved in PBS (pH 7.4) and heated on a stainless steel surface. To the best of our knowledge‚ this is the first time that antibody-based methods have been applied for the detection of ovomucoid adsorbed onto different surfaces under various conditions. The results obtained suggest that use of antibodies to detect ovomucoid after food processing may be problematic. False assurance will be given with the use of inappropriate‚ non-validated immunoassays such as those available commercially as ‘Swab’ tests. A greater understanding of antibody-protein interaction after processing of a protein is required.

Keywords: ovomucoid, thermal treatment, solutions, surfaces

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Authors: Raúl González Muñoz, Essam Shehab, Martin Weinitzke, Chris Fowler, Paul Baguley

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Software applications have become crucial to the aerospace industry, providing a wide range of functionalities and capabilities used during the design, manufacturing and support of aircraft. However, as this criticality increases, so too does the risk for business operations when facing a software failure. Hence, there is a need for new methodologies to be developed to support aerospace companies in effectively managing their software portfolios, avoiding the hazards of business disruption and additional costs. This paper aims to provide a definition of operational software maturity, and how this can be used to assess software operational behaviour, as well as a view on the different aspects that drive software maturity within the aerospace industry. The key research question addressed is, how can operational software maturity monitoring assist the aerospace industry in effectively managing large software portfolios? This question has been addressed by conducting an in depth review of current literature, by working closely with aerospace professionals and by running an industry case study within a major aircraft manufacturer. The results are a software maturity model composed of a set of drivers and a prototype tool used for the testing and validation of the research findings. By utilising these methodologies to assess the operational maturity of software applications in aerospace, benefits in maintenance activities and operations disruption avoidance have been observed, supporting business cases for system improvement.

Keywords: aerospace, software lifecycle, software maintenance, software maturity

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Authors: Dheyaa Wajid Abbood, Ali Mohammed Tawfeeq Baqer, Eitizaz Awad Jasim

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The aim of this investigation is to confirm the activity of a sludge recycling process in trickling filter filled with limestone as an alternative biological process over conventional high-cost treatment process with regard to toxic matter reduction from marginal water. The combination system of stepped cascade weir with limestone trickling filter has been designed and constructed in the Environmental Hydraulic Laboratory, Al-Mustansiriya University, College of Engineering. A set of experiments has been conducted during the period from August 2013 to July 2014. Seven days of continuous operation with different continuous flow rates (0.4m3/hr, 0.5 m3/hr, 0.6 m3/hr, 0.7m3/hr,0.8 m3/hr, 0.9 m3/hr, and 1m3/hr) after ten days of acclimatization experiments were carried out. Results indicate that the concentrations of toxic matter were decreasing with increasing of operation time, sludge recirculation ratio, and flow rate. The toxic matter measured includes (Mineral oils, Petroleum products, Phenols, Biocides, Polychlorinated biphenyls (PCBs), and Surfactants) which are used in these experiments were ranged between (0.074 nm-0.156 nm). Results indicated that the overall reduction efficiency after 4, 28, 52, 76, 100, 124, and 148 hours of operation were (55%, 48%, 42%, 50%, 59%, 61%, and 64%) when the combination of stepped cascade weir with limestone trickling filter is used.

Keywords: Marginal water , Toxic matter, Stepped Cascade weir, limestone trickling filter

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Authors: Ghodhbani Salah, Jemili Farah

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With the growth of cyber attacks, information safety has become an important issue all over the world. Many firms rely on security technologies such as intrusion detection systems (IDSs) to manage information technology security risks. IDSs are considered to be the last line of defense to secure a network and play a very important role in detecting large number of attacks. However the main problem with today’s most popular commercial IDSs is generating high volume of alerts and huge number of false positives. This drawback has become the main motivation for many research papers in IDS area. Hence, in this paper we present a data mining technique to assist network administrators to analyze and reduce false positive alarms that are produced by an IDS and increase detection accuracy. Our data mining technique is unsupervised clustering method based on hybrid ANT algorithm. This algorithm discovers clusters of intruders’ behavior without prior knowledge of a possible number of classes, then we apply K-means algorithm to improve the convergence of the ANT clustering. Experimental results on real dataset show that our proposed approach is efficient with high detection rate and low false alarm rate.

Keywords: intrusion detection system, alarm filtering, ANT class, ant clustering, intruders’ behaviors, false alarms

Procedia PDF Downloads 390