Search results for: machine learning tools and techniques

Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a distributed hybrid algorithm is proposed for solving the job shop scheduling problem. The suggested method executes different artificial neural networks, heuristics and meta-heuristics simultaneously on more than one machine. The neural networks are used to control the constraints of the problem while the meta-heuristics search the global space and the heuristics are used to prevent the premature convergence. To attain an efficient distributed intelligent method for solving big and distributed job shop scheduling problems, Apache Spark and Hadoop frameworks are used. In the algorithm implementation and design steps, new approaches are applied. Comparison between the proposed algorithm and other efficient algorithms from the literature shows its efficiency, which is able to solve large size problems in short time.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, neural network

Procedia PDF Downloads 382

Authors: Ortiz M. Rocío, Rocha G. Karina, Domenech A. Gloria

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There are several tools to assess the nutritional status of the population. A main instrument commonly used to build those tools is the food composition tables (FCT). Despite the importance of FCT, there are many error sources and variability factors that can be presented on building those tables and can lead to an under or over estimation of ingest of nutrients of a population. This work identified different food composition tables used as an instrument to estimate the nutrient ingest in Ecuador.The collection of data for choosing FCT was made through key informants –self completed questionnaires-, supplemented with institutional web research. A questionnaire with general variables (origin, year of edition, etc) and methodological variables (method of elaboration, information of the table, etc) was passed to the identified FCT. Those variables were defined based on an extensive literature review. A descriptive analysis of content was performed. Ten printed tables and three databases were reported which were all indistinctly treated as food composition tables. We managed to get information from 69% of the references. Several informants referred to printed documents that were not accessible. In addition, searching the internet was not successful. Of the 9 final tables, n=8 are from Latin America, and, n= 5 of these were constructed by indirect method (collection of already published data) having as a main source of information a database from the United States department of agriculture USDA. One FCT was constructed by using direct method (bromatological analysis) and has its origin in Ecuador. The 100% of the tables made a clear distinction of the food and its method of cooking, 88% of FCT expressed values of nutrients per 100g of edible portion, 77% gave precise additional information about the use of the table, and 55% presented all the macro and micro nutrients on a detailed way. The more complete FCT were: INCAP (Central America), Composition of foods (Mexico). The more referred table was: Ecuadorian food composition table of 1965 (70%). The indirect method was used for most tables within this study. However, this method has the disadvantage that it generates less reliable food composition tables because foods show variations in composition. Therefore, a database cannot accurately predict the composition of any isolated sample of a food product.In conclusion, analyzing the pros and cons, and, despite being a FCT elaborated by using an indirect method, it is considered appropriate to work with the FCT of INCAP Central America, given the proximity to our country and a food items list that is very similar to ours. Also, it is imperative to have as a reference the table of composition for Ecuadorian food, which, although is not updated, was constructed using the direct method with Ecuadorian foods. Hence, both tables will be used to elaborate a questionnaire with the purpose of assessing the food consumption of the Ecuadorian population. In case of having disparate values, we will proceed by taking just the INCAP values because this is an updated table.

Keywords: Ecuadorian food composition tables, FCT elaborated by direct method, ingest of nutrients of Ecuadorians, Latin America food composition tables

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Authors: Tomáš Vyčítal

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In a simulation model of a railway system it is important, besides other crucial algorithms, to have correct behaviour of train overtaking in stochastic conditions. This problem is being addressed in many simulation tools focused on railway traffic, however these are not very human-realistic. The goal of this paper is to create a more human-realistic overtaking decision support system for the use in railway traffic simulations. A fuzzy system has been chosen for this task as fuzzy systems are well-suited for human-like decision making. The fuzzy system designed takes into account timetables, train positions, delays and buffer times as inputs and provides an instruction to overtake or not overtake.

Keywords: decision-making support, fuzzy systems, simulation, railway, transport

Procedia PDF Downloads 134

Authors: Aya Idriss, Esraa Othman, Lujain Malak

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Artificial intelligence is the emulation of human intelligence processes by machines, particularly computer systems that act logically. Some of the specific applications of AI include natural language processing, speech recognition, and machine vision. Cortana is a virtual assistant and she’s an example of an AI Application. Microsoft made it possible for this app to be accessed not only on laptops and PCs but can be downloaded on mobile phones and used as a virtual assistant which was a huge success. Cortana can offer a lot apart from the basic orders such as setting alarms and marking the calendar. Its capabilities spread past that, for example, it provides us with listening to music and podcasts on the go, managing my to-do list and emails, connecting with my contacts hands-free by simply just telling the virtual assistant to call somebody, gives me instant answers and so on. A questionnaire was sent online to numerous friends and family members to perform the study, which is critical in evaluating Cortana's recognition capacity and the majority of the answers were in favor of Cortana’s capabilities. The results of the questionnaire assisted us in determining the level of Cortana's skills.

Keywords: artificial intelligence, Cortana, AI, abstract

Procedia PDF Downloads 171

Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

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Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: clustering, data mining, DBSCAN, k-means, k-medoids, sensor data

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Authors: Mudrika Singhal

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The research paper is basically about how the genetically modified organisms evolved and their significance in today’s world. It also highlights about the various pros and cons of the genetically modified organisms and the progress of India in this field. A genetically modified organism is the one whose genetic material has been altered using genetic engineering techniques. They have a wide range of uses such as transgenic plants, genetically modified mammals such as mouse and also in insects and aquatic life. Their use is rooted back to the time around 12,000 B.C. when humans domesticated plants and animals. At that humans used genetically modified organisms produced by the procedure of selective breeding and not by genetic engineering techniques. Selective breeding is the procedure in which selective traits are bred in plants and animals and then are domesticated. Domestication of wild plants into a suitable cultigen is a well known example of this technique. GMOs have uses in varied fields ranging from biological and medical research, production of pharmaceutical drugs to agricultural fields. The first organisms to be genetically modified were the microbes because of their simpler genetics. At present the genetically modified protein insulin is used to treat diabetes. In the case of plants transgenic plants, genetically modified crops and cisgenic plants are the examples of genetic modification. In the case of mammals, transgenic animals such as mice, rats etc. serve various purposes such as researching human diseases, improvement in animal health etc. Now coming upon the pros and cons related to the genetically modified organisms, pros include crops with higher yield, less growth time and more predictable in comparison to traditional breeding. Cons include that they are dangerous to mammals such as rats, these products contain protein which would trigger allergic reactions. In India presently, group of GMOs include GM microorganisms, transgenic crops and animals. There are varied applications in the field of healthcare and agriculture. In the nutshell, the research paper is about the progress in the field of genetic modification, taking along the effects in today’s world.

Keywords: applications, mammals, transgenic, engineering and technology

Procedia PDF Downloads 593

Authors: Su-Ping Liu, Yue Tian, Yifan Shen

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This study investigates the effect of corporate governance on earnings management when firms have reported a long stream of earnings increases (hereafter referred to as earnings beaters). We expect that good quality of corporate governance decreases the probability of income-increasing earnings management. We employ transparent tools to capture firms’ opportunistic management behavior, specifically, the repurchase of stock. In addition, we use corporate governance proxies to measure the degree of corporate governance, including board size, board independence, CEO duality, and the frequency of meeting. The results hold after the controlling of variables that suggested in prior literature. We expect that the simple technique, that is, firms’ degree of corporate governance, to be used as an inexpensive first step in detecting earnings management.

Keywords: corporate governance, earnings management, earnings patterns, stock repurchase

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Authors: Yurnalis Usman

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In an organization, institution or enterprise, human resource is very important aspect since many human skills cannot be replaced by technology tools even though technology has advanced rapidly now. The relationship among people is very necessary to create a subordinate and leader relation in the assumption that human beings are creatures who have feeling, desires, needs, aspirations and ideas differing from one another. This study on human relation was conducted at the Faculty of Economics of UNSYIAH, Darussalam, Banda Aceh, while the research object is associated with human relations and employee performance in Faculty of Economics of UNSYIAH. To determine the extent of employee relations in Faculty of Economics with fellow employees or superiors, the employees are given some questions. The result shows that human relations influence the employee performance at Faculty of Economics UNSYIAH strongly.

Keywords: human relation, employee performance, communication, Syiah Kuala

Procedia PDF Downloads 277

Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

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Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

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Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

Procedia PDF Downloads 124

Authors: O. Zlatkin-Troitschanskaia, J. Fischer, C. Lautenbach, H. A. Pant

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In 21st century higher education (HE), the diversity among students has increased in recent years due to the internationalization and higher mobility. Offering and providing equal and fair opportunities based on students’ individual skills and abilities instead of their social or cultural background is one of the major aims of HE. In this context, valid, objective and transparent assessments of students’ preconditions and academic competencies in HE are required. However, as analyses of the current states of research and practice show, a substantial research gap on assessment practices in HE still exists, calling for the development of effective solutions. These demands lead to significant conceptual and methodological challenges. Funded by the German Federal Ministry of Education and Research, the research program 'Modeling and Measuring Competencies in Higher Education – Validation and Methodological Challenges' (KoKoHs) focusses on addressing these challenges in HE assessment practice by modeling and validating objective test instruments. Including 16 cross-university collaborative projects, the German-wide research program contributes to bridging the research gap in current assessment research and practice by concentrating on practical and policy-related challenges of assessment in HE. In this paper, we present a differentiated overview of existing assessments of HE at the national and international level. Based on the state of research, we describe the theoretical and conceptual framework of the KoKoHs Program as well as results of the validation studies, including their key outcomes. More precisely, this includes an insight into more than 40 developed assessments covering a broad range of transparent and objective methods for validly measuring domain-specific and generic knowledge and skills for five major study areas (Economics, Social Science, Teacher Education, Medicine and Psychology). Computer-, video- and simulation-based instruments have been applied and validated to measure over 20,000 students at the beginning, middle and end of their (bachelor and master) studies at more than 300 HE institutions throughout Germany or during their practical training phase, traineeship or occupation. Focussing on the validity of the assessments, all test instruments have been analyzed comprehensively, using a broad range of methods and observing the validity criteria of the Standards for Psychological and Educational Testing developed by the American Educational Research Association, the American Economic Association and the National Council on Measurement. The results of the developed assessments presented in this paper, provide valuable outcomes to predict students’ skills and abilities at the beginning and the end of their studies as well as their learning development and performance. This allows for a differentiated view of the diversity among students. Based on the given research results practical implications and recommendations are formulated. In particular, appropriate and effective learning opportunities for students can be created to support the learning development of students, promote their individual potential and reduce knowledge and skill gaps. Overall, the presented research on competency assessment is highly relevant to national and international HE practice.

Keywords: 21st century skills, academic competencies, innovative assessments, KoKoHs

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Authors: Fabricio Costa Silva, Samuel Xavier de Souza

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A Global Positioning System (GPS) receiver is responsible to determine position, velocity and timing information by using satellite information. To get this information are necessary to combine an incoming and a locally generated signal. The procedure called acquisition need to found two information, the frequency and phase of the incoming signal. This is very time consuming, so there are several techniques to reduces the computational complexity, but each of then put projects issues in conflict. I this papers we present a method that can reduce the computational complexity by reducing the search space and paralleling the search.

Keywords: GPS, acquisition, complexity, parallelism

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Authors: M. J. Park, S. H. Lee, C. H. Lee, O. M. Kwon

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This paper investigates stability problem for linear systems of neutral type with time-varying delay. By constructing various Lyapunov-Krasovskii functional, and utilizing some mathematical techniques, the sufficient stability conditions for the systems are established in terms of linear matrix inequalities (LMIs), which can be easily solved by various effective optimization algorithms. Finally, some illustrative examples are given to show the effectiveness of the proposed criterion.

Keywords: neutral systems, time-delay, stability, Lyapnov method, LMI

Procedia PDF Downloads 344

Authors: Asikhia Olubusayo Aduke

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Students’ inability to set data-based (specific, measurable, attainable, reliable, and time-bound) personal improvement goals threatens their academic success. Hence, the study aimed to investigate year-one students’ academic goal-setting practices at Lagos State University of Education, Nigeria. Descriptive survey research was used in carrying out this study. The study population consisted of 3,101 year-one students of the University. A sample size of five hundred (501) participants was selected through a proportional and simple random sampling technique. The Formative Goal Setting Questionnaire (FGSQ) developed by Research Collaboration (2015) was adapted and used as an instrument for the study. Two main research questions were answered, while two null hypotheses were formulated and tested for the study. The study revealed higher data-based goals for all students than personal improvement goals. Nevertheless, data-based and personal improvement goal-setting for female students was higher than for male students. One sample test statistic and Anova used to analyse data for the two hypotheses also revealed that the mean difference between male and female year one students’ data-based and personal improvement goal-setting formation was statistically significant (p < 0.05). This means year one students’ data-based and personal improvement goals showed significant gender differences. Based on the findings of this study, it was recommended, among others, that therapeutic techniques that can help to change students’ faulty thinking and challenge their lack of desire for personal improvement should be sought to treat students who have problems with setting high personal improvement goals. Counsellors also need to advocate continued research into how to increase the goal-setting ability of male students and should focus more on counselling male students’ goal-setting ability. The main contributions of the study are higher institutions must prioritize early intervention in first-year students' academic goal setting. Researching gender differences in this practice reveals a crucial insight: male students often lag behind in setting meaningful goals, impacting their motivation and performance. Focusing on this demographic with data-driven personal improvement goals can be transformative. By promoting goal setting that is specific, measurable, and focused on self-growth (rather than competition), male students can unlock their full potential. Researchers and counselors play a vital role in detecting and supporting students with lower goal-setting tendencies. By prioritizing this intervention, we can empower all students to set ambitious, personalized goals that ignite their passion for learning and pave the way for academic success.

Keywords: academic goal setting, counselling, practice, university, year one students

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Authors: Abdeta Bayissa Mekessa

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The purpose of this study was to examine the effects of plyometric exercises on agility, power, and speed and improvement of U-17 female sprinters in the case of the Burayu Athletics project. The true experimental research design was employed for conducting this study. The total populations of the study were 14 U-17 female sprinters from Burayu athletics project. The populations were small in numbers; therefore, the researcher took all as a sample by using comprehensive sampling techniques. These subjects were classified into the Experimental group (N=7) and the Control group (N=7) by using simple random sampling techniques. The Experimental group participated in plyometric training for 8 weeks, 3 days per week and 60 minutes duration per day in addition to their regular training. But, the control groups were following their only regular training program. The variables selected for the purpose of this study were agility, power and speed. The tests were the Illinois agility test, standing long jump test, and 30m sprint test, respectively. Both groups were tested before (pre-test) and after (post-test) 8 weeks of plyometric training. For data analysis, the researcher used SPSS version 26.0 software. The collected data was analyzed using a paired sample t-test to observe the difference between the pre-test and post-test results of the plyometric exercises of the study. The significant level of p<0.05 was considered. The result of the study shows that after 8 weeks of plyometric training, significant improvements were found in Agility (MD=0.45, p<0.05), power (MD=-1.157, P<0.05) and speed (MD=0.37, P<0.05) for experimental group subjects. On the other hand, there was no significant change (P>0.05) in those variables in the control groups. Finally, the findings of the study showed that eight (8) weeks of plyometric exercises had a positive effect on agility, power and speed improvement of female sprinters. Therefore, Athletics coaches and athletes are highly recommended to include plyometric exercise in their training program.

Keywords: ploymetric exercise, speed power, aglity, female sprinter

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Authors: Hamid Havasi, Mohamad Reza Gholami Dehbalaei, Hamed Khorami, Shahram Karimi, Hamdi Abdi

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Doubly-fed induction generator (DFIG) equipped with a power converter is an efficient tool for converting mechanical energy of a variable speed system to a fixed-frequency electrical grid. Since electrical energy sources faces with production problems such as harmonics caused by nonlinear loads, so in this paper, compensation performance of DPC and FOC method on harmonics reduction of a DFIG wind turbine connected to a nonlinear load in MATLAB Simulink model has been simulated and effect of each method on nonlinear load harmonic elimination has been compared. Results of the two mentioned control methods shows the advantage of the FOC method on DPC method for harmonic compensation. Also, the fifth and seventh harmonic components of the network and THD greatly reduced.

Keywords: DFIG machine, energy conversion, nonlinear load, THD, DPC, FOC

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Authors: Prema Basargekar

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Facilitating the subject ‘Entrepreneurship Education’ in higher education, such as management studies, can be exhilarating as well as challenging. It is a multi-disciplinary and ever-evolving subject. Capturing entrepreneurship as a phenomenon in a holistic manner is a daunting task as it requires covering various dimensions such as new ideas generation, entrepreneurial traits, business opportunities scanning, the role of policymakers, value creation, etc., to name a few. Implicit entrepreneurship theory and effectuation are two different theories that focus on engaging the participants to create content by using their own experiences, perceptions, and belief systems. It helps in understanding the phenomenon holistically. The assumption here is that all of us are part of the entrepreneurial ecosystem, and effective learning can come through active engagement and peer learning by all the participants together. The present study is an attempt to use these theories in the class assignment given to the students at the beginning of the course to build the course content and understand entrepreneurship as a phenomenon in a better way through peer learning. The assignment was given to three batches of MBA post-graduate students doing the program in one of the private business schools in India. The subject of ‘Entrepreneurship Management’ is facilitated in the third trimester of the first year. At the beginning of the course, the students were given the assignment to submit a brief write-up/ collage/picture/poem or in any other format about “What entrepreneurship means to you?” They were asked to give their candid opinions about entrepreneurship as a phenomenon as they perceive it. Nearly 156 students doing post-graduate MBA submitted the assignment. These assignments were further used to find answers to two research questions. – 1) Are students able to use divergent and innovative forms to express their opinions, such as poetry, illustrations, videos, etc.? 2) What are various dimensions of entrepreneurship which are emerging to understand the phenomenon in a better way? The study uses the Brawn and Clark framework of reflective thematic analysis for qualitative analysis. The study finds that students responded to this assignment enthusiastically and expressed their thoughts in multiple ways, such as poetry, illustration, personal narrative, videos, etc. The content analysis revealed that there could be seven dimensions to looking at entrepreneurship as a phenomenon. They are 1) entrepreneurial traits, 2) entrepreneurship as a journey, 3) value creation by entrepreneurs in terms of economic and social value, 4) entrepreneurial role models, 5) new business ideas and innovations, 6) personal entrepreneurial experiences and aspirations, and 7) entrepreneurial ecosystem. The study concludes that an implicit approach to facilitate entrepreneurship education helps in understanding it as a live phenomenon. It also encourages students to apply divergent and convergent thinking. It also helps in triggering new business ideas or stimulating the entrepreneurial aspirations of the students. The significance of the study lies in the application of implicit theories in the classroom to make higher education more engaging and effective.

Keywords: co-creation of content, divergent thinking, entrepreneurship education, implicit theory

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Authors: Hefzollah Mohammadiyan, Mohammad Bagher Heidari, Ensiyeh Hajeb

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In this paper investigates and analyses the structure of nano sensors will be discussed. The structure can be classified based of nano sensors: quantum points, carbon nanotubes and nano tools, which details into each other and in turn are analyzed. Then will be fully examined to the Carbon nanotubes as chemical and mechanical sensors. The following discussion, be examined compares the advantages and disadvantages as different types of sensors and also it has feature and a wide range of applications in various industries. Finally, the structure and application of Chemical sensor transistors and the sensors will be discussed in air pollution control.

Keywords: carbon nanotubes, quantum points, chemical sensors, mechanical sensors, chemical sensor transistors, single walled nanotube (SWNT), atomic force microscope (AFM)

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Authors: Hanan Alenezi

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Membrane performance depends on the kind of solvent used in preparation. A membrane made by Polyetherimide (PEI) was evaluated for gas separation using X-Ray Diffraction (XRD), Scanning electron microscope (SEM), and Energy Dispersive X-Ray Spectroscopy (EDS). The purity and the thickness are detected to evaluate the membrane in order to optimize PEI membrane preparation.

Keywords: Energy Dispersive X-Ray Spectroscopy (EDS), Membrane, Polyetherimide PEI, Scanning electron microscope (SEM), Solvent, X-Ray Diffraction (XRD)

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Authors: A. Attahiru, Rabi Abdullahi Danjuma, Fatima Bint

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Language and culture are two concepts which are closely related that one affects the other. This paper attempts to examine the definition of language and culture by discussing the relationship between them. The paper further presents some instructional strategies for the teaching of language and culture as well as the influence of culture on language. It also looks at its implication to language education and finally some recommendation and conclusion were drawn.

Keywords: culture, language, relationship, strategies, teaching

Procedia PDF Downloads 407

Authors: Aroona Hashmi

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An economic recession can lead people to feel more insecure about their financial situation. The series of events leading into a recession can be especially distressing for Educated Youth. One of the most salient factors linking economic recession to psychological distress is unemployment. It is proved that a large number of educated young people are facing higher unemployment rate in Pakistan. Young people are likely to get frustrated at the lack of opportunities made available to them. If the young population increases more rapidly than job opportunities, then number of unemployment is likely to increase. The aim of present study was to investigate the relationship between economic instability, growing rate of aggression and frustration among educated youth. The study aimed to find out the impact of increased economic instability on the learning abilities of the students. Data was gathered from six university students of Punjab, Pakistan. The sample of the study consisted of three hundred male and female university students. The data was analyzed by applying Chi -square test. The results of the research indicate that there is a significant relationship between low household income and growing rate of aggression among educated youth. The increasing trend of economic instability significantly influences the learning abilities of the students. The study concludes that feeling of deprivation produce frustration and could be expressed through aggression. Therefore, if factors that are responsible for youth unemployment in Pakistan are addressed, psychological effects will be reduced. The right way of tackling the youth bulge is to turn the youth into a productive workforce. There is a dire need to transform the education system to societal needs. At the same time creating demand for the young workforce is achieved through dynamic changes in the economic structure.

Keywords: psychological effects, economic recession, educated youth, environmental factors

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Authors: Petri Solanti, Russell Klein

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Many designers are asking for an automated path from an abstract mathematical MATLAB model to a high-quality Register-Transfer Level (RTL) hardware description. Manual transformations of MATLAB or intermediate code are needed, when the design abstraction is changed. Design conversion is problematic as it is multidimensional and it requires many different design steps to translate the mathematical representation of the desired functionality to an efficient hardware description with the same behavior and configurability. Yet, a manual model conversion is not an insurmountable task. Using currently available design tools and an appropriate design methodology, converting a MATLAB model to efficient hardware is a reasonable effort. This paper describes a simple and flexible design methodology that was developed together with several design teams.

Keywords: design methodology, high-level synthesis, MATLAB, verification

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Authors: Pei-Jyun Hsieh, Cheng-Hsuan Li, Bor-Chen Kuo

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For hyperspectral image classification, feature reduction is an important pre-processing for avoiding the Hughes phenomena due to the difficulty for collecting training samples. Hence, lots of researches developed feature selection methods such as F-score, HSIC (Hilbert-Schmidt Independence Criterion), and etc., to improve hyperspectral image classification. However, most of them only consider the class separability in the original space, i.e., a linear class separability. In this study, we proposed a nonlinear class separability measure based on kernel trick for selecting an appropriate feature subset. The proposed nonlinear class separability was formed by a generalized RBF kernel with different bandwidths with respect to different features. Moreover, it considered the within-class separability and the between-class separability. A genetic algorithm was applied to tune these bandwidths such that the smallest with-class separability and the largest between-class separability simultaneously. This indicates the corresponding feature space is more suitable for classification. In addition, the corresponding nonlinear classification boundary can separate classes very well. These optimal bandwidths also show the importance of bands for hyperspectral image classification. The reciprocals of these bandwidths can be viewed as weights of bands. The smaller bandwidth, the larger weight of the band, and the more importance for classification. Hence, the descending order of the reciprocals of the bands gives an order for selecting the appropriate feature subsets. In the experiments, three hyperspectral image data sets, the Indian Pine Site data set, the PAVIA data set, and the Salinas A data set, were used to demonstrate the selected feature subsets by the proposed nonlinear feature selection method are more appropriate for hyperspectral image classification. Only ten percent of samples were randomly selected to form the training dataset. All non-background samples were used to form the testing dataset. The support vector machine was applied to classify these testing samples based on selected feature subsets. According to the experiments on the Indian Pine Site data set with 220 bands, the highest accuracies by applying the proposed method, F-score, and HSIC are 0.8795, 0.8795, and 0.87404, respectively. However, the proposed method selects 158 features. F-score and HSIC select 168 features and 217 features, respectively. Moreover, the classification accuracies increase dramatically only using first few features. The classification accuracies with respect to feature subsets of 10 features, 20 features, 50 features, and 110 features are 0.69587, 0.7348, 0.79217, and 0.84164, respectively. Furthermore, only using half selected features (110 features) of the proposed method, the corresponding classification accuracy (0.84168) is approximate to the highest classification accuracy, 0.8795. For other two hyperspectral image data sets, the PAVIA data set and Salinas A data set, we can obtain the similar results. These results illustrate our proposed method can efficiently find feature subsets to improve hyperspectral image classification. One can apply the proposed method to determine the suitable feature subset first according to specific purposes. Then researchers can only use the corresponding sensors to obtain the hyperspectral image and classify the samples. This can not only improve the classification performance but also reduce the cost for obtaining hyperspectral images.

Keywords: hyperspectral image classification, nonlinear feature selection, kernel trick, support vector machine

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Authors: Garima Joshi, Ashima N. Wadhawan

Abstract:

Neuropsychology in India is a fairly new field, having started only four decades back. Neuropsychology has come a long way since the establishment of the first department, from using western batteries for assessing patients to the development of highly reliable indigenous tools for assessing neuropsychological functioning. Clinical neuropsychology has risen as a discipline in the field of assessing and rehabilitating patients with various neurological conditions such as Traumatic Brain Injury, Stroke, Mild Cognitive Impairment, Alzheimer’s, Schizophrenia and other disorders with cognitive decline. The current review attempts to assimilate the history of the discipline in India, along with the current developments and future direction of the field and highlights the pursuit and undertakings of the scientists to provide culturally appropriate services, in terms of assessment and rehabilitation, to the Indian population.

Keywords: clinical neuropsychology, cognitive assessment, cognitive rehabilitation, neuropsychological test batteries in India

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Authors: Hala Kama Ahmed Rashwan

Abstract:

Ensuring the patient safety especially at intensive care units and those exposed to hospital tools and equipment is one of the most important challenges facing healthcare today. Outbreak of food poisoning as a result of food-borne pathogens has been reported in many hospitals and care homes all over the world due to hospital meals. Patient safety of eating hospital meals is a fundamental principle of healthcare; it is new healthcare disciplines that assure the food raw materials, food storage, meals processing, and control of kitchen errors that often lead to adverse healthcare events. The aim of this article is to promote any hospital in attaining the hygienic practices and better quality system during processing of the ready-to- eat meals for intensive care units patients according to the WHO safety guidelines.

Keywords: hospitals, meals, safety, intensive care

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Authors: L. J. Díaz, M. A. Hernández, A. K. Molina, A. Bermúdez, C. Crane, V. M. Pabón

Abstract:

One of the most important biological indicators that show the exposure to the radiation is the micronuclei (MN). This technique is using to determinate the radiation effects in blood cultures as a biological control and a complement to the physics dosimetry. In Colombia the necessity to apply this analysis has emerged due to the current biological indicator most used is the chromosomal aberrations (CA), that is why it is essential the MN technique’s standardization and validation to have enough tools to improve the radioprotection topic in the country. Besides, this technique will be applied on the construction of a dose-response curve, that allow measure an approximately dose to irradiated people according to MN frequency found. Inside the steps that carried out to accomplish the standardization and validation is the statistic analysis from the lectures of “in vitro” peripheral blood cultures with different analysts, also it was determinate the best culture medium and conditions for the MN can be detected easily.

Keywords: micronuclei, radioprotection, standardization, validation

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Authors: B. Laurita

Abstract:

The importance of Water Harvesting (WH) as an effective mean to deal with water scarcity is universally recognized. The collection and storage of rainwater, floodwater or quick runoff and their conversion to productive uses can ensure water availability for domestic and agricultural use, enabling a lower exploitation of the aquifer, preventing erosion events and providing significant ecosystem services. At the same time, it has been proven that it can reduce the insurgence of water conflicts if supported by a cooperative process of planning and management. On the other hand, the construction of water harvesting structures changes the hydrological regime, affecting upstream-downstream dynamics and changing water allocation, often causing contentions. Furthermore, dynamics existing between water harvesting and water conflict are not properly investigated yet. Thus, objective of this study is to analyze the relations between water harvesting and the insurgence of water conflicts, providing a solid theoretical basis and foundations for future studies. Two search engines were selected in order to perform the study: Google Scholar and Scopus. Separate researches were conducted on the mutual influences between water conflicts and the four main water harvesting techniques: rooftop harvesting, surface harvesting, underground harvesting, runoff harvesting. Some of the aforementioned water harvesting techniques have been developed and implemented on scales ranging from the small, household-sided ones, to gargantuan dam systems. Instead of focusing on the collisions related to large-scale systems, this review is aimed to look for and collect examples of the effects that the implementation of small water harvesting systems has had on the access to the water resource and on water governance. The present research allowed to highlight that in the studies that have been conducted up to now, water harvesting, and in particular those structures that allow the collection and storage of water for domestic use, is usually recognized as a positive, palliative element during contentions. On the other hand, water harvesting can worsen and, in some cases, even generate conflicts for water management. This shows the necessity of studies that consider both benefits and negative influences of water harvesting, analyzing its role respectively as triggering or as mitigating factor of conflicting situations.

Keywords: arid areas, governance, water conflicts, water harvesting

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Authors: H. Mahdjoub, B. Hamaidi, B. Zerouali, S. Rouabhia

Abstract:

The issue of fault detection and diagnosis (FDD) has gained widespread industrial interest in process condition monitoring applications. Accordingly, the use of neuro-fuzzy technic seems very promising. This paper treats a diagnosis modeling a strategic equipment of an industrial installation. We propose a diagnostic tool based on adaptive neuro-fuzzy inference system (ANFIS). The neuro-fuzzy network provides an abductive diagnosis. Moreover, it takes into account the uncertainties on the maintenance knowledge by giving a fuzzy characterization of each cause. This work was carried out with real data of a lubrication circuit from the gas turbine. The machine of interest is a gas turbine placed in a gas compressor station at South Industrial Centre (SIC Hassi Messaoud Ouargla, Algeria). We have defined the zones of good and bad functioning, and the results are presented to demonstrate the advantages of the proposed method.

Keywords: fault detection and diagnosis, lubrication system, turbine, ANFIS, training, pattern recognition

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Authors: S. Ghorbani, N. I. Polushin

Abstract:

The machinability of workpieces (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron) in turning operation has been carried out using different types of cutting tool (conventional, cutting tool with holes in toolholder and cutting tool filled up with composite material) under dry conditions on a turning machine at different stages of spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). Experimentation was performed as per Taguchi’s orthogonal array. To evaluate the relative importance of factors affecting surface roughness the single decision tree (SDT), Decision tree forest (DTF) and Group method of data handling (GMDH) were applied.

Keywords: decision tree forest, GMDH, surface roughness, Taguchi method, turning process

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Authors: Kathaleeya Chanda

Abstract:

The schools under the Project Initiated by H.R.H Princess in Maha Chakri Sirindhorn in Nakhonnayok Educational Service Area Office are the small schools, situated in a remote and undeveloped area.Thus, the school-age youth didn’t have or have fewer opportunities to study at the higher education level which can lead to many social and economic problems. This study aims to solve these educational issues of the schools, under The Project Initiated by H.R.H Princess in Maha Chakri Sirindhorn, Nakhonnayok Educational Service Area Office, by the development of teachers, so that teachers could develop teaching and learning system with the ultimate goal to increase students’ academic achievement, increase the educational opportunities for the youth in the area, and help them learn happily. 154 in-service teachers from 22 schools and 4 different districts in Nakhonnayok participated in this teacher training. Most teachers were satisfied with the training content and the trainer. Thereafter, the teachers were given the test to assess the skills and knowledge after training. Most of the teachers earned a score higher than 75%. Accordingly, it can be concluded that after attending the training, teachers have a clear understanding of the contents. After the training session, the teachers have to write a lesson plan that is integrated or adapted to the Sufficiency Economy Philosophy. The teachers can either adopt intradisciplinary or interdisciplinary integration according to their actual teaching conditions in the school. Two weeks after training session, the researchers went to the schools to discuss with the teachers and follow up the assigned integrated lesson plan. It was revealed that the progress of integrated lesson plan could be divided into 3 groups: 1) the teachers who have completed the integrated lesson plan, but are concerned about the accuracy and consistency, 2) teachers who almost complete the lesson plan or made a great progress but are still concerned, confused in some aspects and not fill in the details of the plan, and 3), the teachers who made few progress, are uncertain and confused in many aspects, and may had overloaded tasks from their school. However, a follow-up procedure led to the commitment of teachers to complete the lesson plan. Regarding student learning assessment, from an experiment teaching, most of the students earned a score higher than 50 %. The rate is higher than the one from actual teaching. In addition, the teacher have assessed that the student is happy, enjoys learning, and providing a good cooperates in teaching activities. The students’ interview about the new lesson plan shows that they are happy with it, willing to learn, and able to apply such knowledge in daily life. Integrated lesson plan can increases the educational opportunities for youth in the area.

Keywords: sufficiency, economy, philosophy, integrated education syllabus

Procedia PDF Downloads 178