Search results for: machine learning tools and techniques

Authors: Lukáš Mazánek, Zdeňka Konečná

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The article is devoted to the area of personnel marketing. A comprehensive review of scientific literature and articles published predominantly in personnel-oriented journals was carried out, followed by a qualitative exploratory research with the aim to explore and explain the perception of personnel marketing. Due to the lack of research in this field in Czech Republic, we have focused on Czech HR managers, more specifically, on how they understand the tasks of personnel marketing, which tools they use and whether the companies they work for try to be a preferred employer. The answers from our respondents were used to help us determine what is important within this field. All of the respondents strive to be a preferred employer and try to achieve it by using an extensive range of marketing tools. The most frequently used tools are advertising, job fairs presentations, employee care and employer brand promotion.

Keywords: Czech Republic, personnel marketing, preferred employer, qualitative research study

Procedia PDF Downloads 339

Authors: Pilar Rey del Castillo

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This document describes the building of an average indicator of the general sentiments about the future exposed in the newspapers in Spain. The raw data are collected through the scraping of the Digital Periodical and Newspaper Library website. Basic tools of natural language processing are later applied to the collected information to evaluate the sentiment strength of each word in the texts using a polarized dictionary. The last step consists of summarizing these sentiments to produce daily indices. The results are a first insight into the applicability of these techniques to produce periodic sentiment indicators.

Keywords: natural language processing, periodic indicator, sentiment analysis, web scraping

Procedia PDF Downloads 133

Authors: M. Barański

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The article presents a new vibration diagnostic method designed to (PM) machines with permanent magnets. Those devices are commonly used in small wind and water systems or vehicles drives. The author’s method is very innovative and unique. Specific structural properties of PM machines are used in this method - electromotive force (EMF) generated due to vibrations. There was analysed number of publications which describe vibration diagnostic methods and tests of electrical PM machines and there was no method found to determine the technical condition of such machine basing on their own signals. In this article, the method genesis, the similarity of machines with permanent magnet to vibration sensor and simulation and laboratory tests results will be discussed. The method of determination the technical condition of electrical machine with permanent magnets basing on its own signals is the subject of patent application No P.405669, and it is the main thesis of author’s doctoral dissertation.

Keywords: vibrations, generator, permanent magnet, traction drive, electrical vehicle

Procedia PDF Downloads 366

Authors: Xiaoli Zhang, Xiongfei Li, Yuncong Feng

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ROC curves, as a widely used evaluating tool in machine learning field, are the tradeoff of true positive rate and negative rate. However, they are blamed for ignoring some vital information in the evaluation process, such as the amount of information about the target that each instance carries, predicted score given by each classification model to each instance. Hence, in this paper, a new classification performance method is proposed by extending the Receiver Operator Characteristic (ROC) curves to 3D space, which is denoted as 3D ROC Histogram. In the histogram, the

Keywords: classification, performance evaluation, receiver operating characteristic histogram, hardness prediction

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Authors: Rana Alaa El-Deen Ahmed, M. Elemam Shehab, Shereen Morsy, Nermeen Mekawie

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With the growing popularity and acceptance of e-commerce platforms, users face an ever increasing burden in actually choosing the right product from the large number of online offers. Thus, techniques for personalization and shopping guides are needed by users. For a pleasant and successful shopping experience, users need to know easily which products to buy with high confidence. Since selling a wide variety of products has become easier due to the popularity of online stores, online retailers are able to sell more products than a physical store. The disadvantage is that the customers might not find products they need. In this research the customer will be able to find the products he is searching for, because recommender systems are used in some ecommerce web sites. Recommender system learns from the information about customers and products and provides appropriate personalized recommendations to customers to find the needed product. In this paper eleven classification algorithms are comparatively tested to find the best classifier fit for consumer online shopping attitudes and behavior in the experimented dataset. The WEKA knowledge analysis tool, which is an open source data mining workbench software used in comparing conventional classifiers to get the best classifier was used in this research. In this research by using the data mining tool (WEKA) with the experimented classifiers the results show that decision table and filtered classifier gives the highest accuracy and the lowest accuracy classification via clustering and simple cart.

Keywords: classification, data mining, machine learning, online shopping, WEKA

Procedia PDF Downloads 351

Authors: Farzaneh Badinlou, Reza Kormi-Nouri, Monika Knopf, Kamal Kharrazi

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When we teach, we have two critical elements at our disposal to help students: learning styles as well as testing styles. There are many different ways in which educators can effectively teach their students; verbal learning and experience-based learning. Lecture as a form of verbal learning style is a traditional arrangement in which teachers are more active and share information verbally with students. In experienced-based learning as the process of through, students learn actively through hands-on learning materials and observing teachers or others. Meanwhile, standard testing or assessment is the way to determine progress toward proficiency. Teachers and instructors mainly use essay (requires written responses), multiple choice questions (includes the correct answer and several incorrect answers as distractors), or open-ended questions (respondents answers it with own words). The current study focused on exploring an effective teaching style and testing methods as the function of age over school ages. In the present study, totally 410 participants were selected randomly from four grades (2ⁿᵈ, 4ᵗʰ, 6ᵗʰ, and 8ᵗʰ). Each subject was tested individually in one session lasting around 50 minutes. In learning tasks, the participants were presented three different instructions for learning materials (learning by doing, learning by observing, and learning by listening). Then, they were tested via different standard assessments as free recall, cued recall, and recognition tasks. The results revealed that generally students remember more of what they do and what they observe than what they hear. The age effect was more pronounced in learning by doing than in learning by observing, and learning by listening, becoming progressively stronger in the free-recall, cued-recall, and recognition tasks. The findings of this study indicated that learning by doing and free recall task is more age sensitive, suggesting that both of them are more strategic and more affected by developmental differences. Pedagogically, these results denoted that learning by modeling and engagement in program activities have the special role for learning. Moreover, the findings indicated that the multiple-choice questions can produce the best performance for school-aged children but is less age-sensitive. By contrast, the essay as essay can produce the lowest performance but is more age-sensitive. It will be very helpful for educators to know that what types of learning styles and test methods are most effective for students in each school grade.

Keywords: experience-based learning, learning style, school-aged children, testing methods, verbal learning

Procedia PDF Downloads 202

Authors: Seah Siok Peh, Hashimah Mohd Yunus, Nor Hashimah Hashim, Mariam Mohamad

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A country needs a workforce that encompasses knowledge, skilled labourers to generate innovation, productivity and being able to solve problems creatively via technology. Science education experts believe that the mastery of science skills help preschoolers to generate such knowledge on scientific concepts by providing constructive experiences. Science process skills are skills used by scientists to study or investigate a problem, issue, problem or phenomenon of science. In line with the skills used by scientists. The purpose of this study is to investigate the basic science process skill and interest in learning early science through mobile application. This study aimed to explore six spesific basic science process skills by the use of a mobile application as a learning support tool. The descriptive design also discusses on the extent of the use of mobile application in improving basic science process skill in young children. This study consists of six preschoolers and two preschool teachers from two different classes located in Perak, Malaysia. Techniques of data collection are inclusive of observations, interviews and document analysis. This study will be useful to provide information and give real phenomena to policy makers especially Ministry of education in Malaysia.

Keywords: science education, basic science process skill, interest, early science, mobile application

Procedia PDF Downloads 245

Authors: Prachya Kamonphet

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The purposes of this research were to study the learning motivation factors for Pre-cadets in Armed Forces Academies Preparatory School, Ministry of Defense. The subjects were 320 Pre-cadets (from all 3-year classes of Pre-cadets, the academic year 2015). The research instruments were questionnaires. The collected data were analyzed by means of Descriptive Statistic and One-Way Analysis of Variance. The results of this study were as follows: The relation between the Pre-cadets’ average grade and the motivation in studying was significance.In the aspect of the environment related to Pre-cadets’ families and the motivation in studying.In the aspect of the environment related to Pre-cadets’ studying, it was found that teaching method, learning place, educational media, relationship between teachers and Pre-cadets, relationship between Pre-cadets and their friends, and relationship between Pre-cadets and the commanders were significant.

Keywords: learning motivation factors, learning motivation, armed forces academies preparatory school, learning

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Authors: Petr Sulc, Hana Maresova

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This contribution focuses on online educational tools and language teaching, specifically on literary education in a multi-user virtual environment. The goal of this contribution is to give a basic overview of online language education and teaching in a virtual environment. The main goal of the research survey is to compare language (literary) education in a virtual environment with the traditional way of teaching in a typical classroom. The research concept will be mixed: a didactic test, the grounded theory method, and semi-structured questioning will be used. Kitely’s multi-user virtual environment and printed worksheets will be used for the comparison.

Keywords: online educational tools, virtual environment, virtual teaching objects, literary education, didactic test

Procedia PDF Downloads 163

Authors: Kemal Polat

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In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: fuzzy C-means clustering, fuzzy C-means clustering based attribute weighting, Pima Indians diabetes, SVM

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Authors: Mst. Tuhin Akter, Sharun Akter Khushbu, S. M. Shaqib

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A real-time system architecture is highly effective for monitoring and detecting various damaged products or fruits that may deteriorate over time or become infected with diseases. Deep learning models have proven to be effective in building such architectures. However, building a deep learning model from scratch is a time-consuming and costly process. A more efficient solution is to utilize deep neural network (DNN) based transfer learning models in the real-time monitoring architecture. This study focuses on using a novel strawberry dataset to develop effective transfer learning models for the proposed real-time monitoring system architecture, specifically for evaluating and detecting strawberry freshness. Several state-of-the-art transfer learning models were employed, and the best performing model was found to be Xception, demonstrating higher performance across evaluation metrics such as accuracy, recall, precision, and F1-score.

Keywords: strawberry freshness evaluation, deep neural network, transfer learning, image augmentation

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Authors: Filip Rusak, Yulia Arzhaeva, Dadong Wang

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Machine learning based Computer-Aided Diagnosis (CAD) is gaining much popularity in medical imaging and diagnostic radiology. However, it requires a large amount of high quality and labeled training image datasets. The training images may come from different sources and be acquired from different radiography machines produced by different manufacturers, digital or digitized copies of film radiographs, with various sizes as well as different pixel intensity distributions. In this paper, a content-aware image augmentation method is presented to deal with these variations. The results of the proposed method have been validated graphically by plotting the removed and added seams of pixels on original images. Two different chest X-ray (CXR) datasets are used in the experiments. The CXRs in the datasets defer in size, some are digital CXRs while the others are digitized from analog CXR films. With the proposed content-aware augmentation method, the Seam Carving algorithm is employed to resize CXRs and the corresponding labels in the form of image masks, followed by histogram matching used to normalize the pixel intensities of digital radiography, based on the pixel intensity values of digitized radiographs. We implemented the algorithms, resized the well-known Montgomery dataset, to the size of the most frequently used Japanese Society of Radiological Technology (JSRT) dataset and normalized our digital CXRs for testing. This work resulted in the unified off-the-shelf CXR dataset composed of radiographs included in both, Montgomery and JSRT datasets. The experimental results show that even though the amount of augmentation is large, our algorithm can preserve the important information in lung fields, local structures, and global visual effect adequately. The proposed method can be used to augment training and testing image data sets so that the trained machine learning model can be used to process CXRs from various sources, and it can be potentially used broadly in any medical imaging applications.

Keywords: computer-aided diagnosis, image augmentation, lung segmentation, medical imaging, seam carving

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Authors: Joan Esper Kuhnly, Jess Holden, Lynn Shelley, Nicole Kuhnly

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Empathy serves as a foundational nursing principle inherent in the nurse’s ability to form those relationships from which to care for patients. Evidence supports, including empathy in nursing and healthcare education, but there is limited data on what methods are effective to do so. Building evidence supports experiential and interactive learning methods to be effective for students to gain insight and perspective from a personalized experience. The purpose of this project is to evaluate learning activities designed to promote the attainment of empathic behaviors across 5 levels of the nursing curriculum. Quantitative analysis will be conducted on data from pre and post-learning activities using the Toronto Empathy Questionnaire. The main hypothesis, that simulation learning activities will increase empathy, will be examined using a repeated measures Analysis of Variance (ANOVA) on Pre and Post Toronto Empathy Questionnaire scores for three simulation activities (Stroke, Poverty, Dementia). Pearson product-moment correlations will be conducted to examine the relationships between continuous demographic variables, such as age, credits earned, and years practicing, with the dependent variable of interest, Post Test Toronto Empathy Scores. Krippendorff’s method of content analysis will be conducted to identify the quantitative incidence of empathic responses. The researchers will use Colaizzi’s descriptive phenomenological method to describe the students’ simulation experience and understand its impact on caring and empathy behaviors employing bracketing to maintain objectivity. The results will be presented, answering multiple research questions. The discussion will be relevant to results and educational pedagogy in the nursing curriculum as they relate to the attainment of empathic behaviors.

Keywords: curriculum, empathy, nursing, simulation

Procedia PDF Downloads 111

Authors: M. Roberts Masillamani

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There is a phenomenal difference, as regard to the teaching methodology adopted at the urban and the rural area colleges. However, bright and talented student may be from rural back ground even. But there is huge dearth of the digitization in the rural areas and lesser developed countries. Today’s students need new skills to compete and successful in the future. Education should be combination of practical, intellectual, and social skills. What does this mean for rural classrooms and how can it be achieved. Rural colleges are not able to hire the best resources, since the best teacher’s aim is to move towards the city. If city is provided everywhere, then there will be no rural area. This is possible by forming university clusters (UC). The University cluster is a group of renowned and accredited universities coming together to bridge this dearth. The UC will deliver the live lectures and allow the students’ from remote areas to actively participate in the classroom. This paper tries to present a plan of action of providing a better live classroom teaching and learning system from the city to the rural and the lesser developed countries. This paper titled “University Clusters using ICT for teaching and learning” provides a true concept of opening live digital classroom windows for rural colleges, where resources are not available, thus reducing the digital divide. This is different from pod casting a lecture or distance learning and eLearning. The live lecture can be streamed through digital equipment to another classroom. The rural students can collaborate with their peers and critiques, be assessed, collect information, acquire different techniques in assessment and learning process. This system will benefit rural students and teachers and develop socio economic status. This will also will increase the degree of confidence of the Rural students and teachers. Thus bringing about the concept of ‘Train the Trainee’ in reality. An educational university cloud for each cluster will be built remote infrastructure facilities (RIF) for the above program. The users may be informed, about the available lecture schedules, through the RIF service. RIF with an educational cloud can be set by the universities under one cluster. This paper talks a little more about University clusters and the methodology to be adopted as well as some extended features like, tutorial classes, library grids, remote laboratory login, research and development.

Keywords: lesser developed countries, digital divide, digital learning, education, e-learning, ICT, library grids, live classroom windows, RIF, rural, university clusters and urban

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Authors: S. K. Ashiquer Rahman

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The innovative knowledge threshold significantly shifted education from traditional to an online version which was an emergent state of arts for academic programs of any higher education institutions; the substantive situation thus raises the importance of deliberative integration of education, Knowledge, technology and sustainability as well as knowledge platforms, e.g., ePLANETe. In fact, the concept of 'ePLANETe' an innovative knowledge platform and its functionalities as an experimental digitized platform for contributing sustainable assessment of academic programs of higher education institution(HEI). Besides, this paper assessed and define the common sustainable development challenges of higher education(HE) and identified effective approach and tools of 'ePLANETe’ that is enable to practices sustainability assessment of academic programs through the deliberation methodologies. To investigate the effectiveness of knowledge tools and approach of 'ePLANETe’, I have studied sustainable challenges digitized pedagogical content as well as evaluation of academic programs of two public universities in France through the 'ePLANETe’ evaluation space. The investigation indicated that the effectiveness of 'ePLANETe’s tools and approach perfectly fit for the quality assessment of academic programs, implementation of sustainable challenges, and dynamic balance of ecosystem within the university communities and academic programs through 'ePLANETe’ evaluation process and space. The study suggests to the relevant higher educational institution’s authorities and policymakers could use this approach and tools for assessing sustainability and enhancing the sustainability competencies of academic programs for quality education

Keywords: ePLANETe, deliberation, evaluation, competencies

Procedia PDF Downloads 113

Authors: Hyoshin Kim

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Most post-secondary educational institutions have offered a wide variety of professional development programs and resources in order to advance the quality of education. Such programs are designed to support faculty members by focusing on topics such as course design, behavioral learning objectives, class discussion, and evaluation methods. These are based on good intentions and might help both new and experienced educators. However, the fundamental flaw is that these ‘effective methods’ are assumed to work regardless of what we teach and whom we teach. This paper is focused on intercultural intelligence and its application to education. It presents a comprehensive literature review on context and cultural diversity in terms of beliefs, values and worldviews. What has worked well with a group of homogeneous local students may not work well with more diverse and international students. It is because students hold different notions of what is means to learn or know something. It is necessary for educators to move away from certain sets of generic teaching skills, which are based on a limited, particular view of teaching and learning. The main objective of the research is to expand our teaching strategies by incorporating what students bring to the course. There have been a growing number of resources and texts on teaching international students. Unfortunately, they tend to be based on the deficiency model, which treats diversity not as strengths, but as problems to be solved. This view is evidenced by the heavy emphasis on assimilationist approaches. For example, cultural difference is negatively evaluated, either implicitly or explicitly. Therefore the pressure is on culturally diverse students. The following questions reflect the underlying assumption of deficiencies: - How can we make them learn better? - How can we bring them into the mainstream academic culture?; and - How can they adapt to Western educational systems? Even though these questions may be well-intended, there seems to be something fundamentally wrong as the assumption of cultural superiority is embedded in this kind of thinking. This paper examines how educators can incorporate intercultural intelligence into the course design by utilizing a variety of tools such as pre-course activities, peer learning and reflective learning journals. The main goal is to explore ways to engage diverse learners in all aspects of learning. This can be achieved by activities designed to understand their prior knowledge, life experiences, and relevant cultural identities. It is crucial to link course material to students’ diverse interests thereby enhancing the relevance of course content and making learning more inclusive. Internationalization of higher education can be successful only when cultural differences are respected and celebrated as essential and positive aspects of teaching and learning.

Keywords: intercultural competence, intercultural intelligence, teaching and learning, post-secondary education

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Authors: M.A. Ali, M. Matloob, A. Sahar, M. Yamin, M. Imran, Y.A. Yusof

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Quinoa (Chenopodium quinoa Willd.) is known as pseudocereal was originated in South America's Andes. Quinoa is a good source of protein, amino acids, micronutrients and bioactive components. The lack of gluten makes it suitable for celiac patients. Saponins, the leading ant-nutrient, are found in the pericarp, which adheres to the seed and transmits the bitter flavor to the quinoa grain. It is found in varying amounts in quinoa from 0.1% to 5%. This study was planned to design an indigenous machine to remove saponin from quinoa grains at the farm level to promote entrepreneurship. The machine consisted of a feeding hopper, rotating shaft, grooved stone, perforated steel cylinder, V-belts, pulleys, electric motor and mild steel angle iron and sheets. The motor transmitted power to the shaft with a belt drive. The shaft on which the grooved stone was attached rotated inside the perforated cylinder having a clearance of 2 mm and was removed saponin by an abrasion mechanism. The saponin-removed quinoa was then dipped in water to determine the presence of saponin as it produced foam in water and data were statistically analyzed. The results showed that the raw seed feeding rate of 25 g/s and milling time of 135 s completely removed saponin from seeds with minimum grain losses of 2.85% as compared to the economic analysis of the machine showed that its break-even point was achieved after one and half months with 18,000 s and a production capacity of 33 g/s.

Keywords: quinoa seeds, saponin, abrasion mechanism, stone polishing, indigenous machine

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Authors: Kinda Alsamara

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Foreign language education is a complex endeavor that often presents educators with a range of challenges and difficulties. This study shed light on the specific challenges encountered in the context of teaching Arabic as a foreign language at the Australian National University (ANU). Drawing from real-world experiences and insights, we explore the multifaceted nature of these challenges and discuss strategies that educators have employed to address them. The challenges in teaching the Arabic language encompass various dimensions, including linguistic intricacies, cultural nuances, and diverse learner backgrounds. The complex Arabic script, grammatical structures, and pronunciation patterns pose unique obstacles for learners. Moreover, the cultural context embedded within the language demands a nuanced understanding of cultural norms and practices. The diverse backgrounds of learners further contribute to the challenge of tailoring instruction to meet individual needs and proficiency levels. This study also underscores the importance of technology in tackling these challenges. Technological tools and platforms offer innovative solutions to enhance language acquisition and engagement. Online resources, interactive applications, and multimedia content can provide learners with immersive experiences, aiding in overcoming barriers posed by traditional teaching methods. Furthermore, this study addresses the role of instructors in mitigating challenges. Educators often find themselves adapting teaching approaches to accommodate different learning styles, abilities, and motivations. Establishing a supportive learning environment and fostering a sense of community can contribute significantly to overcoming challenges related to learner diversity. In conclusion, this study provides a comprehensive overview of the challenges faced in teaching Arabic as a foreign language at ANU. By recognizing these challenges and embracing technological and pedagogical advancements, educators can create more effective and engaging learning experiences for students pursuing Arabic language proficiency.

Keywords: Arabic, Arabic online, blended learning, teaching and learning, Arabic language, educational aids, technology

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Authors: Fouad Berrabah, Saad Salah, Zaamouche Fares

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In this paper, the Direct Torque Control (DTC) Control and the Sliding Mode Control for induction motor are presented and compared. The performance of the two control schemes is evaluated in terms of torque and current ripple, and transient response to variations of the torque , speed and robustness, trajectory tracking. In order to identify the more suitable solution for any application, both techniques are analyzed mathematically and simulation results are compared which advantages and drawbacks are discussed.

Keywords: induction motor, DTC- MRAS control, sliding mode control, robustness, trajectory tracking

Procedia PDF Downloads 597

Authors: Khader Musbah Titi

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In this era, traditional education systems do not meet the new challenges created by emerging technologies. On the other hand, eLearning offers all the necessary tools to meet these challenges. Using the Internet has brought numerous benefits to most educational institutions; it has also stretched traditional problems of plagiarism, cheating, stealing, vandalism, and spying into the cyberspace. This research discusses these issues in an eLearning environment. It attempts to provide suggestions and possible solutions to some of these issues. The main aim of this research is to conduct a survey at Irbid National University (INU), one of the oldest and biggest universities in Jordan, to study information related to moral and ethical issues in e-learning environment that affect the construction of the students’ characters in the future. The study will focus on student’s behavior and actions through the Internet using Learning Management System (LMS). Another aim of this research is to analyze the opinions of the instructors and last year students at INU about ethical behavior and interaction through LMS. The results show that educational institutes that use LMS should focus on student character development along with field knowledge. According to disadvantages, the results of the study showed that most of students behave unethically in their online activities (cheating, plagiarism, copy/paste etc.) while studying online courses through LMS. The result showed that instructors play a major role in the character development of students. The result also showed that academic institute must have variant mechanisms and strict policy in LMS to control unethical actions of students.

Keywords: LMS, cyber ethics, e-learning, IT ethics, students’ behaviors

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Authors: Roberto Machado

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We conducted a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology, analyzing 2,996 studies and synthesizing 41 of them to explore the evolution of data science and its integration into geography. By employing optimization algorithms, we accelerated the review process, significantly enhancing the efficiency and precision of literature selection. Our findings indicate that data science has developed over five decades, facing challenges such as the diversified integration of data and the need for advanced statistical and computational skills. In geography, the integration of data science underscores the importance of interdisciplinary collaboration and methodological innovation. Techniques like large-scale spatial data analysis and predictive algorithms show promise in natural disaster management and transportation route optimization, enabling faster and more effective responses. These advancements highlight the transformative potential of data science in geography, providing tools and methodologies to address complex spatial problems. The relevance of this study lies in the use of optimization algorithms in systematic reviews and the demonstrated need for deeper integration of data science into geography. Key contributions include identifying specific challenges in combining diverse spatial data and the necessity for advanced computational skills. Examples of connections between these two fields encompass significant improvements in natural disaster management and transportation efficiency, promoting more effective and sustainable environmental solutions with a positive societal impact.

Keywords: data science, geography, systematic review, optimization algorithms, supervised learning

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Authors: Adel H. Hejaaji

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The need for organisations to be flexible to meet the rapidly changing requirements of their customers is now well appreciated and can be witnessed within companies with their use of techniques such as single-minute exchange of die (SMED) for machine change-over or Kanban as the visual production and inventory control for Just-in-time manufacture and delivery. What is not so well appreciated by companies is the need for agility. Put simply it is the need to be alert for a new and unexpected opportunity and quick to respond with the changes necessary in order to profit from it. This paper aims to study the literature of agility in manufacturing to understand the concept of agility and how it is important and critical for the small and medium size manufacturing organisations (SMEs), and to defined the specific benefits of moving towards agility, and thus what benefit it can bring to an organisation.

Keywords: SMEs, agile manufacturing, manufacturing, industrial engineering

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Authors: Amarjit Singh, Tripatdeep Singh Dua, Vikas Attri

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Mobile Ad-hoc Network is a combination of several nodes that create dynamically a specific network without using any base infrastructure. In this study all the mobile nodes can depended upon each other to send any data. Mobile host can pick up data and forwarding to their destination path. Basically MANET depend upon their Quality of Service which is highly constraints to the user. To give better services we need to improve the QOS. In these days MANET QOS requirement to use soft computing techniques. These techniques depend upon their specific requirement and which exists using MANET concepts. Using a soft computing techniques various protocol and algorithms may be considered. In this paper, we provide comparative study review of existing work done in MANET using various kind of soft computing techniques. Our review research is based on their specific protocol or algorithm which provide concern solution of QOS need. We discuss about various protocol through which routing in MANET. In Second section we clear the concepts of Soft Computing and their types. In third section we review the MANET using different kind of soft computing techniques work done before. In forth section we need to understand the concept of QoS requirement which exists in MANET and we done comparative study on different protocol used before and last we conclude the purpose of using MANET with soft computing techniques metrics.

Keywords: mobile ad-hoc network, fuzzy improved genetic approach, neural network, routing protocol, wireless mesh network

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Authors: Firas A. Al Laban, Mohamed Chabi, Sammani Danwawu Abdullahi

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There are a real needs to integrate types of Open Educational Resources (OER) with an intelligent system to extract information and knowledge in the semantic searching level. Those needs raised because most of current learning standard adopted web based learning and the e-learning systems does not always serve all educational goals. Semantic Web systems provide educators, students, and researchers with intelligent queries based on a semantic knowledge management learning system. An ontology-based learning system is an advanced system, where ontology plays the core of the semantic web in a smart learning environment. The objective of this paper is to discuss the potentials of ontologies and mapping different kinds of ontologies; heterogeneous or homogenous to manage and control different types of Open Educational Resources. The important contribution of this research is to approach a methodology uses logical rules and conceptual relations to map between ontologies of different educational resources. We expect from this methodology to establish for an intelligent educational system supporting student tutoring, self and lifelong learning system.

Keywords: knowledge management systems, ontologies, semantic web, open educational resources

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Authors: Naveen Kumar, Shyambihari Prajapati

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Industry 4.0 is the fourth industrial revolution that focuses on interconnectivity of machine to machine, human to machine and human to human via Internet of Things (IoT). Technologies of industry 4.0 facilitate communication between human and machine through IoT and forms Cyber-Physical Production System (CPPS). In CPPS, multiple shop floors sensor data are connected through IoT and displayed through sensor dashboard to the operator. These sensor dashboards have enormous amount of information to be presented which becomes complex for operators to perform monitoring, controlling and interpretation tasks. Designing handheld sensor dashboards for supervision task will become a challenge for the interface designers. This paper reports emerging technologies of industry 4.0, changing context of increasing information complexity in consecutive industrial revolutions and upcoming design challenges for interface designers in context of Industry 4.0. Authors conclude that information complexity of sensor dashboards design has increased with consecutive industrial revolutions and designs of sensor dashboard causes cognitive load on users. Designing such complex dashboards interfaces in Industry 4.0 context will become main challenges for the interface designers.

Keywords: Industry4.0, sensor dashboard design, cyber-physical production system, Interface designer

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Authors: Dur-E- Shahwar

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Much attention has been given to ‘bridging the gap’ between neuroscience and educational practice. In order to gain a better understanding of the nature of this gap and of possibilities to enable the linking process, we have taken a boundary perspective on these two fields and the brain-based learning approach, focusing on boundary-spanning actors, boundary objects, and boundary work. In 26 semi-structured interviews, neuroscientists and education professionals were asked about their perceptions in regard to the gap between science and practice and the role they play in creating, managing, and disrupting this boundary. Neuroscientists and education professionals often hold conflicting views and expectations of both brain-based learning and of each other. This leads us to argue that there are increased prospects for a neuro-scientifically informed learning practice if science and practice work together as equal stakeholders in developing and implementing neuroscience research.

Keywords: language learning, explore, educational practices, mentalist, practice

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Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

Procedia PDF Downloads 297

Authors: Sylwia Baluta, Joanna Cabaj, Karol Malecha

Abstract:

The evolution of biosensors was driven by the need for faster and more versatile analytical methods for application in important areas including clinical, diagnostics, food analysis or environmental monitoring, with minimum sample pretreatment. Rapid and sensitive neurotransmitters detection is extremely important in modern medicine. These compounds mainly occur in the brain and central nervous system of mammals. Any changes in the neurotransmitters concentration may lead to many diseases, such as Parkinson’s or schizophrenia. Classical techniques of chemical analysis, despite many advantages, do not permit to obtain immediate results or automatization of measurements.

Keywords: adrenaline, biosensor, dopamine, laccase, tyrosinase

Procedia PDF Downloads 142

Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

Abstract:

There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

Procedia PDF Downloads 175

Authors: Rajan Ghimire

Abstract:

One of the diseases caused by the coronavirus shook the whole world. This situation challenged the education system across the world and compelled educators to shift to an online mode of teaching. Many academic institutions that were persistent to keep their traditional pedagogical approach were also forced to change their teaching methods. This study aims to assess science education students' experiences and perceptions of this global issue, especially on the science teaching and learning process. The study is based on qualitative research and through in-depth interviews with respondents and data is analyzed. Online distance teaching and learning processes meet the requirements of students who cannot or prefer not to participate in conventional classroom settings. But there are some challenges for the students and teachers in the science teaching learning process. This study recommends some points to all stakeholders.

Keywords: electronic devices, internet, online and distance learning, science education, educational policy

Procedia PDF Downloads 53