Search results for: translator training/competencies

Authors: Patrick Cormier, Cesar Meylan, Matt Jensen, Dana Agar-Newman, Chloe Werle, Ming-Chang Tsai, Marc Klimstra

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Sprint-derived horizontal force-velocity-power (FVP) profiles can be developed with adequate validity and reliability with satellite (GPS/GNSS) systems. However, FVP metrics are sensitive to small nuances in data processing procedures such that minor differences in defining the onset and end of the sprint could result in different FVP metric outcomes. Furthermore, in team-sports, there is a requirement for rapid analysis and feedback of results from multiple athletes, therefore developing standardized and automated methods to improve the speed, efficiency and reliability of this process are warranted. Thus, the purpose of this study was to compare different methods of sprint end detection on the development of FVP profiles from 10Hz GPS/GNSS data through goodness-of-fit and intertrial reliability statistics. Seventeen national team female soccer players participated in the FVP protocol which consisted of 2x40m maximal sprints performed towards the end of a soccer specific warm-up in a training session (1020 hPa, wind = 0, temperature = 30°C) on an open grass field. Each player wore a 10Hz Catapult system unit (Vector S7, Catapult Innovations) inserted in a vest in a pouch between the scapulae. All data were analyzed following common procedures. Variables computed and assessed were the model parameters, estimated maximal sprint speed (MSS) and the acceleration constant τ, in addition to horizontal relative force (F₀), velocity at zero (V₀), and relative mechanical power (Pmax). The onset of the sprints was standardized with an acceleration threshold of 0.1 m/s². The sprint end detection methods were: 1. Time when peak velocity (MSS) was achieved (zero acceleration), 2. Time after peak velocity drops by -0.4 m/s, 3. Time after peak velocity drops by -0.6 m/s, and 4. When the integrated distance from the GPS/GNSS signal achieves 40-m. Goodness-of-fit of each sprint end detection method was determined using the residual sum of squares (RSS) to demonstrate the error of the FVP modeling with the sprint data from the GPS/GNSS system. Inter-trial reliability (from 2 trials) was assessed utilizing intraclass correlation coefficients (ICC). For goodness-of-fit results, the end detection technique that used the time when peak velocity was achieved (zero acceleration) had the lowest RSS values, followed by -0.4 and -0.6 velocity decay, and 40-m end had the highest RSS values. For intertrial reliability, the end of sprint detection techniques that were defined as the time at (method 1) or shortly after (method 2 and 3) when MSS was achieved had very large to near perfect ICC and the time at the 40 m integrated distance (method 4) had large to very large ICCs. Peak velocity was reached at 29.52 ± 4.02-m. Therefore, sport scientists should implement end of sprint detection either when peak velocity is determined or shortly after to improve goodness of fit to achieve reliable between trial FVP profile metrics. Although, more robust processing and modeling procedures should be developed in future research to improve sprint model fitting. This protocol was seamlessly integrated into the usual training which shows promise for sprint monitoring in the field with this technology.

Keywords: automated, biomechanics, team-sports, sprint

Procedia PDF Downloads 118

Authors: Kelechi Ezeji

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The use of Computer Aided Design (CAD) technologies has become pervasive in the Architecture, Engineering and Construction (AEC) industry. This has led to its inclusion as an important part of the training module in the curriculum for Architecture Schools in Nigeria. This paper examines the ethical questions that arise in the implementation of Computer Aided Design (CAD) Content of the curriculum for Architectural education. Using existing literature, it begins this scrutiny from the propriety of inclusion of CAD into the education of the architect and the obligations of the different stakeholders in the implementation process. It also examines the questions raised by the negative use of computing technologies as well as perceived negative influence of the use of CAD on design creativity. Survey methodology was employed to gather data from the Department of Architecture, Chukwuemeka Odumegwu Ojukwu University Uli, which has been used as a case study on how the issues raised are being addressed. The paper draws conclusions on what will make for successful ethical implementation.

Keywords: computer aided design, curriculum, education, ethics

Procedia PDF Downloads 412

Authors: Matteo Calabrese, Martin Cimmino, Dimos Kapetis, Martina Manfrin, Donato Concilio, Giuseppe Toscano, Giovanni Ciandrini, Giancarlo Paccapeli, Gianluca Giarratana, Marco Siciliano, Andrea Forlani, Alberto Carrotta

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In this paper we describe a machine learning methodology for Predictive Maintenance (PdM) applied on woodworking industrial machines. PdM is a prominent strategy consisting of all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the challenges with PdM approach is to design and develop of an embedded smart system to enable the health status of the machine. The proposed approach allows screening simultaneously multiple connected machines, thus providing real-time monitoring that can be adopted with maintenance management. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime of woodworking machines. The effectiveness of the methodology is demonstrated by testing an independent sample of additional woodworking machines without presenting machine down event.

Keywords: predictive maintenance, machine learning, connected machines, artificial intelligence

Procedia PDF Downloads 222

Authors: Jinsiang Shaw, Pik-Hoe Chen

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This paper aims to integrate human recognition, motion recognition, and object tracking technologies without requiring a pre-training database model for motion recognition or the unknown object itself. Furthermore, it can simultaneously track multiple users and multiple objects. Unlike other existing human motion recognition methods, our approach employs a rule-based condition method to determine if a user hand is approaching or departing an object. It uses a background subtraction method to separate the human and object from the background, and employs behavior features to effectively interpret human object-grabbing actions. With an object’s histogram characteristics, we are able to isolate and track it using back projection. Hence, a moving object trajectory can be recorded and the object itself can be located. This particular technique can be used in a camera surveillance system in a shopping area to perform real-time intelligent surveillance, thus preventing theft. Experimental results verify the validity of the developed surveillance algorithm with an accuracy of 83% for shoplifting detection.

Keywords: Automatic Tracking, Back Projection, Motion Recognition, Shoplifting

Procedia PDF Downloads 331

Authors: Mecheri Zeid Belmecheri, Maamar Ahfir, Izzet Kale

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Automatic cardiac auscultation is still a subject of research in order to establish an objective diagnosis. Recorded heart sounds as Phonocardiogram signals (PCG) can be used for automatic segmentation into components that have clinical meanings. These are the first sound, S1, the second sound, S2, and the systolic and diastolic components, respectively. In this paper, an automatic method is proposed for the robust segmentation of heart sounds. This method is based on calculating an intermediate sawtooth-shaped signal from the length variation of the recorded Phonocardiogram (PCG) signal in the time domain and, using its positive derivative function that is a binary signal in training a Recurrent Neural Network (RNN). Results obtained in the context of a large database of recorded PCGs with their simultaneously recorded ElectroCardioGrams (ECGs) from different patients in clinical settings, including normal and abnormal subjects, show a segmentation testing performance average of 76 % sensitivity and 94 % specificity.

Keywords: heart sounds, PCG segmentation, event detection, recurrent neural networks, PCG curve length

Procedia PDF Downloads 177

Authors: K. Tejasri, K. Suvarna Vani, S. Prathyusha, S. Ramya

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Proteins are chained sequences of amino acids which are brought together by the peptide bonds. Many varying formations of the chains are possible due to multiple combinations of amino acids and rotation in numerous positions along the chain. Protein structure prediction is one of the crucial goals worked towards by the members of bioinformatics and theoretical chemistry backgrounds. Among the four different structure levels in proteins, we emphasize mainly the secondary level structure. Generally, the secondary protein basically comprises alpha-helix and beta-sheets. Multi-class classification problem of data with disparity is truly a challenge to overcome and has to be addressed for the beta strands. Imbalanced data distribution constitutes a couple of the classes of data having very limited training samples collated with other classes. The secondary structure data is extracted from the protein primary sequence, and the beta-strands are predicted using suitable machine learning algorithms.

Keywords: proteins, secondary structure elements, beta-sheets, beta-strands, alpha-helices, machine learning algorithms

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Authors: Siriporn Poolsuwan, Kanyarat Bussaban

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This research aims to investigate and analyze user’s behaviour towards the utilization of the online news clipping database at Suan Sunandha Rajabhat University, Thailand. Data is gathered from 214 lecturers and 380 undergraduate students by using questionnaires. Findings show that most users knew the online news clipping service from their friends, library’s website and their teachers. The users learned how to use it by themselves and others learned by training of SSRU library. Most users used the online news clipping database one time per month at home and always used the service for general knowledge, up-to-date academic knowledge and assignment reference. Moreover, the results of using the online news clipping service problems include the users themselves, service management, service device- computer and tools – and the network, service provider, and publicity. This research would be benefit for librarians and teachers for planning and designing library services in their works and organization.

Keywords: online database, user behavior, news clipping, library services

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Authors: Hediye Saglam

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This research has been carried out to bring in the 6 acquisitions in the 2014 Preschool Teaching Programme of the Turkish Ministry of Education through the method of analogy. This research is practiced based on the experimental pattern with pre-test and final test controlling groups. The working group of the study covers the group between 5-6 ages. The study takes 5 weeks including the 2 weeks spent for pre-test and the final test. It is conducted with the preschool teacher who gives the lesson along with the researcher in the in-class and out-of-class rainbow experiments of the students for 5 weeks. 'One Sample T Test' is used for the evaluation of the pre-test and final test. SPSS 17 programme is applied for the analysis of the data. Results: As an outcome of the study it is observed that analogy method affects children’s learning of the rainbow. For this very reason teachers should receive inservice training for different methods and techniques like analogy. This method should be included in preschool education programme and should be applied by teachers more often.

Keywords: acquisitions of preschool education programme, analogy method, pre-test/final test, rainbow experiments

Procedia PDF Downloads 504

Authors: Muhammad Ajmal, Ahmad Shahrul Nizam Bin Isha, Shahrina Md. Nordin, Paras Behrani, Al-Baraa Abdulrahman Al-Mekhlafi

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This study aims to investigate the impact of safety management practices via safety compliance on occupational injuries in the context of downstream the oil and gas industry of Malaysia. However, it is still challenging for researchers and academicians to control occupational injuries in high-safety-sensitive organizations. In this study response rate was 62%, and 280 valid responses were used for analysis through SmartPLS. The study results revealed that safety management practices (management commitment, safety training, safety promotion policies, workers’ involvement) play a significant role in lowering the rate of accidents in downstream the oil and gas industry via safety compliance. Furthermore, the study results also revealed that safety management practices also reduce safety management costs of organizations, e.g., lost work days and employee absenteeism. Moreover, this study is helpful for safety leaders and managers to understand the importance of safety management practices to lower the ratio of occupational injuries.

Keywords: safety management, safety compliance, occupational injuries, oil and gas, Malaysia

Procedia PDF Downloads 151

Authors: Tanit Pruktara

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The research aimed to study the students’ learning achievement and awareness level on electrical energy consumption and conservation and also to investigate the students’ attitude on the developed multimedia supplemented instructional unit for learning household electrical energy consumption and conservation in grade 10 Thailand student. This study used a quantitative method using MCQ for pre and post-achievement tests and Likert scales for awareness and attitude survey questionnaires. The results from this were employed to improve the multimedia to be appropriate for the classroom and with real life situations in the second phase, the main study. The experimental results showed that the developed learning unit significantly improved the students’ learning achievement as well as their awareness of electric energy conservation. Additional we found the student will enjoy participating in class activities when the lessons are taught using multimedia and helps them to develop the relevance between the course and real world situations.

Keywords: lesson plan, media and animations, training course, vocational school in Thailand

Procedia PDF Downloads 174

Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

Procedia PDF Downloads 383

Authors: Mohamad Kassab, Amal El Fallah Seghrouchni, Frederic Barbaresco, Raed Abu Zitar

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Detecting objects such as drones is a challenging task as their relative size and maneuvering capabilities deceive machine learning models and cause them to misclassify drones as birds or other objects. In this work, we investigate applying several deep learning techniques to benchmark real data sets of flying drones. A deep learning paradigm is proposed for the purpose of mitigating the complexity of those systems. The proposed paradigm consists of a hybrid between the AdderNet deep learning paradigm and the Single Shot Detector (SSD) paradigm. The goal was to minimize multiplication operations numbers in the filtering layers within the proposed system and, hence, reduce complexity. Some standard machine learning technique, such as SVM, is also tested and compared to other deep learning systems. The data sets used for training and testing were either complete or filtered in order to remove the images with mall objects. The types of data were RGB or IR data. Comparisons were made between all these types, and conclusions were presented.

Keywords: drones detection, deep learning, birds versus drones, precision of detection, AdderNet

Procedia PDF Downloads 178

Authors: Azeddine El-Hassouny, Chandrashekhar Meshram, Geraldin Nanfack

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In recent years, learning from data with noisy labels (Label Noise) has been a major concern in supervised learning. This problem has become even more worrying in Deep Learning, where the generalization capabilities have been questioned lately. Indeed, deep learning requires a large amount of data that is generally collected by search engines, which frequently return data with unreliable labels. In this paper, we investigate the Label Noise in Deep Learning using variational inference. Our contributions are : (1) exploiting Label Noise concept where the true labels are learnt using reparameterization variational inference, while observed labels are learnt discriminatively. (2) the noise transition matrix is learnt during the training without any particular process, neither heuristic nor preliminary phases. The theoretical results shows how true label distribution can be learned by variational inference in any discriminate neural network, and the effectiveness of our approach is proved in several target datasets, such as MNIST and CIFAR32.

Keywords: label noise, deep learning, discrete latent variable, variational inference, MNIST, CIFAR32

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Authors: Mohammad Anwar, Shah Waliullah

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The development of science and technology in the present era has an urgent demand for the training of thinking of undergraduates. This requirement actively promotes research and teaching of basic theories, beneficial to the career development of students. This study clarified the dialectical relation between the thermodynamic equilibrium constant and reaction rate constant through the contrast thinking method. Findings reveal that both the isobaric Van't Hoff equation and the Arrhenius equation had four similar forms, and the change in the trend of both constants showed a similar law. By the derivation of the formation rate constant of the product (KY) and the consumption rate constant of the reactant (KA), the ratio of both constants at the end state indicated the nature of the equilibrium state in agreement with that of the thermodynamic equilibrium constant (K^θ (T)). This study has thus presented that the thermodynamic equilibrium constant contained the characteristics of microscopic dynamics based on the analysis of the reaction mechanism, and both constants are organically connected and unified. The reaction enthalpy and activation energy are closely related to each other with the same connotation.

Keywords: thermodynamic equilibrium constant, reaction rate constant, PBL teaching, dialectical relation, innovative thinking

Procedia PDF Downloads 107

Authors: Vine Petzer, Mirna Nel

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An explanatory mixed method design was used to investigate accounting classroom conditions in the Further Education and Training (FET) Phase in South Africa. A descriptive survey research study with a heterogeneous group of learners and teachers was conducted in the first phase. In the qualitative phase, semi-structured individual interviews with learners and teachers, as well as observations in the accounting classroom, were employed to gain more in depth understanding of the learning conditions in the accounting classroom. The findings of the empirical research informed the development of a model for teachers in accounting, supporting them to use more effective teaching methods and create positive learning conditions for all learners to experience successful learning. A model towards creating positive Accounting classroom conditions that support successful learning was developed and recommended for education policy and decision-makers for use as a classroom intervention capacity building tool. The model identifies and delineates classroom practices that exert significant effect on learner attainment of quality education.

Keywords: accounting classroom conditions, positive education, successful learning, teaching accounting

Procedia PDF Downloads 145

Authors: Zongping Wang, Chengjun Cui, Jiacun Wang

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The concept of intelligence has been widely used to access an individual's cognitive abilities to learn, form concepts, understand, apply logic, and reason. According to the multiple intelligence theory, there are eight distinguished types of intelligence. One of them is the bodily-kinaesthetic intelligence that links to the capacity of an individual controlling his body and working with objects. Motor intelligence, on the other hand, reflects the capacity to understand, perceive and solve functional problems by motor behavior. Both bodily-kinaesthetic intelligence and motor intelligence refer directly or indirectly to bodily capacity. Inspired by these two intelligence concepts, this paper introduces motional intelligence (MI). MI is two-fold. (1) Body strength, which is the capacity of various organ functions manifested by muscle activity under the control of the central nervous system during physical exercises. It can be measured by the magnitude of muscle contraction force, the frequency of repeating a movement, the time to finish a movement of body position, the duration to maintain muscles in a working status, etc. Body strength reflects the objective of MI. (2) Level of psychiatric willingness to physical events. It is a subjective thing and determined by an individual’s self-consciousness to physical events and resistance to fatigue. As such, we call it subjective MI. Subjective MI can be improved through education and proper social events. The improvement of subjective MI can lead to that of objective MI. A quantitative score of an individual’s MI is motional quotient (MQ). MQ is affected by several factors, including genetics, physical training, diet and lifestyle, family and social environment, and personal awareness of the importance of physical exercise. Genes determine one’s body strength potential. Physical training, in general, makes people stronger, faster and swifter. Diet and lifestyle have a direct impact on health. Family and social environment largely affect one’s passion for physical activities, so does personal awareness of the importance of physical exercise. The key to the success of the MQ study is developing an acceptable and efficient system that can be used to assess MQ objectively and quantitatively. We should apply different accessing systems to different groups of people according to their ages and genders. Field test, laboratory test and questionnaire are among essential components of MQ assessment. A scientific interpretation of MQ score is part of an MQ assessment system as it will help an individual to improve his MQ. IQ (intelligence quotient) and EQ (emotional quotient) and their test have been studied intensively. We argue that IQ and EQ study alone is not sufficient for an individual’s all round development. The significance of MQ study is that it offsets IQ and EQ study. MQ reflects an individual’s mental level as well as bodily level of intelligence in physical activities. It is well-known that the American Springfield College seal includes the Luther Gulick triangle with the words “spirit,” “mind,” and “body” written within it. MQ, together with IQ and EQ, echoes this education philosophy. Since its inception in 2012, the MQ research has spread rapidly in China. By now, six prestigious universities in China have established research centers on MQ and its assessment.

Keywords: motional Intelligence, motional quotient, multiple intelligence, motor intelligence, all round development

Procedia PDF Downloads 160

Authors: Nuno Biga

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Continuous processes’ improvement is a permanent challenge for managers of any organization. Lean management means that efficiency gains can be obtained through a systematic framework able to explore synergies between processes, eliminate waste of time, and other resources. Leaderships in organizations determine the efficiency of the teams through their influence on collaborators, their motivation, and consolidation of ownership (group) feeling. The “organization health” depends on the leadership style, which is directly influenced by the intrinsic characteristics of each personality and leadership ability (leadership competencies). Therefore, it’s important that managers can correct in advance any deviation from expected leadership exercises. Top management teams must assume themselves as regulatory agents of leadership within the organization, ensuring monitoring of actions and the alignment of managers in accordance with the humanist standards anchored in a visible Code of Ethics and Conduct. This article is built around an innovative model of “Business Interactive Games” (BI GAMES) that simulates a real-life management environment. It shows that the strategic management of operations depends on a complex set of endogenous and exogenous variables to the intervening agents that require specific skills and a set of critical processes to monitor. BI GAMES are designed for each management reality and have already been applied successfully in several contexts over the last five years comprising the educational and enterprise ones. Results from these experiences are used to demonstrate how serious games in working living labs contributed to improve the organizational environment by focusing on the evaluation of players’ (agents’) skills, empower its capabilities, and the critical factors that create value in each context. The implementation of the BI GAMES simulator highlights that leadership skills are decisive for the performance of teams, regardless of the sector of activity and the specificities of each organization whose operation is intended to simulate. The players in the BI GAMES can be managers or employees of different roles in the organization or students in the learning context. They interact with each other and are asked to decide/make choices in the presence of several options for the follow-up operation, for example, when the costs and benefits are not fully known but depend on the actions of external parties (e.g., subcontracted enterprises and actions of regulatory bodies). Each team must evaluate resources used/needed in each operation, identify bottlenecks in the system of operations, assess the performance of the system through a set of key performance indicators, and set a coherent strategy to improve efficiency. Through the gamification and the serious games approach, organizational managers will be able to confront the scientific approach in strategic decision-making versus their real-life approach based on experiences undertaken. Considering that each BI GAME’s team has a leader (chosen by draw), the performance of this player has a direct impact on the results obtained. Leadership skills are thus put to the test during the simulation of the functioning of each organization, allowing conclusions to be drawn at the end of the simulation, including its discussion amongst participants.

Keywords: business interactive games, gamification, management empowerment skills, simulation living labs

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Authors: Purnima K Bajre, Rujula Talloo

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A variety of vehicles are driven on roads such as private vehicles, commercial vehicles, public vehicles, and emergency service vehicles (EMV). Drivers driving different vehicles can have attitude differences towards emergency service vehicles which in turn affects their likelihood to give way to them. The present review aims to understand the factors that mediate this yielding behavior of drivers towards EMVs. Through extensive review of available literature, factors such as effects of lights and sirens, cognitive load, age of the driver, driving general experience, traffic load, drivers’ experience and training with EMVs and drivers’ attitude towards EMV drivers, have emerged as mediating factors. Whereas cognitive load is the most researched area and is observed to be associated negatively with on road drivers’ attitudes towards EMVs, there is a paucity of research to understand the relationships between empathy, pro-social skills, and on road drivers’ attitude towards EMVs.

Keywords: cognitive load, emergency service vehicle, empathy, traffic load

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Authors: Mohaned G. Abed

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Attention Deficit Hyperactivity Disorder (ADHD) is considered one of the most frequently diagnosed psychiatric childhood disorders. It has an effect on 3–5% of school-aged children, and brings about difficulties in academic and social interaction. This study explored the knowledge and beliefs of parents in Saudi Arabia about children with ADHD. The Knowledge about Attention Deficit Disorder Questionnaire (KADD-Q) was administered to a sample of parents, followed by interviews with a subset of the total respondents. The results indicated that the parents knew more about the characteristics of ADHD than they knew about its related causes and treatment. Overall, the findings indicated that these parents had some knowledge about general characteristics of ADHD, but they had little understanding of causes and possible interventions. These results suggest an important need for more formal parents training regarding all aspects of ADHD in school age children.

Keywords: attention deficit hyperactivity disorder, childhood disorders, school-aged children, difficulties in academic, social interaction

Procedia PDF Downloads 110

Authors: Erfan Abdeldaim Mohamed Ahmed Abdalla

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The complexity of Arabic grammar poses challenges for learners, particularly in relation to its arrangement, classification, abundance, and bifurcation. The challenge at hand is a result of the contextual factors that gave rise to the grammatical rules in question, as well as the pedagogical approach employed at the time, which was tailored to the needs of learners during that particular historical period. Consequently, modern-day students encounter this same obstacle. This requires a thorough examination of the arrangement and categorization of Arabic grammatical rules based on particular criteria, as well as an assessment of their objectives. Additionally, it is necessary to identify the prevalent and renowned grammatical rules, as well as those that are infrequently encountered, obscure and disregarded. This paper presents a compilation of grammatical rules that require arrangement and categorization in accordance with the standards outlined in the Common European Framework of Reference for Languages (CEFR). In addition to facilitating comprehension of the curriculum, accommodating learners' requirements, and establishing the fundamental competencies for achieving proficiency in Arabic, it is imperative to ascertain the conventions that language learners necessitate in alignment with explicitly delineated benchmarks such as the CEFR criteria. The aim of this study is to reduce the quantity of grammatical rules that are typically presented to non-native Arabic speakers in Arabic textbooks. This reduction is expected to enhance the motivation of learners to continue their Arabic language acquisition and to approach the level of proficiency of native speakers. The primary obstacle faced by learners is the intricate nature of Arabic grammar, which poses a significant challenge in the realm of study. The proliferation and complexity of regulations evident in Arabic language textbooks designed for individuals who are not native speakers is noteworthy. The inadequate organisation and delivery of the material create the impression that the grammar is being imparted to a student with the intention of memorising "Alfiyyat-Ibn-Malik." Consequently, the sequence of grammatical rules instruction was altered, with rules originally intended for later instruction being presented first and those intended for earlier instruction being presented subsequently. Students often focus on learning grammatical rules that are not necessarily required while neglecting the rules that are commonly used in everyday speech and writing. Non-Arab students are taught Arabic grammar chapters that are infrequently utilised in Arabic literature and may be a topic of debate among grammarians. The aforementioned findings are derived from the statistical analysis and investigations conducted by the researcher, which will be disclosed in due course of the research. To instruct non-Arabic speakers on grammatical rules, it is imperative to discern the most prevalent grammatical frameworks in grammar manuals and linguistic literature (study sample). The present proposal suggests the allocation of grammatical structures across linguistic levels, taking into account the guidelines of the CEFR, as well as the grammatical structures that are necessary for non-Arabic-speaking learners to generate a modern, cohesive, and comprehensible language.

Keywords: grammar, Arabic, functional, framework, problems, standards, statistical, popularity, analysis

Procedia PDF Downloads 87

Authors: Haodong Huang, Zida Zhao, Shilong Sun, Chiyao Li, Wenfu Xu

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The control methods for legged robots based on deep reinforcement learning have seen widespread application; however, the inherent black-box nature of neural networks presents challenges in understanding the decision-making motives of the robots. To address this issue, we propose a fully interpretable deep reinforcement learning training method to elucidate the underlying principles of legged robot motion. We incorporate the dynamics of legged robots into the policy, where observations serve as inputs and actions as outputs of the dynamics model. By embedding the dynamics equations within the multi-layer perceptron (MLP) computation process and making the parameters trainable, we enhance interpretability. Additionally, Bayesian optimization is introduced to train these parameters. We validate the proposed fully interpretable motion control algorithm on a legged robot, opening new research avenues for motion control and learning algorithms for legged robots within the deep learning framework.

Keywords: deep reinforcement learning, interpretation, motion control, legged robots

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Authors: Hamed Rahmani, Wim Groot

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The term "youth not in employment, education or training (NEET)" refers to a combination of youth unemployment and school dropout. This study investigates the variables that increase the risk of becoming NEET in Iran. A selection bias-adjusted Probit model was employed using machine learning to identify these risk factors. We used cross-sectional data obtained from the Statistical Centre of Iran and the Ministry of Cooperatives Labour and Social Welfare that was taken from the labour force survey conducted in the spring of 2021. We look at years of education, work experience, housework, the number of children under the age of six in the home, family education, birthplace, and the amount of land owned by households. Results show that hours spent performing domestic chores enhance the likelihood of youth becoming NEET, and years of education and years of potential work experience decrease the chance of being NEET. The findings also show that female youth born in cities were less likely than those born in rural regions to become NEET.

Keywords: NEET youth, probit, CART, machine learning, unemployment

Procedia PDF Downloads 106

Authors: Lenell D. Walton

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African American families have consistently contended that their child’s special education team does not provide the services necessary to meet their child’s academic goals. Special education teams must guide and mentor African American students and their families through the special education process. This qualitative study examined African American female caregivers' perceptions, experiences, and expectations regarding the special education process. Data collection methods utilized in the study included a survey, semi-structured interviews, and three focus groups. Data were analyzed and compared to identify themes. Three themes emerged from the survey: education and training, participation, and challenges. Six major themes emerged: (a) differences in treatment and cultural disconnect, (b) lack of support and resources, (c) participants’ experiences of the special education process, (d) parent participation, (e) barriers and concerns, and (f) expectations. Implications for policy and practice to improve the special education process are discussed.

Keywords: African American, caregivers, critical race theory, special education

Procedia PDF Downloads 105

Authors: I. Alhajri, G. Zahedi, R. Alazmi, A. Akbari

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In this paper, an Artificial Neural Network (ANN) was developed to predict Asphaltene Precipitation (AP) during the injection of carbon dioxide into crude oil reservoirs. In this study, the experimental data from six different oil fields were collected. Seventy percent of the data was used to develop the ANN model, and different ANN architectures were examined. A network with the Trainlm training algorithm was found to be the best network to estimate the AP. To check the validity of the proposed model, the model was used to predict the AP for the thirty percent of the data that was unevaluated. The Mean Square Error (MSE) of the prediction was 0.0018, which confirms the excellent prediction capability of the proposed model. In the second part of this study, the ANN model predictions were compared with modified Hirschberg model predictions. The ANN was found to provide more accurate estimates compared to the modified Hirschberg model. Finally, the proposed model was employed to examine the effect of different operating parameters during gas injection on the AP. It was found that the AP is mostly sensitive to the reservoir temperature. Furthermore, the carbon dioxide concentration in liquid phase increases the AP.

Keywords: artificial neural network, asphaltene, CO2 injection, Hirschberg model, oil reservoirs

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Authors: Tanya Anand, Arun Kandasamy, L. N. Suman

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Family based therapy for adolescent substance abuse has been studied to be effective in the West. Whereas, based on literature review, family therapy and interventions for adolescent substance abuse is still in its nascent stages in India. A multidimensional perspective to treatment has been indicated consistently in the Indian literature, but standardized therapy which addresses early substance abuse, from a social-ecological perspective has not been developed and studied for Indian population. While numerous researches have been conducted in India on the need of engaging the family in therapy for the purpose of symptom reduction, long-term maintenance of gains, and reducing family burnout, distress and dysfunction; a family based model in the Indian context has not been developed and tried, to the best of our knowledge. Hence, from the aim of building a model to treat adolescent substance abuse within the family context, experts in the area of mental health and deaddiction were interviewed to inform upon the clinical difficulties, challenges, uniqueness that Indian families present with. The integration of indigenous techniques that would be helpful in engaging families of young individuals with difficulties were also explored. Eight experts' who were interviewed, have 10-30 years of experience in working with families and substance users. An open-ended interview was conducted with the experts individually and audio-recorded. The interviews were then transcribed and subjected to qualitative analysis for building a framework and treatment guideline. Additionally, interviews with patients and their parents were conducted to elicit ‘felt needs’. The results of the analysis revealed culture-specific issues widely experienced within Indian families by adolescents and young adults, centering around the theme of Individuation versus collective identity and living. Substance abuse, in this framework, was found to be perceived as one of the maladaptive ways of the youth to disengage from the family and attempt at individuation and the responsibilities that are considered entitlements in the culture. On the other hand, interviews with family members revealed them to be engaging in inconsistent patterns of care and parenting. This was experienced and observed in terms of fostering interdependence within the family, sometimes within adverse socio-economic and societal conditions, where enacted and perceived stigma kept the individual and family members in a vicious loop of maladaptive coping patterns, dysfunctional family arrangements, and often leading to burnout with poor help seeking. The paper inform upon a framework that lays down the foundation for assessments, planning, case management and therapist competencies, required to address alcohol and drug issues in an Indian family context with such etiological factors at its heart. This paper will cover qualitative results of the interviews and present a model that may guide mental health professionals for treatment of adolescent substance use and family therapy.

Keywords: Indian families, family therapy, de-addiction, adolescent, youth, substance abuse, behavioral issues, felt needs, culture, etiology, model building, framework development, interviews

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Authors: Francisco Julio Batle Lorente

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The present paper aims at presenting a new category of role for academia: proactive creator/promoter of communities of practice in emerging areas of innovation. It is based in research among practitioners in three different areas: social entrepreneurship, alumni engaged in entrepreneurship and innovation, and digital nomads. The concept of CoP is related to an intentionally created space to share experiences and collectively reflect on the cases arising from practice. Such an endeavour is not contemplated in the literature on academic roles in an explicit way. The goal of the paper is providing a framework for this function and throw some light on the perception and priorities of members of emerging communities (78 alumni, 154 social entrepreneurs, and 231 digital nomads) regarding community, learning, engagement, and networking, areas in which the university can help and, by doing so, contributing to signal the emerging area and creating new opportunities for the academia. The research methodology was based in Survey research. It is a specific type of field study that involves the collection of data from a sample of elements drawn from a well-defined population through the use of a questionnaire. It was considered that survey research might be valuable to the present project and help outline the utility of various study designs and future projects with the emerging communities that are the object of the investigation. Open questions were used for different topics, as well as critical incident technique. It was used a standard technique for survey sampling and questionnaire design. Finally, it was defined a procedure for pretesting questionnaires and for data collection. The questionnaire was channelled by means of google forms. The results indicate that the members of emerging, innovative CoPs and learning such the ones that were selected for this investigation lack cohesion, inspiration, networking, opportunities for creation of social capital, opportunities for collaboration beyond their existing and close network. The opportunity that arises for the academia from proactively helping articulate CoP (and Communities of learning) are related to key elements of any CoP/ CoL: community construction approaches, technological infrastructure, benefits, participation issues and urgent challenges, trust, networking, technical ability/training/development and collaboration. Beyond training, other three areas (networking, collaboration and urgent challenges) were the ones in which the contribution of universities to the communities were considered more interesting and workable to practitioners. The analysis of the responses for the open questions related to perception of the universities offer options for terra incognita to be explored for universities (signalling new areas, establishing broader collaborations with research, government, media and corporations, attracting investment). Based on the findings from this research, there is some evidence that CoPs can offer a formal and informal method of professional and interprofessional development for member of any emerging and innovative community and can decrease social and professional isolation. The opportunity that it offers to academia can increase the entrepreneurial and engaged university identity. It also moves to academia into a realm of civic confrontation of present and future challenges in a more proactive way.

Keywords: social innovation, new roles of academia, community of learning, community of practice

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Authors: Ahmad Al Aboudi

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The Department of Archaeology at King Saud University conduct a long Term excavations since 2004 at the archaeological site of (Qurh) in Al-Ula area. The history of the site goes back to the eighth century AD. The main aim of the excavations is the training of the students on the archaeological field work associated with the scientific skills of exploring, surveying, classifying, documentations and other necessary in the field archaeology. During the 12th Season of Excavations, an area of 20 × 40 m2 of the site was excavated. The depth of the excavating the site was reached to 2-3 m. Many of the architectural features of a residential area in the northern part of the site were excavated this season. Circular walls made of mud-brick and a brick column drums and tiles made of clay were revealed this season. Additionally, lots of findings such as Gemstones, jars, ceramic plates, metal, glass, and fabric, as well as some jewelers and coins were discovered. This paper will deal with the main results of this field project including the architectural features and phenomena and their interpretations, the classification of excavated material culture remains and stratigraphy.

Keywords: Islamic architecture, Islamic art, excavations, early Islamic city

Procedia PDF Downloads 273

Authors: Elena Perepelova

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As the world approaches the 4th industrial revolution, income inequality has become one of the major societal concerns. Displacement of workers by technology becomes a reality, and in return, new skills and competencies are required. More important than ever, education needs to help individuals understand the wider world around them and make global connections. The author argues for the necessity to incorporate business, economics and finance studies as a part of primary education and offer access to business education to the general population with the primary objective to understand how the world functions. The paper offers a fresh look at existing business theory through an innovative program called 'Usefulnomics'. Realizing that the subject of Economics, Finance and Business are perceived as overwhelming for a large part of the population, the author has taken a holistic approach and created a program that simplifies the definitions of the existing concepts and shifts from the traditional breakdown into subjects and specialties to a teaching method that is based exclusively on real-life example case studies and group debates, in order to better grasp the concepts and put them into context. The paper findings are the result of a two-year project and experimental work with students from UK, USA, Malaysia, Russia, and Spain. The author conducted extensive research through on-line and in-person classes and workshops as well as in-depth interviews of primary and secondary grade students to assess their understanding of what is a business, how businesses operate and the role businesses play in their communities. The findings clearly indicate that students of all ages often understood business concepts and processes only in an intuitive way, which resulted in misconceptions and gaps in knowledge. While knowledge gaps were easier to identify and correct in primary school students, as students’ age increased, the learning process became distorted by career choices, political views, and the students’ actual (or perceived) economic status. While secondary school students recognized more concepts, their real understanding was often on par with upper primary school age students. The research has also shown that lack of correct vocabulary created a strong barrier to communication and real-life application or further learning. Based on these findings, each key business concept was practiced and put into context with small groups of students in order to design the content and format which would be well accepted and understood by the target group. As a result, the final learning program package was based on case studies from daily modern life and used a wide range of examples: from popular brands and well-known companies to basic commodities. In the final stage, the content and format were put into practice in larger classrooms. The author would like to share the key findings from the research, the resulting learning program as well as present new ideas on how the program could be further enriched and adapted so schools and organizations can deliver it.

Keywords: business, finance, economics, lifelong learning, XXI century skills

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Authors: Sanja Seljan, Ivan Dunđer

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The paper presents combined automatic speech recognition (ASR) for English and machine translation (MT) for English and Croatian in the domain of business correspondence. The first part presents results of training the ASR commercial system on two English data sets, enriched by error analysis. The second part presents results of machine translation performed by online tool Google Translate for English and Croatian and Croatian-English language pairs. Human evaluation in terms of usability is conducted and internal consistency calculated by Cronbach's alpha coefficient, enriched by error analysis. Automatic evaluation is performed by WER (Word Error Rate) and PER (Position-independent word Error Rate) metrics, followed by investigation of Pearson’s correlation with human evaluation.

Keywords: automatic machine translation, integrated language technologies, quality evaluation, speech recognition

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Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

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This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system

Procedia PDF Downloads 366