Search results for: flexibility training
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4653

Search results for: flexibility training

1773 Valorization of Gypsum as Industrial Waste

Authors: Hasna Soli

Abstract:

The main objective of this work is the extraction of sulfur from gypsum here is industrial waste. Indeed the sulfuric acid production, passing through the following process; melting sulfur, filtration of the liquid sulfur, sulfur combustion to produce SO₂, conversion of SO₂ to SO₃ and SO₃ absorption in water to produce H₂SO₄ product as waste CaSO₄ the anhydrous calcium sulfate. The main objectives of this work are improving the industrial practices and to find other ways to manage these solid wastes. It should also assess the consequences of treatment in terms of training and become byproducts. Firstly there will be a characterization of this type of waste by an X-ray diffraction; to obtain phase solid compositions and chemical analysis; gravimetrically and atomic absorption spectrometry or by ICP. The samples are mineralized in suitable acidic or basic solutions. The elements analyzed are CaO, Sulfide (SO₃), Al₂O₃, Fe₂O₃, MgO, SiO₂. Then an analysis by EDS energy dispersive spectrometry using an Oxford EDX probe and differential thermal and gravimetric analyzes. Gypsum’s valuation will be performed. Indeed, the CaSO₄ will be reused to produce sulfuric acid, which will be reintroduced into the production line. The second approach explored in this work is the thermal utilization of solid waste to remove sulfur as a dilute sulfuric acid solution.

Keywords: environment, gypsum, sulfur, waste

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1772 The Mission Slimpossible Program: Dietary and Physical Activity Intervention to Combat Obesity among University Students in UITM Puncak Alam

Authors: Kartini Ilias, Nabilah Md Ahir, Nor Zafirah Ab Rahman, Safiah Md Yusof, Nuri Naqieyah Radzuan, Siti Sabariah Buhari

Abstract:

This study aim to develop and assess the effectiveness of an intervention in improving eating habits and physical activity level of university students of UiTM Puncak Alam. The intervention consists of weekly dietary counselling by registered dietitian and high-intensity interval training (HIIT) for three times per week for the duration of 8 weeks. A total of 25 students from the intervention group and 25 students from control group who had BMI equal to or greater than 25kg/m² participated in the study. The results showed a significant reduction in body weight (3.0 kg), body fat percentage (7.9 %), waist circumference (7.3 cm) and BMI (2.9 kg/m²) between pre and post intervention. Besides, there was a significant increase in the level of physical activity among subjects in intervention group. In conclusion, the intervention made an impact on eating habit, physical activity level and improves weight status of the students. It is expected that the intervention could be adopted and implemented by the government and private sector as well as policy-makers in formulating obesity intervention.

Keywords: obesity, diet, obesity intervention, physical activity

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1771 A Theoretical Analysis on the Controversial Issue of Teaching Professional in the Institutionalized Perspective

Authors: Tien-Hui Chiang, Q. Zhou

Abstract:

For structural-functionalism, one set of the common traits of traditional professionals, such as medical practitioners and engineers, can be viewed as the criteria for evaluating whether a given occupation has the right of claiming its professional status or not. Under the influence of this professionalism, teaching practitioners have devoted themselves to acquiring this right as evidenced by the fact that initial training has been extended to even the level of postgraduate. However, for interactionalists, professionalism adopts a predetermined assumption so that it ignores the dynamic nature of social development, which is able to regulate the professional status of a given occupation. Such an interactive approach highlights the concept of professionalization. Furthermore, Marxists argue that structural-functionalists have ignored the impact of proletarianization on the white collar. While professionals gradually lose their control over their practices, the title of profession functions as a self-regulated icon that prevents them from collaborating with the working class and, in turn, creates the ideology of de-politicization sustaining the interests of the ruling class. This article adopts a theoretical analysis on these contradictory arguments. It argues that these criticisms neglect the influence of the institutionalized value system on social operation, which is the core element in sustaining the notion of the profession.

Keywords: teaching profession, professionalism, professionalization, proletarianialization, institutionalized value system

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1770 Emotion Recognition Using Artificial Intelligence

Authors: Rahul Mohite, Lahcen Ouarbya

Abstract:

This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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1769 Computer-Aided Diagnosis of Polycystic Kidney Disease Using ANN

Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

Abstract:

Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

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1768 An Innovative Auditory Impulsed EEG and Neural Network Based Biometric Identification System

Authors: Ritesh Kumar, Gitanjali Chhetri, Mandira Bhatia, Mohit Mishra, Abhijith Bailur, Abhinav

Abstract:

The prevalence of the internet and technology in our day to day lives is creating more security issues than ever. The need for protecting and providing a secure access to private and business data has led to the development of many security systems. One of the potential solutions is to employ the bio-metric authentication technique. In this paper we present an innovative biometric authentication method that utilizes a person’s EEG signal, which is acquired in response to an auditory stimulus,and transferred wirelessly to a computer that has the necessary ANN algorithm-Multi layer perceptrol neural network because of is its ability to differentiate between information which is not linearly separable.In order to determine the weights of the hidden layer we use Gaussian random weight initialization. MLP utilizes a supervised learning technique called Back propagation for training the network. The complex algorithm used for EEG classification reduces the chances of intrusion into the protected public or private data.

Keywords: EEG signal, auditory evoked potential, biometrics, multilayer perceptron neural network, back propagation rule, Gaussian random weight initialization

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1767 The Effect of Acute Creatine Supplementation on Physiological Variables of Continuous and Intermittent Soccer Activities of Men Soccer Players

Authors: Abdolrasoul Daneshjoo

Abstract:

The aim of this study was studying the effect of acute creatine supplementation on physiological variables of continuous and intermittent soccer activities of men soccer players. 32 soccer players from Tarbiat Moalem University aged (22/3+-1/6) volunteered for this research and were divided into two groups randomly. Both experimental and control groups after 6 days taking supplementation were tested. For measuring height and weight meter and balance were used. Questionnaire for health background, lactate electro, heart beat measuring polar electro, continuous and intermittent training program and time recorder were used for data collection. For data analysis descriptive statistical techniques, two-way ANOVA and F test were used. The result of this study showed increased significantly in heart rate in control group. For control group heart beat was (71/6 +- 3/5) and for experimental group it was (75/3 +- 4/9). No significant differences were observed in players weight after taking creatine.

Keywords: heartbeat, lactate Blood, creatine, soccer players of Tarbiat Moalem University

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1766 Performants: A Digital Event Manager-Organizer

Authors: Ioannis Andrianakis, Manolis Falelakis, Maria Pavlidou, Konstantinos Papakonstantinou, Ermioni Avramidou, Dimitrios Kalogiannis, Nikolaos Milios, Katerina Bountakidou, Kiriakos Chatzidimitriou, Panagiotis Panagiotopoulos

Abstract:

Artistic events, such as concerts and performances, are challenging to organize because they involve many people with different skill sets. Small and medium venues often struggle to afford the costs and overheads of booking and hosting remote artists, especially if they lack sponsors or subsidies. This limits the opportunities for both venues and artists, especially those outside of big cities. However, more and more research shows that audiences prefer smaller-scale events and concerts, which benefit local economies and communities. To address this challenge, our project “PerformAnts: Digital Event Manager-Organizer” aims to develop a smart digital tool that automates and optimizes the processes and costs of live shows and tours. By using machine learning, applying best practices and training users through workshops, our platform offers a comprehensive solution for a growing market, enhances the mobility of artists and the accessibility of venues and allows professionals to focus on the creative aspects of concert production.

Keywords: event organization, creative industries, event promotion, machine learning

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1765 A Qualitative Case Study Exploring Zambian Mathematics Teachers' Content Knowledge of Functions

Authors: Priestly Malambo, Sonja Van Putten, Hanlie Botha, Gerrit Stols

Abstract:

The relevance of what is content is taught in tertiary teacher training has long been in question. This study attempts to understand how advanced mathematics courses equip student teachers to teach functions at secondary school level. This paper reports on an investigation that was conducted in an African university, where preservice teachers were purposefully selected for participation in individual semi-structured interviews after completing a test on functions as taught at secondary school. They were asked to justify their reasoning in the test and to explain functions in a way that might bring about understanding of the topic in someone who did not know how functions work. These were final year preservice mathematics teachers who had studied advanced mathematics courses for three years. More than 50% of the students were not able to explain concepts or to justify their reasoning about secondary school functions in a coherent way. The results of this study suggest that the study of advanced mathematics does not automatically enable students to teach secondary school functions, and that, although these students were able to do advanced mathematics, they were unable to explain the working of functions in a way that would allow them to teach this topic successfully.

Keywords: secondary school, mathematical reasoning, student-teachers, functions

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1764 Management Competency in Logistical Function: The Skills That Will Master a Logistical Manager

Authors: Fatima Ibnchahid

Abstract:

Competence approach is considered, since the early 80's as one of the major development of HR policies. Many approaches to manage the professional skills were declined. Some processes are mature whereas the others have been abandoned. Competence can be defined as the set of knowledge (theoretical and practical), know-how (experience) and life skills (personality traits) mobilized by a person in the company. The skills must master a logistics manager are divided into two main categories: depending on whether technical skills, or managerial skills and human. The firsts are broken down into skills on logistical techniques and on general skills in business, seconds in social skills (self with others) and personal (with oneself). Logisticians are faced with new challenges and new constraints that are revolutionizing the way to treat the physical movement of goods and operations related to information flows that trigger, they control and guide the physical movements of these major changes, we can mention the development of information technology and communication, the emergence of strong environmental and security constraints. These changes have important effects on the skills needs of the members of the logistical function and sensitive development for training requested by logistical managers to perform better in their job changes. In this article, we will address two main points, first, a brief overview of the management skills and secondly answer the question asked in the title of the article to know what are the skills that will master a logistical manager.

Keywords: skills, competence, management, logistical function

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1763 The Capacity of Mel Frequency Cepstral Coefficients for Speech Recognition

Authors: Fawaz S. Al-Anzi, Dia AbuZeina

Abstract:

Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: speech recognition, acoustic features, mel frequency, cepstral coefficients

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1762 Petra: Simplified, Scalable Verification Using an Object-Oriented, Compositional Process Calculus

Authors: Aran Hakki, Corina Cirstea, Julian Rathke

Abstract:

Formal methods are yet to be utilized in mainstream software development due to issues in scaling and implementation costs. This work is about developing a scalable, simplified, pragmatic, formal software development method with strong correctness properties and guarantees that are easy prove. The method aims to be easy to learn, use and apply without extensive training and experience in formal methods. Petra is proposed as an object-oriented, process calculus with composable data types and sequential/parallel processes. Petra has a simple denotational semantics, which includes a definition of Correct by Construction. The aim is for Petra is to be standard which can be implemented to execute on various mainstream programming platforms such as Java. Work towards an implementation of Petra as a Java EDSL (Embedded Domain Specific Language) is also discussed.

Keywords: compositionality, formal method, software verification, Java, denotational semantics, rewriting systems, rewriting semantics, parallel processing, object-oriented programming, OOP, programming language, correct by construction

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1761 A Framework of Virtualized Software Controller for Smart Manufacturing

Authors: Pin Xiu Chen, Shang Liang Chen

Abstract:

A virtualized software controller is developed in this research to replace traditional hardware control units. This virtualized software controller transfers motion interpolation calculations from the motion control units of end devices to edge computing platforms, thereby reducing the end devices' computational load and hardware requirements and making maintenance and updates easier. The study also applies the concept of microservices, dividing the control system into several small functional modules and then deploy into a cloud data server. This reduces the interdependency among modules and enhances the overall system's flexibility and scalability. Finally, with containerization technology, the system can be deployed and started in a matter of seconds, which is more efficient than traditional virtual machine deployment methods. Furthermore, this virtualized software controller communicates with end control devices via wireless networks, making the placement of production equipment or the redesign of processes more flexible and no longer limited by physical wiring. To handle the large data flow and maintain low-latency transmission, this study integrates 5G technology, fully utilizing its high speed, wide bandwidth, and low latency features to achieve rapid and stable remote machine control. An experimental setup is designed to verify the feasibility and test the performance of this framework. This study designs a smart manufacturing site with a 5G communication architecture, serving as a field for experimental data collection and performance testing. The smart manufacturing site includes one robotic arm, three Computer Numerical Control machine tools, several Input/Output ports, and an edge computing architecture. All machinery information is uploaded to edge computing servers and cloud servers via 5G communication and the Internet of Things framework. After analysis and computation, this information is converted into motion control commands, which are transmitted back to the relevant machinery for motion control through 5G communication. The communication time intervals at each stage are calculated using the C++ chrono library to measure the time difference for each command transmission. The relevant test results will be organized and displayed in the full-text.

Keywords: 5G, MEC, microservices, virtualized software controller, smart manufacturing

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1760 Fatigue Life Estimation Using N-Code for Drive Shaft of Passenger Vehicle

Authors: Tae An Kim, Hyo Lim Kang, Hye Won Han, Seung Ho Han

Abstract:

The drive shaft of passenger vehicle has its own function such as transmitting the engine torque from the gearbox and differential gears to the wheels. It must also compensate for all variations in angle or length resulting from manoeuvring and deflection for perfect synchronization between joints. Torsional fatigue failures occur frequently at the connection parts of the spline joints in the end of the drive shaft. In this study, the fatigue life of a drive shaft of passenger vehicle was estimated by using the finite element analysis. A commercial software of n-Code was applied under twisting load conditions, i.e. 0~134kgf•m and 0~188kgf•m, in which the shear strain range-fatigue life relationship considering Signed Shear method, Smith-Watson-Topper equation, Neuber-Hoffman Seeger method, size sensitivity factor and surface roughness effect was taken into account. The estimated fatigue life was verified by a twisting load test of the real drive shaft in a test rig. (Human Resource Training Project for Industry Matched R & D, KIAT, N036200004).

Keywords: drive shaft, fatigue life estimation, passenger vehicle, shear strain range-fatigue life relationship, torsional fatigue failure

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1759 Shifted Window Based Self-Attention via Swin Transformer for Zero-Shot Learning

Authors: Yasaswi Palagummi, Sareh Rowlands

Abstract:

Generalised Zero-Shot Learning, often known as GZSL, is an advanced variant of zero-shot learning in which the samples in the unseen category may be either seen or unseen. GZSL methods typically have a bias towards the seen classes because they learn a model to perform recognition for both the seen and unseen classes using data samples from the seen classes. This frequently leads to the misclassification of data from the unseen classes into the seen classes, making the task of GZSL more challenging. In this work of ours, to solve the GZSL problem, we propose an approach leveraging the Shifted Window based Self-Attention in the Swin Transformer (Swin-GZSL) to work in the inductive GSZL problem setting. We run experiments on three popular benchmark datasets: CUB, SUN, and AWA2, which are specifically used for ZSL and its other variants. The results show that our model based on Swin Transformer has achieved state-of-the-art harmonic mean for two datasets -AWA2 and SUN and near-state-of-the-art for the other dataset - CUB. More importantly, this technique has a linear computational complexity, which reduces training time significantly. We have also observed less bias than most of the existing GZSL models.

Keywords: generalised, zero-shot learning, inductive learning, shifted-window attention, Swin transformer, vision transformer

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1758 Determining the Effectiveness of Positive Psychology Education on Social Welfare of High School Girls with Premenstrual Syndrome (PMS)

Authors: Alireza Monzavi Chaleshtari, Mahnaz Aliakbari Dehkordi, Mina Gholampour, Majid Saffarinia, Tayebeh Mohtashami, Amin Asadi Hieh

Abstract:

The study aimed to assess the impact of positive psychology education on the social well-being of high school girls experiencing premenstrual syndrome (PMS). The statistical population comprised high school girls with PMS, with 30 randomly selected participants divided into two groups: 15 in the experimental group and 15 in the control group. The research employed a pre-test and post-test design using a standard questionnaire to evaluate premenstrual syndrome symptoms over a 7-day period before menstruation to a maximum of 2 days after menstruation, along with the Social Keys welfare questionnaire. During the study, the experimental group underwent an 8-session positive psychology group program. Data analysis was conducted using analysis of covariance. The results indicated a significant positive effect of positive psychology training on enhancing the social well-being of girls (p < 0.05). In conclusion, the findings suggest that positive psychology interventions can effectively increase social well-being among high school girls experiencing premenstrual syndrome.

Keywords: positive psychology, premenstrual syndrome, social welfare, girls

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1757 Mapping Iron Content in the Brain with Magnetic Resonance Imaging and Machine Learning

Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

Abstract:

Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

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1756 Access to Climate Change Information Through the Implementation of the Paris Agreement

Authors: Ana Cristina A. P. Carvalho, Solange Teles Da Silva

Abstract:

In April, 174 countries signed the Paris Agreement, a multilateral agreement on climate change which deals with greenhouse gas emissions, mitigation, adaptation, finance, access to information, transparency, among other subjects related to the environment. Since then, Parties shall cooperate in taking measures, as appropriate, to enhance climate change education, training, public awareness, public participation and public access to information, recognizing the importance of these steps with respect to enhancing actions under this Agreement. This paper aims to analyze the consequences of this new rule in terms of the implementation of the Agreement, collecting data from Brazilian and Canadian legislations in order to identify if these countries have rules complying with the Treaty, the steps that have been already taken and if they could be used as examples for other countries. The analysis will take into consideration the different kinds of climate change information, means of transparency, reliability of the data and how to spread the information. The methodology comprehends a comparative legal research based on both the Paris Agreement and domestic laws of Brazil and Canada, as well as on doctrine and Court decisions. The findings can contribute to the implementation of the Paris Agreement through compliance with this Treaty at countries’ domestic and policy level.

Keywords: climate change information, domestic legislation, Paris Agreement, public policy

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1755 Automating 2D CAD to 3D Model Generation Process: Wall pop-ups

Authors: Mohit Gupta, Chialing Wei, Thomas Czerniawski

Abstract:

In this paper, we have built a neural network that can detect walls on 2D sheets and subsequently create a 3D model in Revit using Dynamo. The training set includes 3500 labeled images, and the detection algorithm used is YOLO. Typically, engineers/designers make concentrated efforts to convert 2D cad drawings to 3D models. This costs a considerable amount of time and human effort. This paper makes a contribution in automating the task of 3D walls modeling. 1. Detecting Walls in 2D cad and generating 3D pop-ups in Revit. 2. Saving designer his/her modeling time in drafting elements like walls from 2D cad to 3D representation. An object detection algorithm YOLO is used for wall detection and localization. The neural network is trained over 3500 labeled images of size 256x256x3. Then, Dynamo is interfaced with the output of the neural network to pop-up 3D walls in Revit. The research uses modern technological tools like deep learning and artificial intelligence to automate the process of generating 3D walls without needing humans to manually model them. Thus, contributes to saving time, human effort, and money.

Keywords: neural networks, Yolo, 2D to 3D transformation, CAD object detection

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1754 Flexible, Hydrophobic and Mechanical Strong Poly(Vinylidene Fluoride): Carbon Nanotube Composite Films for Strain-Sensing Applications

Authors: Sudheer Kumar Gundati, Umasankar Patro

Abstract:

Carbon nanotube (CNT) – polymer composites have been extensively studied due to their exceptional electrical and mechanical properties. In the present study, poly(vinylidene fluoride) (PVDF) – multi-walled CNT composites were prepared by melt-blending technique using pristine (ufCNT) and a modified dilute nitric acid-treated CNTs (fCNT). Due to this dilute acid-treatment, the fCNTs were found to show significantly improved dispersion and retained their electrical property. The fCNT showed an electrical percolation threshold (PT) of 0.15 wt% in the PVDF matrix as against 0.35 wt% for ufCNT. The composites were made into films of thickness ~0.3 mm by compression-molding and the resulting composite films were subjected to various property evaluations. It was found that the water contact angle (WCA) of the films increased with CNT weight content in composites and the composite film surface became hydrophobic (e.g., WCA ~104° for 4 wt% ufCNT and 111.5° for 0.5 wt% fCNT composites) in nature; while the neat PVDF film showed hydrophilic behavior (WCA ~68°). Significant enhancements in the mechanical properties were observed upon CNT incorporation and there is a progressive increase in the tensile strength and modulus with increase in CNT weight fraction in composites. The composite films were tested for strain-sensing applications. For this, a simple and non-destructive method was developed to demonstrate the strain-sensing properties of the composites films. In this method, the change in electrical resistance was measured using a digital multimeter by applying bending strain by oscillation. It was found that by applying dynamic bending strain, there is a systematic change in resistance and the films showed piezo-resistive behavior. Due to the high flexibility of these composite films, the change in resistance was reversible and found to be marginally affected, when large number of tests were performed using a single specimen. It is interesting to note that the composites with CNT content notwithstanding their type near the percolation threshold (PT) showed better strain-sensing properties as compared to the composites with CNT contents well-above the PT. On account of the excellent combination of the various properties, the composite films offer a great promise as strain-sensors for structural health-monitoring.

Keywords: carbon nanotubes, electrical percolation threshold, mechanical properties, poly(vinylidene fluoride), strain-sensor, water contact angle

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1753 The Convergence of IoT and Machine Learning: A Survey of Real-time Stress Detection System

Authors: Shreyas Gambhirrao, Aditya Vichare, Aniket Tembhurne, Shahuraj Bhosale

Abstract:

In today's rapidly evolving environment, stress has emerged as a significant health concern across different age groups. Stress that isn't controlled, whether it comes from job responsibilities, health issues, or the never-ending news cycle, can have a negative effect on our well-being. The problem is further aggravated by the ongoing connection to technology. In this high-tech age, identifying and controlling stress is vital. In order to solve this health issue, the study focuses on three key metrics for stress detection: body temperature, heart rate, and galvanic skin response (GSR). These parameters along with the Support Vector Machine classifier assist the system to categorize stress into three groups: 1) Stressed, 2) Not stressed, and 3) Moderate stress. Proposed training model, a NodeMCU combined with particular sensors collects data in real-time and rapidly categorizes individuals based on their stress levels. Real-time stress detection is made possible by this creative combination of hardware and software.

Keywords: real time stress detection, NodeMCU, sensors, heart-rate, body temperature, galvanic skin response (GSR), support vector machine

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1752 Evaluation of the Curricular Content Domain Related to Topics of Human Sexuality in Teachers of Public Elementary Schools

Authors: Ahmed Ali Asadi, Julio R. Martinez-Alvarado, Claudia V. Camacho-Guevara, J. Jesus Cabrales-Ruvalcaba, Julieta Y. Islas-Limon, Bertha M. Viñas-Velazquez

Abstract:

The transformation of education in Mexico incorporates human sexuality subjects in its study plans for elementary education level, leaving aside the training of teachers to educate on such topics. The objective of this study was to evaluate the curricular content domain related to human sexuality subjects of public elementary school teachers in Mexico. For this, a transversal descriptive-prospective study with a quantitative focus has been conducted. The population for this study consisted of 109 fifth and sixth-grade teachers from a school zone of the State Education System. It was found in the results that fifth-grade teachers got a low achievement level, sixth-grade teachers got a medium achievement level, while teachers who give classes on both grades obtained a high achievement level on domain of curricular subjects related to sexuality. Likewise, a relation of different variables with the participant’s achievement level is exposed.

Keywords: curricular content, evaluation, sexual education, teacher

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1751 Increased Efficiency during Oxygen Carrier Aided Combustion of Municipal Solid Waste in an Industrial Scaled Circulating Fluidized Bed-Boiler

Authors: Angelica Corcoran, Fredrik Lind, Pavleta Knutsson, Henrik Thunman

Abstract:

Solid waste volumes are at current predominately deposited on landfill. Furthermore, the impending climate change requires new solutions for a sustainable future energy mix. Currently, solid waste is globally utilized to small extent as fuel during combustion for heat and power production. Due to its variable composition and size, solid waste is considered difficult to combust and requires a technology with high fuel flexibility. One of the commercial technologies used for combustion of such difficult fuels is circulating fluidized beds (CFB). In a CFB boiler, fine particles of a solid material are used as 'bed material', which is accelerated by the incoming combustion air that causes the bed material to fluidize. The chosen bed material has conventionally been silica sand with the main purpose of being a heat carrier, as it transfers heat released by the combustion to the heat-transfer surfaces. However, the release of volatile compounds occurs rapidly in comparison with the lateral mixing in the combustion chamber. To ensure complete combustion a surplus of air is introduced, which decreases the total efficiency of the boiler. In recent years, the concept of partly or entirely replacing the silica sand with an oxygen carrier as bed material has been developed. By introducing an oxygen carrier to the combustion chamber, combustion can be spread out both temporally and spatially in the boiler. Specifically, the oxygen carrier can take up oxygen from the combustion air where it is in abundance and release it to combustible gases where oxygen is in deficit. The concept is referred to as oxygen carrier aided combustion (OCAC) where the natural ore ilmenite (FeTiO3) has been the oxygen carrier used. The authors have validated the oxygen buffering ability of ilmenite during combustion of biomass in Chalmers 12-MWth CFB boiler in previous publications. Furthermore, the concept has been demonstrated on full industrial scale during combustion of municipal solid waste (MSW) in E.ON’s 75 MWth CFB boiler. The experimental campaigns have showed increased mass transfer of oxygen inside the boiler when combustion both biomass and MSW. As a result, a higher degree of burnout is achieved inside the combustion chamber and the plant can be operated at a lower surplus of air. Moreover, the buffer of oxygen provided by the oxygen carrier makes the system less sensitive to disruptions in operation. In conclusion, combusting difficult fuels with OCAC results in higher operation stability and an increase in boiler efficiency.

Keywords: OCAC, ilmenite, combustion, CFB

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1750 A Corpus-Assisted Discourse Analysis of Adjectival Collocation of the Word 'Education' in the American Context

Authors: Ngan Nguyen

Abstract:

The study analyses adjectives collocating with the word ‘education’ in the American language of the Corpus of Global Web-based English using a combination of corpus linguistic and discourse analytical methods to examine not only language patterns but also social political ideologies around the topic. Significant conclusions are deduced: (1) there are a large number of adjectival collocates of the word education which have been identified and classified into four categories representing four different aspects of education: level, quality, forms and types of education; (2) education, as in combination with three first categories, carries the meaning as the act and process of teaching and learning while with the last category having the meaning of a particular kind of teaching or training; (3) higher education is the topic that gains most concerns from the American public; (4) five most significant ideologies are discovered from the corpus: higher education associates with financial affairs, higher education is an industry, monetary policy of the government on higher education, people require greater accessibility to higher education and people value higher education. The study contributes to the field of developing meanings of words through corpus analysis and the field of discourse analysis.

Keywords: adjectival collocation, American context, corpus linguistics, discourse analysis, education

Procedia PDF Downloads 319
1749 Reflections of Young Language Learners’ and Teacher Candidates’ for ‘Easy English’ Project

Authors: F. Özlem Saka

Abstract:

There should be connections between universities and state schools in order to improve the quality of instruction. ELT department of Akdeniz University carries out a project named ‘Easy English’ with a state primary school in Antalya for 2 years. According to the Project requirements, junior students at university teach English to 3rd grade primary school students during the term. They are supposed to teach the topics planned before, preparing different activities for the students. This study reflects the ideas of both students at university and at state school related to the language programme carried out. Their ideas have been collected with a questionnaire consisting of similar structured questions. The result shows that both groups like the programme and evaluate it from their own perspectives. It is believed the efficient results of this project will lead to planning similar programmes for different levels. From this study, curriculum planners and teachers can get ideas to improve language teaching at primary level as both university students, being the teachers in the project and students at state primary school have positive feelings and thoughts about it.

Keywords: foreign language teacher training, games in English teaching, songs in English teaching, teaching English to young learners

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1748 Relationship between Smartphone Addiction and Academic Performance among University Students

Authors: Arooba Azam Khan

Abstract:

The present study aims to focus on the relationship between smartphone addiction and academic performance of students along with social networking sites, overuse of smartphone, GPA’s and time management skills as their sub-variables. In this world of technology, the smartphone becomes a vital part of everyone’s life. The addiction of smartphones has both negative and positive impact on young people (students). Students keep themselves busy with smartphones without noticing that smartphone addiction is creating a negative impact on their social, academic, and personal lives. A quantitative approach was used to collect data through questionnaire from 360 students of two private universities in Pakistan in summer 2017. The target age group was 19-24 studying in Bachelors programmes. Data were analyzed by using SPSS (version 20), linear correlation and regression tests were applied. Results reveal that there is a negative relationship between smartphone addiction and academic performance. Moreover, it has been proved that students with good time management skills achieve high grades/GPA’s than those who have poor time management skills. From the findings, the researcher suggests that students should spend their time wisely and use their smartphones for educational purpose. However, students need training and close monitoring to get benefits out of smartphones use.

Keywords: smartphone addiction, academic performance, time management skills, quantitative research

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1747 Virtual Reality Tilt Brush for Creativity: An Experimental Study among Architecture Students

Authors: Christena Stephen, Biju Kunnumpurath

Abstract:

This study intends to comprehend the effect of the Tilt Brush (TB) Virtual Reality 3D Painting application on creativity among final year architecture students. The research was done over the course of 30 hours and evaluated the performance of a group of 20 university students. Using a Structured Observation Form (SOF), the researcher assessed the research's progress. Four recently graduated artists, educators, and researchers used a Rubric to assess student designs. During the training, the study group was instructed in the fundamentals of virtual Reality, design principles, and TB. The design process, which began with the construction of a 3D design, progressed with the addition of texture, color, and script to items and culminated in the creation of a finished project. The group in the design process is rated as "Good" by the researcher based on feedback from SOF. The creativity evaluation rubric used by the experts rates their work as "Accomplished." According to the researcher's assessment, the group received a "Good" rating. Based on these findings, it can be said that including virtual reality 3D painting in the curriculum for art and design classes will help students improve their imagination and creativity as well as their 21st-century skills in education.

Keywords: creativity, virtual reality, 3D painting, tilt brush, education

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1746 Farmers’ Perceptions of Extension Personnel’s Technical Capabilities: Evidence from India

Authors: Ankit Nagar, Dinesh Kumar Nauriyal, S. P. Singh

Abstract:

This paper examines farmers' perceptions of the efficacy of extension services in equipping them with the necessary information and skills required to maximise agricultural productivity. It is based on primary data collected through an interview schedule in India's Western Uttar Pradesh region. It uses descriptive statistics, factor analysis, and MANOVA to determine the typical farmer's view of an extension worker's technical prowess and behavioural traits, as well as the key factors associated with farmers' perception and the demographic characteristics that affect farmer's perception variations. The vast majority of farmers appear to consider extension personnel's efficiency and accessibility unfavourably. Farmers feel that extension personnel are well-trained notwithstanding their disagreements on the viability of their technical advice. Small and marginal farmers view the effectiveness, objectivity, and cooperativeness of extension agents less favourably than large farmers. This study proposes strategies such as routine follow-ups, practical demonstrations, and regular extension professional training camps as part of a holistic plan to increase farmer trust in the agricultural extension system. In addition, it proposes ensuring their accountability.

Keywords: agriculture extension, farmers’ perception, extension agents, factor analysis

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1745 Collaborative Writing on Line with Apps During the Time of Pandemic: A Systematic Literature Review

Authors: Giuseppe Liverano

Abstract:

Today’s school iscalledupon to take the lead role in supporting students towards the formation of conscious identity and a sense of responsible citizenship, through the development of key competencies for lifelong learning A rolethatrequiresit to be ready for change and to respond to the ever new needs of students, by adopting new pedagogical and didactic models and new didactic devices. Information and Communication Technologies, in this sense, reveal themselves to be usefulresourcesthatpermit to focus attention on the learning of eachindividualstudentunderstoodas a dynamic and relational process of constructing shared and participatedmeanings. The use of collaborative writing apps represents a democratic and shared knowledge way of constructionthroughICTs. It promotes the learning of reading-writing, literacy, and the development of transversal competencies in an inclusive perspective peer-to-peer comparison and reflectionthatstimulates the transfer of thought into speech and writing, the transformation of knowledge through a trialogicalapproach to learning generates enthusiasm and strengthensmotivationItrepresents a “different” way of expressing the training needs which come from several disciplinary fields of subjects with different cultures. The contribution aims to reflect on the formative value of collaborative writing through apps and analyse some proposals on line at school during the time of pandemic in order to highlight their critical aspects and pedagogical perspectives.

Keywords: collaborative writing, formative value, online, apps, pandemic

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1744 The Staff Performance Efficiency of the Faculty of Management Science, Suan Sunandha Rajabhat University

Authors: Nipawan Tharasak, Ladda Hirunyava

Abstract:

The objective of the research was to study factors affecting working efficiency and the relationship between working environment, satisfaction to human resources management and operation employees’ working efficiency of Faculty of Management Science, Suan Sunandha Rajabhat University. The sample size of the research was based on 33 employees of Faculty of Management Science. The researcher had classified the support employees into 4 divisions by using Stratified Random Sampling. Individual sample was randomized by using Simple Random Sampling. Data was collected through the instrument. The Statistical Package for the Windows was utilized for data processing. Percentage, mean, standard deviation, the t-test, One-way ANOVA, and Pearson product moment correlation coefficient were applied. The result found the support employees’ satisfaction in human resources management of Faculty of Management Science in following areas: remuneration; employee recruitment & selection; manpower planning; performance evaluation; staff training & developing; and spirit & fairness were overall in good level.

Keywords: faculty of management science, operational factors, practice performance, staff working

Procedia PDF Downloads 219