Search results for: machine readable format

Authors: Glaoui Hachemi

Abstract:

Wind has been proven as a cost effective and reliable energy source. Technological advancements over the last years have placed wind energy in a firm position to compete with conventional power generation technologies. Algeria has a vast uninhabited land area where the south (desert) represents the greatest part with considerable wind regime. In this paper, an analysis of wind energy utilization as a viable energy substitute in six selected sites widely distributed all over the south of Algeria is presented. In this presentation, wind speed frequency distributions data obtained from the Algerian Meteorological Office are used to calculate the average wind speed and the available wind power. The annual energy produced by the Fuhrlander FL 30 wind machine is obtained using two methods. The analysis shows that in the southern Algeria, at 10 m height, the available wind power was found to vary between 160 and 280 W/m2, except for Tamanrasset. The highest potential wind power was found at Adrar, with 88 % of the time the wind speed is above 3 m/s. Besides, it is found that the annual wind energy generated by that machine lie between 33 and 61 MWh, except for Tamanrasset, with only 17 MWh. Since the wind turbines are usually installed at a height greater than 10 m, an increased output of wind energy can be expected. However, the wind resource appears to be suitable for power production on the south and it could provide a viable substitute to diesel oil for irrigation pumps and electricity generation. In this paper, a model of the wind turbine (WT) with permanent magnet generator (PMSG) and its associated controllers is presented. The increase of wind power penetration in power systems has meant that conventional power plants are gradually being replaced by wind farms. In fact, today wind farms are required to actively participate in power system operation in the same way as conventional power plants. In fact, power system operators have revised the grid connection requirements for wind turbines and wind farms, and now demand that these installations be able to carry out more or less the same control tasks as conventional power plants. For dynamic power system simulations, the PMSG wind turbine model includes an aerodynamic rotor model, a lumped mass representation of the drive train system and generator model. In this paper, we propose a model with an implementation in MATLAB / Simulink, each of the system components off-grid small wind turbines.

Keywords: windgenerator systems, permanent magnet synchronous generator (PMSG), wind turbine (WT) modeling, MATLAB simulink environment

Procedia PDF Downloads 326

Authors: Shayli Varasteh Moradi, Wayne A. Johnston, Dejan Gagoski, Kirill Alexandrov

Abstract:

The demand for a rapid and more efficient technique to identify protein-protein interaction particularly in the areas of therapeutics and diagnostics development is growing. The method described here is a rapid in vitro protein-protein interaction analysis approach based on AlphaLISA technology combined with Leishmania tarentolae cell-free protein production (LTE) system. Cell-free protein synthesis allows the rapid production of recombinant proteins in a multiplexed format. Among available in vitro expression systems, LTE offers several advantages over other eukaryotic cell-free systems. It is based on a fast growing fermentable organism that is inexpensive in cultivation and lysate production. High integrity of proteins produced in this system and the ability to co-express multiple proteins makes it a desirable method for screening protein interactions. Following the translation of protein pairs in LTE system, the physical interaction between proteins of interests is analysed by AlphaLISA assay. The assay is performed using unpurified in vitro translation reaction and therefore can be readily multiplexed. This approach can be used in various research applications such as epitope mapping, antigen-antibody analysis and protein interaction network mapping. The intra-viral protein interaction network of Zika virus was studied using the developed technique. The viral proteins were co-expressed pair-wise in LTE and all possible interactions among viral proteins were tested using AlphaLISA. The assay resulted to the identification of 54 intra-viral protein-protein interactions from which 19 binary interactions were found to be novel. The presented technique provides a powerful tool for rapid analysis of protein-protein interaction with high sensitivity and throughput.

Keywords: AlphaLISA technology, cell-free protein expression, epitope mapping, Leishmania tarentolae, protein-protein interaction

Procedia PDF Downloads 228

Authors: D. Habibinia, M. R. Feyzi

Abstract:

Nowadays, specialized software is vastly used to verify the performance of an electric machine prototype by evaluating a model of the system. These models mainly consist of electrical parameters such as inductances and resistances. However, when the operating frequency of the device is above one kHz, the effect of parasitic capacitances grows significantly. In this paper, a software-based procedure is introduced to model these capacitances within the electromagnetic simulation of the device. The case study is a high-frequency high-voltage pulse transformer. The Finite Element Analysis (FEA) software with coupled field analysis is used in this method.

Keywords: finite element analysis, parasitic capacitance, pulse transformer, high frequency

Procedia PDF Downloads 510

Authors: P. Karthick, K. Mahesh

Abstract:

Video has become an increasingly significant component of our digital everyday contact. With the advancement of greater contents and shows of the resolution, its significant volume poses serious obstacles to the objective of receiving, distributing, compressing, and revealing video content of high quality. In this paper, we propose the primary beginning to complete a deep video compression model that jointly upgrades all video compression components. The video compression method involves splitting the video into frames, comparing the images using convolutional neural networks (CNN) to remove duplicates, repeating the single image instead of the duplicate images by recognizing and detecting minute changes using generative adversarial network (GAN) and recorded with long short-term memory (LSTM). Instead of the complete image, the small changes generated using GAN are substituted, which helps in frame level compression. Pixel wise comparison is performed using K-nearest neighbours (KNN) over the frame, clustered with K-means, and singular value decomposition (SVD) is applied for each and every frame in the video for all three color channels [Red, Green, Blue] to decrease the dimension of the utility matrix [R, G, B] by extracting its latent factors. Video frames are packed with parameters with the aid of a codec and converted to video format, and the results are compared with the original video. Repeated experiments on several videos with different sizes, duration, frames per second (FPS), and quality results demonstrate a significant resampling rate. On average, the result produced had approximately a 10% deviation in quality and more than 50% in size when compared with the original video.

Keywords: video compression, K-means clustering, convolutional neural network, generative adversarial network, singular value decomposition, pixel visualization, stochastic gradient descent, frame per second extraction, RGB channel extraction, self-detection and deciding system

Procedia PDF Downloads 178

Authors: Elcin Timur Cakmak, Ayse Oguzlar

Abstract:

This study presents the results of the tweets sent by Twitter users on social media about the Russia-Ukraine war by bigram and trigram methods. On February 24, 2022, Russian President Vladimir Putin declared a military operation against Ukraine, and all eyes were turned to this war. Many people living in Russia and Ukraine reacted to this war and protested and also expressed their deep concern about this war as they felt the safety of their families and their futures were at stake. Most people, especially those living in Russia and Ukraine, express their views on the war in different ways. The most popular way to do this is through social media. Many people prefer to convey their feelings using Twitter, one of the most frequently used social media tools. Since the beginning of the war, it is seen that there have been thousands of tweets about the war from many countries of the world on Twitter. These tweets accumulated in data sources are extracted using various codes for analysis through Twitter API and analysed by Python programming language. The aim of the study is to find the word sequences in these tweets by the n-gram method, which is known for its widespread use in computational linguistics and natural language processing. The tweet language used in the study is English. The data set consists of the data obtained from Twitter between February 24, 2022, and April 24, 2022. The tweets obtained from Twitter using the #ukraine, #russia, #war, #putin, #zelensky hashtags together were captured as raw data, and the remaining tweets were included in the analysis stage after they were cleaned through the preprocessing stage. In the data analysis part, the sentiments are found to present what people send as a message about the war on Twitter. Regarding this, negative messages make up the majority of all the tweets as a ratio of %63,6. Furthermore, the most frequently used bigram and trigram word groups are found. Regarding the results, the most frequently used word groups are “he, is”, “I, do”, “I, am” for bigrams. Also, the most frequently used word groups are “I, do, not”, “I, am, not”, “I, can, not” for trigrams. In the machine learning phase, the accuracy of classifications is measured by Classification and Regression Trees (CART) and Naïve Bayes (NB) algorithms. The algorithms are used separately for bigrams and trigrams. We gained the highest accuracy and F-measure values by the NB algorithm and the highest precision and recall values by the CART algorithm for bigrams. On the other hand, the highest values for accuracy, precision, and F-measure values are achieved by the CART algorithm, and the highest value for the recall is gained by NB for trigrams.

Keywords: classification algorithms, machine learning, sentiment analysis, Twitter

Procedia PDF Downloads 66

Authors: Wanlapa Boonsod, Nisachon Yangprasong, Udomsak Kitthawee

Abstract:

Thermal physics education is a complicated and challenging topic to discuss in any classroom. As a result, most students tend to be uninterested in learning this topic. In the current study, a convection experiment set was devised to show how heat can be transferred by a convection system to a thermoelectric plate until a LED flashes. This research aimed to 1) create a natural convection experimental set, 2) study learning achievement on the convection experimental set with the predict-observe-explain (POE) technique, and 3) study satisfaction for the convection experimental set with the predict-observe-explain (POE) technique. The samples were chosen by purposive sampling and comprised 28 students in grade 11 at Patumkongka School in Bangkok, Thailand. The primary research instrument was the plan for predict-observe-explain (POE) technique on heat transfer using a convection experimental set. Heat transfer experimental set by convection. The instruments used to collect data included a heat transfer achievement model by convection, a Satisfaction Questionnaire after the learning activity, and the predict-observe-explain (POE) technique for heat transfer using a convection experimental set. The research format comprised a one-group pretest-posttest design. The data was analyzed by GeoGebra program. The statistics used in the research were mean, standard deviation and t-test for dependent samples. The results of the research showed that achievement on heat transfer using convection experimental set was composed of thermo-electrics on the top side attached to the heat sink and another side attached to a stainless plate. Electrical current was displayed by the flashing of a 5v LED. The entire set of thermo-electrics was set up on the top of the box and heated by an alcohol burner. The achievement of learning was measured with the predict-observe-explain (POE) technique, with the natural convection experimental set statistically higher than before learning at a 0.01 level. Satisfaction with POE for physics learning of heat transfer by using convection experimental set was at a high level (4.83 from 5.00).

Keywords: convection, heat transfer, physics education, POE

Procedia PDF Downloads 210

Authors: Hozaifa Zaki, Ghada Soliman

Abstract:

In this paper, we introduced an approach for Automated Dotted Arabic Expiration Date Extraction using Optimized Convolutional Autoencoder (ARABEX) with bidirectional LSTM. This approach is used for translating the Arabic dot-matrix expiration dates into their corresponding filled-in dates. A custom lightweight Convolutional Recurrent Neural Network (CRNN) model is then employed to extract the expiration dates. Due to the lack of available dataset images for the Arabic dot-matrix expiration date, we generated synthetic images by creating an Arabic dot-matrix True Type Font (TTF) matrix to address this limitation. Our model was trained on a realistic synthetic dataset of 3287 images, covering the period from 2019 to 2027, represented in the format of yyyy/mm/dd. We then trained our custom CRNN model using the generated synthetic images to assess the performance of our model (ARABEX) by extracting expiration dates from the translated images. Our proposed approach achieved an accuracy of 99.4% on the test dataset of 658 images, while also achieving a Structural Similarity Index (SSIM) of 0.46 for image translation on our dataset. The ARABEX approach demonstrates its ability to be applied to various downstream learning tasks, including image translation and reconstruction. Moreover, this pipeline (ARABEX+CRNN) can be seamlessly integrated into automated sorting systems to extract expiry dates and sort products accordingly during the manufacturing stage. By eliminating the need for manual entry of expiration dates, which can be time-consuming and inefficient for merchants, our approach offers significant results in terms of efficiency and accuracy for Arabic dot-matrix expiration date recognition.

Keywords: computer vision, deep learning, image processing, character recognition

Procedia PDF Downloads 73

Authors: I. Gupta, B. Karmakar

Abstract:

Bengal has a long history (8^th century A.D. onwards) of decorating the wall of brick-built temples with curved terracotta plaques on a diverse range of subjects. These could be considered as one of the most significant visual archives to understand the various facets of the then contemporary societies. The temples under focus include Char-bangla temple complex (circa 1755 A.D.), Bhavanishvara temple (circa 1755 A.D.) and the Gangeshvara Shiva Jor-bangla temple (circa 1753 A.D.), located within a part of the river Bhagirathi basin in Baranagar, Murshidabad, West Bengal, India. Though, a diverse range of subjects have been intricately carved mainly on the front façades of the Baranagar temple cluster, the study specifically concentrates on depictions related to religious and non-religious acts performed by practitioners of various religious sects of late medieval Bengal with the intention to acquire knowledge about the various facets of their life. Apart from this, the paper also mapped the spatial location of these religious performers on the temples’ façades to examine if any systematic plan or arrangement had been employed for connoting a particular idea. Further, an attempt is made to provide a commentary on the attire worn by followers of various religious sects of late medieval Bengal. The primary materials for the study comprise the depictions which denote religious activities carved on the terracotta plaques. The secondary material has been collected from published and unpublished theses, journals and books. These data have been further supplemented with photographic documentation, some useful line-drawings and descriptions in table format to get a clear understanding of the concerned issues.

Keywords: attire, scheme of allocation, terracotta temple, various religious sect

Procedia PDF Downloads 130

Authors: Masoomeh Alsadat Mirshafaei

Abstract:

The present study aims to explore the effect of an 8-week aerobic training regimen combined with cinnamon extract on serum irisin and leptin levels in insulin-resistant rats. Additionally, this research leverages various machine learning (ML) and deep learning (DL) algorithms to model the complex interdependencies between exercise, nutrition, and metabolic markers, offering a groundbreaking approach to obesity and diabetes research. Forty-eight Wistar rats were selected and randomly divided into four groups: control, training, cinnamon, and training cinnamon. The training protocol was conducted over 8 weeks, with sessions 5 days a week at 75-80% VO2 max. The cinnamon and training-cinnamon groups were injected with 200 ml/kg/day of cinnamon extract. Data analysis included serum data, dietary intake, exercise intensity, and metabolic response variables, with blood samples collected 72 hours after the final training session. The dataset was analyzed using one-way ANOVA (P<0.05) and fed into various ML and DL models, including Support Vector Machines (SVM), Random Forest (RF), and Convolutional Neural Networks (CNN). Traditional statistical methods indicated that aerobic training, with and without cinnamon extract, significantly increased serum irisin and decreased leptin levels. Among the algorithms, the CNN model provided superior performance in identifying specific interactions between cinnamon extract concentration and exercise intensity, optimizing the increase in irisin and the decrease in leptin. The CNN model achieved an accuracy of 92%, outperforming the SVM (85%) and RF (88%) models in predicting the optimal conditions for metabolic marker improvements. The study demonstrated that advanced ML and DL techniques could uncover nuanced relationships and potential cellular responses to exercise and dietary supplements, which is not evident through traditional methods. These findings advocate for the integration of advanced analytical techniques in nutritional science and exercise physiology, paving the way for personalized health interventions in managing obesity and diabetes.

Keywords: aerobic training, cinnamon extract, insulin resistance, irisin, leptin, convolutional neural networks, exercise physiology, support vector machines, random forest

Procedia PDF Downloads 18

Authors: Kefaya Qaddoum

Abstract:

The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: neural network, conformal prediction, cancer classification, regression

Procedia PDF Downloads 275

Authors: Hisham M. Soliman, Hassan Yousef

Abstract:

This manuscript presents new results on design saturated power system stabilizers (PSS) to assign system poles within a desired region for achieving good dynamic performance. The regional pole placement is accomplished against model uncertainties caused by different load conditions. The design is based on a sufficient condition in the form of linear matrix inequalities (LMI) which forces the saturated nonlinear controller to lie within the linear zone. The controller effectiveness is demonstrated on a single machine infinite bus system.

Keywords: power system stabilizer, saturated control, robust control, regional pole placement, linear matrix inequality (LMI)

Procedia PDF Downloads 557

Authors: Solomon Ojo

Abstract:

The study investigated emotional intelligence as a correlate of conflict management styles among managers and supervisors in work organization. The study was a survey and Ex-post facto design was employed. A total of 407 participants took part in the study, and the participants were selected across different work organizations in the six (6) existing Geo-political zones in Nigeria, namely South-West, South East, South-South, North-East, North-West and North-Central. Questionnaire format was used for data collection in the study. Collected data were analyzed by both the Descriptive and Inferential Statistics, specifically using the Statistical Package for Social Sciences (SPSS) version 21.0. The findings revealed that considerate leadership style was significantly and positively related to the use of collaborating conflict management style, [r(405) = .50**, P < .01]; Considerate leadership style was significantly and positively related to the use of compromising conflict management style, [r(405) = .3**, P < .01]; Considerate leadership style was significantly and positively related to accommodation conflict management style, [r(405) = .64**, P < .01]; Considerate leadership style was not significantly related to competing conflict management style, [r(405) = .07, P > .05]; Considerate leadership style was significantly and negatively related to avoiding conflict management style, [r(405) = -.38**, P < .01]. Further, initiating structural leadership style was significantly and positively related to competing conflict management style, [r(405) = .33**, P < .01], avoiding conflict management style, [r(405) = .41**, P < .01]; collaborating conflict management style [r(405) = 51**, P < .01]. However, the findings showed that initiating structural leadership style was significantly and negatively related to compromising style, [r(405) = -.57**, P < .01] and accommodating style, [r(405) = -.13**, P < .01]. The findings were extensively discussed in relation to the existing body of literature. Moreover, it was concluded that leadership styles of managers and supervisors play a crucial role in the choice and use of conflict management styles in work organizations in Nigeria.

Keywords: conflict management style, emotional, intelligence, leadership style, consideration, initiating structure, work organizations

Procedia PDF Downloads 256

Authors: Ali Asghar Memon

Abstract:

A cautious and astute selection of switching devices used in power electronic converters of a switched reluctance (SR) motor is required. It is a matter of choice of best switching devices with respect to their switching ability rather than fulfilling the number of switches. This paper highlights the computational determination of switching losses comprising of switch-on, switch-off and conduction losses respectively by using experimental data in simulation model of a SR machine. The finding of this research is helpful for proper selection of electronic switches and suitable converter topology for switched reluctance motor.

Keywords: converter, operating modes, switched reluctance motor, switching losses

Procedia PDF Downloads 495

Authors: Firdous Nizar, Carmela Cucuzzella

Abstract:

This paper explores how the integrated design process (IDP) was adopted for an architectural project. The IDP is a relatively new approach to collaborative design in architectural design projects in Canada. It has gained much traction recently as the closest possible approach to the successful management of low energy building projects and has been advocated as a productive method for multi-disciplinary collaboration within complex projects. This study is based on the premise that there are explicit and implicit dimensions of power within the integrated design process (IDP) in the green building industry that may or may not lead to irreconcilable differences in a process that demands consensus. To gain insight on the potential gap between the theoretical promises and practical realities of the IDP, a review of existing IDP literature is compared with a case study analysis of a competition-based architectural project in Canada, a first to incorporate the IDP in its overall design format. This paper aims to address the undertheorized power relations of the IDP in a real project. It presents a critical assessment through the lens of the combined theories of deliberative democracy by Jürgen Habermas, with that of agonistic pluralism by political theorist Chantal Mouffe. These two theories are intended to more appropriately embrace the conflictual situations in collaborative environments, and shed light on the relationships of power, between engineers, city officials, architects, and designers in this conventional consensus-based model. In addition, propositions for a shift in approach that embraces conflictual differences among its participants are put forth based on concepts of critical spatial practice by Markus Meissen. As IDP is a relatively new design process, it requires much deliberation on its structure from the theoretical framework built in this paper in order to unlock its true potential.

Keywords: agonistic pluralism, critical spatial practice, deliberative democracy, integrated design process

Procedia PDF Downloads 168

Authors: Virginia Melnyk

Abstract:

This paper explores the design for catenary structure using knitted textiles. Using the advantages of Grasshopper and Kangaroo parametric software to simulate and pre-design an overall form, the design is then translated to a pattern that can be made with hand manipulated stitches on a knitting machine. The textile takes advantage of the structure of knitted materials and the ability for it to stretch. Using different types of stitches to control the amount of stretch that can occur in portions of the textile generates an overall formal design. The textile is then hardened in an upside-down hanging position and then flipped right-side-up. This then becomes a structural catenary form. The resulting design is used as a small Cat House for a cat to sit inside and climb on top of.

Keywords: architectural materials, catenary structures, knitting fabrication, textile design

Procedia PDF Downloads 174

Authors: Hauwau Mohammed

Abstract:

Research purpose: the integration of Traditional Birth Attendants (TBAs) has long been initiated into healthcare systems. This has been to help improve maternal mortality, particularly in developing countries. Nigeria is seen as one of the countries with a high maternal death rate due to common pregnancy complications and low resources. Communities with challenges of universal coverage of skilled workers rely on TBAs for pregnancy-related services, including delivery. The Sokoto State government has conducted several training programs on a significant number of TBAs to enable a formal integration of relationships with skilled healthcare for women in rural regions. This study aims to explore a standard method and develop an assessment framework for improving TBAs training programs in Sokoto State. Research Design, Methodology & Methods : Using a qualitative design, an interpretive phenomenology approach will be applied to explore the lived-experiences of 28 TBAs, who have undergone a form of training while also examining the strategies used to develop those programs through 8 policymakers and/or program trainers. For the collection stage, a focus group discussion and a face-to-face interview will be conducted, where the latter is for TBAs and the former for policymakers and training officials. Analysis: Data will be analyse through IPA format while using Nvivo to code and catalog personal experiential generated patterns. Secondary review: a scoping review of secondary data from Nigeria was used to map the knowledge gap and the extent of available data. The thematic analytic findings suggested that there are various approaches used to incorporate TBAs into the healthcare system, which include interventional programs targeted at specific health issues. In addition, incentives were used to encourage TBAs to facilitate the frequent use of skilled care for women.

Keywords: traditional birth attendants, Nigeria, training, program

Procedia PDF Downloads 73

Authors: Vibhuti Amarnath Madhu Agrawal

Abstract:

Artificial Intelligence (AI) and Intellectual Property are two emerging concepts that are growing at a fast pace and have the potential of having a huge impact on the economy in the coming times. In simple words, AI is nothing but work done by a machine without any human intervention. It is a coded software embedded in a machine, which over a period of time, develops its own intelligence and begins to take its own decisions and judgments by studying various patterns of how people think, react to situations and perform tasks, among others. Intellectual Property, especially Copyright Law, on the other hand, protects the rights of individuals and Companies in content creation that primarily deals with application of intellect, originality and expression of the same in some tangible form. According to some of the reports shared by the media lately, ChatGPT, an AI powered Chatbot, has been involved in the creation of a wide variety of original content, including but not limited to essays, emails, plays and poetry. Besides, there have been instances wherein AI technology has given creative inputs for background, lights and costumes, among others, for films. Copyright Law offers protection to all of these different kinds of content and much more. Considering the two key parameters of Copyright – application of intellect and originality, the question, therefore, arises that will awarding Copyright protection to a person who has not directly invested his / her intellect in the creation of that content go against the basic spirit of Copyright laws? This study aims to analyze the current scenario and provide answers to the following questions: a. If the content generated by AI technology satisfies the basic criteria of originality and expression in a tangible form, why should such content be denied protection in the name of its creator, i.e., the specific AI tool / technology? B. Considering the increasing role and development of AI technology in our lives, should it be given the status of a ‘Legal Person’ in law? C. If yes, what should be the modalities of awarding protection to works of such Legal Person and management of the same? Considering the current trends and the pace at which AI is advancing, it is not very far when AI will start functioning autonomously in the creation of new works. Current data and opinions on this issue globally reflect that they are divided and lack uniformity. In order to fill in the existing gaps, data obtained from Copyright offices from the top economies of the world have been analyzed. The role and functioning of various Copyright Societies in these countries has been studied in detail. This paper provides a roadmap that can be adopted to satisfy various objectives, constraints and dynamic conditions related AI technology and its protection under Copyright Law.

Keywords: artificial intelligence technology, copyright law, copyright societies, intellectual property

Procedia PDF Downloads 63

Authors: Ahmet Faruk Akyuz, Hasan Sakir Bilge

Abstract:

Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea.

Keywords: thermal stereo matching, deep neural networks, CNN, Depth estimation

Procedia PDF Downloads 266

Authors: Alicia Greenbank, Efrat Bengio

Abstract:

The aim of this research was to examine the efficacy of the first course in Israel, whose objective is to train student teachers in the special education department to work cooperatively with parents of children with special needs. Studies often highlight the importance of cooperation between teachers and parents of students with special needs. Israel’s Special Education Law defines parents as complete partners, and the Ministry of Education encourages and even requires that partnership be present. Yet this partnership is difficult to achieve many kindergarten teachers, and teachers have a lot of difficulties establishing and managing a pattern of cooperation with their students’ parents. Often we see different perspectives on the child's development and needs, distrust, lack of appreciation, and communication difficulties on both sides – parents & teachers. The course describes a method of instilling the need for cooperation at an early stage of teacher training-in the teacher training program. 22 students in the special education program for early childhood education in the fourth year of learning took part in the course. The fourth-year is the experiential training year and the first time that students have worked in a school. The course consisted of 14 sessions. Seven parents of students with different disabilities participated at 6 of the sessions. The changes in the students' attitudes towards partnership and their ability to manage this partnership were carried out by examining the reports written by the students before the meetings with the parents and the reflections they wrote after each meeting with the parents and at the end of the course. Three themes emerged from the narrative analysis, corresponding to the three preconditions for joint activities with parents — Approach, Attitude, Appropriate Atmosphere, according to the Four A’s Model. The findings showed that a course combining meetings with parents of children with special needs offers many benefits for teacher training. The course raised student awareness of the question partnership, changed students’ approaches and attitudes towards the parents, stressed the importance of partnership, and provided students with tools for working with parents through the school. Based on the findings of this study, courses in this format can be applied in order to cooperate between teachers and parents, for example, parents of gifted children with special needs.

Keywords: Partnership with parents in special education, parents of children with disabilities, parents of children with special needs, parents’ involvement in special education

Procedia PDF Downloads 183

Authors: Shervin Alaei, Reza Moradi

Abstract:

Trading in financial markets is subject to risks due to their high volatilities. Here, using an LSTM neural network, and by doing some risk-based feature engineering tasks, we developed a method that can accurately predict trends of the Tehran stock exchange market index from a few days ago. Our test results have shown that the proposed method with an average prediction accuracy of more than 94% is superior to the other common machine learning algorithms. To the best of our knowledge, this is the first work incorporating deep learning and risk factors to accurately predict market trends.

Keywords: deep learning, LSTM, trend prediction, risk management, artificial neural networks

Procedia PDF Downloads 139

Authors: Carmel Sofer, Dan Vilenchik, Ron Dotsch, Galia Avidan

Abstract:

Studies investigating emotional facial expressions typically reveal consensus among observes regarding the meaning of basic expressions, whose number ranges between 6 to 15 emotional states. Given this limited number of discrete expressions, how is it that the human vocabulary of emotional states is so rich? The present study argues that perceivers use sequences of these discrete expressions as the basis for a much richer vocabulary of emotional states. Such mechanisms, in which a relatively small number of basic components is expanded to a much larger number of possible combinations of meanings, exist in other human communications modalities, such as spoken language and music. In these modalities, letters and notes, which serve as basic components of spoken language and music respectively, are temporally linked, resulting in the richness of expressions. In the current study, in each trial participants were presented with sequences of two images containing facial expression in different combinations sampled out of the eight static basic expressions (total 64; 8X8). In each trial, using single word participants were required to judge the 'state of mind' portrayed by the person whose face was presented. Utilizing word embedding methods (Global Vectors for Word Representation), employed in the field of Natural Language Processing, and relying on machine learning computational methods, it was found that the perceived meanings of the sequences of facial expressions were a weighted average of the single expressions comprising them, resulting in 22 new emotional states, in addition to the eight, classic basic expressions. An interaction between the first and the second expression in each sequence indicated that every single facial expression modulated the effect of the other facial expression thus leading to a different interpretation ascribed to the sequence as a whole. These findings suggest that the vocabulary of emotional states conveyed by facial expressions is not restricted to the (small) number of discrete facial expressions. Rather, the vocabulary is rich, as it results from combinations of these expressions. In addition, present research suggests that using word embedding in social perception studies, can be a powerful, accurate and efficient tool, to capture explicit and implicit perceptions and intentions. Acknowledgment: The study was supported by a grant from the Ministry of Defense in Israel to GA and CS. CS is also supported by the ABC initiative in Ben-Gurion University of the Negev.

Keywords: Glove, face perception, facial expression perception. , facial expression production, machine learning, word embedding, word2vec

Procedia PDF Downloads 171

Authors: Alexander Street, Nina Wollersberger, Paul Fernie, Leonardo Muller, Ming Hung HSU, Helen Odell-Miller, Jorg Fachner, Patrizia Di Campli San Vito, Stephen Brewster, Hari Shaji, Satvik Venkatesh, Paolo Itaborai, Nicolas Farina, Alexis Kirke, Sube Banerjee, Eduardo Reck Miranda

Abstract:

Escalating neuropsychiatric symptoms (NPS) in people with dementia may lead to earlier care home admission. Music listening has been reported to stimulate cognitive function, potentially reducing agitation in this population. We present a scoping review, reporting on current developments and discussing the potential for music listening with related technology in managing agitation in dementia care. Of two searches for music listening studies, one focused on older people or people living with dementia where music listening interventions, including technology, were delivered in participants’ homes or in institutions to address neuropsychiatric symptoms, quality of life and independence. The second included any population focusing on the use of music technology for health and wellbeing. In search one 70/251 full texts were included. The majority reported either statistical significance (6, 8.5%), significance (17, 24.2%) or improvements (26, 37.1%). Agitation was specifically reported in 36 (51.4%). The second search included 51/99 full texts, reporting improvement (28, 54.9%), significance (11, 21.5%), statistical significance (1, 1.9%) and no difference compared to the control (6, 11.7%). The majority in the first focused on mood and agitation, and the second on mood and psychophysiological responses. Five studies used AI or machine learning systems to select music, all involving healthy controls and reporting benefits. Most studies in both reviews were not conducted in a home environment (review 1 = 12; 17.1%; review 2 = 11; 21.5%). Preferred music listening may help manage NPS in the care home settings. Based on these and other data extracted in the review, a reasonable progression would be to co-design and test music listening systems and protocols for NPS in all settings, including people’s homes. Machine learning and automated technology for music selection and arousal adjustment, driven by live biodata, have not been explored in dementia care. Such approaches may help deliver the right music at the appropriate time in the required dosage, reducing the use of medication and improving quality of life.

Keywords: music listening, dementia, agitation, scoping review, technology

Procedia PDF Downloads 101

Authors: Mahani Razali, Nordin Mamat

Abstract:

The purpose of this research is to identify the teacher’s role and parent’s participation to develop children`s socio emotion through play activities. This research is based on three main objectives which are to identify children`s socio emotion during play activities, teacher’s role and parent’s participation to develop children`s socio emotion. This qualitative study was carried out among 25 pre-school children, three teachers and three parents as the research sample. On the other hand, parent’s support was obtained from their discussions, supervisions and communication at home. The data collection procedures involved structured observation which was to identify socio emotional development element among pre-school children through play activities; as for semi-structured interviews, it was done to study the perception of the teachers and parents on the acquired socio emotional development among the children. Besides, documentation analysis method was used as to triangulate acquired information with observations and interviews. In this study, the qualitative data analysis was tabulated in descriptive manner with frequency and percentage format. This study primarily focused on five main socio emotional elements among the pre-school children: 1) Cooperation, 2) Confidence and Courage, 3) Ability to communicate, 4) patience, and 5) Tolerance. The findings of this study were presented in the form of case to case manner from the researches sample. Findings revealed that the children showed positive outcomes on the socio emotional development during their play. Both teachers and parents showed positive perceptions towards the acquired socio emotional development during their play activities. In conclusion, this research summarizes that teacher’s role and parent’s support can improve children`s socio emotional development through play activities. As a whole, this research highlighted the significance of play activities as to stimulate socio emotional development among the pre-school children.

Keywords: social emotional, children, play activities, stimulating

Procedia PDF Downloads 397

Authors: Tejaswi Agarwal, Amritansh Agarwal

Abstract:

Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

Procedia PDF Downloads 1176

Authors: Selvavinayagan Babiharan

Abstract:

This research aims to develop a deep learning platform to enhance mathematics education for secondary students in Sri Lanka. The platform will be designed to incorporate interactive and user-friendly features to engage students in active learning and promote their mathematical skills. The proposed platform will be developed using TensorFlow and Keras, two widely used deep learning frameworks. The system will be trained on a large dataset of math problems, which will be collected from Sri Lankan school curricula. The results of this research will contribute to the improvement of mathematics education in Sri Lanka and provide a valuable tool for teachers to enhance the learning experience of their students.

Keywords: information technology, education, machine learning, mathematics

Procedia PDF Downloads 74

Authors: Amritansh Agarwal, Tejaswi Agarwal

Abstract:

Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000 km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from USGS website in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud and aerosol free by making using of FLAASH atmospheric correction technique. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean we have analysed the change in ground biomass. Through this paper we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques it is clearly shows that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI change detection

Procedia PDF Downloads 386

Authors: Guolong Zhong, Venkatesh Chennam Vijay, Ilias Oraifige

Abstract:

In the last 20 years, Knowledge Based Engineering (KBE) has shown its advantages in product development in different engineering areas such as automation, mechanical, civil and aerospace engineering in terms of digital design automation and cost reduction by automating repetitive design tasks through capturing, integrating, utilising and reusing the existing knowledge required in various aspects of the product design. However, in primary design stages, the descriptive information of a product is discrete and unorganized while knowledge is in various forms instead of pure data. Thus, it is crucial to have an integrated product model which can represent the entire product information and its associated knowledge at the beginning of the product design. One of the shortcomings of the existing product models is a lack of required knowledge representation in various aspects of product design and its mapping to an interoperable schema. To overcome the limitation of the existing product model and methodologies, two key factors are considered. First, the product model must have well-defined classes that can represent the entire product information and its associated knowledge. Second, the product model needs to be represented in an interoperable schema to ensure a steady data exchange between different product modelling platforms and CAD software. This paper introduced a method to provide a general product model as a generative representation of a product, which consists of the geometry information and non-geometry information, through a product modelling framework. The proposed method for capturing the knowledge from the designers through a knowledge file provides a simple and efficient way of collecting and transferring knowledge. Further, the knowledge schema provides a clear view and format on the data that needed to be gathered in order to achieve a unified knowledge exchange between different platforms. This study used a game-based platform to make product modelling environment accessible for non-engineers. Further the paper goes on to test use case based on the proposed game-based product modelling environment to validate the effectiveness among non-engineers.

Keywords: game-based learning, knowledge based engineering, product modelling, design automation

Procedia PDF Downloads 142

Authors: Min-Feng Hsieh

Abstract:

Nowadays, we are facing a highly competitive environment in which the situation for survival has come even more critical than ever before. The challenge we will be confronted with is no longer can be dealt with the single system of knowledge. The abilities we urgently need to acquire is something that can lead us to cross over the boundaries between different disciplines and take us to a neutral ground that gathers and integrates powers and intelligence that surrounds us. This paper aims at discussing how a trans-disciplinary design course organized by the College of Design at Chaoyang University can react to this modern challenge. By orchestrating an experimental course format and by developing a series of coaching strategies, a trans-disciplinary learning environment has been created and practiced in which students selected from five different departments, including Architecture, Interior Design, Visual Design, Industrial Design, Landscape and Urban Design, are encouraged to think outside their familiar knowledge pool and to learn with/from each other. In the course of implementing this program, a parallel research has been conducted alongside by adopting the theory and principles of Action Research which is a research methodology that can provide the course organizer emergent, responsive, action-oriented, participative and critically reflective insights for the immediate changes and amendments in order to improve the effect of teaching and learning experience. In the conclusion, how the learning and teaching experience of this trans-disciplinary design studio can offer us some observation that can help us reflect upon the constraints and division caused by the subject base curriculum will be pointed out. A series of concepts for course design and teaching strategies developed and implemented in this trans-disciplinary course are to be introduced as a way to promote learners’ self-motivated, collaborative, cross-disciplinary and student-centered learning skills. The outcome of this experimental course can exemplify an alternative approach that we could adopt in pursuing a remedy for dealing with the problematic issues of the current educational practice.

Keywords: course design, coaching strategy, subject base curriculum, trans-disciplinary

Procedia PDF Downloads 194

Authors: F. V. Matta, C. M. Donnelly, M. B. Jaafar, N. I. Ward

Abstract:

‘Yerba Mate’ (Ilex paraguariensis) is a native plant from South America with the main producers being Argentina and Brazil. ‘Mate’ is widely consumed in Argentina, Brazil, Uruguay and Paraguay. The most popular format is as an infusion made from dried leaves of a traditional cup, roasted material in tea bags or iced tea infusions. There are many alleged health benefits resulted from mate consumption, even though there is a lack of conclusive research published in the international literature. The main objective of this study was to develop and evaluate the sample preparation and instrumental analysis stages involved in the determination of trace elements in yerba mate using inductively coupled plasma mass spectrometry (ICP-MS). Specific details on the methods of sample digestion, validation of the ICP-MS analysis especially for polyatomic ion correction and matrix effects associated with the complex medium of mate will be presented. More importantly, mate produced in Brazil and Argentina, is subject to different soil conditions, methods of cultivation and production, especially for loose leaves and tea bags. The highest concentrations for loose mate leaf were for (mg/kg, dry weight): aluminium (253.6 – 506.9 for Brazil (Bra), 230.0 – 541.8 for Argentina (Arg), respectively), manganese (378.3 – 762.6 Bra; 440.8 – 879.9 Arg), iron (32.5 – 85.7 Bra; 28.2 – 132.9 Arg), zinc (28.2 – 91.1 Bra; 39.1 – 92.3 Arg), nickel (2.2 – 4.3 Bra; 2.9 – 10.8 Arg) and copper (4.8 – 9.1 Bra; 4.3 – 9.2 Arg), with lower levels of chromium, cobalt, selenium, molybdenum, cadmium, lead and arsenic. Elemental levels of mate leaf consumed in tea bags were found to be higher, mainly due to only using leaf material (as opposed to leaf and twig for loose packed product). Further implications of the way of consuming yerba mate will be presented, including different infusion methods in Brazil and Argentina. This research provides for the first time an extensive evaluation of mate products from both countries and the possible implications of specific trace elements, especially Mn, Fe, Se, Cu and Zn and the various health claims of consuming yerba mate.

Keywords: beverage analysis, ICP-MS, trace elements, yerba mate

Procedia PDF Downloads 220

Authors: Abbas Raza Ali

Abstract:

Big Data technology is gradually becoming a dire need of large enterprises. These enterprises are generating massively large amount of off-line and streaming data in both structured and unstructured formats on daily basis. It is a challenging task to effectively extract useful insights from the large scale datasets, even though sometimes it becomes a technology constraint to manage transactional data history of more than a few months. This paper presents a framework to efficiently manage massively large and complex datasets. The framework has been tested on a communication service provider producing massively large complex streaming data in binary format. The communication industry is bound by the regulators to manage history of their subscribers’ call records where every action of a subscriber generates a record. Also, managing and analyzing transactional data allows service providers to better understand their customers’ behavior, for example, deep packet inspection requires transactional internet usage data to explain internet usage behaviour of the subscribers. However, current relational database systems limit service providers to only maintain history at semantic level which is aggregated at subscriber level. The framework addresses these challenges by leveraging Big Data technology which optimally manages and allows deep analysis of complex datasets. The framework has been applied to offload existing Intelligent Network Mediation and relational Data Warehouse of the service provider on Big Data. The service provider has 50+ million subscriber-base with yearly growth of 7-10%. The end-to-end process takes not more than 10 minutes which involves binary to ASCII decoding of call detail records, stitching of all the interrogations against a call (transformations) and aggregations of all the call records of a subscriber.

Keywords: big data, communication service providers, enterprise data warehouse, stream computing, Telco IN Mediation

Procedia PDF Downloads 168