Search results for: artificial teacher
712 Vehicle Gearbox Fault Diagnosis Based on Cepstrum Analysis
Authors: Mohamed El Morsy, Gabriela Achtenová
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Research on damage of gears and gear pairs using vibration signals remains very attractive, because vibration signals from a gear pair are complex in nature and not easy to interpret. Predicting gear pair defects by analyzing changes in vibration signal of gears pairs in operation is a very reliable method. Therefore, a suitable vibration signal processing technique is necessary to extract defect information generally obscured by the noise from dynamic factors of other gear pairs. This article presents the value of cepstrum analysis in vehicle gearbox fault diagnosis. Cepstrum represents the overall power content of a whole family of harmonics and sidebands when more than one family of sidebands is present at the same time. The concept for the measurement and analysis involved in using the technique are briefly outlined. Cepstrum analysis is used for detection of an artificial pitting defect in a vehicle gearbox loaded with different speeds and torques. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers introduce the load on the flanges of the output joint shafts. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. Also, a method for fault diagnosis of gear faults is presented based on order cepstrum. The procedure is illustrated with the experimental vibration data of the vehicle gearbox. The results show the effectiveness of cepstrum analysis in detection and diagnosis of the gear condition.Keywords: cepstrum analysis, fault diagnosis, gearbox, vibration signals
Procedia PDF Downloads 371711 An Integrated Framework for Seismic Risk Mitigation Decision Making
Authors: Mojtaba Sadeghi, Farshid Baniassadi, Hamed Kashani
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One of the challenging issues faced by seismic retrofitting consultants and employers is quick decision-making on the demolition or retrofitting of a structure at the current time or in the future. For this reason, the existing models proposed by researchers have only covered one of the aspects of cost, execution method, and structural vulnerability. Given the effect of each factor on the final decision, it is crucial to devise a new comprehensive model capable of simultaneously covering all the factors. This study attempted to provide an integrated framework that can be utilized to select the most appropriate earthquake risk mitigation solution for buildings. This framework can overcome the limitations of current models by taking into account several factors such as cost, execution method, risk-taking and structural failure. In the newly proposed model, the database and essential information about retrofitting projects are developed based on the historical data on a retrofit project. In the next phase, an analysis is conducted in order to assess the vulnerability of the building under study. Then, artificial neural networks technique is employed to calculate the cost of retrofitting. While calculating the current price of the structure, an economic analysis is conducted to compare demolition versus retrofitting costs. At the next stage, the optimal method is identified. Finally, the implementation of the framework was demonstrated by collecting data concerning 155 previous projects.Keywords: decision making, demolition, construction management, seismic retrofit
Procedia PDF Downloads 231710 Convolutional Neural Networks versus Radiomic Analysis for Classification of Breast Mammogram
Authors: Mehwish Asghar
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Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence
Procedia PDF Downloads 219709 Hidden Markov Model for Financial Limit Order Book and Its Application to Algorithmic Trading Strategy
Authors: Sriram Kashyap Prasad, Ionut Florescu
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This study models the intraday asset prices as driven by Markov process. This work identifies the latent states of the Hidden Markov model, using limit order book data (trades and quotes) to continuously estimate the states throughout the day. This work builds a trading strategy using estimated states to generate signals. The strategy utilizes current state to recalibrate buy/ sell levels and the transition between states to trigger stop-loss when adverse price movements occur. The proposed trading strategy is tested on the Stevens High Frequency Trading (SHIFT) platform. SHIFT is a highly realistic market simulator with functionalities for creating an artificial market simulation by deploying agents, trading strategies, distributing initial wealth, etc. In the implementation several assets on the NASDAQ exchange are used for testing. In comparison to a strategy with static buy/ sell levels, this study shows that the number of limit orders that get matched and executed can be increased. Executing limit orders earns rebates on NASDAQ. The system can capture jumps in the limit order book prices, provide dynamic buy/sell levels and trigger stop loss signals to improve the PnL (Profit and Loss) performance of the strategy.Keywords: algorithmic trading, Hidden Markov model, high frequency trading, limit order book learning
Procedia PDF Downloads 145708 Predictive Machine Learning Model for Assessing the Impact of Untreated Teeth Grinding on Gingival Recession and Jaw Pain
Authors: Joseph Salim
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This paper proposes the development of a supervised machine learning system to predict the consequences of untreated bruxism (teeth grinding) on gingival (gum) recession and jaw pain (most often bilateral jaw pain with possible headaches and limited ability to open the mouth). As a general dentist in a multi-specialty practice, the author has encountered many patients suffering from these issues due to uncontrolled bruxism (teeth grinding) at night. The most effective treatment for managing this problem involves wearing a nightguard during sleep and receiving therapeutic Botox injections to relax the muscles (the masseter muscle) responsible for grinding. However, some patients choose to postpone these treatments, leading to potentially irreversible and costlier consequences in the future. The proposed machine learning model aims to track patients who forgo the recommended treatments and assess the percentage of individuals who will experience worsening jaw pain, gingival (gum) recession, or both within a 3-to-5-year timeframe. By accurately predicting these outcomes, the model seeks to motivate patients to address the root cause proactively, ultimately saving time and pain while improving quality of life and avoiding much costlier treatments such as full-mouth rehabilitation to help recover the loss of vertical dimension of occlusion due to shortened clinical crowns because of bruxism, gingival grafts, etc.Keywords: artificial intelligence, machine learning, predictive insights, bruxism, teeth grinding, therapeutic botox, nightguard, gingival recession, gum recession, jaw pain
Procedia PDF Downloads 82707 Challenges for Adopting Circular Economy Toward Business Innovation and Supply Chain
Authors: Kapil Khanna, Swee Kuik, Joowon Ban
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The current linear economic system is unsustainable due to its dependence on the uncontrolled exploitation of diminishing natural resources. The integration of business innovation and supply chain management has brought about the redesign of business processes through the implementation of a closed-loop approach. The circular economy (CE) offers a sustainable solution to improve business opportunities in the near future by following the principles of rejuvenation and reuse inspired by nature. Those business owners start to rethink and consider using waste as raw material to make new products for consumers. The implementation of CE helps organisations to incorporate new strategic plans for decreasing the use of virgin materials and nature resources. Supply chain partners that are geographically dispersed rely heavily on innovative approaches to support supply chain management. Presently, numerous studies have attempted to establish the concept of supply chain management (SCM) by integrating CE principles, which are commonly denoted as circular SCM. While many scholars have recognised the challenges of transitioning to CE, there is still a lack of consensus on business best practices that can facilitate companies in embracing CE across the supply chain. Hence, this paper strives to scrutinize the SCM practices utilised for CE, identify the obstacles, and recommend best practices that can enhance a company's ability to incorporate CE principles toward business innovation and supply chain performance. Further, the paper proposes future research in the field of using specific technologies such as artificial intelligence, Internet of Things, and blockchain as business innovation tools for supply chain management and CE adoption.Keywords: business innovation, challenges, circular supply chain, supply chain management, technology
Procedia PDF Downloads 88706 Substantial Fatigue Similarity of a New Small-Scale Test Rig to Actual Wheel-Rail System
Authors: Meysam Naeimi, Zili Li, Roumen Petrov, Rolf Dollevoet, Jilt Sietsma, Jun Wu
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The substantial similarity of fatigue mechanism in a new test rig for rolling contact fatigue (RCF) has been investigated. A new reduced-scale test rig is designed to perform controlled RCF tests in wheel-rail materials. The fatigue mechanism of the rig is evaluated in this study using a combined finite element-fatigue prediction approach. The influences of loading conditions on fatigue crack initiation have been studied. Furthermore, the effects of some artificial defects (squat-shape) on fatigue lives are examined. To simulate the vehicle-track interaction by means of the test rig, a three-dimensional finite element (FE) model is built up. The nonlinear material behaviour of the rail steel is modelled in the contact interface. The results of FE simulations are combined with the critical plane concept to determine the material points with the greatest possibility of fatigue failure. Based on the stress-strain responses, by employing of previously postulated criteria for fatigue crack initiation (plastic shakedown and ratchetting), fatigue life analysis is carried out. The results are reported for various loading conditions and different defect sizes. Afterward, the cyclic mechanism of the test rig is evaluated from the operational viewpoint. The results of fatigue life predictions are compared with the expected number of cycles of the test rig by its cyclic nature. Finally, the estimative duration of the experiments until fatigue crack initiation is roughly determined.Keywords: fatigue, test rig, crack initiation, life, rail, squats
Procedia PDF Downloads 507705 Performances and Activities of Urban Communities Leader Based on Sufficiency Economy Philosophy in Dusit District, Bangkok Metropolitan
Authors: Phusit Phukamchanoad
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The research studies the behaviors based on sufficiency economy philosophy at individual and community levels as well as the satisfaction of the urban community leaders by collecting data with purposive sampling technique. For in-depth interviews with 26 urban community leaders, the result shows that the urban community leaders have good knowledge and understanding about sufficiency economy philosophy. Especially in terms of money spending, they must consider the need for living and be economical. The activities in the community or society should not take advantage of the others as well as colleagues. At present, most of the urban community leaders live in a sufficient way. They often spend time with public service, but many families are dealing with debt. Many communities have some political conflict and high family allowances because of living in the urban communities with rapid social and economic changes. However, there are many communities that leaders have applied their wisdom in development for their people by gathering and grouping the professionals to form activities such as making chili sauce, textile organization, making artificial flowers worshipping the sanctity. The most prominent group is the foot massage business in Wat Pracha Rabue Tham. This professional group is supported continuously by the government. One of the factors in terms of satisfaction used for evaluating community leaders is the customary administration in brotherly, interdependent way rather than using the absolute power or controlling power, but using the roles of leader to perform the activities with their people intently, determinedly and having a public mind for people.Keywords: performance and activities, sufficiency economy, urban communities leader, Dusit district
Procedia PDF Downloads 355704 Construction Unit Rate Factor Modelling Using Neural Networks
Authors: Balimu Mwiya, Mundia Muya, Chabota Kaliba, Peter Mukalula
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Factors affecting construction unit cost vary depending on a country’s political, economic, social and technological inclinations. Factors affecting construction costs have been studied from various perspectives. Analysis of cost factors requires an appreciation of a country’s practices. Identified cost factors provide an indication of a country’s construction economic strata. The purpose of this paper is to identify the essential factors that affect unit cost estimation and their breakdown using artificial neural networks. Twenty-five (25) identified cost factors in road construction were subjected to a questionnaire survey and employing SPSS factor analysis the factors were reduced to eight. The 8 factors were analysed using the neural network (NN) to determine the proportionate breakdown of the cost factors in a given construction unit rate. NN predicted that political environment accounted 44% of the unit rate followed by contractor capacity at 22% and financial delays, project feasibility, overhead and profit each at 11%. Project location, material availability and corruption perception index had minimal impact on the unit cost from the training data provided. Quantified cost factors can be incorporated in unit cost estimation models (UCEM) to produce more accurate estimates. This can create improvements in the cost estimation of infrastructure projects and establish a benchmark standard to assist the process of alignment of work practises and training of new staff, permitting the on-going development of best practises in cost estimation to become more effective.Keywords: construction cost factors, neural networks, roadworks, Zambian construction industry
Procedia PDF Downloads 355703 Miracle Fruit Application in Sour Beverages: Effect of Different Concentrations on the Temporal Sensory Profile and Overall Linking
Authors: Jéssica F. Rodrigues, Amanda C. Andrade, Sabrina C. Bastos, Sandra B. Coelho, Ana Carla M. Pinheiro
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Currently, there is a great demand for the use of natural sweeteners due to the harmful effects of the high sugar and artificial sweeteners consumption on the health. Miracle fruit, which is known for its unique ability to modify the sour taste in sweet taste, has been shown to be a good alternative sweetener. However, it has a high production cost, being important to optimize lower contents to be used. Thus, the aim of this study was to assess the effect of different miracle fruit contents on the temporal (Time-intensity - TI and Temporal Dominance of Sensations - TDS) sensory profile and overall linking of lemonade, to determine the better content to be used as a natural sweetener in sour beverages. TI and TDS results showed that the concentrations of 150 mg, 300 mg and 600 mg miracle fruit were effective in reducing the acidity and promoting the sweet perception in lemonade. Furthermore, the concentrations of 300 mg and 600 mg obtained similar profiles. Through the acceptance test, the concentration of 300 mg miracle fruit was shown to be an efficient substitute for sucrose and sucralose in lemonade, once they had similar hedonic values between ‘I liked it slightly’ and ‘I liked it moderately’. Therefore, 300mg miracle fruit consists in an adequate content to be used as a natural sweetener of lemonade. The results of this work will help the food industry on the efficient application of a new natural sweetener- the Miracle fruit extract in sour beverages, reducing costs and providing a product that meets the consumer desires.Keywords: acceptance, natural sweetener, temporal dominance of sensations, time-intensity
Procedia PDF Downloads 243702 Influence of Spelling Errors on English Language Performance among Learners with Dysgraphia in Public Primary Schools in Embu County, Kenya
Authors: Madrine King'endo
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This study dealt with the influence of spelling errors on English language performance among learners with dysgraphia in public primary schools in West Embu, Embu County, Kenya. The study purposed to investigate the influence of spelling errors on the English language performance among the class three pupils with dysgraphia in public primary schools. The objectives of the study were to identify the spelling errors that learners with dysgraphia make when writing English words and classify the spelling errors they make. Further, the study will establish how the spelling errors affect the performance of the language among the study participants, and suggest the remediation strategies that teachers could use to address the errors. The study could provide the stakeholders with relevant information in writing skills that could help in developing a responsive curriculum to accommodate the teaching and learning needs of learners with dysgraphia, and probably ensure training of teachers in teacher training colleges is tailored within the writing needs of the pupils with dysgraphia. The study was carried out in Embu county because the researcher did not find any study in related literature review concerning the influence of spelling errors on English language performance among learners with dysgraphia in public primary schools done in the area. Moreover, besides being relatively populated enough for a sample population of the study, the area was fairly cosmopolitan to allow a generalization of the study findings. The study assumed the sampled schools will had class three pupils with dysgraphia who exhibited written spelling errors. The study was guided by two spelling approaches: the connectionist stimulation of spelling process and orthographic autonomy hypothesis with a view to explain how participants with learning disabilities spell written words. Data were collected through interviews, pupils’ exercise books, and progress records, and a spelling test made by the researcher based on the spelling scope set for class three pupils by the ministry of education in the primary education syllabus. The study relied on random sampling techniques in identifying general and specific participants. Since the study used children in schools as participants, voluntary consent was sought from themselves, their teachers and the school head teachers who were their caretakers in a school setting.Keywords: dysgraphia, writing, language, performance
Procedia PDF Downloads 149701 Parallel Self Organizing Neural Network Based Estimation of Archie’s Parameters and Water Saturation in Sandstone Reservoir
Authors: G. M. Hamada, A. A. Al-Gathe, A. M. Al-Khudafi
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Determination of water saturation in sandstone is a vital question to determine the initial oil or gas in place in reservoir rocks. Water saturation determination using electrical measurements is mainly on Archie’s formula. Consequently accuracy of Archie’s formula parameters affects water saturation values rigorously. Determination of Archie’s parameters a, m, and n is proceeded by three conventional techniques, Core Archie-Parameter Estimation (CAPE) and 3-D. This work introduces the hybrid system of parallel self-organizing neural network (PSONN) targeting accepted values of Archie’s parameters and, consequently, reliable water saturation values. This work focuses on Archie’s parameters determination techniques; conventional technique, CAPE technique, and 3-D technique, and then the calculation of water saturation using current. Using the same data, a hybrid parallel self-organizing neural network (PSONN) algorithm is used to estimate Archie’s parameters and predict water saturation. Results have shown that estimated Arche’s parameters m, a, and n are highly accepted with statistical analysis, indicating that the PSONN model has a lower statistical error and higher correlation coefficient. This study was conducted using a high number of measurement points for 144 core plugs from a sandstone reservoir. PSONN algorithm can provide reliable water saturation values, and it can supplement or even replace the conventional techniques to determine Archie’s parameters and thereby calculate water saturation profiles.Keywords: water saturation, Archie’s parameters, artificial intelligence, PSONN, sandstone reservoir
Procedia PDF Downloads 123700 Effect of Fines on Liquefaction Susceptibility of Sandy Soil
Authors: Ayad Salih Sabbar, Amin Chegenizadeh, Hamid Nikraz
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Investigation of liquefaction susceptibility of materials that have been used in embankments, slopes, dams, and foundations is very essential. Many catastrophic geo-hazards such as flow slides, declination of foundations, and damage to earth structure are associated with static liquefaction that may occur during abrupt shearing of these materials. Many artificial backfill materials are mixtures of sand with fines and other composition. In order to provide some clarifications and evaluations on the role of fines in static liquefaction behaviour of sand sandy soils, the effect of fines on the liquefaction susceptibility of sand was experimentally examined in the present work over a range of fines content, relative density, and initial confining pressure. The results of an experimental study on various sand-fines mixtures are presented. Undrained static triaxial compression tests were conducted on saturated Perth sand containing 5% bentonite at three different relative densities (10, 50, and 90%), and saturated Perth sand containing both 5% bentonite and slag (2%, 4%, and 6%) at single relative density 10%. Undrained static triaxial tests were performed at three different initial confining pressures (100, 150, and 200 kPa). The brittleness index was used to quantify the liquefaction potential of sand-bentonite-slag mixtures. The results demonstrated that the liquefaction susceptibility of sand-5% bentonite mixture was more than liquefaction susceptibility of clean sandy soil. However, liquefaction potential decreased when both of two fines (bentonite and slag) were used. Liquefaction susceptibility of all mixtures decreased with increasing relative density and initial confining pressure.Keywords: liquefaction, bentonite, slag, brittleness index
Procedia PDF Downloads 215699 Comparative Study of Properties of Iranian Historical Gardens by Focusing on Climate
Authors: Malihe Ahmadi
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Nowadays, stress, tension and neural problems are among the most important concerns of the present age. The environment plays key role on improving mental health and reducing stress of citizens. Establishing balance and appropriate relationship between city and natural environment is of the most important approaches of present century. Type of approach and logical planning for urban green spaces as one of the basic sections of integration with nature, not only plays key role on quality and efficiency of comprehensive urban planning; but also it increases the system of distributing social activities and happiness and lively property of urban environments that leads to permanent urban development. The main purpose of recovering urban identity is considering culture, history and human life style in past. This is a documentary-library research that evaluates the historical properties of Iranian gardens in compliance with climate condition. Results of this research reveal that in addition to following Iranian gardens from common principles of land lot, structure of flowers and plants, water, specific buildings during different ages, the role of climate at different urban areas is among the basics of determining method of designing green spaces and different buildings located at diverse areas i.e. Iranian gardens are a space for merging natural and artificial elements that has inseparable connection with semantic principles and guarantees different functions. Some of the necessities of designing present urban gardens are including: recognition and recreation.Keywords: historical gardens, climate, properties of Iranian gardens, Iran
Procedia PDF Downloads 393698 Subject Teachers’ Perception of the Changing Role of Language in the Curriculum of Secondary Education
Authors: Moldir Makenova
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Alongside the implementation of trilingual education in schools, the Ministry of Education and Science of the Republic of Kazakhstan innovated the school curriculum in 2013 to include a Content and Language Integrated Learning (CLIL) approach. In this regard, some transition issues have arisen, such as unprepared teachers, a need for more awareness of the CLIL approach, and teaching resources. Some teachers view it as a challenge due to its combination of both content and language. This often creates anxiety among teachers who are knowledgeable about their subject areas in Kazakh or Russian but are deficient in delivering the subject’s content in English. Thus, with this new teaching approach, teachers encounter to choose the role of language and answer how language works in the CLIL classroom. This study aimed to explore how teachers experience the changing role of language in the curriculum and to find out what challenges teachers face related to CLIL implementation and how their language proficiency influences their teaching practices. A qualitative comparative case study was conducted in an X Lyceum and a mainstream school piloting CLIL. Data collection procedures were conducted via semi-structured interviews, classroom observations, and document analysis. Eight content teachers were chosen from these two schools as the target group of this study. Subject teachers, rather than language teachers, were chosen as the target group to grasp how the language-related issues in the new curriculum are interpreted by educators who do not necessarily identify themselves as language experts at the outset. The findings showed that mainstream teachers prioritize content over language because, as content teachers, the knowledge of content is more essential for them rather than the language. In contrast, most X Lyceum teachers balance language and content and additionally showed their preferences to support the ‘English language only' policy among 10-11 graders. Moreover, due to the low-level English proficiency, mainstream teachers did highlight the necessity of CLIL training and further collaboration with language teachers. This study will be beneficial for teachers and policy-makers to enable them to solve the issues mentioned above related to the implementation of CLIL. Larger-scale research conducted in the future would further inform its successful deployment country-wide.Keywords: role of language, trilingual education, updated curriculum, teacher practices
Procedia PDF Downloads 66697 Role of Education on Shaping the Personality of the Students in Rural Areas: A Case Study of Daund Taluka in Pune District of Maharashtra, India
Authors: L. K. Shitole
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Usually on the face of it, personality is regarded as the external appearance of an individual. In psychology, the personality is not viewed merely as self or external appears, but it adds much more. Human resources development encompasses the personality development of the students. The student’s development starts right from the childhood and gradually continues right up to the completion of education in professional courses. This paper attempts to find out the role of the educational institutions in shaping the personality of the students from the rural area. Schools and colleges have infrastructural limitations, obtaining good quality and devoted teaching staff poses problems and even outside the school environment there are no private classes which may take care of this deficiency. The researcher has used the standardized test namely “Vyaktitva Shodhika” developed by Gyan Prabodhini, Pune for the students in Daund Taluka. There are 68 objective types of questions in the said questionnaire. Totally a sample size of 4191 students was selected. The sample was quite representative. It is observed that by and large the response indicates that the educational institutions are taking sincere efforts in shaping the personality of the students. In the semi-urban area i.e. at educational institutions of all levels, the performance on this front is excellent and at rest of Daund Taluka there is scope for improvement. Educational institutions of all levels are showing excellent performance in ensuring availability of the requisite infrastructure conducive for the development of the personality of the students. In rest of Daund Taluka there is ample scope for improving the situation. As far as data relating to role of co-curricular activities and sports programs in mental and physical development at various educational institutions is concerned Daund educational institutions have repeated their performance in securing “A” category, while in the rural area of Daund Taluka, there is need to step up the efforts in this regard. In today’s world of knowledge industry, one cannot ignore the importance of education and thereby the personality growth of the students. Accordingly, the educational institutions should undertake consistent research and extension activities in the area of personality development.Keywords: personality, attitude, infrastructure, quality of education, learning environment, teacher’s contribution, family and society’s role
Procedia PDF Downloads 464696 The Impact of Artificial Intelligence on Human Rights Legislations and Evolution
Authors: Nawal Yacoub Halim Abdelmasih
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The intersection between development and human rights has been the factor of scholarly debate for a long term. therefore, some of standards, which enlarge from the proper to development to the human rights-based totally method to development, had been adopted to apprehend the dynamics among the two standards. no matter these attempts, the exact relationship among improvement and human rights has not been completely determined but. however, the inevitable interdependence between the two notions and the idea that improvement efforts ought to be undertaken with the aid of giving due regard to human rights ensures has won momentum in recent years. then again, the emergence of sustainable development as a extensively common technique in development dreams and policies makes this unsettled convergence even extra complicated. The vicinity of sustainable improvement in human rights regulation discourse and the function of the latter in making sure the sustainability of development applications name for a scientific observe. as a result, this newsletter seeks to discover the relationship among development and human rights, particularly focusing at the location given to sustainable development principles in international human proper regulation. it'll similarly quest whether or not there is a proper to sustainable improvement diagnosed therein. as a result, the item asserts that the ideas of sustainable improvement are immediately or circuitously diagnosed in diverse human rights contraptions, which affords an affirmative response to the question raised hereinabove. This paintings, therefore, will make expeditions via international and regional human rights devices in addition to case legal guidelines and interpretative hints of human rights bodies to show this speculation.Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security
Procedia PDF Downloads 12695 [Keynote Talk]: sEMG Interface Design for Locomotion Identification
Authors: Rohit Gupta, Ravinder Agarwal
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Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.Keywords: classifiers, feature selection, locomotion, sEMG
Procedia PDF Downloads 288694 A Qualitative Evaluation of a Civic Curriculum to Increase Global Citizenship Competences in University Students in the Netherlands
Authors: Park Eri, Sklad Marcin, Tsirogianni Stavroula
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In a world where there is increasing exchange and movement of populations groups, and interconnectedness, there are plenty of opportunities for mutual cultural enrichment. However, in everyday life, relations among different cultural groups do not go that smoothly often resulting in discrimination, inequalities and violence. The increasing differentiation of roles, values and worldviews raise a lot of tensions and dilemmas for the state and people -especially in western liberal societies- about issues of acceptance, fairness, justice, autonomy, plurality, freedom, equality and cohesion. Cultural diversity requires a deeper understanding of the roots, meaning and consequences of group differences. We argue, that a psychology from the standpoint of the subject needs to be developed further according to new societal needs. This means within a globalised society, issues regarding the construction of the other as another have become of utmost importance. In constructing the other human beings construct their ideal and possible worlds and meanings about their lives and their significance by drawing on a set of cultural norms, beliefs and values embedded in the different contexts whereby they find themselves in. In this article, we are describing a series of exercises developed in collaboration with University students in the Netherlands that have been piloted with undergraduate 2nd year University Psychology students. These exercises aimed at making tangible and obvious how students apply different moral principles and norms to regulate relationships, which are linked to hegemonic ideological forces. The exercises were in the form of thought experiments that included 8 moral dilemmas, inspired by the moral foundations theory, that touched on different moral principles. The moral dilemmas were built onto each other in incremental steps: from a very tangible/hands-on level to more challenging and demanding ones which require to step into pre-existing networks on knowledge and discourses. After the execution of every dilemma, a discussion followed, which is focused on building links between the ‘theme of the exercise’ and participants’ own lives experiences. In this paper, we provide an evaluation of the methodology used through a discursive analysis of the discussion between the students and the teacher.Keywords: citizenship, moral dilemmas, social justice, education
Procedia PDF Downloads 316693 Estimation of Twist Loss in the Weft Yarn during Air-Jet Weft Insertion
Authors: Muhammad Umair, Yasir Nawab, Khubab Shaker, Muhammad Maqsood, Adeel Zulfiqar, Danish Mahmood Baitab
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Fabric is a flexible woven material consisting of a network of natural or artificial fibers often referred to as thread or yarn. Today fabrics are produced by weaving, braiding, knitting, tufting and non-woven. Weaving is a method of fabric production in which warp and weft yarns are interlaced perpendicular to each other. There is infinite number of ways for the interlacing of warp and weft yarn. Each way produces a different fabric structure. The yarns parallel to the machine direction are called warp yarns and the yarns perpendicular to the machine direction are called weft or filling yarns. Air jet weaving is the modern method of weft insertion and considered as high speed loom. The twist loss in air jet during weft insertion affects the strength. The aim of this study was to investigate the effect of twist change in weft yarn during air-jet weft insertion. A total number of 8 samples were produced using 1/1 plain and 3/1 twill weave design with two fabric widths having same loom settings. Two different types of yarns like cotton and PC blend were used. The effect of material type, weave design and fabric width on twist change of weft yarn was measured and discussed. Twist change in the different types of weft yarn and weave design was measured and compared the twist change in the weft yarn with the yarn before weft yarn insertion and twist loss is measured. Wider fabric leads to higher twist loss in the yarn.Keywords: air jet loom, twist per inch, twist loss, weft yarn
Procedia PDF Downloads 394692 Cognitive Model of Analogy Based on Operation of the Brain Cells: Glial, Axons and Neurons
Authors: Ozgu Hafizoglu
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Analogy is an essential tool of human cognition that enables connecting diffuse and diverse systems with attributional, deep structural, casual relations that are essential to learning, to innovation in artificial worlds, and to discovery in science. Cognitive Model of Analogy (CMA) leads and creates information pattern transfer within and between domains and disciplines in science. This paper demonstrates the Cognitive Model of Analogy (CMA) as an evolutionary approach to scientific research. The model puts forward the challenges of deep uncertainty about the future, emphasizing the need for flexibility of the system in order to enable reasoning methodology to adapt to changing conditions. In this paper, the model of analogical reasoning is created based on brain cells, their fractal, and operational forms within the system itself. Visualization techniques are used to show correspondences. Distinct phases of the problem-solving processes are divided thusly: encoding, mapping, inference, and response. The system is revealed relevant to brain activation considering each of these phases with an emphasis on achieving a better visualization of the brain cells: glial cells, axons, axon terminals, and neurons, relative to matching conditions of analogical reasoning and relational information. It’s found that encoding, mapping, inference, and response processes in four-term analogical reasoning are corresponding with the fractal and operational forms of brain cells: glial, axons, and neurons.Keywords: analogy, analogical reasoning, cognitive model, brain and glials
Procedia PDF Downloads 180691 Deep Learning Approach for Chronic Kidney Disease Complications
Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia
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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis
Procedia PDF Downloads 129690 Experiencing Daylight in Architectural Spaces: A Case Study of Public Buildings in the Context of Karachi, Pakistan
Authors: Safia Asif, Saadia Bano
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In a world with rapidly depleting resources, using artificial lighting during daytime is an act of human ignorance. Imitated light is the major source of energy consumption in public buildings. Despite, the fact that substantial working hours of these buildings usually persist in natural daylight time; there is a trend of isolated, un-fenestrated and a-contextual interiors majorly dependent on active energy sources. On the contrary, if direct and un-controlled sunlight is allowed inside the building, it will create visual and thermal discomfort. Controlled daylighting with appropriate design mechanisms is one of the important aspects of achieving thermal and visual comfort. The natural sunlight can be utilized intelligently with the help of architectural thermal controlling mechanisms to achieve a healthy and productive environment. This paper is an attempt to investigate and analyze the importance of daylighting with reference to energy efficiency and thermal comfort. For this purpose, three public buildings including two educational institutions and one general post office are selected, as case-studies in the context of Karachi, Pakistan. Various parameters of visual and thermal comfort are analyzed which includes orientation, ceiling heights, overall building profile along with daylight controlling mechanisms in terms of penetration, distribution, protection, and control. In the later part of the research, a questionnaire survey is also conducted to evaluate the user experience in terms of adequate daylighting and thermal comfort.Keywords: daylight, public buildings, sustainable architecture, visual and thermal comfort
Procedia PDF Downloads 204689 An Ethnographic Inquiry: Exploring the Saudi Students’ Motivation to Learn English Language
Authors: Musa Alghamdi
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Although Saudi students’ motivation to learn English language as a foreign language in Saudi Arabia have been investigated by a number of studies; these have appeared almost completely as using the quantitative research paradigm. There is a significant lack of research that explores the Saudi students’ motivation using qualitative methods. It was essential, as an investigator, to be immersed in the community to understand the individuals under study via their actions and words, their thoughts, views and beliefs, and how those individuals credited to activities. Thus, the study aims to explore the Saudi students’ motivation to learn English language as a foreign language in Saudi Arabia employing qualitative methodology via applying ethnography. The study will be carried out in Saudi Arabia. Ethnography qualitative approach will be used in the current study by employing formal and informal interview instruments. Gardner’s motivation theory is used as frameworks for this study to aid the understanding of the research findings. The author, an English language lecturer, will undertake participant observations for 4 months. He will work as teaching-assistant (on an unpaid basis) with EFL lecturers in different discipline department at a Saudi university where students study English language as a minor course. The researcher will start with informal ethnographical interview with students during his existence with the informants in their natural context. Then the researcher will utilize the semi-structural interview. The informal interview will be with 14-16 students, then, he will carry out semi-structural interview with the same informants to go deep in their natural context to find out to what extent the Saudi university students are motivated to learn English as a foreign language. As well as, to find out the reasons that played roles in that. The findings of this study will add new knowledge about what factors motivate universities’ Saudi students to learn English language in Saudi Arabia. Very few chances have given to students to express themselves and to speak about their feelings in a more comfortable way in order to gain a clear image of those factors. The working author as an EFL teacher and lecturer will provide him secure access into EFL teaching and learning setting. It will help him attain richer insights into the nature EFL context in universities what will provide him with richer insights into the reasons behind the weakness of EFL level among Saudi students.Keywords: motivation, ethnography, Saudi, language
Procedia PDF Downloads 291688 Generative Adversarial Network Based Fingerprint Anti-Spoofing Limitations
Authors: Yehjune Heo
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Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.Keywords: anti-spoofing, CNN, fingerprint recognition, GAN
Procedia PDF Downloads 179687 Distributed System Computing Resource Scheduling Algorithm Based on Deep Reinforcement Learning
Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar
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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence
Procedia PDF Downloads 102686 How Natural Environments Are Being Used by Teachers to Improve Student Learning and Wellbeing in Australia
Authors: Jade Fersterer, Tristan Snell, Mark Rickinson
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This paper is designed to provide a review of the literature concerning the impact of natural environments on student learning and wellbeing in Australia. Specific areas of interest include how child-led and teacher-led pedagogies differ in outdoor learning settings, and the impact of each approach on children’s well-being, behavior, relationships with others as well as educational outcomes. The review will include links to possibilities for future research, including a Ph.D. currently being undertaken in Australia, which aims to fulfill a considerable gap in psychological, educational and outdoor learning research, regarding how natural environments are being used by teachers to improve learning and wellbeing among primary school students. The proposed study aims to understand if children’s experience of learning, 1. in a natural environment, and 2. in a child-led way, can support and strengthen their skills across several areas of development, including those required for positive educational outcomes. Data will be collected from a sample of primary school students and teachers via both quantitative and qualitative methods, including a pre- and post-questionnaire, direct observation, and semi-structured interviews. The study will have valuable implications for the provision of quality education as well as the promotion of good health and wellbeing. The implications of the research will be useful not only for teachers and parents but also for Psychologists working with children and young people in both a school and clinical setting. Understanding the impacts and implications of child-led learning and exposure to natural environments provides the opportunity to build on the current school curriculum. The inclusion of child-led experiences in nature may provide a simple way to build enthusiasm for school and learning, cultivating skills for life and relationships as well as meeting current curriculum requirements and building capacity for ongoing academic pursuits. In addition, understanding the impact of learning in a natural environment on wellbeing will assist in the development and dissemination of an educational model that could help mitigate the negative health outcomes associated with reduced physical activity and decreasing contact with nature among children.Keywords: child-led learning, educational outcomes, natural environments, wellbeing
Procedia PDF Downloads 119685 Experiential Language Learning as a Tool for Effective Global Leadership
Authors: Christiane Dumont
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This paper proposes to revisit foreign-language learning as a tool to increase motivation through advocacy and develop effective natural communication skills, which are critical leadership qualities. To this end, collaborative initiatives undertaken by advanced university students of French with local and international community partners will be reviewed. Close attention will be paid to the acquisition of intercultural skills, the reflective process, as well as the challenges and outcomes. Two international development projects conducted in Haiti will be highlighted, i.e., collaboration with a network of providers in the Haitian cultural heritage preservation and tourism sector (2014-15) and development of investigation and teacher training tools for a primary/secondary school in the Port-au-Prince area (current). The choice of community-service learning as a framework to teach French-as-a-second-language stemmed from the need to raise awareness against stereotypes and prejudice, which hinder the development of effective intercultural skills. This type of experiential education also proved very effective in identifying and preventing miscommunication caused by the lack of face-to-face interaction in our increasingly technology-mediated world. Learners experienced first-hand, the challenges and advantages of face-to-face communication, which, in turn, enhanced their motivation for developing effective intercultural skills. Vygotsky's and Kolb's theories, current research on service learning (Dwight, Eyler), action/project-based pedagogy (Beckett), and reflective learning (TSC Farrell), will provide useful background to analyze the benefits and challenges of community-service learning. The ultimate goal of this paper is to find out what makes experiential learning truly unique and transformative for both the learners and the community they wish to serve. It will demonstrate how enhanced motivation, community engagement, and clear, concise, and respectful communication impact and empower learners. The underlying hope is to help students in high-profile, and leading-edge industries become effective global leaders.Keywords: experiential learning, intercultural communication, reflective learning, effective leadership, learner motivation
Procedia PDF Downloads 102684 A Literature Review on Emotion Recognition Using Wireless Body Area Network
Authors: Christodoulou Christos, Politis Anastasios
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The utilization of Wireless Body Area Network (WBAN) is experiencing a notable surge in popularity as a result of its widespread implementation in the field of smart health. WBANs utilize small sensors implanted within the human body to monitor and record physiological indicators. These sensors transmit the collected data to hospitals and healthcare facilities through designated access points. Bio-sensors exhibit a diverse array of shapes and sizes, and their deployment can be tailored to the condition of the individual. Multiple sensors may be strategically placed within, on, or around the human body to effectively observe, record, and transmit essential physiological indicators. These measurements serve as a basis for subsequent analysis, evaluation, and therapeutic interventions. In conjunction with physical health concerns, numerous smartwatches are engineered to employ artificial intelligence techniques for the purpose of detecting mental health conditions such as depression and anxiety. The utilization of smartwatches serves as a secure and cost-effective solution for monitoring mental health. Physiological signals are widely regarded as a highly dependable method for the recognition of emotions due to the inherent inability of individuals to deliberately influence them over extended periods of time. The techniques that WBANs employ to recognize emotions are thoroughly examined in this article.Keywords: emotion recognition, wireless body area network, WBAN, ERC, wearable devices, psychological signals, emotion, smart-watch, prediction
Procedia PDF Downloads 44683 Early Depression Detection for Young Adults with a Psychiatric and AI Interdisciplinary Multimodal Framework
Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin
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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder
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