Search results for: voting machines in the USA
256 Evaluating Machine Learning Techniques for Activity Classification in Smart Home Environments
Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard
Abstract:
With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.Keywords: activities of daily living, classification, internet of things, machine learning, prediction, smart home
Procedia PDF Downloads 358255 The Asymmetric Proximal Support Vector Machine Based on Multitask Learning for Classification
Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang
Abstract:
Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification
Procedia PDF Downloads 136254 A Machine Learning Framework Based on Biometric Measurements for Automatic Fetal Head Anomalies Diagnosis in Ultrasound Images
Authors: Hanene Sahli, Aymen Mouelhi, Marwa Hajji, Amine Ben Slama, Mounir Sayadi, Farhat Fnaiech, Radhwane Rachdi
Abstract:
Fetal abnormality is still a public health problem of interest to both mother and baby. Head defect is one of the most high-risk fetal deformities. Fetal head categorization is a sensitive task that needs a massive attention from neurological experts. In this sense, biometrical measurements can be extracted by gynecologist doctors and compared with ground truth charts to identify normal or abnormal growth. The fetal head biometric measurements such as Biparietal Diameter (BPD), Occipito-Frontal Diameter (OFD) and Head Circumference (HC) needs to be monitored, and expert should carry out its manual delineations. This work proposes a new approach to automatically compute BPD, OFD and HC based on morphological characteristics extracted from head shape. Hence, the studied data selected at the same Gestational Age (GA) from the fetal Ultrasound images (US) are classified into two categories: Normal and abnormal. The abnormal subjects include hydrocephalus, microcephaly and dolichocephaly anomalies. By the use of a support vector machines (SVM) method, this study achieved high classification for automated detection of anomalies. The proposed method is promising although it doesn't need expert interventions.Keywords: biometric measurements, fetal head malformations, machine learning methods, US images
Procedia PDF Downloads 288253 Achieving High Renewable Energy Penetration in Western Australia Using Data Digitisation and Machine Learning
Authors: A. D. Tayal
Abstract:
The energy industry is undergoing significant disruption. This research outlines that, whilst challenging; this disruption is also an emerging opportunity for electricity utilities. One such opportunity is leveraging the developments in data analytics and machine learning. As the uptake of renewable energy technologies and complimentary control systems increases, electricity grids will likely transform towards dense microgrids with high penetration of renewable generation sources, rich in network and customer data, and linked through intelligent, wireless communications. Data digitisation and analytics have already impacted numerous industries, and its influence on the energy sector is growing, as computational capabilities increase to manage big data, and as machines develop algorithms to solve the energy challenges of the future. The objective of this paper is to address how far the uptake of renewable technologies can go given the constraints of existing grid infrastructure and provides a qualitative assessment of how higher levels of renewable energy penetration can be facilitated by incorporating even broader technological advances in the fields of data analytics and machine learning. Western Australia is used as a contextualised case study, given its abundance and diverse renewable resources (solar, wind, biomass, and wave) and isolated networks, making a high penetration of renewables a feasible target for policy makers over coming decades.Keywords: data, innovation, renewable, solar
Procedia PDF Downloads 367252 Advancing Dialysis Care Access and Health Information Management: A Blueprint for Nairobi Hospital
Authors: Kimberly Winnie Achieng Otieno
Abstract:
The Nairobi Hospital plays a pivotal role in healthcare provision in East and Central Africa, yet it faces challenges in providing accessible dialysis care. This paper explores strategic interventions to enhance dialysis care, improve access and streamline health information management, with an aim of fostering an integrated and patient-centered healthcare system in our region. Challenges at The Nairobi Hospital The Nairobi Hospital currently grapples with insufficient dialysis machines which results in extended turn around times. This issue stems from both staffing bottle necks and infrastructural limitations given our growing demand for renal care services. Our Paper-based record keeping system and fragmented flow of information downstream hinders the hospital’s ability to manage health data effectively. There is also a need for investment in expanding The Nairobi Hospital dialysis facilities to far reaching communities. Setting up satellite clinics that are closer to people who live in areas far from the main hospital will ensure better access to underserved areas. Community Outreach and Education Implementing education programs on kidney health within local communities is vital for early detection and prevention. Collaborating with local leaders and organizations can establish a proactive approach to renal health hence reducing the demand for acute dialysis interventions. We can amplify this effort by expanding The Nairobi Hospital’s corporate social responsibility outreach program with weekend engagement activities such as walks, awareness classes and fund drives. Enhancing Efficiency in Dialysis Care Demand for dialysis services continues to rise due to an aging Kenyan population and the increasing prevalence of chronic kidney disease (CKD). Present at this years International Nursing Conference are a diverse group of caregivers from around the world who can share with us their process optimization strategies, patient engagement techniques and resource utilization efficiencies to catapult The Nairobi Hospital to the 21st century and beyond. Plans are underway to offer ongoing education opportunities to keep staff updated on best practices and emerging technologies in addition to utilizing a patient feedback mechanisms to identify areas for improvement and enhance satisfaction. Staff empowerment and suggestion boxes address The Nairobi Hospital’s organizational challenges. Current financial constraints may limit a leapfrog in technology integration such as the acquisition of new dialysis machines and an investment in predictive analytics to forecast patient needs and optimize resource allocation. Streamlining Health Information Management Fully embracing a shift to 100% Electronic Health Records (EHRs) is a transformative step toward efficient health information management. Shared information promotes a holistic understanding of patients’ medical history, minimizing redundancies and enhancing overall care quality. To manage the transition to community-based care and EHRs effectively, a phased implementation approach is recommended. Conclusion By strategically enhancing dialysis care access and streamlining health information management, The Nairobi Hospital can strengthen its position as a leading healthcare institution in both East and Central Africa. This comprehensive approach aligns with the hospital’s commitment to providing high-quality, accessible, and patient-centered care in an evolving landscape of healthcare delivery.Keywords: Africa, urology, diaylsis, healthcare
Procedia PDF Downloads 59251 Civic E-Participation in Central and Eastern Europe: A Comparative Analysis
Authors: Izabela Kapsa
Abstract:
Civic participation is an important aspect of democracy. The contemporary model of democracy is based on citizens' participation in political decision-making (deliberative democracy, participatory democracy). This participation takes many forms of activities like display of slogans and symbols, voting, social consultations, political demonstrations, membership in political parties or organizing civil disobedience. The countries of Central and Eastern Europe after 1989 are characterized by great social, economic and political diversity. Civil society is also part of the process of democratization. Civil society, funded by the rule of law, civil rights, such as freedom of speech and association and private ownership, was to play a central role in the development of liberal democracy. Among the many interpretations of concepts, defining the concept of contemporary democracy, one can assume that the terms civil society and democracy, although different in meaning, nowadays overlap. In the post-communist countries, the process of shaping and maturing societies took place in the context of a struggle with a state governed by undemocratic power. State fraud or repudiation of the institution is a representative state, which in the past was the only way to manifest and defend its identity, but after the breakthrough became one of the main obstacles to the development of civil society. In Central and Eastern Europe, there are many obstacles to the development of civil society, for example, the elimination of economic poverty, the implementation of educational campaigns, consciousness-related obstacles, the formation of social capital and the deficit of social activity. Obviously, civil society does not only entail an electoral turnout but a broader participation in the decision-making process, which is impossible without direct and participative democratic institutions. This article considers such broad forms of civic participation and their characteristics in Central and Eastern Europe. The paper is attempts to analyze the functioning of electronic forms of civic participation in Central and Eastern European states. This is not accompanied by a referendum or a referendum initiative, and other forms of political participation, such as public consultations, participative budgets, or e-Government. However, this paper will broadly present electronic administration tools, the application of which results from both legal regulations and increasingly common practice in state and city management. In the comparative analysis, the experiences of post-communist bloc countries will be summed up to indicate the challenges and possible goals for further development of this form of citizen participation in the political process. The author argues that for to function efficiently and effectively, states need to involve their citizens in the political decision-making process, especially with the use of electronic tools.Keywords: Central and Eastern Europe, e-participation, e-government, post-communism
Procedia PDF Downloads 194250 Railway Crane Accident: A Comparative Metallographic Test on Pins Fractured during Operation
Authors: Thiago Viana
Abstract:
Eventually train accidents occur on railways and for some specific cases it is necessary to use a train rescue with a crane positioned under a platform wagon. These tumbled machines are collected and sent to the machine shop or scrap yard. In one of these cranes that were being used to rescue a wagon, occurred a fall of hoist due to fracture of two large pins. The two pins were collected and sent for failure analysis. This work investigates the main cause and the secondary causes for the initiation of the fatigue crack. All standard failure analysis procedures were applied, with careful evaluation of the characteristics of the material, fractured surfaces and, mainly, metallographic tests using an optical microscope to compare the geometry of the peaks and valleys of the thread of the pins and their respective seats. By metallographic analysis, it was concluded that the fatigue cracks were started from a notch (stress concentration) in the valley of the threads of the pin applied to the right side of the crane (pin 1). In this, it was verified that the peaks of the threads of the pin seat did not have proper geometry, with sharp edges being present that caused such notches. The visual analysis showed that fracture of the pin on the left side of the crane (pin 2) was brittle type, being a consequence of the fracture of the first one. Recommendations for this and other railway cranes have been made, such as nondestructive testing, stress calculation, design review, quality control and suitability of the mechanical forming process of the seat threads and pin threads.Keywords: crane, fracture, pin, railway
Procedia PDF Downloads 109249 Newspaper Headlines as Tool for Political Propaganda in Nigeria: Trend Analysis of Implications on Four Presidential Elections
Authors: Muhammed Jamiu Mustapha, Jamiu Folarin, Stephen Obiri Agyei, Rasheed Ademola Adebiyi, Mutiu Iyanda Lasisi
Abstract:
The role of the media in political discourse cannot be overemphasized as they form an important part of societal development. The media institution is considered the fourth estate of the realm because it serves as a check and balance to the arms of government (Executive, Legislature and Judiciary) especially in a democratic setup, and makes public office holders accountable to the people. They scrutinize the political candidates and conduct a holistic analysis of the achievement of the government in order to make the people’s representative accountable to the electorates. The media in Nigeria play a seminal role in shaping how people vote during elections. Newspaper headlines are catchy phrases that easily capture the attention of the audience and call them (audience) to action. Research conducted on newspaper headlines looks at the linguistic aspect and how the tenses used has a resultant effect on peoples’ attitude and behaviour. Communication scholars have also conducted studies that interrogate whether newspaper headlines influence peoples' voting patterns and decisions. Propaganda and negative stories about political opponents are stapling features in electioneering campaigns. Nigerian newspaper readers have the characteristic of scanning newspaper headlines. And the question is whether politicians effectively have played into this tendency to brand opponents negatively, based on half-truths and inadequate information. This study illustrates major trends in the Nigerian political landscape looking at the past four presidential elections and frames the progress of the research in the extant body of political propaganda research in Africa. The study will use the quantitative content analysis of newspaper headlines from 2007 to 2019 to be able to ascertain whether newspaper headlines had any effect on the election results of the presidential elections during these years. This will be supplemented by Key Informant Interviews of political scientists or experts to draw further inferences from the quantitative data. Drawing on newspaper headlines of selected newspapers in Nigeria that have a political propaganda angle for the presidential elections, the analysis will correspond to and complements extant descriptions of how the field of political propaganda has been developed in Nigeria, providing evidence of four presidential elections that have shaped Nigerian politics. Understanding the development of the behavioural change of the electorates provide useful context for trend analysis in political propaganda communication. The findings will contribute to how newspaper headlines are used partly or wholly to decide the outcome of presidential elections in Nigeria.Keywords: newspaper headlines, political propaganda, presidential elections, trend analysis
Procedia PDF Downloads 238248 Roughness Discrimination Using Bioinspired Tactile Sensors
Authors: Zhengkun Yi
Abstract:
Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination
Procedia PDF Downloads 313247 Resource Leveling Optimization in Construction Projects of High Voltage Substations Using Nature-Inspired Intelligent Evolutionary Algorithms
Authors: Dimitrios Ntardas, Alexandros Tzanetos, Georgios Dounias
Abstract:
High Voltage Substations (HVS) are the intermediate step between production of power and successfully transmitting it to clients, making them one of the most important checkpoints in power grids. Nowadays - renewable resources and consequently distributed generation are growing fast, the construction of HVS is of high importance both in terms of quality and time completion so that new energy producers can quickly and safely intergrade in power grids. The resources needed, such as machines and workers, should be carefully allocated so that the construction of a HVS is completed on time, with the lowest possible cost (e.g. not spending additional cost that were not taken into consideration, because of project delays), but in the highest quality. In addition, there are milestones and several checkpoints to be precisely achieved during construction to ensure the cost and timeline control and to ensure that the percentage of governmental funding will be granted. The management of such a demanding project is a NP-hard problem that consists of prerequisite constraints and resource limits for each task of the project. In this work, a hybrid meta-heuristic method is implemented to solve this problem. Meta-heuristics have been proven to be quite useful when dealing with high-dimensional constraint optimization problems. Hybridization of them results in boost of their performance.Keywords: hybrid meta-heuristic methods, substation construction, resource allocation, time-cost efficiency
Procedia PDF Downloads 153246 Decision Tree Based Scheduling for Flexible Job Shops with Multiple Process Plans
Authors: H.-H. Doh, J.-M. Yu, Y.-J. Kwon, J.-H. Shin, H.-W. Kim, S.-H. Nam, D.-H. Lee
Abstract:
This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i. e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduling approach that selects the best priority rule combination after many simulation runs, this study suggests a decision tree based approach in which a decision tree is used to select a priority rule combination adequate for a specific system state and hence the burdens required for developing simulation models and carrying out simulation runs can be eliminated. The decision tree based scheduling approach consists of construction and scheduling modules. In the construction module, a decision tree is constructed using a four-stage algorithm, and in the scheduling module, a priority rule combination is selected using the decision tree. To show the performance of the decision tree based approach suggested in this study, a case study was done on a flexible job shop with reconfigurable manufacturing cells and a conventional job shop, and the results are reported by comparing it with individual priority rule combinations for the objectives of minimizing total flow time and total tardiness.Keywords: flexible job shop scheduling, decision tree, priority rules, case study
Procedia PDF Downloads 358245 Application of Rapid Eye Imagery in Crop Type Classification Using Vegetation Indices
Authors: Sunita Singh, Rajani Srivastava
Abstract:
For natural resource management and in other applications about earth observation revolutionary remote sensing technology plays a significant role. One of such application in monitoring and classification of crop types at spatial and temporal scale, as it provides latest, most precise and cost-effective information. Present study emphasizes the use of three different vegetation indices of Rapid Eye imagery on crop type classification. It also analyzed the effect of each indices on classification accuracy. Rapid Eye imagery is highly demanded and preferred for agricultural and forestry sectors as it has red-edge and NIR bands. The three indices used in this study were: the Normalized Difference Vegetation Index (NDVI), the Green Normalized Difference Vegetation Index (GNDVI), and the Normalized Difference Red Edge Index (NDRE) and all of these incorporated the Red Edge band. The study area is Varanasi district of Uttar Pradesh, India and Radial Basis Function (RBF) kernel was used here for the Support Vector Machines (SVMs) classification. Classification was performed with these three vegetation indices. The contribution of each indices on image classification accuracy was also tested with single band classification. Highest classification accuracy of 85% was obtained using three vegetation indices. The study concluded that NDRE has the highest contribution on classification accuracy compared to the other vegetation indices and the Rapid Eye imagery can get satisfactory results of classification accuracy without original bands.Keywords: GNDVI, NDRE, NDVI, rapid eye, vegetation indices
Procedia PDF Downloads 362244 Reinforcement Learning Optimization: Unraveling Trends and Advancements in Metaheuristic Algorithms
Authors: Rahul Paul, Kedar Nath Das
Abstract:
The field of machine learning (ML) is experiencing rapid development, resulting in a multitude of theoretical advancements and extensive practical implementations across various disciplines. The objective of ML is to facilitate the ability of machines to perform cognitive tasks by leveraging knowledge gained from prior experiences and effectively addressing complex problems, even in situations that deviate from previously encountered instances. Reinforcement Learning (RL) has emerged as a prominent subfield within ML and has gained considerable attention in recent times from researchers. This surge in interest can be attributed to the practical applications of RL, the increasing availability of data, and the rapid advancements in computing power. At the same time, optimization algorithms play a pivotal role in the field of ML and have attracted considerable interest from researchers. A multitude of proposals have been put forth to address optimization problems or improve optimization techniques within the domain of ML. The necessity of a thorough examination and implementation of optimization algorithms within the context of ML is of utmost importance in order to provide guidance for the advancement of research in both optimization and ML. This article provides a comprehensive overview of the application of metaheuristic evolutionary optimization algorithms in conjunction with RL to address a diverse range of scientific challenges. Furthermore, this article delves into the various challenges and unresolved issues pertaining to the optimization of RL models.Keywords: machine learning, reinforcement learning, loss function, evolutionary optimization techniques
Procedia PDF Downloads 76243 Implementation of European Court of Human Right Judgments and State Sovereignty
Authors: Valentina Tereshkova
Abstract:
The paper shows how the relationship between international law and national sovereignty is viewed through the implementation of European Court of Human Right judgments. Methodology: Сonclusions are based on a survey of representatives of the legislative authorities and judges of the Krasnoyarsk region, the Rostov region, Sverdlovsk region and Tver region. The paper assesses the activities of the Russian Constitutional Court from 1998 to 2015 related to the establishment of the implementation mechanism and the Russian Constitutional Court judgments of 14.07.2015, № 21-P and of 19.04.2016, № 12-P where the Constitutional Court stated the impossibility of executing ECtHR judgments. I. Implementation of ECHR judgments by courts and other authorities. Despite the publication of the report of the RF Ministry of Justice on the implementation, we could not find any formal information on the Russian policy of the ECtHR judgment implementation. Using the results of the survey, the paper shows the effect of ECtHR judgments on law and legal practice in Russia. II. Implementation of ECHR judgments by Russian Constitutional Court. Russian Constitutional Court had implemented the ECtHR judgments. However, the Court determined on July, 14, 2015 its competence to consider the question of implementation of ECHR judgments. Then, it stated that the execution of the judgment [Anchugov and Gladkov case] was impossible because the Russian Constitution has the highest legal force on April, 19, 2016. Recently the CE Committee of Ministers asked Russia to provide ‘without further delay’ a compensation plan for the Yukos case. On November 11, 2016, Constitutional Court accepted a request from the Ministry of Justice to consider the possibility of execution of the ECtHR judgment in the Yukos case. Such a request has been made possible due to a lack of implementation mechanism. Conclusion: ECtHR judgments are as an effective tool to solve the structural problems of a legal system. However, Russian experts consider the ECHR as a tool of protection of individual rights. The paper shows link between the survey results and the absence of the implementation mechanism. New Article 104 par. 2 and Article 106 par. 2 of the Federal Law of the Constitutional Court are in conflict with international obligations of the Convention on the Law on Treaties 1969 and Article 46 ECHR. Nevertheless, a dialogue may be possible between Constitutional Court and the ECtHR. In its judgment [19.04.2016] the Constitutional Court determined that the general measures to ensure fairness, proportionality and differentiation of the restrictions of voting rights were possible in judicial practice. It also stated the federal legislator had the power ‘to optimize the system of Russian criminal penalties’. Despite the fact that the Constitutional Court presented the Görgülü case [Görgülü v Germany] as an example of non-execution of the ECtHR judgment, the paper proposes to draw on the experience of German Constitutional Court, which in the Görgülü case, on the one hand, stressed national sovereignty and, on the other hand, took advantage of this sovereignty, to resolve the issue in accordance with the ECHR.Keywords: implementation of ECtHR judgments, sovereignty, supranational jurisdictions, principle of subsidiarity
Procedia PDF Downloads 194242 Optimization of a Flux Switching Permanent Magnet Machine Using Laminated Segmented Rotor
Authors: Seyedmilad Kazemisangdehi, Seyedmehdi Kazemisangdehi
Abstract:
Flux switching permanent magnet machines are considered for wide range of applications because of their outstanding merits including high torque/power densities, high efficiency, simple and robust rotor structure. Therefore, several topologies have been proposed like the PM exited flux switching machine, hybrid excited flux switching type, and so on. Recently, a novel laminated segmented rotor flux switching permanent magnet machine was introduced. It features flux barriers on rotor structure to enhance the performances of machine including torque ripple reduction and also torque and efficiency improvements at the same time. This is while, the design of barriers was not optimized by the authors. Therefore, in this paper three coefficients regarding the position of the barriers are considered for optimization. The effect of each coefficient on the performance of this machine is investigated by finite element method and finally an optimized design of flux barriers based on these three coefficients is proposed from different points of view including electromagnetic torque maximization and cogging torque/torque ripple minimization. At optimum design from maximum developed torque aspect, this machine generates 0.65 Nm torque higher than that of the not-optimized design with an almost 0.4 % improvement in efficiency.Keywords: finite element analysis, FSPM, laminated segmented rotor flux switching permanent magnet machine, optimization
Procedia PDF Downloads 231241 Industrial Applications of Additive Manufacturing and 3D Printing Technology: A Review from South Africa Perspective
Authors: Micheal O. Alabi
Abstract:
Additive manufacturing (AM) is the official industry standard term (ASTM F2792) for all applications of the technology which is also known as 3D printing technology. It is defined as the process of joining materials to make objects from 3D model data, and it is usually layer upon layer, as opposed to subtractive manufacturing methodologies. This technology has gained significant interest within the academic, research institute and industry because of its ability to create complex geometries with customizable material properties. Despite the late adoption of the technology, additive manufacturing has been active in South Africa for past 21 years and it is predicted that additive manufacturing technology will play a significant and game-changing role in the fourth industrial revolution and in particular it promises to play an ever-growing role in efforts to re-industrialize the economy of South Africa. At the end of 2006, there are approximately ninety 3D printers in South Africa and in 2015 it was estimated that there are 3500 additive manufacturing systems and 3D printers in circulation in South Africa. A reasonable number of these additive manufacturing machines are in the high end of the market, in science councils and higher education institutions and this shows that the future of additive manufacturing in South Africa is very brighter compared to other African countries. This paper reviews the past and current industrial applications of additive manufacturing in South Africa from the academic research and industry perspective and what are the benefits of this technology to manufacturing companies and industrial sectors in the country.Keywords: additive manufacturing, 3D printing technology, industrial applications, manufacturing
Procedia PDF Downloads 473240 Root Mean Square-Based Method for Fault Diagnosis and Fault Detection and Isolation of Current Fault Sensor in an Induction Machine
Authors: Ahmad Akrad, Rabia Sehab, Fadi Alyoussef
Abstract:
Nowadays, induction machines are widely used in industry thankful to their advantages comparing to other technologies. Indeed, there is a big demand because of their reliability, robustness and cost. The objective of this paper is to deal with diagnosis, detection and isolation of faults in a three-phase induction machine. Among the faults, Inter-turn short-circuit fault (ITSC), current sensors fault and single-phase open circuit fault are selected to deal with. However, a fault detection method is suggested using residual errors generated by the root mean square (RMS) of phase currents. The application of this method is based on an asymmetric nonlinear model of Induction Machine considering the winding fault of the three axes frame state space. In addition, current sensor redundancy and sensor fault detection and isolation (FDI) are adopted to ensure safety operation of induction machine drive. Finally, a validation is carried out by simulation in healthy and faulty operation modes to show the benefit of the proposed method to detect and to locate with, a high reliability, the three types of faults.Keywords: induction machine, asymmetric nonlinear model, fault diagnosis, inter-turn short-circuit fault, root mean square, current sensor fault, fault detection and isolation
Procedia PDF Downloads 201239 Improvement of Energy Consumption toward Sustainable Ceramic Industry in Indonesia
Authors: Sawarni Hasibuan, Rudi Effendi Listyanto
Abstract:
The industrial sector is the largest consumer of energy consumption in Indonesia. The ceramics industry includes one of seven industries categorized as an energy-intensive industry. Energy costs on the ceramic floor production process reached 40 percent of the total production cost. The kiln is one of the machines in the ceramic industry that consumes the most gas energy reach 51 percent of gas consumption in ceramic production. The purpose of this research is to make improvement of energy consumption in kiln machine part with the innovation of burner tube to support the sustainability of Indonesian ceramics industry. The tube burner is technically designed to be able to raise the temperature and stabilize the air pressure in the burner so as to facilitate the combustion process in the kiln machine which implies the efficiency of gas consumption required. The innovation of the burner tube also has an impact on the decrease of the combustion chamber pressure in the kiln and managed to keep the pressure of the combustion chamber according to the operational standard of the kiln; consequently, the smoke fan motor power can be lowered and the kiln electric energy consumption is also more efficient. The innovation of burner tube succeeded in saving consume of gas and electricity respectively by 0.0654 GJ and 1,693 x 10-3 GJ for every ton of ceramics produced. Improvement of this energy consumption not only implies the cost savings of production but also supports the sustainability of the Indonesian ceramics industry.Keywords: sustainable ceramic industry, burner tube, kiln, energy efficiency
Procedia PDF Downloads 324238 Comparison Study of Machine Learning Classifiers for Speech Emotion Recognition
Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar
Abstract:
In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers
Procedia PDF Downloads 45237 Sustainable Manufacturing of Solenoid Valve Housing in Fiji: Fused Deposition Modeling (FDM) and Emergy Analysis
Authors: M. Hisham, S. Cabemaiwai, S. Prasad, T. Dauvakatini, R. Ananthanarayanan
Abstract:
A solenoid valve is an important part of many fluid systems. Its purpose is to regulate fluid flow in a machine. Due to the crucial role of the solenoid valve and its design intricacy, it is quite expensive to obtain in Fiji and is not manufactured locally. A concern raised by the local health industry is that the housing of the solenoid valve gets damaged when machines are continuously being used and this part of the valve is very costly to replace due to the lack of availability in Fiji and many other South Pacific region countries. This study explores the agile manufacturing of a solenoid coil housing using the Fused Deposition Modeling (FDM) process. An emergy study was carried out to analyze the feasibility and sustainability of producing the part locally after estimating a Unit Emergy Value (or emergy transformity) of 1.27E+05 sej/j for the electricity in Fiji. The total emergy of the process was calculated to be 3.05E+12 sej, of which a majority was sourced from imported services and materials. Renewable emergy sources contributed to just 16.04% of the total emergy. Therefore, the part is suitable to be manufactured in Fiji with a reasonable quality and a cost of $FJ 2.85. However, the loading on the local environment is found to be significant and therefore, alternative raw materials for the filament like recycled PET should be explored or alternative manufacturing processes may be analyzed before committing to fabricating the part using FDM in its analyzed state.Keywords: emergy analysis, fused deposition modeling, solenoid valve housing, sustainable production
Procedia PDF Downloads 35236 Assessing the Influence of Using Traditional Methods of Construction on Cost and Quality of Building Construction
Authors: Musoke Ivan, Birungi Racheal
Abstract:
The construction trend is characterized by increased use of modern methods yet traditional methods are cheaper in terms of costs, in addition to the benefits it offers to the construction sector, like providing more jobs that could have been worked with the intensive machines. The purpose of this research was to assess the influence of using Traditional methods of construction (TMC) on the costs and quality of building structures and determine the different ways. Traditional methods of construction (TMC) can be applicable and integrated into the construction trend, and propose ways how this can be a success. The study adopted a quantitative method approach targeting various construction professionals like Architects, Quantity surveyors, Engineers, and Construction Managers. Questionnaires and analyses of literature were used to obtain research data and findings. Simple random sampling was used to select 40 construction professionals to which questionnaires were administered. The data was then analyzed using Microsoft Excel. The findings of the research indicate that Traditional methods of construction (TMCs) in Uganda are cheaper in terms of costs, but the quality is still low. This is attributed to a lack of skilled labour and efficient supervision while undertaking tasks leading to low quality. The study identifies strategies that would improve Traditional methods of construction (TMC), which include the employment of skilled manpower and effective supervision. It also identifies the need by stakeholders like the government, clients, and professionals to appreciate Traditional methods of construction (TMCs) and allow for a levelled ground for Traditional Methods of Construction and Modern methods of construction (MMCs).Keywords: traditional methods of construction, integration, cost, quality
Procedia PDF Downloads 63235 Application of Bim Model Data to Estimate ROI for Robots and Automation in Construction Projects
Authors: Brian Romansky
Abstract:
There are many practical, commercially available robots and semi-autonomous systems that are currently available for use in a wide variety of construction tasks. Adoption of these technologies has the potential to reduce the time and cost to deliver a project, reduce variability and risk in delivery time, increase quality, and improve safety on the job site. These benefits come with a cost for equipment rental or contract fees, access to specialists to configure the system, and time needed for set-up and support of the machines while in use. Calculation of the net ROI (Return on Investment) requires detailed information about the geometry of the site, the volume of work to be done, the overall project schedule, as well as data on the capabilities and past performance of available robotic systems. Assembling the required data and comparing the ROI for several options is complex and tedious. Many project managers will only consider the use of a robot in targeted applications where the benefits are obvious, resulting in low levels of adoption of automation in the construction industry. This work demonstrates how data already resident in many BIM (Building Information Model) projects can be used to automate ROI estimation for a sample set of commercially available construction robots. Calculations account for set-up and operating time along with scheduling support tasks required while the automated technology is in use. Configuration parameters allow for prioritization of time, cost, or safety as the primary benefit of the technology. A path toward integration and use of automatic ROI calculation with a database of available robots in a BIM platform is described.Keywords: automation, BIM, robot, ROI.
Procedia PDF Downloads 88234 Sound Noise Control of a Steam Ejector in a Typical Power Plant: Design, Manufacturing, and Testing a Silencer-Muffler
Authors: Ali Siami, Masoud Asayesh, Asghar Najafi, Amirhosein Hamedanian
Abstract:
There are so many noise sources in power generation units that these sources can produce high-level sound noise. Therefore, sound noise reduction methods can assist these industries, especially in these days that laws related to environmental issues become more strict. In a typical power plant, so many machines and devices with high-level sound noise are arranged beside of each others. Therefore, the sound source identification and reducing the noise level can be very vital. In this paper, the procedure for designing, manufacturing and testing of a silencer-muffler used for a power plant steam vent is mentioned. This unit is placed near the residential area and so it is very important to reduce the noise emission. For this purpose, in the first step, measurements have done to identify the sound source and the frequency content of noise. The overall level of noise was so high and it was more than 120dB. Then, the appropriate noise control device is designed according to the measurement results and operational conditions. In the next step, the designed silencer-muffler has been manufactured and installed on the steam discharge of the ejector. For validation of the silencer-muffler effect, the acoustic test was done again in operating mode. Finally, the measurement results before and after the installation are compared. The results have confirmed a considerable reduction in noise level resultant of using silencer-muffler in the designed frequency range.Keywords: silencer-muffler, sound noise control, sound measurement, steam ejector
Procedia PDF Downloads 385233 Diminishing Constitutional Hyper-Rigidity by Means of Digital Technologies: A Case Study on E-Consultations in Canada
Authors: Amy Buckley
Abstract:
The purpose of this article is to assess the problem of constitutional hyper-rigidity to consider how it and the associated tensions with democratic constitutionalism can be diminished by means of using digital democratic technologies. In other words, this article examines how digital technologies can assist us in ensuring fidelity to the will of the constituent power without paying the price of hyper-rigidity. In doing so, it is impossible to ignore that digital strategies can also harm democracy through, for example, manipulation, hacking, ‘fake news,’ and the like. This article considers the tension between constitutional hyper-rigidity and democratic constitutionalism and the relevant strengths and weaknesses of digital democratic strategies before undertaking a case study on Canadian e-consultations and drawing its conclusions. This article observes democratic constitutionalism through the lens of the theory of deliberative democracy to suggest that the application of digital strategies can, notwithstanding their pitfalls, improve a constituency’s amendment culture and, thus, diminish constitutional hyper-rigidity. Constitutional hyper-rigidity is not a new or underexplored concept. At a high level, a constitution can be said to be ‘hyper-rigid’ when its formal amendment procedure is so difficult to enact that it does not take place or is limited in its application. This article claims that hyper-rigidity is one problem with ordinary constitutionalism that fails to satisfy the principled requirements of democratic constitutionalism. Given the rise and development of technology that has taken place since the Digital Revolution, there has been a significant expansion in the possibility for digital democratic strategies to overcome the democratic constitutionalism failures resulting from constitutional hyper-rigidity. Typically, these strategies have included, inter alia, e- consultations, e-voting systems, and online polling forums, all of which significantly improve the ability of politicians and judges to directly obtain the opinion of constituents on any number of matters. This article expands on the application of these strategies through its Canadian e-consultation case study and presents them as a solution to poor amendment culture and, consequently, constitutional hyper-rigidity. Hyper-rigidity is a common descriptor of many written and unwritten constitutions, including the United States, Australian, and Canadian constitutions as just some examples. This article undertakes a case study on Canada, in particular, as it is a jurisdiction less commonly cited in academic literature generally concerned with hyper-rigidity and because Canada has to some extent, championed the use of e-consultations. In Part I of this article, I identify the problem, being that the consequence of constitutional hyper-rigidity is in tension with the principles of democratic constitutionalism. In Part II, I identify and explore a potential solution, the implementation of digital democratic strategies as a means of reducing constitutional hyper-rigidity. In Part III, I explore Canada’s e-consultations as a case study for assessing whether digital democratic strategies do, in fact, improve a constituency’s amendment culture thus reducing constitutional hyper-rigidity and the associated tension that arises with the principles of democratic constitutionalism. The idea is to run a case study and then assess whether I can generalise the conclusions.Keywords: constitutional hyper-rigidity, digital democracy, deliberative democracy, democratic constitutionalism
Procedia PDF Downloads 79232 Mathematical Modelling of Slag Formation in an Entrained-Flow Gasifier
Authors: Girts Zageris, Vadims Geza, Andris Jakovics
Abstract:
Gasification processes are of great interest due to their generation of renewable energy in the form of syngas from biodegradable waste. It is, therefore, important to study the factors that play a role in the efficiency of gasification and the longevity of the machines in which gasification takes place. This study focuses on the latter, aiming to optimize an entrained-flow gasifier by reducing slag formation on its walls to reduce maintenance costs. A CFD mathematical model for an entrained-flow gasifier is constructed – the model of an actual gasifier is rendered in 3D and appropriately meshed. Then, the turbulent gas flow in the gasifier is modeled with the realizable k-ε approach, taking devolatilization, combustion and coal gasification into account. Various such simulations are conducted, obtaining results for different air inlet positions and by tracking particles of varying sizes undergoing devolatilization and gasification. The model identifies potential problematic zones where most particles collide with the gasifier walls, indicating risk regions where ash deposits could most likely form. In conclusion, the effects on the formation of an ash layer of air inlet positioning and particle size allowed in the main gasifier tank are discussed, and possible solutions for decreasing a number of undesirable deposits are proposed. Additionally, an estimate of the impact of different factors such as temperature, gas properties and gas content, and different forces acting on the particles undergoing gasification is given.Keywords: biomass particles, gasification, slag formation, turbulence k-ε modelling
Procedia PDF Downloads 286231 Constraints and Opportunities of Wood Production Value Chain: Evidence from Southwest Ethiopia
Authors: Abduselam Faris, Rijalu Negash, Zera Kedir
Abstract:
This study was initiated to identify constraints and opportunities of the wood production value chain in Southwest Ethiopia. About 385 wood trees growing farmers were randomly interviewed. Similarly, about 30 small-scale wood processors, 30 retailers, 15 local collectors and 5 wholesalers were purposively included in the study. The results of the study indicated that 98.96 % of the smallholder farmers that engaged in the production of wood trees which is used for wood were male-headed, with an average age of 46.88 years. The main activity that the household engaged was agriculture (crop and livestock) which accounts for about 61.56% of the sample respondents. Through value chain mapping of actors, the major value chain participant and supporting actors were identified. On average, the tree-growing farmers generated gross income of 9385.926 Ethiopian birr during the survey year. Among the critical constraints identified along the wood production value chain was limited supply of credit, poor market information dissemination, high interference of brokers, and shortage of machines, inadequate working area and electricity. The availability of forest resources is the leading opportunity in the wood production value chain. Reinforcing the linkage among wood production value chain actors, providing skill training for small-scale processors, and developing suitable policy for wood tree wise use is key recommendations forward.Keywords: value chain analysis, wood production, southwest Ethiopia, constraints and opportunities
Procedia PDF Downloads 97230 Deep Reinforcement Learning Approach for Optimal Control of Industrial Smart Grids
Authors: Niklas Panten, Eberhard Abele
Abstract:
This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control
Procedia PDF Downloads 196229 Human-factor and Ergonomics in Bottling Lines
Authors: Parameshwaran Nair
Abstract:
Filling and packaging lines for bottling of beverages into glass, PET or aluminum containers require specialized expertise and a different configuration of equipment like – Filler, Warmer, Labeller, Crater/Recrater, Shrink Packer, Carton Erector, Carton Sealer, Date Coder, Palletizer, etc. Over the period of time, the packaging industry has evolved from manually operated single station machines to highly automized high-speed lines. Human factor and ergonomics have gained significant consideration in this course of transformation. A pre-requisite for such bottling lines, irrespective of the container type and size, is to be suitable for multi-format applications. It should also be able to handle format changeovers with minimal adjustment. It should have variable capacity and speeds, for providing great flexibility of use in managing accumulation times as a function of production characteristics. In terms of layout as well, it should demonstrate flexibility for operator movement and access to machine areas for maintenance. Packaging technology during the past few decades has risen to these challenges by a series of major breakthroughs interspersed with periods of refinement and improvement. The milestones are many and varied and are described briefly in this paper. In order to have a brief understanding of the human factor and ergonomics in the modern packaging lines, this paper, highlights the various technologies, design considerations and statutory requirements in packaging equipment for different types of containers used in India.Keywords: human-factor, ergonomics, bottling lines, automized high-speed lines
Procedia PDF Downloads 438228 Benefits of Social Justice Pedagogy and Ecofeminist Discourse for Engineering Education
Authors: Hollie M. Lewis
Abstract:
A large body of corroborating research provides evidence that traditional undergraduate engineering education fails to provide students with a role and identity that requires social concern and moral reasoning. Engineering students demonstrate a low level of engagement with social and political contexts, which further declines over the course of engineering education. This detachment is thought to stem from beliefs that the role of the engineer is purely to design machines, systems, and structures. In effect, engineers objectify the world. The purpose of this paper is to provide an ecofeminist critique of engineering education and pose the benefits of social justice pedagogies incorporating ecofeminist discourse. The challenges currently facing the world stem from anthropocentric industrialization, an agenda that is historically absent of Environmental, Feminist, People of Color, and Indigenous voices. A future in which the global collective achieves its Sustainable Development Goals requires its engineers to have a solid understanding of the broader social and political contexts in which they manage projects. Engineering education must convey the influence of the professional role of engineer and encourage the practice of critical reflection and social perspective-taking, priming students with the skills to engage with varying perspectives and discourses. There will be discussed the facets of social justice pedagogies that aid students in surpassing threshold concepts in social justice.Keywords: feminism in engineering, sustainable development, engineering education, social justice pedagogies
Procedia PDF Downloads 64227 Modeling Aeration of Sharp Crested Weirs by Using Support Vector Machines
Authors: Arun Goel
Abstract:
The present paper attempts to investigate the prediction of air entrainment rate and aeration efficiency of a free over-fall jets issuing from a triangular sharp crested weir by using regression based modelling. The empirical equations, support vector machine (polynomial and radial basis function) models and the linear regression techniques were applied on the triangular sharp crested weirs relating the air entrainment rate and the aeration efficiency to the input parameters namely drop height, discharge, and vertex angle. It was observed that there exists a good agreement between the measured values and the values obtained using empirical equations, support vector machine (Polynomial and rbf) models, and the linear regression techniques. The test results demonstrated that the SVM based (Poly & rbf) model also provided acceptable prediction of the measured values with reasonable accuracy along with empirical equations and linear regression techniques in modelling the air entrainment rate and the aeration efficiency of a free over-fall jets issuing from triangular sharp crested weir. Further sensitivity analysis has also been performed to study the impact of input parameter on the output in terms of air entrainment rate and aeration efficiency.Keywords: air entrainment rate, dissolved oxygen, weir, SVM, regression
Procedia PDF Downloads 436