Search results for: DFIG machine

Authors: Afroze Ibrahim Baqapuri, Ilya Trofimov

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Sponsored search is a multi-billion dollar industry and makes up a major source of revenue for search engines (SE). Click-through-rate (CTR) estimation plays a crucial role for ads selection, and greatly affects the SE revenue, advertiser traffic and user experience. We propose a novel architecture of solving CTR prediction problem by combining artificial neural networks (ANN) with decision trees. First, we compare ANN with respect to other popular machine learning models being used for this task. Then we go on to combine ANN with MatrixNet (proprietary implementation of boosted trees) and evaluate the performance of the system as a whole. The results show that our approach provides a significant improvement over existing models.

Keywords: neural networks, sponsored search, web advertisement, click prediction, click-through rate

Procedia PDF Downloads 572

Authors: Omar Imhemed Alramli

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As Transmission Control Protocol (TCP), User Datagram Protocol (UDP) is transfer protocol in the transportation layer in Open Systems Interconnection model (OSI model) or in TCP/IP model of networks. The UDP aspects evaluation were not recognized by using the pcattcp tool on the windows operating system platform like TCP. The study has been carried out to find a tool which supports UDP aspects evolution. After the information collection about different tools, iperf tool was chosen and implemented on Cygwin tool which is installed on both Windows XP platform and also on Windows XP on virtual box machine on one computer only. Iperf is used to make experimental evaluation of UDP and to see what will happen during the sending the packets between the Host and Guest in wired and wireless networks. Many test scenarios have been done and the major UDP aspects such as jitter, packet losses, and throughput are evaluated.

Keywords: TCP, UDP, IPERF, wireless LAN

Procedia PDF Downloads 354

Authors: Stephanie Lehmann, Esther Ruf, Sabina Misoch

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Background: Due to demographic change and shortage of skilled nursing staff, assistive robots are built to support older adults at home and nursing staff in care institutions. When assistive robots facilitate tasks that are usually performed by humans, user acceptance is essential. Even though they are an important aspect of acceptance, emotions towards different assistive robots and different situations of robot-use have so far not been examined in detail. The appearance of assistive robots can trigger emotions that affect their acceptance. Acceptance of robots is assumed to be greater when they look more human-like; however, too much human similarity can be counterproductive. Regarding different groups, it is assumed that older adults have a more negative attitude towards robots than younger adults. Within the framework of a simulated robot study, the aim was to investigate emotions of older adults compared to students towards robots with different appearances and in different situations and so contribute to a deeper view of the emotions influencing acceptance. Methods: In a questionnaire study, vignettes were used to assess emotions toward robots in different situations and of different appearance. The vignettes were composed of two situations (service and care) shown by video and four pictures of robots varying in human similarity (machine-like to android). The combination of the vignettes was randomly distributed to the participants. One hundred forty-two older adults and 35 bachelor students of nursing participated. They filled out a questionnaire that surveyed 30 positive and 30 negative emotions. For each group, older adults and students, a sum score of “positive emotions” and a sum score of “negative emotions” was calculated. Mean value, standard deviation, or n for sample size and % for frequencies, according to the scale level, were calculated. For differences in the scores of positive and negative emotions for different situations, t-tests were calculated. Results: Overall, older adults reported significantly more positive emotions than students towards robots in general. Students reported significantly more negative emotions than older adults. Regarding the two different situations, the results were similar for the care situation, with older adults reporting more positive emotions than students and less negative emotions than students. In the service situation, older adults reported significantly more positive emotions; negative emotions did not differ significantly from the students. Regarding the appearance of the robot, there were no significant differences in emotions reported towards the machine-like, the mechanical-human-like and the human-like appearance. Regarding the android robot, students reported significantly more negative emotions than older adults. Conclusion: There were differences in the emotions reported by older adults compared to students. Older adults reported more positive emotions, and students reported more negative emotions towards robots in different situations and with different appearances. It can be assumed that older adults have a different attitude towards the use of robots than younger people, especially young adults in the health sector. Therefore, the use of robots in the service or care sector should not be rejected rashly based on the attitudes of younger persons, without considering the attitudes of older adults equally.

Keywords: emotions, robots, seniors, young adults

Procedia PDF Downloads 466

Authors: Benchalak Muangmeesri

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The purpose of this paper is to discuss how to test the best control performance of a ceramics. Hydraulic press machine (HPM) is the most common shaping of advanced ceramic with products, dimensions, and ceramic products mainly from synthetic powders. A microcontroller can be achieved to control process and has set high standards in the shaping of raw materials in powder form. HPM was proposed to develop a position control system that linked to the embedded controller PIC16F877 via Proportional and Derivative (PD) controller. The model is performed using MATLAB/SIMULINK and the best control performance of an HPM. Finally, PD controller results, showing the best performance as it had the smallest overshoot and highest quality using a microcontroller control.

Keywords: ceramics, hydraulic press, microcontroller, PD controller

Procedia PDF Downloads 356

Authors: Senthuran Manoharan, Rathesan Sivagananalingam

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One of the main issues in system security is Authentication. Authentication can be defined as the process of recognizing the user's identity and it is the most important step in the access control process to safeguard data/resources from being accessed by unauthorized users. The static method of authentication cannot ensure the genuineness of the user. Due to this reason, more innovative authentication mechanisms came into play. At first two factor authentication was introduced and later, multi-factor authentication was introduced to enhance the security of the system. It also had some issues and later, adaptive authentication was introduced. In this research paper, the design of an adaptive authentication engine was put forward. The user risk profile was calculated based on the user parameters and then the user was challenged with a suitable authentication method.

Keywords: authentication, adaptive authentication, machine learning, security

Procedia PDF Downloads 249

Authors: Ruzanna Muradyan

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Medical data mining is a crucial field in contemporary healthcare that offers cutting-edge tactics with enormous potential to transform patient care. This abstract examines how sophisticated data mining techniques could transform the healthcare industry, with a special focus on how they might improve patient outcomes. Healthcare data repositories have dynamically evolved, producing a rich tapestry of different, multi-dimensional information that includes genetic profiles, lifestyle markers, electronic health records, and more. By utilizing data mining techniques inside this vast library, a variety of prospects for precision medicine, predictive analytics, and insight production become visible. Predictive modeling for illness prediction, risk stratification, and therapy efficacy evaluations are important points of focus. Healthcare providers may use this abundance of data to tailor treatment plans, identify high-risk patient populations, and forecast disease trajectories by applying machine learning algorithms and predictive analytics. Better patient outcomes, more efficient use of resources, and early treatments are made possible by this proactive strategy. Furthermore, data mining techniques act as catalysts to reveal complex relationships between apparently unrelated data pieces, providing enhanced insights into the cause of disease, genetic susceptibilities, and environmental factors. Healthcare practitioners can get practical insights that guide disease prevention, customized patient counseling, and focused therapies by analyzing these associations. The abstract explores the problems and ethical issues that come with using data mining techniques in the healthcare industry. In order to properly use these approaches, it is essential to find a balance between data privacy, security issues, and the interpretability of complex models. Finally, this abstract demonstrates the revolutionary power of modern data mining methodologies in transforming the healthcare sector. Healthcare practitioners and researchers can uncover unique insights, enhance clinical decision-making, and ultimately elevate patient care to unprecedented levels of precision and efficacy by employing cutting-edge methodologies.

Keywords: data mining, healthcare, patient care, predictive analytics, precision medicine, electronic health records, machine learning, predictive modeling, disease prognosis, risk stratification, treatment efficacy, genetic profiles, precision health

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Authors: I Lamri, L Arabet, M. Hidjeb

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The direct shear test was used to determine the shear strength parameters C and Ø of a series of samples with different cement content. Samples stabilized with a certain percentage of cement showed a substantial gain in compressive strength and a significant increase in shear strength parameters. C and Ø. The laboratory equipment used in UCS tests consisted of a conventional 102mm diameter sample triaxial loading machine. Beyond 4% cement content a very important increase in shear strength was observed. It can be deduced from a comparative study of shear strength of soil samples with 4%, 7%, and 10% cement with sample containing 2 %, that the sample with a 4% cement content showed 90% increase in shear strength while those with 7% and 10% showed an increase of around 13 and 21 fold.

Keywords: cement, compression strength, shear stress, cohesion, angle of internal friction

Procedia PDF Downloads 488

Authors: Emre Kara, Metehan Demir, Şura Karakuzu, Kadir Koç, Ahmet F. Geylan, Halil Aykul

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While the polymeric foam cored sandwiches have been realized for many years, recently there is a growing and outstanding interest on the use of sandwiches consisting of aluminum foam core because of their some of the distinct mechanical properties such as high bending stiffness, high load carrying and energy absorption capacities. These properties make them very useful in the transportation industry (automotive, aerospace, shipbuilding industry), where the "lightweight design" philosophy and the safety of vehicles are very important aspects. Therefore, in this study, the sandwich panels with aluminum alloy foam core and various types and thicknesses of glass fiber reinforced polymer (GFRP) skins produced via Vacuum Assisted Resin Transfer Molding (VARTM) technique were obtained by using a commercial toughened epoxy based adhesive with two components. The aim of this contribution was the analysis of the bending response of sandwiches with various glass fiber reinforced polymer skins. The three point bending tests were performed on sandwich panels at different values of support span distance using a universal static testing machine in order to clarify the effects of the type and thickness of the GFRP skins in terms of peak load, energy efficiency and absorbed energy values. The GFRP skins were easily bonded to the aluminum alloy foam core under press machine with a very low pressure. The main results of the bending tests are: force-displacement curves, peak force values, absorbed energy, collapse mechanisms and the influence of the support span length and GFRP skins. The obtained results of the experimental investigation presented that the sandwich with the skin made of thicker S-Glass fabric failed at the highest load and absorbed the highest amount of energy compared to the other sandwich specimens. The increment of the support span distance made the decrease of the peak force and absorbed energy values for each type of panels. The common collapse mechanism of the panels was obtained as core shear failure which was not affected by the skin materials and the support span distance.

Keywords: aluminum foam, collapse mechanisms, light-weight structures, transport application

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Authors: S. Tehsin, S. Kausar

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The ultimate aim of machine intelligence is to explore and materialize the human capabilities, one of which is the ability to detect various text objects within one or more images displayed on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However, it needs to technologically testify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed. Subsequent examination bears testimony to the fact that the features extracted proved instrumental to text detection.

Keywords: biologically inspired vision, content based retrieval, document analysis, text extraction

Procedia PDF Downloads 444

Authors: Kemal Polat

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In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

Procedia PDF Downloads 248

Authors: Bashir Aliyu Yauri, Rufai Aliyu Yauri

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With the introduction of cash-less society policy by the Central Bank of Nigeria, the concept of e-banking services has experienced a significant improvement over the years. Today quite a number of people are embracing e-banking activities especially ATM, thereby moving away from the conventional banking system. This paper presents a review of the underlying Architectural Layout of Intra-Bank and Inter-Bank ATM connectivity in Nigeria. The paper further investigates and discusses factors affecting the Intra-Bank and Inter-Bank ATM connectivity in Nigeria. And as well possible solutions to these factors affecting ATM Connectivity and Operations are proposed.

Keywords: architectural layout, automated teller machine, e-services, postilion

Procedia PDF Downloads 634

Authors: M. N. Osman Zahid, K. Case, D. Watts

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This paper reports an advanced approach in the application of CNC machining for rapid manufacturing processes (CNC-RM). The aim of this study is to improve the quality of machined parts by introducing different cutting tools during finishing operations. As the cutting is performed in different directions, the surfaces presented on part can be classified into several categories. Therefore, suitable cutting tools are assigned to machine particular surfaces and to improve the quality. Experimental studies have been carried out by fabricating several parts based on the suggested approach. The results provide further support for implementing this approach in rapid machining processes.

Keywords: CNC machining, end mill tool, finishing operation, rapid manufacturing

Procedia PDF Downloads 346

Authors: Jawharah Alasmari

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In verb inflection, tense marks past/present/future action, and aspect marks progressive/continues perfect/completed actions. This usage and meaning of tense and aspect differ in Arabic and English. In this research, we applied data mining methods to test the predictive function of candidate features by using our dataset of Arabic verbs in-context, and their 7 translations. Weka machine learning classifiers is used in this experiment in order to examine the key features that can be used to provide guidance to enable a translator’s appropriate English translation of the Arabic verb tense and aspect.

Keywords: Arabic verb, English translations, mining methods, Weka software

Procedia PDF Downloads 272

Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

Procedia PDF Downloads 63

Authors: Hikmet Cicek

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Metal nitrides show excellence tribological properties and they used for especially on machine parts. In this work, the vacuum gas nitriding proses were applied to the titanium, D2 and 52100 steel substrates at three different proses temperatures (500 °C, 600°C and 700 °C). Structural, mechanical and tribological properties of the samples were characterized. X-Ray diffractometer, scanning electron microscope and energy dispersive spectroscopy analyses were conducted to determine structural properties. Microhardness test and pin-on-disc wear test were made to observe tribological properties. Coefficient of friction, wear rate and wear traces were examined comparatively. According to the test results, the process temperature very effective parameter for the vacuum gas nitriding method.

Keywords: gas nitriding, tribology, wear, coating

Procedia PDF Downloads 199

Authors: Jung-Min Yang

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Fault diagnosis of composite asynchronous sequential machines with parallel composition is addressed in this paper. An adversarial input can infiltrate one of two submachines comprising the composite asynchronous machine, causing an unauthorized state transition. The objective is to characterize the condition under which the controller can diagnose any fault occurrence. Two control configurations, state feedback and output feedback, are considered in this paper. In the case of output feedback, the exact estimation of the state is impossible since the current state is inaccessible and the output feedback is given as the form of burst. A simple example is provided to demonstrate the proposed methodology.

Keywords: asynchronous sequential machines, parallel composition, fault diagnosis, corrective control

Procedia PDF Downloads 298

Authors: Arun Prasad Jaganathan

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In today's rapidly evolving technological landscape, the need for efficient and proactive maintenance management solutions has become increasingly evident across various industries. Traditional approaches often suffer from drawbacks such as reactive strategies, leading to potential downtime, increased costs, and decreased operational efficiency. In response to these challenges, this paper proposes an AI-enabled approach to object-based maintenance management aimed at enhancing reliability and efficiency. The paper contributes to the growing body of research on AI-driven maintenance management systems, highlighting the transformative impact of intelligent technologies on enhancing object reliability and operational efficiency.

Keywords: AI, machine learning, predictive maintenance, object-based maintenance, expert team scheduling

Procedia PDF Downloads 58

Authors: Mahshid Arabi

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With the rapid expansion of digital technologies and the internet, information security has become a critical priority for organizations and individuals. The widespread use of digital tools such as smartphones and internet networks facilitates the storage of vast amounts of data, but simultaneously, vulnerabilities and security threats have significantly increased. The aim of this study is to examine and analyze modern methods of information security management and to develop a comprehensive model to counteract threats and information misuse. This study employs a mixed-methods approach, including both qualitative and quantitative analyses. Initially, a systematic review of previous articles and research in the field of information security was conducted. Then, using the Delphi method, interviews with 30 information security experts were conducted to gather their insights on security challenges and solutions. Based on the results of these interviews, a comprehensive model for information security management was developed. The proposed model includes advanced encryption techniques, machine learning-based intrusion detection systems, and network security protocols. AES and RSA encryption algorithms were used for data protection, and machine learning models such as Random Forest and Neural Networks were utilized for intrusion detection. Statistical analyses were performed using SPSS software. To evaluate the effectiveness of the proposed model, T-Test and ANOVA statistical tests were employed, and results were measured using accuracy, sensitivity, and specificity indicators of the models. Additionally, multiple regression analysis was conducted to examine the impact of various variables on information security. The findings of this study indicate that the comprehensive proposed model reduced cyber-attacks by an average of 85%. Statistical analysis showed that the combined use of encryption techniques and intrusion detection systems significantly improves information security. Based on the obtained results, it is recommended that organizations continuously update their information security systems and use a combination of multiple security methods to protect their data. Additionally, educating employees and raising public awareness about information security can serve as an effective tool in reducing security risks. This research demonstrates that effective and up-to-date information security management requires a comprehensive and coordinated approach, including the development and implementation of advanced techniques and continuous training of human resources.

Keywords: data protection, digital technologies, information security, modern management

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Authors: Abdul Basit Kiani

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Web development, the art of creating and maintaining websites, has witnessed remarkable advancements. The aim is to provide an overview of some of the cutting-edge developments in the field. Firstly, the rise of responsive web design has revolutionized user experiences across devices. With the increasing prevalence of smartphones and tablets, web developers have adapted to ensure seamless browsing experiences, regardless of screen size. This progress has greatly enhanced accessibility and usability, catering to the diverse needs of users worldwide. Additionally, the evolution of web frameworks and libraries has significantly streamlined the development process. Tools such as React, Angular, and Vue.js have empowered developers to build dynamic and interactive web applications with ease. These frameworks not only enhance efficiency but also bolster scalability, allowing for the creation of complex and feature-rich web solutions. Furthermore, the emergence of progressive web applications (PWAs) has bridged the gap between native mobile apps and web development. PWAs leverage modern web technologies to deliver app-like experiences, including offline functionality, push notifications, and seamless installation. This innovation has transformed the way users interact with websites, blurring the boundaries between traditional web and mobile applications. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) has opened new horizons in web development. Chatbots, intelligent recommendation systems, and personalization algorithms have become integral components of modern websites. These AI-powered features enhance user engagement, provide personalized experiences, and streamline customer support processes, revolutionizing the way businesses interact with their audiences. Lastly, the emphasis on web security and privacy has been a pivotal area of progress. With the increasing incidents of cyber threats, web developers have implemented robust security measures to safeguard user data and ensure secure transactions. Innovations such as HTTPS protocol, two-factor authentication, and advanced encryption techniques have bolstered the overall security of web applications, fostering trust and confidence among users. Hence, recent progress in web development has propelled the industry forward, enabling developers to craft innovative and immersive digital experiences. From responsive design to AI integration and enhanced security, the landscape of web development continues to evolve, promising a future filled with endless possibilities.

Keywords: progressive web applications (PWAs), web security, machine learning (ML), web frameworks, advancement responsive web design

Procedia PDF Downloads 54

Authors: Weiwei Shan, Wenjing Ding, Juan Ning, Chao He, Zijuan Wang

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Gravity circulation loop for the cryopumps of the space simulator is introduced, and two phase mathematic model of flow heat transfer is analyzed as well. Based on this model, the liquid nitrogen (LN₂) gravity circulation loop including its equipment and layout is designed and has served as LN₂ feeding system for cryopumps in one large space simulator. With the help of control software and human machine interface, this system can be operated flexibly, simply, and automatically under four conditions. When running this system, the results show that the cryopumps can be cooled down and maintained under the required temperature, 120 K.

Keywords: cryopumps, gravity circulation loop, liquid nitrogen, two-phase

Procedia PDF Downloads 401

Authors: Damanjit Kaur, Avani Bhatia

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Color constancy is significant for human vision since color is a pictorial cue that helps in solving different visions tasks such as tracking, object recognition, or categorization. Therefore, several computational methods have tried to simulate human color constancy abilities to stabilize machine color representations. Two different kinds of methods have been used, i.e., normalization and constancy. While color normalization creates a new representation of the image by canceling illuminant effects, color constancy directly estimates the color of the illuminant in order to map the image colors to a canonical version. Color constancy is the capability to determine colors of objects independent of the color of the light source. This research work studies the most of the well-known color constancy algorithms like white point and gray world.

Keywords: color constancy, gray world, white patch, modified white patch

Procedia PDF Downloads 319

Authors: P. Raajeswari, S. M. Devatha, S. Yuvajanani, U. Rashika

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Edible food packaging are the need of the hour to save life on land and under water by eliminating waste cycle and replacing Single Use Plastics at grass root level as it can be eaten or composted as such. Cassava (Manihot esculenta) selected for making edible films are rich source of starch, and also it exhibit good sheeting propertiesdue to the high amylose: amylopectin content. Cassava starch was extracted by manual method at a laboratory scale and yielded 65 per cent. Edible films were developed by adding food grade plasticizers and water. Glycerol showed good plasticizing property as compared to sorbitol and polylactic acid in both manual (petri dish) and machine (film making machine) production. The thickness of the film is 0.25±0.03 mm. Essential oil and components from peels like pomegranate, orange, pumpkin, onion, and banana brat, and herbs like tulsi and country borage was extracted through the standardized aqueous and alkaline method. In the standardized film, the essential oil and components from selected peel and herbs were added to the casting solution separately and casted the film. It was added to improve the anti-oxidant, anti-microbial and optical properties. By inclusion of extracts, it reduced the bubble formation while casting. FTIR, Water Vapor and Oxygen Transmission Rate (WVTR and OTR), tensile strength, microbial load, shelf life, and degradability of the films were done to analyse the mechanical property of the standardized films. FTIR showed the presence of essential oil. WVTR and OTR of the film was improved after inclusion of essential oil and extracts from 1.312 to 0.811 cm₃/m₂ and 15.12 to 17.81 g/ m₂.d. Inclusion of essential oil from herbs showed better WVTR and OTR than the inclusion of peel extract and standard. Tensile strength and Elongation at break has not changed by essential oil and extracts at 0.86 ± 0.12 mpa and 14 ± 2 at 85 N force. By inclusion of extracts, an optical property of the film enhanced, and it increases the appearance of the packaging material. The films were completely degraded on 84thdays and partially soluble in water. Inclusion of essential oil does not have impact on degradability and solubility. The microbial loads of the active films were decreased from 15 cfu/gm to 7 cfu/gm. The films can be stored at frozen state for 24 days and 48 days at atmospheric temperature when packed with South Indian snacks and savories.

Keywords: active films, cassava starch, plasticizer, characterization

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Authors: M. Soltan Rezaee, M. R. Ghazavi, A. Najafi, W.-H. Liao

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Generally, different rods in shaft systems can be misaligned based on the mechanical system usages. These rods can be linked together via U-coupling easily. The system is self-stimulated and may cause instabilities due to the inherent behavior of the coupling. In this study, each rod includes an elastic shaft with an angular stiffness and structural damping. Moreover, the mass of shafts is considered via attached solid disks. The impact of the system architecture and shaft mass on the instability of such mechanism are studied. Stability charts are plotted via a method based on Floquet theory. Eventually, the unstable points have been found and analyzed in detail. The results show that stabilizing the driveline is feasible by changing the system characteristics which include shaft mass and architecture.

Keywords: coupling, mechanical systems, oscillations, rotating shafts

Procedia PDF Downloads 181

Authors: Bharath R., Tharun Sai N., Bhuvan G.

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This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.

Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks

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Authors: C. Mayr, J. Periya, A. Kariminezhad

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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

Procedia PDF Downloads 246

Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad, Nurfadhlina Mohammad Sharef

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Sarcasm is a common phenomenon in social media which is a nuanced form of language for stating the opposite of what is implied. Due to the intentional ambiguity, analysis of sarcasm is a difficult task not only for a machine but even for a human. Although sarcasm detection has an important effect on sentiment, it is usually ignored in social media analysis because sarcasm analysis is too complicated. While there is a few systems exist which can detect sarcasm, almost no work has been carried out on a study and the review of the existing work in this area. This survey presents a nearly full image of sarcasm detection techniques and the related fields with brief details. The main contributions of this paper include the illustration of the recent trend of research in the sarcasm analysis and we highlight the gaps and propose a new framework that can be explored.

Keywords: sarcasm detection, sentiment analysis, social media, sarcasm analysis

Procedia PDF Downloads 458

Authors: Jung-Min Yang

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A method of tolerating input faults for input/state asynchronous sequential machines is proposed. A corrective controller is placed in front of the considered asynchronous machine to realize model matching with a reference model. The value of the external input transmitted to the closed-loop system may change by fault. We address the existence condition for the controller that can counteract adverse effects of any input fault while maintaining the objective of model matching. A design procedure for constructing the controller is outlined. The proposed reachability condition for the controller design is validated in an illustrative example.

Keywords: asynchronous sequential machines, corrective control, fault tolerance, input faults, model matching

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Authors: Rana Atta Ur Rahman, Daniel Juhre

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Initiation of crack during fatigue of casting alloys are noticed mainly on the basis of experimental results. Crack initiation and strength of fatigue of AA320 are summarized here. Load sequence effect is applied to notify initiation phase life. Crack initiation at notch root and fatigue life is calculated under single & two-step mechanical loading (ML) with and without combined thermal cycling (CTC). An Experimental setup is proposed to create the working temperature as per alloy applications. S-N curves are plotted, and a comparison is made between crack initiation leading to failure under different ML with & without thermal loading (TL).

Keywords: fatigue, initiation, SN curve, alloy

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Authors: Andri Setiyoso, Agus Purwadi, Nanda Avianto Wicaksono

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This paper present about induction generator design for 100kW power output capacity. Induction machine had been chosen because of the capability for energy conversion from electric energy to mechanical energy and vise-versa with operation on variable speed condition. Stator Controlled Induction Generator (SCIG) was applied as wind power plant in Desa Taman Jaya, Sukabumi, Indonesia. Generator was designed to generate power 100 kW with wind speed at 12 m/s and survival condition at speed 21 m/s.

Keywords: wind energy, induction generator, Stator Controlled Induction Generator (SCIG), variable speed generator

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Authors: Mehmet Savsar

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This paper presents a practical case application of simulation modeling and analysis in a specific industrial setting. Various maintenance related parameters of the equipment in the system under consideration are determined and a simulation model is developed to study system behavior. System performance is determined based on established parameters and operational policies, which included system operation with and without preventive maintenance implementation. The results show that preventive maintenance practice has significant effects on improving system productivity. The simulation procedures outlined in this paper can be used by operation managers to perform production line analysis under different maintenance policies in various industrial settings.

Keywords: simulation, production line, machine failures, maintenance, industrial bakery

Procedia PDF Downloads 487