Search results for: voting machines in the USA
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 766

Search results for: voting machines in the USA

406 Modeling and Simulation of Flow Shop Scheduling Problem through Petri Net Tools

Authors: Joselito Medina Marin, Norberto Hernández Romero, Juan Carlos Seck Tuoh Mora, Erick S. Martinez Gomez

Abstract:

The Flow Shop Scheduling Problem (FSSP) is a typical problem that is faced by production planning managers in Flexible Manufacturing Systems (FMS). This problem consists in finding the optimal scheduling to carry out a set of jobs, which are processed in a set of machines or shared resources. Moreover, all the jobs are processed in the same machine sequence. As in all the scheduling problems, the makespan can be obtained by drawing the Gantt chart according to the operations order, among other alternatives. On this way, an FMS presenting the FSSP can be modeled by Petri nets (PNs), which are a powerful tool that has been used to model and analyze discrete event systems. Then, the makespan can be obtained by simulating the PN through the token game animation and incidence matrix. In this work, we present an adaptive PN to obtain the makespan of FSSP by applying PN analytical tools.

Keywords: flow-shop scheduling problem, makespan, Petri nets, state equation

Procedia PDF Downloads 299
405 Model of Application of Blockchain Technology in Public Finances

Authors: M. Vlahovic

Abstract:

This paper presents a model of public finances, which combines three concepts: participatory budgeting, crowdfunding and blockchain technology. Participatory budgeting is defined as a process in which community members decide how to spend a part of community’s budget. Crowdfunding is a practice of funding a project by collecting small monetary contributions from a large number of people via an Internet platform. Blockchain technology is a distributed ledger that enables efficient and reliable transactions that are secure and transparent. In this hypothetical model, the government or authorities on local/regional level would set up a platform where they would propose public projects to citizens. Citizens would browse through projects and support or vote for those which they consider justified and necessary. In return, they would be entitled to a tax relief in the amount of their monetary contribution. Since the blockchain technology enables tracking of transactions, it can be used to mitigate corruption, money laundering and lack of transparency in public finances. Models of its application have already been created for e-voting, health records or land registries. By presenting a model of application of blockchain technology in public finances, this paper takes into consideration the potential of blockchain technology to disrupt governments and make processes more democratic, secure, transparent and efficient. The framework for this paper consists of multiple streams of research, including key concepts of direct democracy, public finance (especially the voluntary theory of public finance), information and communication technology, especially blockchain technology and crowdfunding. The framework defines rules of the game, basic conditions for the implementation of the model, benefits, potential problems and development perspectives. As an oversimplified map of a new form of public finances, the proposed model identifies primary factors, that influence the possibility of implementation of the model, and that could be tracked, measured and controlled in case of experimentation with the model.

Keywords: blockchain technology, distributed ledger, participatory budgeting, crowdfunding, direct democracy, internet platform, e-government, public finance

Procedia PDF Downloads 151
404 A Hybrid Distributed Algorithm for Multi-Objective Dynamic Flexible Job Shop Scheduling Problem

Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid distributed algorithm has been suggested for multi-objective dynamic flexible job shop scheduling problem. The proposed algorithm is high level, in which several algorithms search the space on different machines simultaneously also it is a hybrid algorithm that takes advantages of the artificial intelligence, evolutionary and optimization methods. Distribution is done at different levels and new approaches are used for design of the algorithm. Apache spark and Hadoop frameworks have been used for the distribution of the algorithm. The Pareto optimality approach is used for solving the multi-objective benchmarks. The suggested algorithm that is able to solve large-size problems in short times has been compared with the successful algorithms of the literature. The results prove high speed and efficiency of the algorithm.

Keywords: distributed algorithms, apache-spark, Hadoop, flexible dynamic job shop scheduling, multi-objective optimization

Procedia PDF Downloads 354
403 Heuristic for Scheduling Correlated Parallel Machine to Minimize Maximum Lateness and Total Weighed Completion Time

Authors: Yang-Kuei Lin, Yun-Xi Zhang

Abstract:

This research focuses on the bicriteria correlated parallel machine scheduling problem. The two objective functions considered in this problem are to minimize maximum lateness and total weighted completion time. We first present a mixed integer programming (MIP) model that can find the entire efficient frontier for the studied problem. Next, we have proposed a bicriteria heuristic that can find non-dominated solutions for the studied problem. The performance of the proposed bicriteria heuristic is compared with the efficient frontier generated by solving the MIP model. Computational results indicate that the proposed bicriteria heuristic can solve the problem efficiently and find a set of diverse solutions that are uniformly distributed along the efficient frontier.

Keywords: bicriteria, correlated parallel machines, heuristic, scheduling

Procedia PDF Downloads 141
402 Traffic Sign Recognition System Using Convolutional Neural NetworkDevineni

Authors: Devineni Vijay Bhaskar, Yendluri Raja

Abstract:

We recommend a model for traffic sign detection stranded on Convolutional Neural Networks (CNN). We first renovate the unique image into the gray scale image through with support vector machines, then use convolutional neural networks with fixed and learnable layers for revealing and understanding. The permanent layer can reduction the amount of attention areas to notice and crop the limits very close to the boundaries of traffic signs. The learnable coverings can rise the accuracy of detection significantly. Besides, we use bootstrap procedures to progress the accuracy and avoid overfitting problem. In the German Traffic Sign Detection Benchmark, we obtained modest results, with an area under the precision-recall curve (AUC) of 99.49% in the group “Risk”, and an AUC of 96.62% in the group “Obligatory”.

Keywords: convolutional neural network, support vector machine, detection, traffic signs, bootstrap procedures, precision-recall curve

Procedia PDF Downloads 123
401 Speech Emotion Recognition with Bi-GRU and Self-Attention based Feature Representation

Authors: Bubai Maji, Monorama Swain

Abstract:

Speech is considered an essential and most natural medium for the interaction between machines and humans. However, extracting effective features for speech emotion recognition (SER) is remains challenging. The present studies show that the temporal information captured but high-level temporal-feature learning is yet to be investigated. In this paper, we present an efficient novel method using the Self-attention (SA) mechanism in a combination of Convolutional Neural Network (CNN) and Bi-directional Gated Recurrent Unit (Bi-GRU) network to learn high-level temporal-feature. In order to further enhance the representation of the high-level temporal-feature, we integrate a Bi-GRU output with learnable weights features by SA, and improve the performance. We evaluate our proposed method on our created SITB-OSED and IEMOCAP databases. We report that the experimental results of our proposed method achieve state-of-the-art performance on both databases.

Keywords: Bi-GRU, 1D-CNNs, self-attention, speech emotion recognition

Procedia PDF Downloads 114
400 Evaluation of Environmental, Technical, and Economic Indicators of a Fused Deposition Modeling Process

Authors: M. Yosofi, S. Ezeddini, A. Ollivier, V. Lavaste, C. Mayousse

Abstract:

Additive manufacturing processes have changed significantly in a wide range of industries and their application progressed from rapid prototyping to production of end-use products. However, their environmental impact is still a rather open question. In order to support the growth of this technology in the industrial sector, environmental aspects should be considered and predictive models may help monitor and reduce the environmental footprint of the processes. This work presents predictive models based on a previously developed methodology for the environmental impact evaluation combined with a technical and economical assessment. Here we applied the methodology to the Fused Deposition Modeling process. First, we present the predictive models relative to different types of machines. Then, we present a decision-making tool designed to identify the optimum manufacturing strategy regarding technical, economic, and environmental criteria.

Keywords: additive manufacturing, decision-makings, environmental impact, predictive models

Procedia PDF Downloads 132
399 A Secure System for Handling Information from Heterogeous Sources

Authors: Shoohira Aftab, Hammad Afzal

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Information integration is a well known procedure to provide consolidated view on sets of heterogeneous information sources. It not only provides better statistical analysis of information but also facilitates users to query without any knowledge on the underlying heterogeneous information sources The problem of providing a consolidated view of information can be handled using Semantic data (information stored in such a way that is understandable by machines and integrate-able without manual human intervention). However, integrating information using semantic web technology without any access management enforced, will results in increase of privacy and confidentiality concerns. In this research we have designed and developed a framework that would allow information from heterogeneous formats to be consolidated, thus resolving the issue of interoperability. We have also devised an access control system for defining explicit privacy constraints. We designed and applied our framework on both semantic and non-semantic data from heterogeneous resources. Our approach is validated using scenario based testing.

Keywords: information integration, semantic data, interoperability, security, access control system

Procedia PDF Downloads 359
398 Design and Performance of a Large Diameter Shaft in Old Alluvium

Authors: Tamilmani Thiruvengadam, Ramasthanan Arulampalam

Abstract:

This project comprises laying approximately 1.8km of 400mm, 1200mm and 2400mm diameter sewer pipes using pipe jacking machines along Mugliston Park, Buangkok Drive, and Buangkok Link. The works include an estimated 14 circular shafts with depth ranging from 10.0 meters to 29.0 meters. Cast in-situ circular shaft will be used for the temporary shaft excavation. The geology is predominantly Backfill and old alluvium with weak material encountered in between. Where there is a very soft clay, F1 material or weak soil is expected, ground improvement will be carried out outside of the shaft followed by cast in-situ concrete ring wall within the improved soil zone. This paper presents the design methodology, analysis and results of temporary shafts for micro TBM launching and constructing permanent manholes. There is also a comparison of instrumentation readings with the analysis predicted values.

Keywords: circular shaft, ground improvement, old alluvium, temporary shaft

Procedia PDF Downloads 289
397 Impact of Network Workload between Virtualization Solutions on a Testbed Environment for Cybersecurity Learning

Authors: Kevin Fernagut, Olivier Flauzac, Erick M. G. Robledo, Florent Nolot

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The adoption of modern lightweight virtualization often comes with new threats and network vulnerabilities. This paper seeks to assess this with a different approach studying the behavior of a testbed built with tools such as Kernel-Based Virtual Machine (KVM), Linux Containers (LXC) and Docker, by performing stress tests within a platform where students experiment simultaneously with cyber-attacks, and thus observe the impact on the campus network and also find the best solution for cyber-security learning. Interesting outcomes can be found in the literature comparing these technologies. It is, however, difficult to find results of the effects on the global network where experiments are carried out. Our work shows that other physical hosts and the faculty network were impacted while performing these trials. The problems found are discussed, as well as security solutions and the adoption of new network policies.

Keywords: containerization, containers, cybersecurity, cyberattacks, isolation, performance, virtualization, virtual machines

Procedia PDF Downloads 151
396 Fire Safety Engineering of Wood Dust Layer or Cloud

Authors: Marzena Półka, Bożena Kukfisz

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This paper presents an analysis of dust explosion hazards in the process industries. It includes selected testing method of dust explosibility and presentation two of them according to experimental standards used by Department of Combustion and Fire Theory in The Main School of Fire Service in Warsaw. In the article are presented values of maximum acceptable surface temperature (MAST) of machines operating in the presence of dust cloud and chosen dust layer with thickness of 5 and 12,5mm. The comparative analysis, points to the conclusion that the value of the minimum ignition temperature of the layer (MITL) and the minimum ignition temperature of dust cloud (MTCD) depends on the granularity of the substance. Increasing the thickness of the dust layer reduces minimum ignition temperature of dust layer. Increasing the thickness of dust at the same time extends the flameless combustion and delays the ignition.

Keywords: fire safety engineering, industrial hazards, minimum ignition temperature, wood dust

Procedia PDF Downloads 320
395 Enhancing Engineering Students Educational Experience: Studying Hydrostatic Pumps Association System in Fluid Mechanics Laboratories

Authors: Alexandre Daliberto Frugoli, Pedro Jose Gabriel Ferreira, Pedro Americo Frugoli, Lucio Leonardo, Thais Cavalheri Santos

Abstract:

Laboratory classes in Engineering courses are essential for students to be able to integrate theory with practical reality, by handling equipment and observing experiments. In the researches of physical phenomena, students can learn about the complexities of science. Over the past years, universities in developing countries have been reducing the course load of engineering courses, in accordance with cutting cost agendas. Quality education is the object of study for researchers and requires educators and educational administrators able to demonstrate that the institutions are able to provide great learning opportunities at reasonable costs. Didactic test benches are indispensable equipment in educational activities related to turbo hydraulic pumps and pumping facilities study, which have a high cost and require long class time due to measurements and equipment adjustment time. In order to overcome the aforementioned obstacles, aligned with the professional objectives of an engineer, GruPEFE - UNIP (Research Group in Physics Education for Engineering - Universidade Paulista) has developed a multi-purpose stand for the discipline of fluid mechanics which allows the study of velocity and flow meters, loads losses and pump association. In this work, results obtained by the association in series and in parallel of hydraulic pumps will be presented and discussed, mainly analyzing the repeatability of experimental procedures and their agreement with the theory. For the association in series two identical pumps were used, consisting of the connection of the discharge of a pump to the suction of the next one, allowing the fluid to receive the power of all machines in the association. The characteristic curve of the set is obtained from the curves of each of the pumps, by adding the heads corresponding to the same flow rates. The same pumps were associated in parallel. In this association, the discharge piping is common to the two machines together. The characteristic curve of the set was obtained by adding to each value of H (head height), the flow rates of each pump. For the tests, the input and output pressure of each pump were measured. For each set there were three sets of measurements, varying the flow rate in range from 6.0 to 8.5 m 3 / h. For the two associations, the results showed an excellent repeatability with variations of less than 10% between sets of measurements and also a good agreement with the theory. This variation agrees with the instrumental uncertainty. Thus, the results validate the use of the fluids bench designed for didactic purposes. As a future work, a digital acquisition system is being developed, using differential sensors of extremely low pressures (2 to 2000 Pa approximately) for the microcontroller Arduino.

Keywords: engineering education, fluid mechanics, hydrostatic pumps association, multi-purpose stand

Procedia PDF Downloads 222
394 Mapping the Digital Landscape: An Analysis of Party Differences between Conventional and Digital Policy Positions

Authors: Daniel Schwarz, Jan Fivaz, Alessia Neuroni

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Although digitization is a buzzword in almost every election campaign, the political parties leave voters largely in the dark about their specific positions on digital issues. In the run-up to the 2019 elections in Switzerland, the ‘Digitization Monitor’ project (DMP) was launched in order to change this situation. Within the framework of the DMP, all 4,736 candidates were surveyed about their digital policy positions and values. The DMP is designed as a digital policy supplement to the existing ‘smartvote’ voting advice application. This enabled a direct comparison of the digital policy attitudes according to the DMP with the topics of the ‘smartvote’ questionnaire which are comprehensive in content but mainly related to conventional policy areas. This paper’s main research goal is to analyze and visualize possible differences between conventional and digital policy areas in terms of response patterns between and within political parties. The analysis is based on dimensionality reduction methods (multidimensional scaling and principal component analysis) for the visualization of inter-party differences, and on standard deviation as a measure of variation for the evaluation of intra-party unity. The results reveal that digital issues show a lower degree of inter-party polarization compared to conventional policy areas. Thus, the parties have more common ground in issues on digitization than in conventional policy areas. In contrast, the study reveals a mixed picture regarding intra-party unity. Homogeneous parties show a lower degree of unity in digitization issues whereas parties with heterogeneous positions in conventional areas have more united positions in digital areas. All things considered, the findings are encouraging as less polarized conditions apply to the debate on digital development compared to conventional politics. For the future, it would be desirable if in further countries similar projects to the DMP could emerge to broaden the basis for conclusions.

Keywords: comparison of political issue dimensions, digital awareness of candidates, digital policy space, party positions on digital issues

Procedia PDF Downloads 187
393 Providing a Practical Model to Reduce Maintenance Costs: A Case Study in Golgohar Company

Authors: Iman Atighi, Jalal Soleimannejad, Ahmad Akbarinasab, Saeid Moradpour

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In the past, we could increase profit by increasing product prices. But in the new decade, a competitive market does not let us to increase profit with increase prices. Therefore, the only way to increase profit will be reduce costs. A significant percentage of production costs are the maintenance costs, and analysis of these costs could achieve more profit. Most maintenance strategies such as RCM (Reliability-Center-Maintenance), TPM (Total Productivity Maintenance), PM (Preventive Maintenance) etc., are trying to reduce maintenance costs. In this paper, decreasing the maintenance costs of Concentration Plant of Golgohar Company (GEG) was examined by using of MTBF (Mean Time between Failures) and MTTR (Mean Time to Repair) analyses. These analyses showed that instead of buying new machines and increasing costs in order to promote capacity, the improving of MTBF and MTTR indexes would solve capacity problems in the best way and decrease costs.

Keywords: Golgohar Iron Ore Mining and Industrial Company, maintainability, maintenance costs, reliability-center-maintenance

Procedia PDF Downloads 303
392 Utilizing Grid Computing to Enhance Power Systems Performance

Authors: Rafid A. Al-Khannak, Fawzi M. Al-Naima

Abstract:

Power load is one of the most important controlling keys which decide power demands and illustrate power usage to shape power market. Hence, power load forecasting is the parameter which facilitates understanding and analyzing all these aspects. In this paper, power load forecasting is solved under MATLAB environment by constructing a neural network for the power load to find an accurate simulated solution with the minimum error. A developed algorithm to achieve load forecasting application with faster technique is the aim for this paper. The algorithm is used to enable MATLAB power application to be implemented by multi machines in the Grid computing system, and to accomplish it within much less time, cost and with high accuracy and quality. Grid Computing, the modern computational distributing technology, has been used to enhance the performance of power applications by utilizing idle and desired Grid contributor(s) by sharing computational power resources.

Keywords: DeskGrid, Grid Server, idle contributor(s), grid computing, load forecasting

Procedia PDF Downloads 476
391 Combined Machine That Fertilizes Evenly under Plowing on Slopes and Planning an Experiment

Authors: Qurbanov Huseyn Nuraddin

Abstract:

The results of scientific research on a machine that pours an equal amount of mineral fertilizer under the soil to increase the productivity of grain in mountain farming and obtain quality grain are substantiated. The average yield of the crop depends on the nature of the distribution of fertilizers in the soil. Therefore, the study of effective energy-saving methods for the application of mineral fertilizers is the actual task of modern agriculture. Depending on the type and variety of plants in mountain farming, there is an optimal norm of mineral fertilizers. Applying an equal amount of fertilizer to the soil is one of the conditions that increase the efficiency of the field. One of the main agro-technical indicators of the work of mineral fertilizing machines is to ensure equal distribution of mineral fertilizers in the field. Taking into account the above-mentioned issues, a combined plough has been improved in our laboratory.

Keywords: combined plough, mineral fertilizers, sprinkle fluently, fertilizer rate, cereals

Procedia PDF Downloads 73
390 An Experimental Testbed Using Virtual Containers for Distributed Systems

Authors: Parth Patel, Ying Zhu

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Distributed systems have become ubiquitous, and they continue their growth through a range of services. With advances in resource virtualization technology such as Virtual Machines (VM) and software containers, developers no longer require high-end servers to test and develop distributed software. Even in commercial production, virtualization has streamlined the process of rapid deployment and service management. This paper introduces a distributed systems testbed that utilizes virtualization to enable distributed systems development on commodity computers. The testbed can be used to develop new services, implement theoretical distributed systems concepts for understanding, and experiment with virtual network topologies. We show its versatility through two case studies that utilize the testbed for implementing a theoretical algorithm and developing our own methodology to find high-risk edges. The results of using the testbed for these use cases have proven the effectiveness and versatility of this testbed across a range of scenarios.

Keywords: distributed systems, experimental testbed, peer-to-peer networks, virtual container technology

Procedia PDF Downloads 147
389 The Application on Interactivity of Light in New Media Art

Authors: Yansong Chen

Abstract:

In the age of media convergence, new media technology is constantly impacting, changing, and even reshaping the limits of Art. From the technological ontology of the new media art, the concept of interaction design has always been dominated by I/O (Input/Output) systems through the ages, which ignores the content of systems and kills the aura of art. Light, as a fusion media, basically comes from the extension of some human feelings and can be the content of the input or the effect of output. In this paper, firstly, on the basis of literature review, the interaction characteristics research was conducted on light. Secondly, starting from discourse patterns of people and machines, people and people, people, and imagining things, we propose three light modes: object-oriented interaction, Immersion interaction, Tele-Presence interaction. Finally, this paper explains how to regain the aura of art through light elements in new media art and understand multiple levels of 'Interaction design'. In addition, the new media art, especially the light-based interaction art, enriches the language patterns and motivates emerging art forms to be more widespread and popular, which achieves its aesthetics growth.

Keywords: new media art, interaction design, light art, immersion

Procedia PDF Downloads 237
388 Translation Training in the AI Era

Authors: Min Gao

Abstract:

In the past year, the advent of large language models (LLMs) has brought about a revolution in the language service industry, making it possible to efficiently produce more satisfactory and higher-quality translations. This is groundbreaking news for commercial companies involved in language services since much of a translator's work can now be completed by machines. However, it may be bad news for universities that provide translation training programs. They need to confront the challenges posed by AI in education by reconsidering issues such as the reform of traditional teaching methods, the translation ethics of students, and the new demands of the job market for their graduates. This article is an exploratory study of these issues based on the author's experiences in translation teaching. The research combines methods in the form of questionnaires and interviews. The findings include: (1) students may lose their motivation to learn in the AI era, but this can be compensated for by encouragement from the lecturer; (2) Translation ethics are not a serious problem in schools, considering the strict policies and regulations in place; (3) The role of translators has evolved in the new era, necessitating a reform of the traditional teaching methods.

Keywords: job market of translation, large language model, translation ethics, translation training

Procedia PDF Downloads 68
387 Process of Production of an Artisanal Brewery in a City in the North of the State of Mato Grosso, Brazil

Authors: Ana Paula S. Horodenski, Priscila Pelegrini, Salli Baggenstoss

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The brewing industry with artisanal concepts seeks to serve a specific market, with diversified production that has been gaining ground in the national environment, also in the Amazon region. This growth is due to the more demanding consumer, with a diversified taste that wants to try new types of beer, enjoying products with new aromas, flavors, as a differential of what is so widely spread through the big industrial brands. Thus, through qualitative research methods, the study aimed to investigate how is the process of managing the production of a craft brewery in a city in the northern State of Mato Grosso (BRAZIL), providing knowledge of production processes and strategies in the industry. With the efficient use of resources, it is possible to obtain the necessary quality and provide better performance and differentiation of the company, besides analyzing the best management model. The research is descriptive with a qualitative approach through a case study. For the data collection, a semi-structured interview was elaborated, composed of the areas: microbrewery characterization, artisan beer production process, and the company supply chain management. Also, production processes were observed during technical visits. With the study, it was verified that the artisan brewery researched develops preventive maintenance strategies with the inputs, machines, and equipment, so that the quality of the product and the production process are achieved. It was observed that the distance from the supplying centers makes the management of processes and the supply chain be carried out with a longer planning time so that the delivery of the final product is satisfactory. The production process of the brewery is composed of machines and equipment that allows the control and quality of the product, which the manager states that for the productive capacity of the industry and its consumer market, the available equipment meets the demand. This study also contributes to highlight one of the challenges for the development of small breweries in front of the market giants, that is, the legislation, which fits the microbreweries as producers of alcoholic beverages. This makes the micro and small business segment to be taxed as a major, who has advantages in purchasing large batches of raw materials and tax incentives because they are large employers and tax pickers. It was possible to observe that the supply chain management system relies on spreadsheets and notes that are done manually, which could be simplified with a computer program to streamline procedures and reduce risks and failures of the manual process. In relation to the control of waste and effluents affected by the industry is outsourced and meets the needs. Finally, the results showed that the industry uses preventive maintenance as a productive strategy, which allows better conditions for the production and quality of artisanal beer. The quality is directly related to the satisfaction of the final consumer, being prized and performed throughout the production process, with the selection of better inputs, the effectiveness of the production processes and the relationship with the commercial partners.

Keywords: artisanal brewery, production management, production processes, supply chain

Procedia PDF Downloads 121
386 A Strategy of Direct Power Control for PWM Rectifier Reducing Ripple in Instantaneous Power

Authors: T. Mohammed Chikouche, K. Hartani

Abstract:

Based on the analysis of basic direct torque control, a parallel master slave for four in-wheel permanent magnet synchronous motors (PMSM) fed by two three phase inverters used in electric vehicle is proposed in this paper. A conventional system with multi-inverter and multi-machine comprises a three phase inverter for each machine to be controlled. Another approach consists in using only one three-phase inverter to supply several permanent magnet synchronous machines. A modified direct torque control (DTC) algorithm is used for the control of the bi-machine traction system. Simulation results show that the proposed control strategy is well adapted for the synchronism of this system and provide good speed tracking performance.

Keywords: electric vehicle, multi-machine single-inverter system, multi-machine multi-inverter control, in-wheel motor, master-slave control

Procedia PDF Downloads 221
385 A Performance Comparison between Conventional and Flexible Box Erecting Machines Using Dispatching Rules

Authors: Min Kyu Kim, Eun Young Lee, Dong Woo Son, Yoon Seok Chang

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In this paper, we introduce a flexible box erecting machine (BEM) that swiftly and automatically transforms cardboard into a three dimensional box. Recently, the parcel service and home-shopping industries have grown rapidly, and there is an increasing need for various box types to ship various products. However, workers cannot fold thousands of boxes manually in a day. As such, automatic BEMs are garnering greater attention. This study takes equipment operation into consideration as well as mechanical improvements in order to design a BEM that is able to outperform its conventional counterparts. We analyzed six dispatching rules – First In First Out (FIFO), Shortest Processing Time (SPT), Earliest Due Date (EDD), Setup Avoidance, EDD + SPT, and EDD + Setup Avoidance – to determine which one was most suitable for BEM operation. Consequently, SPT and Setup Avoidance were found to be the most critical rules, followed by EDD + Setup Avoidance, EDD + SPT, EDD, and FIFO. This hierarchy was valid for both our conventional BEM and our new flexible BEM from the viewpoint of processing time. We believe that this research can contribute to flexible BEM management, which has the potential to increase productivity and convenience.

Keywords: automation, box erecting machine, dispatching rule, setup time

Procedia PDF Downloads 365
384 The Effect of Dynamic Eccentricity on the Stator Current Spectrum of 550 kW Induction Motor

Authors: Saleh Elawgali

Abstract:

In order to present the effect of the dynamic eccentricity on the stator currents of squirrel cage induction machines, the current spectrums of a 550 kW induction motor was calculated for the cases of full symmetry and dynamic eccentricity. The calculations presented in this paper are based on the Poly-Harmonic Model accounting for static and dynamic eccentricity, stator and rotor slotting, parallel branches as well as cage asymmetry. The calculations were followed by Fourier analysis of the stator currents in steady state operation. The paper presents the stator current spectrums for full symmetry and dynamic eccentricity cases, and demonstrates the harmonics present in each case. The effect of dynamic eccentricity is demonstrating via comparing the current spectrums related to dynamic eccentricity cases with the full symmetry one.

Keywords: current spectrum, dynamic eccentricity, harmonics, Induction machine, slot harmonic zone.

Procedia PDF Downloads 400
383 Experimental Set-Up for Investigation of Fault Diagnosis of a Centrifugal Pump

Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

Abstract:

Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

Procedia PDF Downloads 411
382 Automatic Diagnosis of Electrical Equipment Using Infrared Thermography

Authors: Y. Laib Dit Leksir, S. Bouhouche

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Analysis and processing of data bases resulting from infrared thermal measurements made on the electrical installation requires the development of new tools in order to obtain correct and additional information to the visual inspections. Consequently, the methods based on the capture of infrared digital images show a great potential and are employed increasingly in various fields. Although, there is an enormous need for the development of effective techniques to analyse these data base in order to extract relevant information relating to the state of the equipments. Our goal consists in introducing recent techniques of modeling based on new methods, image and signal processing to develop mathematical models in this field. The aim of this work is to capture the anomalies existing in electrical equipments during an inspection of some machines using A40 Flir camera. After, we use binarisation techniques in order to select the region of interest and we make comparison between these methods of thermal images obtained to choose the best one.

Keywords: infrared thermography, defect detection, troubleshooting, electrical equipment

Procedia PDF Downloads 477
381 Hydrodynamic Analysis of Journal Bearing Operating With Nanolubricants

Authors: R. Hariprakash, K. Prabhakaran Nair

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In this paper, the static and dynamic characteristics of hydrodynamic journal bearings operating under nano lubricants are presented. Hydrodynamic journal bearings are used in turbo machines of power plants to support heavy load. In power plants, bearings are getting failure because of its inability to support the heavy load due to various reasons. Failures of bearings make the power plant to be shutdown. The load carrying capacity of journal bearing mainly depends upon the viscosity of the lubricants. The addition of nano particles on commercially available lubricant may enhance the viscosity of lubricant and in turn, change the performance characteristics. In the literature, though many studies have been carried out for the hydrodynamic bearing operating under Newtonian and non-Newtonian lubricants, studies on hydrodynamic bearings operating under nano lubricants is scarce. Thus, it is felt that there is a need to recompute the performance characteristics of journal bearings operating under nano lubricants.

Keywords: hydrodynamic, journal, bearing, analysis

Procedia PDF Downloads 435
380 Hardware Error Analysis and Severity Characterization in Linux-Based Server Systems

Authors: Nikolaos Georgoulopoulos, Alkis Hatzopoulos, Konstantinos Karamitsios, Konstantinos Kotrotsios, Alexandros I. Metsai

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In modern server systems, business critical applications run in different types of infrastructure, such as cloud systems, physical machines and virtualization. Often, due to high load and over time, various hardware faults occur in servers that translate to errors, resulting to malfunction or even server breakdown. CPU, RAM and hard drive (HDD) are the hardware parts that concern server administrators the most regarding errors. In this work, selected RAM, HDD and CPU errors, that have been observed or can be simulated in kernel ring buffer log files from two groups of Linux servers, are investigated. Moreover, a severity characterization is given for each error type. Better understanding of such errors can lead to more efficient analysis of kernel logs that are usually exploited for fault diagnosis and prediction. In addition, this work summarizes ways of simulating hardware errors in RAM and HDD, in order to test the error detection and correction mechanisms of a Linux server.

Keywords: hardware errors, Kernel logs, Linux servers, RAM, hard disk, CPU

Procedia PDF Downloads 158
379 Adopting Cloud-Based Techniques to Reduce Energy Consumption: Toward a Greener Cloud

Authors: Sandesh Achar

Abstract:

The cloud computing industry has set new goals for better service delivery and deployment, so anyone can access services such as computation, application, and storage anytime. Cloud computing promises new possibilities for approaching sustainable solutions to deploy and advance their services in this distributed environment. This work explores energy-efficient approaches and how cloud-based architecture can reduce energy consumption levels amongst enterprises leveraging cloud computing services. Adopting cloud-based networking, database, and server machines provide a comprehensive means of achieving the potential gains in energy efficiency that cloud computing offers. In energy-efficient cloud computing, virtualization is one aspect that can integrate several technologies to achieve consolidation and better resource utilization. Moreover, the Green Cloud Architecture for cloud data centers is discussed in terms of cost, performance, and energy consumption, and appropriate solutions for various application areas are provided.

Keywords: greener cloud, cloud computing, energy efficiency, energy consumption, metadata tags, green cloud advisor

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378 Numerical Simulation of Magnetohydrodynamic (MHD) Blood Flow in a Stenosed Artery

Authors: Sreeparna Majee, G. C. Shit

Abstract:

Unsteady blood flow has been numerically investigated through stenosed arteries to achieve an idea about the physiological blood flow pattern in diseased arteries. The blood is treated as Newtonian fluid and the arterial wall is considered to be rigid having deposition of plaque in its lumen. For direct numerical simulation, vorticity-stream function formulation has been adopted to solve the problem using implicit finite difference method by developing well known Peaceman-Rachford Alternating Direction Implicit (ADI) scheme. The effects of magnetic parameter and Reynolds number on velocity and wall shear stress are being studied and presented quantitatively over the entire arterial segment. The streamlines have been plotted to understand the flow pattern in the stenosed artery, which has significant alterations in the downstream of the stenosis in the presence of magnetic field. The results show that there are nominal changes in the flow pattern when magnetic field strength is enhanced upto 8T which can have remarkable usage to MRI machines.

Keywords: magnetohydrodynamics, blood flow, stenosis, energy dissipation

Procedia PDF Downloads 276
377 Regression Model Evaluation on Depth Camera Data for Gaze Estimation

Authors: James Purnama, Riri Fitri Sari

Abstract:

We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

Procedia PDF Downloads 539