Search results for: future system operation.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 24867

Search results for: future system operation.

23517 Hard Disk Failure Predictions in Supercomputing System Based on CNN-LSTM and Oversampling Technique

Authors: Yingkun Huang, Li Guo, Zekang Lan, Kai Tian

Abstract:

Hard disk drives (HDD) failure of the exascale supercomputing system may lead to service interruption and invalidate previous calculations, and it will cause permanent data loss. Therefore, initiating corrective actions before hard drive failures materialize is critical to the continued operation of jobs. In this paper, a highly accurate analysis model based on CNN-LSTM and oversampling technique was proposed, which can correctly predict the necessity of a disk replacement even ten days in advance. Generally, the learning-based method performs poorly on a training dataset with long-tail distribution, especially fault prediction is a very classic situation as the scarcity of failure data. To overcome the puzzle, a new oversampling was employed to augment the data, and then, an improved CNN-LSTM with the shortcut was built to learn more effective features. The shortcut transmits the results of the previous layer of CNN and is used as the input of the LSTM model after weighted fusion with the output of the next layer. Finally, a detailed, empirical comparison of 6 prediction methods is presented and discussed on a public dataset for evaluation. The experiments indicate that the proposed method predicts disk failure with 0.91 Precision, 0.91 Recall, 0.91 F-measure, and 0.90 MCC for 10 days prediction horizon. Thus, the proposed algorithm is an efficient algorithm for predicting HDD failure in supercomputing.

Keywords: HDD replacement, failure, CNN-LSTM, oversampling, prediction

Procedia PDF Downloads 79
23516 Vehicular Speed Detection Camera System Using Video Stream

Authors: C. A. Anser Pasha

Abstract:

In this paper, a new Vehicular Speed Detection Camera System that is applicable as an alternative to traditional radars with the same accuracy or even better is presented. The real-time measurement and analysis of various traffic parameters such as speed and number of vehicles are increasingly required in traffic control and management. Image processing techniques are now considered as an attractive and flexible method for automatic analysis and data collections in traffic engineering. Various algorithms based on image processing techniques have been applied to detect multiple vehicles and track them. The SDCS processes can be divided into three successive phases; the first phase is Objects detection phase, which uses a hybrid algorithm based on combining an adaptive background subtraction technique with a three-frame differencing algorithm which ratifies the major drawback of using only adaptive background subtraction. The second phase is Objects tracking, which consists of three successive operations - object segmentation, object labeling, and object center extraction. Objects tracking operation takes into consideration the different possible scenarios of the moving object like simple tracking, the object has left the scene, the object has entered the scene, object crossed by another object, and object leaves and another one enters the scene. The third phase is speed calculation phase, which is calculated from the number of frames consumed by the object to pass by the scene.

Keywords: radar, image processing, detection, tracking, segmentation

Procedia PDF Downloads 467
23515 Internet of Things-Based Smart Irrigation System

Authors: Ahmed Abdulfatah Yusuf, Collins Oduor Ondiek

Abstract:

The automation of farming activities can have a transformational impact on the agricultural sector, especially from the emerging new technologies such as the Internet of Things (IoT). The system uses water level sensors and soil moisture sensors that measure the content of water in the soil as the values generated from the sensors enable the system to use an appropriate quantity of water, which avoids over or under irrigation. Due to the increase in the world’s population, there is a need to increase food production. With this demand in place, it is difficult to increase crop yield using the traditional manual approaches that lead to the wastage of water, thus affecting crop production. Food insecurity has become a scourge greatly affecting the developing countries and agriculture is an essential part of human life and tends to be the mainstay of the economy in most developing nations. Thus, without the provision of adequate food supplies, the population of those living in poverty is likely to multiply. The project’s main objective is to design and develop an IoT (Internet of Things) microcontroller-based Smart Irrigation System. In addition, the specific research objectives are to find out the challenges with traditional irrigation approaches and to determine the benefits of IoT-based smart irrigation systems. Furthermore, the system includes Arduino, a website and a database that works simultaneously in collecting and storing the data. The system is designed to pave the way in attaining the Sustainable Development Goal (SDG 1), which aims to end extreme poverty in all forms by 2030. The research design aimed at this project is a descriptive research design. Data was gathered through online questionnaires that used both quantitative and qualitative in order to triangulate the data. Out of the 32 questionnaires sent, there were 32 responses leading to a 100% response rate. In terms of sampling, the target group of this project is urban farmers, which account for about 25% of the population of Nairobi. From the findings of the research carried out, it is evident that there is a need to move away from manual irrigation approaches due to the high wastage of water to the use of smart irrigation systems that propose a better way of conserving water while maintaining the quality and moisture of the soil. The research also found out that urban farmers are willing to adopt this system to better their farming practices. However, this system can be improved in the future by incorporating it with other features and deploying it to a larger geographical area.

Keywords: crop production, food security, smart irrigation system, sustainable development goal

Procedia PDF Downloads 151
23514 Residual Life Estimation of K-out-of-N Cold Standby System

Authors: Qian Zhao, Shi-Qi Liu, Bo Guo, Zhi-Jun Cheng, Xiao-Yue Wu

Abstract:

Cold standby redundancy is considered to be an effective mechanism for improving system reliability and is widely used in industrial engineering. However, because of the complexity of the reliability structure, there is little literature studying on the residual life of cold standby system consisting of complex components. In this paper, a simulation method is presented to predict the residual life of k-out-of-n cold standby system. In practical cases, failure information of a system is either unknown, partly unknown or completely known. Our proposed method is designed to deal with the three scenarios, respectively. Differences between the procedures are analyzed. Finally, numerical examples are used to validate the proposed simulation method.

Keywords: cold standby system, k-out-of-n, residual life, simulation sampling

Procedia PDF Downloads 401
23513 A Machine Learning Based Method to Detect System Failure in Resource Constrained Environment

Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

Abstract:

Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

Procedia PDF Downloads 195
23512 Empirical Investigation of Bullwhip Effect with Sensitivity Analysis in Supply Chain

Authors: Shoaib Yousaf

Abstract:

The main purpose of this research is to the empirical investigation of the bullwhip effect under sensitivity analysis in the two-tier supply chain. The simulation modeling technique has been applied in this research as a research methodology to see the sensitivity analysis of the bullwhip effect in the rice industry of Pakistan. The research comprises two case studies that have been chosen as a sample. The results of this research have confirmed that reduction in production delay reduces the bullwhip effect, which conforms to the time compressing paradigm and the significance of the reduction in production delay to lessen demand amplification. The result of this research also indicates that by increasing the value of time to adjust inventory decreases the bullwhip effect. Furthermore, by decreasing the value of alpha increases the damping effect of the exponential smoother, it is not surprising that it also reduces the bullwhip effect. Moreover, by reducing the value of time to work in progress also reduces the bullwhip effect. This research will help practitioners and operation managers to reduces the major costs of their products in three ways. They can reduce their i) inventory levels, ii) better utilize their capacity and iii) improve their forecasting techniques. However, this study is based on two tier supply chain, while in reality the supply chain has got many tiers. Hence, future work will be extended across more than two-tier supply chains.

Keywords: bullwhip effect, rice industry, supply chain dynamics, simulation, sensitivity analysis

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23511 Unraveling Biostimulation of Decolorized Mediators for Microbial Fuel Cell-Aided Textile Dye Decontamination

Authors: Pei-Lin Yueh, Bor-Yann Chen, Chuan-Chung Hsueh

Abstract:

This first-attempt study revealed that decolorized intermediates of azo dyes could act as redox mediators to assist wastewater (WW) decolorization due to enhancement of electron-transport phenomena. Electrochemical impedance spectra indicated that hydroxyl and amino-substituent(s) were functional group(s) as redox-mediator(s). As azo dyes are usually multiple benzene rings structured, their derived decolorized intermediates are likely to play roles of electron shuttles due to lower barrier of energy gap for electron shuttling. According to cyclic voltammetric profiles, redox-mediating characteristics of decolorized intermediates of azo dyes (e.g., RBu171, RR198, RR141, and RBk5) were clearly disclosed. With supplementation of biodecolorized metabolites of RR141 and 198, decolorization performance of could be evidently augmented. This study also suggested the optimal modes of microbial fuel cell (MFC)-assisted WW decolorization would be plug-flow or batch mode of operation with no mix. Single chamber-MFCs would be more favourable than double chamber MFCs due to non-mixing contacting reactor scheme for operation.

Keywords: redox mediators, dye decolorization, bioelectricity generation, microbial fuel cells

Procedia PDF Downloads 325
23510 The Temporal Implications of Spatial Prospects

Authors: Zhuo Job Chen, Kevin Nute

Abstract:

The work reported examines potential linkages between spatial and temporal prospects, and more specifically, between variations in the spatial depth and foreground obstruction of window views, and observers’ sense of connection to the future. It was found that external views from indoor spaces were strongly associated with a sense of the future, that partially obstructing such a view with foreground objects significantly reduced its association with the future, and replacing it with a pictorial representation of the same scene (with no real actual depth) removed most of its temporal association. A lesser change in the spatial depth of the view, however, had no apparent effect on association with the future. While the role of spatial depth has still to be confirmed, the results suggest that spatial prospects directly affect temporal ones. The word “prospect” typifies the overlapping of the spatial and temporal in most human languages. It originated in classical times as a purely spatial term, but in the 16th century took on the additional temporal implication of an imagined view ahead, of the future. The psychological notion of prospection, then, has its distant origins in a spatial analogue. While it is not yet proven that space directly structures our processing of time at a physiological level, it is generally agreed that it commonly does so conceptually. The mental representation of possible futures has been a central part of human survival as a species (Boyer, 2008; Suddendorf & Corballis, 2007). A sense of the future seems critical not only practically, but also psychologically. It has been suggested, for example, that lack of a positive image of the future may be an important contributing cause of depression (Beck, 1974; Seligman, 2016). Most people in the developed world now spend more than 90% of their lives indoors. So any direct link between external views and temporal prospects could have important implications for both human well-being and building design. We found that the ability to see what lies in front of us spatially was strongly associated with a sense of what lies ahead temporally. Partial obstruction of a view was found to significantly reduce that sense connection to the future. Replacing a view with a flat pictorial representation of the same scene removed almost all of its connection with the future, but changing the spatial depth of a real view appeared to have no significant effect. While foreground obstructions were found to reduce subjects’ sense of connection to the future, they increased their sense of refuge and security. Consistent with Prospect and Refuge theory, an ideal environment, then, would seem to be one in which we can “see without being seen” (Lorenz, 1952), specifically one that conceals us frontally from others, without restricting our own view. It is suggested that these optimal conditions might be translated architecturally as screens, the apertures of which are large enough for a building occupant to see through unobstructed from close by, but small enough to conceal them from the view of someone looking from a distance outside.

Keywords: foreground obstructions, prospection, spatial depth, window views

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23509 Artificial Neural Network Approach for Vessel Detection Using Visible Infrared Imaging Radiometer Suite Day/Night Band

Authors: Takashi Yamaguchi, Ichio Asanuma, Jong G. Park, Kenneth J. Mackin, John Mittleman

Abstract:

In this paper, vessel detection using the artificial neural network is proposed in order to automatically construct the vessel detection model from the satellite imagery of day/night band (DNB) in visible infrared in the products of Imaging Radiometer Suite (VIIRS) on Suomi National Polar-orbiting Partnership (Suomi-NPP).The goal of our research is the establishment of vessel detection method using the satellite imagery of DNB in order to monitor the change of vessel activity over the wide region. The temporal vessel monitoring is very important to detect the events and understand the circumstances within the maritime environment. For the vessel locating and detection techniques, Automatic Identification System (AIS) and remote sensing using Synthetic aperture radar (SAR) imagery have been researched. However, each data has some lack of information due to uncertain operation or limitation of continuous observation. Therefore, the fusion of effective data and methods is important to monitor the maritime environment for the future. DNB is one of the effective data to detect the small vessels such as fishery ships that is difficult to observe in AIS. DNB is the satellite sensor data of VIIRS on Suomi-NPP. In contrast to SAR images, DNB images are moderate resolution and gave influence to the cloud but can observe the same regions in each day. DNB sensor can observe the lights produced from various artifact such as vehicles and buildings in the night and can detect the small vessels from the fishing light on the open water. However, the modeling of vessel detection using DNB is very difficult since complex atmosphere and lunar condition should be considered due to the strong influence of lunar reflection from cloud on DNB. Therefore, artificial neural network was applied to learn the vessel detection model. For the feature of vessel detection, Brightness Temperature at the 3.7 μm (BT3.7) was additionally used because BT3.7 can be used for the parameter of atmospheric conditions.

Keywords: artificial neural network, day/night band, remote sensing, Suomi National Polar-orbiting Partnership, vessel detection, Visible Infrared Imaging Radiometer Suite

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23508 Augmentation of Automatic Selective Door Operation systems with UWB positioning

Authors: John Chan, Jake Linnenbank, Gavin Caird

Abstract:

Automatic Selective Door Operation (ASDO) systems are increasingly used in railways to provide Correct Side Door Enable (CSDE) protection as well as to protect passenger doors opening off the platform where the train is longer than the platform, or in overshoot or undershoot scenarios. Such ASDO systems typically utilise trackside-installed RFID beacons, such as Eurobalises for odometry positioning purposes. Installing such trackside infrastructure may not be desirable or possible due to various factors such as conflict with existing infrastructure, potential damage from track tamping and jurisdiction constraints. Ultra-wideband (UWB) positioning technology could enable ASDO positioning requirements to be met without requiring installation of equipment directly on track since UWB technology can be installed on adjacent infrastructure such as on platforms. This paper will explore the feasibility of upgrading existing ASDO systems with UWB positioning technology, the feasibility of retrofitting UWB-enabled ASDO systems onto unfitted trains, and any other considerations relating to the use of UWB positioning for ASDO applications.

Keywords: UWB, ASDO, automatic selective door operations, CSDE, correct side door enable

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23507 Energy Consumption and GHG Production in Railway and Road Passenger Regional Transport

Authors: Martin Kendra, Tomas Skrucany, Jozef Gnap, Jan Ponicky

Abstract:

Paper deals with the modeling and simulation of energy consumption and GHG production of two different modes of regional passenger transport – road and railway. These two transport modes use the same type of fuel – diesel. Modeling and simulation of the energy consumption in transport is often used due to calculation satisfactory accuracy and cost efficiency. Paper deals with the calculation based on EN standards and information collected from technical information from vehicle producers and characteristics of tracks. Calculation included maximal theoretical capacity of bus and train and real passenger’s measurement from operation. Final energy consumption and GHG production is calculated by using software simulation. In evaluation of the simulation is used system ‘well to wheel’.

Keywords: bus, consumption energy, GHG, production, simulation, train

Procedia PDF Downloads 443
23506 The Development of XML Resume System in Thailand

Authors: Jarumon Nookhong, Thanakorn Uiphanit

Abstract:

This study is a research and development project which aims to develop XML Resume System to be the standard system in Thailand as well as to measure the efficiency of the XML Resume System in Thailand. This research separates into 2 stages: 1) to develop XML Document System to be the standard in Thailand, and 2) to experiment the system performance. The sample in this research is committed by 50 specialists in the field of human resources by selecting specifically. The tool that uses in this research is XML Resume System in Thailand and the performance evaluation format of system while the analysis of the data is calculated by using average and standard deviation. The result of the research found that the development of the XML Resume System that aims to be the standard system in Thailand had the result 2.67 of the average which is in a good level. The evaluation in testing the performance of the system had been done by the specialists of human resources who use the XML Resume system. When analyzing each part, it found out that the abilities according to the user’s requirement from specialists in the field of human resources, the convenience and easiness in usages, and the functional competency are respectively in a good level. The average of the ability according to the user’s need from specialists of human resources is 2.92. The average of the convenience and easiness in usages is 2.56. The average of functional competency is 2.53. These can be used as the standard effectively.

Keywords: resume, XML, XML schema, computer science

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23505 Application of Supervised Deep Learning-based Machine Learning to Manage Smart Homes

Authors: Ahmed Al-Adaileh

Abstract:

Renewable energy sources, domestic storage systems, controllable loads and machine learning technologies will be key components of future smart homes management systems. An energy management scheme that uses a Deep Learning (DL) approach to support the smart home management systems, which consist of a standalone photovoltaic system, storage unit, heating ventilation air-conditioning system and a set of conventional and smart appliances, is presented. The objective of the proposed scheme is to apply DL-based machine learning to predict various running parameters within a smart home's environment to achieve maximum comfort levels for occupants, reduced electricity bills, and less dependency on the public grid. The problem is using Reinforcement learning, where decisions are taken based on applying the Continuous-time Markov Decision Process. The main contribution of this research is the proposed framework that applies DL to enhance the system's supervised dataset to offer unlimited chances to effectively support smart home systems. A case study involving a set of conventional and smart appliances with dedicated processing units in an inhabited building can demonstrate the validity of the proposed framework. A visualization graph can show "before" and "after" results.

Keywords: smart homes systems, machine learning, deep learning, Markov Decision Process

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23504 Forecasting 24-Hour Ahead Electricity Load Using Time Series Models

Authors: Ramin Vafadary, Maryam Khanbaghi

Abstract:

Forecasting electricity load is important for various purposes like planning, operation, and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet, and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria, namely, the mean absolute error and root mean square error. The National Renewable Energy Laboratory (NREL) residential energy consumption data is used to train the models. The results of this study show that the SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts, we can improve the robustness of the models for 24 hours ahead of electricity load forecasting.

Keywords: bagging, Fbprophet, Holt-Winters, LSTM, load forecast, SARIMA, TensorFlow probability, time series

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23503 Investigating the Role of Positive Adolescent Development on Hope for the Future in Adolescents Aged 14 to 18 with Anxiety in the City of Ahvaz in the Country of Iran in 2023

Authors: Negar Mirzaie, Hedayet Allah Sharifi

Abstract:

The present study was conducted with the aim of investigating the role of positive adolescent development on hope for the future in adolescents aged 14 to 18 with anxiety in the city of Ahvaz in the country of Iran in 2023. This research was descriptive and correlational. The statistical population of the present research was the adolescents aged 14 to 18 with anxiety of Ahvaz city in Iran in 2023. 150 people were selected by Purposeful sampling method and answered questionnaires of positive adolescent development and hope. The data were analyzed by Pearson correlation and multiple regression. The results showed that there is a significant relationship between the positive development of adolescence and hope for the future in anxious adolescents aged 14 to 18 in the city of Ahvaz in Iran in 2023 (p<0.05). Therefore, it is suggested to use the program of positive transformation of adolescents as hope in adolescents.

Keywords: positive adolescent development, hope, adolescents, anxiety

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23502 The Significance of a Well-Defined Systematic Approach in Risk Management for Construction Projects within Oil Industry

Authors: Batool Ismaeel, Umair Farooq, Saad Mushtaq

Abstract:

Construction projects in the oil industry can be very complex, having unknown outcomes and uncertainties that cannot be easily predicted. Each project has its unique risks generated by a number of factors which, if not controlled, will impact the successful completion of the project mainly in terms of schedule, cost, quality, and safety. This paper highlights the historic risks associated with projects in the south and east region of Kuwait Oil Company (KOC) collated from the company’s lessons learned database. Starting from Contract Award through to handover of the project to the Asset owner, the gaps in project execution in terms of managing risk will be brought to discussion and where a well-defined systematic approach in project risk management reflecting many claims, change of scope, exceeding budget, delays in engineering phase as well as in the procurement and fabrication of long lead items should be adopted. This study focuses on a proposed feasible approach in risk management for engineering, procurement and construction (EPC) level projects including the various stakeholders involved in executing the works from International to local contractors and vendors in KOC. The proposed approach covers the areas categorized into organizational, design, procurement, construction, pre-commissioning, commissioning and project management in which the risks are identified and require management and mitigation. With the effective deployment and implementation of the proposed risk management system and the consideration of it as a vital key in achieving the project’s target, the outcomes will be more predictable in the future, and the risk triggers will be managed and controlled. The correct resources can be allocated on a timely basis for the company for avoiding any unpredictable outcomes during the execution of the project. It is recommended in this paper to apply this risk management approach as an integral part of project management and investigate further in the future, the effectiveness of this proposed system for newly awarded projects and compare the same with those projects of similar budget/complexity that have not applied this approach to risk management.

Keywords: construction, project completion, risk management, uncertainties

Procedia PDF Downloads 153
23501 Design of the Ubiquitous Cloud Learning Management System

Authors: Panita Wannapiroon, Noppadon Phumeechanya, Sitthichai Laisema

Abstract:

This study is the research and development which is intended to: 1) design the ubiquitous cloud learning management system and: 2) assess the suitability of the design of the ubiquitous cloud learning management system. Its methods are divided into 2 phases. Phase 1 is the design of the ubiquitous cloud learning management system, phase 2 is the assessment of the suitability of the design the samples used in this study are work done by 25 professionals in the field of Ubiquitous cloud learning management systems and information and communication technology in education selected using the purposive sampling method. Data analyzed by arithmetic mean and standard deviation. The results showed that the ubiquitous cloud learning management system consists of 2 main components which are: 1) the ubiquitous cloud learning management system server (u-Cloud LMS Server) including: cloud repository, cloud information resources, social cloud network, cloud context awareness, cloud communication, cloud collaborative tools, and: 2) the mobile client. The result of the system suitability assessment from the professionals is in the highest range.

Keywords: learning management system, cloud computing, ubiquitous learning, ubiquitous learning management system

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23500 The Effect of Microgrid on Power System Oscillatory Stability

Authors: Burak Yildirim, Muhsin Tunay Gencoglu

Abstract:

This publication shows the effects of Microgrid (MG) integration on the power systems oscillating stability. Generated MG model power systems were applied to the IEEE 14 bus test system which is widely used in stability studies. Stability studies were carried out with the help of eigenvalue analysis over linearized system models. In addition, Hopf bifurcation point detection was performed to show the effect of MGs on the system loadability margin. In the study results, it is seen that MGs affect system stability positively by increasing system loadability margin and has a damper effect on the critical modes of the system and the electromechanical local modes, but they make the damping amount of the electromechanical interarea modes reduce.

Keywords: Eigenvalue analysis, microgrid, Hopf bifurcation, oscillatory stability

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23499 An Open Source Advertisement System

Authors: Pushkar Umaranikar, Chris Pollett

Abstract:

An online advertisement system and its implementation for the Yioop open source search engine are presented. This system supports both selling advertisements and displaying them within search results. The selling of advertisements is done using a system to auction off daily impressions for keyword searches. This is an open, ascending price auction system in which all accepted bids will receive a fraction of the auctioned day’s impressions. New bids in our system are required to be at least one half of the sum of all previous bids ensuring the number of accepted bids is logarithmic in the total ad spend on a keyword for a day. The mechanics of creating an advertisement, attaching keywords to it, and adding it to an advertisement inventory are described. The algorithm used to go from accepted bids for a keyword to which ads are displayed at search time is also presented. We discuss properties of our system and compare it to existing auction systems and systems for selling online advertisements.

Keywords: online markets, online ad system, online auctions, search engines

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23498 Application the Queuing Theory in the Warehouse Optimization

Authors: Jaroslav Masek, Juraj Camaj, Eva Nedeliakova

Abstract:

The aim of optimization of store management is not only designing the situation of store management itself including its equipment, technology and operation. In optimization of store management we need to consider also synchronizing of technological, transport, store and service operations throughout the whole process of logistic chain in such a way that a natural flow of material from provider to consumer will be achieved the shortest possible way, in the shortest possible time in requested quality and quantity and with minimum costs. The paper deals with the application of the queuing theory for optimization of warehouse processes. The first part refers to common information about the problematic of warehousing and using mathematical methods for logistics chains optimization. The second part refers to preparing a model of a warehouse within queuing theory. The conclusion of the paper includes two examples of using queuing theory in praxis.

Keywords: queuing theory, logistics system, mathematical methods, warehouse optimization

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23497 Remote Sensing and Gis Use in Trends of Urbanization and Regional Planning

Authors: Sawan Kumar Jangid

Abstract:

The paper attempts to study various facets of urbanization and regional planning in the framework of the present conditions and future needs. Urbanization is a dynamic system in which development and changes are prominent features; which implies population growth and changes in the primary, secondary and tertiary sector in the economy. Urban population is increasing day by day due to a natural increase in population and migration from rural areas, and the impact is bound to have in urban areas in terms of infrastructure, environment, water supply and other vital resources. For the organized way of planning and monitoring the implementation of Physical urban and regional plans high-resolution satellite imagery is the potential solution. Now the Remote Sensing data is widely used in urban as well as regional planning, infrastructure planning mainly telecommunication and transport network planning, highway development, accessibility to market area development in terms of catchment and population built-up area density. With Remote Sensing it is possible to identify urban growth, which falls outside the formal planning control. Remote Sensing and GIS technique combined together facilitate the planners, in making a decision, for general public and investors to have relevant data for their use in minimum time. This paper sketches out the Urbanization modal for the future development of Urban and Regional Planning. The paper suggests, a dynamic approach towards regional development strategy.

Keywords: development, dynamic, migration, resolution

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23496 Wind Load Reduction Effect of Exterior Porous Skin on Facade Performance

Authors: Ying-Chang Yu, Yuan-Lung Lo

Abstract:

Building envelope design is one of the most popular design fields of architectural profession in nowadays. The main design trend of such system is to highlight the designer's aesthetic intention from the outlook of building project. Due to the trend of current façade design, the building envelope contains more and more layers of components, such as double skin façade, photovoltaic panels, solar control system, or even ornamental components. These exterior components are designed for various functional purposes. Most researchers focus on how these exterior elements should be structurally sound secured. However, not many researchers consider these elements would help to improve the performance of façade system. When the exterior elements are deployed in large scale, it creates an additional layer outside of original façade system and acts like a porous interface which would interfere with the aerodynamic of façade surface in micro-scale. A standard façade performance consists with 'water penetration, air infiltration rate, operation force, and component deflection ratio', and these key performances are majorly driven by the 'Design Wind Load' coded in local regulation. A design wind load is usually determined by the maximum wind pressure which occurs on the surface due to the geometry or location of building in extreme conditions. This research was designed to identify the air damping phenomenon of micro turbulence caused by porous exterior layer leading to surface wind load reduction for improvement of façade system performance. A series of wind tunnel test on dynamic pressure sensor array covered by various scale of porous exterior skin was conducted to verify the effect of wind pressure reduction. The testing specimens were designed to simulate the typical building with two-meter extension offsetting from building surface. Multiple porous exterior skins were prepared to replicate various opening ratio of surface which may cause different level of damping effect. This research adopted 'Pitot static tube', 'Thermal anemometers', and 'Hot film probe' to collect the data of surface dynamic pressure behind porous skin. Turbulence and distributed resistance are the two main factors of aerodynamic which would reduce the actual wind pressure. From initiative observation, the reading of surface wind pressure was effectively reduced behind porous media. In such case, an actual building envelope system may be benefited by porous skin from the reduction of surface wind pressure, which may improve the performance of envelope system consequently.

Keywords: multi-layer facade, porous media, facade performance, turbulence and distributed resistance, wind tunnel test

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23495 Prediction of Springback in U-bending of W-Temper AA6082 Aluminum Alloy

Authors: Jemal Ebrahim Dessie, Lukács Zsolt

Abstract:

High-strength aluminum alloys have drawn a lot of attention because of the expanding demand for lightweight vehicle design in the automotive sector. Due to poor formability at room temperature, warm and hot forming have been advised. However, warm and hot forming methods need more steps in the production process and an advanced tooling system. In contrast, since ordinary tools can be used, forming sheets at room temperature in the W temper condition is advantageous. However, springback of supersaturated sheets and their thinning are critical challenges and must be resolved during the use of this technique. In this study, AA6082-T6 aluminum alloy was solution heat treated at different oven temperatures and times using a specially designed and developed furnace in order to optimize the W-temper heat treatment temperature. A U-shaped bending test was carried out at different time periods between W-temper heat treatment and forming operation. Finite element analysis (FEA) of U-bending was conducted using AutoForm aiming to validate the experimental result. The uniaxial tensile and unload test was performed in order to determine the kinematic hardening behavior of the material and has been optimized in the Finite element code using systematic process improvement (SPI). In the simulation, the effect of friction coefficient & blank holder force was considered. Springback parameters were evaluated by the geometry adopted from the NUMISHEET ’93 benchmark problem. It is noted that the change of shape was higher at the more extended time periods between W-temper heat treatment and forming operation. Die radius was the most influential parameter at the flange springback. However, the change of shape shows an overall increasing tendency on the sidewall as the increase of radius of the punch than the radius of the die. The springback angles on the flange and sidewall seem to be highly influenced by the coefficient of friction than blank holding force, and the effect becomes increases as increasing the blank holding force.

Keywords: aluminum alloy, FEA, springback, SPI, U-bending, W-temper

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23494 A Location Routing Model for the Logistic System in the Mining Collection Centers of the Northern Region of Boyacá-Colombia

Authors: Erika Ruíz, Luis Amaya, Diego Carreño

Abstract:

The main objective of this study is to design a mathematical model for the logistics of mining collection centers in the northern region of the department of Boyacá (Colombia), determining the structure that facilitates the flow of products along the supply chain. In order to achieve this, it is necessary to define a suitable design of the distribution network, taking into account the products, customer’s characteristics and the availability of information. Likewise, some other aspects must be defined, such as number and capacity of collection centers to establish, routes that must be taken to deliver products to the customers, among others. This research will use one of the operation research problems, which is used in the design of distribution networks known as Location Routing Problem (LRP).

Keywords: location routing problem, logistic, mining collection, model

Procedia PDF Downloads 217
23493 Location Tracking of Human Using Mobile Robot and Wireless Sensor Networks

Authors: Muazzam A. Khan

Abstract:

In order to avoid dangerous environmental disasters, robots are being recognized as good entrants to step in as human rescuers. Robots has been gaining interest of many researchers in rescue matters especially which are furnished with advanced sensors. In distributed wireless robot system main objective for a rescue system is to track the location of the object continuously. This paper provides a novel idea to track and locate human in disaster area using stereo vision system and ZigBee technology. This system recursively predict and updates 3D coordinates in a robot coordinate camera system of a human which makes the system cost effective. This system is comprised of ZigBee network which has many advantages such as low power consumption, self-healing low data rates and low cost.

Keywords: stereo vision, segmentation, classification, human tracking, ZigBee module

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23492 Defect Identification in Partial Discharge Patterns of Gas Insulated Switchgear and Straight Cable Joint

Authors: Chien-Kuo Chang, Yu-Hsiang Lin, Yi-Yun Tang, Min-Chiu Wu

Abstract:

With the trend of technological advancement, the harm caused by power outages is substantial, mostly due to problems in the power grid. This highlights the necessity for further improvement in the reliability of the power system. In the power system, gas-insulated switches (GIS) and power cables play a crucial role. Long-term operation under high voltage can cause insulation materials in the equipment to crack, potentially leading to partial discharges. If these partial discharges (PD) can be analyzed, preventative maintenance and replacement of equipment can be carried out, there by improving the reliability of the power grid. This research will diagnose defects by identifying three different defects in GIS and three different defects in straight cable joints, for a total of six types of defects. The partial discharge data measured will be converted through phase analysis diagrams and pulse sequence analysis. Discharge features will be extracted using convolutional image processing, and three different deep learning models, CNN, ResNet18, and MobileNet, will be used for training and evaluation. Class Activation Mapping will be utilized to interpret the black-box problem of deep learning models, with each model achieving an accuracy rate of over 95%. Lastly, the overall model performance will be enhanced through an ensemble learning voting method.

Keywords: partial discharge, gas-insulated switches, straight cable joint, defect identification, deep learning, ensemble learning

Procedia PDF Downloads 78
23491 Study on Angle Measurement Interferometer around Any Axis Direction Selected by Transmissive Liquid Crystal Device

Authors: R. Furutani, G. Kikuchi

Abstract:

Generally, the optical interferometer system is too complicated and difficult to change the measurement items, pitch, yaw, and row, etc. In this article, the optical interferometer system using the transmissive Liquid Crystal Device (LCD) as the switch of the optical path was proposed. At first, the normal optical interferometer, Michelson interferometer, was constructed to measure the pitch angle and the yaw angle. In this optical interferometer, the ball lenses with the refractive indices of 2.0 were used as the retroreflectors. After that, the transmissive LCD was introduced as the switch to select the adequate optical path. In this article, these optical systems were constructed. Pitch measurement interferometer and yaw measurement interferometer were switched by the transmissive LCD. When the LCD was open for the yaw measurement, the yaw was sufficiently measured and optical path for the pitch measurement was blocked. On the other hand, when the LCD was open for the pitch measurement, the pitch was measured and the optical path for the yaw measurement was also blocked. In this article, the results of both of pitch measurement and yaw measurement were shown, and the result of blocked yaw measurement and pitch measurement were shown. As this measurement system was based on Michelson interferometer, the other measuring items, the deviation along the optical axis, the vertical deviation to the optical axis and row angle, could be measured by the additional ball lenses and the additional switching in future work.

Keywords: any direction angle, ball lens, laser interferometer, transmissive liquid crystal device

Procedia PDF Downloads 161
23490 Designing an Automatic Mechanical System to Prevent Cancers Caused by Drinks

Authors: Ghasem Yazadani, Hamidreza Ahmadi, Masoud Ahmadi, Sajad Rezazadeh

Abstract:

In this paper with designing and proposing a compound of a heating and cooling system has been tried to show effect of this system on preventing esophagus cancer that can be caused by hot and cold drinks such as tea, coffee and ice water. This system has been simulated mechanically by fluent software and also has been validated by experimental way and a comprehensive result has been presented. Both of solution ways show that this system can reduce or increase temperature of drink to safe very dramatically and it can be a huge step toward consuming drinks safely and also it can be efficient about time issues. The system consists of a temperature sensor and an electronic controller that has a computer program to act automatically this task. Also this system has been presented after many different simulations and has been tried to find the best one in the point view of velocity of heating and cooling.

Keywords: fluent, heat transfer, controller, esophagus cancer

Procedia PDF Downloads 385
23489 Development of the Independent Building Permit System to Improve Productivity and Quality Service

Authors: Hartomo Soewardi, Bachtiar Jouhari

Abstract:

Ineffectiveness and inefficiency of the building permit process in Indonesia still becomes a major problems for people to apply. Long time of service, the complicated administration process, and an expensive fees are a process that causing a dissatisfaction and discomfort for applicant. Therefore, it is critical to improve the quality of service of building permit system. Objectives of this research is to develop a better process of the system to improve productivity and quality service. Lean six sigma concept by using DMAIC procedures was used to analyze the existing system. Moreover, improvement of the system was conducted by using the Axiomatic Design method. Verification test was done to test the hypothesis of the proposed system design. Result of this research shows that proposed system can produce increasing 61.8% of efficiency on service time, and more effective and easier.

Keywords: axiomatic design, bbuilding permit system, DMAIC, Lean Six Sigma

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23488 Development of Deep Neural Network-Based Strain Values Prediction Models for Full-Scale Reinforced Concrete Frames Using Highly Flexible Sensing Sheets

Authors: Hui Zhang, Sherif Beskhyroun

Abstract:

Structural Health monitoring systems (SHM) are commonly used to identify and assess structural damage. In terms of damage detection, SHM needs to periodically collect data from sensors placed in the structure as damage-sensitive features. This includes abnormal changes caused by the strain field and abnormal symptoms of the structure, such as damage and deterioration. Currently, deploying sensors on a large scale in a building structure is a challenge. In this study, a highly stretchable strain sensors are used in this study to collect data sets of strain generated on the surface of full-size reinforced concrete (RC) frames under extreme cyclic load application. This sensing sheet can be switched freely between the test bending strain and the axial strain to achieve two different configurations. On this basis, the deep neural network prediction model of the frame beam and frame column is established. The training results show that the method can accurately predict the strain value and has good generalization ability. The two deep neural network prediction models will also be deployed in the SHM system in the future as part of the intelligent strain sensor system.

Keywords: strain sensing sheets, deep neural networks, strain measurement, SHM system, RC frames

Procedia PDF Downloads 99