Search results for: automated teller machines

Authors: Jinsiang Shaw, Sheng-Xiang Xu

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This paper presents the development of an autonomous automated guided vehicle (AGV) with a robot arm attached on top of it within the framework of robot operation system (ROS). ROS can provide libraries and tools, including hardware abstraction, device drivers, libraries, visualizers, message-passing, package management, etc. For this reason, this AGV can provide automatic navigation and parts transportation and pick-and-place task using robot arm for typical industrial production line use. More specifically, this AGV will be controlled by an on-board host computer running ROS software. Command signals for vehicle and robot arm control and measurement signals from various sensors are transferred to respective microcontrollers. Users can operate the AGV remotely through the TCP / IP protocol and perform SLAM (Simultaneous Localization and Mapping). An RGBD camera and LIDAR sensors are installed on the AGV, using these data to perceive the environment. For SLAM, Gmapping is used to construct the environment map by Rao-Blackwellized particle filter; and AMCL method (Adaptive Monte Carlo localization) is employed for mobile robot localization. In addition, current AGV position and orientation can be visualized by ROS toolkit. As for robot navigation and obstacle avoidance, A* for global path planning and dynamic window approach for local planning are implemented. The developed ROS AGV with a robot arm on it has been experimented in the university factory. A 2-D and 3-D map of the factory were successfully constructed by the SLAM method. Base on this map, robot navigation through the factory with and without dynamic obstacles are shown to perform well. Finally, pick-and-place of parts using robot arm and ensuing delivery in the factory by the mobile robot are also accomplished.

Keywords: automated guided vehicle, navigation, robot operation system, Simultaneous Localization and Mapping

Procedia PDF Downloads 123

Authors: H. M. B. N Jayasinghe

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The water is found almost everywhere on Earth. Water resources contain a lot of pollution. Some diseases can be spread through the water to the living beings. So to be clean water it should undergo a number of treatments necessary to make it drinkable. So it is must to have purification technology for the wastewater. So the waste water treatment plants act a major role in these issues. When considering the procedures taken after the water treatment process was always based on manual calculations and recordings. Water purification plants may interact with lots of manual processes. It means the process taking much time consuming. So the final evaluation and chemical, biological treatment process get delayed. So to prevent those types of drawbacks there are some computerized programmable calculation and analytical techniques going to be introduced to the laboratory staff. To solve this problem automated system will be a solution in which guarantees the rational selection. A decision support system is a way to model data and make quality decisions based upon it. It is widely used in the world for the various kind of process automation. Decision support systems that just collect data and organize it effectively are usually called passive models where they do not suggest a specific decision but only reveal information. This web base system is based on global positioning data adding facility with map location. Most worth feature is SMS and E-mail alert service to inform the appropriate person on a critical issue. The technological influence to the system is HTML, MySQL, PHP, and some other web developing technologies. Current issues in the computerized water chemistry analysis are not much deep in progress. For an example the swimming pool water quality calculator. The validity of the system has been verified by test running and comparison with an existing plant data. Automated system will make the life easier in productively and qualitatively.

Keywords: automated system, wastewater, purification technology, map location

Procedia PDF Downloads 225

Authors: Bin Liu

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As one of the most important tasks in protein sequence analysis, protein remote homology detection has been studied for decades. Currently, the profile-based methods show state-of-the-art performance. Position-Specific Frequency Matrix (PSFM) is widely used profile. However, there exists noise information in the profiles introduced by the amino acids with low frequencies. In this study, we propose a method to remove the noise information in the PSFM by removing the amino acids with low frequencies called Top frequency profile (TFP). Three new matrix transformation methods, including Autocross covariance (ACC) transformation, Tri-gram, and K-separated bigram (KSB), are performed on these profiles to convert them into fixed length feature vectors. Combined with Support Vector Machines (SVMs), the predictors are constructed. Evaluated on two benchmark datasets, and experimental results show that these proposed methods outperform other state-of-the-art predictors.

Keywords: protein remote homology detection, protein fold recognition, top frequency profile, support vector machines

Procedia PDF Downloads 100

Authors: Hyunchul Ahn, William X. S. Wong

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Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: corporate credit rating prediction, Feature selection, genetic algorithms, instance selection, multiclass support vector machines

Procedia PDF Downloads 266

Authors: Riccardo Bonazzi, Michaël Poli, Abeba Nigussie Turi

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This paper presents an applied research of a new module for the financial administration and management industry, Personalizable and Automated Checklists Integrator, Overseeing Legal Investigations (PACIOLI). It aims at designing the business model of the trust company of the future. By identifying the key stakeholders, we draw a general business process design of the industry. The business model focuses on disintermediating the traditional form of business through the new technological solutions of a software company based in Switzerland and hence creating a new interactive platform. The key stakeholders of this interactive platform are identified as IT experts, legal experts, and the New Edge Trust Company (NATC). The mechanism we design and propose has a great importance in improving the efficiency of the financial business administration and management industry, and it also helps to foster the provision of high value added services in the sector.

Keywords: new edge trust company, business model design, automated checklists, financial technology

Procedia PDF Downloads 337

Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

Procedia PDF Downloads 583

Authors: Galal Omer, Onisimo Mutanga, Elfatih M. Abdel-Rahman, Elhadi Adam

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Threatened tree species (TTS) play a significant role in ecosystem functioning and services, land use dynamics, and other socio-economic aspects. Such aspects include ecological, economic, livelihood, security-based, and well-being benefits. The development of techniques for mapping and monitoring TTS is thus critical for understanding the functioning of ecosystems. The advent of advanced imaging systems and supervised learning algorithms has provided an opportunity to classify TTS over fragmenting landscape. Recently, vegetation maps have been produced using advanced imaging systems such as WorldView-2 (WV-2) and robust classification algorithms such as support vectors machines (SVM) and artificial neural network (ANN). However, delineation of TTS in a fragmenting landscape using high resolution imagery has widely remained elusive due to the complexity of the species structure and their distribution. Therefore, the objective of the current study was to examine the utility of the advanced WV-2 data for mapping TTS in the fragmenting Dukuduku indigenous forest of South Africa using SVM and ANN classification algorithms. The results showed the robustness of the two machine learning algorithms with an overall accuracy (OA) of 77.00% (total disagreement = 23.00%) for SVM and 75.00% (total disagreement = 25.00%) for ANN using all eight bands of WV-2 (8B). This study concludes that SVM and ANN classification algorithms with WV-2 8B have the potential to classify TTS in the Dukuduku indigenous forest. This study offers relatively accurate information that is important for forest managers to make informed decisions regarding management and conservation protocols of TTS.

Keywords: artificial neural network, threatened tree species, indigenous forest, support vector machines

Procedia PDF Downloads 490

Authors: Salam Alzubaidi, G. Fantoni, F. Failli, M. Frosolini

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The dynamic facility layout problem is a really critical issue in the competitive industrial market; thus, solving this problem requires robust design and effective simulation systems. The sustainable simulation requires inputting reliable and accurate data into the system. So this paper describes an automated system integrated into the real environment to measure the duration of the material handling operations, collect the data in real-time, and determine the variances between the actual and estimated time schedule of the operations in order to update the simulation software and redesign the facility layout periodically. The automated method- time measurement system collects the real data through using Radio Frequency-Identification (RFID) and Internet of Things (IoT) technologies. Hence, attaching RFID- antenna reader and RFID tags enables the system to identify the location of the objects and gathering the time data. The real duration gathered will be manipulated by calculating the moving average duration of the material handling operations, choosing the shortest material handling path, and then updating the simulation software to redesign the facility layout accommodating with the shortest/real operation schedule. The periodic simulation in real-time is more sustainable and reliable than the simulation system relying on an analysis of historical data. The case study of this methodology is in cooperation with a workshop team for producing mechanical parts. Although there are some technical limitations, this methodology is promising, and it can be significantly useful in the redesigning of the manufacturing layout.

Keywords: dynamic facility layout problem, internet of things, method time measurement, radio frequency identification, simulation

Procedia PDF Downloads 102

Authors: Watcharapan Sukkerd, Teeradej Wuttipornpun

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This paper aims to present non-population search algorithms called tabu search (TS), simulated annealing (SA) and variable neighborhood search (VNS) to minimize the total cost of capacitated MRP problem in multi-stage assembly flow shop with two alternative machines. There are three main steps for the algorithm. Firstly, an initial sequence of orders is constructed by a simple due date-based dispatching rule. Secondly, the sequence of orders is repeatedly improved to reduce the total cost by applying TS, SA and VNS separately. Finally, the total cost is further reduced by optimizing the start time of each operation using the linear programming (LP) model. Parameters of the algorithm are tuned by using real data from automotive companies. The result shows that VNS significantly outperforms TS, SA and the existing algorithm.

Keywords: capacitated MRP, tabu search, simulated annealing, variable neighborhood search, linear programming, assembly flow shop, application in industry

Procedia PDF Downloads 212

Authors: Rohaya Abdul Wahab, Raja Mohd Fuad Tengku Aziz, Nazaliza Othman, Sharifah Saleh, Nabihah Razali, Rozaimah Baharim, M. Hanif M. Nasir

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This paper will discuss how EDA tools are integrated and automated in an Integrated Circuit Design Environment. Some of the problems face in our current environment is that users need to configure manually on the library paths, start-up files and project directories. Certain manual processes that happen between the users and applications can be automated but they must be transparent to the users. For example, the users can run the applications directly after login without knowing the library paths and start-up files locations. The solution to these problems is to automate the processes using standard configuration files which will benefit the users and EDA support. This paper will discuss how the implementation is done to automate the process using scripting languages such as Perl, Tcl, Scheme and Shell Script. These scripting tools are great assets for design engineers to build a robust and powerful design flow and this technique is widely used to integrate all the tools together.

Keywords: EDA tools, Integrated Circuits, scripting, integration, automation

Procedia PDF Downloads 292

Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar

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In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.

Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding

Procedia PDF Downloads 143

Authors: Aisha Adam

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This study critically examines the transformative impact of automated decision-making (ADM) and artificial intelligence (AI) systems on South African labour law. As AI technologies increasingly infiltrate workplaces, existing liability frameworks face challenges in addressing the unique complexities presented by these innovations. This article explores the necessity of redefining liability to accommodate the nuanced landscape of ADM and AI within South African labour law. It emphasises the importance of ensuring responsible deployment and safeguarding the rights of workers amid evolving technological dynamics. This research investigates the central concern of fairness, bias, and discrimination in ADM and AI decision-making. Focusing on algorithmic bias and discriminatory outcomes, the paper advocates for the integration of mechanisms within the South African legal framework, particularly under the Promotion of Equality and Prevention of Unfair Discrimination Act (PEPUDA) and the Employment Equity Act (EEA). The study scrutinises the shifting dynamics of the employment relationship, calling for clear guidelines on the responsibilities and liabilities of employers, employees, and technology providers. Furthermore, the article analyses legal and policy responses to ADM and AI within South African labour law, exploring potential amendments to legislation, guidelines, and codes of practice. It assesses the role of regulatory bodies, specifically the Commission for Conciliation, Mediation, and Arbitration (CCMA), in overseeing and enforcing responsible practices in the workplace. Lastly, the research evaluates the impact of ADM and AI on human and social rights in the South African context. Emphasising the protection of constitutional rights, including fair labour practices, privacy, and equality, the study proposes remedies and safeguards. It advocates for a multidisciplinary approach involving legal, technological, and ethical considerations to redefine liability in South African labour law effectively. The article contends that a shift from accountability to responsibility is crucial for promoting fairness, antidiscrimination, and the protection of human and social rights in the age of automated decision-making. It calls for collaborative efforts among stakeholders to shape responsible practices and redefine liability in this evolving technological landscape.

Keywords: automated decision-making, artificial intelligence, labour law, vicarious liability

Procedia PDF Downloads 46

Authors: Sanjay Singh, Sushil Kumar, Rashmi Jain

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Quantum registering is another pattern in computational hypothesis and a quantum mechanical framework has a few helpful properties like Entanglement. We plan to store data concerning the structure and substance of a basic picture in a quantum framework. Consider a variety of n qubits which we propose to use as our memory stockpiling. In recent years classical processing is switched to quantum image processing. Quantum image processing is an elegant approach to overcome the problems of its classical counter parts. Image storage, retrieval and its processing on quantum machines is an emerging area. Although quantum machines do not exist in physical reality but theoretical algorithms developed based on quantum entangled states gives new insights to process the classical images in quantum domain. Here in the present work, we give the brief overview, such that how entangled states can be useful for quantum image storage and retrieval. We discuss the properties of tripartite Greenberger-Horne-Zeilinger and W states and their usefulness to store the shapes which may consist three vertices. We also propose the techniques to store shapes having more than three vertices.

Keywords: Greenberger-Horne-Zeilinger, image storage and retrieval, quantum entanglement, W states

Procedia PDF Downloads 277

Authors: Julio Franco

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Water is used, directly and indirectly, in all activities of the construction productive chain, making it a subject of worldwide relevance for sustainable development. The ongoing expansion of urban areas leads to a high demand for natural resources, which in turn cause significant environmental impacts. The present work proposes the application of BIM tools to assist the measurement of the water footprint (WF) of civil construction supplies. Data was inserted into the model as element properties, allowing them to be analyzed by element or in the whole model. The WF calculation was automated using parameterization in Autodesk Revit software. Parameterization was associated to the materials of each element in the model so that any changes in these elements directly alter the results of WF calculations. As a case study, we applied into a building project model to test the parameterized calculus of WF. Results show that the proposed parameterization successfully automated WF calculations according to design changes. We envision this tool to assist the measurement and rationalization of the environmental impact in terms of WF of construction projects.

Keywords: building information modeling, BIM, sustainable development, water footprint

Procedia PDF Downloads 121

Authors: Onur Ozveri, Korkut Karabag, Cagri Keles

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It is an important issue that the occurring of production downtime and repair costs when machines fail in the machine intensive production industries. In the case of failure of more than one machine at the same time, which machines will have the priority to repair, how to determine the optimal repair time should be allotted for this machines and how to plan the resources needed to repair are the key issues. In recent years, Business Process Management (BPM) technique, bring effective solutions to different problems in business. The main feature of this technique is that it can improve the way the job done by examining in detail the works of interest. In the industries, maintenance and repair works are operating as a process and when a breakdown occurs, it is known that the repair work is carried out in a series of process. Maintenance main-process and repair sub-process are evaluated with process management technique, so it is thought that structure could bring a solution. For this reason, in an international manufacturing company, this issue discussed and has tried to develop a proposal for a solution. The purpose of this study is the implementation of maintenance and repair works which is integrated with process management technique and at the end of implementation, analyzing the maintenance related parameters like quality, cost, time, safety and spare part. The international firm that carried out the application operates in a free region in Turkey and its core business area is producing original equipment technologies, vehicle electrical construction, electronics, safety and thermal systems for the world's leading light and heavy vehicle manufacturers. In the firm primarily, a project team has been established. The team dealt with the current maintenance process again, and it has been revised again by the process management techniques. Repair process which is sub-process of maintenance process has been discussed again. In the improved processes, the ABC equipment classification technique was used to decide which machine or machines will be given priority in case of failure. This technique is a prioritization method of malfunctioned machine based on the effect of the production, product quality, maintenance costs and job security. Improved maintenance and repair processes have been implemented in the company for three months, and the obtained data were compared with the previous year data. In conclusion, breakdown maintenance was found to occur in a shorter time, with lower cost and lower spare parts inventory.

Keywords: ABC equipment classification, business process management (BPM), maintenance, repair performance

Procedia PDF Downloads 166

Authors: Hyun June Kim, Tailong Shi, Seden Akdagli, Sam Most, Yuling Yan

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Quantitative analysis of mouse whisker movement can be used to study functional recovery and regeneration of facial nerve after an injury. However, it is challenging to accurately track mouse whisker movements, and most whisker tracking methods require manual intervention, e.g. fixing the head of the mouse during a study. Here we describe a semi-automated image processing method that is applied to high-speed video recordings of free-moving mice to track whisker movements. We first track the head movement of a mouse by delineating the lower head contour frame-by-frame to locate and determine the orientation of its head. Then, a region of interest is identified for each frame, with subsequent application of the Hough transform to track individual whisker movements on each side of the head. Our approach is used to examine the functional recovery of damaged facial nerves in mice over a course of 21 days.

Keywords: mystacial macrovibrissae, whisker tracking, head tracking, facial nerve recovery

Procedia PDF Downloads 562

Authors: Abigail Rosenberg, Jennifer Duan, Michael Poteuck, Chunshui Yu

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The Barry M. Goldwater Range, West in southwestern Arizona encompasses 2,808 square kilometers of Sonoran Desert. The hyper-arid range has an annual rainfall of less than 10 cm with an average high temperature of 41 degrees Celsius in July to an average low of 4 degrees Celsius in January. The range shares approximately 60 kilometers of the international border with Mexico. A majority of the range is open for recreational use, primarily off-highway vehicles. Because of its proximity to Mexico, the range is also heavily patrolled by U.S. Customs and Border Protection seeking to intercept and apprehend inadmissible people and illicit goods. Decades of off-roading and Border Patrol activities have negatively impacted this sensitive desert ecosystem. To assist the range program managers, this study is developing a model to identify erosion prone areas and calibrate the model’s parameters using the Automated Geospatial Watershed Assessment modeling tool.

Keywords: arid lands, automated geospatial watershed assessment, erosion modeling, sedimentation modeling, watershed modeling

Procedia PDF Downloads 341

Authors: Hozaifa Zaki, Ghada Soliman

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In this paper, we introduced an approach for Automated Dotted Arabic Expiration Date Extraction using Optimized Convolutional Autoencoder (ARABEX) with bidirectional LSTM. This approach is used for translating the Arabic dot-matrix expiration dates into their corresponding filled-in dates. A custom lightweight Convolutional Recurrent Neural Network (CRNN) model is then employed to extract the expiration dates. Due to the lack of available dataset images for the Arabic dot-matrix expiration date, we generated synthetic images by creating an Arabic dot-matrix True Type Font (TTF) matrix to address this limitation. Our model was trained on a realistic synthetic dataset of 3287 images, covering the period from 2019 to 2027, represented in the format of yyyy/mm/dd. We then trained our custom CRNN model using the generated synthetic images to assess the performance of our model (ARABEX) by extracting expiration dates from the translated images. Our proposed approach achieved an accuracy of 99.4% on the test dataset of 658 images, while also achieving a Structural Similarity Index (SSIM) of 0.46 for image translation on our dataset. The ARABEX approach demonstrates its ability to be applied to various downstream learning tasks, including image translation and reconstruction. Moreover, this pipeline (ARABEX+CRNN) can be seamlessly integrated into automated sorting systems to extract expiry dates and sort products accordingly during the manufacturing stage. By eliminating the need for manual entry of expiration dates, which can be time-consuming and inefficient for merchants, our approach offers significant results in terms of efficiency and accuracy for Arabic dot-matrix expiration date recognition.

Keywords: computer vision, deep learning, image processing, character recognition

Procedia PDF Downloads 51

Authors: E. K. A. Ogunshile

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This paper is aimed at creating an Automatic Java X-Machine testing tool for software development. The nature of software development is changing; thus, the type of software testing tools required is also changing. Software is growing increasingly complex and, in part due to commercial impetus for faster software releases with new features and value, increasingly in danger of containing faults. These faults can incur huge cost for software development organisations and users; Cambridge Judge Business School’s research estimated the cost of software bugs to the global economy is $312 billion. Beyond the cost, faster software development methodologies and increasing expectations on developers to become testers is driving demand for faster, automated, and effective tools to prevent potential faults as early as possible in the software development lifecycle. Using X-Machine theory, this paper will explore a new tool to address software complexity, changing expectations on developers, faster development pressures and methodologies, with a view to reducing the huge cost of fixing software bugs.

Keywords: conformance testing, finite state machine, software testing, x-machine

Procedia PDF Downloads 244

Authors: Qiang Zhang, Xiaojian Hu1

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Intersection is the place where vehicles and pedestrians must pass through, turn and evacuate. Obtaining the motion data of vehicles near the intersection is of great significance for transportation research. Since there are usually many targets and there are more conflicts between targets, this makes it difficult to obtain vehicle motion parameters in traffic videos of intersections. According to the characteristics of traffic videos, this paper applies video technology to realize the automated track, count and trajectory extraction of vehicles to collect traffic data by roadside surveillance cameras installed near the intersections. Based on the video recognition method, the vehicles in each lane near the intersection are tracked with extracting trajectory and counted respectively in various degrees of occlusion and visibility. The performances are compared with current recognized CPU-based algorithms of real-time tracking-by-detection. The speed of the presented system is higher than the others and the system has a better real-time performance. The accuracy of direction has reached about 94.99% on average, and the accuracy of classification and statistics has reached about 75.12% on average.

Keywords: tracking and statistics, vehicle, signalized intersection, motion parameter, trajectory

Procedia PDF Downloads 192

Authors: Wiwat Kittinaraporn, Napat Harnpornchai, Sutja Boonyachut

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This paper deals with the application of a novel neural network technique, so-called Support Vector Machine (SVM). The objective of this study is to explore the variable and parameter of forecasting factors in the construction industry to build up forecasting model for construction quantity in Thailand. The scope of the research is to study the non-residential construction quantity in Thailand. There are 44 sets of yearly data available, ranging from 1965 to 2009. The correlation between economic indicators and construction demand with the lag of one year was developed by Apichat Buakla. The selected variables are used to develop SVM models to forecast the non-residential construction quantity in Thailand. The parameters are selected by using ten-fold cross-validation method. The results are indicated in term of Mean Absolute Percentage Error (MAPE). The MAPE value for the non-residential construction quantity predicted by Epsilon-SVR in corporation with Radial Basis Function (RBF) of kernel function type is 5.90. Analysis of the experimental results show that the support vector machine modelling technique can be applied to forecast construction quantity time series which is useful for decision planning and management purpose.

Keywords: forecasting, non-residential, construction, support vector machines

Procedia PDF Downloads 406

Authors: Melike Yaylacı, Tuğba Bilgin

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Against the climate crisis, an increasing number of countries are working on green energy, carbon emission measurement, calculation and reduction. The work of industrial organizations with the highest carbon emissions on these issues is increasing. Aim of this paper is calculating carbon emissions of laser cutting machine with cradle-to-grave approach and discuss the potential affects of usage condisions, such as laser power, gas type, gas pressure, on carbon footprint. In particular, this study includes consumption of electricity used in production, laser cutting machine raw materials, and disposal of the machine. In the process of raw material supplying, machine procesing and shipping, all calculations were studied using the Tier1 approach. Laser cutting machines require a specified cutting parameter set for each different material in different thickneses, this parameters are a combination of laser power, gas type, cutting speed, gas pressure and focus point, The another purpose of this study is examine the potential affect of different cutting parameters for the same material in same thickness on carbon footprint.

Keywords: life cycle assessment, carbon emission, laser cutting machine, cutting parameters

Procedia PDF Downloads 65

Authors: Youji Miyake

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In aircraft assembly, a large number of preparatory holes are required for screw and rivet joints. Currently, many holes are drilled manually because it is difficult to machine the holes using conventional computerized numerical control(CNC) machines. The application of industrial robots to drill the hole has been considered as an alternative to the CNC machines. However, the rigidity of robot arms is so low that vibration is likely to occur during drilling. In this study, it is proposed constant-load feed machining as a method to perform high-precision drilling while minimizing the thrust force, which is considered to be the cause of vibration. In this method, the drill feed is realized by a constant load applied onto the tool so that the thrust force is theoretically kept below the applied load. The performance of the proposed method was experimentally examined through the deep hole drilling of plastic and simultaneous drilling of metal/plastic stack plates. It was confirmed that the deep hole drilling and simultaneous drilling could be performed without generating vibration by controlling the tool feed rate in the appropriate range.

Keywords: constant load feed machining, robotic drilling, deep hole, simultaneous drilling

Procedia PDF Downloads 168

Authors: Vimal Jasoliya, Purnank Bhatt, Mit Shah

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The Injection Moulding is one of the principle methods of conversions of plastics into various end products using a very wide range of plastics materials from commodity plastics to specialty engineering plastics. Injection Moulding Machines are rated as per the tonnage force applied. The work present includes Design & Finite Element Analysis of a structure component of injection moulding machine i.e. clamp cylinder. The work of the project is to upgrade the 1300T clamp cylinder to 1500T clamp cylinder for injection moulding machine. The design of existing clamp cylinder of 1300T is checked. Finite Element analysis is carried out for 1300T clamp cylinder in ANSYS Workbench, and the stress values are compared with acceptance criteria and theoretical calculation. The relation between the clamp cylinder diameter and the tonnage capacity has been derived and verified for 1300T clamp cylinder. The same correlation is used to find out the thickness for 1500T clamp cylinder. The detailed design of 1500T cylinder is carried out based on calculated thickness.

Keywords: clamp cylinder, fatigue analysis, finite element analysis, injection moulding machines

Procedia PDF Downloads 310

Authors: M. Akhlaque Ahmed, Maliha Afshan Siddiqui

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A study has been carried out to see the prospect of wind power potential of southern Sindh namely Karachi, Hawksbay, Norriabad, Hyderabad, Ketibander and Shahbander using local wind speed data. The monthly average wind speed for these area ranges from 4.5m/sec to 8.5m/sec at 30m height from ground. Extractable wind power, wind energy and Weibul parameter for above mentioned areas have been examined. Furthermore, the power output using fast and slow wind machine using different blade diameter along with the 4Kw and 20 Kw aero-generator were examined to see the possible use for deep well pumping and electricity supply to remote villages. The analysis reveals that in this wind corridor of southern Sindh Hawksbay, Ketibander and Shahbander belongs to wind power class-3 Hyderabad and Nooriabad belongs to wind power class-5 and Karachi belongs to wind power class-2. The result shows that the that higher wind speed values occur between June till August. It was found that considering maximum wind speed location, Hawksbay,Noriabad are the best location for setting up wind machines for power generation.

Keywords: wind energy generation, Southern Sindh, seasonal change, Weibull parameter, wind machines

Procedia PDF Downloads 123

Authors: David Tresner-Kirsch

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Reconciling patient medication lists from multiple sources is a critical task supporting the safe delivery of patient care. Manual reconciliation is a time-consuming and error-prone process, and recently attempts have been made to develop efficiency- and safety-oriented automated support for professionals performing the task. An important capability of any such support system is automated alignment – finding which medications from a list correspond to which medications from a different source, regardless of misspellings, naming differences (e.g. brand name vs. generic), or changes in treatment (e.g. switching a patient from one antidepressant class to another). This work describes a new algorithmic solution to this alignment task, using a greedy matching approach based on string similarity, edit distances, concept extraction and normalization, and synonym search derived from the RxNorm nomenclature. The accuracy of this algorithm was evaluated against a gold-standard corpus of 681 medication records; this evaluation found that the algorithm predicted alignments with 99% precision and 91% recall. This performance is sufficient to support decision support applications for medication reconciliation.

Keywords: clinical decision support, medication reconciliation, natural language processing, RxNorm

Procedia PDF Downloads 261

Authors: John Sweeney, Martin Leeming, Raj Thaker, Cristina L. Tuinea-Bobe

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Shrink wrapping is widely used as a method for secondary packaging to assemble individual items, such as cans or other consumer products, into single packages. This method involves conveying the packages into heated tunnels and so has the disadvantages that it is energy-intensive, and, in the case of aerosol products, potentially hazardous. We are developing an automated packaging system that uses stretch wrapping to address both these problems, by using a mechanical rather than a thermal process. In this study, we present a comparative study of shrink wrapping and stretch wrapping materials to assess the relative capability of candidate stretch wrap polymer film in terms of mechanical response. The stretch wrap materials are of oriented polymer and therefore elastically anisotropic. We are developing material constitutive models that include both anisotropy and nonlinearity. These material models are to be incorporated into computer simulations of the automated stretch wrapping system. We present results showing the validity of these models and the feasibility of applying them in the simulations.

Keywords: constitutive model, polymer, mechanical testing, wrapping system

Procedia PDF Downloads 273

Authors: Jiangbo Shi, Zeyu Gao, Chen Li

Abstract:

Nuclei segmentation is a fundamental task in digital pathology analysis and can be automated by deep learning-based methods. However, the development of such an automated method requires a large amount of data with precisely annotated masks which is hard to obtain. Training with weakly labeled data is a popular solution for reducing the workload of annotation. In this paper, we propose a novel meta-learning-based nuclei segmentation method which follows the label correction paradigm to leverage data with noisy masks. Specifically, we design a fully conventional meta-model that can correct noisy masks by using a small amount of clean meta-data. Then the corrected masks are used to supervise the training of the segmentation model. Meanwhile, a bi-level optimization method is adopted to alternately update the parameters of the main segmentation model and the meta-model. Extensive experimental results on two nuclear segmentation datasets show that our method achieves the state-of-the-art result. In particular, in some noise scenarios, it even exceeds the performance of training on supervised data.

Keywords: deep learning, histopathological image, meta-learning, nuclei segmentation, weak annotations

Procedia PDF Downloads 116

Authors: G. Rajeshwari, V. D. M. Jabez Daniel

Abstract:

Radio Frequency Identification systems are used for automated identification in various applications such as automobiles, health care and security. It is also called as the automated data collection technology. RFID readers are placed in any area to scan large number of tags to cover a wide distance. The placement of the RFID elements may result in several types of collisions. A major challenge in RFID system is collision avoidance. In the previous works the collision was avoided by using algorithms such as ALOHA and tree algorithm. This work proposes collision reduction and increased throughput through reading enhancement method with tree algorithm. The reading enhancement is done by improving interrogation procedure and increasing the data handling capacity of RFID reader with parallel processing. The work is simulated using Xilinx ISE 14.5 verilog language. By implementing this in the RFID system, we can able to achieve high throughput and avoid collision in the reader at a same instant of time. The overall system efficiency will be increased by implementing this.

Keywords: antenna, anti-collision protocols, data management system, reader, reading enhancement, tag

Procedia PDF Downloads 266

Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

Abstract:

Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

Procedia PDF Downloads 224