Search results for: process data

Authors: Young Jae Choung, Seoung Bum Kim

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Statistical Process Control (SPC) is a popular technique for process monitoring. A widely used tool in SPC is a control chart, which is used to detect the abnormal status of a process and maintain the controlled status of the process. Traditional control charts, such as Hotelling’s T2 control chart, are effective techniques to detect abnormal observations and monitor processes. However, many complicated manufacturing systems exhibit nonlinearity because of the different demands of the market. In this case, the unregulated use of a traditional linear modeling approach may not be effective. In reality, many industrial processes contain the nonlinear and time-varying properties because of the fluctuation of process raw materials, slowing shift of the set points, aging of the main process components, seasoning effects, and catalyst deactivation. The use of traditional SPC techniques with time-varying data will degrade the performance of the monitoring scheme. To address these issues, in the present study, we propose a parameterless self-organizing map (PLSOM)-based control chart. The PLSOM-based control chart not only can manage a situation where the distribution or parameter of the target observations changes, but also address the nonlinearity of modern manufacturing systems. The control limits of the proposed PLSOM chart are established by estimating the empirical level of significance on the percentile using a bootstrap method. Experimental results with simulated data and actual process data from a thin-film transistor-liquid crystal display process demonstrated the effectiveness and usefulness of the proposed chart.

Keywords: control chart, parameter-less self-organizing map, self-organizing map, time-varying property

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Authors: Syamala Krishnannair

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A multivariate statistical process monitoring methodology using dissimilarity scale-based singular spectrum analysis (SSA) is proposed for the detection and diagnosis of process faults in the base metal flotation plant. Process faults are detected based on the multi-level decomposition of process signals by SSA using the dissimilarity structure of the process data and the subsequent monitoring of the multiscale signals using the unified monitoring index which combines T² with SPE. Contribution plots are used to identify the root causes of the process faults. The overall results indicated that the proposed technique outperformed the conventional multivariate techniques in the detection and diagnosis of the process faults in the flotation plant.

Keywords: fault detection, fault diagnosis, process monitoring, dissimilarity scale

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Authors: Siti Nur Izati Azmi, Zatil Afifah Omar, Kathi Swaran, Navin Kumar

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Organophilic Clays, also known as Organoclays, is used as a viscosifier in Oil based Drilling fluids. Most often, Organophilic clay are produced from modified Sodium and Calcium based Bentonite. Many studies and data show that Organophilic Clay using Hectorite based clays provide the best yield and good fluid loss properties in an oil-based drilling fluid at a higher cost. In terms of the manufacturing process, the two common methods of manufacturing organophilic clays are a Wet Process and a Dry Process. Wet process is known to produce better performance product at a higher cost while Dry Process shorten the production time. Hence, the purpose of this study is to evaluate the various formulation of an organophilic clay and its performance vs. the cost, as well as to determine the most efficient and cost-effective method of manufacturing organophilic clays.

Keywords: organophilic clay, viscosifier, wet process, dry process

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Authors: T. Wejrzanowski, M. Grybczuk, E. Tymicki, K. J. Kurzydlowski

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In the present study numerical simulations silicon carbide single crystal growth process in Physical Vapor Transport reactor are addressed. Silicon Carbide is a perspective material for many applications in modern electronics. One of the main challenges for wider applications of SiC is high price of high quality mono crystals. Improvement of silicon carbide manufacturing process has a significant influence on the product price. Better understanding of crystal growth allows for optimization of the process, and it can be achieved by numerical simulations. In this work Virtual Reactor software was used to simulate the process. Predicted geometrical properties of the final product and information about phenomena occurring inside process reactor were obtained. The latter is especially valuable because reactor chamber is inaccessible during the process due to high temperature inside the reactor (over 2000˚C). Obtained data was used for improvement of the process and reactor geometry. Resultant crystal quality was also predicted basing on crystallization front shape evolution and threading dislocation paths. Obtained results were confronted with experimental data and the results are in good agreement.

Keywords: Finite Volume Method, semiconductors, Physical Vapor Transport, silicon carbide

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Authors: Himanshu Payal, Sachin Maheshwari, Pushpendra S. Bharti

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Electrical discharge machining (EDM), a non-conventional machining process, finds wide applications for shaping difficult-to-cut alloys. Process modeling of EDM is required to exploit the process to the fullest. Process modeling of EDM is a challenging task owing to involvement of so many electrical and non-electrical parameters. This work is an attempt to model the EDM process using artificial neural network (ANN). Experiments were carried out on die-sinking EDM taking Inconel 825 as work material. ANN modeling has been performed using experimental data. The prediction ability of trained network has been verified experimentally. Results indicate that ANN can predict the values of performance measures of EDM satisfactorily.

Keywords: artificial neural network, EDM, metal removal rate, modeling, surface roughness

Procedia PDF Downloads 389

Authors: Bolin Hua

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In city governance, various data are involved, including city component data, demographic data, housing data and all kinds of business data. These data reflects different aspects of people, events and activities. Data generated from various systems are different in form and data source are different because they may come from different sectors. In order to reflect one or several facets of an event or rule, data from multiple sources need fusion together. Data from different sources using different ways of collection raised several issues which need to be resolved. Problem of data fusion include data update and synchronization, data exchange and sharing, file parsing and entry, duplicate data and its comparison, resource catalogue construction. Governments adopt statistical analysis, time series analysis, extrapolation, monitoring analysis, value mining, scenario prediction in order to achieve pattern discovery, law verification, root cause analysis and public opinion monitoring. The result of Multi-source data fusion is to form a uniform central database, which includes people data, location data, object data, and institution data, business data and space data. We need to use meta data to be referred to and read when application needs to access, manipulate and display the data. A uniform meta data management ensures effectiveness and consistency of data in the process of data exchange, data modeling, data cleansing, data loading, data storing, data analysis, data search and data delivery.

Keywords: multi-source data fusion, urban comprehensive management, information fusion, government data

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Authors: Maram Saleh

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Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains.

Keywords: Data Mining, Knowledge management, Knowledge discovery, Knowledge creation.

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Authors: Wannee Sutthachaidee

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The study of the production process of coconut-shell product in Amphawa, Samutsongkram Province is objected to study the pattern of the process of coconut-shell product by focusing in the 3 main processes which are inbound logistics process, production process and outbound process. The result of the research: There were 4 main results from the study. Firstly, most of the manufacturer of coconut-shell product is usually owned by a single owner and the quantity of the finished product is quite low and the main labor group is local people. Secondly, the production process can be divided into 4 stages which are pre-production process, production process, packaging process and distribution process. Thirdly, each 3 of the logistics process of coconut shell will find process which may cause the problem to the business but the process which finds the most problem is the production process because the production process needs the skilled labor and the quantity of the labor does not match with the demand from the customers. Lastly, the factors which affect the production process of the coconut shell can be founded in almost every process of the process such as production design, packaging design, sourcing supply and distribution management.

Keywords: production process, coconut-shell product, Amphawa District, inbound logistics process

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Authors: Tabinda Sadiq, Tehmina Ashfaq Qazi, Hoor Shumail

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Recently, the advent of emerging technology has created an emerging generation of restaurant marketing. It explores the aspects that influence customers’ decision-making process in selecting a restaurant after reading food bloggers' reviews online. The motivation behind this research is to investigate the correlation between the credibility of the source and their attitude toward restaurant visits. The researcher collected the data by distributing a survey questionnaire through google forms by employing the Source credibility theory. Non- probability purposive sampling technique was used to collect data. The questionnaire used a predeveloped and validated scale by Ohanian to measure the relationship. Also, the researcher collected data from 250 respondents in order to investigate the influence of food bloggers on Gen Z's decision-making process. SPSS statistical version 26 was used for statistical testing and analyzing the data. The findings of the survey revealed that there is a moderate positive correlation between the variables. So, it can be analyzed that food bloggers do have an impact on Generation Z's decision making process.

Keywords: credibility, decision making, food bloggers, generation z, e-wom

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Authors: Byungmin Cho, Dongchul Lee, Taejin Kim, Minhee Lee

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The procedure for the seismic retrofit of existing buildings includes the seismic evaluation. In the evaluation step, it is assessed whether the buildings have satisfactory performance against seismic load. Based on the results of that, the buildings are upgraded. To evaluate seismic performance of the buildings, it usually goes through the model transformation from elastic analysis to inelastic analysis. However, when the data is not delivered through the interwork, engineers should manually input the data. In this process, since it leads to inaccuracy and loss of information, the results of the analysis become less accurate. Therefore, in this study, the process for the seismic evaluation of existing buildings using structural information modeling is suggested. This structural information modeling makes the work economic and accurate. To this end, it is determined which part of the process could be computerized through the investigation of the process for the seismic evaluation based on ASCE 41. The structural information modeling process is developed to apply to the seismic evaluation using Perform 3D program usually used for the nonlinear response history analysis. To validate this process, the seismic performance of an existing building is investigated.

Keywords: existing building, nonlinear analysis, seismic performance, structural information modeling

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Authors: Denise Hexom, Judith Menoher

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Teachers and administrators across America are being asked to use data and hard evidence to inform practice as they begin the task of implementing Common Core State Standards. Yet, the courses they are taking in schools of education are not preparing teachers or principals to understand the data-driven decision making (DDDM) process nor to utilize data in a much more sophisticated fashion. DDDM has been around for quite some time, however, it has only recently become systematically and consistently applied in the field of education. This paper discusses the theoretical framework of DDDM; empirical evidence supporting the effectiveness of DDDM; a process a department in a school of education has utilized to implement DDDM; and recommendations to other schools of education who attempt to implement DDDM in their decision-making processes and in their students’ coursework.

Keywords: data-driven decision making, institute of higher education, special education, continuous improvement

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Authors: Handie Pramana Putra, Ani Dijah Rahajoe

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The proliferation of smart devices and advancements in mobile communication technologies have permeated various facets of life with the widespread influence of e-commerce. Detecting abnormal transactions holds paramount significance in this realm due to the potential for substantial financial losses. Moreover, the fusion of data flow and control flow assumes a critical role in the exploration of process modeling and data analysis, contributing significantly to the accuracy and security of business processes. This paper introduces an alternative approach to identify abnormal transactions through a model that integrates both data and control flows. Referred to as the Extended Data Petri net (DPNE), our model encapsulates the entire process, encompassing user login to the e-commerce platform and concluding with the payment stage, including the mobile transaction process. We scrutinize the model's structure, formulate an algorithm for detecting anomalies in pertinent data, and elucidate the rationale and efficacy of the comprehensive system model. A case study validates the responsive performance of each system component, demonstrating the system's adeptness in evaluating every activity within mobile transactions. Ultimately, the results of anomaly detection are derived through a thorough and comprehensive analysis.

Keywords: database, data analysis, DPNE, extended data flow, e-commerce

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Authors: Widjojo Suprapto, Zeplin Jiwa Husada Tarigan, Sautma Ronni Basana

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Business process reengineering can be conducted by some procedure rationalization for all related departments in a company so that all data and business processes are connected. The changing of any business process is used to set up the working standard so that it gives an impact to the implementation of ERP and the company performance. After collecting and processing the data from 77 manufacturing companies, it is obtained that BPR (Business Process Reengineering) has no direct impact on the implementation of ERP (Enterprise Resource Planning) in the companies and manufacturing performance; however, it influences the implementation of TQM. The implementation of TQM influences directly the implementation of ERP, but it does not influence directly the company performance. The implementation of ERP gives a significant increase in the work performance of the manufacturing companies in East Java.

Keywords: enterprise resources planning, business process reengineering, TQM, company performance

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Authors: Sikander Singh Cheema, Jasmeen Kaur

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In this paper, the concept of data mining is summarized and its one of the important process i.e KDD is summarized. The data mining based on Genetic Algorithm is researched in and ways to achieve the data mining Genetic Algorithm are surveyed. This paper also conducts a formal review on the area of data mining tasks and genetic algorithm in various fields.

Keywords: data mining, KDD, genetic algorithm, descriptive mining, predictive mining

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Authors: M. V. Manoj Kumar, Likewin Thomas, Annappa

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Process mining research discipline bridges the gap between data mining and business process modeling and analysis, it offers the process-centric and end-to-end methods/techniques for analyzing information of real-world process detailed in operational event-logs. In this paper, we have proposed a notation called trace logo for graphically representing control-flow perspective (order of execution of activities) of process. A trace logo consists of a stack of activity names at each position, sizes of the activity name indicates their frequency in the traces and the total height of the activity depicts the information content of the position. A trace logo created from a set of aligned traces generated using Multiple Trace Alignment technique.

Keywords: consensus trace, process mining, multiple trace alignment, trace logo

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Authors: Nay Myo Sandar

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With the growth of technologies and applications, a large amount of data has been producing at increasing rate from various resources such as social media networks, sensor devices, and other information serving devices. This large collection of massive, complex and exponential growth of dataset is called big data. The traditional database systems cannot store and process such data due to large and complexity. Consequently, cloud computing is a potential solution for data storage and processing since it can provide a pool of resources for servers and storage. However, moving large amount of data to and from is a challenging issue since it can encounter a high latency due to large data size. With respect to big data movement problem, this paper reviews the literature of previous works, discusses about research issues, finds out approaches for dealing with big data movement problem.

Keywords: Big Data, Cloud Computing, Big Data Movement, Network Techniques

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Authors: Noor Abdelhamid, Donovan Nelson, Cara Prosser

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The architectural design process could be mapped out as a dialogue between designer and user that is constructed across multiple phases with the overarching goal of aligning design outcomes with user needs. Traditionally, this dialogue is bounded within a preliminary phase of determining factors that will direct the design intent, and a completion phase, of handing off the project to the client. Pre- and post-occupancy evaluations (P/POE’s) could provide an alternative process by extending this dialogue on both ends of the design process. The purpose of this research is to study the influence of systematic pre-occupancy data collection in achieving design goals by conducting post-occupancy evaluations of two case studies. In the context of this study, systematic pre-occupancy data collection is defined as the preliminary documentation of the existing conditions that helps portray stakeholders’ needs. When implemented, pre-occupancy occurs during the early phases of the architectural design process, utilizing the information to shape the design intent. Investigative POE’s are performed on two case studies with distinct early design approaches to understand how the current space is impacting user needs, establish design outcomes, and inform future strategies. The first case study underwent systematic pre-occupancy data collection and synthesis, while the other represents the traditional, uncoordinated practice of informally collecting data during an early design phase. POE’s target the dynamics between the building and its occupants by studying how spaces are serving the needs of the users. Data collection for this study consists of user surveys, audiovisual materials, and observations during regular site visits. Mixed methods of qualitative and quantitative analyses are synthesized to identify patterns in the data. The paper concludes by positioning value on both sides of the architectural design process: the integration of systematic pre-occupancy methods in the early phases and the reinforcement of a continued dialogue between building and design team after building completion.

Keywords: architecture, design process, pre-occupancy data, post-occupancy evaluation

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Authors: Herminio Martínez-García, Juan Gámiz, Yolanda Bolea, Antoni Grau

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This article presents an interactive system for data acquisition in vehicle testing according to the test process defined in automotive directive 2004/104/EC. The project has been designed and developed by authors for the Spanish company Applus-LGAI. The developed project will result in a new process, which will involve the creation of braking cycle test defined in the aforementioned automotive directive. It will also allow the analysis of new vehicle features that was not feasible, allowing an increasing interaction with the vehicle. Potential users of this system in the short term will be vehicle manufacturers and in a medium term the system can be extended to testing other automotive components and EMC tests.

Keywords: automotive process, data acquisition system, electromagnetic compatibility (EMC) testing, European Directive 2004/104/EC

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Authors: Fouzi Harrou, Ying Sun, Sofiane Khadraoui

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Anomaly detection based on Principal Component Analysis (PCA) was studied intensively and largely applied to multivariate processes with highly cross-correlated process variables. Monitoring metrics such as the Hotelling's T2 and the Q statistics are usually used in PCA-based monitoring to elucidate the pattern variations in the principal and residual subspaces, respectively. However, these metrics are ill suited to detect small faults. In this paper, the Exponentially Weighted Moving Average (EWMA) based on the Q and T statistics, T2-EWMA and Q-EWMA, were developed for detecting faults in the process mean. The performance of the proposed methods was compared with that of the conventional PCA-based fault detection method using synthetic data. The results clearly show the benefit and the effectiveness of the proposed methods over the conventional PCA method, especially for detecting small faults in highly correlated multivariate data.

Keywords: data-driven method, process control, anomaly detection, dimensionality reduction

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Authors: Arslan Ellahi, Syed Amjad Hussain

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Software Testing is a vital process in software development life cycle. We can attain the quality of software after passing it through software testing phase. We have tried to find out automatic test data generation techniques that are a key research area of software testing to achieve test automation that can eventually decrease testing time. In this paper, we review some of the approaches presented in the literature which use evolutionary search based algorithms like Genetic Algorithm, Particle Swarm Optimization (PSO), etc. to validate the test data generation process. We also look into the quality of test data generation which increases or decreases the efficiency of testing. We have proposed test data generation techniques for model-based testing. We have worked on tuning and fitness function of PSO algorithm.

Keywords: search based, evolutionary algorithm, particle swarm optimization, genetic algorithm, test data generation

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Authors: Prashant Shrivastava

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The purpose of this study is to explore re3dat.org registry to identify research data repositories registration workflow process. Further objective is to depict a graph for present development of research data repositories in India. Preliminarily with an approach to understand re3data.org registry framework and schema design then further proceed to explore the status of research data repositories of India in re3data.org registry. Research data repositories are getting wider relevance due to e-research concepts. Now available registry re3data.org is a good tool for users and researchers to identify appropriate research data repositories as per their research requirements. In Indian environment, a compatible National Research Data Policy is the need of the time to boost the management of research data. Registry for Research Data Repositories is a crucial tool to discover specific information in specific domain. Also, Research Data Repositories in India have not been studied. Re3data.org registry and status of Indian research data repositories both discussed in this study.

Keywords: research data, research data repositories, research data registry, re3data.org

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Authors: Georg Ebner

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The National Defence Academy, an element of the Austrian Ministry of Defence, is undergoing a transition process leading the Academy towards a new target structure that is currently being developed. In so doing, in addition to a subject-oriented approach, also an employee-oriented process was introduced. This process was initiated by the Ministry of Defence and should lead the National Defence Academy into a new constellation. During this process, the National Defence Academy worked in very special adapted World Café sessions. The “change manager” dealed with very different issues. They took the data feedback from the sessions and prepared with the feedback and information from the guidance the next session. So they got various information and a very different picture around the academy. It was very helpful to involve most of the employees of the academy during this process and to take their knowledge and wisdom. The process himself started with very different feelings and ended with great consent. A very interesting part of this process was also that the commander and his deputy worked together during all of this sessions and they answered all questions from the employees in time. The adapted World Café phases were necessary to deal with the information of the staff and to implement these absolutely needful data into this process. In cooperation with the responsible Headquarters, the first items resulting from the World Café phases could already be fed back to the employees and be implemented. The staff-oriented process is currently supported via a point of contact, through which the staff can contribute ideas as well, but also by the active information policy on the part of the Headquarters. The described change process makes innovative innovations possible. So far, in the event of change processes staff members have been entrusted only with the concrete implementation plan and tied into the process when the respective workplaces were to be re-staffed. The procedure described here can be seen as food-for-thought for further change processes. The findings of this process are that a staff oriented process can lead an organisation into a new era of thinking and working. This process has shown, that a lot of innovative ideas can also take place in a ministry. This process can be a background for a lot of change management processes in ministries and governmental and non-governmental organisations.

Keywords: both directions approach, change management, knowledge database, transformation process, World Cafe

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Authors: Prateep Wajeetongratana

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The purpose of this research was to study the influence of accountants’ potential performance on their working process, a case study of Government Savings Banks in the northeast of Thailand. The independent variables included accounting knowledge, accounting skill, accounting value, accounting ethics, and accounting attitude, while the dependent variable included the success of the working process. A total of 155 accountants working for Government Savings Banks were selected by random sampling. A questionnaire was used as a tool for collecting data. Descriptive statistics in this research included percentage, mean, and multiple regression analyses. The findings revealed that the majority of accountants were female with an age between 35-40 years old. Most of the respondents had an undergraduate degree with ten years of experience. Moreover, the factors of accounting knowledge, accounting skill, accounting a value and accounting ethics and accounting attitude were rated at a high level. The findings from regression analysis of observation data revealed a causal relationship in that the observation data could explain at least 51 percent of the success in the accountants’ working process.

Keywords: influence, potential performance, success, working process

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Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos

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Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.

Keywords: diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion process, trends functions, bi-parameters weibull density function

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Authors: Hyun-Koo Kim, Yong-Hun Kim, Soo-Young Suk, Ju H. Park, Ho-Youl Jung

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This paper presents an effective speed hump detection process at the day-time. we focus only on round types of speed humps in the day-time dynamic road environment. The proposed speed hump detection scheme consists mainly of two process as stereo matching and speed hump detection process. Our proposed process focuses to speed hump detection process. Speed hump detection process consist of noise reduction step, data fusion step, and speed hemp detection step. The proposed system is tested on Intel Core CPU with 2.80 GHz and 4 GB RAM tested in the urban road environments. The frame rate of test videos is 30 frames per second and the size of each frame of grabbed image sequences is 1280 pixels by 670 pixels. Using object-marked sequences acquired with an on-vehicle camera, we recorded speed humps and non-speed humps samples. Result of the tests, our proposed method can be applied in real-time systems by computation time is 13 ms. For instance; our proposed method reaches 96.1 %.

Keywords: data fusion, round types speed hump, speed hump detection, surface filter

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Authors: Shashank Tiwari, S. P. Mahapatra

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The aim of this technique is to reduce the steps of process scales up, save time & cost of the industries. This technique will minimise the steps of process scale up. The new steps are, Novel Lab Scale, Novel Lab Scale Trials, Novel Trial Batches, Novel Exhibit Batches, Novel Validation Batches. In these steps, it is not divided to validation batches in three parts but the data of trials batches, Exhibit Batches and Validation batches are use and compile for production and used for validation. It also increases the batch size of the trial, exhibit batches. The new size of trials batches is not less than fifty Thousand, the exhibit batches increase up to two lack and the validation batches up to five lack. After preparing the batches all their data & drugs use for stability & maintain the validation record and compile data for the technology transfer in production department for preparing the marketed size batches.

Keywords: batches, technique, preparation, scale up, validation

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Authors: Adrian J. Forca, Simeon J. Cainday III

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The Jordan Water District Interactive Billing and Accounting Information Systems is designed for Jordan Water District to uplift the efficiency and effectiveness of its services to its customers. It is designed to process computations of water bills in accurate and fast way through automating the manual process and ensures that correct rates and fees are applied. In addition to billing process, a mobile app will be integrated into it to support rapid and accurate water bill generation. An interactive feature will be incorporated to support electronic billing to customers who wish to receive water bills through the use of electronic mail. The system will also improve, organize and avoid data inaccuracy in accounting processes because data will be stored in a database which is designed logically correct through normalization. Furthermore, strict programming constraints will be plunged to validate account access privilege based on job function and data being stored and retrieved to ensure data security, reliability, and accuracy. The system will be able to cater the billing and accounting services of Jordan Water District resulting in setting forth the manual process and adapt to the modern technological innovations.

Keywords: accounting, bill, information system, interactive

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Authors: Kirill Filianin, Satu-Pia Reinikainen, Tuomo Sainio

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Frequent measurements of product steam quality create a data overload that becomes more and more difficult to handle. In the current study, plant history data with multiple variables was successfully treated by principal component analysis to detect abnormal process behavior, particularly, in copper solvent extraction. The multivariate model is based on the concentration levels of main process metals recorded by the industrial on-stream x-ray fluorescence analyzer. After mean-centering and normalization of concentration data set, two-dimensional multivariate model under principal component analysis algorithm was constructed. Normal operating conditions were defined through control limits that were assigned to squared score values on x-axis and to residual values on y-axis. 80 percent of the data set were taken as the training set and the multivariate model was tested with the remaining 20 percent of data. Model testing showed successful application of control limits to detect abnormal behavior of copper solvent extraction process as early warnings. Compared to the conventional techniques of analyzing one variable at a time, the proposed model allows to detect on-line a process failure using information from all process variables simultaneously. Complex industrial equipment combined with advanced mathematical tools may be used for on-line monitoring both of process streams’ composition and final product quality. Defining normal operating conditions of the process supports reliable decision making in a process control room. Thus, industrial x-ray fluorescence analyzers equipped with integrated data processing toolbox allows more flexibility in copper plant operation. The additional multivariate process control and monitoring procedures are recommended to apply separately for the major components and for the impurities. Principal component analysis may be utilized not only in control of major elements’ content in process streams, but also for continuous monitoring of plant feed. The proposed approach has a potential in on-line instrumentation providing fast, robust and cheap application with automation abilities.

Keywords: abnormal process behavior, failure detection, principal component analysis, solvent extraction

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Authors: Julius Onyancha, Valentina Plekhanova

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One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: web log data, web user profile, user interest, noise web data learning, machine learning

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Authors: Nagmani Lnu

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Often, Quality Engineering refers to testing the applications that either have a User Interface (UI) or an Application Programming Interface (API). We often find mature test practices, standards, and automation regarding UI or API testing. However, another kind is present in almost all types of industries that deal with data in bulk and often get handled through something called a Batch Application. This is primarily an offline application companies develop to process large data sets that often deal with multiple business rules. The challenge gets more prominent when we try to automate batch testing. This paper describes the approaches taken to test a Batch application from a Financial Industry to test the payment settlement process (a critical use case in all kinds of FinTech companies), resulting in 100% test automation in Test Creation and Test execution. One can follow this approach for any other batch use cases to achieve a higher efficiency in their testing process.

Keywords: batch testing, batch test automation, batch test strategy, payments testing, payments settlement testing

Procedia PDF Downloads 31