Search results for: intelligent manufacturing systems
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5268

Search results for: intelligent manufacturing systems

4998 Interoperable CNC System for Turning Operations

Authors: Yusri Yusof, Stephen Newman, Aydin Nassehi, Keith Case

Abstract:

The changing economic climate has made global manufacturing a growing reality over the last decade, forcing companies from east and west and all over the world to collaborate beyond geographic boundaries in the design, manufacture and assemble of products. The ISO10303 and ISO14649 Standards (STEP and STEP-NC) have been developed to introduce interoperability into manufacturing enterprises so as to meet the challenge of responding to production on demand. This paper describes and illustrates a STEP compliant CAD/CAPP/CAM System for the manufacture of rotational parts on CNC turning centers. The information models to support the proposed system together with the data models defined in the ISO14649 standard used to create the NC programs are also described. A structured view of a STEP compliant CAD/CAPP/CAM system framework supporting the next generation of intelligent CNC controllers for turn/mill component manufacture is provided. Finally a proposed computational environment for a STEP-NC compliant system for turning operations (SCSTO) is described. SCSTO is the experimental part of the research supported by the specification of information models and constructed using a structured methodology and object-oriented methods. SCSTO was developed to generate a Part 21 file based on machining features to support the interactive generation of process plans utilizing feature extraction. A case study component has been developed to prove the concept for using the milling and turning parts of ISO14649 to provide a turn-mill CAD/CAPP/CAM environment.

Keywords:

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4997 Simulation Aided Life Cycle Sustainability Assessment Framework for Manufacturing Design and Management

Authors: Mijoh A. Gbededo, Kapila Liyanage, Ilias Oraifige

Abstract:

Decision making for sustainable manufacturing design and management requires critical considerations due to the complexity and partly conflicting issues of economic, social and environmental factors. Although there are tools capable of assessing the combination of one or two of the sustainability factors, the frameworks have not adequately integrated all the three factors. Case study and review of existing simulation applications also shows the approach lacks integration of the sustainability factors. In this paper we discussed the development of a simulation based framework for support of a holistic assessment of sustainable manufacturing design and management. To achieve this, a strategic approach is introduced to investigate the strengths and weaknesses of the existing decision supporting tools. Investigation reveals that Discrete Event Simulation (DES) can serve as a rock base for other Life Cycle Analysis frameworks. Simio-DES application optimizes systems for both economic and competitive advantage, Granta CES EduPack and SimaPro collate data for Material Flow Analysis and environmental Life Cycle Assessment, while social and stakeholders’ analysis is supported by Analytical Hierarchy Process, a Multi-Criteria Decision Analysis method. Such a common and integrated framework creates a platform for companies to build a computer simulation model of a real system and assess the impact of alternative solutions before implementing a chosen solution.

Keywords: Discrete event simulation, life cycle sustainability analysis, manufacturing, sustainability.

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4996 Optimal Manufacturing Scheduling for Dependent Details Processing

Authors: Ivan C. Mustakerov, Daniela I. Borissova

Abstract:

The increasing competitiveness in manufacturing industry is forcing manufacturers to seek effective processing schedules. The paper presents an optimization manufacture scheduling approach for dependent details processing with given processing sequences and times on multiple machines. By defining decision variables as start and end moments of details processing it is possible to use straightforward variables restrictions to satisfy different technological requirements and to formulate easy to understand and solve optimization tasks for multiple numbers of details and machines. A case study example is solved for seven base moldings for CNC metalworking machines processed on five different machines with given processing order among details and machines and known processing time-s duration. As a result of linear optimization task solution the optimal manufacturing schedule minimizing the overall processing time is obtained. The manufacturing schedule defines the moments of moldings delivery thus minimizing storage costs and provides mounting due-time satisfaction. The proposed optimization approach is based on real manufacturing plant problem. Different processing schedules variants for different technological restrictions were defined and implemented in the practice of Bulgarian company RAIS Ltd. The proposed approach could be generalized for other job shop scheduling problems for different applications.

Keywords: Optimal manufacturing scheduling, linear programming, metalworking machines production, dependant details processing.

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4995 Feature Analysis of Predictive Maintenance Models

Authors: Zhaoan Wang

Abstract:

Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: Automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation.

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4994 Eye-Gesture Analysis for Driver Hazard Awareness

Authors: Siti Nor Hafizah binti Mohd Zaid, Mohamed Abdel-Maguid, Abdel-Hamid Soliman

Abstract:

Because road traffic accidents are a major source of death worldwide, attempts have been made to create Advanced Driver Assistance Systems (ADAS) able to detect vehicle, driver and environmental conditions that are cues for possible potential accidents. This paper presents continued work on a novel Nonintrusive Intelligent Driver Assistance and Safety System (Ni-DASS) for assessing driver attention and hazard awareness. It uses two onboard CCD cameras – one observing the road and the other observing the driver-s face. The windscreen is divided into cells and analysis of the driver-s eye-gaze patterns allows Ni-DASS to determine the windscreen cell the driver is focusing on using eye-gesture templates. Intersecting the driver-s field of view through the observed windscreen cell with subsections of the camera-s field of view containing a potential hazard allows Ni-DASS to estimate the probability that the driver has actually observed the hazard. Results have shown that the proposed technique is an accurate enough measure of driver observation to be useful in ADAS systems.

Keywords: Advanced Driver Assistance Systems (ADAS), Driver Hazard Awareness, Driver Vigilance, Eye Tracking

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4993 Teachers’ Perceptions of Their Principals’ Interpersonal Emotionally Intelligent Behaviours Affecting Their Job Satisfaction

Authors: Prakash Singh

Abstract:

For schools to be desirable places in which to work, it is necessary for principals to recognise their teachers’ emotions, and be sensitive to their needs. This necessitates that principals are capable to correctly identify their emotionally intelligent behaviours (EIBs) they need to use in order to be successful leaders. They also need to have knowledge of their emotional intelligence and be able to identify the factors and situations that evoke emotion at an interpersonal level. If a principal is able to do this, then the control and understanding of emotions and behaviours of oneself and others could improve vastly. This study focuses on the interpersonal EIBS of principals affecting the job satisfaction of teachers. The correlation coefficients in this quantitative study strongly indicate that there is a statistical significance between the respondents’ level of job satisfaction, the rating of their principals’ EIBs and how they believe their principals’ EIBs will affect their sense of job satisfaction. It can be concluded from the data obtained in this study that there is a significant correlation between the sense of job satisfaction of teachers and their principals’ interpersonal EIBs. This means that the more satisfied a teacher is at school, the more appropriate and meaningful a principal’s EIBs will be. Conversely, the more dissatisfied a teacher is at school the less appropriate and less meaningful a principal’s interpersonal EIBs will be. This implies that the leaders’ EIBs can be construed as one of the major factors affecting the job satisfaction of employees.

Keywords: Emotional intelligence, teachers’ emotions, teachers’ job satisfaction, principals’ emotionally intelligent behaviours.

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4992 Web-Based Architecture of a System for Design Assessment of Night Vision Devices

Authors: Daniela I. Borissova, Ivan C. Mustakerov, Evgeni D. Bantutov

Abstract:

Nowadays the devices of night vision are widely used both for military and civil applications. The variety of night vision applications require a variety of the night vision devices designs. A web-based architecture of a software system for design assessment before producing of night vision devices is developed. The proposed architecture of the web-based system is based on the application of a mathematical model for designing of night vision devices. An algorithm with two components – for iterative design and for intelligent design is developed and integrated into system architecture. The iterative component suggests compatible modules combinations to choose from. The intelligent component provides compatible combinations of modules  satisfying given user requirements to device parameters. The proposed web-based architecture of a system for design assessment of night vision devices is tested via a prototype of the system. The testing showed the applicability of both iterative and intelligent components of algorithm. 

Keywords: Night vision devices, design modeling, software architecture, web-based system.

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4991 The Data Mining usage in Production System Management

Authors: Pavel Vazan, Pavol Tanuska, Michal Kebisek

Abstract:

The paper gives the pilot results of the project that is oriented on the use of data mining techniques and knowledge discoveries from production systems through them. They have been used in the management of these systems. The simulation models of manufacturing systems have been developed to obtain the necessary data about production. The authors have developed the way of storing data obtained from the simulation models in the data warehouse. Data mining model has been created by using specific methods and selected techniques for defined problems of production system management. The new knowledge has been applied to production management system. Gained knowledge has been tested on simulation models of the production system. An important benefit of the project has been proposal of the new methodology. This methodology is focused on data mining from the databases that store operational data about the production process.

Keywords: data mining, data warehousing, management of production system, simulation

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4990 A WIP Control Based On an Intelligent Controller

Authors: Chih-Hui Chiu, Chun-Hsien Lin

Abstract:

In this study, a robust intelligent backstepping tracking control (RIBTC) system combined with adaptive output recurrent cerebellar model articulation control (AORCMAC) and H∞ control technique is proposed for wheeled inverted pendulums (WIPs) real-time control with exact system dynamics unknown. Moreover, a robust H∞ controller is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. The experimental results indicate that the WIPs can stand upright stably when using the proposed RIBTC.

Keywords: Wheeled inverted pendulum, backsteppingtracking control, H∞ control, adaptive output recurrentcerebellar model articulation control.

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4989 Moving Data Mining Tools toward a Business Intelligence System

Authors: Nittaya Kerdprasop, Kittisak Kerdprasop

Abstract:

Data mining (DM) is the process of finding and extracting frequent patterns that can describe the data, or predict unknown or future values. These goals are achieved by using various learning algorithms. Each algorithm may produce a mining result completely different from the others. Some algorithms may find millions of patterns. It is thus the difficult job for data analysts to select appropriate models and interpret the discovered knowledge. In this paper, we describe a framework of an intelligent and complete data mining system called SUT-Miner. Our system is comprised of a full complement of major DM algorithms, pre-DM and post-DM functionalities. It is the post-DM packages that ease the DM deployment for business intelligence applications.

Keywords: Business intelligence, data mining, functionalprogramming, intelligent system.

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4988 Laser Data Based Automatic Generation of Lane-Level Road Map for Intelligent Vehicles

Authors: Zehai Yu, Hui Zhu, Linglong Lin, Huawei Liang, Biao Yu, Weixin Huang

Abstract:

With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm.

Keywords: Curve fitting, lane-level road map, line recognition, multi-thresholding, two-stage clustering.

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4987 Intelligent Transport System: Classification of Traffic Signs Using Deep Neural Networks in Real Time

Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

Abstract:

Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: Multiclass classification, convolution neural network, OpenCV, Data Augmentation.

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4986 Design and Implementation of an Intelligent System for Detection of Hazardous Gases using PbPc Sensor Array

Authors: Mahmoud Z. Iskandarani, Nidal F. Shilbayeh

Abstract:

The voltage/current characteristics and the effect of NO2 gas on the electrical conductivity of a PbPc gas sensor array is investigated. The gas sensor is manufactured using vacuum deposition of gold electrodes on sapphire substrate with the leadphathalocyanine vacuum sublimed on the top of the gold electrodes. Two versions of the PbPc gas sensor array are investigated. The tested types differ in the gap sizes between the deposited gold electrodes. The sensors are tested at different temperatures to account for conductivity changes as the molecular adsorption/desorption rate is affected by heat. The obtained results found to be encouraging as the sensors shoed stability and sensitivity towards low concentration of applied NO2 gas.

Keywords: Intelligent System, PbPc, Gas Sensor, Hardware, Software, Neural.

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4985 Improved Algorithms for Construction of Interface Agent Interaction Model

Authors: Huynh Quyet Thang, Le Hai Quan

Abstract:

Interaction Model plays an important role in Modelbased Intelligent Interface Agent Architecture for developing Intelligent User Interface. In this paper we are presenting some improvements in the algorithms for development interaction model of interface agent including: the action segmentation algorithm, the action pair selection algorithm, the final action pair selection algorithm, the interaction graph construction algorithm and the probability calculation algorithm. The analysis of the algorithms also presented. At the end of this paper, we introduce an experimental program called “Personal Transfer System".

Keywords: interface agent, interaction model, user model.

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4984 Highly Accurate Tennis Ball Throwing Machine with Intelligent Control

Authors: Ferenc Kovács, Gábor Hosszú

Abstract:

The paper presents an advanced control system for tennis ball throwing machines to improve their accuracy according to the ball impact points. A further advantage of the system is the much easier calibration process involving the intelligent solution of the automatic adjustment of the stroking parameters according to the ball elasticity, the self-calibration, the use of the safety margin at very flat strokes and the possibility to placing the machine to any position of the half court. The system applies mathematical methods to determine the exact ball trajectories and special approximating processes to access all points on the aimed half court.

Keywords: Control system, robot programming, robot control, sports equipment, throwing machine.

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4983 Fuzzy Hierarchical Clustering Applied for Quality Estimation in Manufacturing System

Authors: Y. Q. Lv, C.K.M. Lee

Abstract:

This paper develops a quality estimation method with the application of fuzzy hierarchical clustering. Quality estimation is essential to quality control and quality improvement as a precise estimation can promote a right decision-making in order to help better quality control. Normally the quality of finished products in manufacturing system can be differentiated by quality standards. In the real life situation, the collected data may be vague which is not easy to be classified and they are usually represented in term of fuzzy number. To estimate the quality of product presented by fuzzy number is not easy. In this research, the trapezoidal fuzzy numbers are collected in manufacturing process and classify the collected data into different clusters so as to get the estimation. Since normal hierarchical clustering methods can only be applied for real numbers, fuzzy hierarchical clustering is selected to handle this problem based on quality standards.

Keywords: Quality Estimation, Fuzzy Quality Mean, Fuzzy Hierarchical Clustering, Fuzzy Number, Manufacturing system

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4982 Automatic Motion Trajectory Analysis for Dual Human Interaction Using Video Sequences

Authors: Yuan-Hsiang Chang, Pin-Chi Lin, Li-Der Jeng

Abstract:

Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.). 

Keywords: Motion detection, motion tracking, trajectory analysis, video surveillance.

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4981 Machine Learning Methods for Environmental Monitoring and Flood Protection

Authors: Alexander L. Pyayt, Ilya I. Mokhov, Bernhard Lang, Valeria V. Krzhizhanovskaya, Robert J. Meijer

Abstract:

More and more natural disasters are happening every year: floods, earthquakes, volcanic eruptions, etc. In order to reduce the risk of possible damages, governments all around the world are investing into development of Early Warning Systems (EWS) for environmental applications. The most important task of the EWS is identification of the onset of critical situations affecting environment and population, early enough to inform the authorities and general public. This paper describes an approach for monitoring of flood protections systems based on machine learning methods. An Artificial Intelligence (AI) component has been developed for detection of abnormal dike behaviour. The AI module has been integrated into an EWS platform of the UrbanFlood project (EU Seventh Framework Programme) and validated on real-time measurements from the sensors installed in a dike.

Keywords: Early Warning System, intelligent environmentalmonitoring, machine learning, flood protection.

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4980 Integrating Agents and Computational Intelligence Techniques in E-learning Environments

Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

Abstract:

In this contribution a newly developed elearning environment is presented, which incorporates Intelligent Agents and Computational Intelligence Techniques. The new e-learning environment is constituted by three parts, the E-learning platform Front-End, the Student Questioner Reasoning and the Student Model Agent. These parts are distributed geographically in dispersed computer servers, with main focus on the design and development of these subsystems through the use of new and emerging technologies. These parts are interconnected in an interoperable way, using web services for the integration of the subsystems, in order to enhance the user modelling procedure and achieve the goals of the learning process.

Keywords: E-learning environments, intelligent agents, user modeling, Bayesian Networks, computational intelligence.

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4979 Eye Gesture Analysis with Head Movement for Advanced Driver Assistance Systems

Authors: Siti Nor Hafizah bt Mohd Zaid, Mohamed Abdel Maguid, Abdel Hamid Soliman

Abstract:

Road traffic accidents are a major cause of death worldwide. In an attempt to reduce accidents, some research efforts have focused on creating Advanced Driver Assistance Systems (ADAS) able to detect vehicle, driver and environmental conditions and to use this information to identify cues for potential accidents. This paper presents continued work on a novel Non-intrusive Intelligent Driver Assistance and Safety System (Ni-DASS) for assessing driver point of regard within vehicles. It uses an on-board CCD camera to observe the driver-s face. A template matching approach is used to compare the driver-s eye-gaze pattern with a set of eye-gesture templates of the driver looking at different focal points within the vehicle. The windscreen is divided into cells and comparison of the driver-s eye-gaze pattern with templates of a driver-s eyes looking at each cell is used to determine the driver-s point of regard on the windscreen. Results indicate that the proposed technique could be useful in situations where low resolution estimates of driver point of regard are adequate. For instance, To allow ADAS systems to alert the driver if he/she has positively failed to observe a hazard.

Keywords: Head rotation, Eye-gestures, Windscreen, Template matching.

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4978 A Fast Sign Localization System Using Discriminative Color Invariant Segmentation

Authors: G.P. Nguyen, H.J. Andersen

Abstract:

Building intelligent traffic guide systems has been an interesting subject recently. A good system should be able to observe all important visual information to be able to analyze the context of the scene. To do so, signs in general, and traffic signs in particular, are usually taken into account as they contain rich information to these systems. Therefore, many researchers have put an effort on sign recognition field. Sign localization or sign detection is the most important step in the sign recognition process. This step filters out non informative area in the scene, and locates candidates in later steps. In this paper, we apply a new approach in detecting sign locations using a new color invariant model. Experiments are carried out with different datasets introduced in other works where authors claimed the difficulty in detecting signs under unfavorable imaging conditions. Our method is simple, fast and most importantly it gives a high detection rate in locating signs.

Keywords: Sign localization, color-based segmentation.

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4977 The AI Application and Talent Demand of Taiwan High-Tech Manufacturing Industry

Authors: Shi-Yu Lu, Chung-Han Yeh, Li-Ping Chen, Yu-Cheng Chang

Abstract:

This paper uses both quantitative and qualitative approaches to survey the current status of AI-related applications and the structure of key AI jobs in Taiwan's high-tech manufacturing industry, as well as the demand for professional AI talents, skills, and training. The result shows that AI applications and talent demand vary from different industries in many aspects, including technologies used, talent structure, and training methods. This paper serves as a reference for the government to establish appropriate talent training programs, and to reduce the demand gap for professional AI talents in Taiwan manufacturers.

Keywords: Artificial intelligence, manufacturing, talent, training.

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4976 Exchange Rate Volatility, Its Determinants and Effects on the Manufacturing Sector in Nigeria

Authors: Chimaobi V. Okolo, Onyinye S. Ugwuanyi, Kenneth A. Okpala

Abstract:

This study evaluated the effect of exchange rate volatility on the manufacturing sector of Nigeria. The flow and stock market theories of exchange rate determination was adopted considering macroeconomic determinants such as balance of trade, trade openness, and net international investment. Furthermore, the influence of changes in parallel exchange rate, official exchange rate and real effective exchange rate was modeled on the manufacturing sector output. Vector autoregression techniques and vector error correction mechanism were adopted to explore the macroeconomic determinants of exchange rate fluctuation in Nigeria and to examine the influence of exchange rate volatility on the manufacturing sector output in Nigeria. The exchange rate showed an unstable and volatile movement in Nigeria. Official exchange rate significantly impacted on the manufacturing sector of Nigeria and shock to previous manufacturing sector output caused 60.76% of the fluctuation in the manufacturing sector output in Nigeria. Trade balance, trade openness and net international investments did not significantly determine exchange rate in Nigeria. However, own shock accounted for about 95% of the variation of exchange rate fluctuation in the short-run and long-run. Among other macroeconomic variables, net international investment accounted for about 2.85% variation of the real effective exchange rate fluctuation in the short-run and in the long-run. Monetary authorities should maintain stability of the exchange rates through proper management so as to encourage local production and government should formulate and implement policies that will develop other sectors of the economy as this will widen the country’s revenue base, reduce our over reliance on oil sector for our foreign exchange earnings and in turn reduce the shocks on our domestic economy.

Keywords: Exchange rate volatility, exchange rate determinants, manufacturing sector, official exchange rate, parallel exchange rate, real effective exchange rate.

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4975 Introducing an Image Processing Base Idea for Outdoor Children Caring

Authors: Hooman Jafarabadi

Abstract:

In this paper application of artificial intelligence for baby and children caring is studied. Then a new idea for injury prevention and safety announcement is presented by using digital image processing. The paper presents the structure of the proposed system. The system determines the possibility of the dangers for children and babies in yards, gardens and swimming pools or etc. In the presented idea, multi camera System is used and receiver videos are processed to find the hazardous areas then the entrance of children and babies in the determined hazardous areas are analyzed. In this condition the system does the programmed action capture, produce alarm or tone or send message.

Keywords: Baby and children Care and Nursing, Intelligent Control Systems for Nursing, Electronic Care and Nursing, Dangers and safety for children and babies, Motion detection, Expert danger alarm systems.

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4974 Computational Intelligence Techniques and Agents- Technology in E-learning Environments

Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

Abstract:

In this contribution a newly developed e-learning environment is presented, which incorporates Intelligent Agents and Computational Intelligence Techniques. The new e-learning environment is constituted by three parts, the E-learning platform Front-End, the Student Questioner Reasoning and the Student Model Agent. These parts are distributed geographically in dispersed computer servers, with main focus on the design and development of these subsystems through the use of new and emerging technologies. These parts are interconnected in an interoperable way, using web services for the integration of the subsystems, in order to enhance the user modelling procedure and achieve the goals of the learning process.

Keywords: Computational Intelligence, E-learning Environments, Intelligent Agents, User Modelling, Bayesian Networks.

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4973 An Agent Oriented Approach to Operational Profile Management

Authors: Sunitha Ramanujam, Hany El Yamany, Miriam A. M. Capretz

Abstract:

Software reliability, defined as the probability of a software system or application functioning without failure or errors over a defined period of time, has been an important area of research for over three decades. Several research efforts aimed at developing models to improve reliability are currently underway. One of the most popular approaches to software reliability adopted by some of these research efforts involves the use of operational profiles to predict how software applications will be used. Operational profiles are a quantification of usage patterns for a software application. The research presented in this paper investigates an innovative multiagent framework for automatic creation and management of operational profiles for generic distributed systems after their release into the market. The architecture of the proposed Operational Profile MAS (Multi-Agent System) is presented along with detailed descriptions of the various models arrived at following the analysis and design phases of the proposed system. The operational profile in this paper is extended to comprise seven different profiles. Further, the criticality of operations is defined using a new composed metrics in order to organize the testing process as well as to decrease the time and cost involved in this process. A prototype implementation of the proposed MAS is included as proof-of-concept and the framework is considered as a step towards making distributed systems intelligent and self-managing.

Keywords: Software reliability, Software testing, Metrics, Distributed systems, Multi-agent systems

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4972 Tool Path Generation and Manufacturing Process for Blades of a Compressor Rotor

Authors: C. Tung, P.-L. Tso

Abstract:

This paper presents a complete procedure for tool path planning and blade machining in 5-axis manufacturing. The actual cutting contact and cutter locations can be determined by lead and tilt angles. The tool path generation is implemented by piecewise curved approximation and chordal deviation detection. An application about drive surface method promotes flexibility of tool control and stability of machine motion. A real manufacturing process is proposed to separate the operation into three regions with five stages and to modify the local tool orientation with an interactive algorithm.

Keywords: 5-axis machining, tool orientation, lead and tilt angles, tool path generation.

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4971 QoS Improvement Using Intelligent Algorithm under Dynamic Tropical Weather for Earth-Space Satellite Applications

Authors: Joseph S. Ojo, Vincent A. Akpan, Oladayo G. Ajileye, Olalekan L, Ojo

Abstract:

In this paper, the intelligent algorithm (IA) that is capable of adapting to dynamical tropical weather conditions is proposed based on fuzzy logic techniques. The IA effectively interacts with the quality of service (QoS) criteria irrespective of the dynamic tropical weather to achieve improvement in the satellite links. To achieve this, an adaptive network-based fuzzy inference system (ANFIS) has been adopted. The algorithm is capable of interacting with the weather fluctuation to generate appropriate improvement to the satellite QoS for efficient services to the customers. 5-year (2012-2016) rainfall rate of one-minute integration time series data has been used to derive fading based on ITU-R P. 618-12 propagation models. The data are obtained from the measurement undertaken by the Communication Research Group (CRG), Physics Department, Federal University of Technology, Akure, Nigeria. The rain attenuation and signal-to-noise ratio (SNR) were derived for frequency between Ku and V-band and propagation angle with respect to different transmitting power. The simulated results show a substantial reduction in SNR especially for application in the area of digital video broadcast-second generation coding modulation satellite networks.

Keywords: Fuzzy logic, intelligent algorithm, Nigeria, QoS, satellite applications, tropical weather.

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4970 A Business Intelligence System Design Based on ASP Platform

Authors: Fengchi Shen, Rongtao Ding

Abstract:

The Informational Infrastructures of small and medium-sized manufacturing enterprises are relatively poor, there are serious shortages of capitals which can be invested in informatization construction, computer hardware and software resources, and human resources. To address the informatization issue in small and medium-sized manufacturing enterprises, and enable them to the application of advanced management thinking and enhance their competitiveness, the paper establish a manufacturing-oriented small and medium-sized enterprises informatization platform based on the ASP business intelligence technology, which effectively improves the scientificity of enterprises decision and management informatization.

Keywords: ASP, business intelligence, data warehouse.

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4969 A Paradigm Shift towards Personalized and Scalable Product Development and Lifecycle Management Systems in the Aerospace Industry

Authors: David E. Culler, Noah D. Anderson

Abstract:

Integrated systems for product design, manufacturing, and lifecycle management are difficult to implement and customize. Commercial software vendors, including CAD/CAM and third party PDM/PLM developers, create user interfaces and functionality that allow their products to be applied across many industries. The result is that systems become overloaded with functionality, difficult to navigate, and use terminology that is unfamiliar to engineers and production personnel. For example, manufacturers of automotive, aeronautical, electronics, and household products use similar but distinct methods and processes. Furthermore, each company tends to have their own preferred tools and programs for controlling work and information flow and that connect design, planning, and manufacturing processes to business applications. This paper presents a methodology and a case study that addresses these issues and suggests that in the future more companies will develop personalized applications that fit to the natural way that their business operates. A functioning system has been implemented at a highly competitive U.S. aerospace tooling and component supplier that works with many prominent airline manufacturers around the world including The Boeing Company, Airbus, Embraer, and Bombardier Aerospace. During the last three years, the program has produced significant benefits such as the automatic creation and management of component and assembly designs (parametric models and drawings), the extensive use of lightweight 3D data, and changes to the way projects are executed from beginning to end. CATIA (CAD/CAE/CAM) and a variety of programs developed in C#, VB.Net, HTML, and SQL make up the current system. The web-based platform is facilitating collaborative work across multiple sites around the world and improving communications with customers and suppliers. This work demonstrates that the creative use of Application Programming Interface (API) utilities, libraries, and methods is a key to automating many time-consuming tasks and linking applications together.

Keywords: CAD/CAM, CAPP, PDM, PLM, Scalable Systems.

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