A Web-Based System for Mapping Features into ISO 14649-Compliant Machining Workingsteps

The rapid development of manufacturing and information systems has caused significant changes in manufacturing environments in recent decades. Mass production has given way to flexible manufacturing systems, in which an important characteristic is customized or "on demand" production. In this scenario, the seamless and without gaps information flow becomes a key factor for success of enterprises. In this paper we present a framework to support the mapping of features into machining workingsteps compliant with the ISO 14649 standard (known as STEP-NC). The system determines how the features can be made with the available manufacturing resources. Examples of the mapping method are presented for features such as a pocket with a general surface.

Evolution, Tendencies and Impact of Standardization of Input/Output Platforms in Full Scale Simulators for Training Power Plant Operators

This article presents the evolution and technological changes implemented on the full scale simulators developed by the Simulation Department of the Instituto de Investigaciones Eléctricas1 (Mexican Electric Research Institute) and located at different training centers around the Mexican territory, and allows US to know the last updates, basically from the input/output view point, of the current simulators at some facilities of the electrical sector as well as the compatible industry of the electrical manufactures and industries such as Comision Federal de Electricidad (CFE*, The utility Mexican company). Tendencies of these developments and impact within the operators- scope are also presented.

An Advanced Approach Based on Artificial Neural Networks to Identify Environmental Bacteria

Environmental micro-organisms include a large number of taxa and some species that are generally considered nonpathogenic, but can represent a risk in certain conditions, especially for elderly people and immunocompromised individuals. Chemotaxonomic identification techniques are powerful tools for environmental micro-organisms, and cellular fatty acid methyl esters (FAME) content is a powerful fingerprinting identification technique. A system based on an unsupervised artificial neural network (ANN) was set up using the fatty acid profiles of standard bacterial strains, obtained by gas-chromatography, used as learning data. We analysed 45 certified strains belonging to Acinetobacter, Aeromonas, Alcaligenes, Aquaspirillum, Arthrobacter, Bacillus, Brevundimonas, Enterobacter, Flavobacterium, Micrococcus, Pseudomonas, Serratia, Shewanella and Vibrio genera. A set of 79 bacteria isolated from a drinking water line (AMGA, the major water supply system in Genoa) were used as an example for identification compared to standard MIDI method. The resulting ANN output map was found to be a very powerful tool to identify these fresh isolates.

Recent Developments in Speed Control System of Pipeline PIGs for Deepwater Pipeline Applications

Pipeline infrastructures normally represent high cost of investment and the pipeline must be free from risks that could cause environmental hazard and potential threats to personnel safety. Pipeline integrity such monitoring and management become very crucial to provide unimpeded transportation and avoiding unnecessary production deferment. Thus proper cleaning and inspection is the key to safe and reliable pipeline operation and plays an important role in pipeline integrity management program and has become a standard industry procedure. In view of this, understanding the motion (dynamic behavior), prediction and control of the PIG speed is important in executing pigging operation as it offers significant benefits, such as estimating PIG arrival time at receiving station, planning for suitable pigging operation, and improves efficiency of pigging tasks. The objective of this paper is to review recent developments in speed control system of pipeline PIGs. The review carried out would serve as an industrial application in a form of quick reference of recent developments in pipeline PIG speed control system, and further initiate others to add-in/update the list in the future leading to knowledge based data, and would attract active interest of others to share their view points.

Effects of the Sintering Process on Properties of Triaxial Electrical Porcelain from Ugandan Ceramic Minerals

Porcelain specimens were fired at 6C/min to 1250C (dwell time 0.5-3h) and cooled at 6C/min to room temperature. Additionally, three different slower firing/cooling cycles were tried. Sintering profile and effects on MOR, crystalline phase content and morphology were investigated using dilatometry, 4-point bending strength, XRD and FEG-SEM respectively. Industrial-sized specimens prepared using the promising cycle were tested basing on the ANSI standards. Increasing dwell time from 1h to 3h at peak temperature of 1250C resulted in neither a significant effect on the quartz and mullite content nor MOR. Reducing the firing/cooling rate to below 6C/min, for peak temperature of 1250C (dwell time of 1h) does not result in improvement of strength of porcelain. The industrial sized specimen exhibited flashover voltages of 20.3kV (dry) and 9.3kV (wet) respectively, transverse strength of 12.5kN and bulk density of 2.27g/cm3, which are satisfactory. There was however dye penetration during porosity test. KeywordsDwell time, Microstructure, Porcelain, Strength.

Self-Organizing Maps in Evolutionary Approachmeant for Dimensioning Routes to the Demand

We present a non standard Euclidean vehicle routing problem adding a level of clustering, and we revisit the use of self-organizing maps as a tool which naturally handles such problems. We present how they can be used as a main operator into an evolutionary algorithm to address two conflicting objectives of route length and distance from customers to bus stops minimization and to deal with capacity constraints. We apply the approach to a real-life case of combined clustering and vehicle routing for the transportation of the 780 employees of an enterprise. Basing upon a geographic information system we discuss the influence of road infrastructures on the solutions generated.

Working Motivation Factors Affecting Job Performance Effectiveness

The purpose of this paper was to study motivation factors affecting job performance effectiveness. This paper drew upon data collected from an Internal Audit Staffs of Internal Audit Line of Head Office of Krung Thai Public Company Limited. Statistics used included frequency, percentage, mean and standard deviation, t-test, and one-way ANOVA test. The finding revealed that the majority of the respondents were female of 46 years of age and over, married and live together, hold a bachelor degree, with an average monthly income over 70,001 Baht. The majority of respondents had over 15 years of work experience. They generally had high working motivation as well as high job performance effectiveness. The hypotheses testing disclosed that employees with different working status had different level of job performance effectiveness at a 0.01 level of significance. Working motivation factors had an effect on job performance in the same direction with high level. Individual working motivation included working completion, reorganization, working progression, working characteristic, opportunity, responsibility, management policy, supervision, relationship with their superior, relationship with co-worker, working position, working stability, safety, privacy, working conditions, and payment. All of these factors related to job performance effectiveness in the same direction with medium level.

RBF modeling of Incipient Motion of Plane Sand Bed Channels

To define or predict incipient motion in an alluvial channel, most of the investigators use a standard or modified form of Shields- diagram. Shields- diagram does give a process to determine the incipient motion parameters but an iterative one. To design properly (without iteration), one should have another equation for resistance. Absence of a universal resistance equation also magnifies the difficulties in defining the model. Neural network technique, which is particularly useful in modeling a complex processes, is presented as a tool complimentary to modeling incipient motion. Present work develops a neural network model employing the RBF network to predict the average velocity u and water depth y based on the experimental data on incipient condition. Based on the model, design curves have been presented for the field application.

A Preference-Based Multi-Agent Data Mining Framework for Social Network Service Users' Decision Making

Multi-Agent Systems (MAS) emerged in the pursuit to improve our standard of living, and hence can manifest complex human behaviors such as communication, decision making, negotiation and self-organization. The Social Network Services (SNSs) have attracted millions of users, many of whom have integrated these sites into their daily practices. The domains of MAS and SNS have lots of similarities such as architecture, features and functions. Exploring social network users- behavior through multiagent model is therefore our research focus, in order to generate more accurate and meaningful information to SNS users. An application of MAS is the e-Auction and e-Rental services of the Universiti Cyber AgenT(UniCAT), a Social Network for students in Universiti Tunku Abdul Rahman (UTAR), Kampar, Malaysia, built around the Belief- Desire-Intention (BDI) model. However, in spite of the various advantages of the BDI model, it has also been discovered to have some shortcomings. This paper therefore proposes a multi-agent framework utilizing a modified BDI model- Belief-Desire-Intention in Dynamic and Uncertain Situations (BDIDUS), using UniCAT system as a case study.

RDFGraph: New Data Modeling Tool for Semantic Web

The emerging Semantic Web has been attracted many researchers and developers. New applications have been developed on top of Semantic Web and many supporting tools introduced to improve its software development process. Metadata modeling is one of development process where supporting tools exists. The existing tools are lack of readability and easiness for a domain knowledge expert to graphically models a problem in semantic model. In this paper, a metadata modeling tool called RDFGraph is proposed. This tool is meant to solve those problems. RDFGraph is also designed to work with modern database management systems that support RDF and to improve the performance of the query execution process. The testing result shows that the rules used in RDFGraph follows the W3C standard and the graphical model produced in this tool is properly translated and correct.

Generalized Exploratory Model of Human Category Learning

One problem in evaluating recent computational models of human category learning is that there is no standardized method for systematically comparing the models' assumptions or hypotheses. In the present study, a flexible general model (called GECLE) is introduced that can be used as a framework to systematically manipulate and compare the effects and descriptive validities of a limited number of assumptions at a time. Two example simulation studies are presented to show how the GECLE framework can be useful in the field of human high-order cognition research.

A Distinguish Attack on COSvd Cipher

The COSvd Ciphers has been proposed by Filiol and others (2004). It is a strengthened version of COS stream cipher family denoted COSvd that has been adopted for at least one commercial standard. We propose a distinguish attack on this version, and prove that, it is distinguishable from a random stream. In the COSvd Cipher used one S-Box (10×8) on the final part of cipher. We focus on S-Box and use weakness this S-Box for distinguish attack. In addition, found a leak on HNLL that the sub s-boxes don-t select uniformly. We use this property for an Improve distinguish attack.

Emerging Wireless Standards - WiFi, ZigBee and WiMAX

The world of wireless telecommunications is rapidly evolving. Technologies under research and development promise to deliver more services to more users in less time. This paper presents the emerging technologies helping wireless systems grow from where we are today into our visions of the future. This paper will cover the applications and characteristics of emerging wireless technologies: Wireless Local Area Networks (WiFi-802.11n), Wireless Personal Area Networks (ZigBee) and Wireless Metropolitan Area Networks (WiMAX). The purpose of this paper is to explain the impending 802.11n standard and how it will enable WLANs to support emerging media-rich applications. The paper will also detail how 802.11n compares with existing WLAN standards and offer strategies for users considering higher-bandwidth alternatives. The emerging IEEE 802.15.4 (ZigBee) standard aims to provide low data rate wireless communications with high-precision ranging and localization, by employing UWB technologies for a low-power and low cost solution. WiMAX (Worldwide Interoperability for Microwave Access) is a standard for wireless data transmission covering a range similar to cellular phone towers. With high performance in both distance and throughput, WiMAX technology could be a boon to current Internet providers seeking to become the leader of next generation wireless Internet access. This paper also explores how these emerging technologies differ from one another.

Automatic Segmentation of Lung Areas in Magnetic Resonance Images

Segmenting the lungs in medical images is a challenging and important task for many applications. In particular, automatic segmentation of lung cavities from multiple magnetic resonance (MR) images is very useful for oncological applications such as radiotherapy treatment planning. However, distinguishing of the lung areas is not trivial due to largely changing lung shapes, low contrast and poorly defined boundaries. In this paper, we address lung segmentation problem from pulmonary magnetic resonance images and propose an automated method based on a robust regionaided geometric snake with a modified diffused region force into the standard geometric model definition. The extra region force gives the snake a global complementary view of the lung boundary information within the image which along with the local gradient flow, helps detect fuzzy boundaries. The proposed method has been successful in segmenting the lungs in every slice of 30 magnetic resonance images with 80 consecutive slices in each image. We present results by comparing our automatic method to manually segmented lung cavities provided by an expert radiologist and with those of previous works, showing encouraging results and high robustness of our approach.

Computing Entropy for Ortholog Detection

Biological sequences from different species are called or-thologs if they evolved from a sequence of a common ancestor species and they have the same biological function. Approximations of Kolmogorov complexity or entropy of biological sequences are already well known to be useful in extracting similarity information between such sequences -in the interest, for example, of ortholog detection. As is well known, the exact Kolmogorov complexity is not algorithmically computable. In prac-tice one can approximate it by computable compression methods. How-ever, such compression methods do not provide a good approximation to Kolmogorov complexity for short sequences. Herein is suggested a new ap-proach to overcome the problem that compression approximations may notwork well on short sequences. This approach is inspired by new, conditional computations of Kolmogorov entropy. A main contribution of the empir-ical work described shows the new set of entropy-based machine learning attributes provides good separation between positive (ortholog) and nega-tive (non-ortholog) data - better than with good, previously known alter-natives (which do not employ some means to handle short sequences well).Also empirically compared are the new entropy based attribute set and a number of other, more standard similarity attributes sets commonly used in genomic analysis. The various similarity attributes are evaluated by cross validation, through boosted decision tree induction C5.0, and by Receiver Operating Characteristic (ROC) analysis. The results point to the conclu-sion: the new, entropy based attribute set by itself is not the one giving the best prediction; however, it is the best attribute set for use in improving the other, standard attribute sets when conjoined with them.

A New Fast Intra Prediction Mode Decision Algorithm for H.264/AVC Encoders

The H.264/AVC video coding standard contains a number of advanced features. Ones of the new features introduced in this standard is the multiple intramode prediction. Its function exploits directional spatial correlation with adjacent block for intra prediction. With this new features, intra coding of H.264/AVC offers a considerably higher improvement in coding efficiency compared to other compression standard, but computational complexity is increased significantly when brut force rate distortion optimization (RDO) algorithm is used. In this paper, we propose a new fast intra prediction mode decision method for the complexity reduction of H.264 video coding. for luma intra prediction, the proposed method consists of two step: in the first step, we make the RDO for four mode of intra 4x4 block, based the distribution of RDO cost of those modes and the idea that the fort correlation with adjacent mode, we select the best mode of intra 4x4 block. In the second step, we based the fact that the dominating direction of a smaller block is similar to that of bigger block, the candidate modes of 8x8 blocks and 16x16 macroblocks are determined. So, in case of chroma intra prediction, the variance of the chroma pixel values is much smaller than that of luma ones, since our proposed uses only the mode DC. Experimental results show that the new fast intra mode decision algorithm increases the speed of intra coding significantly with negligible loss of PSNR.

Development of the Measurement Apparatus for the Effective Thermal Conductivity of Core Material

A measurement apparatus is designed and fabricated to measure the effective thermal conductivity (keff) of a VIP (vacuum insulation panel) core specimen under various vacuum states and external loads. The apparatus consists of part for measuring keff, and parts for controlling external load and vacuum condition. Uncertainty of the apparatus is validated by measuring the standard reference material and comparing with commercial devices with VIP samples. Assessed uncertainty is maximum 2.5 % in case of the standard reference material, 10 % in case of VIP samples. Using the apparatus, keff of glass paper under various vacuum levels is examined.

A Black-box Approach for Response Quality Evaluation of Conversational Agent Systems

The evaluation of conversational agents or chatterbots question answering systems is a major research area that needs much attention. Before the rise of domain-oriented conversational agents based on natural language understanding and reasoning, evaluation is never a problem as information retrieval-based metrics are readily available for use. However, when chatterbots began to become more domain specific, evaluation becomes a real issue. This is especially true when understanding and reasoning is required to cater for a wider variety of questions and at the same time to achieve high quality responses. This paper discusses the inappropriateness of the existing measures for response quality evaluation and the call for new standard measures and related considerations are brought forward. As a short-term solution for evaluating response quality of conversational agents, and to demonstrate the challenges in evaluating systems of different nature, this research proposes a blackbox approach using observation, classification scheme and a scoring mechanism to assess and rank three example systems, AnswerBus, START and AINI.

Agrowaste: Phytosterol from Durian Seed

Presence of phytosterol compound in Durian seed (Durio zibethinus) or known as King of fruits has been discovered from screening work using reagent test. Further analysis work has been carried out using mass spectrometer in order to support the priliminary finding. Isolation and purification of the major phytosterol has been carried out using an open column chromatography. The separation was monitored using thin layer chromatography (TLC). Major isolated compounds and purified phytosterol were identified using mass spectrometer and nuclear magnetic resonance (NMR). This novel finding could promote utilization of durian seeds as a functional ingredient in food products through production of standardized extract based on phytosterol content.

Removal of Boron from Waste Waters by Ion- Exchange in a Batch System

Boron minerals are very useful for various industrial activities, such as glass industry and detergent industry, due to its mechanical and chemical properties. During the production of boron compounds, many of these are introduced into the environment in the form of waste. Boron is also an important micro nutrient for the plants to vegetate but if it exists in high concentrations, it could have toxic effects. The maximum boron level in drinking water for human health is given as 0.3 mg/L in World Health Organization (WHO) standards. The toxic effects of boron should be noted especially for dry regions, thus, in recent years, increasing attention has been paid to remove the boron from waste waters. In this study, boron removal is implemented by ion exchange process using Amberlite IRA-743 resin. Amberlite IRA-743 resin is a boron specific resin and it belongs to the polymerizate sorbent group within the aminopolyol functional group. Batch studies were performed to investigate the effects of various experimental parameters, such as adsorbent dose, initial concentration and pH, on the removal of boron. It is found that, when the adsorbent dose increases removal of boron from the liquid phase increases. However, an increase in the initial concentration decreases the removal of boron. The effective pH values for removal of boron are determined between 8.5 and 9. Equilibrium isotherms were also analyzed by Langmuir and Freundlich isotherm models. The Langmuir isotherm is obeyed better than the Freundlich isotherm.