The Measurement of Endogenous Higher-Order Formative Composite Variables in PLS-SEM: An Empirical Application from CRM System Development

In recent methodological articles related to structural equation modeling (SEM), the question of how to measure endogenous formative variables has been raised as an urgent, unresolved issue. This research presents an empirical application from the CRM system development context to test a recently developed technique, which makes it possible to measure endogenous formative constructs in structural models. PLS path modeling is used to demonstrate the feasibility of measuring antecedent relationships at the formative indicator level, not the formative construct level. Empirical results show that this technique is a promising approach to measure antecedent relationships of formative constructs in SEM.

A Semi-Fragile Signature based Scheme for Ownership Identification and Color Image Authentication

In this paper, a novel scheme is proposed for ownership identification and authentication using color images by deploying Cryptography and Digital Watermarking as underlaying technologies. The former is used to compute the contents based hash and the latter to embed the watermark. The host image that will claim to be the rightful owner is first transformed from RGB to YST color space exclusively designed for watermarking based applications. Geometrically YS ÔèÑ T and T channel corresponds to the chrominance component of color image, therefore suitable for embedding the watermark. The T channel is divided into 4×4 nonoverlapping blocks. The size of block is important for enhanced localization, security and low computation. Each block along with ownership information is then deployed by SHA160, a one way hash function to compute the content based hash, which is always unique and resistant against birthday attack instead of using MD5 that may raise the condition i.e. H(m)=H(m'). The watermark payload varies from block to block and computed by the variance factorα . The quality of watermarked images is quite high both subjectively and objectively. Our scheme is blind, computationally fast and exactly locates the tampered region.

Application of Wireless Visual Sensor for Semi- Autonomous Mine Navigation System

The present paper represent the efforts undertaken for the development of an semi-automatic robot that may be used for various post-disaster rescue operation planning and their subsequent execution using one-way communication of video and data from the robot to the controller and controller to the robot respectively. Wireless communication has been used for the purpose so that the robot may access the unapproachable places easily without any difficulties. It is expected that the information obtained from the robot would be of definite help to the rescue team for better planning and execution of their operations.

Parametric Investigation of Diode and CO2 Laser in Direct Metal Deposition of H13 Tool Steel on Copper Substrate

In the present investigation, H13 tool steel has been deposited on copper alloy substrate using both CO2 and diode laser. A detailed parametric analysis has been carried out in order to find out optimum processing zone for coating defect free H13 tool steel on copper alloy substrate. Followed by parametric optimization, the microstructure and microhardness of the deposited clads have been evaluated. SEM micrographs revealed dendritic microstructure in both clads. However, the microhardness of CO2 laser deposited clad was much higher compared to diode laser deposited clad.

Using a Semantic Self-Organising Web Page-Ranking Mechanism for Public Administration and Education

In the proposed method for Web page-ranking, a novel theoretic model is introduced and tested by examples of order relationships among IP addresses. Ranking is induced using a convexity feature, which is learned according to these examples using a self-organizing procedure. We consider the problem of selforganizing learning from IP data to be represented by a semi-random convex polygon procedure, in which the vertices correspond to IP addresses. Based on recent developments in our regularization theory for convex polygons and corresponding Euclidean distance based methods for classification, we develop an algorithmic framework for learning ranking functions based on a Computational Geometric Theory. We show that our algorithm is generic, and present experimental results explaining the potential of our approach. In addition, we explain the generality of our approach by showing its possible use as a visualization tool for data obtained from diverse domains, such as Public Administration and Education.

The Influence of Thermic Plastic Films on Vegetative and Reproductive Growth of Iceberg Lettuce ‘Dublin’

Photoselective plastic films with thermic properties are now available so that greenhouses clad with such plastics exhibit a higher degree of “Greenhouse Effect” with a consequent increase in night time temperature. In this study, we investigate the potential benefits of a range of thermic plastic films used as greenhouse cover materials on the vegetative and reproductive growth and development of Iceberg lettuce (Lactuca sativa L). Transplants were grown under thermic films and destructively harvested 4, 5, and 6 weeks after transplanting. Thermic films can increase night temperatures up to 2 ⁰C reducing the wide fluctuation in greenhouse temperature during winter compared to the standard commercial film and consequently increased the yield (leaf number, fresh weight, and dry weight) of lettuce plants. Lettuce plants grown under Clear film respond to cold stress by the accumulation of secondary products (phenolics, and flavonoids).

New Methods for E-Commerce Databases Designing in Semantic Web Systems (Modern Systems)

The purpose of this paper is to study Database Models to use them efficiently in E-commerce websites. In this paper we are going to find a method which can save and retrieve information in Ecommerce websites. Thus, semantic web applications can work with, and we are also going to study different technologies of E-commerce databases and we know that one of the most important deficits in semantic web is the shortage of semantic data, since most of the information is still stored in relational databases, we present an approach to map legacy data stored in relational databases into the Semantic Web using virtually any modern RDF query language, as long as it is closed within RDF. To achieve this goal we study XML structures for relational data bases of old websites and eventually we will come up one level over XML and look for a map from relational model (RDM) to RDF. Noting that a large number of semantic webs get advantage of relational model, opening the ways which can be converted to XML and RDF in modern systems (semantic web) is important.

An Empirical Model to Calculate the Threads Stripping of a Bolt Installed in a Tapped Part

To determine the length of engagement threads of a bolt installed in a tapped part in order to avoid the threads stripping remains a very current problem in the design of the thread assemblies. It does not exist a calculation method formalized for the cases where the bolt is screwed directly in a ductile material. In this article, we study the behavior of the threads stripping of a loaded assembly by using a modelling by finite elements and a rupture criterion by damage. This modelling enables us to study the different parameters likely to influence the behavior of this bolted connection. We study in particular, the influence of couple of materials constituting the connection, of the bolt-s diameter and the geometrical characteristics of the tapped part, like the external diameter and the length of engagement threads. We established an experiments design to know the most significant parameters. That enables us to propose a simple expression making possible to calculate the resistance of the threads whatever the metallic materials of the bolt and the tapped part. We carried out stripping tests in order to validate our model. The estimated results are very close to those obtained by the tests.

Computer Generated Hologram for SemiFragile Watermarking with Encrypted Images

The protection of the contents of digital products is referred to as content authentication. In some applications, to be able to authenticate a digital product could be extremely essential. For example, if a digital product is used as a piece of evidence in the court, its integrity could mean life or death of the accused. Generally, the problem of content authentication can be solved using semifragile digital watermarking techniques. Recently many authors have proposed Computer Generated Hologram Watermarking (CGHWatermarking) techniques. Starting from these studies, in this paper a semi-fragile Computer Generated Hologram coding technique is proposed, which is able to detect malicious tampering while tolerating some incidental distortions. The proposed technique uses as watermark an encrypted image, and it is well suitable for digital image authentication.

Innovative Teaching in Systems Analysis and Design - an Action Research Project

Systems Analysis and Design is a key subject in Information Technology courses, but students do not find it easy to cope with, since it is not “precise" like programming and not exact like Mathematics. It is a subject working with many concepts, modeling ideas into visual representations and then translating the pictures into a real life system. To complicate matters users who are not necessarily familiar with computers need to give their inputs to ensure that they get the system the need. Systems Analysis and Design also covers two fields, namely Analysis, focusing on the analysis of the existing system and Design, focusing on the design of the new system. To be able to test the analysis and design of a system, it is necessary to develop a system or at least a prototype of the system to test the validity of the analysis and design. The skills necessary in each aspect differs vastly. Project Management Skills, Database Knowledge and Object Oriented Principles are all necessary. In the context of a developing country where students enter tertiary education underprepared and the digital divide is alive and well, students need to be motivated to learn the necessary skills, get an opportunity to test it in a “live" but protected environment – within the framework of a university. The purpose of this article is to improve the learning experience in Systems Analysis and Design through reviewing the underlying teaching principles used, the teaching tools implemented, the observations made and the reflections that will influence future developments in Systems Analysis and Design. Action research principles allows the focus to be on a few problematic aspects during a particular semester.

Functionalization and Characterization of Carbon Nanotubes/ Polypropylene Nanocomposite

Chemical and physical functionalization of multiwalled carbon nanotubes (MWCNT) has been commonly practiced to achieve better dispersion of carbon nanotubes (CNTs) in polymer matrix. This work describes various functionalization methods (acidtreatment, non-ionic surfactant treatment with TritonX-100), fabrication of MWCNT/PP nanocomposites via melt blending and characterization of mechanical properties. Microscopy analysis (FESEM, TEM, XPS) showed effective purification of MWCNTs under acid treatment, and better dispersion under both chemical and physical functionalization techniques combined, in their respective order. Tensile tests showed increase in tensile strength for the nanocomposites that contain MWCNTs up to 2 wt%. A decrease in tensile strength was seen in samples that contain 4 wt% of MWCNTs for both raw and Triton X-100 functionalized, signifying MWCNT degradation/rebundling at composition with higher content of MWCNTs. For the acid-treated MWCNTs, however, the tensile results showed slight improvement even at 4wt%, indicating effective dispersion of MWCNTs.

ANN-Based Classification of Indirect Immuno Fluorescence Images

In this paper we address the issue of classifying the fluorescent intensity of a sample in Indirect Immuno-Fluorescence (IIF). Since IIF is a subjective, semi-quantitative test in its very nature, we discuss a strategy to reliably label the image data set by using the diagnoses performed by different physicians. Then, we discuss image pre-processing, feature extraction and selection. Finally, we propose two ANN-based classifiers that can separate intrinsically dubious samples and whose error tolerance can be flexibly set. Measured performance shows error rates less than 1%, which candidates the method to be used in daily medical practice either to perform pre-selection of cases to be examined, or to act as a second reader.

Application of Formal Methods for Designing a Separation Kernel for Embedded Systems

A separation-kernel-based operating system (OS) has been designed for use in secure embedded systems by applying formal methods to the design of the separation-kernel part. The separation kernel is a small OS kernel that provides an abstract distributed environment on a single CPU. The design of the separation kernel was verified using two formal methods, the B method and the Spin model checker. A newly designed semi-formal method, the extended state transition method, was also applied. An OS comprising the separation-kernel part and additional OS services on top of the separation kernel was prototyped on the Intel IA-32 architecture. Developing and testing of a prototype embedded application, a point-of-sale application, on the prototype OS demonstrated that the proposed architecture and the use of formal methods to design its kernel part are effective for achieving a secure embedded system having a high-assurance separation kernel.

UD Covariance Factorization for Unscented Kalman Filter using Sequential Measurements Update

Extended Kalman Filter (EKF) is probably the most widely used estimation algorithm for nonlinear systems. However, not only it has difficulties arising from linearization but also many times it becomes numerically unstable because of computer round off errors that occur in the process of its implementation. To overcome linearization limitations, the unscented transformation (UT) was developed as a method to propagate mean and covariance information through nonlinear transformations. Kalman filter that uses UT for calculation of the first two statistical moments is called Unscented Kalman Filter (UKF). Square-root form of UKF (SRUKF) developed by Rudolph van der Merwe and Eric Wan to achieve numerical stability and guarantee positive semi-definiteness of the Kalman filter covariances. This paper develops another implementation of SR-UKF for sequential update measurement equation, and also derives a new UD covariance factorization filter for the implementation of UKF. This filter is equivalent to UKF but is computationally more efficient.

Ontology Population via NLP Techniques in Risk Management

In this paper we propose an NLP-based method for Ontology Population from texts and apply it to semi automatic instantiate a Generic Knowledge Base (Generic Domain Ontology) in the risk management domain. The approach is semi-automatic and uses a domain expert intervention for validation. The proposed approach relies on a set of Instances Recognition Rules based on syntactic structures, and on the predicative power of verbs in the instantiation process. It is not domain dependent since it heavily relies on linguistic knowledge. A description of an experiment performed on a part of the ontology of the PRIMA1 project (supported by the European community) is given. A first validation of the method is done by populating this ontology with Chemical Fact Sheets from Environmental Protection Agency2. The results of this experiment complete the paper and support the hypothesis that relying on the predicative power of verbs in the instantiation process improves the performance.

Investigation of Drying Kinetics of Viscose Yarn Bobbins

This study is concerned with the investigation of the suitability of several empirical and semi-empirical drying models available in the literature to define drying behavior of viscose yarn bobbins. For this purpose, firstly, experimental drying behaviour of viscose bobbins was determined on an experimental dryer setup which was designed and manufactured based on hot-air bobbin dryers used in textile industry. Afterwards, drying models considered were fitted to the experimentally obtained moisture ratios. Drying parameters were drying temperature and bobbin diameter. The fit was performed by selecting the values for constants in the models in such a way that these values make the sum of the squared differences between the experimental and the model results for moisture ratio minimum. Suitability of fitting was specified as comparing the correlation coefficient, standard error and mean square deviation. The results show that the most appropriate model in describing the drying curves of viscose bobbins is the Page model.

Evaluation and Preparation of Crystal Modifications of Artesunate: In vivo Studies

Five crystal modifications of water insoluble artesunate were generated by recrystallizing it from various solvents with improved physicochemical properties. These generated crystal forms were characterized to select the most potent and soluble form. SEM of all the forms showed changes in external shape leading them to be different morphologically. DSC thermograms of Form III and Form V showed broad endotherm peaks at 83.04oC and 76.96oC prior to melting fusion of drug respectively. Calculated weight loss in TGA revealed that Form III and Form V are methanol and acetone solvates respectively. However, few additional peaks were appeared in XRPD pattern in these two solvate forms. All forms exhibit exothermic behavior in buffer and two solvates display maximum ease of molecular release from the lattice. Methanol and acetone solvates were found to be most soluble forms and exhibited higher antimalarial efficacy showing higher survival rate (83.3%) after 30 days.

Photo Catalytic Oxidation Degradation of Volatile Organic Compound with Nano-TiO2/LDPE Composite Film

The photocatalytic activity efficiency of TiO2 for the degradation of Toluene in photoreactor can be enhanced by nano- TiO2/LDPE composite film. Since the amount of TiO2 affected the efficiency of the photocatalytic activity, this work was mainly concentrated on the effort to embed the high amount of TiO2 in the Polyethylene matrix. The developed photocatalyst was characterized by XRD, UV-Vis spectrophotometer and SEM. The SEM images revealed the high homogeneity of the deposition of TiO2 on the polyethylene matrix. The XRD patterns interpreted that TiO2 embedded in the PE matrix exhibited mainly in anatase form. In addition, the photocatalytic results show that the toluene removal efficiencies of 30±5%, 49±4%, 68±5%, 42±6% and 33±5% were obtained when using the catalyst loading at 0%, 10%, 15%, 25% and 50% (wt. cat./wt. film), respectively.

LOWL: Logic and OWL, an Extension

Current research on semantic web aims at making intelligent web pages meaningful for machines. In this way, ontology plays a primary role. We believe that logic can help ontology languages (such as OWL) to be more fluent and efficient. In this paper we try to combine logic with OWL to reduce some disadvantages of this language. Therefore we extend OWL by logic and also show how logic can satisfy our future expectations of an ontology language.

Application of Machine Learning Methods to Online Test Error Detection in Semiconductor Test

As in today's semiconductor industries test costs can make up to 50 percent of the total production costs, an efficient test error detection becomes more and more important. In this paper, we present a new machine learning approach to test error detection that should provide a faster recognition of test system faults as well as an improved test error recall. The key idea is to learn a classifier ensemble, detecting typical test error patterns in wafer test results immediately after finishing these tests. Since test error detection has not yet been discussed in the machine learning community, we define central problem-relevant terms and provide an analysis of important domain properties. Finally, we present comparative studies reflecting the failure detection performance of three individual classifiers and three ensemble methods based upon them. As base classifiers we chose a decision tree learner, a support vector machine and a Bayesian network, while the compared ensemble methods were simple and weighted majority vote as well as stacking. For the evaluation, we used cross validation and a specially designed practical simulation. By implementing our approach in a semiconductor test department for the observation of two products, we proofed its practical applicability.