Do Students Really Understand Topology in the Lesson? A Case Study

This study aims to specify to what extent students understand topology during the lesson and to determine possible misconceptions. 14 teacher trainees registered at Secondary School Mathematics education department were observed in the topology lessons throughout a semester and data collected at the first topology lesson is presented here. Students- knowledge was evaluated using a written test right before and after the topology lesson. Thus, what the students learnt in terms of the definition and examples of topologic space were specified as well as possible misconceptions. The findings indicated that students did not fully comprehend the topic and misunderstandings were due to insufficient pre-requisite knowledge of abstract mathematical topics and mathematical notation.

HPL-TE Method for Determination of Coatings Relative Total Emissivity Sensitivity Analysis of the Influences of Method Parameters

High power laser – total emissivity method (HPL-TE method) for determination of coatings relative total emissivity dependent on the temperature is introduced. Method principle, experimental and evaluation parts of the method are described. Computer model of HPL-TE method is employed to perform the sensitivity analysis of the effect of method parameters on the sample surface temperature in the positions where the surface temperature and radiation heat flux are measured.

Generation of Artificial Earthquake Accelerogram Compatible with Spectrum using the Wavelet Packet Transform and Nero-Fuzzy Networks

The principal purpose of this article is to present a new method based on Adaptive Neural Network Fuzzy Inference System (ANFIS) to generate additional artificial earthquake accelerograms from presented data, which are compatible with specified response spectra. The proposed method uses the learning abilities of ANFIS to develop the knowledge of the inverse mapping from response spectrum to earthquake records. In addition, wavelet packet transform is used to decompose specified earthquake records and then ANFISs are trained to relate the response spectrum of records to their wavelet packet coefficients. Finally, an interpretive example is presented which uses an ensemble of recorded accelerograms to demonstrate the effectiveness of the proposed method.

The Effect of Cyclone Shape and Dust Collector on Gas-Solid Flow and Performance

Numerical analysis of flow characteristics and separation efficiency in a high-efficiency cyclone has been performed. Several models based on the experimental observation for a design purpose were proposed. However, the model is only estimated the cyclone's performance under the limited environments; it is difficult to obtain a general model for all types of cyclones. The purpose of this study is to find out the flow characteristics and separation efficiency numerically. The Reynolds stress model (RSM) was employed instead of a standard k-ε or a k-ω model which was suitable for isotropic turbulence and it could predict the pressure drop and the Rankine vortex very well. For small particles, there were three significant components (entrance of vortex finder, cone, and dust collector) for the particle separation. In the present work, the particle re-entraining phenomenon from the dust collector to the cyclone body was observed after considerable time. This re-entrainment degraded the separation efficiency and was one of the significant factors for the separation efficiency of the cyclone.

Robust Stability Criteria for Uncertain Genetic Regulatory Networks with Time-Varying Delays

This paper presents the robust stability criteria for uncertain genetic regulatory networks with time-varying delays. One key point of the criterion is that the decomposition of the matrix ˜D into ˜D = ˜D1 + ˜D2. This decomposition corresponds to a decomposition of the delayed terms into two groups: the stabilizing ones and the destabilizing ones. This technique enables one to take the stabilizing effect of part of the delayed terms into account. Meanwhile, by choosing an appropriate new Lyapunov functional, a new delay-dependent stability criteria is obtained and formulated in terms of linear matrix inequalities (LMIs). Finally, numerical examples are presented to illustrate the effectiveness of the theoretical results.

Trust In Ad Media

Advertising today has already become an integral part of human life as a building block of the consumer community. A component of the value chain of the media, advertising sector is struggling increasingly harder to find new methods to reach consumers. The tendency towards experimental marketing practices is increasing day by day, especially to divert consumers from the idea “They are selling something to me.” It is therefore considered a good idea to investigate the trust in ad media of consumers, who are today exposed to a great bulk of information from advertising sector. In this study, the current value of ad media for the young consumer will be investigated. Data on various ad media reliability will be comparatively analyzed and young consumers will be traced by including university students in the study. In this research, which will be performed on students studying at the Selçuk University (Turkey) by random sampling method, data will be obtained by survey technique and evaluated by a statistical analysis.

A Trust Model using Fuzzy Logic in Wireless Sensor Network

Adapting various sensor devices to communicate within sensor networks empowers us by providing range of possibilities. The sensors in sensor networks need to know their measurable belief of trust for efficient and safe communication. In this paper, we suggested a trust model using fuzzy logic in sensor network. Trust is an aggregation of consensus given a set of past interaction among sensors. We applied our suggested model to sensor networks in order to show how trust mechanisms are involved in communicating algorithm to choose the proper path from source to destination.

SMaTTS: Standard Malay Text to Speech System

This paper presents a rule-based text- to- speech (TTS) Synthesis System for Standard Malay, namely SMaTTS. The proposed system using sinusoidal method and some pre- recorded wave files in generating speech for the system. The use of phone database significantly decreases the amount of computer memory space used, thus making the system very light and embeddable. The overall system was comprised of two phases the Natural Language Processing (NLP) that consisted of the high-level processing of text analysis, phonetic analysis, text normalization and morphophonemic module. The module was designed specially for SM to overcome few problems in defining the rules for SM orthography system before it can be passed to the DSP module. The second phase is the Digital Signal Processing (DSP) which operated on the low-level process of the speech waveform generation. A developed an intelligible and adequately natural sounding formant-based speech synthesis system with a light and user-friendly Graphical User Interface (GUI) is introduced. A Standard Malay Language (SM) phoneme set and an inclusive set of phone database have been constructed carefully for this phone-based speech synthesizer. By applying the generative phonology, a comprehensive letter-to-sound (LTS) rules and a pronunciation lexicon have been invented for SMaTTS. As for the evaluation tests, a set of Diagnostic Rhyme Test (DRT) word list was compiled and several experiments have been performed to evaluate the quality of the synthesized speech by analyzing the Mean Opinion Score (MOS) obtained. The overall performance of the system as well as the room for improvements was thoroughly discussed.

Distributional Semantics Approach to Thai Word Sense Disambiguation

Word sense disambiguation is one of the most important open problems in natural language processing applications such as information retrieval and machine translation. Many approach strategies can be employed to resolve word ambiguity with a reasonable degree of accuracy. These strategies are: knowledgebased, corpus-based, and hybrid-based. This paper pays attention to the corpus-based strategy that employs an unsupervised learning method for disambiguation. We report our investigation of Latent Semantic Indexing (LSI), an information retrieval technique and unsupervised learning, to the task of Thai noun and verbal word sense disambiguation. The Latent Semantic Indexing has been shown to be efficient and effective for Information Retrieval. For the purposes of this research, we report experiments on two Thai polysemous words, namely  /hua4/ and /kep1/ that are used as a representative of Thai nouns and verbs respectively. The results of these experiments demonstrate the effectiveness and indicate the potential of applying vector-based distributional information measures to semantic disambiguation.

Generating State-Based Testing Models for Object-Oriented Framework Interface Classes

An application framework provides a reusable design and implementation for a family of software systems. Application developers extend the framework to build their particular applications using hooks. Hooks are the places identified to show how to use and customize the framework. Hooks define the Framework Interface Classes (FICs) and the specifications of their methods. As part of the development life cycle, it is required to test the implementations of the FICs. Building a testing model to express the behavior of a class is an essential step for the generation of the class-based test cases. The testing model has to be consistent with the specifications provided for the hooks. State-based models consisting of states and transitions are testing models well suited to objectoriented software. Typically, hand-construction of a state-based model of a class behavior is expensive, error-prone, and may result in constructing an inconsistent model with the specifications of the class methods, which misleads verification results. In this paper, a technique is introduced to automatically synthesize a state-based testing model for FICs using the specifications provided for the hooks. A tool that supports the proposed technique is introduced.

An Investigation on the Variation of Software Development Productivity

The productivity of software development is one of the major concerns for project managers. Given the increasing complexity of the software being developed and the concomitant rise in the typical project size, the productivity has not consistently improved. By analyzing the latest release of ISBSG data repository with 4106 projects ever developed, we report on the factors found to significantly influence productivity, and present an original model for the estimation of productivity during project design. We further illustrate that software development productivity has experienced irregular variations between the years 1995 and 2005. Considering the factors significant to productivity, we found its variations are primarily caused by the variations of average team size for the development and the unbalanced use of the less productive development language 3GL.

Improved Neutron Leakage Treatment on Nodal Expansion Method for PWR Reactors

For a quick and accurate calculation of spatial neutron distribution in nuclear power reactors 3D nodal codes are usually used aiming at solving the neutron diffusion equation for a given reactor core geometry and material composition. These codes use a second order polynomial to represent the transverse leakage term. In this work, a nodal method based on the well known nodal expansion method (NEM), developed at COPPE, making use of this polynomial expansion was modified to treat the transverse leakage term for the external surfaces of peripheral reflector nodes. The proposed method was implemented into a computational system which, besides solving the diffusion equation, also solves the burnup equations governing the gradual changes in material compositions of the core due to fuel depletion. Results confirm the effectiveness of this modified treatment of peripheral nodes for practical purposes in PWR reactors.

Investigation of Heavy Metals Uptake by Vegetable Crops from Metal-Contaminated Soil

The use of sewage sludge and effluents from wastewater treatment plants for irrigation of agricultural lands is on the rise particularly in peri-urban areas of developing countries. The reuse of nutrients and organic matter in treated wastewater and sewage sludge via land application is a desirable goal. However, trace or heavy metals present in sludge pose the risk of human or phytotoxicity from land application. Long-term use of sewage sludge, heavy metals can accumulate to phytotoxic levels and results in reduced plants growth and/or enhanced metal concentrations in plants, which consumed by animals then enter the food chain. In this research, the amount of heavy metals was measured in plants irrigated with wastewater and sludge application. For this purpose, three pilots were made in a Shush treatment plant in south of Tehran. Three plants species, spinach, lettuce and radish were selected and planted in the pilots.First pilot was irrigated just with wastewater of treatment plant and second pilot was irrigated with wastewater and sludge application .Third pilot was irrigated with simulated heavy metals solution equal 50 years of irrigation. The results indicate that the average of amount of heavy metals Pb, Cd in three plant species in first pilot were lower than permissible limits .In second pilot, Cadmium accumulations are high in three species plants and more than the standard limits. Concentration of Cd , Pb have exceed their permitted limits in plants in third pilot . It was concluded that the use of wastewater and sludge application in agricultural lands enriched soils with heavy metals to concentrations that may pose potential environmental and health risks in the long-term.

Optimal Convolutive Filters for Real-Time Detection and Arrival Time Estimation of Transient Signals

Linear convolutive filters are fast in calculation and in application, and thus, often used for real-time processing of continuous data streams. In the case of transient signals, a filter has not only to detect the presence of a specific waveform, but to estimate its arrival time as well. In this study, a measure is presented which indicates the performance of detectors in achieving both of these tasks simultaneously. Furthermore, a new sub-class of linear filters within the class of filters which minimize the quadratic response is proposed. The proposed filters are more flexible than the existing ones, like the adaptive matched filter or the minimum power distortionless response beamformer, and prove to be superior with respect to that measure in certain settings. Simulations of a real-time scenario confirm the advantage of these filters as well as the usefulness of the performance measure.

Robust H∞ Filter Design for Uncertain Fuzzy Descriptor Systems: LMI-Based Design

This paper examines the problem of designing a robust H∞ filter for a class of uncertain fuzzy descriptor systems described by a Takagi-Sugeno (TS) fuzzy model. Based on a linear matrix inequality (LMI) approach, LMI-based sufficient conditions for the uncertain nonlinear descriptor systems to have an H∞ performance are derived. To alleviate the ill-conditioning resulting from the interaction of slow and fast dynamic modes, solutions to the problem are given in terms of linear matrix inequalities which are independent of the singular perturbation ε, when ε is sufficiently small. The proposed approach does not involve the separation of states into slow and fast ones and it can be applied not only to standard, but also to nonstandard uncertain nonlinear descriptor systems. A numerical example is provided to illustrate the design developed in this paper.

Glass Bottle Inspector Based on Machine Vision

This text studies glass bottle intelligent inspector based machine vision instead of manual inspection. The system structure is illustrated in detail in this paper. The text presents the method based on watershed transform methods to segment the possible defective regions and extract features of bottle wall by rules. Then wavelet transform are used to exact features of bottle finish from images. After extracting features, the fuzzy support vector machine ensemble is putted forward as classifier. For ensuring that the fuzzy support vector machines have good classification ability, the GA based ensemble method is used to combining the several fuzzy support vector machines. The experiments demonstrate that using this inspector to inspect glass bottles, the accuracy rate may reach above 97.5%.

Lightweight Materials Obtained by Utilization of Agricultural Waste

Lightweight ceramic materials in the form of bricks and blocks are widely used in modern construction. They may be obtained by adding of rice husk, rye straw, etc, as porous forming materials. Rice husk is a major by-product of the rice milling industry. Its utilization as a valuable product has always been a problem. Various technologies for utilization of rice husk through biological and thermochemical conversion are being developed. The purpose of this work is to develop lightweight ceramic materials with clay matrix and filler of rice husk and examine their main physicomechanical properties. The results obtained allow to suppose that the materials synthesized on the basis of waste materials can be used as lightweight materials for construction purpose.

Investigation of Gas Phase Composition During Carbon Nanotube Production

Chemical vapor deposition method was used to produce carbon nanotubes on an iron based catalyst from acetylene. Gas-phase samples collected from the different positions of the tubular reactor were analyzed by GC/MS. A variety of species ranging from hydrogen to naphthalene were observed and changes in their concentrations were plotted against the reactor position. Briefly benzene, toluene, styrene, indene and naphthalene were the main higher molecular weight species and vinylacetylene and diacetylene were the important intermediates. Nanotube characterization was performed by scanning electron microscopy and transmission electron microscopy.

Nonlinear Sensitive Control of Centrifugal Compressor

In this work, we treat the problems related to chemical and petrochemical plants of a certain complex process taking the centrifugal compressor as an example, a system being very complex by its physical structure as well as its behaviour (surge phenomenon). We propose to study the application possibilities of the recent control approaches to the compressor behaviour, and consequently evaluate their contribution in the practical and theoretical fields. Facing the studied industrial process complexity, we choose to make recourse to fuzzy logic for analysis and treatment of its control problem owing to the fact that these techniques constitute the only framework in which the types of imperfect knowledge can jointly be treated (uncertainties, inaccuracies, etc..) offering suitable tools to characterise them. In the particular case of the centrifugal compressor, these imperfections are interpreted by modelling errors, the neglected dynamics, no modelisable dynamics and the parametric variations. The purpose of this paper is to produce a total robust nonlinear controller design method to stabilize the compression process at its optimum steady state by manipulating the gas rate flow. In order to cope with both the parameter uncertainty and the structured non linearity of the plant, the proposed method consists of a linear steady state regulation that ensures robust optimal control and of a nonlinear compensation that achieves the exact input/output linearization.