An integrated approach to concept evaluation in a new product development

A new product development (NPD) process can be thought as a comprehensive process in which the design is progressively detailed through a series of phases. At the end of each phase a design review is held to approve the design and release or not it to the next level. As one of these phases, concept selection aiming to select the most appropriate concept for further development, is conducted earlier in the process. As the further development progresses on a selected concept, it becomes more difficult to make design changes in terms of cost and schedule dimensions, and therefore, selecting the best concept among a set of available alternatives has been an important issue for companies. On the other hand, in the presence of many alternatives and selection criteria, the selection problem becomes a multiple-criteria decision making concept selection problem. To solve this problem, in this work, an integrated approach bringing two popular methods together: the modified technique for order preference by similarity to ideal solution (TOPSIS) and the analytical network process (ANP). The ANP method is used to determine the relative weights of a set of quantitative and qualitative evaluation criteria, as the modified TOPSIS method utilized to rank competing concept alternatives. In addition, a real example is presented to demonstrate the effectiveness and applicability of the proposed approach for potential practitioners and readers.     

Visualization of fibrous and thread-like data

Thread-like structures are becoming more common in modern volumetric data sets as our ability to image vascular and neural tissue at higher resolutions improves. The thread-like structures of neurons and micro-vessels pose a unique problem in visualization since they tend to be densely packed in small volumes of tissue. This makes it difficult for an observer to interpret useful patterns from the data or trace individual fibers. In this paper we describe several methods for dealing with large amounts of thread-like data, such as data sets collected using Knife-Edge Scanning Microscopy (KESM) and Serial Block-Face Scanning Electron Microscopy (SBF-SEM). These methods allow us to collect volumetric data from embedded samples of whole-brain tissue. The neuronal and microvascular data that we acquire consists of thin, branching structures extending over very large regions. Traditional visualization schemes are not sufficient to make sense of the large, dense, complex structures encountered. In this paper, we address three methods to allow a user to explore a fiber network effectively. We describe interactive techniques for rendering large sets of neurons using self-orienting surfaces implemented on the GPU. We also present techniques for rendering fiber networks in a way that provides useful information about flow and orientation. Third, a global illumination framework is used to create high-quality visualizations that emphasize the underlying fiber structure. Implementation details, performance, and advantages and disadvantages of each approach are discussed.     

Assessment of Water Quality Management in Turkey

Abstract

There has been a noticeable increase in the amount of pollution in water resources in Turkey in recent years. Negative environmental developments, such as industrialization, increasing urbanization, improper pesticide and fertilizer applications in agricultural lands, and the drainage of domestic and industrial wastewater into water resources without any waste treatment applications, cause rapid pollution of both surface and groundwater resources. Therefore, it is necessary to allocate more attention to water resources monitoring and evaluation studies to prevent the pollution of water resources, and to reclaim these resources.     

Vibration analysis of rolling element bearings with various defects under the action of an unbalanced force

In this paper, a method based on the finite element vibration analysis is presented for defect detection in rolling element bearings with single or multiple defects on different components of the bearing structure using the time and frequency domain parameters. A dynamic loading model is proposed in order to create the nodal excitation functions used in the finite element vibration analysis as external loading. A computer code written in Visual Basic programming language with a graphical user interface is developed to create the nodal excitations for different cases including the outer ring, inner ring or rolling element defects. Forced vibration analysis of a bearing structure is performed using the commercial finite element package I-DEAS under the action of an unbalanced force transferred to the structure via a ball bearing. Time and frequency domain parameters such as rms, crest factor, kurtosis and band energy ratio for the frequency spectrum of the enveloped signals are used to analyse the effect of the defect location and the number of defects on the time and frequency domain parameters. The role of the receiving point for vibration measurements is also investigated. The vibration data for various defect cases including the housing structure effect can be obtained using the finite element vibration analysis in order to develop an optimum monitoring method in condition monitoring studies.     

PSW statistical LSB image steganalysis

Multimedia Tools and Applications - Steganography is the art and science of producing covert communications by concealing secret messages in apparently innocent media, while steganalysis is the art...     

Ion Chromatographic Determination of Free Cyanide in Different Classes of Bottled Natural Mineral Water Consumed in Turkey

An ion chromatographic method for the quantitative determination of free cyanide in bottled natural mineral waters were measured in terms of selectivity, linearity, the limit of detection, limit of quantification, repeatability, precision, and accuracy. Chromatographic separation of free cyanide ions was accomplished with an anion-exchange column and detected by pulsed amperometric detection with a silver working electrode. The method was found to be selective, linear (r² = 0.999) at a concentration range of 0.5 to 134 μg L^?1, precise, and accurate. Recovery values of free cyanide in all classes of natural mineral water varied from 65.9 ± 1.6 to 95.2 ± 0.7 at different spiking levels (5–70 μg L^?1). Parameters (total dissolved solids, mineral interferences, and added sodium hydroxide) affecting the recovery values were studied in this project. The limit of detection and limit of quantification were found to be 0.295 and 0.983 μg L^?1, respectively. The proposed method was applied to 27 different brands of commercially available bottled natural mineral water products sold in Turkish markets. These natural mineral waters were classified as: (i) very low mineral concentration, (ii) low mineral concentration, (iii) intermediate mineral concentration, and (iv) high mineral concentration based on their total dissolved solids contents according to European Union Directive (Directive 80/777/EEC). Levels of free cyanide residues in the samples ranged from > limit of detection to 6.12 μg L^?1. The highest average concentration of free cyanide residues was found in the class of “high mineral concentration waters.” However, the determined free cyanide values in all of the tested natural mineral water samples were found to be within the limits of European Union legislation.     

Biodiversity and technological properties of yeasts from Turkish sourdough

Food Science and Biotechnology - In this study, yeasts were isolated and characterized from twelve traditional sourdough samples which belongs to Black Sea and Aegean regions of Turkey. Twenty six...     

Evaluating of traumatic brain injuries using artificial neural networks

The purpose of this study is to develop a diagnostic system to detect the severity of traumatic brain injuries using artificial neural networks. Three layered back propagation neural network with an input layer of 10 nodes whose output providing the inputs to a hidden layer was used. Thirty-two patients with traumatic brain injuries in different age and gender were taken in the study. Electroencephalography, Trauma and Glasgow coma scores were used for evaluating the data. The results obtained from the system were compared with the findings of neurologists. We found a significant relationship between the findings of neurologists and systems output for normal, mild, moderate and severe electroencephalography tracing data. Getting this system in routine use will lead to make a rapid decision for the degree of trauma with electroencephalography and revised trauma score.     

Early prostate cancer diagnosis by using artificial neural networks and support vector machines

The aim of this study is to design a classifier based expert system for early diagnosis of the organ in constraint phase to reach informed decision making without biopsy by using some selected features. The other purpose is to investigate a relationship between BMI (body mass index), smoking factor, and prostate cancer. The data used in this study were collected from 300 men (100: prostate adenocarcinoma, 200: chronic prostatism or benign prostatic hyperplasia). Weight, height, BMI, PSA (prostate specific antigen), Free PSA, age, prostate volume, density, smoking, systolic, diastolic, pulse, and Gleason score features were used and independent sample t-test was applied for feature selection. In order to classify related data, we have used following classifiers; scaled conjugate gradient (SCG), Broyden–Fletcher–Goldfarb–Shanno (BFGS), and Levenberg–Marquardt (LM) training algorithms of artificial neural networks (ANN) and linear, polynomial, and radial based kernel functions of support vector machine (SVM). It was determined that smoking is a factor increases the prostate cancer risk whereas BMI is not affected the prostate cancer. Since PSA, volume, density, and smoking features were to be statistically significant, they were chosen for classification. The proposed system was designed with polynomial based kernel function, which had the best performance (accuracy: 79%). In Turkish Family Health System, family physician to whom patients are applied firstly, would contribute to extract the risk map of illness and direct patients to correct treatments by using expert system such proposed.