Evaluation of Texture of Packhams Pears

The textural parameters, together with appearance and flavor, are sensory attributes of great importance for the product to be accepted by the consumer. The objective of the present study was the evaluation of the textural attributes of Packhams pears in the fresh state, after drying in a chamber with forced convection at 50ºC, lyophilized and re-hydrated. In texture analysis it was used the method of Texture Profile Analysis (TPA). The parameters analyzed were hardness, cohesiveness, adhesiveness, elasticity and chewiness. From the results obtained is possible to see that the drying operation greatly affected some textural properties of the pears, so that the hardness diminished very much with drying, for both drying methods.

Recognition and Reconstruction of Partially Occluded Objects

A new automatic system for the recognition and re¬construction of resealed and/or rotated partially occluded objects is presented. The objects to be recognized are described by 2D views and each view is occluded by several half-planes. The whole object views and their visible parts (linear cuts) are then stored in a database. To establish if a region R of an input image represents an object possibly occluded, the system generates a set of linear cuts of R and compare them with the elements in the database. Each linear cut of R is associated to the most similar database linear cut. R is recognized as an instance of the object 0 if the majority of the linear cuts of R are associated to a linear cut of views of 0. In the case of recognition, the system reconstructs the occluded part of R and determines the scale factor and the orientation in the image plane of the recognized object view. The system has been tested on two different datasets of objects, showing good performance both in terms of recognition and reconstruction accuracy.

Weight Functions for Signal Reconstruction Based On Level Crossings

Although the level crossing concept has been the subject of intensive investigation over the last few years, certain problems of great interest remain unsolved. One of these concern is distribution of threshold levels. This paper presents a new threshold level allocation schemes for level crossing based on nonuniform sampling. Intuitively, it is more reasonable if the information rich regions of the signal are sampled finer and those with sparse information are sampled coarser. To achieve this objective, we propose non-linear quantization functions which dynamically assign the number of quantization levels depending on the importance of the given amplitude range. Two new approaches to determine the importance of the given amplitude segment are presented. The proposed methods are based on exponential and logarithmic functions. Various aspects of proposed techniques are discussed and experimentally validated. Its efficacy is investigated by comparison with uniform sampling.

Proffering a Brand New Methodology to Resource Discovery in Grid based on Economic Criteria Using Learning Automata

Resource discovery is one of the chief services of a grid. A new approach to discover the provenances in grid through learning automata has been propounded in this article. The objective of the aforementioned resource-discovery service is to select the resource based upon the user-s applications and the mercantile yardsticks that is to say opting for an originator which can accomplish the user-s tasks in the most economic manner. This novel service is submitted in two phases. We proffered an applicationbased categorization by means of an intelligent nerve-prone plexus. The user in question sets his or her application as the input vector of the nerve-prone nexus. The output vector of the aforesaid network limns the appropriateness of any one of the resource for the presented executive procedure. The most scrimping option out of those put forward in the previous stage which can be coped with to fulfill the task in question is picked out. Te resource choice is carried out by means of the presented algorithm based upon the learning automata.

Phase Control Array Synthesis Using Constrained Accelerated Particle Swarm Optimization

In this paper, the phase control antenna array synthesis is presented. The problem is formulated as a constrained optimization problem that imposes nulls with prescribed level while maintaining the sidelobe at a prescribed level. For efficient use of the algorithm memory, compared to the well known Particle Swarm Optimization (PSO), the Accelerated Particle Swarm Optimization (APSO) is used to estimate the phase parameters of the synthesized array. The objective function is formed using a main objective and set of constraints with penalty factors that measure the violation of each feasible solution in the search space to each constraint. In this case the obtained feasible solution is guaranteed to satisfy all the constraints. Simulation results have shown significant performance increases and a decreased randomness in the parameter search space compared to a single objective conventional particle swarm optimization.

Hybrid Approach for Memory Analysis in Windows System

Random Access Memory (RAM) is an important device in computer system. It can represent the snapshot on how the computer has been used by the user. With the growth of its importance, the computer memory has been an issue that has been discussed in digital forensics. A number of tools have been developed to retrieve the information from the memory. However, most of the tools have their limitation in the ability of retrieving the important information from the computer memory. Hence, this paper is aimed to discuss the limitation and the setback for two main techniques such as process signature search and process enumeration. Then, a new hybrid approach will be presented to minimize the setback in both individual techniques. This new approach combines both techniques with the purpose to retrieve the information from the process block and other objects in the computer memory. Nevertheless, the basic theory in address translation for x86 platforms will be demonstrated in this paper.

Shelf Life Extension of Milk Pomade Sweet – Sherbet with Crunchy Peanut Chips by MAP in Various Packaging Materials

The objective of the research was to evaluate the hardness stability of milk pomade sweets packed in several packaging materials (OPP, Multibarrier 60 HFP, BIALON 65 HFP, BIALON 50 HFP, ECOLEAN) by several packaging technologies – modified atmosphere (MAP) (consisting of 30% CO2+70% N2; 30% N2+70% CO2 and 100% CO2) and control – in air ambiance. Samples were stored at the room temperature +21±1 °C. The studies of the samples were carried out before packaging and after 2, 4, 6, 8, and 10 storage weeks.

Real Time Compensation of Machining Errors for Machine Tools NC based on Systematic Dispersion

Manufacturing tolerancing is intended to determine the intermediate geometrical and dimensional states of the part during its manufacturing process. These manufacturing dimensions also serve to satisfy not only the functional requirements given in the definition drawing, but also the manufacturing constraints, for example geometrical defects of the machine, vibration and the wear of the cutting tool. In this paper, an experimental study on the influence of the wear of the cutting tool (systematic dispersions) is explored. This study was carried out on three stages .The first stage allows machining without elimination of dispersions (random, systematic) so the tolerances of manufacture according to total dispersions. In the second stage, the results of the first stage are filtered in such way to obtain the tolerances according to random dispersions. Finally, from the two previous stages, the systematic dispersions are generated. The objective of this study is to model by the least squares method the error of manufacture based on systematic dispersion. Finally, an approach of optimization of the manufacturing tolerances was developed for machining on a CNC machine tool

Collaborative Business Strategy of PTT Energy Trading Co. Ltd. for LNG form of Coal Bed Methane in B2B Transaction to Japanese Shareholder, Especially to Electricity and Power Supply Companies

A research study was conducted with an objective to propose a collaborative business strategy of a oil and gas trading company, representing PPT Energy Trading Co., Ltd., with its shareholder, especially electricity and power supply companies for LNG Form of Coal Bed Methane in B2B Transaction. Collaborative business strategy is a strategy to collaborate with other organizations due to have future benefits in both parties, or achieve the business objective through the collaboration of business, its strategy and partners. A structured interview was established to collect the required primary data from the company. Not only interview, but also company’s business plan and annual report were collected and analyzed for the company’s current condition. As the result, this research shows a recommendation to propose a new collaborative strategy with limiting its target market, diversifying product, conducting new business model, and considering other stakeholders.

Interaction between Environmental Performance and Logistic System: A Case Study of International Company

The activities which are mostly related to the environmental performance need to be pointed, especially how logistics systems influence on environmental performance. This paper analyses how company could lead the initiative in this area by incorporating environmental management principles into their daily activities. The analysis is based on literature review about logistics and environment, the information from company R website as well as face-to-face interviews. A case study is given to show how they can turn practices into green while simultaneously meet the efficiency objectives. The research results show that the adoption of EMS and ISO 14001 certification is an effective tool for the logistics management. Such practices simultaneously reduce the negative contribute to better company performance. The results also show that the emissions to air and water, and energy consumption are the main logistics impacts to the environment.

ISCS (Information Security Check Service) for the Safety and Reliability of Communications

Recent widespread use of information and communication technology has greatly changed information security risks that businesses and institutions encounter. Along with this situation, in order to ensure security and have confidence in electronic trading, it has become important for organizations to take competent information security measures to provide international confidence that sensitive information is secure. Against this backdrop, the approach to information security checking has come to an important issue, which is believed to be common to all countries. The purpose of this paper is to introduce the new system of information security checking program in Korea and to propose synthetic information security countermeasures under domestic circumstances in order to protect physical equipment, security management and technology, and the operation of security check for securing services on ISP(Internet Service Provider), IDC(Internet Data Center), and e-commerce(shopping malls, etc.)

Artificial Intelligence Techniques applied to Biomedical Patterns

Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.

Ignition Delay Correlation for a Direct Injection Diesel Engine Fuelled with Automotive Diesel and Water Diesel Emulsion

Most of ignition delay correlations studies have been developed in a constant volume bombs which cannot capture the dynamic variation in pressure and temperature during the ignition delay as in real engines. Watson, Assanis et. al. and Hardenberg and Hase correlations have been developed based on experimental data of diesel engines. However, they showed limited predictive ability of ignition delay when compared to experimental results. The objective of the study was to investigate the dependency of ignition delay time on engine brake power. An experimental investigation of the effect of automotive diesel and water diesel emulsion fuels on ignition delay under steady state conditions of a direct injection diesel engine was conducted. A four cylinder, direct injection naturally aspirated diesel engine was used in this experiment over a wide range of engine speeds and two engine loads. The ignition delay experimental data were compared with predictions of Assanis et. al. and Watson ignition delay correlations. The results of the experimental investigation were then used to develop a new ignition delay correlation. The newly developed ignition delay correlation has shown a better agreement with the experimental data than Assanis et. al. and Watson when using automotive diesel and water diesel emulsion fuels especially at low to medium engine speeds at both loads. In addition, the second derivative of cylinder pressure which is the most widely used method in determining the start of combustion was investigated.

Multiple Object Tracking using Particle Swarm Optimization

This paper presents a particle swarm optimization (PSO) based approach for multiple object tracking based on histogram matching. To start with, gray-level histograms are calculated to establish a feature model for each of the target object. The difference between the gray-level histogram corresponding to each particle in the search space and the target object is used as the fitness value. Multiple swarms are created depending on the number of the target objects under tracking. Because of the efficiency and simplicity of the PSO algorithm for global optimization, target objects can be tracked as iterations continue. Experimental results confirm that the proposed PSO algorithm can rapidly converge, allowing real-time tracking of each target object. When the objects being tracked move outside the tracking range, global search capability of the PSO resumes to re-trace the target objects.

Electric Field and Potential Distributions along Surface of Silicone Rubber Polymer Insulators Using Finite Element Method

This paper presents the simulation the results of electric field and potential distributions along surface of silicone rubber polymer insulators. Near the same leakage distance subjected to 15 kV in 50 cycle salt fog ageing test, alternate sheds silicone rubber polymer insulator showed better contamination performance than straight sheds silicone rubber polymer insulator. Severe surface ageing was observed on the straight sheds insulator. The objective of this work is to elucidate that electric field distribution along straight sheds insulator higher than alternate shed insulator in salt fog ageing test. Finite element method (FEM) is adopted for this work. The simulation results confirmed the experimental data, as well.

Using Morphological and Microsatellite (SSR) Markers to Assess the Genetic Diversity in Alfalfa (Medicago sativa L.)

Utilization of diverse germplasm is needed to enhance the genetic diversity of cultivars. The objective of this study was to evaluate the genetic relationships of 98 alfalfa germplasm accessions using morphological traits and SSR markers. From the 98 tested populations, 81 were locals originating in Europe, 17 were introduced from USA, Australia, New Zealand and Canada. Three primers generated 67 polymorphic bands. The average polymorphic information content (PIC) was very high (> 0.90) over all three used primer combinations. Cluster analysis using Unweighted Pair Group Method with Arithmetic Means (UPGMA) and Jaccard´s coefficient grouped the accessions into 2 major clusters with 4 sub-clusters with no correlation between genetic and morphological diversity. The SSR analysis clearly indicated that even with three polymorphic primers, reliable estimation of genetic diversity could be obtained.

From Maskee to Audible Noise in Perceptual Speech Enhancement

A new analysis of perceptual speech enhancement is presented. It focuses on the fact that if only noise above the masking threshold is filtered, then noise below the masking threshold, but above the absolute threshold of hearing, can become audible after the masker filtering. This particular drawback of some perceptual filters, hereafter called the maskee-to-audible-noise (MAN) phenomenon, favours the emergence of isolated tonals that increase musical noise. Two filtering techniques that avoid or correct the MAN phenomenon are proposed to effectively suppress background noise without introducing much distortion. Experimental results, including objective and subjective measurements, show that these techniques improve the enhanced speech quality and the gain they bring emphasizes the importance of the MAN phenomenon.

Fuzzy Group Decision Making for the Assessment of Health-Care Waste Disposal Alternatives in Istanbul

Disposal of health-care waste (HCW) is considered as an important environmental problem especially in large cities. Multiple criteria decision making (MCDM) techniques are apt to deal with quantitative and qualitative considerations of the health-care waste management (HCWM) problems. This research proposes a fuzzy multi-criteria group decision making approach with a multilevel hierarchical structure including qualitative as well as quantitative performance attributes for evaluating HCW disposal alternatives for Istanbul. Using the entropy weighting method, objective weights as well as subjective weights are taken into account to determine the importance weighting of quantitative performance attributes. The results obtained using the proposed methodology are thoroughly analyzed.

Interval Type-2 Fuzzy Vibration Control of an ERF Embedded Smart Structure

The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system.  

Relative Radiometric Correction of Cloudy Multitemporal Satellite Imagery

Repeated observation of a given area over time yields potential for many forms of change detection analysis. These repeated observations are confounded in terms of radiometric consistency due to changes in sensor calibration over time, differences in illumination, observation angles and variation in atmospheric effects. This paper demonstrates applicability of an empirical relative radiometric normalization method to a set of multitemporal cloudy images acquired by Resourcesat1 LISS III sensor. Objective of this study is to detect and remove cloud cover and normalize an image radiometrically. Cloud detection is achieved by using Average Brightness Threshold (ABT) algorithm. The detected cloud is removed and replaced with data from another images of the same area. After cloud removal, the proposed normalization method is applied to reduce the radiometric influence caused by non surface factors. This process identifies landscape elements whose reflectance values are nearly constant over time, i.e. the subset of non-changing pixels are identified using frequency based correlation technique. The quality of radiometric normalization is statistically assessed by R2 value and mean square error (MSE) between each pair of analogous band.