Rethinking Research for Genetically Modified (GM) Food

This paper suggests a rethinking of the existing research about Genetically Modified (GM) food. Since the first batch of GM food was commercialised in the UK market, GM food rapidly received and lost media attention in the UK. Disagreement on GM food policy between the US and the EU has also drawn scholarly attention to this issue. Much research has been carried out intending to understand people-s views about GM food and the shaping of these views. This paper was based on the data collected in twenty-nine semi-structured interviews, which were examined through Erving Goffman-s idea of self-presentation in interactions to suggest that the existing studies investigating “consumer attitudes" towards GM food have only considered the “front stage" in the dramaturgic metaphor. This paper suggests that the ways in which people choose to present themselves when participating these studies should be taken into account during the data analysis.

Shunt Power Active Filter Control under NonIdeal Voltages Conditions

In this paper, we propose the Modified Synchronous Detection (MSD) Method for determining the reference compensating currents of the shunt active power filter under non sinusoidal voltages conditions. For controlling the inverter switching we used the PI regulator. The numerical simulation results, using Power System Blockset Toolbox PSB of Matlab, from a complete structure, are presented and discussed.

Power Quality Improvement Using PI and Fuzzy Logic Controllers Based Shunt Active Filter

In recent years the large scale use of the power electronic equipment has led to an increase of harmonics in the power system. The harmonics results into a poor power quality and have great adverse economical impact on the utilities and customers. Current harmonics are one of the most common power quality problems and are usually resolved by using shunt active filter (SHAF). The main objective of this work is to develop PI and Fuzzy logic controllers (FLC) to analyze the performance of Shunt Active Filter for mitigating current harmonics under balanced and unbalanced sinusoidal source voltage conditions for normal load and increased load. When the supply voltages are ideal (balanced), both PI and FLC are converging to the same compensation characteristics. However, the supply voltages are non-ideal (unbalanced), FLC offers outstanding results. Simulation results validate the superiority of FLC with triangular membership function over the PI controller.

Faults Forecasting System

This paper presents Faults Forecasting System (FFS) that utilizes statistical forecasting techniques in analyzing process variables data in order to forecast faults occurrences. FFS is proposing new idea in detecting faults. Current techniques used in faults detection are based on analyzing the current status of the system variables in order to check if the current status is fault or not. FFS is using forecasting techniques to predict future timing for faults before it happens. Proposed model is applying subset modeling strategy and Bayesian approach in order to decrease dimensionality of the process variables and improve faults forecasting accuracy. A practical experiment, designed and implemented in Okayama University, Japan, is implemented, and the comparison shows that our proposed model is showing high forecasting accuracy and BEFORE-TIME.

A Multiresolution Approach for Noised Texture Classification based on the Co-occurrence Matrix and First Order Statistics

Wavelet transform provides several important characteristics which can be used in a texture analysis and classification. In this work, an efficient texture classification method, which combines concepts from wavelet and co-occurrence matrices, is presented. An Euclidian distance classifier is used to evaluate the various methods of classification. A comparative study is essential to determine the ideal method. Using this conjecture, we developed a novel feature set for texture classification and demonstrate its effectiveness

Corporate Knowledge Communication and Knowledge Communication Difficulties

Communication is an important factor and a prop in directing corporate activities efficiently, in ensuring the flow of knowledge which is necessary for the continuity of the institution, in creating a common language in the institution, in transferring corporate culture and ultimately in corporate success. The idea of transmitting the knowledge among the workers in a healthy manner has revived knowledge communication. Knowledge communication can be defined as the act of mutual creation and communication of intuitions, assessments, experiences and capabilities, as long as maintained effectively, can provide advantages such as corporate continuity, access to corporate objectives and making true administrative decisions. Although the benefits of the knowledge communication to corporations are known, and the necessary worth and care is given, some hardships may arise which makes it difficult or even block it. In this article, difficulties that prevent knowledge communication will be discussed and solutions will be proposed.

Isobaric Vapor-Liquid Equilibria of Mesitylene + 1- Heptanol and Mesitylene +1-Octanol at 97.3 kPa

Isobaric vapor-liquid equilibrium measurements are reported for the binary mixtures of Mesitylene + 1-Heptanol and Mesitylene + 1-Octanol at 97.3 kPa. The measurements have been performed using a vapor recirculating type (modified Othmer's) equilibrium still. Both the mixtures show positive deviation from ideality. The Mesitylene + 1-Heptanol mixture forms an azeotrope whereas Mesitylene + 1- Octanol form a non – azeotropic mixture. The activity coefficients have been calculated taking into consideration the vapor phase nonideality. The data satisfy the thermodynamic consistency tests of Herington, and Hirata. The activity coefficients have been satisfactorily correlated by means of the Margules, Redlich-Kister, Wilson, Black, and NRTL equations. The activity coefficient values have also been obtained by UNIFAC method.

A Task-Based Design Approach for Augmented Reality Systems

User interaction components of Augmented Reality (AR) systems have to be tested with users in order to find and fix usability problems as early as possible. In this paper we will report on a user-centered design approach for AR systems following the experience acquired during the design and evaluation of a software prototype for an AR-based educational platform. In this respect we will focus on the re-design of the user task based on the results from a formative usability evaluation. The basic idea of our approach is to describe task scenarios in a tabular format, to develop a task model in a task modeling environment and then to simulate the execution.

A Method to Annotate Programs with High-Level Knowledge of Computation

When programming in languages such as C, Java, etc., it is difficult to reconstruct the programmer's ideas only from the program code. This occurs mainly because, much of the programmer's ideas behind the implementation are not recorded in the code during implementation. For example, physical aspects of computation such as spatial structures, activities, and meaning of variables are not required as instructions to the computer and are often excluded. This makes the future reconstruction of the original ideas difficult. AIDA, which is a multimedia programming language based on the cyberFilm model, can solve these problems allowing to describe ideas behind programs using advanced annotation methods as a natural extension to programming. In this paper, a development environment that implements the AIDA language is presented with a focus on the annotation methods. In particular, an actual scientific numerical computation code is created and the effects of the annotation methods are analyzed.

The Link between Financial and Overall Corporate Strategies

Company strategy expresses a basic idea of how to reach company objectives. A whole range of models of strategic management are used in practice. The concept of strategic management should fulfill some basic requirements to make it applicable for both the typical, but also more specific company environment. The financial strategy plays an important role in corporate strategy. The paper develops a methodology of strategic model implementing into the category of micro, small and medium-sized enterprises (SMEs). Furthermore, the methodology recommends procedures while solving an up-to-date worldwide task of the definition of the company strategy and its financial strategy.

A Direct Probabilistic Optimization Method for Constrained Optimal Control Problem

A new stochastic algorithm called Probabilistic Global Search Johor (PGSJ) has recently been established for global optimization of nonconvex real valued problems on finite dimensional Euclidean space. In this paper we present convergence guarantee for this algorithm in probabilistic sense without imposing any more condition. Then, we jointly utilize this algorithm along with control parameterization technique for the solution of constrained optimal control problem. The numerical simulations are also included to illustrate the efficiency and effectiveness of the PGSJ algorithm in the solution of control problems.

Creating or Destroying Objects Plan in the Graphplan Framework

At present, intelligent planning in the Graphplan framework is a focus of artificial intelligence. While the Creating or Destroying Objects Planning (CDOP) is one unsolved problem of this field, one of the difficulties, too. In this paper, we study this planning problem and bring forward the idea of transforming objects to propositions, based on which we offer an algorithm, Creating or Destroying Objects in the Graphplan framework (CDOGP). Compared to Graphplan, the new algorithm can solve not only the entire problems that Graphplan do, but also a part of CDOP. It is for the first time that we introduce the idea of object-proposition, and we emphasize the discussion on the representations of creating or destroying objects operator and an algorithm in the Graphplan framework. In addition, we analyze the complexity of this algorithm.

Heuristic Continuous-time Associative Memories

In this paper, a novel associative memory model will be proposed and applied to memory retrievals based on the conventional continuous time model. The conventional model presents memory capacity is very low and retrieval process easily converges to an equilibrium state which is very different from the stored patterns. Genetic Algorithms is well-known with the capability of global optimal search escaping local optimum on progress to reach a global optimum. Based on the well-known idea of Genetic Algorithms, this work proposes a heuristic rule to make a mutation when the state of the network is trapped in a spurious memory. The proposal heuristic associative memory show the stored capacity does not depend on the number of stored patterns and the retrieval ability is up to ~ 1.

Optimization of Energy Consumption in Sequential Distillation Column

Distillation column is one of the most common operations in process industries and is while the most expensive unit of the amount of energy consumption. Many ideas have been presented in the related literature for optimizing energy consumption in distillation columns. This paper studies the different heat integration methods in a distillation column which separate Benzene, Toluene, Xylene, and C9+. Three schemes of heat integration including, indirect sequence (IQ), indirect sequence with forward energy integration (IQF), and indirect sequence with backward energy integration (IQB) has been studied in this paper. Using shortcut method these heat integration schemes were simulated with Aspen HYSYS software and compared with each other with regarding economic considerations. The result shows that the energy consumption has been reduced 33% in IQF and 28% in IQB in comparison with IQ scheme. Also the economic result shows that the total annual cost has been reduced 12% in IQF and 8% in IQB regarding with IQ scheme. Therefore, the IQF scheme is most economic than IQB and IQ scheme.

A Fuzzy Logic Based Model to Predict Surface Roughness of A Machined Surface in Glass Milling Operation Using CBN Grinding Tool

Nowadays, the demand for high product quality focuses extensive attention to the quality of machined surface. The (CNC) milling machine facilities provides a wide variety of parameters set-up, making the machining process on the glass excellent in manufacturing complicated special products compared to other machining processes. However, the application of grinding process on the CNC milling machine could be an ideal solution to improve the product quality, but adopting the right machining parameters is required. In glass milling operation, several machining parameters are considered to be significant in affecting surface roughness. These parameters include the lubrication pressure, spindle speed, feed rate and depth of cut. In this research work, a fuzzy logic model is offered to predict the surface roughness of a machined surface in glass milling operation using CBN grinding tool. Four membership functions are allocated to be connected with each input of the model. The predicted results achieved via fuzzy logic model are compared to the experimental result. The result demonstrated settlement between the fuzzy model and experimental results with the 93.103% accuracy.

Classifier Based Text Mining for Neural Network

Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.

Isobaric Vapor-Liquid Equilibrium Data for Binary Mixture of 2-Methyltetrahydrofuran and Cumene

Isobaric vapor-liquid equilibrium measurements are reported for binary mixture of 2-Methyltetrahydrofuran and Cumene at 97.3 kPa. The data were obtained using a vapor recirculating type (modified Othmer's) equilibrium still. The mixture shows slight negative deviation from ideality. The system does not form an azeotrope. The experimental data obtained in this study are thermodynamically consistent according to the Herington test. The activity coefficients have been satisfactorily correlated by means of the Margules, and NRTL equations. Excess Gibbs free energy has been calculated from the experimental data. The values of activity coefficients have also been obtained by the UNIFAC group contribution method.

Modern Method for Solving Pure Integer Programming Models

In this paper, all variables are supposed to be integer and positive. In this modern method, objective function is assumed to be maximized or minimized but constraints are always explained like less or equal to. In this method, choosing a dual combination of ideal nonequivalent and omitting one of variables. With continuing this act, finally, having one nonequivalent with (n-m+1) unknown quantities in which final nonequivalent, m is counter for constraints, n is counter for variables of decision.

On Weakly Prime and Weakly Quasi-Prime Fuzzy Left Ideals in Ordered Semigroups

In this paper, we first introduce the concepts of weakly prime and weakly quasi-prime fuzzy left ideals of an ordered semigroup S. Furthermore, we give some characterizations of weakly prime and weakly quasi-prime fuzzy left ideals of an ordered semigroup S by the ordered fuzzy points and fuzzy subsets of S.

Structure of Doctoral Students- Research Competences in Sustainability Context

Qualification of doctoral students- and the candidates for a scientific degree is evaluated by the ability to solve scientific ideas in an innovative way, consequently, being a potential of research and science they play a significant role in the sustainability context of the society. The article deals with the analysis of the results of the pilot project, the aim of which has been to study the structure of doctoral students- research competences in the sustainability context. With the existance of variety of theories on research competence development, their analysis focuses on the attained aim approach. Three competence groups have been identified in this study: informative, communicative and instrumental. Within the study the doctoral students and candidates for a scientific degree (N=64) made their self-assessment of research competences. The study results depict their present research competence development level and its dynamics according to the aim to attain.