The Job Satisfaction of the Employees with the Organization Retention of Metropolitan Waterworks Authority at Bangkhen

This research aimed to study correlation between work satisfaction and organization core value of officers in Waterworks Authority, Bangkean Branch. Sample group of the study was 112 officers who worked in the Waterworks Authority, Bangkean Branch. Questionnaires were employed as a research tools, while, Percentage, Mean, Standard Deviation, T-test, One-way ANOVA, and Pearson Product Moment Correlation were claimed as statistics used in this study. Researcher found that overall and individual aspects of work satisfaction namely, work characteristic, work progress, and colleagues significantly correlated with organization core value in aspect of perception in choice of work at 0.5, 0.01, and 0.01 respectively. Also, such aspects were compatible with income at .05 which indicated the low level of correlation, mid low correlation respectively at the same direction, same direction, opposite direction, and same direction, correspondingly.

Performance Evaluation of Neural Network Prediction for Data Prefetching in Embedded Applications

Embedded systems need to respect stringent real time constraints. Various hardware components included in such systems such as cache memories exhibit variability and therefore affect execution time. Indeed, a cache memory access from an embedded microprocessor might result in a cache hit where the data is available or a cache miss and the data need to be fetched with an additional delay from an external memory. It is therefore highly desirable to predict future memory accesses during execution in order to appropriately prefetch data without incurring delays. In this paper, we evaluate the potential of several artificial neural networks for the prediction of instruction memory addresses. Neural network have the potential to tackle the nonlinear behavior observed in memory accesses during program execution and their demonstrated numerous hardware implementation emphasize this choice over traditional forecasting techniques for their inclusion in embedded systems. However, embedded applications execute millions of instructions and therefore millions of addresses to be predicted. This very challenging problem of neural network based prediction of large time series is approached in this paper by evaluating various neural network architectures based on the recurrent neural network paradigm with pre-processing based on the Self Organizing Map (SOM) classification technique.

Designing Early Warning System: Prediction Accuracy of Currency Crisis by Using k-Nearest Neighbour Method

Developing a stable early warning system (EWS) model that is capable to give an accurate prediction is a challenging task. This paper introduces k-nearest neighbour (k-NN) method which never been applied in predicting currency crisis before with the aim of increasing the prediction accuracy. The proposed k-NN performance depends on the choice of a distance that is used where in our analysis; we take the Euclidean distance and the Manhattan as a consideration. For the comparison, we employ three other methods which are logistic regression analysis (logit), back-propagation neural network (NN) and sequential minimal optimization (SMO). The analysis using datasets from 8 countries and 13 macro-economic indicators for each country shows that the proposed k-NN method with k = 4 and Manhattan distance performs better than the other methods.

Using the Keystrokes Dynamic for Systems of Personal Security

This paper presents a boarding on biometric authentication through the Keystrokes Dynamics that it intends to identify a person from its habitual rhythm to type in conventional keyboard. Seven done experiments: verifying amount of prototypes, threshold, features and the variation of the choice of the times of the features vector. The results show that the use of the Keystroke Dynamics is simple and efficient for personal authentication, getting optimum resulted using 90% of the features with 4.44% FRR and 0% FAR.

The Removal of Cu (II) Ions from Aqueous Solutions on Synthetic Zeolite NaA

In this study the adsorption of Cu (II) ions from aqueous solutions on synthetic zeolite NaA was evaluated. The effect of solution temperature and the determination of the kinetic parameters of adsorption of Cu(II) from aqueous solution on zeolite NaA is important in understanding the adsorption mechanism. Variables of the system include adsorption time, temperature (293- 328K), initial solution concentration and pH for the system. The sorption kinetics of the copper ions were found to be strongly dependent on pH (the optimum pH 3-5), solute ion concentration and temperature (293 – 328 K). It was found, the pseudo-second-order model was the best choice among all the kinetic models to describe the adsorption behavior of Cu(II) onto ziolite NaA, suggesting that the adsorption mechanism might be a chemisorptions process The activation energy of adsorption (Ea) was determined as Cu(II) 13.5 kJ mol-1. The low value of Ea shows that Cu(II) adsorption process by zeolite NaA may be an activated chemical adsorption. The thermodynamic parameters (ΔG0, ΔH0, and ΔS0) were also determined from the temperature dependence. The results show that the process of adsorption Cu(II) is spontaneous and endothermic process and rise in temperature favors the adsorption.

Critical Analysis of Decision Making Experience with a Machine Learning Approach in Playing Ayo Game

The major goal in defining and examining game scenarios is to find good strategies as solutions to the game. A plausible solution is a recommendation to the players on how to play the game, which is represented as strategies guided by the various choices available to the players. These choices invariably compel the players (decision makers) to execute an action following some conscious tactics. In this paper, we proposed a refinement-based heuristic as a machine learning technique for human-like decision making in playing Ayo game. The result showed that our machine learning technique is more adaptable and more responsive in making decision than human intelligence. The technique has the advantage that a search is astutely conducted in a shallow horizon game tree. Our simulation was tested against Awale shareware and an appealing result was obtained.

Influence of Social-Psychological Training on Selected Features of University Students

We presented results of research aimed on findings influence of social - psychological training (realized with students of Constantine the Philosopher University- future teachers within their undergraduate preparation) on the choice of intrapersonal and interpersonal features. After social- psychological training using Interpersonal Check List (ICL) we found out shift of behavior to more adaptive forms in categories, which are characterized by extroversive friendly behavior, willingness to cooperation, conformity regard to social situation, responsible and regardful behavior. Using State-Trait Anxiety Inventory (STAI) we found out the cut down of state anxiety and of trait anxiety. The report was processed within grants KEGA 3/5269/07 and VEGA 1/3675/06.

The Project of Three Photovoltaic Systems in an Italian Natural Park

The development of renewable energies - particularly energy from wind, water, solar power and biomass - is a central aim of the European Commission's energy policy. There are several reasons for this choice: renewable energies are sustainable, nonpolluting, widely available and clean. Increasing the share of renewable energy in the energy balance enhances sustainability. It also helps to improve the security of energy supply by reducing the Community's growing dependence on imported energy sources.In this paper it was studied the possibility to realize three photovoltaic systems in the Italian Natural Park “Gola della Rossa e di Frasassi". The first photovoltaic system is a grid-connected system for Services and Documentation Center of Castelletta with a nominal power of about 6 kWp. The second photovoltaic system is a grid-connected integrated system on the ticket office-s roof with a nominal power of about 4 kWp. The third project is set up by five grid-connected systems integrated on the roofs of the bungalows in Natural Park-s tourist camping with a nominal power of about 10 kWp. The electricity which is generated by all these plants is purchased according to the Italian program called “Conto Energia". Economical analysis and the amount of the avoided CO2 emissions are elaborated for these photovoltaic systems.

Currency Boards in Crisis: Experience of Baltic Countries

The European countries that during the past two decades based their exchange rate regimes on currency board arrangement (CBA) are usually analysed from the perspective of corner solution choice’s stabilisation effects. There is an open discussion on the positive and negative background of a strict exchange rate regime choice, although it should be seen as part of the transition process towards the monetary union membership. The focus of the paper is on the Baltic countries that after two decades of a rigid exchange rate arrangement and strongly influenced by global crisis are finishing their path towards the euro zone. Besides the stabilising capacity, the CBA is highly vulnerable regime, with limited developing potential. The rigidity of the exchange rate (and monetary) system, despite the ensured credibility, do not leave enough (or any) space for the adjustment and/or active crisis management. Still, the Baltics are in a process of recovery, with fiscal consolidation measures combined with (painful and politically unpopular) measures of internal devaluation. Today, two of them (Estonia and Latvia) are members of euro zone, fulfilling their ultimate transition targets, but de facto exchanging one fixed regime with another. The paper analyses the challenges for the CBA in unstable environment since the fixed regimes rely on imported stability and are sensitive to external shocks. With limited monetary instruments, these countries were oriented to the fiscal policies and used a combination of internal devaluation and tax policy measures. Despite their rather quick recovery, our second goal is to analyse the long term influence that the measures had on the national economy.

An Overview of Some High Order and Multi-Level Finite Difference Schemes in Computational Aeroacoustics

In this paper, we have combined some spatial derivatives with the optimised time derivative proposed by Tam and Webb in order to approximate the linear advection equation which is given by = 0. Ôêé Ôêé + Ôêé Ôêé x f t u These spatial derivatives are as follows: a standard 7-point 6 th -order central difference scheme (ST7), a standard 9-point 8 th -order central difference scheme (ST9) and optimised schemes designed by Tam and Webb, Lockard et al., Zingg et al., Zhuang and Chen, Bogey and Bailly. Thus, these seven different spatial derivatives have been coupled with the optimised time derivative to obtain seven different finite-difference schemes to approximate the linear advection equation. We have analysed the variation of the modified wavenumber and group velocity, both with respect to the exact wavenumber for each spatial derivative. The problems considered are the 1-D propagation of a Boxcar function, propagation of an initial disturbance consisting of a sine and Gaussian function and the propagation of a Gaussian profile. It is known that the choice of the cfl number affects the quality of results in terms of dissipation and dispersion characteristics. Based on the numerical experiments solved and numerical methods used to approximate the linear advection equation, it is observed in this work, that the quality of results is dependent on the choice of the cfl number, even for optimised numerical methods. The errors from the numerical results have been quantified into dispersion and dissipation using a technique devised by Takacs. Also, the quantity, Exponential Error for Low Dispersion and Low Dissipation, eeldld has been computed from the numerical results. Moreover, based on this work, it has been found that when the quantity, eeldld can be used as a measure of the total error. In particular, the total error is a minimum when the eeldld is a minimum.

Weld Defect Detection in Industrial Radiography Based Digital Image Processing

Industrial radiography is a famous technique for the identification and evaluation of discontinuities, or defects, such as cracks, porosity and foreign inclusions found in welded joints. Although this technique has been well developed, improving both the inspection process and operating time, it does suffer from several drawbacks. The poor quality of radiographic images is due to the physical nature of radiography as well as small size of the defects and their poor orientation relatively to the size and thickness of the evaluated parts. Digital image processing techniques allow the interpretation of the image to be automated, avoiding the presence of human operators making the inspection system more reliable, reproducible and faster. This paper describes our attempt to develop and implement digital image processing algorithms for the purpose of automatic defect detection in radiographic images. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of global and local preprocessing and segmentation methods must be appropriated.

Design and Simulation of Low Noise Amplifier Circuit for 5 GHz to 6 GHz

In first stage of each microwave receiver there is Low Noise Amplifier (LNA) circuit, and this stage has important rule in quality factor of the receiver. The design of a LNA in Radio Frequency (RF) circuit requires the trade-off many importance characteristics such as gain, Noise Figure (NF), stability, power consumption and complexity. This situation Forces desingners to make choices in the desing of RF circuits. In this paper the aim is to design and simulate a single stage LNA circuit with high gain and low noise using MESFET for frequency range of 5 GHz to 6 GHz. The desing simulation process is down using Advance Design System (ADS). A single stage LNA has successfully designed with 15.83 dB forward gain and 1.26 dB noise figure in frequency of 5.3 GHz. Also the designed LNA should be working stably In a frequency range of 5 GHz to 6 GHz.

A Secure Semi-Fragile Watermarking Scheme for Authentication and Recovery of Images Based On Wavelet Transform

Authentication of multimedia contents has gained much attention in recent times. In this paper, we propose a secure semi-fragile watermarking, with a choice of two watermarks to be embedded. This technique operates in integer wavelet domain and makes use of semi fragile watermarks for achieving better robustness. A self-recovering algorithm is employed, that hides the image digest into some Wavelet subbands to detect possible malevolent object manipulation undergone by the image (object replacing and/or deletion). The Semi-fragility makes the scheme tolerant for JPEG lossy compression as low as quality of 70%, and locate the tempered area accurately. In addition, the system ensures more security because the embedded watermarks are protected with private keys. The computational complexity is reduced using parameterized integer wavelet transform. Experimental results show that the proposed scheme guarantees the safety of watermark, image recovery and location of the tempered area accurately.

Social Software Approach to E-Learning 3.0

In the present paper, we-ll explore how social media tools provide an opportunity for new developments of the e-Learning in the context of managing personal knowledge. There will be a discussion how social media tools provide a possibility for helping knowledge workersand students to gather, organize and manage their personal information as a part of the e-learning process. At the centre of this social software driven approach to e-learning environments are the challenges of personalization and collaboration. We-ll share concepts of how organizations are using social media for e-Learning and believe that integration of these tools into traditional e-Learning is probably not a choice, but inevitability. Students- Survey of use of web technologies and social networking tools is presented. Newly developed framework for semantic blogging capable of organizing results relevant to user requirements is implemented at Varna Free University (VFU) to provide more effective navigation and search.

A Security Model of Voice Eavesdropping Protection over Digital Networks

The purpose of this research is to develop a security model for voice eavesdropping protection over digital networks. The proposed model provides an encryption scheme and a personal secret key exchange between communicating parties, a so-called voice data transformation system, resulting in a real-privacy conversation. The operation of this system comprises two main steps as follows: The first one is the personal secret key exchange for using the keys in the data encryption process during conversation. The key owner could freely make his/her choice in key selection, so it is recommended that one should exchange a different key for a different conversational party, and record the key for each case into the memory provided in the client device. The next step is to set and record another personal option of encryption, either taking all frames or just partial frames, so-called the figure of 1:M. Using different personal secret keys and different sets of 1:M to different parties without the intervention of the service operator, would result in posing quite a big problem for any eavesdroppers who attempt to discover the key used during the conversation, especially in a short period of time. Thus, it is quite safe and effective to protect the case of voice eavesdropping. The results of the implementation indicate that the system can perform its function accurately as designed. In this regard, the proposed system is suitable for effective use in voice eavesdropping protection over digital networks, without any requirements to change presently existing network systems, mobile phone network and VoIP, for instance.

A Parameter-Tuning Framework for Metaheuristics Based on Design of Experiments and Artificial Neural Networks

In this paper, a framework for the simplification and standardization of metaheuristic related parameter-tuning by applying a four phase methodology, utilizing Design of Experiments and Artificial Neural Networks, is presented. Metaheuristics are multipurpose problem solvers that are utilized on computational optimization problems for which no efficient problem specific algorithm exist. Their successful application to concrete problems requires the finding of a good initial parameter setting, which is a tedious and time consuming task. Recent research reveals the lack of approach when it comes to this so called parameter-tuning process. In the majority of publications, researchers do have a weak motivation for their respective choices, if any. Because initial parameter settings have a significant impact on the solutions quality, this course of action could lead to suboptimal experimental results, and thereby a fraudulent basis for the drawing of conclusions.

Hybrid Method Using Wavelets and Predictive Method for Compression of Speech Signal

The development of the signal compression algorithms is having compressive progress. These algorithms are continuously improved by new tools and aim to reduce, an average, the number of bits necessary to the signal representation by means of minimizing the reconstruction error. The following article proposes the compression of Arabic speech signal by a hybrid method combining the wavelet transform and the linear prediction. The adopted approach rests, on one hand, on the original signal decomposition by ways of analysis filters, which is followed by the compression stage, and on the other hand, on the application of the order 5, as well as, the compression signal coefficients. The aim of this approach is the estimation of the predicted error, which will be coded and transmitted. The decoding operation is then used to reconstitute the original signal. Thus, the adequate choice of the bench of filters is useful to the transform in necessary to increase the compression rate and induce an impercevable distortion from an auditive point of view.

From e-Government to e-Democracy Challenges and Opportunities for Development in Montenegro

Internet today has a huge impact on all aspects of life, and also in the area of the broader context of democracy, politics and politicians. If democracy is freedom of choice, there are a number of conditions that can ensure in practice the freedom to be achieved and realized. These preconditions must be achieved regardless of the manner of voting. The key contribution of ICT to achieve freedom of choice is that technology enables the correlation of the citizens and elected representatives on the better way than it was possible without the Internet. In this sense, we can say that the Internet and ICT are changing significantly, and potentially improving the environment in which democratic processes are taking place. This paper aims to describe trends in use of ICT in democratic processes, and analyzes the challenges for implementation of e-Democracy in Montenegro

A Proposed Framework for Visualization to Teach Computer Science

Computer programming is considered a very difficult course by many computer science students. The reasons for the difficulties include cognitive load involved in programming, different learning styles of students, instructional methodology and the choice of the programming languages. To reduce the difficulties the following have been tried: pair programming, program visualization, different learning styles etc. However, these efforts have produced limited success. This paper reviews the problem and proposes a framework to help students overcome the difficulties involved.

A Discrete Choice Modeling Approach to Modular Systems Design

The paper proposes an approach for design of modular systems based on original technique for modeling and formulation of combinatorial optimization problems. The proposed approach is described on the example of personal computer configuration design. It takes into account the existing compatibility restrictions between the modules and can be extended and modified to reflect different functional and users- requirements. The developed design modeling technique is used to formulate single objective nonlinear mixedinteger optimization tasks. The practical applicability of the developed approach is numerically tested on the basis of real modules data. Solutions of the formulated optimization tasks define the optimal configuration of the system that satisfies all compatibility restrictions and user requirements.