With the contributions of computer technology, digital learning has evolved into a stage of mobile learning. However, school classes require teachers to perform face-to-face humanized lectures. Digital learning remains to function as a tool for assisted teaching. Few studies have investigated what proportions digital learning should occupy in teaching activities. In this study, to investigate the optimal proportion of face-to-face instructions and digital learning, we conducted a one-semester teaching experiment on two classes of students in the informatics department in a public vocational high school in Taipei City. In addition, the Kruskal-Wallis one-way analysis of variance was adopted for the statistical analysis to determine the optimal blending proportions. Our results indicate that optimal effects are achieved at a time ratio of 2:1 of traditional face-to-face teaching to digital learning.

Quality is key term to be considered when developing the Web applications. If this is not adequately measured; there will be little to force users to use web applications. The focus of Web2.0 is to enhance the interactions between the application and end users and among users. The main challenge of this research is to identify the key quality attributes that gain the end user attention towards the Web applications. There are many Quality Models available for measuring the W2A (Web2.0 Applications). This paper has a critical review of the previously defined quality models. It defines a theoretical quality model containing essential attributes to assess the quality of W2A.

In the article dimensional lexicographic noncooperative games are defined for the players' for which there exists a characteristic function . Some main features are proved of function in a lexicographic case. A lexicographic cooperative game is called a couple, whereis a real vector-function on subsets and the following conditions are fulfilled =O; Such cooperative game is denoted by . imputation and its set is defined in game. It is proved that is nonempty and its full characterisation is given. Domination over set is defined. Thus, the main foundations are given, according to this, it is possible to explore the main principles of optimality.

The main objective of this paper is to suggest a model for improving and retaining the highly qualified teachers in higher technical education. There are numerous researches going on all over the world regarding the key quality factors which are directly linked with teacher’s performance and the methods to improve them. Whatever the methods and measures, the teacher’s active participation and dedication is very important to achieve these objectives. A detailed questionnaire was distributed to highly qualified and experienced teachers who are working in engineering colleges for more than five years. Since the variables in this study are quality factors, the collected data is analyzed using the fuzzy logic and inference is drawn for getting more accurate results compared to probability study of the same case. Based on the results obtained from fuzzy inference system, a new model called Adaptive Performance-Incentive-Development (PID) control system for improving the quality as well as retaining the highly qualified teachers in the teaching profession is created.

Several experimental studies revealed that expert systems have been successfully applied in real world domains such as medical diagnoses, traffic control, and many others. However, one of the major drawbacks of classic expert systems is their reliance on human domain experts which require time, care, experience and accuracy. This shortcoming also may result in building knowledge bases that may contain inconsistent rules or contradicting rules. To treat the abovementioned we intend to propose and develop automated methods based on data mining called Associative Classification (AC) that can be easily integrated into an expert system to produce the knowledge base according to hidden correlations in the input database. The methodology employed in the proposed expert system is based on learning the rules from the database rather than inputting the rules by the knowledge engineer from the domain expert and therefore, care and accuracy as well as processing time are improved. The proposed automated expert system contains a novel learning method based on AC mining that has been evaluated on Islamic textual data according to several evaluation measures including recall, precision and classification accuracy. Furthermore, five different classification approaches: Decision trees (C4.5, KNN, SVM, MCAR and NB) and the proposed automated expert system have been tested on the Islamic data set to determine the suitable method in classifying Arabic texts.

This paper proposes a four stage, denoising, feature extraction, optimization and classification method for detection of premature ventricular contractions. In the first stage, we investigate the application of wavelet denoising in noise reduction of multi-channel high resolution ECG signals. In this stage, the Stationary Wavelet Transform is used. Feature extraction module extracts ten ECG morphological features and one timing interval feature. Then a number of radial basis function (RBF) neural networks with different value of spread parameter are designed and compared their ability for classification of three different classes of ECG signals. Genetic Algorithm is used to find best value of RBF parameters. A classification accuracy of 100% for training dataset and 95.66% for testing dataset and an overall accuracy of detection of 95.83% were achieved over seven files from the MIT/BIH arrhythmia database.

Different optimization techniques have been used to solve Sudoku. Zong Woo Geem have applied harmony search in Sudoku to get better result. He has taken a Sudoku and time complexity has been optimized by different values of parameters. But, he has not given way of solution in details. He has also not given any idea to recognize the level of Sudoku. In this paper, an algorithm has been proposed based on harmony search to solve and identify the Sudoku efficiently. It has been observed that time complexity i.e. the maximum number of iteration has been reduced by choosing appropriate parameter values. The level of Sudoku has also been identified using probability metric. Finally, the number of iterations has been calculated with different values of parameters and the level of different Sudoku has been identified.

Microcontrollers and FPGAs both are widely used in digital system design. Microcontroller-based instruments are becoming increasingly widespread. This paper presents design and implementation of a new low-cost and minimum embedded board based on ATMEGA32L AVR microcontroller and Spartan-3 (XCS400-4PQG208C) FPGA in two layers with mount elements on top and button of board. Using of AVR microcontroller in proposed board it adds many features include Analog to Digital Converter (ADC), Digital to Analog Converter (DAC), 32 Kbytes flash memory, 2 Kbytes SRAM, 1024 bytes EEPROM memory. The design goal was to implement as many as possible low-cost and minimum size of the board, also to receive and process input signals in a short time period as real time. The board features are; mount elements in two side of the board for minimization of proposed board and also place decoupling capacitors (by pass) for the FPGA in bottom layer of board strictly below this IC because they should be placed as close as possible to the power supply pins FPGA, use GND polygon layer in total top layer and microcomputer ground for FPGA in bottom layer, use two RS-232 serial port, one VGA connector, PS/2 serial port, and SPI serial port on FPGA, use MT48LC16M16A SDRAM-256MB(4*4MB*16), and XCF02S configuration PROM. Size of the proposed embedded board is 10cm*15cm thus this board was optimized of aspect cost, performance, power, weight, and size.