Earticle

The purpose of this study was to develop e-learning content for advertising theory applying Gagné's Nine Events of Instruction, and to apply it to advertising courses offered in college programs. In advertising courses, emotional appeals based on visual images and multimedia materials are becoming more important. In addition, e-learning content is becoming important in educational programs, but most of the content is not based upon the principles of instruction models for the learners. This study, therefore, has developed e-learning content for advertising theory while applying Gagné’s ‘Nine Events of Instruction’. The results of this research indicate how Gagné's principles can be applied to content for advertising theory. To measure the content’s efficiency, questionnaires given to 120 advertising majors were analyzed. The results can be summarized as follows. First, the e-learning content for advertising theory had positive learning effects on the students. Second, Gagné’s Nine Steps of Instruction produced effective classroom participation among the students. Third, the content provided an effective learning atmosphere for the students, and learning activities were activated among the learners. In conclusion, this research has found that e-learning content applying Gagné's Nine Events of Instruction worked properly in the advertising classes. Most importantly, the effectiveness of the content depends upon the reflection of the principles on the instruction model.

Studying patterns in DNA sequences has been for years the subject of many research papers in bioinformatics. This paper evaluates two algorithms used for DNA comparison. Those are: Longest Common Substring and Subsequence (LCS, LCSS). Evaluation is performed based on the different code implementations for those two algorithms. Accuracy and performance are the two major criteria that are used for the evaluation of algorithms’ implementation. Results showed that while those two algorithms are popular, their implementations are not consistent through research papers or websites that use and implement those algorithms for DNA sequence comparison.

Case-based reasoning is an approach to problem solving and learning that has got a lot of attention over the last few years. This paper provides an overview of the case-based reasoning, brief outline on applicability of case-based reasoning to test suite, describing the various features of adaptive test suite system based on CBR framework will possess, focuses on benefits of adaptive approach over existing test case selection/retrieval approaches. The current work demonstrates the benefit of case base in reasoning approach for selecting test case or for testing the product during system testing and regression testing phases of the product.

It has been observed that with ever changing technologies need for different software methodologies also evolved. Different methodologies are actually developed to cater the needs of different software development technologies. These methodologies are so technology specific that it becomes a hazard whenever these are applied as generic methodologies for all type of applications. For example it is evident that none of these methodologies can fully cope with the development of expert system, soft computing systems or scientific applications. Moreover Rational Unified process, besides its numerous disadvantages, is very effective uniform and having wide range of applicability. On the other hand Cleanroom software Engineering is an efficient methodology which is aimed develop zero defect software. At the very mundane level it is very much unrealistic to think of a man-made product without any fault or any error, but a still believe that the efforts involved in Cleanroom software engineering at utmost level, or the ultimate efforts to remove the possibility of errors, with the mapping of RUP with CRM the effort for development is to be decreased. However the Cleanroom methodology is not the sole solution for the efficient and effective development of software.

Abrasive machining is a widely employed finishing process for different materials such as metals, ceramics, glass, rocks, etc to achieve close tolerances and good dimensional accuracy and surface integrity. High efficiency abrasive machining is one of the important techniques of advanced manufacture. Combined with raw and finishing machining, it can attain high material removal rate like turning, milling and planning. The difficult-to-grinding materials can also be ground by means of this method with high performance. In the present paper, development status and latest progresses on high efficiency abrasive machining technologies relate to high speed and super-high speed grinding, quick point-grinding, high efficiency deep-cut grinding, creep feed deep grinding, heavy-duty snagging and abrasive belt grinding were summarized. The efficiency and parameters range of these abrasive machining processes were compared. The key technologies of high efficiency abrasive machining, including grinding wheel, spindle and bearing, grinder, coolant supplying, installation and orientation of wheel and workpiece and safety defended, as well as intelligent monitor and NC grinding were investigated. It is concluded that high efficiency abrasive machining is a promising technology in the future.

Many effective watermarking algorithms have been proposed and implemented for multimedia. Human auditory system (HAS) is far more complex and sensitive than human visual system (HVS). For this reason, a few algorithms have been proposed for audio watermarking. In this paper, a new method of embedding gray image data into the audio signal and additive audio watermarking algorithm based on Fast Fourier Transformation (FFT) domain is proposed. First, the original audio is transformed into FFT domain. The FFT coefficients are divided into a fixed number of subsections and the energy of each subsection is calculated. Next, watermark is generated from gray image. Watermarks are then embedded into selected peaks of highest energy subsection. Experimental results demonstrate that the watermark is inaudible and this algorithm is robust to common operations of digital audio signal processing, such as noise addition, re-sampling, re-quantization and so on. To evaluate the performance of the proposed audio watermarking method, subjective and objective quality tests including Similarity (SIM) and Signal to Noise ratio (SNR) are conducted.

Motorcycles generate dissimilar sound patterns under different working conditions. Generally, the experienced mechanics in authorized service stations take test rides to hear the sounds produced to diagnose the faults. The presented work attempts to locate the faults in motorcycles based on the sound. The features are extracted using pseudospectra of sound signals. Integration is performed for estimating the areas under different segments of the spectral curve. Manhattan distance is used for comparing the test feature vectors with reference feature vectors for classification. The results are over 85% for fault location experiment with combination of 4 faults and over 90% for combinations of 3 faults and 2 faults. The proposed work can be extended to consider some more faults of motorcycles. The proposed work finds applications in surveillance, fault diagnosis of vehicles, machinery, musical instruments and the like.

Data Grid environment is a geographically distributed that deal with date-intensive application in scientific and enterprise computing. In data-intensive applications data transfer is a primary cause of job execution delay. Data access time depends on bandwidth, especially when hierarchy of bandwidth appears in network. Effective job scheduling can reduce data transfer time by considering hierarchy of bandwidth and also dispatching a job to where the needed data are present. Additionally, replication of data from primary repositories to other locations can be an important optimization step to reduce the frequency of remote data access. Objective of dynamic replica strategies is reducing file access time which leads to reducing job runtime. In this paper we develop a job scheduling policy, called SS (Scheduling strategy), and a dynamic data replication strategy, called DRS (Distributed Replication Strategy), to improve the data access efficiencies in a cluster grid. We study our approach and evaluate it through simulation. The results show that combination of SS and DRS has improved 17% over other combinations.

Merging query-hits in large scale systems, like P2P, is challenging and potentially complex because results have to be ranked with respect to each other while sources are heterogeneous and with no centralized control. To solve this problem, we advocated in [10] a knowledge-based approach relying on users’ profiles. A user profile includes information about past interests derived from the user past actions as well as information about peers from which results were obtained in the past for similar queries. Using a knowledge base can lead to the system obsolescence unless an effective approach is proposed to evolve this learned knowledge. Most used approaches for knowledge update are periodic and cannot react on user needs changes at the appropriate time. For this reason, we propose, in this paper, a controlled and distributed mechanism for knowledge evolution based on need observers. A need detector aims to detect the user new needs expressed in his queries, as well as the new resources. Experiments show a clear improvement of the system performance with our controlled mechanism.

Human Identification systems provide increased potential for security. In the absence of robust personal recognition schemes, these systems are vulnerable to the deception of an impostor. The proposed work in this paper is used to explore the merits of the Biometric Encryption approach of verifying identity, protecting privacy and ensuring security like secure access to buildings, computer systems, laptops, cellular phones and ATMs. An efficient and secured technique has been proposed by applying the hashed key on biometric template generated from input test image. The cryptographic key is generated independently and can be updated periodically via a re-enrollment procedure. The ease and protection provided by proposed technique will certainly help to promote widespread use of cryptographic systems. This technique not only outputs high entropy keys, but also conceals the original biometric data such that it is impossible to recover the biometric data even when the stored information in the system is open to an attacker.

Offshore software development outsourcing (OSDO) is an emerging business approach adopted by many software development organisations in developed countries. However significant outsourcing failure rates have also been reported. One of the major issues in is cultural distance which should be taken into account by software outsourcing organisations (vendors) in order to develop high quality software products and in turn to establish long lasting relationships with client organisations. The objective of this project is to develop an Intercultural Challenges Mitigation Model (ICCMM) in order to help organisations (vendors) to address the intercultural challenges in OSDO relationships. Two types of data will be collected in this research project: firstly, to identify Intercultural challenges/factors faced by vendors in OSDO relationships via Systematic Literature Review (SLR); and secondly, how one can implement these intercultural challenges/factors in OSDO relationships. An empirical study will be conducted in order to seek opinions of software outsourcing experts about the guidelines or practices required to implement these factors in vendor organisations. The probable outcome of this project will be an Intercultural challenges mitigation model to help OSDO vendors in addressing and identifying intercultural challenges occur in the OSDO relationships.