Nanna Suryana Herman

An efficient compact Tchebichef Moment for image compression

Orthogonal moment functions have long been used in image analysis. This paper proposes a novel approach based on discrete orthogonal Tchebichef Moment for efficient image compression. The method incorporates simplified mathematical framework techniques using matrices, as well as a block-wise reconstruction technique to eliminate possible occurrences of numerical instabilities at higher moment orders. The comparison between Tchebichef Moment compression and JPEG compression has been done. The results show significant advantages for Tchebichef Moment in terms of its image quality and compression rate. Tchebichef moment provides a more compact support to the image via sub-block reconstruction for compression. Tchebichef Moment Compression has clear potential to perform better for broader domain on real digital images and graphically generated images.

Genetic Algorithms and designing membership function in Fuzzy Logic Controllers

This paper studies the use of Genetic Algorithms (GA) in the design of Fuzzy Logic Controllers (FLC) and show how population size, probability of crossover and rate of mutation can effect the performance of the GA. The comparison of various parameters shows that GA is helpful in improving the performance of FLC. A fuzzy logic is fully defined by its membership function. What is the best to determine the membership function is the first question that has be tackled. Thus it is important to select the accurate membership functions but these methods possess one common weakness where conventional FLC use membership function generated by human operators. The membership function selection process is done with trial and error and it runs step by step which is too long in completing the problem. This research develops a system that may help users to determine the membership function of FLC using the technique of GA optimization for the fastest processing in completing the problems. The data collection is based on the simulation results and the results refer to the transient response specification is maximum overshoot. From the results presented, the system which we developed is very helpful to determine membership function and it is clear that the GA is very promising in improving the performance of the FLC to get more accurate in order to find the optimum result.

A Study of Tracing and Writing Performance of Novice Students in Introductory Programming

The tasks of programming include complex knowledge and skills that is, from understanding problems to evaluating validity of program. Novice students often face difficulties in learning programming due to various issues and the nature of the subject, which can be vague and invisible. A survey was conducted on 294 students from two universities to study novices’ problems in dealing with tracking the logical flow and writing a simple code. The average score for tracking and writing skills were quite disappointing. Students were only able to master the static part of programming knowledge. They lacked the knowledge in understanding and tracing the dynamic behavior of the program. This research attempts to propose a model to shift the internal working memory load of students through integrated visualization tools that can reveal the dynamic behavior of programs and related concepts that appear in each level of program abstractions.

CNC PCB drilling machine using Novel Natural Approach to Euclidean TSP

Nowadays, many industries use the Computerized Numerical Control (CNC) for Printed Circuit Board (PCB) drilling machines in industrial operations. It takes a long time to find optimal tour for large number of nodes (up to thousands). To achieve more effective results, optimization systems approach is required to be equipped in drilling machine. Euclidean Traveling Salesman Problem (TSP) is one of optimization method that gives fast near optimal solution for the drilling machine movement using novel friendly techniques. This paper describes the development of that CNC PCB drilling machine with novel approach to Euclidean TSP. This design can be widely applied to various CNC PCB drilling machines in small and medium scale manufacturing industries.

Clustering Strategy to Euclidean TSP Hamilton Path Role in Tour Construction

TSP arises in many applications such as transportation, manufacturing and various logistics and scheduling. This problem has caught much attention of mathematicians and computer scientists. A clustering strategy will decompose TSP into subgraphs and form clusters, so it may reduce problem size into smaller problem. The primary objective of this research is to produce a better clustering strategy that fit into Euclidean TSP. Hamilton path play important role to construct Euclidean TSP tour in this approach. Hamilton will be applied within clusters and inter clusters. Hamilton path construction will be proceed after clustering process, followed by producing inter cluster connection algorithm to find global tour. This approach is capable of producing fast solution result with error less than 10% compare to best known solution in TSPLib. This paper proposes an improvement to a hierarchical clustering algorithm in searching for Euclidean TSP solution.

Preliminary design and development of industrial inspection e-monitoring system

This paper discusses on the initial design and development of industrial inspection e-monitoring system (IIEMS). IIEMS is an intelligent web-based system that monitors defect occurs in the production line. The defect is collected from targeted machines, which are considered as the most critical one. By setting all the related parameters, defects will be logged into the system. Then, the system will send a message through email and personal data assistant (PDA) to the person in charge. An artificial neural network (ANN) will be used to classify the severity of the defect. According to the result, appropriate actions are performed. Throughout this paper, initial analysis, design and development of the system are explained. This includes the requirement analysis, logical and interface design. In the development phase, an early stage of the system development is reported. An overview of the system prototype and some observations based on the initial results are also discussed.

An enhancement of the spectral statistical test for randomness

Random numbers play essential roles in cryptography, modeling and simulation applications. NIST statistical test suite for randomness is the most comprehensive set of random tests. It has been popular and used as a benchmark test for randomness. One of the random tests is spectral test. There has been serious problem in spectral test as pointed out by few researchers. In this paper, further theoretical improvement shall be proposed on the spectral test based on computational observation being made on random noise. A recommendation on the spectral test setting for short cryptographic keys shall also be made.

Initial Result of Clustering Strategy to Euclidean TSP

There has been growing interest in studying combinatorial optimization problems by clustering strategy, with a special emphasis on the traveling salesman problem (TSP). Since TSP naturally arises as a sub problem in many transportation, manufacturing and various logistics application, this problem has caught much attention of mathematicians and computer scientists. A clustering strategy will decompose TSP into subgraph and form clusters, so it may reduce the TSP graph to smaller problem. The primary objective of this research is to produce a better clustering strategy that fit into Euclidean TSP. General approach for this research is to produce an algorithm for generating clusters and able to handle large size cluster. The next step is to produce Hamilton path algorithm and followed by inter cluster connection algorithm to form global tour. The significant of this research is solution result error less than 10% compare to best known solution (TSPLIB) and there is an improvement to a hierarchical clustering strategy in order to fit in such the Euclidean TSP method.

The Application of Genetic Algorithm into Membership Function FLC Used Floating Point

This study investigates the use of Genetic Algorithms (GA) to the design and implementation of Fuzzy Logic Controllers (FLC). A fuzzy logic is fully defined by its membership function. What is the best to determine the membership function is the first question that has been tackled. Thus it is important to select the accurate membership functions but these methods possess one common weakness where conventional FLC use membership function generated by human operators. The membership function selection process is done with trial and error and it runs step by step which is too long in completing the problem. This research develops a system that may help users to determine the membership function of FLC using the technique of GA optimization for the fastest processing in completing the problems. The data collection is based on the simulation results and the results refer to the transient response specification is maximum overshoot. From the results presented, the system which we developed is very helpful to determine membership function and it is clear that GA is very promising in improving the performance of the FLC to get more accurate in order to find the optimum result.

Sparse coded decomposition for single image-based specular removal

In this paper, we propose a method to separate diffuse and specular images from a single image based on sparse representation. The proposed method relax the recent sparse-based technique for removing specular highlights that require multiple input images. Instead, we use only a single input image and then generate multiple specular-free images from this image. The specular removal problem is formulated as the recovery of a sparse representation and an outlier representation. From the obtained specular-free images, a dictionary is reconstructed as the basis function for sparse representation. The sparse signal and the dictionary is used to estimate diffuse image while the specular image is obtained from the outlier. The sparse coding was solved using alternating direction method of multiplier. In addition, a new variant of the specular-free image based on XYZ color space is also proposed to improve sparse representation. The experimental results showed that this method outperformed the accuracy of standard specular removal methods.