Zuraida Abal Abas

Development of a Fingerprint Gender Classification Algorithm Using Fingerprint Global Features

In forensic world, the process of identifying and calculating the fingerprint features is complex and take time when it is done manually using fingerprint laboratories magnifying glass. This study is meant to enhance the forensic manual method by proposing a new algorithm for fingerprint global feature extraction for gender classification. The result shows that the new algorithm gives higher acceptable readings which is above 70% of classification rate when it is compared to the manual method. This algorithm is highly recommended in extracting a fingerprint global feature for gender classification process.

Simulation for Applied Graph Theory Using Visual C

The tool for visualization is Microsoft Visual C++. This popular software has the standard C++ combined with the Microsoft Foundation Classes (MFC) libraries for Windows visualization. This book explains how to create a graph interactively, solve problems in graph theory with minimum number of C++ codes, and provide friendly interfaces that makes learning the topics an interesting one. Each topic in the book comes with working Visual C++ codes which can easily be adapted as solutions to various problems in science and engineering.

A New HMCR Parameter of Harmony Search for Better Exploration

As a meta-heuristic algorithm, Harmony Search (HS) algorithm is a population-based meta-heuristics approach that is superior in solving diversified large scale optimization problems. Several studies have pointed that Harmony Search (HS) is an efficient and flexible tool to resolve optimization problems in diversed areas of construction, engineering, robotics, telecommunication, health and energy. In this respect, the three main operators in HS, namely the Harmony Memory Consideration Rate (HMCR), Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing the local exploitation and the global exploration. These parameters influence the overall performance of HS algorithm, and therefore it is very crucial to fine turn them. However, when performing a local search, the harmony search algorithm can be easily trapped in the local optima. Therefore, there is a need to improve the fine tuning of the parameters. This research focuses on the HMCR parameter adjustment strategy using step function with combined Gaussian distribution function to enhance the global optimality of HS. The result of the study showed a better global optimum in comparison to the standard HS.

Data normalization for triangle features by adapting triangle nature for better classification

Geometry features especially triangle has been widely used in face, fingerprint, vehicle detection and digit recognition. Features from the triangle are used to generate useful features for classification processed. Recently, triangle features used in digit recognition has adopted angle as part of features. This has influenced accuracy due to big gap between angle values and other feature values such as ratio and gradient of sides. To overcome this issue, data normalization can be used to address the issue. Experiments have been made using existing normalization techniques such as Z-score, Minimax and libSVM scale function. Experiments have been conducted using Z-Score and libSVM scale function, but results of classification are worst compared to triangle features without normalization. Thus, the results of classification can be improved by proposed a new technique of normalization based on nature of triangle geometry. In this paper, we have proposed a new normalization technique by adopting the nature of triangle geometry. Datasets HODA, MNIST, IFHCDB and BANGLA digit have been chosen to extract triangle features. Then, we will apply normalization on the extracted features before classify them by using Support Vector Machine. The results shows normalization by adapting the nature of triangle geometry gives better result compared to other techniques. The proposed normalization technique only applies to Cartesian Plane Zone that contributes 45 features. The benchmarking for other researchers should refer to our 25 zones that give 225 features of triangle geometry.

Internet of Things and Healthcare Analytics for Better Healthcare Solution: Applications and Challenges

The total number of population in the world will keep on increasing. This will eventually pose challenges towards quality of life for example issues related to healthcare. Hence, a proper solution needs to be devised in order to face the challenges. Internet of Things (IoT), which is one of the digital technologies, that is becoming a trend now can offer promising solution. This paper serves as a short communication in introducing IoT and its application in healthcare domain as well as the analytics combined with the technology. Some examples are presented according to the categories of the application. It must be noted that the analytics play an important role in making the IoT healthcare as a comprehensive solution. At the end of the paper, challenges in making this digital as an accessible solution is discussed.

Modified Parameters of Harmony Search Algorithm for Better Searching

The scheduling and rostering problems are deliberated as integrated due to they depend on each other whereby the input of rostering problems is a scheduling problems. In this research, the integrated scheduling and rostering bus driver problems are defined as maximising the balance of the assignment of tasks in term of distribution of shifts and routes. It is essential to achieve is fairer among driver because this can bring to increase in driver levels of satisfaction. The latest approaches still unable to address the fairness problem that has emerged, thus this research proposes a strategy to adopt an amendment of a harmony search algorithm in order to address the fairness issue and thus the level of fairness will be escalate. The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems. In this respect, the three main operators in HS, namely the Harmony Memory Consideration Rate (HMCR), Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration. These parameters influence the overall performance of the HS algorithm, and therefore it is crucial to fine-tune them. The contributions to this research are the HMCR parameter using step function while the fret spacing concept on guitars that is associated with mathematical formulae is also applied in the BW parameter. The model of constant step function is introduced in the alteration of HMCR parameter. The experimental results revealed that our proposed approach is superior than parameter adaptive harmony search algorithm. In conclusion, this proposed approach managed to generate a fairer roster and was thus capable of maximising the balancing distribution of shifts and routes among drivers, which contributed to the lowering of illness, incidents, absenteeism and accidents.

Fingerprint Gender Classification using Univariate Decision Tree (J48)

Data mining is the process of analyzing data from a different category. This data provide information and data mining will extracts a new knowledge from it and a new useful information is created. Decision tree learning is a method commonly used in data mining. The decision tree is a model of decision that looklike as a tree-like graph with nodes, branches and leaves. Each internal node denotes a test on an attribute and each branch represents the outcome of the test. The leaf node which is the last node will holds a class label. Decision tree classifies the instance and helps in making a prediction of the data used. This study focused on a J48 algorithm for classifying a gender by using fingerprint features. There are four types of features in the fingerprint that is used in this study, which is Ridge Count (RC), Ridge Density (RD), Ridge Thickness to Valley Thickness Ratio (RTVTR) and White Lines Count (WLC). Different cases have been determined to be executed with the J48 algorithm and a comparison of the knowledge gain from each test is shown. All the result of this experiment is running using Weka and the result achieve 96.28% for the classification rate.