The Enforcement Role Of The Companies Commission Of Malaysia

This paper explores the role of the enforcement efforts undertaken by the Companies Commission of Malaysia (CCM) as a regulator of the Companies Act of 1965, which is entrusted to uphold and ensure good practices of corporate governance among Malaysian companies.  The paper attempts to provide an understanding on various enforcement actions in terms of the effectiveness and adequacy of the measures adopted by the CCM in promoting and improving the level of corporate governance practices in Malaysia.  CCM has adopted the Balanced Enforcement Approach to promote effective corporate governance practices among the Malaysian companies. An increasing compliance rate and greater corporate governance awareness at a level similar to other countries indicates at least aminimum success of the Balanced Enforcement Approach.  Indicated is the need for CCM to establish a benchmarking or ranking procedure in order to determine the level of corporate governance practices among companies in Malaysia

A review on feature extraction and feature selection for handwritten character recognition

The development of handwriting character recognition (HCR) is an interesting area in pattern recognition. HCR system consists of a number of stages which are preprocessing, feature extraction, classification and followed by the actual recognition. It is generally agreed that one of the main factors influencing performance in HCR is the selection of an appropriate set of features for representing input samples. This paper provides a review of these advances. In a HCR, the set of features plays as main issues, as procedure in choosing the relevant feature that yields minimum classification error. To overcome these issues and maximize classification performance, many techniques have been proposed for reducing the dimensionality of the feature space in which data have to be processed. These techniques, generally denoted as feature reduction, may be divided in two main categories, called feature extraction and feature selection. A large number of research papers and reports have already been published on this topic. In this paper we provide an overview of some of the methods and approach of feature extraction and selection. Throughout this paper, we apply the investigation and analyzation of feature extraction and selection approaches in order to obtain the current trend. Throughout this paper also, the review of metaheuristic harmony search algorithm (HSA) has provide

Investigating and developing the best method in shortest path for implementing a geographical information system (e-map) for Peninsular Malaysia

The shortest path is a part of the subject in the graph theory in the field of operational research. The idea of the shortest path is to find the best possible routes that linking between a given source and a destination. There are many algorithms have been designed to find these paths. The algorithms such as Djikstra, Bellman-Ford or Floyd- Warshall are difference from one to another due to the simplicity, effectiveness and duration of processing the nodes. This research will be focused on determining the best shortest path algorithm for the first possible best (fastest, safest and cheapest) route and also to search the other possible best routes. Assessment will be done by calculating the algorithm complexion and runtime using the computer. The fastest route can be attained via traveling on the highway. The safest route is might considered as a route with an accident free (data from police department). The cheapest route is a toll-free route, i.e., federal or state routes. The numbering assigned to every route in Peninsular Malaysia will be used to calculate and distinguish these routes and the alternatives. A development of GIS database is also involved in prototype covering the road network in Peninsular Malaysia (the e-map) will be developed to show the viability or validity of the findings. The system will be developed by using Microsoft Visual Basic and some supporting software. It is hoped the system will serve at test platform for the deeper research in the future

Sistem Carian Laluan Terpendek Destinasi Pelancongan Menggunakan Algoritma Floyd Warshall

Gra! adalah salah satu cabang matematik yang dapat digunakan dalam menyelesaikan masalah melibatkan pengiraan yang kompleks. Antara penggunaannya yang popular adalah penganalisaan sistem rangkaian jalan raya me/alui kaedah teori graf Sistem ini dibangunkan untuk menentukan laluan terpendek bagi destinasidestinasi pelancongan di negeri Kelantan. Maklumat anggaran berkaitanjarak, kos dan tempoh masa perjalanan bagi laluan terpendek akan turut disenaraikan melalui sistem yang dibangunkan. Algoritma Floyd Warshall digunakan untuk proses pencarian laluan terpendek bagi lokasi mula dan akhir yang dikehendaki pengguna sistem. Manakala perisian pengaturcaraan Microsoft Visual Basic 6.0 dan aplikasi Microsoft Access pula telah digunakan bagi membangunkan sistem

Facial Emotion Images Recognition Based On Binarized Genetic Algorithm-Random Forest

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Oriented Gradients) is utilized to extract from the images. In addition, the Binarized Genetic Algorithm (BGA) is utilized as a features selection in order to select the most effective features of HOG. Random Forest (RF) functions as a classifier to categories facial emotions in people according to the image samples. The facial human examples of photos that have been extracted from the Yale Face dataset, where it contains the eleven human facial expressions are as follows; normal, left light, no glasses, joyful, centre light, sad, sleepy, wink and surprised. The proposed system performance is evaluated relates to accuracy, sensitivity (i.e., recall), precision, F-measure (i.e., F1-score), and G-mean. The highest accuracy for the proposed BGA-RF method is up to 96.03%. Besides, the proposed BGA-RF has performed more accurately than its counterparts. In light of the experimental findings, the suggested BGA-RF technique has proved its effectiveness in the human facial emotions identification utilizing images