Workshop time management system

The Workshop Time Management System is a web-based application that is specially built for the third party logistics provider and workshops, with the goals to improve efficiency and shortening processing time by automating all processes and workflows involved in a central application. This project will focus more on human resources planning and efficiency such as pending job assignment, mechanic job log, task efficiency, evaluation of mechanic performance and mechanic duty shift control. By implementing the new solutions to the system, the maintenance staff will be better informed of pending jobs or faults at the workshop whereas the mechanics will be able to access the necessary information instantly to rectify the problem. A number of improvements on the existing features will also be included, such as urgent task handling, vehicle quality inspection and job activation to ensure more accurate time estimation and further improve the flexibility of the system in handling the various situations. The project will be carried out systematically with the waterfall model of Software Development Life Cycle and Structured System Analysis and Design Methodology. The business process and environment is analyzed to enable a more thorough understanding of the problems, opportunities and directives that triggered the project. Overall, this project is expected to deliver a range of mission-critical applications, including a proprietary environmental compliance database for its corporate administrative staff, and a fleet management application for its vehicle maintenance crew at the workshop

Practical and user friendly tool of analytic hierarchy process for decision making

This paper discusses on the use of analytic hierarchy process (AHP) aiming at improving and enhancing the decision making process.Currently, the decision provided by user is referring to their opinion and experience.If there is a supported tool, normally mean for expert users or researchers.By using a practical and user friendly AHP tool, many users are benefited from the tool. There are three basic features of AHP called criteria, sub-criteria and alternative.These features consist of a combination of users experience and mathematical approach. The method aim to give users a decision making process according to the given problem. The results will suggest users on what is the best decision should be made.In order to test its applicability, a real world case study at Palm Oil Mill (POM) plant is used.A satisfactory result has confirmed the practicality and user friendliness of the tool

A Novel Image Encryption Using an Integration Technique of Blocks Rotation Based on the Magic Cube and the AES Algorithm

In recent years, several encryption algorithms have been proposed to protect digital images from cryptographic attacks. These encryption algorithms typically use a relatively small key space and therefore, provide safe, especially if they are of a dimension. In this paper proposes an encryption algorithm for a new image protection scheme based on the rotation of the faces of a Magic Cube. The original image is divided into six sub-images and these sub-images are divided amongst a number of blocks and attached to the faces of a Magic Cube. The faces are then scrambled using rotation of the Magic Cube. Then the rotated image is fed to the AES algorithm which is applied to the pixels of the image to encrypt the scrambled image. Finally, experimental results and security analysis show that the proposed image encryption scheme not only encrypts the picture to achieve perfect hiding, but the algorithm can also withstand exhaustive, statistical and differential attacks

Convolutional-NN and Word Embedding for Making an Effective Product Recommendation Based on Enhanced Contextual Understanding of a Product Review

E-commerce is one of the most popular service applications in the world in the last decade. It has become a revolutionary model from traditional shopping transaction to entire internet commerce. E-commerce needs essential artificial intelligence (AI) to provide the customer with information about a product, called a recommendation machine. Collaborative filtering is a model of a recommendation algorithm that relies on rating as the fundamental calculation to make a recommendation. It has been successfully implemented in e-commerce. Even so, this model has a weakness in sparse product data in which the rating number is very low or sparse. Mostly, only less than 3% of the total user population rate a product, leading to the rise of sparse data. A text sentence document is a part of customers’ feedback that can be converted into a product rating.  According to a traditional approach, bag of word and lexicon model are ignored in a contextual approach. This experiment, it developed a new model to increase the contextuality of text sentences, leading to a more effective rating prediction. We employed a kind of convolutional neural network to generate item latent factor vectors that could be incorporated with probabilistic matrix factorization to make rating prediction. Our method outperformed several previous works based on a metric evaluation using the Root Mean Squared Error (RMSE). In this experiment, we analyzed MovieLens and IMDB datasets, which contained a movie product review

Paper Survey And Example Of Collaborative Filtering Implementation In Recommender System

The development of recommender system research has expanded to various applications. Recommender system issues can be analyzed from many perspectives such as user rating strategy, user preferences and text mining. User rating strategy and user preferences are associated with user behavior to find suitable recommended items. Text mining is considered the most related field to database management and web search queries. The relation to the database query, it needs suitable query algorithm web search and user profiling strategy. Our paper survey showed that Latent Semantic Analysis (LSA) method has a better chance to solve recommender system issues especially in web search and user profiling. By comparing with restaurant samples, we describe adequate measures to evaluate the recommender system quality in user profiling. Some algorithm can provide benefits to improve the quality of personalized recommendations that are tailored to user attributes. Further research can provide newer algorithm to handle cold start problem and sparse data from both text mining and mining computation perspectives

Exam timetabling using graph colouring approach

Timetabling at large covering many different types of problems which have their own unique characteristics. In education, the three most common academic timetabling problems are school timetable, university timetable and exam timetable. Exam timetable is crucial but difficult to be done manually due to the complexity of the problem. The main problem includes dual academic calendar, increasing student enrolments and limitations of resources. This study presents a solution method for exam timetable problem in centre for foundation studies and extension education (FOSEE), Multimedia University, Malaysia. The method of solution is a heuristic approach that include graph colouring, cluster heuristic and sequential heuristic

Novel Computerized Halal Pharmaceuticals Supply Chain Framework for Warehouse and Procurement

Computerized systems and software technology are extensively used to enhance manufacturing and supply chain performance in the pharmaceutical industry. The halal pharmaceuticals industry is growing and more study is required to cater this evolving industry as technology progresses and advanced computerized systems are introduced in the manufacturing sector to increase productivity. Enforcement and religious authorities require a documented guideline to enforce halal certification whenever a manual operation is substituted by a computerized system. The current halal pharmaceuticals certification guidelines by enforcement agencies in Malaysia and Indonesia mainly focus on manual operations. This paper shall propose a framework to manage the halal supply chain when computerized systems are being used for the warehouse and procurement module. The proposed framework is the outcome of a case study of a Malaysian pharmaceutical organization, Pharmaniaga Manufacturing Berhad in Bangi, Selangor

Evaluation Of e-Service Quality, Perceived Value On Customer Satisfaction And Customer Loyalty: A Study In Indonesia

Even though customer loyalty has been studied anywhere, there is lack of information to explain why online customers is reluctant to use online platform. This study observed e-Service quality effect toward customer loyalty and satisfaction. This study used Structural Equation Modelling (SEM) method with 5-items Likert rating. It consisted of chi-square, probability level, CMIN/df, CFI, RMSEA, TLI, GFI, AGFI as the indicator of model eligibility. Our study found that adequate information and informative sites will lead to customer satisfaction which representing e-Service quality in ecommerce website. A higher e-Service quality will impact to customer satisfaction to use frequently the ecommerce sites as their choice. In addition, e-Service quality impacted e-Commerce customer satisfaction and customer loyalty mediated by customer’s perceived value. Our study contributed to expand information for e-Commerce practitioner to implement e-Service quality to increase their customer loyalty. However, this study does not observe the product attributes or specific ecommerce type. Future research can propose such model especially for better and accurate recommendation

Correlated Node Behavior Model based on Semi Markov Process for MANETS

This paper introduces a new model for node behavior namely Correlated Node Behavior Model which is an extension of Node Behavior Model. The model adopts semi Markov process in continuous time which clusters the node that has correlation. The key parameter of the process is determined by five probabilistic parameters based on the Markovian model. Computed from the transition probabilities of the semi-Markov process, the node correlation impact on network survivability and resilience can be measure quantitatively. From the result, the quantitative analysis of correlated node behavior on the survivability is obtained through mathematical description, and the effectiveness and rationality of the proposed model are verified through numerical analysis. The analytical results show that the effect from correlated failure nodes on network survivability is much severer than other misbehaviors

Operational Design And Modelling Of Fire Event Tracking System In Wireless Sensor Networks

In recent years, WSNs have been widely used for monitoring of environmental changes as they are capable of combining their sensing of a phenomenon with their computational functions and operate with limited resources to accomplish an intended task. Sensors can cooperatively monitor the surrounding environment and provide data that help in realizing the time evolution of the phenomenon and anticipating its effects. Consequently, such information would facilitate performing control actions that meet the predetermined goals. As distributed computing enables the exchange of real time data statistics obtained from various sources that need to be combined together to infer real abnormal conditions for management decisions. As tracking of an event depends on the event type, high-accuracy localization of an event such as fire is a serious challenge, where most of traditional detection systems depend on visualization (cameras) in making their control decision. Moreover, those systems concern the continuous detection of fire and do not provide reliable and feasible mechanism for tracking fire spread. This paper presents the design and modelling of a fire event tracking system that consists of indoor distributed sensor nodes and a powerful intelligent processing unit (controller) to detect fire events and compute information to provide desired safety decisions. Whenever the temperature in a premise increases, the system deploys cooperative centralized control functions to collect and process data statistics related to the fire. It exchanges direction, velocity, and/or position to take proper decision such as evacuating people from fire areas to a safe exit