Hairulnizam Mahdin

An approach for removing redundant data from RFID data streams.

Radio frequency identification (RFID) systems are emerging as the primary object identification mechanism, especially in supply chain management. However, RFID naturally generates a large amount of duplicate readings. Removing these duplicates from the RFID data stream is paramount as it does not contribute new information to the system and wastes system resources. Existing approaches to deal with this problem cannot fulfill the real time demands to process the massive RFID data stream. We propose a data filtering approach that efficiently detects and removes duplicate readings from RFID data streams. Experimental results show that the proposed approach offers a significant improvement as compared to the existing approaches.

An Approach to Filtering Duplicate RFID Data Streams

In a system where distributed network of Radio Frequency Identification (RFID) readers are used to collaboratively collect data from tagged objects, a scheme that detects and eliminates redundant data streams is required. To address this problem, we propose an approach that is based on Bloom filter to detect duplicate readings and filter redundant RFID data streams. We have evaluated the performance of the proposed approach and compared it with existing approaches. The experimental results demonstrate that the proposed approach provides superior performance as compared to the baseline approaches.

An Approach to Filtering RFID Data Streams

RFID is gaining significant thrust as the preferred choice of automatic identification and data collection system. However, there are various data processing and management problems such as missed readings and duplicate readings which hinder wide scale adoption of RFID systems. To this end we propose an approach that filters the captured data including both noise removal and duplicate elimination. Experimental results demonstrate that the proposed approach improves missed data restoration process when compared with the existing method.

Economical and environmental operation of smart networked microgrids under uncertainties using NSGA-II

The future smart grid is expected to be an interconnected network of small-scale and self-contained micro-grids (MGs), in which renewable energy sources (RESs) play significant role in generation level as well as attract special attention to the aim at a friendly environmental society. In this paper, optimal operation of distributed generations (DGs) are analyzed probabilistically due to uncertainties of loads and RESs. In addition, probability distribution function (PDF) is used to describe the fluctuation model of input data. This paper establishes smart networked Microgrids (MGs) based on NSGA-II algorithm, including the lowest operating cost and the least pollutants emission. In order to make a comparison, the problem is converted to a single-objective function and then, solved by two heuristic algorithms, namely particle swarm optimization (PSO) and Imperialist competitive algorithm (ICA). Simulation results support the capability of the proposed algorithm to minimize jointly the operating power and pollution emission as compared to the results obtained by using current heuristics.

Indoor Navigation Using A* Algorithm

This paper introduced an indoor navigation application that helps junior students in Faculty of Computer Science and Information Technology (FSKTM) to find their classroom location. This project implements the A* (pronounced A Star) path finding algorithm to calculate the shortest path for users. Users can choose to view the floor plan of the building or start navigation. Users can choose their starting point from the list and set their destination to start navigation. The application is then calculate the shortest path for users by implement the A* algorithm. The route path will show on the floor plan after calculation done. Thus, users will find this project is easy to use and time saving.

E-Code Checker Application

Nowadays, many areas in computer sciences use ontology such as knowledge engineering, software reuse, digital libraries, web on the heterogeneous information processing, semantic web, and information retrieval. The area of halal industry is the fastest growing global business across the world. The halal food industry is thus crucial for Muslims all over the world as it serves to ensure them that the food items they consume daily are syariah compliant. However, ontology has still not been used widely in the halal industry. Today, Muslim community still have problem to verify halal status for halal products in the market especially in foods consisting of E number. In this paper, ontology will apply at E numbers as a method to solve problems of various halal sources. There are various chemical ontology and databases found to help this ontology construction. The E numbers in this chemical ontology are codes for chemicals that can be used as food additives. With this E numbers ontology, Muslim community could identify and verify the halal status effectively for halal products in the market.

Filtering Redundant Data from RFID Data Streams

Radio Frequency Identification (RFID) enabled systems are evolving in many applications that need to know the physical location of objects such as supply chain management. Naturally, RFID systems create large volumes of duplicate data. As the duplicate data wastes communication, processing, and storage resources as well as delaying decision-making, filtering duplicate data from RFID data stream is an important and challenging problem. Existing Bloom Filter-based approaches for filtering duplicate RFID data streams are complex and slow as they use multiple hash functions. In this paper, we propose an approach for filtering duplicate data from RFID data streams. The proposed approach is based on modified Bloom Filter and uses only a single hash function. We performed extensive empirical study of the proposed approach and compared it against the Bloom Filter, d-Left Time Bloom Filter, and the Count Bloom Filter approaches. The results show that the proposed approach outperforms the baseline approaches in terms of false positive rate, execution time, and true positive rate.

Minimizing Heatstroke Incidents for Young Children Left inside Vehicle

The number of children dying because of heatstroke after being left in the car is worrying. From 1998, there are about 618 children have died in the United State of America (USA) because of heatstroke. It was the leading cause of fatalities in non-crash incident in USA. The same situation also arises in other countries. Life stress is being identified as among the factor that lead to this incident. In this paper, we proposed the used of Android Apps with an Estimote Beacon, a bluetooth device, to warn parents or guardians about their children being left in the car. An alarm will be raised after the parent leaves their children at prespecified range to avoid any risk of heatstroke from occurring.

Modelling End-User of Electronic-Government Service: The Role of Information quality, System Quality and Trust

Many governments around the world increasingly use internet technologies such as electronic government to provide public services. These services range from providing the most basic informational website to deploying sophisticated tools for managing interactions between government agencies and beyond government. Electronic government (e-government) aims to provide a more accurate, easily accessible, cost-effective and time saving for the community. In this study, we develop a new model of e-government adoption service by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) through the incorporation of some variables such as System Quality, Information Quality and Trust. The model is then tested using a large-scale, multi-site survey research of 237 Indonesian citizens. This model will be validated by using Structural Equation Modeling (SEM). The result indicates that System Quality, Information Quality and Trust variables proven to effect user behavior. This study extends the current understanding on the influence of System Quality, Information Quality and Trust factors to researchers, practitioners, and policy makers.

A Review on Bloom Filter Based Approaches for RFID Data Cleaning

This paper provides comprehensive review about data cleaning for RFID data streams. It serves the purpose to understand the current undertakings to ensure data quality in RFID. It focused on three major RFID data issues which are noise readings, duplicate readings and missed readings. It includes in-depth analysis on existing approaches specifying on Bloom filter based approaches. This literature can be used by researcher to understand the background of RFID data filtering, the challenges and expectation in the future.