A Review on Sensor Node Placement Techniques in Wireless Sensor Networks

One way to provide Wireless Sensor Network (WSN) with maximum coverage, maximum connectivity, minimum deployment cost and minimum energy consumption is through an effective planning mechanism in arranging an optimum number of sensor nodes. Proper planning will provide a cost-effective deployment by having optimal placements for the sensor nodes. Sensor node placement schemes are needed to accommodate the balance of coverage and energy consumption since closer sensor nodes not only reduces the energy consumption but will result in the network coverage becoming smaller. This paper critically reviews the research and development work done in sensor node placement. Based on the review, the design objectives that need to be considered are identified. Most of the work reviewed focused on two or three design objectives

Efficient human motion detection with adaptive background for vision-based security system

Motion detection is very important in video surveillance system especially for video compression, human detection, and behaviour analysis. Various approaches have been used for detecting motion in a continuous video stream but for real-time video surveillance system; we need a motion detection that can provide accurate detection even in non-static background regardless of surroundings (outdoor or indoor), object speed and size, robust to camera noisy pixels or sudden change in light intensity. This is very important to ensure that the security of a monitored parameter or area is not compromised. In this paper, we propose a method for human motion detection that employs adaptive background subtraction, camera noise reduction and white pixel count threshold for real-time video streams

Human Emotion Detection via Brain Waves Study by Using Electroencephalogram (EEG)

Human emotion is very difficult to determine just by looking at the face and also the behavior of a person. This research was conducted to detect or identify human emotion via the study of brain waves. In addition, the research aims to develop computer software that can detect human emotions quickly and easily. This study aims at EEG signals of relationship and human emotions. The main objective of this recognition is to develop "mind-implementation of Robots". While the research methodology is divided into four; (i) both visibility and EEG data were used to extract the date at the same time from the respondent, (ii) the process of complete data record includes the capture of images using the camera and EEG, (iii) pre-processing, classification and feature extraction is done at the same time, (iv) the features extracted is classified using artificial intelligence techniques to emotional faces. Researchers expect the following results; (i) studies brain waves for the purpose of emotions, (ii) the study of human emotion with facial emotions and to relate the brain waves, (iii). In conclusion, this study is very useful for doctors in hospitals and police departments for criminal investigation. As a result of this study, it also helps to develop a software package

Advanced Manufacturing of an Aircraft Component (Fish-Head): A Technology Review on the Fabrication

The Airbus fish-head is machined using a 5-axis Computerized Numerical Control (CNC) milling machine, which consists of many complex shapes that are built into it. A conventional CNC machining requires tremendous effort in programming and investment due to the increasing in features complexity of the fish-head to be machined. An alternative method through advanced manufacturing processes namely vacuum casting, Fused Deposition Modelling (FDM) and three dimensional printing (3DP) is reviewed. The fish-head prototypes are manufactured through the concept of reverse engineering and rapid prototyping. The fish-head master pattern is digitized using a three dimensional laser scanner and edited using a surface modelling software to generate the Standard Triangulation Language (STL), which is common to most rapid prototyping (RP) machines. The fish-head prototypes are fabricated through FDM and 3DP using the STL data files, whereas the master pattern is used to fabricated silicone mould for vacuum casting. The quality of the prototypes is accessed in terms of dimensional accuracy and time to produce a single prototype. The dimensional accuracy is analysed using coordinate measuring machine (CMM). The dimensional accuracy error is found to be less than 5%. However, all prototypes require secondary surface treatment processing in order to achieve the desired surface roughness quality. All three prototypes can be manufactured less than 24 hours per prototype. The advanced manufacturing processes allows parts to be fabricated similar to parts manufactured through CNC but at a lower cost and faster

Integration of CompTIA Cloud+ into Universiti Teknologi MARA’s Computer Engineering Special Topics Syllabus

Cloud computing is one of the frontier technologies in computer engineering. Therefore, it is important to prepare the students with the knowledge and skills required in this field. This paper describes the integration of the renowned CompTIA Cloud+ professional training course into the ECE648: Special Topics in Computer Networking subject. The subject is a final year elective for the Faculty of Electrical Engineering, Universiti Teknologi MARA, Malaysia undergraduate computer engineering students. We first begin by assessing the current teaching syllabus of a variety of international universities to establish fundamental topics that should be covered in a cloud computing course. We then proceed to describe our implementation, which is done in accordance with the CompTIA Cloud+ certification syllabus. Among the items described are how the Cloud+ course contents are adjusted to be more suitable for the course, as well as additional practical elements (not originally available in the Cloud+ course) added to the course syllabus. Implementation results are described