Measuring a Level of Water Pollution in Sungai Pinang Using a Mathematical Model

Mathematical models are now a popular tool in many applications such as physics, economics and engineering; and provide useful information for decision making and planning. Water pollution in Malaysia has reached a level that needs attention and intervention from environmental department and government. In order to make a strong case, this paper has done a study on measuring the pollution level of Sungai Pinang which is located in Penang Island, Malaysia. Advection-Dispersion equation is one of the mathematical models that often use in evaluating the level of water pollution in the river. This paper applies this model and compares the result of this study with the studies done in the previous research worldwide to evaluate the severity of the pollution. The authors hope that this paper will create awareness to relevant department and also to community in genera

Mechanical properties of longitudinal basalt/woven-glass-fiber-reinforced unsaturated polyester-resin hybrid composites

This work represents a study to investigate the mechanical properties of longitudinal basalt/woven-glass-fiber-reinforced unsaturated polyester-resin hybrid composites. The hybridization of basalt and glass fiber enhanced the mechanical properties of hybrid composites. The unsaturated polyester resin (UP), basalt (B) and glass fibers (GF) were fabricated using the hand lay-up method in six formulations (UP, GF, B7.5/G22.5, B15/G15, B22.5/G7.5 and B) to produce the composites, respectively. This study showed that the addition of basalt to glass-fiber-reinforced unsaturated polyester resin increased its density, tensile and flexural properties. The tensile strength of the B22.5/G7.5 hybrid composites increased by 213.92 MPa compared to neat UP, which was 8.14 MPa. Scanning electron microscopy analysis was used to observe the fracture mode and fiber pullout of the hybrid composites

Software optimization of vision-based around view monitoring system on embedded platform

Image processing algorithm requires high computational power. Optimizing the algorithm to be run on an embedded platform is very critical as the platform provides limited computational resources. This research focused on optimizing and implementing a vision-based Around View Monitoring (AVM) system running on two embedded boards of Cortex-A7 quad and Cortex-A15 quad-core, and desktop platform of Intel i7 core. This paper presented a study on several techniques of software optimization that is removing code redundancy and multi-threading. The two methods improve the total processing time of the AVM system by 45% on ARM Cortex-A15 and 47% on ARM Cortex-A7

Deep learning-based single-shot and real-time vehicle detection and ego-lane estimation

Vision-based Forward Collision Warning System (FCWS) is a promising assist feature in a car to alleviate road accidents and make roads safer. In practice, it is exceptionally hard to accurately and efficiently develop an algorithm for FCWS application due to the complexity of steps involved in FCWS. For FCWS application, multiple steps are involved namely vehicle detection, target vehicle verification and time-to-collision (TTC). These involve an elaborated FCWS pipeline using classical computer vision methods which limits the robustness of the overall system and limits the scalability of the algorithm. Deep neural network (DNN) has shown unprecedented performance for the task of vision-based object detection which opens the possibility to be explored as an effective perceptive tool for automotive application. In this paper, a DNN based single-shot vehicle detection and ego-lane estimation architecture is presented. This architecture allows simultaneous detection of vehicles and estimation of ego-lanes in a single-shot. SSD-MobileNetv2 architecture was used as a backbone network to achieve this. Traffic ego-lanes in this paper were defined as semantic regression points. We collected and labelled 59,068 images of ego-lane datasets and trained the feature extractor architecture MobileNetv2 to estimate where the ego-lanes are in an image. Once the feature extractor is trained for ego-lane estimation the meta-architecture single-shot detector (SSD) was then trained to detect vehicles. Our experimental results show that this method achieves real-time performance with test results of 88% total precision on the CULane dataset and 91% on our dataset for ego-lane estimation. Moreover, we achieve a 63.7% mAP for vehicle detection on our dataset. The proposed architecture shows that an elaborate pipeline of multiple steps to develop an algorithm for the FCWS application is eliminated. The proposed method achieves real-time at 60 fps performance on standard PC running on Nvidia GTX1080 proving its potential to run on an embedded device for FCWS

Effect of sugar palm nanofibrillated cellulose concentrations on morphological, mechanical and physical properties of biodegradable films based on agro-waste sugar palm (Arenga pinnata (Wurmb.) Merr) starch

Sugar palm (Arenga pinnata) fibres and starches are considered as agro-industrial residue in the agricultural industry. This paper aims to investigate the effect of different concentrations (0–1.0 wt%) of sugar palm nanofibrillated cellulose (SPNFCs) reinforced sugar palm starch (SPS) on morphological, mechanical and physical properties of the bionanocomposites film. The SPNFCs, having a diameter of 5.5 ± 0.99 nm and length of several micrometres, were prepared from sugar palm fibres via a high-pressure homogenisation process. FESEM investigation of casting solution displayed good miscibility between SPS and SPNFCs. The FTIR analysis revealed good compatibility between the SPS and SPNFCs, and there were existence of intermolecular hydrogen bonds between them. The SPS/sPNFCs with 1.0 wt% had undergone an increment in both the tensile strength and Young’s modulus when compared with the SPS film, from 4.80 MPa to 10.68 MPa and 53.97 MPa to 121.26 MPa, respectively. The enhancement in water barrier resistance was led by reinforcing SPNFCs into the matrix, which resulted in bionanocomposites. The properties of bionanocomposites will be enhanced for short-life applications, such as recyclable container and plastic packaging through the incorporation of SPNFCs within the SPS bionanocomposites