Kernelized radial basis probabilistic neural network for classification of river water quality

Radial Basis Probabilistic Neural Network (RBPNN) demonstrates broader and much more generalized capabilities which have been successfully applied to different fields.In this paper, the RBPNN is extended by calculating the Euclidean distance of each data point based on a kernel-induced distance instead of the conventional sum-of squares distance.The kernel function is a generalization of the distance metric that measures the distance between two data points as the data points are mapped into a high dimensional space.Through comparing the four constructed classification models with Kernelized RBPNN, Radial Basis Function networks, RBPNN and Back-Propagation networks as intended, results showed that, model classification on River water quality of Langat river in Selangor, Malaysia by Kernelized RBPNN exhibited excellent performance in this regard

Investigation of Water Hammer Effect Through Pipeline System

This paper we study the condition where the water hammer effect is occurs in pipe line. Water hammer can cause the pipe to break if the pressure is high enough. The experiment will be set-up to investigate the water hammer effect in order to avoid the water hammer effect happen. The prevention of water hammer effect will be propose and prove the prevention method is successfully reduce the water hammer effect. The prevention method using is installing the bypass pipe with non-return valve. The experiment is done by capture the vibration signal by using data acquisition device and accelerometer. The pressure signal is capture after a sudden shutoff for the valve. The signal is than analyze and convert to wave speed. The project is differentiating and compares the water hammer phenomenon with different pipe material, pipe length, inlet diameter of pipe, and pressure in pipeline. From the experiment, result shown that the lower strength material pipe, smaller inlet diameter pipe, and longer pipe will deal with lager water hammer effect. Besides, the prevention method by installing by pass pipe with non-return valve of water hammer effect is proved successfully reduce the water hammer phenomenon by 33.33% of pressure

Development of Low Wind Speed Anemometer

Anemometer is a measuring device used to measure the wind speed of an area. Before design or installing a wind turbine, it is important to determine the average wind speed of that particular area throughout the year. But it is illogically to purchase anemometer to measure the wind velocity for a year period. The purpose of this project is to design and fabricate a small scale of anemometer which will able to give the wind velocity with an acceptable range of uncertainty. The fabrication of the anemometer is developed using design methodology and simulation to obtain the optimized design. The designed anemometer has the mean absolute percentage error (MAPE) of 3.23 % when compared with Dwyer series 471 thermo-anemometer

In-situ Noise Measurement and Analysis for the Motorcycle Muffler

Noise from the vehicles is one of the noise pollution to the environment. The noises emitted by the vehicles have to obey the requirement of regulation of maximum sound pressure level permitted for respective vehicles. In this study, the aim is to reduce the noise emitted from the motorcycle muffler. The noise emitted from the motorcycle muffler is analyzed and measured using a sound level meter. The average sound pressure level of the motorcycle muffler is determined in certain conditions. The sound pressure level is obtained from original motorcycle muffler, when it is under constant speed (10 km/hr, 20 km/hr, 30 km/hr) and under acceleration (in the scope of 0 km/hr to 30 km/hr). The study is continued by using a modified motorcycle muffler which contains sound absorptive materials. The absorptive materials chosen are glass wool, cotton and Styrofoam and they are taking turn to be placed into the motorcycle muffler to reduce the sound pressure level. Then the experiment is repeated. It is found that Styrofoam does not perform significantly in absorbing sound or noise in this study. Glass wool demonstrates relatively better sound energy absorption compared with cotton. In general, soft and porous materials are considered good performance in sound absorption. Denser materials are better at soundproofing or sound blocking. Therefore, glass wool with relatively higher density among the investigated absorptive materials in this study has the greatest sound absorption performance

I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences

The I4U consortium was established to facilitate a joint entry to NIST speaker recognition evaluations (SRE). The latest edition of such joint submission was in SRE 2018, in which the I4U submission was among the best-performing systems. SRE'18 also marks the 10-year anniversary of I4U consortium into NIST SRE series of evaluation. The primary objective of the current paper is to summarize the results and lessons learned based on the twelve sub-systems and their fusion submitted to SRE'18. It is also our intention to present a shared view on the advancements, progresses, and major paradigm shifts that we have witnessed as an SRE participant in the past decade from SRE'08 to SRE'18. In this regard, we have seen, among others, a paradigm shift from supervector representation to deep speaker embedding, and a switch of research challenge from channel compensation to domain adaptation.Comment: 5 page

Simulating Evacuations with Obstacles Using a Modified Dynamic Cellular Automata Model

A modified dynamic cellular automata model is proposed to simulate the evacuation of occupants from a room with obstacles. The model takes into account some factors that play an important role in an evacuation process, such as human emotions and crowd density around the exits. It also incorporates people’s ability to select a less congested exit route, a factor that is rarely investigated. The simulation and experimental results show that modifications to the exits provide reasonable improvement to evacuation time, after taking into account the fact that people will tend to select exit routes based on the distance to the exits and the crowd density around the exits. In addition, the model is applied to simulations of classroom and restaurant evacuation. Results obtained with the proposed model are compared with those of several existing models. The outcome of the comparison demonstrates that it performs better than existing models