Emotion Detection by Analyzing Voice Signal Using Wavelet

Emotion is such a unique power of human trial that plays a vital role in distinguishing human civilization from others. Voice is one of the most important media of expressing emotion. We can identify many types of emotions by talking or listening to voices. This is what we know as a voice signal. Just as the way people talk is different, so is the way they express emotions. By looking or hearing a person’s way of speaking, we can easily guess his/her personality and instantaneous emotions. People’s emotion and feelings are expressed in different ways. It is through the expression of emotions and feelings that people fully express his thoughts. Happiness, sadness, and anger are the main medium of expression way of different human emotions. To express these emotions, people use body postures, facial expressions and vocalizations. Though people use a variety of means to express emotions and feelings, the easiest and most complete way to express emotion and feelings is voice signal. The subject of our study is whether we can identify the right human emotion by examining the human voice signal. By analyzing the voice signal through wavelet, we have tried to show whether the mean frequency, maximum frequency and Lp values conform to a pattern according to its different sensory types. Moreover, the technique applied here is to develop a concept using MATLAB programming, which will compare the mean frequency, maximum frequency and Lp norm to find relation and detect emotion by analyzing different voices.

Most Suitable Power System Stabilizer Selection for the Improvement of Dynamic Stability

A method of enhancing power system stability for a single machine to infinite bus power system is presented. The technique used compromises the effectiveness of Proportional-Integral-Derivative controller （PID）. In order to satisfy the damping characteristics for the proposed power system over a wide range of operating interval, rotational speed, torque angle and terminal voltage signals of the synchronous machine are utilized as control signals of the system. It is well known that these variables have significant effects on damping the generators shaft mechanical oscillations, it＇ll be so easy to validate the most suitable controller as seen from the simulation results.

PoreScript:Semi-automated pore size algorithm for scaffold characterization

The scaffold pore size influences many critical physical aspects of tissue engineering,including tissue infiltration,biodegradation rate,and mechanical properties.Manual measurements of pore sizes from scanning electron micrographs using ImageJ/FIJI are commonly used to characterize scaffolds,but these methods are both time-consuming and subject to user bias.Current semi-automated analysis tools are limited by a lack of accessibility or limited sample size in their verification process.The work here describes the development of a new MATLAB algorithm,PoreScript,to address these limitations.The algorithm was verified using three common scaffold fabrication methods(e.g.,salt leaching,gas foaming,emulsion templating)with varying pore sizes and shapes to demonstrate the versatility of this new tool.Our results demonstrate that the pore size characterization using PoreScript is comparable to manual pore size measurements.The PoreScript algorithm was further evaluated to determine the effect of user-input and image parameters(relative image magnification,pixel intensity threshold,and pore structure).Overall,this work validates the accuracy of the PoreScript algorithm across several fabrication methods and provides user-guidance for semi-automated image analysis and increased throughput of scaffold characterization.