DEVELOPMENT OF A LOW COST IMPEDANCE TUBE TO MEASURE THE ACOUSTIC ABSORPTION AND TRANSMISSION LOSS OF MATERIALS

Traditional methods of measuring sound absorption coefficient and sound transmission loss of a material are time consuming. To overcome this limitation, normal incidence sound absorption and transmission loss measurement technique was developed. Unfortunately the equipment required for this task is equally expensive. Hence efforts are taken to develop a cost-effective equipment for measuring normal incidence sound absorption coefficient and transmission loss. An impedance tube capable of measure absorption coefficient and transmission loss is designed and built under a budget of $1500 for educational institutes. A background study is performed to gain knowledge and understanding of the normal incidence measurements technique. Based on the literature review, parameters involved such as tube material, source and microphone properties, sample holders, etc. are discussed in depth. Based on these parameters, design options are generated to meet the cost and functionality targets pre-assigned. After selection of materials and components, an impedance tube is built and tested using three fibrous absorption materials for absorption and a barrier for transmission loss performance. These measured results then compared with those obtained with the help of industry recognized Brüel & Kjær impedance tube. The results show performances are comparable, hence validation the new built tube.

Automatic Food Intake Assessment Using Camera Phones

Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user's memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors.