Fine-grained food image classification and recipe extraction using a customised Deep Neural Network and NLP

Global eating habits cause health issues leading people to mindful eating. This has directed attention to applying deep learning to food-related data. The proposed work develops a new framework integrating neural network and natural language processing for classification of food images and automated recipe extraction. It address the challenges of intra-class variability and inter-class similarity in food images that have received shallow attention in the literature. Firstly, a customised lightweight deep convolution neural network model, MResNet-50 for classifying food images is proposed. Secondly, automated ingredient processing and recipe extraction is done using natural language processing algorithms: Word2Vec and Transformers in conjunction. Thirdly, a representational semi-structured domain ontology is built to store the relationship between cuisine, food item, and ingredients. The accuracy of the proposed framework on the Food-101 and UECFOOD256 datasets is increased by 2.4% and 7.5%, respectively, outperforming existing models in literature such as DeepFood, CNN-Food, Wiser, and other pre-trained neural networks

Diseño y construcción de una máquina prototipo, para rehabilitación de muñeca con esguince de grado 1, mediante el control de movimientos asistidos

En el presente trabajo de titulación, se encuentra enfocado en el diseño y construcción de una máquina prototipo, que servirá para realizar la rehabilitación de un esguince de muñeca de grado uno, enfocado a personas de la tercera edad. Para el diseño y construcción del prototipo se parte con el estudio de la fisiología de la muñeca, y los grados de lesiones para establecer las características principales, que debe tener el equipo para permitir una correcta rehabilitación. Con el estudio de la base teórica se proponen 3 alternativas para el diseño del rehabilitador de muñeca. Por medio del diseño y simulación en SolidWorks de cada una de las partes de la máquina, se obtiene el factor de seguridad que permitirá conocer la viabilidad para la construcción del prototipo, con los materiales seleccionados en el estudio de alternativas. Para comprobar el funcionamiento de los controladores en el prototipo de rehabilitador, se realizan pruebas de funcionamiento mediante la variación del ángulo para los movimientos de flexo extensión y aducción-abducción, con y sin carga para determinar los errores en estado estable, el tiempo de subida y tiempo establecimiento.In the present graduation work, we present the design and construction of a prototype machine that serves to perform the rehabilitation of a grade one wrist sprain; this machine focuses on the elderly. For the design and construction of the prototype, we start with the study of the physiology of the wrist, and the degrees of injuries to establish the main characteristics that the equipment must have to allow a correct rehabilitation. With the study of the theoretical basis, 3 alternatives are proposed for the design of the wrist rehabilitator. Through the design and simulation in SolidWorks of each of the parts of the machine, the safety factor is obtained that will allow knowing the feasibility for the construction of the prototype, with the materials selected in the study of alternatives. To verify the operation of the controllers in the rehabilitator prototype, performance tests are carried out by varying the angle for the flexo- extension and adduction-abduction movements, with and without load, to determine the errors in the stable state, the rise time and establishment time

Performance analysis for wireless G (IEEE 802.11G) and wireless N (IEEE 802.11N) in outdoor environment

This paper described an analysis the different capabilities and limitation of both IEEE technologies that has been utilized for data transmission directed to mobile device. In this work, we have compared an IEEE 802.11/g/n outdoor environment to know what technology is better. The comparison consider on coverage area (mobility), throughput and measuring the interferences. The work presented here is to help the researchers to select the best technology depending of their deploying case, and investigate the best variant for outdoor. The tool used is Iperf software which is to measure the data transmission performance of IEEE 802.11n and IEEE 802.11g

Performance Analysis For Wireless G (IEEE 802.11 G) And Wireless N (IEEE 802.11 N) In Outdoor Environment

This paper described an analysis the different capabilities and limitation of both IEEE technologies that has been utilized for data transmission directed to mobile device. In this work, we have compared an IEEE 802.11/g/n outdoor environment to know what technology is better. the comparison consider on coverage area (mobility), through put and measuring the interferences. The work presented here is to help the researchers to select the best technology depending of their deploying case, and investigate the best variant for outdoor. The tool used is Iperf software which is to measure the data transmission performance of IEEE 802.11n and IEEE 802.11g