physical activity and cancer fact sheet national cancer on this page what is physical activity what is known about the relationship between physical activity and cancer risk how might physical activity be, diet and cancer report american institute for cancer the american institute for cancer research aicr is the cancer charity that fosters research on diet and cancer prevention and educates the public about the results, download resources and toolkits world cancer research downloads for scientists from the wcrf aicr third expert report diet nutrition physical activity and cancer a global perspective, nutritional science university of washington school of public health school of public health nutritional science detailed course offerings time schedule are available for spring quarter 2019, 2019 aicr research conference american institute for about aicr we fund cutting edge research and give people practical tools and information to help them prevent and survive cancer more about aicr, agence fruits et l gumes frais aprifel the global fruit and veg newsletter is a monthly newsletter distributing to 29 countries involved in the promotion of the consumption of fruit and vegetable worldwide, world cancer research fund international we are experts in cancer prevention we analyse global research on diet nutrition physical activity cancer and make public health policy recommendations, the fractions of cancer attributable sciencedirect com a proportion of cancers at many body sites are attributable to potentially modifiable factors no global summaries of the preventable cancer burden have been, who controlling the global obesity epidemic more information obesity and overweight fact sheet who global strategy on diet physical activity and health who global database on body mass index, espen guidelines on nutrition in cancer patients gl nutrition in cancer patients outline o methods o1 basic information o2 methods o3 post publication impact a background a1 catabolic alterations in, un news global perspective human stories un news produces daily news content in arabic chinese english french kiswahili portuguese russian and spanish and weekly programmes in hindi urdu and bangla, recommended community strategies and measurements to table continued summary of recommended community strategies and measurements to prevent obesity in the united states strategies to encourage physical, food as medicine preventing treating the most dreaded food as medicine preventing treating the most dreaded diseases with diet, video resources bc cancer these videos help patients learn about their cancer and its treatment, prostate cancer nutrition and dietary supplements pdq nutrition methods and dietary supplements have been studied for prostate cancer prevention or treatment read about the history of research laboratory, who europe food safety food safety ingestion and handling of contaminated food causes significant illness and death worldwide across the who european region foodborne diseases, creating healthy food and eating environments policy and food and eating environments likely contribute to the increasing epidemic of obesity and chronic diseases over and above individual factors such as knowledge skills, health risks obesity prevention source harvard t h obesity and reproduction obesity can influence various aspects of reproduction from sexual activity to conception among women the association between, top nutrition schools undergraduate degree programs ncr want to know the top nutrition schools and best undergraduate degree programs here we review analyze rank rate them figure out which is best for you , overeating caloric restriction and breast cancer risk by this study analyzes the association of excessive energy intake and caloric restriction with breast cancer bc risk taking into account the individual, calcium what s best for your bones and health the possible increased risk of ovarian cancer high levels of galactose a sugar released by the digestion of lactose in milk have been studied as being, cancer protocol nutrition supplements cancer protocol nutrition supplements herbs enzymes note do not email me unless you would like a personalized protocol free with a suggested donation of 250

Food, Nutrition, Physical Activity, and the Prevention of Cancer : a Global Perspective : 食物、栄養、身体活動とがんの予防 : 世界的展望(後篇)

Matrix Factorization Techniques for Recommender Systems

Páginas de Salud Pública. Food, nutrition and the prevention of cancer: A global perspective. Conocimientos actuales sobre nutrición

A comprehensive survey on support vector machine classification: Applications, challenges and trends

Over the years, a large number of methods have been proposed to analyze human pose and motion information from images, videos, and recently from depth data. Most methods, however, have been evaluated on datasets that were too specific to each application, limited to a particular modality, and more importantly, captured under unknown conditions. To address these issues, we introduce the Berkeley Multimodal Human Action Database (MHAD) consisting of temporally synchronized and geometrically calibrated data from an optical motion capture system, multi-baseline stereo cameras from multiple views, depth sensors, accelerometers and microphones. This controlled multimodal dataset provides researchers an inclusive testbed to develop and benchmark new algorithms across multiple modalities under known capture conditions in various research domains. To demonstrate possible use of MHAD for action recognition, we compare results using the popular Bag-of-Words algorithm adapted to each modality independently with the results of various combinations of modalities using the Multiple Kernel Learning. Our comparative results show that multimodal analysis of human motion yields better action recognition rates than unimodal analysis.

Berkeley MHAD: A comprehensive Multimodal Human Action Database

Problem statement: Image recognition is a challenging problem researchers had been research into this area for so long especially in the recent years, due to distortion, noise, segmentation errors, overlap and occlusion of objects in digital images. In our study, there are many fields concern with pattern recognition, for example, fingerprint verification, face recognition, iris discrimination, chromosome shape discrimination, optical character recognition, texture discrimination and speech recognition, the subject of pattern recognition appears. A system for recognizing isolated pattern of interest may be as an approach for dealing with such application. Scientists and engineers with interests in image processing and pattern recognition have developed various approaches to deal with digital image recognition problems such as, neural network, contour matching and statistics. Approach: In this study, our aim was to recognize an isolated pattern of interest in the image based on the combination between robust features extraction. Where depend on size and shape measurements, that were extracted by measuring the distance and geometrical measurements. Results: We presented a system prototype for dealing with such problem. The system started by acquiring an image containing pattern of fish, then the image features extraction is performed relying on size and shape measurements. Our system has been applied on 20 different fish families, each family has a different number of fish types and our sample consists of distinct 350 of fish images. These images were divided into two datasets: 257 training images and 93 testing images. An overall accuracy was obtained using the neural network associated with the back-propagation algorithm was 86% on the test dataset used. Conclusion: We developed a classifier for fish images recognition. We efficiently have chosen a features extraction method to fit our demands. Our classifier successfully design and implement a decision which performed efficiently without any problems. Eventually, the classifier is able to categorize the given fish into its cluster and categorize the clustered fish into its poison or non-poison fish and categorizes the poison and non-poison fish into its family.

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Fish Recognition Based on Robust Features Extraction from Size and Shape Measurements Using Neural Network

A multilayer perceptron is a feedforward artificial neural network model that maps sets of input data onto a set of appropriate output. It is a modification of the standard linear perceptron in that it uses three or more layers of neurons (nodes) with nonlinear activation functions, and is more powerful than the perceptron in that it can distinguish data that is not linearly separable, or separable by a hyper plane. MLP networks are general-purpose, flexible, nonlinear models consisting of a number of units organised into multiple layers. The complexity of the MLP network can be changed by varying the number of layers and the number of units in each layer. Given enough hidden units and enough data, it has been shown that MLPs can approximate virtually any function to any desired accuracy. This paper presents the performance comparison between Multi-layer Perceptron (Back Propagation, Delta Rule and Perceptron). Perceptron is a steepest descent type algorithm that normally has slow convergence rate and the search for the global minimum often becomes trapped at poor local minima. The current study investigates the performance of three algorithms to train MLP networks. Its was found that the Perceptron algorithm are much better than others algorithms.

Performance Comparison of Multi-layer Perceptron (Back Propagation, Delta Rule and Perceptron) algorithms in Neural Networks

In recent times, the recommender systems (RSs) have considerable importance in academia, commercial activities, and industry. They are widely used in various domains such as shopping (Amazon), music (Pandora), movies (Netflix), travel (TripAdvisor), restaurant (Yelp), people (Facebook), and articles (TED). Most of the RSs approaches rely on a single-criterion rating (overall rating) as a primary source for the recommendation process. However, the overall rating is not enough to gain high accuracy of recommendations because the overall rating cannot express fine-grained analysis behind the user’s behavior. To solve this problem, multi-criteria recommender systems (MCRSs) have been developed to improve the accuracy of the RS performance. Additionally, a new source of information represented by the user-generated reviews is incorporated in the recommendation process because of the rich and numerous information included (i.e. review elements) related to the whole item or to a certain feature of the item or the user’s preferences. The valuable review elements are extracted using either text mining or sentiment analysis. MCRSs benefit from the review elements of the user-generated reviews in building their criteria forming multi-criteria review based recommender systems. The review elements improve the accuracy of the RS performance and mitigate most of the RS’s problems such as the cold start and sparsity. In this review, we focused on the multi-criteria review-based recommender system and explained the user reviews elements in detail and how these can be integrated into the RSs to help develop their criteria to enhance the RSs performance. Finally, based on the survey, we presented four future trends based on this type of RSs to support researchers who wish to pursue studies in this area.

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Multi-Criteria Review-Based Recommender System–The State of the Art

Problem statement: Traditional Malay poetry called pantun is a form of art to express ideas, emotions and feelings in the form of rhyming lines. Malay poetry usually has a broad and deep meaning making it difficult to be interpreted. More over, few efforts have been done on automatic classification of literary text such as poetry. Approach: This research concerns with the classification of Malay pantun using Support Vector Machines (SVM). The capability of SVM through Radial Basic Function (RBF) and linear kernel function are imple mented to classify pantun by theme, as well as poetry or non-poetry. A total of 1500 pantun are di vided into 10 themes with 214 Malaysian folklore documents used as the training and testing datasets . We used tfidf for both classification experiments and the shape feature for the classification of poe try and non-poetry experiment alone. Results: The results of each experiment showed that the linear k ernel achieved a better percentage of average accuracy compared to the RBF kernel. Conclusion: The results show the potential of SVM technique in classifying poems into various classification of which previous approaches only focused on classifying prose only.

Poetry Classification Using Support Vector Machines

With the rapidly increasing learning materials and learning resources, either offline or online, it is quite difficult to find suitable materials based on learner's need. Recommender systems help learners find the appropriate learning materials in which they would need to learn. This paper discusses about the personalized recommendation systems in e-learning and compares their recommendation techniques. Two concepts are the main discussion topics in this research. The first one is about the learner's requirement and the second one in about the personalized recommendation technique. Finally, this study proposes the knowledge based recommendation system as suitable recommendation technique. This recommendation aims to recommend to the learner, some materials based on the learner's need. By using the semantic relationship between learning materials and the learner's need, system can select the suitable materials as a recommendation to the learner. To develop the proposed knowledge based recommendation system is the next work for the future.

Shahrul Azman Mohd Noah

Papers

Fish Recognition Based on Robust Features Extraction from Size and Shape Measurements Using Neural Network

Performance Comparison of Multi-layer Perceptron (Back Propagation, Delta Rule and Perceptron) algorithms in Neural Networks

Multi-Criteria Review-Based Recommender System–The State of the Art

Poetry Classification Using Support Vector Machines

Review of personalized recommendation techniques for learners in e-learning systems