Design of feasibility analysis platform for college physical education based on mobile social network

In order to promote the development of sports distance network education, a college sports teaching feasibility analysis platform based on mobile social network is designed. The key technologies such as Ajax, database and XML, Java Web containers applied to mobile social networks provide a technical basis for the platform design of this paper. Design the feasibility analysis platform framework using MVC mode, three platform functional modules were designed. Among it, the member function module is responsible for the registration and modification of the platform personal information of members; The feasibility analysis interactive discussion module is based on the cloud database storage and analysis platform user discussion records; The feasibility evaluation module of mobile social network is based on mobile social network, builds the hierarchical model of feasibility analysis and completes the design of feasibility analysis of distance teaching in universities. Experimental performance tested the platform, with an average response time of 2.3 ms and an analysis time of 18 ms. The feasibility analysis results of the platform have high reliability and effectiveness to meet the practical application requirements.

An Improved Performance of Fuzzy logic Based Controller Design for Bioreactor Process Plant

Proportional Integral Derivative, PID control is one of the earlier control strategies and most widely used controller for industries. A nonlinear technique, Mamdani structure was used for the bioreactor Simulink model. The fuzzy logic and its structure of the controller were adopted to set the fuzzy logic input member function. The fuzzy logic controller automatically tuned the PID controller, using an existing complex mapping function to generate the suitable values for the bioreactor process plant.

Pendekatan Fuzzy Pada Peramalan Jumlah Kunjungan Wisatawan Mancanegara ke Kabupaten Badung

This work is directed to forecast the number of foreign visitors come to tourist’s destinations at Badung regency, Province of Bali. Using visit historical data for period January 2000 to February 2015, Markov Transition Matrix and Fuzzy Triangular Number are applied to represent fuzzy logical relationship group and member function in fuzzy model, respectively. The results showed the in-sample forecasting accuracy for our fuzzy model as much as 2,48 percent. To validate the model, we found the average forecasting error rate for five consecutive months (March – July 2015) as much as 2,70 percent.

Design of Fuzzy Classification System Applying Expertise Based on Genetic Algorithms

In this paper, a design method of applying rational expertise to the learning mechanism based on fuzzy genetic algorithm is proposed. Firstly, we introduce the accuracy and explanatory of the fuzzy classification system, and then the application of expertise to the fuzzy system, and the adjustment of the member function using genetic algorithm to obtain the final classification results. Finally, the classification results of our experiments demonstrate the effectiveness of the design method with the Irvine classification sample data, and we can obtain better accuracy and explanatory through this learning mechanism with the designed fuzzy classification system.

IMAGE THRESHOLDING USING FUZZY CORRELATION CRITERION AND HARMONY SEARCH ALGORITHM

This paper reports a novel image thresholding method based on fuzzy set theory and maximum correlation criterion using harmony search algorithm. In this study, the maximum fuzzy correlation criterion is defined using Z- and S- fuzzy member function on image gray level histogram. Then fuzzy correlation criterion image segmentation based on harmony search algorithm is implemented. The experimental studies were conducted on a variety of images by testing the proposed method and some classical thresholding methods. The experimental results demonstrate that the proposed method can select the threshold automatically and effectively. Compared with the exhaustive search method, the harmony search algorithm can give high degree of accuracy while needing less search time and has good search stability in the segmentation experiments.

Extraction of Individual Tree Height Using a Combination of Large-Scale Aerial Photo and LiDAR

With the LiangShui forestry centre as study area, high-density LiDAR data and to synchronously processed high-resolution digital image are taken as data source to extract Individual Tree Height. The LiDAR data of the study area is filtered and classified, using TIN Filter to extract the ground echo points and trees echo points. Then these ground echo points generate Digital Elevation Model (DEM), and these trees echo points generate Digital Surface Model (DSM). Then the DEM and DSM are Taken as a subtraction to obtain Canopy Height Model (CHM), then the object-oriented approach is used to segment air digital image. Through multi-scale and canopy-model which create image objects and class division level, with the nearest neighbor distance and member function, the image objects are classified, and re-segmentation is based on classification results. And the edge is optimized to accurately identify individual tree. The canopy polygon obtained after image segmentation and CHM were superimposed to calculate polygon maximum elevation difference from LiDAR data as a tree height. Associated with the measured height analysis, the accuracy is 92.04%.

Pemodelan Sistem Fuzzy Dengan Menggunakan Matlab

Fuzzy logic is a method in soft computing category, a method that could process uncertain, inaccurate, and less cost implemented data. Some methods in soft computing category besides fuzzy logic are artificial network nerve, probabilistic reasoning, and evolutionary computing. Fuzzy logic has the ability to develop fuzzy system that is intelligent system in uncertain environment. Some stages in fuzzy system formation process is input and output analysis, determining input and output variable, defining each fuzzy set member function, determining rules based on experience or knowledge of an expert in his field, and implementing fuzzy system. Overall, fuzzy logic uses simple mathematical concept, understandable, detectable uncertain and accurate data. Fuzzy system could create and apply expert experiences directly without exercise process and effort to decode the knowledge into a computer until becoming a modeling system that could be relied on decision making.

Diagnosis and treatment of depression in patients with advanced illness

This article reviews common sources of suffering in patients with advanced illness, identifies challenges in appropriately diagnosing and treating depression in this setting, and examines the relationship between depression and other key clinical outcomes in the setting of advanced disease. A systematic literature review was conducted. Most of the existing research on patients with advanced illness has been conducted with cancer patients. Approximately 18 percent of patients with advanced illness meet criteria for major or minor depression; multiple psychiatric co-morbidities occur frequently. Prevalence rates increase as patients become sicker. However, depression is frequently underdiagnosed and undertreated in the setting of advanced illness. One of the key clinical challenges is differentiating depression from grief. Both psychosocial and psychopharmacologic interventions have been shown to be effective in treating depression in patients with advanced cancer. In conclusion, depression is a regular complication of advanced illness, reduces quality of life, compromises family member function, interferes with treatment decisions, and may shorten survival. However, numerous effective treatment approaches, including both medications and psychotherapy, exist and can be used to alleviate depression.

miR-8 microRNAs regulate the response to osmotic stress in zebrafish embryos

MicroRNAs (miRNAs) are highly conserved small RNAs that act as translational regulators of gene expression, exerting their influence by selectively targeting mRNAs bearing complementary sequence elements. These RNAs function in diverse aspects of animal development and physiology. Because of an ability to act as rapid responders at the level of translation, miRNAs may also influence stress response. In this study, we show that the miR-8 family of miRNAs regulates osmoregulation in zebrafish embryos. Ionocytes, which are a specialized cell type scattered throughout the epidermis, are responsible for pH and ion homeostasis during early development before gill formation. The highly conserved miR-8 family is expressed in ionocytes and enables precise control of ion transport by modulating the expression of Nherf1, which is a regulator of apical trafficking of transmembrane ion transporters. Ultimately, disruption of miR-8 family member function leads to an inability to respond to osmotic stress and blocks the ability to properly traffic and/or cluster transmembrane glycoproteins at the apical surface of ionocytes.