积极探索和谐社会下青少年健康网络人生构建

网络时代的青少年把大量的时间和精力投入到网络世界里,网络虚拟生活成为青少年现实生活的重要补充,他们正书写着属于自己的网络人生。文章分析了青少年网络人生的种种不良表现,探讨了在和谐社会下如何从各个方面去共同构建青少年的健康网络人生。

论网络私人生活安宁权及其保护限度

《民法典》颁布后,其第1032条第2款隐私条款加入了私人生活安宁的表述,引起了学界的热议各方争论的焦点是私人生活安宁是一项权利还是一种利益。私人生活安宁权通常受到公共利益、言论自由权、自动化算法决策、容忍义务等的限制,存在保护限度难题,其中网络私人生活安宁权的限度问题尤为突出。应界定网络私人生活安宁权为特殊的隐私权,设置公共利益限制网络私人生活安宁权的基本原则,构建网络私人生活安宁权妨害认定标准,建立以算法透明为中心的网络服务提供者问责体系,划定权利人容忍义务与网络服务提供者注意义务的边界,实现权利人、网络用户和网络服务提供者之间的利益互动与平衡。如此,方能在保证网络健康发展的同时,切实保障权利人和网络用户的合法权益。

“三观”教育是网络思想政治教育的核心内容

在网络环境中,人们会逐渐地形成带有鲜明网络特点的网络社会意识,它主要指网络世界观、网络人生观和网络价值观。它是网络思想政治教育的核心内容。

Study on Artificial Neural Network Model for Crop Evapotranspiration

Based on potted plant experiment, BP-artifieial neural network was used to simulate crop evapotranspiration and 3 kinds of artificial neural network models were constructed as ET1 （meteorological factors）, ET2（ meteorological factors and sowing days） and ET3 （meteorological factors, sowing days and water content）. And the predicted result was compared with actual value ET that was obtained by weighing method. The results showed that the ET3 model had higher calculation precision and an optimum BP-artificial neural network model for calculating crop evapotranspiration.

A hybrid neural network system for prediction and recognition of promoter regions in human genome

This paper proposes a high specificity and sensitivity algorithm called PromPredictor for recognizing promoter regions in the human genome. PromPredictor extracts compositional features and CpG islands information from genomic sequence,feeding these features as input for a hybrid neural network system (HNN) and then applies the HNN for prediction. It combines a novel promoter recognition model, coding theory, feature selection and dimensionality reduction with machine learning algorithm.Evaluation on Human chromosome 22 was ～66% in sensitivity and ～48% in specificity. Comparison with two other systems revealed that our method had superior sensitivity and specificity in predicting promoter regions. PromPredictor is written in MATLAB and requires Matlab to run. PromPredictor is freely available at http://www.whtelecom.com/Prompredictor.htm.

The social determinants of health influencing obesity for the aged in the Pakpoon community context:A qualitative study

Objective:This study aimed to describe the social determinants of health influencing obesity for the aged in a community context and based on the perspectives of various stakeholders.Methods:This was qualitative content analysis study using data from the focus group,individual in-depth interview,and observation.The study population was domiciled in Pakpoon Village,Mung Dis-trict,Nakhon Si Thammarat Province,a tight-knit settlement typical of most retirement communities.Data were collected through two focus group discussions,direct observation,and in-depth interviews with 19 participants.Respondents represented key community groups:local nurses and public health officers,elderly residents,family caregivers(family members),and village health volunteers.Results:The participants shared similar perspectives about the social determinants of health influencing obesity in the aged,which spanned three themes.These were:1)neighborhood food environment(easy access to unhealthy food,no choice to recruit healthy food);2)social networks influencing obesity(family affects food choices and prohibitions on exercise;belief,and socially imposed body image per-ceptions contributing to obesity in the aged);and 3)knowledge,attitudes,and beliefs behind lifestyle choices that cause obesity in the elderly(lack of awareness,personal attitudes,job and familial duties as barriers to engaging in physical activities;over-consumption behaviors lead to obesity in older people).Conclusion:These three themes were the root causes of obesity in the elderly in Pakpoon’s retirement community.This finding suggests that policymakers and nurses can create healthy environments,both to treat and prevent obesity,by raising awareness in younger generations,providing aging the provision of healthy food choices for older adults,encouraging health care professionals to share knowledge,and by modifying the attitudes and beliefs of both caregivers and older adults.

Community-based flood disaster management for older adults in southern of Thailand:A qualitative study

Objective:This study explored the approaches for community-based flood disaster management for older adults in Southern Thailand.It sought to understand community culture for supporting older adults and promoting community strength in case of flood disaster.Method:This was a qualitative content analysis study using data from observation,in-depth interviews,secondary data,and focus group discussion.One hundred and twenty-seven people in total were selected specifically for the study,including Local Administration Organization(LAO),community leaders,public sector officers,civil groups,and older adult groups and family caregivers.Results:The results of this study were two main themes,focusing on 1)approaches to community-based flood disaster management for older adults as follows:eight approaches in the phase of prevention and preparedness in flood disaster management for older adults,eight approaches in the phase of response in flood disaster management for older adults,and six approaches in the phase of recovery and rehabilitation in flood disaster management for older adults;and 2)factors contributing to success in flood disaster management for older adults has four factors,including the human factor,the work factor,the data factor,and the resource factor.Conclusion:The findings showed significant roles in improving the potential and strength in communitybased flood disaster management for older adults and providing suggestions for community nurses and health practice personnel involving in flood disaster management to mitigate the potential influence on older adults in the community.

Predicting Model for Complex Production Process Based on Dynamic Neural Network

Based on the comparison of several methods of time series predicting, this paper points out that it is necessary to use dynamic neural network in modeling of complex production process. Because self feedback and mutual feedback are adopted among nodes at the same layer in Elman network, it has stronger ability of dynamic approximation, and can describe any non linear dynamic system. After the structure and mathematical description being given, dynamic back propagation (BP) algorithm of training weights of Elman neural network is deduced. At last, the network is used to predict ash content of black amber in jigging production process. The results show that this neural network is powerful in predicting and suitable for modeling, predicting, and controling of complex production process.

Ecosystem Health Assessment of Honghu Lake Wetland of China Using Artificial Neural Network Approach

Honghu Lake,located in the southeast of Hubei Province,China,has suffered a severe disturbance during the past few decades.To restore the ecosystem,the Honghu Lake Wetland Protection and Restoration Demonstration Project(HLWPRDP) has been implemented since 2004.A back propagation(BP) artificial neural network(ANN) approach was applied to evaluatinig the ecosystem health of the Honghu Lake wetland.And the effectiveness of the HLWPRDP was also assessed by comparing the ecosystem health before and after the project.Particularly,12 ecosystem health indices were used as evaluation parameters to establish a set of three-layer BP ANNs.The output is one layer of ecosystem health index.After training and testing the BP ANNs,an optimal model of BP ANNs was selected to assess the ecosystem health of the Honghu Lake wetland.The result indicates that four stages can be identified based on the change of the ecosystem health from 1990 to 2008 and the ecosystem health index ranges from morbidity before the implementation of HLWPRDP(in 2002) to middle health after the implementation of the HLWPRDP(in 2005).It demonstrates that the HLWPRDP is effective and the BP ANN could be used as a tool for the assessment of ecosystem health.

The Internet and its Psychological and Social Effects on the UAEs Youth

The subject of this research concentrate on indicating psychological and social effects for the Internet on students in Sharjah University/Communication College/in other words the researcher try to know students opinion and impressions regarding the use of Internet and effect of the same, as well as opinion of positive and negative benefits regarding Internet, especially for the university＇s students who use Internet repeatedly in their daily routine. This stage marked by facts and characteristics based on search for information, explore the students world, and their expectations for that science. This study is the first in its kind in United Arab Emirates that try to shed light on the social and psychological effects of the lnternet, therefore we pave the way in front of those who administer lnternet and indicate to them guidelines for that to allow decisions maker to be aware about the world around university＇s student, the world that enjoy less interest for use of Internet at university, and what is the social and psychological effects of the use of Internet. And the study allow providing information and data that several sectors in society need. It draws clear image for the use of Internet at university by the student and whatever social and psychological effects that happened as a result of that use, so it consider as a survey for whom desire to know such information in United Arab Emirates.

Soft-Control for Collective Opinion of Weighted DeGroot Model

The DeGroot model is a classic model to study consensus of opinion in a group of individuals(agents). Consensus can be achieved under some circumstances. But when the group reach consensus with a convergent opinion value which is not what we expect, how can we intervene the system and change the convergent value? In this paper a mechanism named soft control is first introduced in opinion dynamics to guide the group's opinion when the population are given and evolution rules are not allowed to change. According to the idea of soft control, one or several special agents,called shills, are added and connected to one or several normal agents in the original group. Shills act and are treated as normal agents. The authors prove that the change of convergent opinion value is decided by the initial opinion and influential value of the shill, as well as how the shill connects to normal agents. An interesting and counterintuitive phenomenon is discovered: Adding a shill with an initial opinion value which is smaller(or larger) than the original convergent opinion value dose not necessarily decrease(or increase) the convergent opinion value under some conditions. These conditions are given through mathematical analysis and they are verified by the numerical tests. The authors also find out that the convergence speed of the system varies when a shill is connected to different normal agents. Our simulations show that it is positively related to the degree of the connected normal agent in scale-free networks.

Exploring link generation in a temporal evolution network for human mobility

The prevalence of mobile devices has spurred human mobility to be applied in mobile networking and communications by using network science, in which the temporal evolution of a network topology is of great importance for protocol design and performance analysis. This paper focuses on link generation in a temporal evolution network. Based on observations revealing the strong correlation between the connection patterns of different time periods, a link generation potential based on historical connections is proposed in this paper, aiming to provide a method for making topological predictions with less randomness. Using MIT Reality dataset, an evaluation of the accuracy of the proposed method was conducted. The experimental results demonstrate the proposal's adequacy in terms of its accuracy.

A biologically inspired model for pattern recognition

In this paper, a novel bionic model and its performance in pattern recognition are presented and discussed. The model is constructed from a bulb model and a three-layered cortical model, mimicking the main features of the olfactory system. The olfactory bulb and cortex models are connected by feedforward and feedback fibers with distributed delays. The Breast Cancer Wisconsin dataset consisting of data from 683 patients divided into benign and malignant classes is used to demonstrate the capacity of the model to learn and recognize patterns, even when these are deformed versions of the originally learned patterns. The performance of the novel model was compared with three artificial neural networks (ANNs), a back-propagation network, a support vector machine classifier, and a radial basis function classifier. All the ANNs and the olfactory bionic model were tested in a benchmark study of a standard dataset. Experimental results show that the bionic olfactory system model can learn and classify patterns based on a small training set and a few learning trials to reflect biological intelligence to some extent.