A secure and low‐energy zone‐based wireless sensor networks routing protocol for pollution monitoring

Sensor networks can be used in many sorts of environments. The increase of pollution and carbon footprint are nowadays an important environmental problem. The use of sensors and sensor networks can help to make an early detection in order to mitigate their effect over the medium. The deployment of wireless sensor networks (WSNs) requires high‐energy efficiency and secures mechanisms to ensure the data veracity. Moreover, when WSNs are deployed in harsh environments, it is very difficult to recharge or replace the sensor's batteries. For this reason, the increase of network lifetime is highly desired. WSNs also work in unattended environments, which is vulnerable to different sort of attacks. Therefore, both energy efficiency and security must be considered in the development of routing protocols for WSNs. In this paper, we present a novel Secure and Low‐energy Zone‐based Routing Protocol (SeLeZoR) where the nodes of the WSN are split into zones and each zone is separated into clusters. Each cluster is controlled by a cluster head. Firstly, the information is securely sent to the zone‐head using a secret key; then, the zone‐head sends the data to the base station using the secure and energy efficient mechanism. This paper demonstrates that SeLeZoR achieves better energy efficiency and security levels than existing routing protocols for WSNs. Copyright © 2016 John Wiley & Sons, Ltd.     

A regression‐based performance prediction framework for synchronous iterative algorithms on general purpose graphical processing unit clusters

Heterogeneous performance prediction models are valuable tools to accurately predict application runtime, allowing for efficient design space exploration and application mapping. The existing performance models require intricate system architecture knowledge, making the modeling task difficult. In this research, we propose a regression‐based performance prediction framework for general purpose graphical processing unit (GPGPU) clusters that statistically abstracts the system architecture characteristics, enabling performance prediction without detailed system architecture knowledge. The regression‐based framework targets deterministic synchronous iterative algorithms using our synchronous iterative GPGPU execution model and is broken into two components: the computation component that models the GPGPU device and host computations and the communication component that models the network‐level communications. The computation component regression models use algorithm characteristics such as the number of floating‐point operations and total bytes as predictor variables and are trained using several small, instrumented executions of synchronous iterative algorithms that include a range of floating‐point operations‐to‐byte requirements. The regression models for network‐level communications are developed using micro‐benchmarks and employ data transfer size and processor count as predictor variables. Our performance prediction framework achieves prediction accuracy over 90% compared with the actual implementations for several tested GPGPU cluster configurations. The end goal of this research is to offer the scientific computing community, an accurate and easy‐to‐use performance prediction framework that empowers users to optimally utilize the heterogeneous resources. Copyright © 2013 John Wiley & Sons, Ltd.     

New semiconducting silicides assembled from transition-metal-encapsulating Si clusters

We synthesized amorphous films composed of transition-metal-encapsulating Si clusters (MSi_n: M = Zr, Nb, Mo and W) by deposition of hydrogenated MSi_nH_x clusters onto solid substrates followed by annealing at 400-500 °C for dehydrogenation. The MSi_n (n = 7-20) cluster films are amorphous semiconductors with an optical gap > 0.4 eV and have larger electron and hole mobility than that of the hydrogenated amorphous Si (a-Si:H) film. In these films, while Si atoms form amorphous networks similar to those in a-Si:H films, the thermal stability is enhanced and the electronic disorder is reduced by the use of MSi_n clusters as the unit structures. Structure modeling by ab initio calculations for MSi_n films suggests that the encapsulated M atom works as a terminator of dangling bonds of the Si network.     

Relationship between electrical and morphological properties of nanocomposites

This paper presents a computer study of electrical and morphological properties of composite and nanocomposite films by help of self-made analytical software tools. Main attention is devoted to a relationship between the electrical properties and the morphology of the films. Methods of mathematical morphology are used to obtain structural parameters. A Monte Carlo method and the theory of percolation are used for the study of electrical properties. Conductivity is supposed to be either ohmic or by tunnel effect, or both in parallel. Current paths inside the composite structure form so-called fuzzy clusters below and especially close to the percolation threshold. Their study produces valuable additional information. The results of the morphological and transport analyses are compared and discussed. From them, information is searched about the processes.     

包装印刷材料实验课程化与学生创新思维培养

包装印刷材料实验课程化使得单纯的验证性实验转变为设计性实验,学生在综合设计各种材料的性能测试方案时,不仅能提高发现问题、分析问题、解决问题的能力,还能形成创新性思维。以广东工业大学为例,学校施行了包装印刷材料实践课程的教学改革,由此学生制定了制作四层瓦楞纸板并进行性能测试的课程实践方案,取得了较好的效果。实践证明：实验课程化有助于学生创新性思维的形成,值得总结和推广。     

Citizen Participation in Planning: The Relationship Between Objectives and Techniques

Problem: As Richard Florida's writings about the creative class garnered attention across the globe, planners and local government officials responded by enacting policies to attract and retain creative workers, often favoring spending for amenity and lifestyle attractions over more established economic development approaches. It is not clear, however, if the presence of these workers drives regional growth and development as effectively as more traditionally accepted place-based and institutional factors.

Purpose: In this article we explore the relationships between the presence of the creative class and regional economic performance, contrasting measures of regional creative capacity with traditional competitiveness factors.

Methods: We examine how Florida's creative class measures correlate with each other and with common indicators of economic performance for U.S. metropolitan areas. We also estimate multivariate regression models to compare the influence of Florida's measures to those of more traditional indicators of economic competitiveness on metropolitan job growth, income growth, and job instability.

Results and conclusions: We find that differences in Florida's measures of creativity are not generally associated with differences in metropolitan economic performance. Indicators of human capital and industry composition perform as well or better than talent, tolerance, and technology in explaining metropolitan job and income growth and job instability.

Takeaway for practice: Since we find measures derived from Florida's creative class hypotheses to be no more associated with positive economic outcomes than traditional competitiveness measures, we do not advocate replacing traditional economic development strategies with those based primarily on attracting the creative class. Programs supporting education, business creation, and industrial diversity are more likely to be effective tools for promoting economic well-being.

Research support: We received support from the Center for the Study of the American South and the Office of Economic and Business Development's Program on Southern Politics, Media, and Public Life, both of the University of North Carolina at Chapel Hill.     

The Inventive,the Educated and the Creative: How Do They Affect Metropolitan Productivity?

A longstanding research tradition assumes that endogenous technological development increases regional productivity. It has been assumed that measures of regional patenting activity or human capital are an adequate way to capture the endogenous creation of new ideas that result in productivity improvements. This process has been conceived as occurring in two stages. First, an invention or innovation is generated, and then it is developed and commercialized to create benefits for the individual or firm owning the idea. Typically these steps are combined into a single model of the “invention in/productivity out” variety. Using data on Gross Metropolitan Product per worker and on inventors, educational attainment, and creative workers (together with other important socioeconomic controls), we unpack the model back to the two-step process and use a SEM modeling framework to investigate the relationships among inventive activity and potential inventors, regional technology levels, and regional productivity outcomes. Our results show almost no significant direct relationship between invention and productivity, except through technology. Clearly, the simplification of the “invention in/productivity out” model does not hold, which supports other work that questions the use of patents and patenting related measures as meaningful innovation inputs to processes that generate regional productivity and productivity gains. We also find that the most effective measure of regional inventive capacity, in terms of its effect on technology, productivity, and productivity growth is the share of the workforce engaged in creative activities.