Trend Analysis of Landcover/ Landuse Change in Patani L.G.A, Delta State Nigeria

This study examines the use of GIS and Remote Sensing in trend analysis of landcover/landuse change in Patani L.G.A, Delta State Nigeria from 2005 to 2015. Thus the study is to carry out a multi-temporal analysis of development trends, thereby detecting the changes that have taken place between these periods. Two Landsat images, Landsat 7ETM+ (2005) and Landsat 8OLI (2015) were acquired, classified and change detection analysis was performed to determine the multi-temporal landcover/landuse changes between the years. The results showed that vegetation decreased from 16673.73 hectares in 2005 to 15973.9 hectares in 2015 covering 75.45% of landcover/landuse class in the study area, built up area gained from 3684.03 hectares in 2005 to 4346.37 hectares in 2015 covering 20.53 % in the study area, while water bodies also increased from 812.29 hectares in 2005 to 849.78 hectares in 2015 covering 4% of the study area. The study also indicated that the annual growth rate of Built up area has increased at 0.82% from 2005 to 2015, vegetation decreasing significantly at the rate of -0.21% from 2005 to 2015, and water bodies also increasing at a rate of 0.22% from 2005 to 2015. The results from this study can serve as a base for decision making and planning for urban planning and regional developments in Patani L.G.A

Cartographic Trend Analysis of Furbearer Harvest Distributions in Arkansas

Average by-county fur harvest for the last nine harvest seasons (1977-1985) was used as data points to be interpolated using nearest neighbor algorithms in computer-assisted trend analyses. COMPLOT maps were produced which represented a surface of harvest densities drawn over a map of Arkansas. Twelve furbearer species are examined, and topographic features of harvest density for each are interpreted in terms of ecology and/or buyer distribution. The trend surface technique removed some of the error inherent to harvest records, and produced an aesthetic graphical display of the information that was more easily interpreted and explained than other methods of analysis usually allow

China's Changing Energy Intensity Trend: A Decomposition Analysis

China experienced a dramatic decline in energy intensity from the onset of economic reform in the late 1970s until 2000, but since then rate of decline slowed and energy intensity actually increased in 2003. Most previous studies found that most of the decline was due to technological change, but disagreed on the role of structural change. To the best of our knowledge, no decomposition study has investigated the role of inter-fuel substitution in the decline in energy intensity or the causes of the rise in energy intensity since 2000. In this paper, we use logarithmic mean Divisia index (LMDI) techniques to decompose changes in energy intensity in the period 1980-2003. We find that: (1) technological change is confirmed as the dominant contributor to the decline in energy intensity; (2) structural change at the industry and sector (sub-industry) level actually increased energy intensity over the period of 1980-2003, although the structural change at the industry level was very different in the 1980s and in the post 1990 period; (3) structural change involving shifts of production between sub-sectors, however, decreased overall energy intensity; (4) the increase in energy intensity since 2000 is explained by negative technological progress; (5) inter-fuel substitution is found to contribute little to the changes in energy intensity.

Application of Trend Impact Analysis for predicting future fruit consumption

Knowledge of those aspects that motivate consumers towards more fruit consumption is necessary in order to implement policies to stimulate fruit consumption. To predict future fruit consumption based on such knowledge from experts, and based on historic consumption data, the method of Trend Impact Analysis (TIA) was applied to four countries. From the historic data, a trend or baseline has been estimated. TIA combines this information with expert knowledge to forecast future consumption. A Monte Carlo simulation was used to handle uncertainty in the TIA model thus developed. Despite the disadvantages of TIA, the method is suitable to explain a trend by means of impact factors, and offers an opportunity to deal with uncertain prognoses by experts. TIA is a relatively unknown method and requires more research and experience to judge if it is widely applicable, and if it provides a good alternative to more traditional forecasting methods

Trend Analysis of Annual and Seasonal Rainfall in Tawa command Area

The main objective of the study is to identify the trend in annual rainfall time series data as well as seasonal rainfall time series of four rainy months i.e. June, July, August and September during the period of 1971 to 2015. The annual sessional trend of rainfall was determinedby non-parametric Mann-Kendall test. Also a non-parametric Sen's Slope estimator was used for the determination of magnitude of trend. A functional relationship has been developed between variables using linear regression analysis in order to determine a linear trend of rainfall for the study area. The study concludes considering the result of all statistical test results, that the study area has shown variability in annual sessional rainfall pattern due to climatic variations. Also the sessional trend analysis of rainfall has suggested that there is a trendvariationof rainfall in the rainymonths

Recruitment Market Trend Analysis with Sequential Latent Variable Models

Recruitment market analysis provides valuable understanding of industry-specific economic growth and plays an important role for both employers and job seekers. With the rapid development of online recruitment services, massive recruitment data have been accumulated and enable a new paradigm for recruitment market analysis. However, traditional methods for recruitment market analysis largely rely on the knowledge of domain experts and classic statistical models, which are usually too general to model large-scale dynamic recruitment data, and have difficulties to capture the fine-grained market trends. To this end, in this paper, we propose a new research paradigm for recruitment market analysis by leveraging unsupervised learning techniques for automatically discovering recruitment market trends based on large-scale recruitment data. Specifically, we develop a novel sequential latent variable model, named MTLVM, which is designed for capturing the sequential dependencies of corporate recruitment states and is able to automatically learn the latent recruitment topics within a Bayesian generative framework. In particular, to capture the variability of recruitment topics over time, we design hierarchical dirichlet processes for MTLVM. These processes allow to dynamically generate the evolving recruitment topics. Finally, we implement a prototype system to empirically evaluate our approach based on real-world recruitment data in China. Indeed, by visualizing the results from MTLVM, we can successfully reveal many interesting findings, such as the popularity of LBS related jobs reached the peak in the 2nd half of 2014, and decreased in 2015.Comment: 11 pages, 30 figure, SIGKDD 201

The Trend Analysis on the Research Methods and Techniques Used in Research on Speaking

This research aimed to identify the method of research and teaching technique used and the educational levels preferred in students' thesis on speaking. Thisresearch used descriptive method. The subjects of research were 40 theses on speaking by students of English Education Study Program during the period of 2009-2012.The research data were taken from UPT Perpustakaan Tanjungpura University. The result of the study showed that based on the method of research used, Classroom Action Research was 65% or it was the most frequently used. Pre Experimental was 20% and Descriptive Study was 12.5%. Based on the teaching techniques used, Role Play was dominated about 22.5%, Chain Pictures was 10%, Songs andDrama were 5% in each. Based on the educational level researchers preferred; Junior High was 40%, Senior High was 40%, University was 7.5%, Course was 7.5% and Elementary level was 5%

From Trend Analysis to Virtual World System Design Requirement Satisfaction Study

Virtual worlds have become global platforms connecting millions of people and containing various technologies. The development of technology, shift of market value, and change of user preference shape the features of virtual worlds. In this paper, we first study the new features of virtual worlds and emergent requirements of system development through trend analysis. Based on the trend analysis, we constructed the new design requirement space. We then discuss the requirement satisfaction of existing virtual world system architectures and highlight their limitations through a literature survey. The comparison of existing system architectures sheds some light on future virtual world system development to match the changing trends of the user market. At the end of this study, we briefly introduce our ongoing study, a new architecture, called Virtual Net, and discuss its possibility in requirement satisfaction and new research challenges.Comment: 30 pages, 8 figures, 2 table