Trend Analysis Approach Research Articles

Characteristics of Grain Size Distribution on Beaches Sediment of Sumba Island, Nusa Tenggara Timur Based on Grainsize and Geochemical Data

Study of beaches sediment characteristics were conducted on three beaches on Sumba Island, East Nusa Tenggara.The research is a part of Widya Nusantara Expedition which conducted by using Research Vessel of Baruna Jaya VIII. The aim of this study is to determine the characteristics of coastal deposits through the observation of grain size by using the grain size trend analysis approach (Grain Size Trend Analysis, commonly abbreviated as GSTA) and geochemical analysis. A total of 36 samples were taken on each coast representing high tide, transition and low tide along the coast. A grain size analysis was performed using a Malvern Mastersizer 2000 that was processed with Gradistat 4.0 software. Geochemical analysis was carried out using X-ray fluorescence spectrometry (XRF). The distribution of beach sediments is dominated by moderate sand - coarse sand and differences on content of geochemical elements (Ca, Sr, Fe, K, and Ti). The coastal conditions that are connected to the Indian Ocean (B1) have different characteristics from the beach that connected to the Sumba strait (B5 and B7). GSTA analysis showed sediment of Laboya Beach finer than sediment on Waikelo and Melolo Beach. Geochemical elements on Laboya Beach indicates different values than others. It indicates there are differences in the provenance and composition of sediment on the all three beaches. The supply of coastal deposits on these three beaches is influenced by the mechanism of precipitation of the walls and the processes of waves and rivers.Keywords: distribution, sediment, grainsize, geochemical, XRF, beach sediment.

A trend analysis approach for air quality network data

Trend analysis of air pollutant concentrations becomes problematic when applied to data from air quality monitoring networks containing time series of differing lengths. The average trend from such data can be misleading due to biases in the monitoring network. For example, if new monitoring sites located in more polluted locations are added to a network, the introduction of these time series can leverage the trend upwards. A method for resolving this problem was developed, using rolling window regression to recursively calculate the change in pollutant concentration as a function of time, which can be used as a proxy for the true trend. The efficacy of the method was established by conducting simulations with known trends. The rolling change trend was shown to more accurately reflect the true trend than simply averaging the time series. Application of the technique to estimate trends in NOx, NO2 and NO2/NOx concentrations at London roadside monitoring sites over the period 2000–2017 revealed clear differences from the simple average. In particular, a significant monotonic downward trend in NOx concentration was observed, in stark contrast to the average trend, which suggested little change in NOx concentration had occurred over the same period. By accurately representing trends using time series of different lengths, this method has the benefit of being able to describe changes in air quality for locations and time periods with otherwise insufficient data.

Machine learning combined with non-targeted LC-HRMS analysis for a risk warning system of chemical hazards in drinking water: A proof of concept

Guaranteeing clean drinking water to the global population is becoming more challenging, because of the cases of water scarcity across the globe, growing population, and increased chemical footprint of this population. Existing targeted strategies for hazard monitoring in drinking water are not adequate to handle such diverse and multidimensional stressors. In the current study, we have developed, validated, and tested a machine learning algorithm based on the data produced via non-targeted liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) for the identification of potential chemical hazards in drinking water. The machine learning algorithm consisted of a composite statistical model including an unsupervised component (i.e. principal component analysis PCA) and a supervised one (i.e. partial least square discrimination analysis PLS-DA). This model was trained using a training set of 20 drinking water samples previously tested via conventional suspect screening. The developed model was validated using a validation set of 20 drinking water samples of which 4 were spiked with 15 labeled standards at four different concentration levels. The model successfully detected all of the added analytes in the four spiked samples without producing any cases of false detection. The same validation set was processed via conventional trend analysis in order to cross validate the composite model. The results of cross validation showed that even though the conventional trend analysis approach produced a false positive detection rate of ≤5% the composite model outperformed that approach by producing zero cases of false detection. Additionally, the validated model went through an additional test with 42 extra drinking water samples from the same source for an unbiased examination of the model. Finally, the potentials and limitations of this approach were further discussed.

Trend estimation for complex survey designs of water chemistry indicators from Sierra Nevada Lakes

Surveys for long-term monitoring programs managing natural resources often incorporate sampling design complexity. However, design weights are often ignored in trend models of data from complex sampling designs. Generalized random tessellation stratified samples of a simulated population of lakes are selected with various levels of survey design complexity, and three trend approaches are compared. We compare an unweighted trend model, linear regression models of the trend in design-based estimates of annual status, and a probability-weighted iterative generalized least squares (PWIGLS) approach with a linearization variance. The bias and confidence interval coverage of the trend estimate and the size and power of the trend test are used to evaluate weighted and unweighted approaches. We find that the unweighted approach often outperforms the other trend approaches by providing high power for trend detection and nominal confidence interval coverage of the true trend regression parameter. We also find that variance composition and revisit design structure affect the performance of the PWIGLS estimator. When a subpopulation exhibiting an extreme trend is sampled disproportionately to its occurrence in the population, the unweighted approach may produce biased estimates of trend with poor confidence interval coverage. We recommend considering variance composition and potential subpopulation trends when selecting sampling designs and trend analysis approaches.

FREQUENCY ANALYSIS OF MODIS NDVI TIME SERIES FOR DETERMINING HOTSPOT OF LAND DEGRADATION IN MONGOLIA

Abstract. This study examines MODIS NDVI satellite imagery time series can be used to determine hotspot of land degradation area in whole Mongolia. The trend statistical analysis of Mann-Kendall was applied to a 16-year MODIS NDVI satellite imagery record, based on 16-day composited temporal data (from May to September) for growing seasons and from 2000 to 2016. We performed to frequency analysis that resulting NDVI residual trend pattern would enable successful determined of negative and positive changes in photo synthetically health vegetation. Our result showed that negative and positive values and generated a map of significant trends. Also, we examined long-term of meteorological parameters for the same period. The result showed positive and negative NDVI trends concurred with land cover types change representing an improve or a degrade in vegetation, respectively. Also, integrated the climate parameters which were precipitation and air temperature changes in the same time period seem to have had an affecting on huge NDVI trend area. The time series trend analysis approach applied successfully determined hotspot of an improvement and a degraded area due to land degradation and desertification.

Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

Abstract Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA) approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS) and end of season (EOS) was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0) and a significant decrease in other greenness trend maps (amplitude 1 and phase 1) was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0) was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1) was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

RELIGI, BUDAYA DAN EKONOMI KREATIF: Prospek dan Pengembangan Pariwisata Halal di Cirebon

Abstract This article confirms that tourism activities including religious, cultural and creative centers in Cirebon are developing separately from local government policy and program implementation, but tourism development activities are getting more advanced in the city and district of Cirebon. With a trend-analysis approach, this article is based on data collected through interviews, exploration of events, news, and information from print media and electronic media, as well as documents from tourism organizers in Cirebon. This paper concludes that Cirebon positioned itself as one of the destinations for the development of halal tourism that became the center of the tourism industry in the future. Keywords : Religion, Culture, Creative Economy, Halal Tourism. Abstrak Artikel ini menegaskan bahwa aktivitas pariwisata termasuk sentra religi, budaya dan ekonomi kreatif di Cirebon berkembang secara terpisah dari sisi kebijakan pemerintah daerah, pelaksanaan program-program, dan strategi pengembangan kawasan wisata baik di kota dan kabupaten Cirebon. Dengan pendekatan trend-analysis, artikel ini berpijak pada data yang dikumpulkan melalui hasil wawancara, eksplorasi terhadap peristiwa, berita, dan informasi dari media cetak dan media elektronik, serta dokumen dari institusi penyelenggara pariwisata di Cirebon. Tulisan ini men yimpulkan bahwa Cirebon memposisikan diri sebagai salah satu destinasi bagi pengembangan wisata halal yang menjadi sentra industri pariwisata di masa mendatang. Kata Kunci : Religi, Budaya, Ekonomi Kreatif, Wisata Halal

A stylized trend analysis approach for process monitoring and fault diagnosis

A stylized trend analysis was developed to identify recurring or standard operating procedures (SOP) such as equipment switching or maintenance from plant process history data to detect faults and near misses due to operator errors or equipment failures. Trend based fault detection and diagnosis systems have not been implemented widely in the chemical process industries because known fault scenarios are typically required. Known fault scenarios were not required for the stylized trend analysis because faults and near misses were identified by comparing trends with normal SOP transition responses. Large volumes of historical data were processed automatically allowing corrective action to be taken prior to an incident. The stylized trend analysis was demonstrated to detect unsteady‐state transition faults on historical distributed control system data simulated for a continuous process ethylene plant dryer switching operation. © 2017 American Institute of Chemical Engineers Process Process Saf Prog 37:411–418, 2018

Half a century of changing mercury levels in Swedish freshwater fish.

The variability of mercury (Hg) levels in Swedish freshwater fish during almost 50 years was assessed based on a compilation of 44 927 observations from 2881 waters. To obtain comparable values, individual Hg concentrations of fish from any species and of any size were normalized to correspond to a standard 1-kg pike [median: 0.69 mg kg−1 wet weight (ww), mean ± SD: 0.84 ± 0.67 mg kg−1 ww]. The EU Environmental Quality Standard of 0.02 mg kg−1 was exceeded in all waters, while the guideline set by FAO/WHO for Hg levels in fish used for human consumption (0.5–1.0 mg kg−1) was exceeded in 52.5 % of Swedish waters after 2000. Different trend analysis approaches indicated an overall long-term decline of at least 20 % during 1965–2012 but trends did not follow any consistent regional pattern. During the latest decade (2003–2012), however, a spatial gradient has emerged with decreasing trends predominating in southwestern Sweden.

PROYEKSI PRODUKSI BERAS DAN STRATEGI MEWUJUDKAN SWASEMBADA BERAS DI KABUPATEN KETAPANG

Total rice production in Ketapang District compared with other districts in West Kalimantan is quite high, which is take the the fourth place in rice producing district in West Kalimantan Province. However, based on the development of rice production number is also known that rice production in Ketapang District experienced a significant decline, from a range of more than 100,000 tons per year down to less than 100,000 tons per year starting in 2008 (BPS Ketapang District, 2011) . Based on its development , the rate of change in the availability of rice in Ketapang very volatile and tends to decrease, while the rate of population increase. This needs to be a concern because the population rate will always increase, so it must be balanced with stability increase of rice production, to fulfill the basic needs of the staple food of the community . Based on the problem, this research aims to provide the projection of rice production and consumption in the next seven years and its implications for self-sufficiency in rice and to formulate appropriate strategies that should be implemented in order to achieve self-sufficiency in rice in Ketapang District. Analysis of projected production and consumption of rice in Ketapang calculated using Sofware Analysis of Food Consumption Patterns, with trend analysis approach, by considering the changes of the amount of food production and consumption within the last 5 years to predict the amount of rice production and consumption in the next 7 years. The data used are secondary data from annual data from BPS, namely Ketapang in Numbers 2007-2011. As for formulating strategies in order to achieve self-sufficiency in rice used SWOT analysis . The analysis showed that the district can achieve rice surplus in 2016 if the rice harvested area and productivity can be increased respectively by 3 % and 5 %, while still retaining the decline in rice consumption by 0.75 % per year. Based on the results of the SWOT analysis appropriate strategy to be applied is progressive strategy, by focusing on the strength of Ketapang District. Thus, the formulation of a strategy that gained intensification and extension of land, diversification of food in community and institutional strengthening. Key words : projections of production , self-sufficiency in rice

A Longitudinal Study of Possible Links between Tax Imputation and Dividend Reinvestment Plans: Australian Evidence

This study focuses on the relationship between dividend payout ratio and DRP (Dividend Reinvestment Plan) adoption within the framework of the Australian dividend tax imputation system. Since the decision to adopt the DRP (Dividend Reinvestment Plan) is effected through the distribution of dividends, a longitudinal study of dividend payout ratios and DRP adoptions over time during the sample period (1995-2009), places the DRP decision in the right perspective. We also look at the DRP effect on certain firm characteristics over time using cross-sectional longitudinal data. The study addresses the binary longitudinal data analysis, using the trend and GEE (General Estimating Equation) approaches, to examine the DRP effect on dividend payout ratio and other firm characteristics. The results of both the trend analysis and GEE approach indicate that DRP decisions are prompted by high dividend payout ratio, low profitability and low liquidity over time. The highly significant time coefficient in GEE estimates shows the longitudinal effect on the DRP decision.

Role of Loan Syndication in Project Finance: An Approach to Risk Management

Loan syndication as a project financing mechanism has increased over the last decade despite the diverging needs of the lenders. Loan syndication as a mechanism to finance a project is becoming a trend in developing economy. Many international project like infrastructure project and power project are being financed by the lenders through loan syndication. Both private sector and public sector financial institution are taking major participation in this lending process through a syndicate which is enhancing the entrepreneurship strategy in the emerging economy. This paper examines the application of loan syndication in project finance through analyzing the data of 2006-2011 loan allocation derived from Bank for international settlement by applying the trend analysis approach. The objective of the analysis is to know about the mechanism and to study the trend, how this concept is useful for both side i.e. lender (syndicate) and the project executer (borrower) from risk management point of view. Finally the findings give a bird’s eye view about the concept and how it is used as a strategic approach for fund mobilization and risk diversification.

Trend and extreme occurrence of precipitation in a mid‐latitude Eurasian steppe watershed at various time scales

AbstractThe confounding effects of step change invalidate the stationarity assumption of commonly used trend analysis methods such as the Mann–Kendall test technique, so previous studies have failed to explain inconsistencies between detected trends and observed large precipitation anomalies. The objectives of this study were to (1) formulate a trend analysis approach that considers nonstationarity due to step changes, (2) use this approach to detect trends and extreme occurrences of precipitation in a mid‐latitude Eurasian steppe watershed in North China, and (3) examine how runoff responds to precipitation trends in the study watershed. Our results indicate that annual precipitation underwent a marginal step jump around 1995. The significant annual downward trend after 1994 was primarily due to a decrease in summer rainfall; other seasons exhibited no significant precipitation trends. At a monthly scale, July rainfall after 1994 exhibited a significant downward trend, whereas precipitation in other months had no trend. The percentage of wet days also underwent a step jump around 1994 following a significant decreasing trend, although the precipitation intensity exhibited neither a step change nor any significant trend. However, both low‐frequency and high‐frequency precipitation events in the study watershed occurred more often after than before 1994; probably as either a result or an indicator of climate change. In response to these precipitation changes, the study watershed had distinctly different precipitation‐runoff relationships for observed annual precipitations of less than 300 mm, between 300 and 400 mm, and greater than 400 mm. Copyright © 2013 John Wiley & Sons, Ltd.

Does the Planetree Patient-Centered Approach to Care Pay Off?

Although the Planetree patient-centered approach to care is being implemented in many institutions around the world, its impact is still the subject of some debate. On the one hand, it is viewed as the most cost-effective way to provide care and create a positive work environment that reduces staff burnout. On the other hand, it is argued that it requires higher staffing ratios and a substantial infusion of financial resources and is time consuming, which in turn results in more work. The present study addresses the economic agenda of the Planetree patient-centered approach to care and has been designed to answer the following question: do the advantages of the Planetree patient-centered approach outweigh its costs? This question is of considerable interest for health care administrators and managers because the relevant authorities the world over have limited resources to allocate to health care organizations. Using a trend analysis approach to cost-benefit in a rehabilitation center, this study shows that the revenues the model generates are greater than the costs of implementing it. Fewer grievances and vacant positions, an improved employee retention rate, a better working atmosphere, and a high level of employee satisfaction (higher than in similar establishments) were also noted.

Swell impact on reef sedimentary processes: A case study of the La Reunion fringing reef

AbstractTwo surface‐sediment sampling campaigns were carried out in November and December 2003, before and after a strong swell event, in the back‐reef area of a microtidal fringing reef on the western coast of La Reunion, Indian Ocean. The spatial distributions of the mean grain size, sorting and skewness parameters are determined, and grain‐size trend analysis is performed to estimate the main sediment transport pathways in the reef. The results of this analysis are compared with hydrodynamic records obtained in the same reef area during fair weather conditions and during swell events. Sediment dynamics inferred from the hydrodynamic records show that significant sediment erosion and transport occur only during swell events and under strongly agitated sea states. Under normal wave conditions, there is a potential for onshore sediment transport from the reef‐flat to the back‐reef, but this transport is episodic and occurs principally during high‐tide stages. Sediment transport trends revealed by the grain‐size trend analysis method show onshore and alongshore low‐energy transport processes that are in agreement with the hydrodynamic records. The grain‐size trend analysis method also provides evidence of an offshore high‐energy transport trend that could be interpreted as a real physical process associated with return flow from the shore to the reef. The impact of swell on the reef sediment dynamics is clearly demonstrated by onshore and alongshore transport. Considering different combinations of the vector transport trends computed through the grain‐size trend analysis approach, more realistic and pertinent results can be obtained by applying an exclusive OR operation (XOR case) on the vectors. The main results presented here highlight a trend towards the accumulation of carbonate sands in the back‐reef area of the fringing reef. These sediments can only be resuspended during extreme events such as storms or tropical cyclones.

Trend analysis of acousto-ultrasonic signals for integrity evaluation of metallic aerostructures

By attaching a network of piezoelectric transducers over a metallic aircraft fuselage panel, the paper shows the changes of multi-path acousto-ultrasonic (AU) signals which pass through the aerostructure under fatigue loading. Based on the whole life-cycle of the multi-path AU signals collected from a metallic aerostructure until complete fracture, two different trend analysis approaches are presented in detail for evaluation of structural deterioration. One is based on damage indices computed from the changes of the AU signals with respect to their baseline signals in terms of extracted waveform envelopes and phases, and the other is based on principal component analysis (PCA) to reveal the hidden variation patterns of the AU signals. Consistent trends are shown to be produced by both approaches. Whilst the relationship between the complete set of the multi-path AU signals acquired and the gradual deterioration in structural integrity is found to be represented by the statistical trends of the damage indices in the first approach, it is found to generally follow an inverse U-shape trajectory in the feature space formed by the two most significant principal bases in the second approach. Furthermore, the PCA results are shown to provide a good basis to develop an AU-based traffic light system for aerostructure integrity.

An integrated qualitative trend analysis approach to identify process abnormalities: A case of oil export pumps in an offshore oil and gas production facility

Oil and gas production can be largely benefited by minimizing unwanted production losses. This can be done by effective identification of system anomalies and faults. In standard control systems these abnormalities can be observed as gradually deviating trends from the norms. Available tools for monitoring these trends, in some cases, may not be enough to reveal hidden faulty features. In order to interpret these changes accurately, measured data must be visualized as a combination of multiple sensor signals within a particular domain. This article suggests an approach to effectively utilize integrated data from multiple sources, and defines a set of 12 fault features. The approach, in principle, encodes real plant data in the form of logical IF-THEN rules in Microsoft Excel. Confidence values are set based on these interpretations to differentiate between normal and abnormal conditions exhibited by the system. This is to provide an opportunity for the process and maintenance engineers to effectively identify the equipment's health based on the early identification of developing abnormalities.

A trend pattern assessment approach to microarray gene expression profiling data analysis

We study the problem of how to assess the reliability of a statistical measurement on data set containing unknown quantity of noises, inconsistencies, and outliers. A practical approach that analyzes the dynamical patterns (trends) of the statistical measurements through a sequential extreme-boundary-points (EBP) weed-out process is explored. We categorize the weed-out trend patterns (WOTP) and examine their relation to the reliability of the measurement. The approach is applied to the processes of extracting genes that are predictive to BCL2 translocations and to clinical survival outcomes of diffuse large B-cell lymphoma (DLBCL) from DNA Microarray gene expression profiling data sets. Fisher’s Discriminate Criterion (FDC) is used as a statistical measurement in the processes. It is found that the weed-out trend analysis (WOTA) approach is effective for qualitatively assessing the statistics-based measurements in the experimentations conducted.

Trend Analysis for the Projection of Energy-Related Carbon Dioxide Emissions

Carbon dioxide is one of the most foremost greenhouse gases in the atmosphere. Carbon dioxide emission is very crucial for both health and environment. Trend analysis approach was employed for modeling world total carbon dioxide emissions from the consumption of coal and all fossil fuels (petroleum, flaring of natural gas, natural gas, and coal). The results obtained from the analyses showed that the models can be used for CO2 emission projections into the future planning.

MAROS: a decision support system for optimizing monitoring plans.

The Monitoring and Remediation Optimization System (MAROS), a decision-support software, was developed to assist in formulating cost-effective ground water long-term monitoring plans. MAROS optimizes an existing ground water monitoring program using both temporal and spatial data analyses to determine the general monitoring system category and the locations and frequency of sampling for future compliance monitoring at the site. The objective of the MAROS optimization is to minimize monitoring locations in the sampling network and reduce sampling frequency without significant loss of information, ensuring adequate future characterization of the contaminant plume. The interpretive trend analysis approach recommends the general monitoring system category for a site based on plume stability and site-specific hydrogeologic information. Plume stability is characterized using primary lines of evidence (i.e., Mann-Kendall analysis and linear regression analysis) based on concentration trends, and secondary lines of evidence based on modeling results and empirical data. The sampling optimization approach, consisting of a two-dimensional spatial sampling reduction method (Delaunay method) and a temporal sampling analysis method (Modified CES method), provides detailed sampling location and frequency results. The Delaunay method is designed to identify and eliminate redundant sampling locations without causing significant information loss in characterizing the plume. The Modified CES method determines the optimal sampling frequency for a sampling location based on the direction, magnitude, and uncertainty in its concentration trend. MAROS addresses a variety of ground water contaminants (fuels, solvents, and metals), allows import of various data formats, and is designed for continual modification of long-term monitoring plans as the plume or site conditions change over time.