Trend Template Research Articles

Classical and Innovative-?en Trend Assessment under Climate Change Perspective

The main purpose of this paper is to provide a comparison between the innovative-Sen and classical trend methods. Additionally, significance levels at ±5% and ±10% levels are suggested for the first time on the innovative-Sen trend template, which works with the categorisation of given data into a set of classes such as 'low', 'medium' and 'high' values. However, the classical approaches consider holistic monotonic trend identification without categorisation. Classical trend analyses methods, Mann-Kendall trend test coupled with, Sen's slope and the classical regression line, are based on a set of restrictive assumptions, but the innovative-Sen approach does not have assumptions. Application of classical methods do not present significant trend component, however, the innovative-Sen trend method provides possible trend components in each cluster within the significance limits. Although the classical approaches do not indicate a significant trend, but innovative-Sen approach provides some categorically significant trends in detail and quantitative information.

Trend Analyses Revision and Global Monthly Temperature Innovative Multi-Duration Analysis

BackgroundClimate change evidence has been documented by different authors based on the long years’ monthly temperature measurements since long back. In the literature, annual-mean and 5-year moving average time series of global mean land–ocean temperature index and meteorological station data of global annual-mean surface air temperature changes are presented with a base period including some parts as uncertainty estimates. This paper provides an innovative method for refined calculation of global warming calculation.PurposeThe innovative multi-duration trend analysis application to the global monthly temperature data for identification of monthly temperature variability leads to temperature increase identifications in an innovative manner. The purpose is to present a detailed and refined innovative trend application methodology for global temperature increment calculation.MethodsAfter the general revision of non-parametric and parametric trend methodology explanations, the innovative trend template (ITT) analysis application is presented by considering two-half and multi-duration trend possibilities in the global monthly temperature records. ResultsThe ITT methodology also presents various features of the global temperature increments during the whole record duration on monthly basis leading to a set of verbal interpretations and numerical values for each month including “Low” (minimum), “High” (maximum), and “Medium” (moderate) temperature amounts. It is proven that, on average, there is 0.9 °C and 1.78 °C monthly temperature increments for “Low” and “High” temperatures, respectively, in addition to average incremental temperature of 1.33 °C.ConclusionThe innovative trend template (ITT) methodology is explained briefly and applied to global monthly temperature records from 1881 to 2013. This new methodology provides information about “Low” (minimum) and “High” (maximum) temperature records in addition to the “Medium” transitional temperatures. First, two-half and then multi-period innovative trend analysis implementations are explained graphically, verbally, and numerically. Finally, the ITTs application indicated that the warming at global scale is at about 0.75 °C, which was determined by some other approach as 0.76 °C ± 0.19 °C (IPCC, 2007).

Global warming quantification by innovative trend template method

Global warming quantification by innovative trend template method

Global warming quantification by innovative trend template method

As for the trend identification, the literature is full of quantitative studies, but with respect to two-probability distribution function (PDF) description remains at qualitative level. The main purpose of this paper is to convert the two-PDF description into quantitative form for objective and quantitative assessments. Such a goal is achieved on the basis of innovative trend templates, which indicate the arithmetic averages and the standard deviations of the two equal length halves of the given temperature record. Two-PDF explanations are represented by three combinations as changes in the arithmetic averages, standard deviations and in both parameters through their logical connections with the innovative template description. The application of the methodology is given for four mean annual temperature records from Istanbul City, Turkey. Global warming variations are described quantitatively as increases or decreases in the statistical parameters. The proposed methodology can be applied for any temperature record in the world.

Bearing Fault Diagnosis Based on Fault Characteristic Trend Template

Bearing Fault Diagnosis Based on Fault Characteristic Trend Template

Algerian rainfall innovative trend analysis and its implications to Macta watershed

Climate and land use changes impact hydrological records and especially precipitation time series, which have significance priority in any water resource planning, operation, management, and maintenance studies. In this paper, Macta watershed monthly precipitation records at 25 stations are studies by the innovative trend analysis method application in order to identify the climatological tendencies in each station leading to the regional variation pattern in the precipitation over the study area. For this purpose, innovative trend template is prepared separately for each station. The comparison of the arithmetic averages provides the trend slope in the meteorological records and the standard deviations provide a measure of variability. These templates also provide qualitative interpretations about the “low,” “medium,” and “high” precipitation range trends. It is noticed that there is the sub-region of decreasing trends in the northern part close to the Mediterranean Sea coastal area in the Macta basin, whereas at the south, the trends are in the increasing style. It is noticed from the quantitative analysis that in the Macta watershed “low” and “medium” rainfall ranges have commonly no-trend cases, but “high” rainfall values have decreasing trends.

Constraint-based Trend Template for Intrusion Detection

Intrusion detection systems (IDS) are special computer security tools which help detect intrusion attempts. Misuse based detection is one of the techniques which is used by IDS to recognize predefined attack signatures. Attack languages, also known as detection languages, are used to describe attack signatures. Detection languages should be simple, expressive and flexible enough to help encode event signature accurately and conveniently. This paper shows the effectiveness of constraint based Trend Template (TT) as an efficient detection language by encoding some attack scenarios and focusing on the Trend Detector which recognizes those signatures from intrusion data.

Diagnostic monitoring in anaesthesia using fuzzy trend templates for matching temporal patterns

A technique based on the concept of a ‘fuzzy trend template’ has been developed to identify characteristic patterns in multiple time-series. The method has its foundation in fuzzy logic and allows for the intuitive and transparent description of ‘templates’, which preserve nuances of vagueness, temporal relationships and quantitative descriptors. Evaluation of fuzzy trend templates can provide both belief and plausibility information for use in diagnostic applications. The technique has been applied to the diagnosis of specific problems in anaesthesia and has demonstrated sensitivity and specificity of 95 and 65%, respectively. Evaluation of fuzzy trend templates is, computationally, relatively efficient and has allowed a real-time implementation. The technique has the potential to be useful in any domain that requires temporal pattern recognition based on linguistic rules.

Managing temporal worlds for medical trend diagnosis

The medical trend diagnosis system TrenDx has been applied as a prototype for diagnosing pediatric growth disorders, and as a proof of concept in detecting clinically significant trends in hemodynamics and blood gases in intensive care unit patients. TrenDx diagnoses trends by matching patient data to patterns of normal and abnormal trends called trend templates that define disorders as typical patterns of relevant variables. These patterns consist of a partially ordered set of temporal intervals with uncertain endpoints. Bound to each temporal interval are value constraints on real-valued functions of measurable parameters. The temporal uncertainty in trend templates allows TrenDx to conclude both what trend pattern best matches the data and also when significant landmarks and phase transitions have occurred within the best matching trend. The temporal uncertainty in trend templates requires that TrenDx consider alternate temporal worlds in monitoring patient data. The number of temporal worlds grows worst case polynomially in the number of time slices of data. To manage the competing temporal worlds, TrenDx employs two techniques: beam search based on regression scores, and temporal granularity in the trend template definitions. These two techniques, described here in detail, allow TrenDx to choose different points in the trade-off between accuracy of trend detection and algorithm efficiency.