SPECTRAL TECHNIQUES AND SOFT COMPUTING

Soft Computing denotes a set of paradigma related to cognitive modelling, which in the last years have been intensively studied, since important synergy effects among members of this set have been disclosed. Because of this, Soft Computing has emerged as an environment to effectively work with red world complex problems. Fuzzy Logic, Genetic Algorithms and Neural Networks are possibly the best known representatives of Soft Computing. In this paper we show how Spectral Techniques may help to further study these subjects or to improve their performance. The name Spectral Techniques comprises Methods and Applications based on Abstract Harmonic Analysis.

SPECTRAL TECHNIQUES FOR OFF-LINE TESTING AND DIAGNOSIS OF COMPUTER SYSTEMS

In this paper we present some of our recent results on applications of spectral techniques over finite fields to the problems of testing and diagnosis of computer systems.

Impact of Spectral Nudging on the Downscaling of Tropical Cyclones in Regional Climate Simulations

This study investigated the simulations of three months of seasonal tropical cyclone （TC） activity over the western North Pacific using the Advanced Research WRF Model. In the control experiment （CTL）, the TC frequency was considerably overestimated. Additionally, the tracks of some TCs tended to have larger radii of curvature and were shifted eastward. The large-scale environments of westerly monsoon flows and subtropical Pacific highs were unreasonably simulated. The overestimated frequency of TC formation was attributed to a strengthened westerly wind field in the southern quadrants of the TC center. In comparison with the experiment with the spectral nudging method, the strengthened wind speed was mainly modulated by large-scale flow that was greater than approximately 1000 km in the model domain. The spurious formation and undesirable tracks of TCs in the CTL were considerably improved by reproducing realistic large-scale atmospheric monsoon circulation with substantial adjustment between large-scale flow in the model domain and large-scale boundary forcing modified by the spectral nudging method. The realistic monsoon circulation took a vital role in simulating realistic TCs. It revealed that, in the downscaling from large-scale fields for regional climate simulations, scale interaction between model-generated regional features and forced large-scale fields should be considered, and spectral nudging is a desirable method in the downscaling method.

Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000–2015) data

Mapping croplands,including fallow areas,are an important measure to determine the quantity of food that is produced,where they are produced,and when they are produced(e.g.seasonality).Furthermore,croplands are known as water guzzlers by consuming anywhere between 70%and 90%of all human water use globally.Given these facts and the increase in global population to nearly 10 billion by the year 2050,the need for routine,rapid,and automated cropland mapping year-after-year and/or season-after-season is of great importance.The overarching goal of this study was to generate standard and routine cropland products,year-after-year,over very large areas through the use of two novel methods:(a)quantitative spectral matching techniques(QSMTs)applied at continental level and(b)rule-based Automated Cropland Classification Algorithm(ACCA)with the ability to hind-cast,now-cast,and future-cast.Australia was chosen for the study given its extensive croplands,rich history of agriculture,and yet nonexistent routine yearly generated cropland products using multi-temporal remote sensing.This research produced three distinct cropland products using Moderate Resolution Imaging Spectroradiometer(MODIS)250-m normalized difference vegetation index 16-day composite time-series data for 16 years:2000 through 2015.The products consisted of:(1)cropland extent/areas versus cropland fallow areas,(2)irrigated versus rainfed croplands,and(3)cropping intensities:single,double,and continuous cropping.An accurate reference cropland product(RCP)for the year 2014(RCP2014)produced using QSMT was used as a knowledge base to train and develop the ACCA algorithm that was then applied to the MODIS time-series data for the years 2000–2015.A comparison between the ACCA-derived cropland products(ACPs)for the year 2014(ACP2014)versus RCP2014 provided an overall agreement of 89.4%(kappa=0.814)with six classes:(a)producer’s accuracies varying between 72%and 90%and(b)user’s accuracies varying between 79%and 90%.ACPs for the individual years 2000–2013 and 2015(ACP2000–ACP2013,ACP2015)showed very strong similarities with several other studies.The extent and vigor of the Australian croplands versus cropland fallows were accurately captured by the ACCA algorithm for the years 2000–2015,thus highlighting the value of the study in food security analysis.

Role of Triad Kinetic Energy Interactions for Maintenance of Upper Tropospheric Low Frequency Waves during Summer Monsoon 1988

In order to determine nonlinear energy exchanges into individual triad interactions in the frequency domain,spectral formulas are derived by use of the cross-spectral technique. First time attempt has been made to understandthe problem of maintenance of low frequency waves for tropical weather system by using this technique.The TOGAbasic level ill daily wind analyses on a 2.5 degree square grid around the global zone from 20°S-30°N at 200 hpa for92-day periods covering June, July and August of 1988 are used. Kinetic energy is gained at high frequencies and lostat low frequencies.In the planetary scale dynamics over tropics, barotropic nonlinear energy transfer plays a negativerole.Low frequency wave of period 45 day loses maximum amount of energy when it interacted with frequencies ofperiods 92 day and 30 day.45 day cycle is also the main source of energy for other frequencies. Distrubances of periodl 5 day gain maximum amount of energy.The major contribution comes from the triad interaction of the frequencies<7,l,6>.North of 20'N low frequency waves of period 30 to 92--day gain energy through nonlinear triadinteraction with the maximum gain at 22.5'N. The study may help to investigate the rapid loss of predictability of lowfrequency modes over tropics.

Novel Approach to Characterization of Rare Earth Complexation with 1, 5-Bis(2-Hydroxy-5-Chlorphenyl)-3-Cyanoformazan in Presence of Cetyltrimethylammonium Bromide

The ternary interaction of 1, 5 bis(2 hydroxy 5 chlorphenyl) 3 cyanoformazan (HCPCF) with cetyltrimethylammonium bromide (CTAB) and rare earths (RE: Yb, Dy, Er and Eu) was investigated at pH 9.84 by the microsurface adsorption spectral correction technique (MSASC). The aggregation of HCPCF on CTAB obeys the Langmuir isothermal adsorption and the interaction of RE with the HCPCF CTAB aggregate was first found to accord with the monolayer binding. The effects of temperature and ionic strength of solution on the aggregations were made. The binary aggregate and the ternary complex were characterized.

Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data

The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia,using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period.Rice-fallow cropland areas are those areas where rice is grown during the kharif growing season(June–October),followed by a fallow during the rabi season(November–February).These cropland areas are not suitable for growing rabi-season rice due to their high water needs,but are suitable for a short-season(≤3 months),low water-consuming grain legumes such as chickpea(Cicer arietinum L.),black gram,green gram,and lentils.Intensification(double-cropping)in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands.Several grain legumes,primarily chickpea,are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region.The suitability of rainfed and irrigated rice-fallow croplands for grain legume cultivation across South Asia were defined by these identifiers:(a)rice crop is grown during the primary(kharif)crop growing season or during the north-west monsoon season(June–October);(b)same croplands are left fallow during the second(rabi)season or during the south-east monsoon season(November–February);and(c)ability to support low water-consuming,short-growing season(≤3 months)grain legumes(chickpea,black gram,green gram,and lentils)during rabi season.Existing irrigated or rainfed crops such as rice or wheat that were grown during kharif were not considered suitable for growing during the rabi season,because the moisture/water demand of these crops is too high.The study established cropland classes based on the every 16-day 250 m normalized difference vegetation index(NDVI)time series for one year(June 2010–May 2011)of Moderate Resolution Imaging Spectroradiometer(MODIS)data,using spectral matching techniques(SMTs),and extensive field knowledge.Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics.The producers’and users’accuracies of the cropland fallow classes were between 75%and 82%.The overall accuracy and the kappa coefficient estimated for rice classes were 82%and 0.79,respectively.The analysis estimated approximately 22.3 Mha of suitable rice-fallow areas in South Asia,with 88.3%in India,0.5%in Pakistan,1.1%in Sri Lanka,8.7%in Bangladesh,1.4%in Nepal,and 0.02%in Bhutan.Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.

Rapid discovery and identification of 68 compounds in the active fraction from Xiao-Xu-Ming decoction(XXMD) by HPLC-HRMS and MTSF technique

Xiao-Xu-Ming decoction（XXMD） was a traditional Chinese prescription and first recorded in ＂Bei Ji Qian Jin Yao Fang＂.It has been widely used to treat theoplegia and the sequel of theoplegia in China.In the present work,high-performance liquid chromatography coupled with high resolution mass spectrometry（HPLC-HRMS） combined with the mass spectral tree similarity filter technique（MTSF）was used to rapidly discover and identify the compounds of the active fraction of XXMD.A total of 3362 compounds were automatically detected by HPLC-HRMS,and final 68 compounds were identified in the active fraction of XXMD.including 14 templated compounds（reference compounds）,50 related compounds fished by MTSF technique,and 4 unrelated compounds identified by manual method.This study successfully applied MTSF technology for the first time to discover and identify the components of Chinese prescription.The results demonstrated that MTSF technique should be useful to the discovery and identification of compounds in Chinese prescription.This study also proved that MTSF can be applied to the targeted phytochemical separation.