Quantifying Spatio Temporal Changes in Coastal Buit-up area of South Goa based on Landsat Imageries using Google Earth Engine

Urban flooding has become a significant concern across many towns and cities in the Asia Pacific. Vulnerabilityand its components must be understood in order to minimize flood risks. Rapid urban growth occurs in developing countries,resulting from unplanned settlements growing along the rivers, and coastlines are at greater risk. On average, a total of 40%of the world’s population lives in narrow coastal belts that take up 7% of the total world land area. Coastal areas areurbanizing at an unprecedented rate that is posing a common threat to humans and ecosystems. Low-lying coastal areas areespecially susceptible to climate change related coastal hazards such as; sea level rise, storm surge, coastal flooding, landsubsidence etc.This study has been carriedoutacross four talukas of South Goa district, India's smallest state, locatedalong the Arabian sea. The low-lying coastal belt of South Goa district is dotted with world famous sandy beaches ofPalolem, Agonda, Colva etc. which attract millions of tourists every year. The present study has assessed the spatio-temporalgrowth of built-up land in low-lying coastal areas (Marmugao, Salcette, Quepem and Canacona) of South goa district.GoogleEarthEngineplatformwasusedtoestimateNormalizedDifferenceBuildIndex(NDBI)basedonLandsatETM+/OLI imageries for 2009, 2015 and 2020 to determine and map spatio-temporal changes in the total built-up area. Theresult revealed that there had been a rapid built-up area increment in South goa coastal belt by 24.94 Sq. Km between 2009(88.46 Sq. Km) and 2015 (113.40 Sq. Km) and by 15.14 Sq. Km between 2015 (113.40 Sq. Km) and 2020 (128.54 Sq. Km).The main driving force behind this phenomenon is the extensive land use changes for haphazard tourism development (inSalcetteandCanacona)andimmigration(inMarmugao).However,theconversionoftraditionalpaddyfieldsandmodification of natural drainage systemtoincrease built-up areas cansignificantly increase the physical andsocialvulnerability in low lying areas of Salcette and Canacona against the coastal hazards. This study may help urban planners/authoritiestolettheregiondevelopin sustainablemanne

Processing and Prospect of Electronic Nose

Recently, a Novel Coronavirus Pneumonia (NCP) swept the globe. This kind of new virus has extremely high infection efficiency, which has brought great disaster to human's production and daily life. However, it is reported that lung cancer and other diseases with a high incidence will lead to a very high mortality rate if they are not diagnosed and treated in time. Therefore, it is urgent to design an accurate and convenient new diagnostic equipment. Due to the increasing innovation of sensor module in the field of Information and Communication Technology (ICT), electronic nose emerges as the times require. The device can use sensors to analyze Volatile Organic Compounds exhaled by people with certain diseases and identify chemical components of various odor and flavor. In addition, many other types of sensors and classification methods such as machine learning (ML) algorithms are also mentioned in this paper. At the end of the paper, the author attached a related experiment and some shortcomings and prospects of electronic nose as well

Optimized High Resolution 3D Dense-U-Net Network for Brain and Spine Segmentation

The 3D image segmentation is the process of partitioning a digital 3D volumes into multiple segments. This paper presents a fully automatic method for high resolution 3D volumetric segmentation of medical image data using modern supervised deep learning approach. We introduce 3D Dense-U-Net neural network architecture implementing densely connected layers. It has been optimized for graphic process unit accelerated high resolution image processing on currently available hardware (Nvidia GTX 1080ti). The method has been evaluated on MRI brain 3D volumetric dataset and CT thoracic scan dataset for spine segmentation. In contrast with many previous methods, our approach is capable of precise segmentation of the input image data in the original resolution, without any pre-processing of the input image. It can process image data in 3D and has achieved accuracy of 99.72% on MRI brain dataset, which outperformed results achieved by human expert. On lumbar and thoracic vertebrae CT dataset it has achieved the accuracy of 99.80%. The architecture proposed in this paper can also be easily applied to any task already using U-Net network as a segmentation algorithm to enhance its results. Complete source code was released online under open-source license

Determination of the breast cancer tumor diameter using a UWB microwave antenna system

This paper presents a novel ultra-wideband microwave antenna system to detect breast cancer and estimate tumor diameter. The system operates within the frequency range of 1 to 12 GHz and comprises a microstrip-fed monopole antenna that encircles the breast to identify the presence of tumors. The study demonstrates that a tumor within the breast can be detected by observing changes in the distribution of current density within the breast tissue, particularly in regions containing tumors of varying sizes. The research findings reveal that the system can identify breast tumors with the highest recorded current density of 188 A/m2 in cases with a tumor diameter of 30 mm, while the lowest recorded current density is 140 A/m2 for tumors with a diameter of 5 mm. Furthermore, the highest Specific Absorption Rate (SAR) value measured at the surface of the breast model is 0.2 W/kg. To determine the diameter of the tumors, the system collects and analyzes backscattered waves from a breast model. The investigation covers tumors with diameters ranging from 1 mm to 35 mm, and the received signals are recorded. In contrast to prior research, this study introduces an empirical model with a remarkable accuracy rate of 92.28% for characterizing the diameter of breast tumors based on the measurement analysis.</p

FOPI/FOPID Tuning Rule Based on a Fractional Order Model for the Process

This paper deals with the design of a control system based on fractional order models and fractional order proportional-integral-derivative (FOPID) controllers and fractional-order proportional-integral (FOPI) controllers. The controller design takes into account the trade-off between robustness and performance as well as the trade-off between the load disturbance rejection and set-point tracking tasks. The fractional order process model is able to represent an extensive range of dynamics, including over-damped and oscillatory behaviors and this simplifies the process modelling. The tuning of the FOPID and FOPI controllers is achieved by using an optimization, as a first step, and in a second step, several fitting functions were used to capture the behavior of the optimal parameters of the controllers. In this way, a new set of tuning rules called FOMCoRoT (Fractional Order Model and Controllers Robust Tuning) is obtained for both FOPID and FOPI controllers. Simulation examples show the effectiveness of the proposed control strategy based on fractional calculus

Advanced Parameterisation of Online Handwriting in Writers with Graphomotor Disabilities

Grafomotorick© obt­e (GD) vraznÄ ovlivuj­ kvalitu ivota koln­m vÄkem poÄ­naj­c, kde se vyv­jej­ grafomotorick© schopnosti, a do dchodov©ho vÄku. VÄasn diagnza tÄchto obt­­ a terapeutick zsah maj­ velk vznam k jejich zlepen­. Vzhledem k tomu, e GD souvis­ z v­cermi symptomy v oblasti kinematiky, zkladn­ kinematick© parametry jako rychlost, zrychlen­ a vih prokzaly efektivn­ kvantizaci tÄchto symptom. Objektivn­ vpoÄetn­ syst©m podpory rozhodovn­ pro identifikaci a vyeten­ GD vak nen­ dostupn. A proto je hlavn­m c­lem m© disertaÄn­ prce vzkum pokroÄil© metody parametrizace online p­sma pro analzu GD se speciln­m zamÄen­m na vyuit­ metod zlomkov©ho kalkulu. Tato prce je prvn­, kter experimentuje s vyuit­m derivac­ neceloÄ­seln©ho du (FD) pro analzu GD pomoc­ online p­sma z­skan©ho od pacient s Parkinsonovou nemoc­ a u dÄt­ koln­ho vÄku. Byla navrena a evaluovna nov metoda parametrizace online p­sma zaloena na FD vyuit­m Grnwald-Letnikova p­stupu. Bylo dokzno, e navren metoda vznamnÄ zlepuje diskriminaÄn­ s­lu a deskriptivn­ schopnosti v oblasti Parkinsonick© dysgrafie. StejnÄ tak metoda pozitivnÄ ovlivnila i nejmodernÄj­ techniky v oblasti analzy GD u dÄt­ koln­ho vÄku. Vyvinut parametrizace byla optimalizovna s ohledem na vpoÄetn­ nroÄnost (a o 80 %) a tak© na vyladÄn­ du FD. Ke konci prce byly porovnny v­cer© p­stupy vpoÄtu FD, jmenovitÄ Riemann-Liouvillv, Caputv spoleÄnÄ z Grnwald-Letnikovm p­stupem za Äelem identifikace tÄch nejvhodnÄj­ch pro jednotliv© oblasti analzy GD.Graphomotor disabilities (GD) significantly affect the quality of life beginning from the school-age, when the graphomotor skills are developed, until the elderly age. The timely diagnosis of these difficulties and therapeutic interventions are of great importance. As GD are associated with several symptoms in the field of kinematics, the basic kinematic features such as velocity, acceleration, and jerk were proved to effectively quantify these symptoms. Nevertheless, an objective computerized decision support system for the identification and assessment of GD is still missing. Therefore, the main objective of my dissertation is the research of an advanced online handwriting parametrization utilized in the field of GD analysis, with a special focus on methods based on fractional calculus. This work is the first to experiment with fractional-order derivatives (FD) in the GD analysis by online handwriting of Parkinsonâs disease (PD) patients and school-age children. A new online handwriting parametrization technique based on the Grnwald-Letnikov approach of FD has been proposed and evaluated. In the field of PD dysgraphia, a significant improvement in the discrimination power and descriptive abilities was proven. Similarly, the proposed methodology improved current state-of-the-art techniques of GD analysis in school-aged children. The newly designed parametrization has been optimized in the scope of the computational performance (up to 80 %) as well as in FD order fine-tuning. Finally, various FD-approaches were compared, namely Riemann-Liouville, Caputoâs, together with Grnwald-Letnikov approximation to identify the most suitable approach for particular areas of GD analysis.