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One of the most active volcanoes in the island of Java is Merapi mount which was experienced the last major eruption peak on October 26th, 2010. This volcanic eruption was effusive eruption type where magmatic gas pressure in the crater was not too strong and magma eruption was just flown out past the slopes of the Merapi mount area. However, magmatic gas pressure and magma volume still result in deformation changes that have a direct impact on residential areas throughout the Merapi mount area. Residential areas were obtained through supervised classification process from Landsat 7 and 8-satellite imagery in the 2009, 2011 and 2019 acquisition year. The reason of observation year selection was based on pre and post eruption concept to get pattern of Merapi’s mountain body change through deformation analysis. The work focuses on spatial-temporal variability of land use land cover analysis at Mount Merapi pre and post 2010 eruption event considered here. The technique is based on NDVI (Normalized Difference Vegetation Index), Maximum Likelihood Classification (MLC) and False Colour Composite methodology. Based on change in number of pixels it was analysed. Actually, some portion of land was covered with clouds and its shadows. From the results it was observed that, water body, barren and built up features were miss classified. So finally False Colour Composite (FCC) images are used to identify the misclassified classes.

The development of sustainable materials, considering the design aspects is one of the real challenges among the researchers. In general. the renewable resources used in several applications, should not harm ecosystems and maintain the environmental sustainability. In this context, local agricultural by-products or wastes are focused on as an alternative material due to their lightweight and can be easily disposed of after their usage. Agro-waste and biomass materials are plentifully available in the world. The fibers obtained from the agricultural by-products are often used as fillers or reinforcement. Presently, biodegradable polymer matrixes are becoming popular and are finding in number of applications in manufacturing components used in automobiles, medical, domestic, and others. Polylactide (PLA) is a compostable and biodegradable thermoplastic polymer that is derived from renewable agro-sources such as potatoes, corn, or sugarcane. When suitable filler materials are reinforced with these polymers, an improvement in the strength can be seen. In the present work, the rice straw reinforced polylactide (PLA) composites are fabricated with the standard procedure, in accordance with ASTM standards. The experimental studies for the three types of polylactide composites are carried out to characterize their Impact and hardness strength. It is found a higher impact strength for 20 wt% un-treated fiber content of PLA composites. The hardness value is better for treated fiber content PLA composites.

Investigation of three-body abrasive wear behavior of rice husk-filled Polylactic acid (PLA) composites of different weight percentages of 90/10, 80/20, and 70/30 and compared with the pure PLA. The experiments were carried in accordance with the ASTM G65 by using a rubber wheel abrasion tester (RWAT). The experiments were conducted for a load of 9.81, 29.46, and 49.65 N at an abrading distance of 300 m using 106microns abrasive dry Silica sand particles as a third body. The results of the experimental study revealed that the weight loss increases with an increase in applied load and wear resistance increases with an increase in fiber content in PLA composites. The greater wear resistance occurred at 30 wt% of rice husk fiber in the composite. With the help of a Scanning Electron Microscope (SEM), the worn surfaces are analyzed.

This manuscript is discussing the growth of a new class semi-organic nonlinear crystal l-Lysine hydrogen chloride (LLHC) was grown by slow evaporation method using a mixed solvent of deionized water + ethanol and pure deionized water. The crystal crystallizes in orthorhombic space group of P212121. Lattice parameters were revealed by single crystal X-ray diffraction analysis. The FT-IR spectral analysis was performed on the grown crystal LLHC to identify its functional groups. The position of protons and carbons was determined by the NMR technique. The grown crystal was characterized by optical transparency through UV–Vis range with a short cutoff wavelength of 212nm. Thermal and physiochemical stability of the title crystal was found out through the TG-DTA analysis, which proves the crystal stability up to 251.4 °C. Brewster’s point method was used to find out the refractive index of the grown compound LLHC. Vickers’s microhardness test was performed on LLHC to find out its mechanical stability. The second harmonic generation (SHG) of the grown crystal LLHC was confirmed by the Kurtz-perry powder method and the SHG efficiency was compared with the known Potassium Dihydrogen phosphate (KDP) standard. By using a minimal bactericidal concentration (MBC) benchmark, their antibacterial activity was evaluated. The grown crystal shows long-term and outstanding antibacterial activity against E.coli and S.aureus.

In boring operations, tool vibration is a significant parameter which leads to poor surface finish, tool wear and damage of cutting tool. The relative dynamic motion between the cutting tool and work material induces vibration which accelerates tool wear, damage surface finish and produce irritating noise. In order to restrain tool vibration in metal cutting, it is necessary to develop and analyze suitable method which increases stability thereby improving cutting performance. The present investigation aims at developing a smart material controlled boring bar which will respond to an applied field with a dramatic change in rheological behavior. Magnetorheological fluid which was controlled by size of the particle, viscosity of fluid and positioning of rheological fluid is used as smart material in this paper. Magnetorheological fluid was developed and cutting experiments were conducted to arrive at a set of parameters that can reduce tool vibration and promote better cutting performance during boring of hardened AISI 4340 steel. From the results, it was observed that smart material controlled boring bar reduces tool vibration and also improves the cutting performance.

The systematic review aimed to report the prevalence of electronic cigarette (e-cigarette) usage among medical students in Saudi Arabia. Electronic databases were searched for scientific research articles published from January 2010 until December 2020. The data search was performed in electronic search engines such as PubMed, Google Scholar, Scopus, Web of Science, Medline, Embase, Cochrane, and Saudi Digital Library. A total of five research articles that qualified the eligibility criteria were analyzed for qualitative data. The sample size in the included studies ranged from 229 to 1007 participants. The prevalence of e-cigarette usage ranged from 10.6% to 27.7% among medical students in Saudi Arabia. Studies have also reported that the prevalence of e-cigarette usage is higher among the male population in comparison with the female population. The prevalence of e-cigarette usage among medical students in Saudi Arabia is high. Similar to tobacco smoking, e-cigarette usage is a major public health issue and concern among the younger population because they have potential benefits in some and are harmful to some and also it is still unclear whether they are effective for quitting smoking. Regulatory bodies must focus and initiate strict laws and policies to minimize the sales of these products to the younger population. Health promotion strategies need to be developed to reduce the usage of e-cigarettes.

Nowadays, research and development is focused on environmentally benign, sustainable materials to replace and reduce the dependence on existing petroleum-based products. In this framework, the growth of natural and man-made fiber reinforced composite materials is rising at a faster rate in the field of engineering and technology due to its promising characteristics. The current research work is focused on the development of coir fiber reinforced polypropylene composites (PPC) that is having widespread variety of applications and their characteristics are equivalent to present synthetic composites. The work is focused on the study of fracture toughness behavior of these composites and further characterization of mechanical properties. The fabrication of the specimen was carried out using Injection molding technique. Fracture toughness (Compact Tension) tests were done as per ASTM D-5045 standards. The Tensile, Impact, Flexural Strength, and Hardness tests were done to evaluate the mechanical characteristics. It is found that natural coconut coir fiber reinforced composites showed higher fracture toughness values and improved mechanical properties when compared to neat polypropylene.

To separate examples from neuroimaging information, different measurable strategies and AI calculations have been investigated for the analysis of Alzheimer's sickness among more established grown-ups in both clinical and examination applications; in any case, recognizing Alzheimer's and solid cerebrum information has been trying in more seasoned grown-ups (age greater than 70) because of exceptionally comparable examples of mind decay and picture forces. As of late, bleeding edge profound learning innovations have quickly ventured into various fields, including clinical picture investigation. This paper diagrams cutting edge DL-formed pipelines utilized to recognize Alzheimer's Magnetic resonance imaging (MRI) and functional MRI (fMRI) from typical sound control information for a given age gathering. Utilizing these pipelines, which were performed on a GPU-based superior processing stage, the information were carefully and cautiously preprocessed. Then, scale-and move invariant low-to undeniable intensity highlights were acquired from elevated amount of preparing pictures utilizing convolutional neural organization (CNN) engineering. In this examination, fMRI information were utilized without precedent for profound learning applications for the motivations behind clinical picture investigation and Alzheimer's infection forecast.

Purpose In the internal turning process, tool life and work piece quality are greatly influenced by the generation of heat in the cutting zone. During machining, cutting fluids are applied at the cutting zones to reduce heat generation and enhance tribological properties. However, in the boring process, cutting fluids cannot be applied at cutting zone properly, and wastage of cutting fluid is a threat to the ecology and personnel health. Hence, application of semisolid lubricant in the boring process is considered as an innovative technique for temperature reduction in cutting zone because of its eco-friendly system, which also has a higher ability of biodegradability. This paper aims to study the influence of semisolid lubricants comprising of grease,graphite, aluminium oxide in different composition applied at a tool–chip,tool–work interface using a semisolid lubricant applicator applied with varying pressure. Design/methodology/approach In the present study, the cutting performance during boring of AISI4340 steel is enhanced through the application of semisolid lubricant with different composition of grease, graphite and aluminium oxide applied at tool-work and tool-chip interface with varying pressure using semisolid lubricant applicator. Findings The results show that use of semisolid lubricant like grease, graphite and nano aluminium oxide at tool-chip interface with maximum pressure reduces cutting temperature, tool vibration, cutting force and surface roughness. Originality/value Reduce cutting temperature, tool vibration, cutting force and surface roughness.

In this paper, a numerical density function of Impulsive symmetric α-stable (ISAS) noise was presented and simulated in the turbo coding environment. The ISAS noise has no closed-form expression, making it difficult to realize. The ISAS noise can be used to approximate many kinds of noise sources. In this paper, one of the parameters is used to set it as the Cauchy distribution. In addition, an improved interleaver structure is presented where the multiple interleavers of smaller capacity replace a single epic interleaver. Simulation results show that the hybrid interleaver outperforms the other interleavers presented in this paper.

Lead poisoning has been identified as a problem in adults as well as in children. Chronic exposure to lead has been implicated in neurological disorders such as amyotrophic lateral sclerosis, Parkinson's disease, and Alzheimer's disease. In the present study, we evaluated the impact of chronic lead exposure on cerebral glutamatergic and GABAergic metabolic activity in mice. C57BL6 mice were provided lead acetate in drinking water for two months. The regional cerebral metabolic activity was measured using

On transport networks, traffic congestion is a phenomenon that arises as usage increases and is marked by slower speeds, longer travel times and increased queuing of automobiles. In plain terms, “the ability of a vehicle to move forward in a traffic state” defines congestion. Traffic congestion in smart cities has been a major concern. In heterogeneous flow like India, congestion impacts the movement of people both in perception and in reality that leads to consumption of time, energy and also leads to the pollution. In order to save precious human life, eliminate road accidents and the essence factor called time, it is essential to ensure a proper measure for traffic congestion. Earlier there were several attempts made to develop different approaches for congestion analysis. At present the congestion levels of ten different road stretches of Visakhapatnam city within the central business district (CBD) area. The key purpose of this analysis is to introduce a scalable fuzzy logic traffic flow model capable of optimally forecasting traffic to define the city's congestion levels by taking into account parameters such as vehicle volume, average speed and road speed limits by using MATLAB and to generate the desired congestion index of the specified study stretches. This research sets the framework for the forecast, early warning and constructive alleviation of traffic congestion

In boring process, tool vibration is an important parameter which results in progressive tool wear, poor surface finish and cutting tool damage. This tool vibration was reduced by passive, semi-active and active techniques which are used by various researchers in the past. In this paper, various techniques employed to prevent tool vibration in boring operation are reviewed, analyzed and presented. It was inferred that the control of tool vibration was effective by utilizing appropriate damping mechanism in the boring process. Also, from the overall review of the literature, it was observed that as the tool wear started to progress, the tool vibration gets increased which leads to failure of the tool. In this review paper, scope of developing a damper where tool vibration can be suppressed by varying the damping ability based on requirement was established.

During boring process, tool vibration is a major concern due to its overhanging length, which results in high cutting force, poor surface finish, and increase in tool wear. To suppress tool vibration and improve cutting performance, a novel technique in rheological fluid was designed and developed. In this work, a magnetorheological elastomer (MRE) was developed, and parameters, such as piston location, current intensity, and coil winding direction, were considered. Cutting experiments were conducted to obtain a set of parameters that can efficiently control vibration during boring of hardened AISI 4340 steel. Taguchi method was used to optimize the cutting condition, and findings show that the cutting tool embedded with the MRE reduced tool vibration and effectively increased cutting performance.

Tool vibration is a dynamic instability of cutting process, which is a result of interaction between metal-cutting process and dynamics of machined tool. In metal-cutting process, the presence of t...

The beginning of dementia can be generally credited to Alzheimer's illness (AD). The reformist idea of AD grounds the synapse crumbling that significantly prompts actual reliance and mental incapacity which upsets an individual's ordinary life. A Personal Computer helped symptomatic framework is very much predominant in assisting doctors in identifying AD continuously. In this undertaking we proposed a methodology for execution investigation of Alzheimer's stage detection framework and characterization framework dependent on deep features utilizing a pre-prepared Deep Learning Neural Network (DNN). The performance of classifier in the Deep Learning networks is principal and influence the overall performance of the system. The performance of Rectified Linear Activation Function (ReLU), Soft Max and Support Vector Machines (SVM) are evaluated in the proposed system.

In the boring process, tool vibration is an important parameter due to its overhanging length and also leads to high cutting force, poor surface finish and increase in tool wear. To suppress tool vibration and increase the cutting performance, a novel idea has been developed in rheological fluid. In present work, a boring tool holder with magnetorheological damper was analysed. Magnetorheological damper received massive responsive due to their capability to reversely change from a linear, free-flowing viscous fluid to semis solid within seconds when a magnetic field is applied. In this paper, a boring tool holder was analysed using ANSYS software with damping force applied in various direction and without MR effect. The results prove that the use of Magnetorheological damper reduces tool vibration significantly.

We investigate the asymptotic growth of the canonical measures on the fibers of morphisms between vector spaces over local fields of arbitrary characteristic. For non-archimedean local fields we use a version of the Łojasiewicz inequality (\cite{lojasiewicz1959}, \cite{hormander1958division}) which follows from Greenberg \cite{greenberg1966rational}, \cite{bollaerts1990estimate}, together with the theory of the Brauer group of local fields to construct definite forms of arbitrarily high degree, and to transfer questions at infinity to questions near the origin. We then use these to generalize results of H{o}rmander \cite{hormander1958division} on estimating the growth of polynomials at infinity in terms of the distance to their zero loci. Specifically, when a fiber corresponds to a non-critical value which is stable, i.e. remains non-critical under small perturbations, we show that the canonical measure on the fiber is tempered, which generalizes results of Igusa and Raghavan \cite{igusa1978lectures}, and Virtanen and Weisbart \cite{virtanen2014elementary}.

Two women presenting with fragility fractures during lactation had bone mineral density (BMD) reduced more greatly than usually associated with lactation. The first woman was 29 years old with a BMD T-score of - 3.2 SD at the spine and- 2.0 SD at the femoral neck. The second woman was 35 years old with a BMD T-score of - 4.5 SD at the spine and - 2.8 SD at the femoral neck. Both women had increased cortical porosity and reduced trabecular density. Investigation identified an elevated serum tryptase, and marrow biopsy confirmed the diagnosis of mastocytosis. Lactation causes bone loss, but the occurrence of fractures in the setting of severe deficits in BMD and microstructural deterioration signals the need to consider additional causes of bone loss.

In cryptography, data encryption turns ordinary information into an obfuscated code, and the information cannot be viewed without being decrypted. Thus, cryptography remains the main element of data protection. There are two kinds of cryptography, such as symmetric and asymmetric. There are many existing symmetric algorithms that are used to encrypt data, such as the Data Encryption Standard (DES), Triple Data Encryption Algorithm (TDEA), Enigmatic Diagonal Encryption Standard (EDES), Advanced Encryption Standard (AES), BLOWFISH, TWOFISH, Rivest Cipher 4 (RC4), Rivest Cipher 6 (RC6), which have been reviewed in this paper. It compares and tracks a summary of productive encryption calculations. The performance is compared with key size, space, time, security, and features of encryption methods.

In the boring process, the tool is subjected to excessive wear due to an increase in cutting temperature which affects the quality of the finished product. To avoid the rise in cutting temperature multilayer-coated tools were used to improve machining performance. In this present investigation, Aluminum oxide+zirconium oxide, titanium oxide+zirconium oxide and zirconium oxide were used as coating material with various coating techniques such as dip, spin and spray for dry, semisolid and wet condition. A 27 run experimental results were optimized using the Taguchi technique and analysis of variance and found that two-layered TiO2 +ZrO2 deposited in series gives a better performance against the Al2O3 +ZrO2 and ZrO2 with spray technique and wet condition.

The design and analysis of Rectangular microstrip patch antenna is presented with varying patch size and material properties and substrate thickness as parameters at UHF frequencies for the application of an antenna array of UHF Spaced Wind Profiler Radar. The Rectangular microstrip patch antenna has been simulated using High Frequency Structure Simulator (HFSS) software and examined experimentally at 445 MHz. The 50 Ω coaxial probe feed is used for coupling of power to the microstrip patch antenna. As a result of varying airgap substrate thickness, gain, bandwidth, return loss, VSWR, characteristic impedance and of rectangular microstrip patch antenna are improved. Finally, critical needs in the design and development of antenna array of wind profiler Radar are discussed.

This research letter considered land use/land cover (LU/LC) changes in Kadapa region from 2001 to 2016 by using GIS (Geographical Information Systems) LANDSAT 7 and 8 images level-1 data of ETM+ sensor were collected for the years 2001 and 2016 to estimate the NDVI values. Based on index values study area is classified into five classes like water bodies, built-up area, barren land, sparse vegetation and dense vegetation. The proposed method performs two-stage classification. From the results it is observed that, increase in barren land of 6.23%, built-up area of 24.74% and decrease of water resources of 2.87%, sparse vegetation of 2.62% and dense vegetation/forest land of 25.47% in the Kadapa region. Finally, the classification algorithm was assessed by the confusion matrix method. As NDVI is used basis for classification process vegetation and water resources classification is 100% and 86% built up and barren lands are classification, i.e., some of built-up areas classified as barren land and barren land as built-up area. Compared to existing classification algorithms based on Principal Component Analysis (PCA) and False Color Composite (FCC) the proposed NDVI histogram and Maximum Likelihood Classifier (MLC) multiple classification gives the best results to estimate the change detection. The work was carried out by using ArcGIS software.

The Number of observable facts and structures that are accessible with an airglow images which are captured by an All Sky Imager (ASI). All of these images are required to convert from the spherical coordinating system into the rectangular coordinating image system. The spatial calibration is also most important for the perfect measurement of gravity wave characteristics, plasma characteristics and OH emission parameters in the upper atmosphere, mesosphere, ionosphere study when that calibrations are used in real life dimensions. In this paper, we expressed an effective and simple technique for the coordinate mapping and the spatial calibration for accurate dimensions used in real world life and also implemented the same procedure by using Matlab R2013a. The pixel resolutions of OH image of 840 nm, a mesospheric image of 557.7 nm and ionospheric image of 630 nm are measured. These pixel resolutions are nearly same and measuring technique is very simple than other method used in the same area.

Objectives: To design a system with high accuracy, sensitivity and specificity to detect brain tumour. Methods/ Statistical Analysis: Over the years, extensive research works have been done for brain tumour diagnosis using various imaging modalities. Magnetic Resonance Imaging (MRI) method has been proven to be effective in imaging the human brain for detection and classification of the tumours for clinical diagnosis. In this paper, Tetrolet Transform (TT) and Support Vector Machine (SVM) Classifier have been utilized for recognition of tumour from brain MRI images. Findings: The brain MRI image is transformed into a set of features that best describes the information content of the image. So as to use the Tetrolet transform for recognition of tumour, MRI brain tumour image is decomposed by utilizing the Tetrolet transform at a predefined level. Statistical features such as mean, standard deviation, and variance of each tetromino sub bands are computed and extracted. The t-test class separability model is applied to the calculated features keeping in mind the objective to choose the best features from the database images. The receiver operating characteristics (ROC) curves and confusion matrix are make use of, to decide the accuracy level of the proposed method. The experimental results show an accuracy level of 98.8% with fifth level of decomposition and SVM based classification while testing with images from Repository of Molecular Brain Neoplasia Data (REMBRANDT) database. The performance of the proposed system have been evaluated by using the parameters namely- accuracy, sensitivity and specificity. Application/Improvements: This technique is applied to the training images and the selected features are put away in a feature vector. 10-fold cross validation method is utilized to test viability of the proposed technique.

Engineered magnetic nanosystems exhibit attractive options for implementing unique diagnostic options and therapeutic solutions in biomedical applications. Here we report a facile, thermo-free and aqueous synthetic method to prepare ascorbic acid-stabilized iron-platinum nanoparticles. The effects of reducing agent, pH and sequence of precursor addition are investigated, and optimized reaction condition is identified to obtain a unique iron-platinum (Pt-FePt) nanosystems. The multifunctionality of the developed nanosystem has been realized by catalytic efficiency of platinum for therapeutic application and superparamagnetic property of FePt for magnetic resonance imaging contrast enhancement. Moreover, the multifunctional imaging and therapeutic activities have been achieved at physiological pH. The developed multifunctional nanoparticles are monodisperse with uniform morphology as well as stable in solution and non-toxic.

Hard turning with minimal fluid application is a recently developed technique to alleviate the problem associated with cutting fluid. During this process, very small quantity of cutting fluid is applied as a narrow high velocity pulsing jet at the cutting zone. As the quantity of cutting fluid is very small, some auxiliary cooling of tool using heat pipe was attempted in the present work to enhance heat dissipation and thus improving cutting performance. Heat pipe was installed in vertical position in contact with the tool for extracting more heat from the tool. The influence of heat pipe cooling of tool on the cutting performance was analyzed by Taguchi's design of experiments. It was observed that the use of heat pipe in minimal fluid application reduced cutting temperature and tool wear to a maximum of 22% and 15%, respectively, in comparison with conventional hard turning with minimal fluid application without the aid of heat pipe. It appears that heat pipe can be successively employed as a mean of cooling the tool during hard turning with minimal fluid application.