An enhanced method for predicting and analysing forest fires using an attention-based CNN model

Prediction,prevention,and control of forest fires are crucial on at all scales.Developing effective fire detection systems can aid in their control.This study proposes a novel CNN(convolutional neural network)using an attention blocks module which combines an attention module with numerous input layers to enhance the performance of neural networks.The suggested model focuses on predicting the damage affected/burned areas due to possible wildfires and evaluating the multilateral interactions between the pertinent factors.The results show the impacts of CNN using attention blocks for feature extraction and to better understand how ecosystems are affected by meteorological factors.For selected meteorological data,RMSE 12.08 and MAE 7.45 values provide higher predictive power for selecting relevant and necessary features to provide optimal performance with less operational and computational costs.These findings show that the suggested strategy is reliable and effective for planning and managing fire-prone regions as well as for predicting forest fire damage.

Fake News Classification Using a Fuzzy Convolutional Recurrent Neural Network

In recent years,social media platforms have gained immense popularity.As a result,there has been a tremendous increase in content on social media platforms.This content can be related to an individual’s sentiments,thoughts,stories,advertisements,and news,among many other content types.With the recent increase in online content,the importance of identifying fake and real news has increased.Although,there is a lot of work present to detect fake news,a study on Fuzzy CRNN was not explored into this direction.In this work,a system is designed to classify fake and real news using fuzzy logic.The initial feature extraction process is done using a convolutional recurrent neural network(CRNN).After the extraction of features,word indexing is done with high dimensionality.Then,based on the indexing measures,the ranking process identifies whether news is fake or real.The fuzzy CRNN model is trained to yield outstanding resultswith 99.99±0.01%accuracy.This work utilizes three different datasets(LIAR,LIAR-PLUS,and ISOT)to find the most accurate model.

Statistical Change Detection in Water Cycle over Two Decades and Assessment of Impact of Urbanization on Surface and Sub-Surface Water Flows

Urbanization is termed as physical transformation of landscapes that alter the natural regime of the environment of its surrounding resulting in further changes in macro as well as micro climate of the region [1]. Urban areas are continually facing problems of water scarcity and urban flash floods. Recent news from IPCC report 2010, CIESIN’s Global Rural Urban Mapping Project [2] and World Water Vol. 7 2007, it is clear that urban land area has doubled and affected the hydrological cycle. The components of hydrological cycle affected are Infiltration, Runoff and Evaporation and the causing components are derived by studies as land use, land cover, water withdrawal and urban developments. Thus water availability, water recharge and water cycle are all destabilized in course or urban development. The paper is an attempt to correlate and identify the periodical changes in urban water cycle, during urbanization of Bhopal City, India, during last twenty years and above. The observations are based on GIS mapping of the study area from 1991 to 2009 using rational method of runoff and recharge calculations and statistical analysis of related built-up areas. Also change in natural course of drainages with the help of GIS imageries which have been detected during twenty years that help to observe the adaptation of natural system to urban course. Also the observations show an interesting relation which can be used for further research and sustainable development [3].

Quercetin attenuates the development of 7,12-dimethyl benz(a)anthracene(DMBA) and croton oil-induced skin cancer in mice

To evaluate the chemopreventive potential of quercetin in an experimental skin carcinogenesis mouse model.Skin tumor was induced by topical application of 7,12-dimethyl Benz（a） anthracene（DMBA） and Croton oil in Swiss albino mouse.Quercetin was orally administered at a concentration of 200 mg/kg and 400 mg/kg body weight daily for 16 weeks in mouse to evaluate chemopreventive potential.Skin cancer was assessed by histopathological analysis.We found that quercetin reduced the tumor size and the cumulative number of papillomas.The mean latent period was significantly increased as compared to carcinogen treated controls.Quercetin significantly decreased the serum levels of glutamate oxalate transaminase,glutamate pyruvate transaminase,alkaline phosphatase and bilirubin.It significantly increased the levels of glutathione,superoxide dismutase and catalase.The elevated level of lipid peroxides in the control group was significantly inhibited by quercetin.Futhermore,DNA damage was significantly decreased in quercetin treated mice as compared to DMBA and croton oil treated mice.The results suggest that quercetin exerts chemopreventive effect on DMBA and croton oil induced skin cancer in mice by increasing antioxidant activities.

Sentiment Analysis on Social Media Using Genetic Algorithm with CNN

There are various intense forces causing customers to use evaluated data when using social media platforms and microblogging sites.Today,customers throughout the world share their points of view on all kinds of topics through these sources.The massive volume of data created by these customers makes it impossible to analyze such data manually.Therefore,an efficient and intelligent method for evaluating social media data and their divergence needs to be developed.Today,various types of equipment and techniques are available for automatically estimating the classification of sentiments.Sentiment analysis involves determining people’s emotions using facial expressions.Sentiment analysis can be performed for any individual based on specific incidents.The present study describes the analysis of an image dataset using CNNswithPCA intended to detect people’s sentiments(specifically,whether a person is happy or sad).This process is optimized using a genetic algorithm to get better results.Further,a comparative analysis has been conducted between the different models generated by changing the mutation factor,performing batch normalization,and applying feature reduction using PCA.These steps are carried out across five experiments using theKaggledataset.The maximum accuracy obtained is 96.984%,which is associated with the Happy and Sad sentiments.

Review of Linear Switched Reluctance Motor Designs for Linear Propulsion Applications

Linear switched reluctance motor(LSRM)and its applications in different industries have been an interesting research topic for the past few years.LSRMs have proved to be a suitable alternative in a variety of applications requiring linear motion.However,its use is not that popular which instigated an active interest in the evolution of newer LSRM configurations.Enhancement in its propulsion force along with the reduction in force ripples,weight,acoustic noise,and vibration have been the main objectives in recently proposed LSRM designs.In this paper,recently proposed LSRM designs are reviewed and analyzed.The paper presents a one-stop introduction and a complete update to the designs,both in terms of qualitative and quantitative parameters.In addition,it takes into account the challenges in the implementation of these designs.Based on a detailed comparison of these designs as presented in this paper,an appropriate design can be chosen for a given application.

Geological Behaviours in Urban Areas for Surface Runoff and Recharge

Urbanization is rapidly growing all over the world affecting life styles and environment to a large scale. The most challenging impacts that can be observed are the reducing water levels and increasing surface flows in form of flash floods. Urban sprawl has converted hectares of agriculture and forest land into developed surfaces which have zero infiltration resulting in increased flow of precipitation. Apart from sealed land surfaces, the ignorance of soil behavior also leads to added surface flows and unnatural infiltration into soil. Incompatibility of urban planning and functions with the natural environment is becoming vast. Changes in land patterns due to Build up, pavements, roads and similar land cover affect surface water flow seriously. Wise use of modern means and best technologies available are not in use resulting in a huge gap between basic knowledge of natural processes and its requirement for balanced development having minimum impact on water recharge. Present paper is a research on various soil groups and urban water sheds for impacts of increasing Build up on runoff and behavior of soil under developed conditions. The method adopted was to analyze Build up from 1971 to 2014 using ArcGis 9.3 and hydrological modeling using SWMM software for resulting runoff in 40 years of urbanization. Results were compared for different soil groups to observe best conditions for suitable Build up on soil groups for sustainable development.

A Novel High-Performance Lekage-Tolerant, Wide Fan-In Domino Logic Circuit in Deep-Submicron Technology

As technology shrinks in modern era the demand on high speed, low power consumption and small chip area in microprocessors is come into existence. In this paper we have presented a new class of domino circuit design for low power consumption, faster circuit speed and high performance. Due to wide fan-in domino logic, its logic gate suffer from noise sensitivity, if we improve sensitivity, sub-threshold and gate oxide leakage current dominate in evaluation network, which increases the power consumption and reduces the performance of the circuit. The proposed circuit improves the dynamic power consumption and reduces the delay which improves the speed of the circuit. Simulation is performed in BISM4 Cadence environment at 65 nm process technology, with supply voltage 1 V at 100 MHz frequency and bottleneck operating temperature of 27°C with CL = 1 fF. From the result average power improvement by proposed circuit 1 & 2 for 8 input OR gate is 10.1%, 15.28% SFLD, 48.56%, 51.49% CKD, 55.17%, 57.71% HSD and improvement of delay is 1.10%, 12.76% SFLD, 19.13%, 28.63% CKD, 4.32%, 15.59% HSD, 19.138%, 44.25% DFD respectively.

Design of a Concentration Sensor Based on Photonic Crystal Fiber Placed between Two Single Mode Fibers

We demonstrate the use of photonic crystal fiber (PCF) joined in between two single mode fibers (SMF) as a concentration sensor. To realize this, one micrometer length PCF of hexagonal lattice is sandwiched between two SMF having one micrometer length each. To maximize the coupling between SMF and PCF, the core diameters are made equal. Then the output from a given input through this structure is analyzed with respect to different concentrations in the air holes of PCF using Finite Difference Time Domain (FDTD) method. It is found that the variation of electric field intensity at the output is linear with respect to concentration of alcohol.

Effect of Anisotropy,Temperature,Strain Rate on Deep Drawing Using Conical Die

This paper covers the role of anisotropy,temperature,and strain rate on the flow behavior of the material when a conical die is used instead of conventional blank holder.The effect of anisotropy was investigated using Lankford’s coefficient(r)in three directions(0°,45°,and 90°).The effect of working temperatures(Room temperature,100°C-300°C)on drawing stress and strain rate sensitivity on punch pressure were also investigated in detail.ANSYS APDL was used to investigate the effects of temperature,strain rate and anisotropy.The simulation results have confirmed that the strain variation in the direction of r0 and r45 are more than the variation of r90.

Power Quality Improvement and Signal Conditioning of PV Array and Grid Interfaced Off-board Charger for Electric Vehicles with V2G and G2V Capabilities

In this work,we present a photovoltaic(PV)-based off-board charging system integrated with the grid using a voltage source converter(VSC).The control of the grid-tied off-board charger is derived from the joint logarithmic hyperbolic cosine robust sparse adaptive filter(JLHCAF)algorithm.This algorithm effectively tracks the fundamental component of the load current in a short duration,providing a good dynamic response.Due to its robustness against impulsive interference,the JLHCAF outperforms other sparsity-aware robust algorithms The cascaded proportional-integral(PI)controller is used to control the bidirectional buck-boost converter for electric vehicle(EV)charging/discharging,which acts in buck operation if the EV is being charged and in boost operation if it is discharged.The reference DC link voltage for the controller is derived by using adaptive MPPT technique.The bidirectional properties of the system enable various functions,including grid-to-vehicle(G2V),vehicle-to-grid(V2G),PV source-to-grid(PV2G),vehicle-to-home(V2H),and PV source-to-vehicle(PV2V)operations.Additionally,the system can supply power to critical nonlinear loads.The control strategy ensures compliance with the power quality requirements set by the IEEE standard,as demonstrated in the results.To validate the effectiveness of the proposed system,we conducted tests under dynamic conditions by disconnecting and reconnecting household loads.Furthermore,the off-board charging system was subjected to actual conditions,such as variations in solar PV insolation,and its steady-state performance was evaluated through simulation and laboratory experimental prototypes.The results,including total harmonic distortion(THD),support the validation of the developed charging system.

Detection of oxidative stress and DNA damage in freshwater snail Lymnea leuteola exposed to profenofos

Extensive production and use of organophosphate pesticide in agriculture,has risen concerned about its ecotoxicity and risk assessment of insecticides,which are more important.Therefore,the present investigation was aimed to study the induction of oxidative stress and DNA damage by organophosphate insecticide profenofos(PFF)in freshwater snail Lymnea luteola(L.luteola).The median lethal value(96 h LC50)of PFF was estimated as 1.26 mg/L for L.luteola in a semi-static system and on the basis of LC50 value three concentrations viz.,0.126(1/10 of LC50,Sublethal I),0.63(1/2 of LC50,Sublethal II)and 0.84 mg/L(2/3 of LC50,Sublethal III)were determined.Snails were exposed to above-mentioned concentrations of PFF along with solvent control(acetone)and negative control for 96 h.The haemolymph was collected at 24 and 96 h of after treatment.In heamolymph of PFF exposed snail,lipid peroxide,glutathione reduced glutathione S transferase and superoxide dismutase activities at the tested concentrations significantly differ from those in the control.The genotoxicity induced in hemocytes of treated snails was measured by alkaline single cell gel electrophoresis assay.The data of this experiment demonstrated significantly enhancement of oxidative stress and DNA damage in the treated snails as compared to controls.Also,we observed statistically significant correlations of ROS with DNA damage(%tail DNA)(R^(2)=0.9708)for 24 h and DNA damage(R^(2)=0.9665)for 96 h.Results of the current experiment can be useful in risk evaluation of PFF among aquatic organisms.The study confirmed the use of comet assay for in vivo laboratory experiments using freshwater snail for selecting the toxic potential of industrial chemicals and environmental contaminants.

A comprehensive review of the influence of physicochemical properties of biodiesel on combustion characteristics,engine performance and emissions

Energy is a basic requirement for development in the world.The continuously rising demand for energy resources and the fast depletion of fossil fuel is raises researcher's concern to focus on alternative sources of energy that can replace the shortage of fossil fuels soon.Biodiesel is recognized as one of the potential alternative renewable energy fuels that can be easily available in a wide range in every part of the world.This paper reviews biodiesel's prospect and focuses on the different fuel properties(physicochemical)of 100 biodiesels from first-,second-and third-generation followed by the evaluation of CI engine characteristics.It has been observed that the fuel properties of first-,second-and third-generation biodiesel are compatible with the ASTM standards.The present paper discussed the potential of various generations of biodiesel feedstocks from production perspectives.This paper also examined many aspects of these feedstocks which include different biodiesel feedstock sources,biodiesel conversion technology,and second-generation biodiesel performance and emission characteristics.Most of the studies showed that biodiesel derived from plant feedstock is costly than diesel.Thus,more influence is to be given to non-edible sources.However,the engine characteristics are shown promising behavior with biodiesel and a slight increase in NOX is also reported on using various biodiesel.

FELERION: a new approach for leakage power reduction

The circuit proposed in this paper simultaneously reduces the sub threshold leakage power and saves the state of art aspect of the logic circuits. Sleep transistors and PMOS-only logic are used to further reduce the leakage power. Sleep transistors are used as the keepers to reduce the sub threshold leakage current providing the low resistance path to the output. PMOS-only logic is used between the pull up and pull down devices to mitigate the leakage power further. Our proposed fast efficient leakage reduction circuit not only reduces the leakage current but also reduces the power dissipation. Power and delay are analyzed at the 32 nm BSIM4 model for a chain of four inverters, NAND, NOR and ISCAS-85 c17 benchmark circuits using DSCH3 and the Microwind tool. The simulation results reveal that our proposed approach mitigates leakage power by 90%–94% as compared to the conventional approach.