Smart Healthcare Activity Recognition Using Statistical Regression and Intelligent Learning

In this present time,Human Activity Recognition(HAR)has been of considerable aid in the case of health monitoring and recovery.The exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and significance.Although many research works conducted on Smart Healthcare Monitoring,there remain a certain number of pitfalls such as time,overhead,and falsification involved during analysis.Therefore,this paper proposes a Statistical Partial Regression and Support Vector Intelligent Agent Learning(SPR-SVIAL)for Smart Healthcare Monitoring.At first,the Statistical Partial Regression Feature Extraction model is used for data preprocessing along with the dimensionality-reduced features extraction process.Here,the input dataset the continuous beat-to-beat heart data,triaxial accelerometer data,and psychological characteristics were acquired from IoT wearable devices.To attain highly accurate Smart Healthcare Monitoring with less time,Partial Least Square helps extract the dimensionality-reduced features.After that,with these resulting features,SVIAL is proposed for Smart Healthcare Monitoring with the help of Machine Learning and Intelligent Agents to minimize both analysis falsification and overhead.Experimental evaluation is carried out for factors such as time,overhead,and false positive rate accuracy concerning several instances.The quantitatively analyzed results indicate the better performance of our proposed SPR-SVIAL method when compared with two state-of-the-art methods.

Analysis on the Development of College Art Education Status

Art Teacher Education or the local college art education major have a particular responsibility in promoting in the development of quality education of basic education and cultivating all-round development of high-quality innovative talents. For art education is recognized as one of the most effective trainings for creativity, art education plays a special and irreplaceable role for the cultivation of innovative thinking. Fine Art Education has become an important part of Chinese modem art education and made a tremendous contribution. Education is the hope for the nation＇s revitalization, teachers is the hope for education revitalization. Building a good political quality, reasonable structure, stable team of teachers is a fundamental plan for reform and development.

Conducting Polymers Meet Lithium-Sulfur Batteries:Progress,Challenges,and Perspectives

Lithium-sulfur(Li-S)batteries have attracted increased interest because of the high theoretical energy density,low cost,and environmental friendliness.Conducting polymers(CPs),as one of the most promising materials used in Li-S batteries,can not only facilitate electron transfer and buffer the large volumetric change of sulfur benefiting from their porous structure and excellent flexibility,but also enable stronger physical/chemical adsorption capacity toward polysulfides(LiPSs)when doped with abundant heteroatoms to promote the sulfur redox kinetics and achieve the high sulfur loading.This review firstly introduces the properties of various CPs including structural CPs(polypyrrole(PPy),polyaniline(PANi),polyethylene dioxothiophene[PEDOT])and compound CPs(polyethylene oxide(PEO),polyvinyl alcohol(PVA)and poly(acrylic acid)[PAA]),and their application potential in Li-S batteries.Furthermore,the research progress of various CPs in different components(cathode,separator,and interlayer)of Li-S batteries is systematically summarized.Finally,the application perspective of the CPs in Li-S batteries as a potential guidance is comprehensively discussed.

Generative Adversarial Networks for Secure Data Transmission in Wireless Network

In this paper,a communication model in cognitive radios is developed and uses machine learning to learn the dynamics of jamming attacks in cognitive radios.It is designed further to make their transmission decision that automati-cally adapts to the transmission dynamics to mitigate the launched jamming attacks.The generative adversarial learning neural network(GALNN)or genera-tive dynamic neural network(GDNN)automatically learns with the synthesized training data(training)with a generator and discriminator type neural networks that encompass minimax game theory.The elimination of the jamming attack is carried out with the assistance of the defense strategies and with an increased detection rate in the generative adversarial network(GAN).The GDNN with game theory is designed to validate the channel condition with the cross entropy loss function and back-propagation algorithm,which improves the communica-tion reliability in the network.The simulation is conducted in NS2.34 tool against several performance metrics to reduce the misdetection rate and false alarm rates.The results show that the GDNN obtains an increased rate of successful transmis-sion by taking optimal actions to act as a defense mechanism to mislead the jam-mer,where the jammer makes high misclassification errors on transmission dynamics.

Adaptive Momentum-Backpropagation Algorithm for Flood Prediction and Management in the Internet of Things

Flooding is a hazardous natural calamity that causes significant damage to lives and infrastructure in the real world.Therefore,timely and accurate decision-making is essential for mitigating flood-related damages.The traditional flood prediction techniques often encounter challenges in accuracy,timeliness,complexity in handling dynamic flood patterns and leading to substandard flood management strategies.To address these challenges,there is a need for advanced machine learning models that can effectively analyze Internet of Things(IoT)-generated flood data and provide timely and accurate flood predictions.This paper proposes a novel approach-the Adaptive Momentum and Backpropagation(AM-BP)algorithm-for flood prediction and management in IoT networks.The AM-BP model combines the advantages of an adaptive momentum technique with the backpropagation algorithm to enhance flood prediction accuracy and efficiency.Real-world flood data is used for validation,demonstrating the superior performance of the AM-BP algorithm compared to traditional methods.In addition,multilayer high-end computing architecture(MLCA)is used to handle weather data such as rainfall,river water level,soil moisture,etc.The AM-BP’s real-time abilities enable proactive flood management,facilitating timely responses and effective disaster mitigation.Furthermore,the AM-BP algorithm can analyze large and complex datasets,integrating environmental and climatic factors for more accurate flood prediction.The evaluation result shows that the AM-BP algorithm outperforms traditional approaches with an accuracy rate of 96%,96.4%F1-Measure,97%Precision,and 95.9%Recall.The proposed AM-BP model presents a promising solution for flood prediction and management in IoT networks,contributing to more resilient and efficient flood control strategies,and ensuring the safety and well-being of communities at risk of flooding.

Arithmetic Optimization with Ensemble Deep Transfer Learning Based Melanoma Classification

Melanoma is a skin disease with high mortality rate while earlydiagnoses of the disease can increase the survival chances of patients. Itis challenging to automatically diagnose melanoma from dermoscopic skinsamples. Computer-Aided Diagnostic (CAD) tool saves time and effort indiagnosing melanoma compared to existing medical approaches. In this background,there is a need exists to design an automated classification modelfor melanoma that can utilize deep and rich feature datasets of an imagefor disease classification. The current study develops an Intelligent ArithmeticOptimization with Ensemble Deep Transfer Learning Based MelanomaClassification (IAOEDTT-MC) model. The proposed IAOEDTT-MC modelfocuses on identification and classification of melanoma from dermoscopicimages. To accomplish this, IAOEDTT-MC model applies image preprocessingat the initial stage in which Gabor Filtering (GF) technique is utilized.In addition, U-Net segmentation approach is employed to segment the lesionregions in dermoscopic images. Besides, an ensemble of DL models includingResNet50 and ElasticNet models is applied in this study. Moreover, AOalgorithm with Gated Recurrent Unit (GRU) method is utilized for identificationand classification of melanoma. The proposed IAOEDTT-MC methodwas experimentally validated with the help of benchmark datasets and theproposed model attained maximum accuracy of 92.09% on ISIC 2017 dataset.

Enhancing Police Officers’ Cybercrime Investigation Skills Using a Checklist Tool

This paper addressed the current state of police officers’ capabilities, skills, and their readiness to deal with the developments of cybercrime. This study discussed definition of cybercrime, cybercrime categories as well as comparison between traditional criminal techniques and cybercrime. As the abilities and skills required for detectives to investigate cybercrime have been discussed. Additionally, literature review and related work, was addressed challenges role of the police in combating cybercrime and facing cybercrime policing. We proposed the main tool in the study which is “Checklist of essential skills for a cybercrime investigator”. Thus, to gain the ability to Identify technical and practical requirements in terms of skills, programs, and equipment to achieve effective and professional results in fight cybercrimes.

New Results on One Modulo N-Difference Mean Graphs

A graph G is said to be one modulo N-difference mean graph if there is an injective function f from the vertex set of G to the set , where N is the natural number and q is the number of edges of G and f induces a bijection from the edge set of G to given by and the function f is called a one modulo N-difference mean labeling of G. In this paper, we show that the graphs such as arbitrary union of paths, , ladder, slanting ladder, diamond snake, quadrilateral snake, alternately quadrilateral snake, , , , , friendship graph and admit one modulo N-difference mean labeling.

Emotion Deduction from Social Media Text Data Using Machine Learning Algorithm

Emotion represents the feeling of an individual in a given situation. There are various ways to express the emotions of an individual. It can be categorized into verbal expressions, written expressions, facial expressions and gestures. Among these various ways of expressing the emotion, the written method is a challenging task to extract the emotions, as the data is in the form of textual dat. Finding the different kinds of emotions is also a tedious task as it requires a lot of pre preparations of the textual data taken for the research. This research work is carried out to analyse and extract the emotions hidden in text data. The text data taken for the analysis is from the social media dataset. Using the raw text data directly from the social media will not serve the purpose. Therefore, the text data has to be pre-processed and then utilised for further processing. Pre-processing makes the text data more efficient and would infer valuable insights of the emotions hidden in it. The preprocessing steps also help to manage the text data for identifying the emotions conveyed in the text. This work proposes to deduct the emotions taken from the social media text data by applying the machine learning algorithm. Finally, the usefulness of the emotions is suggested for various stake holders, to find the attitude of individuals at that moment, the data is produced. .

Effect on Optical and Antibacterial Activity of SnO2 and CuO Blended SnO2 Nanoparticles

Nanocrystalline SnO2 and CuO doped with SnO2 were prepared by the co-precipitation method and characterized for different physiochemical properties and microbiological activity. The composition and morphological formation were characterized by XRD, HRTEM, Raman, FTIR, and UV-vis spectroscopy. The Powder X-ray analysis reveals that Sn4+ ions have substituted the Cu2+ ions without changing the monoclinic structure of SnO2 but the average particle size of the SnO2 and CuO doped SnO2 samples from 11 and 5 nm respectively. However, it exhibits an inhibiting strong bacterial growth against tested bacterial strains.

Effect of Temperature on Photovoltaic Solar Cell Cadmium Telluride Thin Film

Solar cell technology comes with unique temperature coefficients. These temperature coefficients are important and temperature of the solar cell has direct influence on the power output of a photovoltaic cells. CdTe is a very robust and chemically stable material and for this reason its related solar cell. Thin film photovoltaic technology is now the only thin film technology in the first top 10 producers in the world. The strong improvement in efficiency in the last 7 years was obtained by a new redesign of the CdTe solar cell device reaching a single solar cell. In this paper, we describe the fabrication process following the history of the solar cell as it was developed in the early years up to the latest development and changes. The configuration of fabricated cell is n-CdTe/NaOH (0.15 M) + S (0.15 M) + Na2S (0.15 M)/C(graphite). The junction ideality factor was found to be 2.63, 2.13, and 1.89. The flat band potential is found to be -0.400, -0.450, -0.501 V. The barrier height value was found to be 0.523, 0.487, and 0.436 eV. The study of power output characteristic shows open circuit voltage, short circuit current, fill factor and efficiency were found to be 120 mV, 24.2 μA, 32.68%, 26.18%, and 19.73% and 0.63%, 0.37%, and 0.23%, respectively. The lighted ideality factor was calculated and found to be 3.26, 1.87, and 1.17. Spectra attain maximum value of current at λ = 580 nm and decrease with increase in wavelength. The photovoltaic cell characterization of the thin films is carried out by studying current-voltage characteristics in dark, capacitance-voltage in dark, barrier height measurements, power output characteristics.

柜类家具防震设计中滑移运动数值模拟研究

柜类家具在地震中产生的震害形式多样,易造成人员伤亡和财产损失。笔者通过研究自由式柜子水平滑移模型,推导出柜子滑移的运动方程并求解;利用MATLAB对算例计算,进行自由式柜子地震滑移反应参数影响研究。结果表明:柜子滑移反应随着水平地震力输入的增大而增大,滑移距离随着柜体与支撑面之间摩擦系数的增大而减小,竖向地震力对滑移距离的影响不容忽视。

Chromatographic finger print analysis of steroids in Aerva lanata L by HPTLC technique

Objective:To determine the chemical profile and steroids composition of the medicinally important plant Aerva lanata(A.lanata) L.Methods:Preliminary phytochemicul screening was done by the method as Harborne described.HPTLC studies were canied out as Harborne and Wagner et al described.The Ethyl acetate-ethanol-water(8:2:1.2) was employed as mobile phase for glycosides.Results:The desired aim was achieved using Chloroform-acetone(8:2) as the mobile phase.The methanolic extract of stem,leaves,root,flower and seeds of A.lanata showed the presence of 30 different types of steroids with 30 different Rf values from 0.04 to 0.97. Maximum number(11) of steroids has been observed in leaves followed by root(10).Conclusions: HPTLC profile of steroids has been chosen here to reveal the diversity existing in A.lanata.Such finger printing is useful in differentiating the species from the adulterant and act as biochemical markers for this medicinally important plant in the pharma industry and plant systematic studies.

Biological activities of Solanum pseudocapsicum(Solanaceae)against cotton bollworm,Helicoverpa armigera Hübner and armyworm,Spodoptera litura Fabricius(Lepidotera:Noctuidae)

Objective:To evaluate the antifeedant,insecticidal and growth inhibition activities of Solanum pseudocapsicum(S.pseudocapsicum)seed extracts against Spodoptera litura(S.litura)and Helicotverpa armigera(H.armigera).Methods:Hcxane,diethyl cther,dichloromethanc and ethyl acetate seed extracts were prepared and tested for autifeedant,insecticidal and growth inhibitory activities against fourth instar larvae of&litura and H.armigera.Results:Ethyl acetate extract showed promising antifeedant and insecticidal activities against S.litura and H.armigera.Percentage of deformed larvae,pupae and adults were maximum in treatment of ethyl acetate extract.Percentage of successful adult emergence was deteriorated by seeds on extract treated larvae.Conclusions:Ethyl acetate extracts of S.pseudocapsicum,showed higher efficiency of antifeedant,insecticidal and growth inhibition activities.Hence,it can be used to controll agricultural insect pests,S.litura and H.armigera.

Tight Focusing Properties of Radially Polarized Gaussian Beams with Pair of Vortices

The tight focusing properties of a radially polarized Gaussian beam with a nested pair of vortices having a radial wave front distribution are investigated theoretically by the vector diffraction theory. The results show that the optical intensity in the focal region can be altered considerably by changing the location of the vortices nested in a radially polarized Gaussian beam. It is noted that focal evolution from one annular focal pattern to a highly confined focal spot in the transverse direction is observed corresponding to the change in the location of the optical vortices in the input plane. It is also observed that the generated focal hole or spot lead to a focal shift along the optical axis remarkably under proper radial phase modulation. Hence the proposed system may be applied to construct tunable optical traps for both high and low refractive index particles.

Antibacterial activity of leaves and inter-nodal callus extracts of Mentha arvensis L

Objective:To determine the anti-bacterial efficacy of chloroform,ethanol,ethyl acetate and water extracts of inter-nodal and leaves derived calli extracts from Mentha arvensis(M.arvensis) against Salmonella typhi(S.typhi),Streptococcus pyogenes(S.pyogenes),Proteus vulgaris(P. vulgaris) and Bacillus subtilis(B.subtilis).Methods:The inter-nodal and leaves segments of M.arvensis were cut into 0.5-0.7 cm in length and cultured on Murashige and Skoog solid medium supplemented with 3%sucrose,gelled with 0.7%agar and different concentration of 2,4-Dichlorophenoxyacetie acid(2,4-D) either alone or in combinations.The preliminary phytochemical screening was performed by Brindha et al method.Antibacterial efficacy was performed by disc diffusion method and incubated for 24 h at 37℃.Results:Maximum percentage of callus formation(inter-nodal segments 84.3±0.78;leaves segments 93.8±1.27) was obtained on Murashige and Skoog’s basal medium supplemented with 3%sucrose and 1.5 mg/L of 2,4-D.The ethanol extracts of leaves derived calli showed the maximum bio-efficacy than other solvents.The leaves and stem derived calli extracts on Proteus sp.showed that the plants can be used in the treatment of urinary tract infection associated with Proteus sp.Through the bacterial efficacy studies,it is confirmed that the in vitro raised calli tissue was more effective compared to in vivo tissue.Conclusions:The bio-efficacy study confirmed that the calli mediated tissues showed the maximum zone of inhibition.The present study paved a protocol to establish high potential cell lines by in vitro culture.

In vivo and in vitro phytochemical and antibacterial efficacy of Baliospermum montanum (Willd.) Muell.Arg.

Objective:To evaluate the phytochemical and anti-bacterial potential of mother plants in vivo and in vitro derived callus of Baliospermum montanum(B.montanum)(Willd.) Muell.-Arg. leaves and root.Methods:The in vitro derived rootlets and leaves segments of B.montanum were cut into 0.5-0.7 cm in length and cultured on Murashige and Skoog solid medium supplemented with 3%sucrose,gelled with 0.7%agar and different concentration of 2,4-D either alone or in combinations.The preliminary phytochemical screening was performed by Harborne method.Antibacterial efficacy was performed by well diffusion method and incubated for 24 h at 37℃.Results:The highest percentage of callus formation(leaves segments 86.9±0.56:root segments 78.7±0.51) was obtained on Murashige and Skoog’s basal medium supplemented with 3%sucrose and 2.0 mg/L of 2.4-Dichlorophenoxy acetic acid.The phytochemical study revealed the high quantity presence of steroids,triterpenoids,glycosides,saponins,alkaloids,flavanoids, phenolic compounds,tannins,sugars etc of root and leaves derived calli.The ethanol extract of leaves segment derived calli of B.montanum showed the maximum solubility and antimicrobial activity with the MIC ranged from 100 to 200μL.Conclusions:The preliminary phytochemical study confirmed that the calli mediated tissues showed the higher percentage of metabolite constituents and extraction value compared to the in vivo leaves and roots.The present study observation suggested that a possibility to establish high yielding genotypes by in vitro culture for production of medicinally important bioactive compounds.

Mosquitocidal properties of Solanum trilobatum L.(Solanaceae) leaf extracts against,three important human vector mosquitoes(Diptera:Culicidae)

Objective:To determine the larvicidal and pupicidal activites of Solanum trilobatum(S. trilobatum) leaf extracts against Aedes aegypti(Ae.aegypti),Culex quinquefasciatus(Cx. quinquefasciatus) and Anopheles stephensi(An.stephensi).Methods:The larvicidal and pupucidal was determined at five different concentrations of 50,100,150,200 and 250 ppm.Percentage of larval mortality was assessed after 48 h.Results:Methanol extracts of S.trilobatum was found to be more susceptible against the larvae of Ae.aegypti.Cx.quinquefasciatus and An.stephensi at 250 ppm with a LC_(50) value of 125.43,127.77 and 116.64 ppm respectively.Leaf methanol extracts of S.trilobatum also exhibited pupicidal and adult emergence properties.Conclusions:These results suggested that the leaf extracts of S.Irilobalum showed potential to be used as an ideal ecofriendly approach for the control of the Ae.Aegypti,Cx.quinquefasciatus and An.stephensi.

The effect of leaves extracts of Clitoria ternatea Linn against the fish pathogens

Objective:To investigate the antimicrobial activity of Clitoria ternatea(C.ternatea) against the fish pathogens viz.,Pseudomonas aeruginosa(P.aeruginosa),Escherichia coli(E.coli),Klebsiella pneumonia(K.pneumonia),Bacillus subtilis(B.subtilis),Aeromonas formican(A.formicans)s, Aeromonas hydrophila(A.hydrophila) and Streptococcus agalactiae(S.agalactiae )isolated from diseased Tilapia(Oreochromis niloticus).Methods:The extracts of C.ternatea was tested against P.aeruginosa,E.coli,K.pneumonia,B.subtilis,A.formicans,A.hydrophila and S.agalactiae by the agar well diffusion method.Results:Different extracts of C.ternatea showed inhibitory effects against P.aeruginosa,E.coli,K.pneumonia,B.subtilis,A.formicans,A.hydrophila and S. agalactiae.Ethyl acetate extracts of C.ternatea showed maximum of zone of inhibition against A. formicans(18 mm),A.hydrophilia(19 mm),B.subtilis(19 mm) and P.aeruginosa(21 mm) next to that ethanol extract of C.ternatea showed A.formicans(18 mm) and E.coli(14 mm) followed by Acetone extract showed maximum zone of inhibition S.agalactiae(19 mm) and K.pneumonia(17 mm).Conclusions:The antimicrobial activities of all the four plant extracts are comparable and their potential as alternative in the treatment of infectious by these microorganisms was present in the fish.Susceptibility testing is conducted on isolates using drugs selected on the basis of their importance to human medicine and use in fish production.

Antifungal activity of Ocimum sanctum Linn.(Lamiaceae) on clinically isolated dermatophytic fungi

Objective:To assess antifungal activity of Ocimum sanctum leaves against dermatophytic fungi. Methods:Antifungal activity of Ocimum sanctum leaves was measured by 38 A NCCLS method. Minimum inhibitory concentration(MIC) and minimum fungicidal concentration(MFC) of various extracts and fractions of Ocimum sanctum leaves were also determined.Results:Ocimum sanctum leaves possessed antifungal activity against clinically isolated dermatophytes at the concentration of 200μg/mL.MIC and MFC were high with water fraction(200μg/mL) against dermatophytic fungi used.Conclusions:Ocimum sanctum has antifungal activity,and the leaf extracts may be a useful source for dermatophytic infections.