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Diagnosis and Detection of Alzheimer’s Disease Using Learning Algorithm

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Big Data Mining and Analytics 2023年第4期6卷 504-512页

作者： Gargi Pant Shukla Santosh Kumar Saroj Kumar Pandey Rohit Agarwal neeraj varshney Ankit Kumar the Department of Management Doon Business SchoolDehradun 248001India. Jaipuria Institute of Management Jaipur 302033India Department of Computer Engineering and Apllications GLA UniversityMathura 281406India.

In Computer-Aided Detection(CAD)brain disease classification is a vital ***’s Disease(AD)and brain tumors are the primary reasons of *** studies of these diseases are carried out by Magnetic Resonance Imaging(MRI),Positron Emission Tomography(PET),and Computed Tomography(CT)scans which require expertise to understand the *** disease is the most prevalent in the elderly and can be fatal in its later *** result can be determined by calculating the mini-mental state exam score,following which the MRI scan of the brain is *** from that,various classification algorithms,such as machine learning and deep learning,are useful for diagnosing MRI ***,they do have some limitations in terms of *** paper proposes some insightful pre-processing methods that significantly improve the classification performance of these MRI ***,it reduced the time it took to train the model of various pre-existing learning algorithms.A dataset was obtained from Alzheimer’s Disease Neurological Initiative(ADNI)and converted from a 4D format to a 2D *** clipping,grayscale image conversion,and histogram equalization techniques were used to pre-process the *** pre-processing,we proposed three learning algorithms for AD classification,that is random forest,XGBoost,and Convolution Neural Networks(CNN).Results are computed on dataset and show that it outperformed with exiting work in terms of accuracy is 97.57%and sensitivity is 97.60%.

关键词： alzheimer’s disease deep learning random forest XGBoost

A PLS-SEM Based Approach: Analyzing Generation Z Purchase Intention Through Facebook’s Big Data

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Big Data Mining and Analytics 2023年第4期6卷 491-503页

作者： Vikas Kumar Preeti Shaiku Shahida Saheb Sunil Kumari Kanishka Pathak Jai Kishan Chandel neeraj varshney Ankit Kumar Humanities and Management Department Dr.B.R.Ambedkar National Institute of Technology JalandharJalandhar 144027India Department of Commerce and Business Administration Kanya Maha Vidyalaya(KMV)Jalandhar 144004India Mittal School of Business Lovely Professional UniversityPhagwara 144402India Government College for Women Indra Gandhi UniversityAteli 123021India Institute of Management Studies Kurukshetra UniversityKurukshetra 136119India Kumar are with the Department of Computer Engineering and Applications GLA UniversityMathura 281406India

The objective of this paper is to provide a better rendition of Generation Z purchase intentions of retail products through *** study gyrated around the favorable attitude formation of Generation Z translating into intentions to purchase retail products through *** role of antecedents of attitude,namely enjoyment,credibility,and peer communication was also *** main purpose was to analyze the F-commerce pervasiveness(retail purchases through Facebook)among Generation Z in India and how could it be materialized effectively.A conceptual fac¸ade was proposed after trotting out germane and urbane *** study focused exclusively on Generation Z *** data were statistically analyzed using partial least squares structural equation *** study found the proposed conceptual model had a high prediction power of Generation Z intentions to purchase retail products through Facebook verifying the materialization of ***,credibility,and peer communication were proved to be good predictors of attitude(R^(2)=0.589)and furthermore attitude was found to be a stellar antecedent to purchase intentions(R^(2)=0.540).

关键词： Facebook enjoyment credibility peer communication attitude intentions to purchase

Detection of Behavioral Patterns Employing a Hybrid Approach of Computational Techniques

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Computers, Materials & Continua 2022年第7期72卷 2015-2031页

作者： Rohit Raja Chetan Swarup Abhishek Kumar Kamred Udham Singh Teekam Singh Dinesh Gupta neeraj varshney Swati Jain Department of Information Technology Guru Ghasidas VishwavidyalayaBilaspur495009India Department of Basic Science College of Science&Theoretical StudiesSaudi Electronic University13316Saudi Arabia Department of Computer Science&IT JAIN(Deemed to be University)Bangalore560069India Computer Science and Information Science Cheng Kung University621301Taiwan School of Computer Science University of Petroleum and Energy StudiesDehradun248007India Department of CSE I K Gujral Punjab Technical UniversityJalandhar144603India Department of Computer Engineering and Applications GLA UniversityMathura281406India Department of Computer Science Government J Yoganandam Chhattisgarh CollegeRaipur492001India

As far as the present state is concerned in detecting the behavioral pattern of humans(subject)using morphological image processing,a considerable portion of the study has been conducted utilizing frontal vision data of human *** present research work had used a side vision of human-face data to develop a theoretical framework via a hybrid analytical model *** this example,hybridization includes an artificial neural network(ANN)with a genetic algorithm(GA).We researched the geometrical properties extracted from side-vision human-face *** additional study was conducted to determine the ideal number of geometrical characteristics to pick while *** close vicinity ofminimum distance measurements is done for these clusters,mapped for proper classification and decision process of behavioral *** identify the data acquired,support vector machines and artificial neural networks are utilized.A method known as an adaptiveunidirectional associative memory(AUTAM)was used to map one side of a human face to the other side of the same *** behavioral pattern has been detected based on two-class problem classification,and the decision process has been done using a genetic algorithm with best-fit *** developed algorithm in the present work has been tested by considering a dataset of 100 subjects and tested using standard databases like FERET,Multi-PIE,Yale Face database,RTR,CASIA,*** complexity measures have also been calculated under worst-case and best-case situations.

关键词： Adaptive-unidirectional-associative-memory technique artificial neural network genetic algorithm hybrid approach

Detection and Classification of Potential Caves on the Flank of Elysium Mons,Mars

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Research in Astronomy and Astrophysics 2022年第6期22卷 81-90页

作者： Ravi Sharma neeraj Srivastava J.J.T.University Jhunjhunu.Rajasthan 333001India Planetary Science Division Physical Research LaboratoryAhmedabad 380009India

Martian caves have revived interest in the field of subsurface exploration because they are the potential destinations for future human habitats and astrobiological *** are many pits on Mars,but some of them look like collapsed cave *** special pits are formed by the collapse of surface materials into the subsurface void *** signature of life is probable in a subsurface cave on Mars as the subsurface environment can protect life from the harsh and dangerous radiation environment of the *** a cave,there may be an abundance of minerals,fluids,and other key ***,locating the access point of the subsurface cave is essential and crucial for formulating plans for robotic/human explorations of the Red Planet,*** have used remote sensing data from Mars Reconnaissance Orbiter(MRO;NASA),Mars Global Surveyor(MGS;NASA),and Mars Odyssey(NASA)for identifying,mapping,and classifying selected special pit candidates on the flank of Elysium Mons,Mars.A total of 32 special pit candidates has been identified and classified based upon morphology and geological *** of these,26 are newly discovered *** thermal behavior of 23 special pit candidates confirms that the special pits are radiating heat energy at nighttime,similar to potential ***,cave entrances have been detected in nine candidates using data from the Hi RISE camera onboard *** sites could be important destinations for future robotic/human exploration and the search for life on Mars.

关键词： planets and satellites individual(Mars)-planets and satellites surfaces-planets and satellites general

A relativistic model of stellar objects with core-crust-envelope division

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Research in Astronomy and Astrophysics 2021年第7期21卷 71-83页

作者： Ravindra K.Bisht Satyanarayana Gedela neeraj Pant neeraj Tewari Department of Mathematics National Defence AcademyKhadakwaslaPune-411023India Department of Mathematics SSJ CampusKumaun UniversityAlmora-263601India Department of Physics Lajpat Rai CollegeGhaziabad-201005India

In this work, we present a cogent and physically well-behaved solution for neutron stars envisaged with a core layer having quark matter satisfying the MIT-bag equation of state(Eo S), meso layer with Bose-Einstein condensate(BEC) matter satisfying modified BEC Eo S and an envelope having neutron fluid and Coulomb liquids satisfying quadratic Eo S. All the required physical and geometrical parameters like gravitational potentials, pressures, radial velocity, anisotropy, adiabatic index, mass function, compactification factor, and gravitational and surface redshift functions show a feasible trend and are continuous with smooth variation throughout the interior and across the regions of the ***, causality condition, energy conditions, static stability criterion(using Tolman-OppenheimerVolkoff equation) and Herrera cracking stability criterion are met throughout the star. The approach seems to be resulting in more realistic and accurate modeling of stellar objects, particularly realized by us for X-ray binary stars 4 U 1608–52(M = 1.7 M_⊙, R = 9.5 km) and SAX J1808.4–3658(M = 1.2 M_⊙,R = 7.2 km). Furthermore, we have ascertained that the continuity of the stability factor in all three regions of the stars demand a smaller core. As the core region of the star increases, the stability factor becomes discontinuous at all the interfaces inside the star.

关键词： stars:interiors stars:neutron Galaxy:stellar content

Assessing the bird guild patterns in heterogeneous land use types around Jammu,Jammu and Kashmir,India

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Ecological Processes 2020年第1期9卷 564-578页

作者： Asha Sohil neeraj Sharma Institute of Mountain Environment University of JammuJammuIndia

Land-use sprawl in the Himalayas has caused the conversion of natural habitat into human-modified habitats,thus degrading ecosystem *** of birds to changing physical environment can be well understood by analyzing their habitat preferences,and foraging dynamics explored to a limited extent in the Himalayan region,as *** achieve a comprehensive understanding of avian guild structure,we used multivariate statistical techniques to classify bird species according to their similarities in foraging patterns and habitat *** based on habitat and diet affinities accounted for rich avian diversity with a total of 208 bird species(about 15%of country’s avifauna)recorded from six different sites during 1 year *** pair-group average cluster analysis performed on the families revealed ten feeding and fifteen habitat guilds among 63 bird families *** forests harbored more species followed by urban forests and agricultural *** and omnivorous outnumbered other feeding guilds in the study *** assemblages were richer in protected areas and semidisturbed landscapes and did not show significant variation between the *** of the study revealed that different functional groups of birds behaved differently,primarily induced by choice of *** site heterogeneity favored avifaunal persistence by providing favorable foraging,roosting,and nesting opportunities to *** of avian guilds indicated level of intactness and ecological integrity of ecosystems *** outcome thus sets the background for long-term analysis of bird-habitat relationship and their foraging *** study has the relevance for decision-makers to integrate avian guild structure as an essential ingredient in formulating conservation strategies.

关键词： Avian guild Food resource utilization Habitat preference Heterogeneous landscape Eutrophic wetland Protected area

EMD-Att-LSTM: A Data-driven Strategy Combined with Deep Learning for Short-term Load Forecasting

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Journal of Modern Power Systems and Clean Energy 2022年第5期10卷 1229-1240页

作者： neeraj Jimson Mathew Ranjan Kumar Behera Indian Instituteof Technology Patna801103India

Electric load forecasting is an efficient tool for system planning, and consequently, building sustainable power systems. However, achieving desirable performance is difficult owing to the irregular, nonstationary, nonlinear, and noisy nature of the observed data. Therefore, a new attention-based encoderdecoder model is proposed, called empirical mode decomposition-attention-long short-term memory(EMD-Att-LSTM).EMD is a data-driven technique used for the decomposition of complex series into subsequent simpler series. It explores the inherent properties of data to obtain the components such as trend and seasonality. Neural network architecture driven by deep learning uses the idea of a fine-grained attention mechanism, that is, considering the hidden state instead of the hidden state vectors, which can help reflect the significance and contributions of each hidden state dimension. In addition, it is useful for locating and concentrating the relevant temporary data,leading to a distinctly interpretable network. To evaluate the proposed model, we use the repository dataset of Australian energy market operator(AEMO). The proposed architecture provides superior empirical results compared with other advanced models. It is explored using the indices of root mean square error(RMSE) and mean absolute percentage error(MAPE).

关键词： Short-term load forecasting Australian energy market operator long short-term memory(LSTM) empirical mode decomposition(EMD) attention mechanism

Enhanced thermoelectric figure of merit at near room temperature in n-type binary silver telluride nanoparticles

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Journal of Materiomics 2023年第2期9卷 310-317页

作者： Amish Kumar Gautam neeraj Khare Department of Physics Indian Institute of Technology DelhiHauz KhasNew Delhi110016India

In the present study,we have synthesized Ag2Te nanoparticles using the hydrothermal method and showed significant improvement in the thermoelectric properties compared to the bulk Ag2Te ***2Te nanoparticles showed the highest figure of merit(zT)of 1.37 at 373 K,which is the highest zT reported for this undoped *** high zT in Ag2Te nanoparticles is mainly due to about~2 times higher electrical conductivity(1967 S/cm)and subsequently~2 times lower thermal conductivity(0.53 W/(m$K))as compared to the bulk Ag2Te *** higher electrical conductivity in Ag2Te nanoparticles can be accredited for two reasons(i)better mobility of the charge carrier and(ii)increased carrier *** low thermal conductivity is associated with the enhanced scattering of phonons at the interface of the Ag2Te nanoparticles.

关键词： Silver telluride Nanoparticles Thermoelectrics Figure of merit

Bone-targeted therapies to reduce skeletal morbidity in prostate cancer

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Asian Journal of Andrology 2018年第3期20卷 215-220页

作者： Tanya B Dorff neeraj Agarwal USC Keck School of Medicine USC Norris Comprehensive Cancer Center Genitourinary Oncology Los Angeles CA 90033 USA Hunts Man Cancer Institute Universityof Utah 2000 Circle of Hope Salt Lake City UT 84112 USA

Bone metastases are the main driver of morbidity and mortality in advanced prostate cancer. Targeting the bone microenvironment, a key player in the pathogenesis of bone metastasis, has become one of the mainstays of therapy in men with advanced prostate cancer. This review will evaluate the data supporting the use of bone-targeted therapy, including （1） bisphosphonates such as zoledronic acid, which directly target osteoclasts, （2） denosumab, a receptor activator of nuclear factor-kappa B （RANK） ligand inhibitor, which targets a key component of bone stromal interaction, and （3） radium-223, an alpha-emitting calcium mimetic, which hones to the metabolically active areas of osteoblastic metastasis and induces double-strand breaks in the DNA. Denosumab has shown enhanced delay in skeletal-related events compared to zoledronic acid in patients with metastatic castration-resistant prostate cancer （mCRPC）. Data are mixed with regard to pain control as a primary measure of efficacy. New data call into question dosing frequency, with quarterly dosing strategy potentially achieving similar effect compared to monthly dosing for zoledronic acid. In the case of radium-223, there are data for both pain palliation and improved overall survival in mCRPC. Further studies are needed to optimize timing and combination strategies for bone-targeted therapies. Ongoing studies will explore the impact of combining bone-targeted therapy with investigational therapeutic agents such as immunotherapy, for advanced prostate cancer. Future studies should strive to develop biomarkers of response, in order to improve efficacy and cost-effectiveness of these agents.

关键词： bisphosphonate bone metastases prostate cancer radiopharmaceutical receptor activator of nuclear factor-kappa B-ligand