bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding the Value of Green Event: A Case Study of Event’s Company
Authors: Zamzuri Norol Hamiza , Wong Anthony , Abd Latif Zulkiflee
Published: August 2021

This paper attempts to bring forward the idea of organizing a green event. A case study was conducted at AOS Convention and Events Sdn. Bhd. which is one of event’s company in Kuala Lumpur. Based on active participative observation and semi-structure interview it found that AOS Convention and Events Sdn. Bhd. is very committed to practice green during an event. It also found that the event’s attendees who attended the event were very satisfied with the organizing of event by the event’s organizer. Future researcher is suggested to explore more on the value of organizing a green event.
Keywords: Green event; Salue; Sustainable event
eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.
DOI: https://doi.org/10.21834/ebpj.v6iSI4.2920
Отрицательное маховское отражение с множественными тройными конфигурациями при дифракции ударной волны на клине
Authors: Георгиевский П.Ю. , Максимов А.Н. , Фокеев В.П.
Published: August 2021

Within the framework of the Euler equations, a numerical study of the structure of a self-similar flow for various types of negative Mach reflection during diffraction of a shock wave by a wedge is performed. Along with the known modes of double and triple Mach reflection, a qualitatively new mode of negative Mach reflection with multiple three-shock configurations is observed. Peculiarities of the transition from multiple Mach reflection to regular reflection when changing the wedge angle are noted.
Определение трещиностойкости образцов с шевронным надрезом с использованием трехточечного изгиба
Authors: Дерюгин E.E. , Богданов А.А.
Published: August 2021

A method is proposed for the experimental determination of the specific fracture energy of a material under loading by a 3-point bending of a rectangular specimen with a chevron notch. It is shown that at the initial stages of crack propagation in the chevron notch zone, a linear dependence of the specimen compliance on the crack length is observed. This makes it possible to calculate the specific fracture energy of the material without using the phenomenological equations used under standard test conditions. The calculations were carried out for technical titanium VT1-0.
Циркулярно поляризованная электролюминесценция при комнатной температуре в гетероструктурах на основе разбавленного магнитного полупроводника GaAs:Fe
Authors: Ведь М.В. , Дорохин М.В. , Лесников В.П. , Кудрин А.В. , Дёмина П.Б. , Здоровейщев А.В. , Данилов Ю.А.
Published: August 2021

In this work, we demonstrate the possibility of using a diluted magnetic semiconductor GaAs:Fe as a ferromagnetic injector in a spin light-emitting diode based on a GaAs/InGaAs quantum well heterostructure. It is shown that in such a device it is possible to observe partially circularly polarized electroluminescence at room temperature.
Исследование условий пробоя газов в пористом диэлектрике
Authors: Медведев Д.Д. , Белов Н.К. , Гранкина О.О. , Книжник А.А. , Коробцев С.В. , Потапкин Б.В.
Published: August 2021

Plasma treatment of porous polymeric materials is a promising method for creating new materials that can be used in various applied problems, including medicine, in the development of new types of biocompatible and biodegradable polymeric materials. This work is devoted to the study of the processes of plasma treatment of porous polymeric materials depending on the size and type of pores in order to clarify the breakdown conditions and optimize the treatment process. A convenient semi-empirical model of the development of breakdown in a porous dielectric is proposed.
Machine Learning Methodologies for Prediction of Rhythm-Control Strategy in Patients Diagnosed With Atrial Fibrillation: Observational, Retrospective, Case-Control Study
Authors: Kim Rachel S , Simon Steven , Powers Brett , Sandhu Amneet , Sanchez Jose , Borne Ryan T , Tumolo Alexis , Zipse Matthew , West J Jason , Aleong Ryan , Tzou Wendy , Rosenberg Michael A
Published: August 2021

Background

The identification of an appropriate rhythm management strategy for patients diagnosed with atrial fibrillation (AF) remains a major challenge for providers. Although clinical trials have identified subgroups of patients in whom a rate- or rhythm-control strategy might be indicated to improve outcomes, the wide range of presentations and risk factors among patients presenting with AF makes such approaches challenging. The strength of electronic health records is the ability to build in logic to guide management decisions, such that the system can automatically identify patients in whom a rhythm-control strategy is more likely and can promote efficient referrals to specialists. However, like any clinical decision support tool, there is a balance between interpretability and accurate prediction.

Objective

This study aims to create an electronic health record–based prediction tool to guide patient referral to specialists for rhythm-control management by comparing different machine learning algorithms.

Methods

We compared machine learning models of increasing complexity and used up to 50,845 variables to predict the rhythm-control strategy in 42,022 patients within the University of Colorado Health system at the time of AF diagnosis. Models were evaluated on the basis of their classification accuracy, defined by the F1 score and other metrics, and interpretability, captured by inspection of the relative importance of each predictor.

Results

We found that age was by far the strongest single predictor of a rhythm-control strategy but that greater accuracy could be achieved with more complex models incorporating neural networks and more predictors for each participant. We determined that the impact of better prediction models was notable primarily in the rate of inappropriate referrals for rhythm-control, in which more complex models provided an average of 20% fewer inappropriate referrals than simpler, more interpretable models.

Conclusions

We conclude that any health care system seeking to incorporate algorithms to guide rhythm management for patients with AF will need to address this trade-off between prediction accuracy and model interpretability.
COVID-19 Mortality Prediction From Deep Learning in a Large Multistate Electronic Health Record and Laboratory Information System Data Set: Algorithm Development and Validation
Authors: Sankaranarayanan Saranya , Balan Jagadheshwar , Walsh Jesse R , Wu Yanhong , Minnich Sara , Piazza Amy , Osborne Collin , Oliver Gavin R , Lesko Jessica , Bates Kathy L , Khezeli Kia , Block Darci R , DiGuardo Margaret , Kreuter Justin , O’Horo John C , Kalantari John , Klee Eric W , Salama Mohamed E , Kipp Benjamin , Morice William G , Jenkinson Garrett
Published: August 2021

Background

COVID-19 is caused by the SARS-CoV-2 virus and has strikingly heterogeneous clinical manifestations, with most individuals contracting mild disease but a substantial minority experiencing fulminant cardiopulmonary symptoms or death. The clinical covariates and the laboratory tests performed on a patient provide robust statistics to guide clinical treatment. Deep learning approaches on a data set of this nature enable patient stratification and provide methods to guide clinical treatment.

Objective

Here, we report on the development and prospective validation of a state-of-the-art machine learning model to provide mortality prediction shortly after confirmation of SARS-CoV-2 infection in the Mayo Clinic patient population.

Methods

We retrospectively constructed one of the largest reported and most geographically diverse laboratory information system and electronic health record of COVID-19 data sets in the published literature, which included 11,807 patients residing in 41 states of the United States of America and treated at medical sites across 5 states in 3 time zones. Traditional machine learning models were evaluated independently as well as in a stacked learner approach by using AutoGluon, and various recurrent neural network architectures were considered. The traditional machine learning models were implemented using the AutoGluon-Tabular framework, whereas the recurrent neural networks utilized the TensorFlow Keras framework. We trained these models to operate solely using routine laboratory measurements and clinical covariates available within 72 hours of a patient’s first positive COVID-19 nucleic acid test result.

Results

The GRU-D recurrent neural network achieved peak cross-validation performance with 0.938 (SE 0.004) as the area under the receiver operating characteristic (AUROC) curve. This model retained strong performance by reducing the follow-up time to 12 hours (0.916 [SE 0.005] AUROC), and the leave-one-out feature importance analysis indicated that the most independently valuable features were age, Charlson comorbidity index, minimum oxygen saturation, fibrinogen level, and serum iron level. In the prospective testing cohort, this model provided an AUROC of 0.901 and a statistically significant difference in survival (P<.001, hazard ratio for those predicted to survive, 95% CI 0.043-0.106).

Conclusions

Our deep learning approach using GRU-D provides an alert system to flag mortality for COVID-19–positive patients by using clinical covariates and laboratory values within a 72-hour window after the first positive nucleic acid test result.
Forecasting the COVID-19 Epidemic By Integrating Symptom Search Behavior Into Predictive Models: Infoveillance Study (Preprint)
Authors: Rabiolo Alessandro , Alladio Eugenio , Morales Esteban , McNaught Andrew Ian , Bandello Francesco , Afifi Abdelmonem A , Marchese Alessandro
Published: August 2021

BACKGROUND

Previous studies have suggested associations between trends of web searches and COVID-19 traditional metrics. It remains unclear whether models incorporating trends of digital searches lead to better predictions.

OBJECTIVE

The aim of this study is to investigate the relationship between Google Trends searches of symptoms associated with COVID-19 and confirmed COVID-19 cases and deaths. We aim to develop predictive models to forecast the COVID-19 epidemic based on a combination of Google Trends searches of symptoms and conventional COVID-19 metrics.

METHODS

An open-access web application was developed to evaluate Google Trends and traditional COVID-19 metrics via an interactive framework based on principal component analysis (PCA) and time series modeling. The application facilitates the analysis of symptom search behavior associated with COVID-19 disease in 188 countries. In this study, we selected the data of nine countries as case studies to represent all continents. PCA was used to perform data dimensionality reduction, and three different time series models (error, trend, seasonality; autoregressive integrated moving average; and feed-forward neural network autoregression) were used to predict COVID-19 metrics in the upcoming 14 days. The models were compared in terms of prediction ability using the root mean square error (RMSE) of the first principal component (PC1). The predictive abilities of models generated with both Google Trends data and conventional COVID-19 metrics were compared with those fitted with conventional COVID-19 metrics only.

RESULTS

The degree of correlation and the best time lag varied as a function of the selected country and topic searched; in general, the optimal time lag was within 15 days. Overall, predictions of PC1 based on both search terms and COVID-19 traditional metrics performed better than those not including Google searches (median 1.56, IQR 0.90-2.49 versus median 1.87, IQR 1.09-2.95, respectively), but the improvement in prediction varied as a function of the selected country and time frame. The best model varied as a function of country, time range, and period of time selected. Models based on a 7-day moving average led to considerably smaller RMSE values as opposed to those calculated with raw data (median 0.90, IQR 0.50-1.53 versus median 2.27, IQR 1.62-3.74, respectively).

CONCLUSIONS

The inclusion of digital online searches in statistical models may improve the nowcasting and forecasting of the COVID-19 epidemic and could be used as one of the surveillance systems of COVID-19 disease. We provide a free web application operating with nearly real-time data that anyone can use to make predictions of outbreaks, improve estimates of the dynamics of ongoing epidemics, and predict future or rebound waves.
Authors’ Response to Peer Reviews of “Finding Potential Adverse Events in the Unstructured Text of Electronic Health Care Records: Development of the Shakespeare Method” (Preprint)
Authors: Bright Roselie A , Rankin Summer K , Dowdy Katherine , Blok Sergey V , Bright Susan J , Palmer Lee Anne M
Published: August 2021

UNSTRUCTURED

These are author responses to peer review.
Economic burden of rivaroxaban and warfarin among nonvalvular atrial fibrillation patients with obesity and polypharmacy
Authors: Laliberté François , Ashton Veronica , Kharat Akshay , Lejeune Dominique , Moore Kenneth Todd , Jung Young , Lefebvre Patrick , Berger Jeffrey S
Published: August 2021

Aim:
Evaluate healthcare resource utilization (HRU) and costs associated with rivaroxaban and warfarin among nonvalvular atrial fibrillation (NVAF) patients with obesity and polypharmacy.
Materials & methods:
IQVIA PharMetrics
®
Plus (January 2010–September 2019) data were used to identify NVAF patients with obesity (BMI ≥30 kg/m
2
) and polypharmacy (≥5 medications) initiated on rivaroxaban or warfarin. Weighted rate ratios and cost differences were evaluated post-treatment initiation.
Results:
Rivaroxaban was associated with significantly lower rates of HRU, including hospitalization (rate ratio [95% CI]: 0.83 [0.77, 0.92]). Medical costs were reduced in rivaroxaban users (difference [95% CI]: -US$6868 [-US$10,628, -US$2954]), resulting in significantly lower total healthcare costs compared with warfarin users (difference [95% CI]: -US$4433 [-US$8136, -US$582]).
Conclusion:
Rivaroxaban was associated with lower HRU and costs compared with warfarin among NVAF patients with obesity and polypharmacy in commercially insured US patients.
El proceso de institucionalización de la ciencia política en Canadá: una lectura comparativa desde México.
Authors: Flores-Mariscal J. R. Joel
Published: August 2021

A partir de una revisión de la literatura metadisciplinar se realiza una exploración histórica y descripción de algunos factores contextuales y de la influencia de la tradición estadounidense en la conformación del perfil contemporáneo de la ciencia política en Canadá, ello desde el punto de vista de la tradición e historia de la ciencia política mexicana, la cual se considera tuvo un proceso de desarrollo con algunos aspectos paralelos particularmente en lo que respecta a la influencia de la tradición estadounidense en su perfil disciplinar.
Políticas monetarias no convencionales en Estados Unidos. La trampa de la liquidez en la economía contemporánea
Authors: Duarte Cesar
Published: August 2021

El artículo analiza el fundamento teórico detrás de las políticas monetarias no convencionales implementadas en Estados Unidos a raíz de la crisis 2008 y la Gran Recesión, en la versión institucional oficial, a partir de la revisión de los informes publicados por la Reserva Federal y el Banco Internacional de Pagos. A esta perspectiva se contrapone el concepto de trampa de liquidez de la teoría keynesiana. Se muestra que el análisis teórico de estas instituciones ignora un elemento clave en el diagnóstico de las dificultades enfrentadas por la política monetaria, la situación de las expectativas respecto al futuro. Adicionalmente, se hace énfasis en la idea de que, en las condiciones actuales del capitalismo, la trampa de liquidez es un fenómeno permanente debido al poder que tienen los intermediarios financieros, lo que rompe con el mecanismo de transmisión tradicional de la política monetaria.

 
Raíces políticas de la ineficiencia del mercado de deuda pública en la eurozona
Authors: Waszkiewicz Grzegorz
Published: August 2021

La literatura internacional confirma la ineficiencia de los mercados de deuda soberana de la Eurozona antes de la última crisis, al mismo tiempo, adolece de la explicación suficiente de este fenómeno. Esto se debe a que las razones económicas y financieras no son completamente persuasivas, mientras que los aspectos relacionados con la política necesitan una aclaración más profunda.

Por lo tanto, este artículo tiene como objetivo definir las raíces políticas de la ineficiencia de los mercados de deuda soberana en la zona euro antes de 2009. Combinando el escrutinio de datos estadísticos con hallazgos de la literatura internacional, concluye que la gobernanza económica europea deformaba los requisitos de eficiencia del mercado. En consecuencia, los agentes del mercado que operan sin apoyo institucional no pudieron realizar una valoración fiable.

 
Reestructuración laboral en México frente al T-MEC
Authors: Cypher James M. , Crossa Mateo
Published: August 2021

Uno de los principales objetivos del T-MEC es la “legitimación” de las relaciones laborales de México bajo los nuevos criterios para la fuerza de trabajo mexicano. Las disposiciones laborales del T-MEC exigen la creación de instituciones clave financiadas por el gobierno de Estados Unidos (EU) y, sobre todo, México.  Los asuntos relacionados con la implementación de la reforma laboral de México de 2019, la cual incorpora diversos elementos novedosos en torno a procesos de ratificación de contratos colectivos de trabajo y titularidad sindical, en la cual se prioriza el ejercicio de votación libre y secreto, ahora es oficio del Representante Comercial de Estados Unidos (United States Trade Representative, -USTR). Afirma el gobierno de EU que tiene el poder de monitorear los derechos laborales de México, lo que permite que el USTR actúe sin el consentimiento de México. Irónicamente, sindicatos de EU están abogando por un “salario digno” para los obreros mexicanos para evitar o disminuir la desindustrialización. La imposición desde afuera de un mejoramiento en los salarios miserables es algo inimaginable para la oligarquía mexicana y las empresas transnacionales de EU con fábricas y minas en México.

 
Sensor less Control of Switched Reluctance Motor
Authors: Kruthika Tumma
Published: August 2021

Switched reluctance motor is considered for variable speed applications. It is a power device which can be manufactured easily and inexpensively and relatively high reliable. A sensor less control of SRM is proposed. Here, the communication of SRM is done without use of position detector. It is ensured that the switching of each phase winding takes place during positive slope of inductance profile. Simulation is carried out using MATLAB. A 6/4 SRM is used for this purpose.
Sentiment Analysis: Classifier and Summarizer
Authors: Aggarwal Ayushi
Published: August 2021

Sentiment Analysis and summarization has a large number of application that are useful for determining the sentiment of the text and summarizing a big text into a small paragraph of few lines. Thus it has become an important topic to work on and for fulling the requirements of the customer. It has also become an important topic for researchers to focus on, as it is highly demanded and beneficial in different fields of product, services and growth of the business. At present when 89.9% of people are using social media platform, they express their reviews, feelings, emotions and share their comments and some exciting activities of their life through social media platform, so it becomes very important to analyses them and classify them as positive or negative, this can be done with the help of sentiment analysis. Also, to find the summary of a big document with large amount of data summarizer is very useful as we can get the summary of a document in the favorable number of line. The basic model of sentimental analysis classify the word as positive as negative with the help of some machine learning approaches, which will help in improving the quality of product and providing the service to the customer for building up a healthy competition in market and keeping the goodwill of the business . It also displays the output in the form of graph whose data is taken from social media platform. Sentimental analysis also helps in getting the summary of the document by picking the lines containing the words having maximum repetitions. It has been found that sentiment analysis able to classify the positive sentence by giving the output as 1 and negative sentences as 0. The model which is being built also graphically represents the classifications of positive and negative words picked from the dataset and it’s also useful in summarizing a document Thus sentiment analysis comes out to be very important for classify the unstructured data on social media platform and so there is always a scope of building a better model which is more accurate and efficient.
Low Powered IOT Enable Smart Medicine Pill Box Using ESP 8266
Authors: Ughade Sneha M.
Published: August 2021

There can be a lot of individuals out there who need constant help – may it be our elderly people, family members, the ones who have special needs. These people apparently need the kind of care which most busy family members cannot provide. Some people may forget to take the medicines at the correct time and can forget the medicines which they have to take. So in order to help them with this liability we have developed this project. The people are provided a smart med box on which there will be a display which notifies the people about the medicine. Along with this we can alert them with an alarm and light indications. So that even if the person is sleeping or busy with some work the alarm helps in alerting him. to confirm that the person has taken that medicine or not we can put one button at the opening end of the pill box. so when the person tries to open the box the button is pressed and the alarm will be off only if the buzzer is pressed by this data we can tell that the person has taken medicine. It comes with one more feature that when the person is feeling uneasy or in case of some emergency he can notify the people by pressing the button on the device. There are different buttons, one is used to notify the doctor and the other one is used to notify family members about the emergency.
Free Vibration Analysis of Hybrid Laminated Composite Plate
Authors: Lamkhade Bajirao B.
Published: August 2021

In past decade a new manufacturing and Design technology developed across the globe because of that it possible to manufacture and analyses a hybrid laminated composite plate which is used in the various applications like aerospace, marine, spacecraft application were its subjected to dynamic loading so it is necessary estimate the response of the system under free vibration. Aim of this paper is Dynamic analysis of laminated composite plate which is made of hybridization of carbon epoxy and glass epoxy material. Natural frequencies are evaluated by FEM with the help of abaqus software for of hybrid laminated composite plate. The Parameter like aspect ratio, fiber orientation, boundary condition and mesh size of the FEA elements and stacking sequence affects natural frequencies of the plate. A hybrid laminated composite in which carbon fiber on top as well as bottom and glass fiber in inters layer gives maximum natural frequency at any boundary condition. FEM uses first order shear deformation theory.
A Conceptual Study on Security Issues in IoT
Authors: Vishwakarma Pawan
Published: August 2021

IoT is the component which is set up between advanced machines and associated gadgets. It is an interrelated framework where every thing has a novel identifier and consequently moves information and works the framework which works in the internet. Be that as it may, it isn't protected to leave the gadgets open since programmers or infections can undoubtedly assault or cut the information of the concerned individual or client. Various high-profile episodes where a typical IoT gadget was utilized to invade and assault the bigger organization has caused to notice the requirement for IoT security. Lacking information insurance (correspondence and capacity) The most regular worries in the information security of IoT applications are because of shaky interchanges and information stockpiling. One of the critical difficulties for IoT protection and security is that compromised gadgets can be utilized to get to classified information. It is basic to guaranteeing the security of organizations with IoT gadgets associated with them. Security in IoT is the demonstration of getting Internet of Things gadgets and the organizations they're associated with. In the business setting, IoT gadgets incorporate modern machines, keen energy networks, building mechanization, in addition to whatever individual IoT gadgets representatives bring to work. This scope of gadgets can present security hazards that can undermine your business. Every now and again planned without security, IoT gadgets have become another danger vector for agitators to utilize when dispatching assaults. We have effectively seen a few assaults utilizing these disseminated, apparently blameless gadgets. IoT security, incorporates a wide scope of procedures, systems, conventions and activities that intend to alleviate the expanding IoT weaknesses of present day organizations. In this paper the theoretical investigation of safety issues in IoT is given
An Emperical Investigation of Socio-Economic Parameters Associated with Crime in Karnataka Using Predictive Analysis
Authors: Mundada Dr. Monica R
Published: August 2021

The crime rate in India has been on a rise with growing population and rapid development. Crimes are a social nuisance and brings disrepute to the society and nation at large. Data mining techniques have enabled models to predict crime. The law enforcement officers and police personnel’s need to spend umpteen time to analyze crime from the crime reports published by National Crime Records Bureau and respective State police departments. Therefore, there is necessity of a mechanism which can predict crime by identifying factors responsible for increase in crime rate. This project is an attempt to address this. Socio-economic variables like poverty, urbanization, literacy, and the demographic and social composition of the population are recorded from Census data. Machine Learning algorithms namely Multiple Linear Regression, Random Forest Regressor and Generalized Linear Models are trained and deployed. These algorithms have been implemented assuming both linear and non-linear ship of data and subsequent results have been compared. Further, choropleth maps have been plotted to represent and understand data in a simple way. The results show that socio-economic factors are good indicator in explaining crime rates and good performance is observed with few models
Tunneling in Various Shapes Using Numerical Analysis
Authors: Dhake Shubham
Published: August 2021

Tunnelling has gained popularity in the recent times due to lack of space and the rapidly increasing population. Thus, going underground is the only option to provide the infrastructure facilities which will meet the need of increasing population. The shape and dimensions of the tunnel cross section usually depends on certain parameters like purpose for which the tunnel is provided, drainage & maintenance requirements, requirement of escape route, etc. Geology plays an important role in deciding the shape of the tunnel. The ground behaves in a complex manner, when a tunnel is excavated in it as new stresses are developed. Based on the ground types, the shape is selected in such a way that the stresses developed in the ground should distribute properly around the tunnel periphery and should not cause convergence of the tunnel boundary. Also, requirement of support system should not be too heavy, as it will increase the cost. Apart from the above parameters, the availability of the equipment & the construction method also decides the shape of the tunnel. There are various shapes of tunnels like D-shape, Circular, Elliptical, Egg-shape, Box type, Horseshoe & Modified Horseshoe shape. In the present course of work three shapes of tunnels viz. Horseshoe Shape, Modified Horseshoe Shape & D-Shape tunnels are considered. By hypothetical assumption the geology and overburden are taken into account for the tunnels and the tunnels are simulated for roof collapse and shear failure case by using RS2 FEM based software.
Assessment of Heavy Metals Contamination in Ground Water around Industrial Region in Nadar Ganj Lucknow
Authors: Singh Satyendra
Published: August 2021

Nadar Ganj being a prominent industrial area of Lucknow Uttar Pradesh, owes its significance to diverse group of industries. this study is to investigate the pollution of bore water in the industrial region in Nadar Ganj industrial area in Lucknow. The contamination of groundwater is one of the most important environmental issues in the world. Among the various pollutants that affect water resources, pollutants containing heavy metals are particularly important due to their high toxicity, even at low concentrations. The percolation water picks up a large number of heavy metals and reaches the aquifer system and contaminates ground water. five ground water sample were collected from the study area in February 2021.the heavy metals (Pb, Fe, Cu, Cr, Ni).
Fake News Classification Using Outliner Detection and Trend Analysis
Authors: Srivastava Anurag
Published: August 2021

In modern era fake news is one of the major causes for disrupted social harmony, impact of fake news can lead to various unforeseen situations and thus affect the society as a whole. This paper proposed the use of anomaly detection and trend analysis for detecting fake news.
Craft Cloud (E-Doorway for Artistic Works) Web Development
Authors: Singhal Mrs. Anjali
Published: August 2021

Craft Cloud is an online platform where people with different skills can showcase and sell their talent and Artworks. Like, a musician can add their skills and can get paid for a performance in a birthday, anniversary celebration, or whatsoever. It will also have a separate place on the platform for selling and purchasing handicraft etc. from all over India with a price predicting algorithm that will help clients from not getting underpaid and users from not getting overcharged for their service. In today’s fast changing business environment, it’s extremely important to be able to answer client needs within the simplest and timely manner. This project allows viewing various products available, enables registered users to urge desired products instantly using PayPal payment processor (Instant Pay) and may also place orders by using the Cash on Delivery (Pay Later) option. This project provides quick access to Administrators and Managers to look at orders placed using Pay Later and Instant Pay options. The project technologies are server and client-­side scripting techniques, multi-­tiered architecture, relational databases, implementation technologies, and programming language. This is often a project with the target to develop a basic website where a consumer is given a handcart application and also to know about the technologies wont to develop such an application. This document briefs each of the underlying technologies to implement and form an ecommerce website.
Altruistic Values amongst Multigenerational Faculty Members
Authors: Saxena Dr. Priyanka
Published: August 2021

The changing scenario of academic structure especially with the different age groups of faculty members has lead to varying expectations. Each generation has a different set of skills and experience and that needs to be shared amongst other faculty members. But due to the behavioral differences between the generations, it leads to hindrance in communication and sharing of knowledge. This empirical paper highlights the difference in altruistic behavior of Multi-Generational Faculty members. For this purpose study group included 383 faculty members from Prayagraj and Lucknow. Cohort Analysis will help in understanding the importance of encouraging altruistic behavior amongst Multi-Generational Faculty members. In this paper three generations that are Baby Boomers, Gen X, and Gen Y has been taken for the study. It was also analyzed to find out the difference that the altruistic behavior amongst the generation and within the generation varies or not. The findings and results are based on ANOVA analysis and further on Tukey HSD Test.
Population and Group Size of Cheer Pheasant Catreus Wallichii in Pokhari Valley, Garhwal Himalaya, India
Authors: Kukreti Manish
Published: August 2021

Present paper reports population dynamics of Cheer pheasant Catreus wallichii in Pokhari valley, Garhwal Himalaya during January 2019 to December 2019. A total of 405 individuals with 145 groups were recorded. Overall individuals per sighting and group size (3.88±0.51 and 3.40±0.45) were also recorded during the study period respectively. Maximum value of individuals per sighting and group size were recorded in months of July and November (6.13±0.76 and 7.32±0.97), while minimum were recorded in May and April (1.75±0.27 and 1.17±0.26). Seasonal variation was also observed in population and group size. Maximum value of individual per sighting was recorded during the Monsoon season and minimum were recorded in spring season. While maximum and minimum group size were recorded in winter and spring Season.
Fake News Detection Using ML
Authors: Sharma Udit
Published: August 2021

Fake news is depicted as a story that is made up with an aim to mislead or to swindle the peruser. We have introduced a reaction for the undertaking of phony news disclosure by utilizing Deep Learning structures. Because of various number of instances of phony news the outcome has been an augmentation in the in the spread of phony news. Due to the wide impacts of the immense onsets of phony news, people are conflicting if not by huge helpless finders of phony news. The most liked of such exercises consolidate "boycotts" of sources and producers that are not trustworthy. While these instruments are used to make an inexorably unique complete beginning to end plan, we need to address continuously inconvenient situations where logically strong sources and makers discharge fake news. As, the objective of this endeavor was to make a mechanical assembly for perceiving the language designs that portray phony and confirmed news using AI, AI and customary language getting ready techniques. The consequences of this undertaking exhibit the breaking point with respect to AI and AI to be huge. We have developed a model that gets numerous no of normal indications of veritable and phony news and additionally an application that aides in the portrayal of the order decision.
Dielectric Relaxation and Thermodynamic Study of Caffeine-Chloroform Solution using TDR
Authors: Lathi A. R.
Published: August 2021

The Complex permittivity of caffeine – Chloroform solution for different temperature and various concentrations have been measured in the range of 10MHZ to 30 GHz using Time Domain Reflectometry. From complex permittivity spectra, Static dielectric constant (εo) and relaxation time (τ) were determined using nonlinear least square fit method. Using Erying rate equation, for different molar concentration of caffeine Enthalpy of Activation ∆H and Entropy of Activation ∆S were determined.
Design & Analysis of Integrated Battery Mounting Tray for Commercial Vehicle
Authors: Sutar Pritesh
Published: August 2021

In vehicle battery mounting systems are very important due to different aspects and performance. At the start of improvement, the construction of the battery holder should be promptly checked and accurately analyzed, without sufficient authorization from the vehicle. The battery mounting bracket has been designed as a frame to support the battery. Battery carrier vibration and fatigue has always been a concern that can lead to tray failure if the design is wrong, due to vehicle vibration and stress, the mounting tray will be damaged. This is an important study that requires extensive investigation to understand the structural features and its dynamic behavior. This research presents a Finite Element (FE) analysis of a typical battery mounting tray of a car will be performed and the natural frequency will be determined.
Restaurant Success Rate Prediction
Authors: Shete Apoorva
Published: August 2021

Online reviews are becoming more and more vital when it comes to decision making of the consumer. Every business wants to succeed in the present and the upcoming future, thus good online reviews help the business grow. Especially in a restaurant business, its rating holds an important indicator to whether the restaurant is any good or not. It not only helps us understand the quality and services but also attracts more customers. Ordinarily a new restaurant owner would have to invest time in building a menu, setting the correct price range and making something unique to scope out their competition as well as improve their ratings on online services such as Zomato. Thus, this paper attempts to ease the efforts of new restaurant owners by predicting the success rate of a restaurant on the Zomato app.
Optimization Study of Tilt Angle for Single Slope Solar Still
Authors: Joshi Onkar
Published: August 2021

Water is essential to life. The origin and continuation of mankind is based on water. The supply of drinking water is an important problem for the developing countries. The wooden box has a thickness of 8mm. It consists of a top cover of transparent glass with a tilt of 18°, 26° and is coated with black paint to absorb the maximum possible solar energy. The yield of the single basin solar still is very less and it increases considerably when the solar still was built with copper sheet. An analysis of single slope solar still has done on different tilt angle to optimizing study of tilt angle. They greatly improve the rate of evaporation and the rate of condensation on the cooler surface. The efficiency is higher for solar still made up of copper sheet and its output we have got 1.24 for 18° angle. The optimized tilt angle gave more efficiency than other tilt angle. The optimize water depth is 18mm for 18° angle. This cost-effective design is expected to provide the rural communities an efficient way to convert the brackish water in to potable water.
Application of Block-Chain Technology in Healthcare Industry to Pursue COVID 19 Challenges
Authors: Pawar Mr. Chetan R.
Published: August 2021

In the year of 2019 coronavirus (COVID-19) start spreading in China, but at the starting of 2020 the pandemic of COVID-19 disease has uncontrolled spread and adversely affected the whole world. The rapid explosion and worldwide spread shows the constraints of our healthcare systems to handle public healthcare emergencies. an outsized amount of our healthcare system is centralized, so it can’t provide important information about patients contact tracing, frauds in vaccination certificates, testing related data and medical supply related data. In such contexts innovative and newest technologies like blockchain have initiate as promising solutions for fighting with such situations like pandemic. By using blockchain technology we will combat pandemics by enabling early detection of patients, ensuring the orders of medical data and maintain reliable medical supply chain during pandemic. This study proposes a narrative innovative approach for handling challenges of (COVID-19) pandemic and contagion. This study proposes a Blockchain-based framework which investigate the chance of utilizing peer-to peer, time stamping, and decentralized storage advantages of blockchain to create a brand new system to verify and detect the unknown infected cases of COVID-19 (SARS COV-2) virus. The framework will enable to make sure citizens in addition as government to predict the infection risk of virus, to provide an efficient system able to support governments, healthcare experts, health related authorities and citizens to require critical decisions regarding infection and infection avoidance. this method consists of Blockchain Platform, Mobile application, closed-circuit television these components works together for detecting unknown infected patients and predict the infection risk of corona virus. to create decisions on vaccination and medical supply.
Blockchain Based Bidding System
Authors: Srinivas Mr. C. K
Published: August 2021

The E-auction, one of the most common e-commerce events, allows bidders to bid directly on the Internet. As with the sealed deal, additional transaction costs are needed with intermediaries, as the third party plays an essential role between buyers and sellers in helping to negotiate both during the auction. In fact, it never confirms that a third party is trustworthy. To solve the problems, we propose the low transaction cost blockchain technology which is used to build the public bid and sealed bid smart contract. The smart contract consists of the Auctioneer address, the start time for the auction, the deadline, the current winner's address, and the current highest price. The project demonstrates the bidding framework with blockchain technology. This bidding application prepared by using Advanced Encryption Standard(AES) Algorithm. This algorithm contains AES cipher specifiers the number of repetitions of transformation rounds, that converts the input called the plain text, then into the final output called cipher text.
VAMANAKARMA: AN ANCIENT AYURVEDIC CLEANSING THERAPY
Authors: Giri D
Published: August 2021

‘Charaka Samhita’ an ancient text of Ayurveda emphasizes the cleansing of the body through Panchakarma. Today’s generation is out of touch with nature. Poor dietary habits, fast foods, no proper exercise regimen, stress and strain of daily life to compete and survive- these patterns have led to a lot of hormonal changes, and the agents that regulate the body’s mechanism have become poor leading to the spread of toxins throughout the body causing various diseases. As per Ayurveda, these toxins are called “ama”. This foul-smelling, sticky, harmful fluid needs to be completely removed from the body. This is done through Panchkarma, which is advised quarterly, half-yearly, or yearly to get rid of the toxins from the body and also to provide protection from different diseases. This process has twofold benefits – cleansing of the body and also rejuvenation, thus giving a youthful appearance to the body. Panchakarma includes five methods through which the body is detoxified –Procedure of Vamana (induced vomiting), Procedure of Virechana (induced purgation), Basti (enema), Nasya (nasal application), Rakthamokshanana (bloodletting). The three Doshas (vital physiological factors according to Ayurveda) in the human body that is - Vata, Pita, and Kapha are balanced, leading to good physical health and mental balance. Vamanaprocedure means induction of emesis. Through this procedure, the toxins are removed from the body especially through the upper body parts. Vamanaisthe best remedy for Kapha-related diseases. Most of the diseases today are due to improper digestion and metabolism (Agni). The cause is the changing lifestyle full of stress and anxiety. Irregular dietary habits add further to these issues. Diseases need to be uprooted from the base. Therapies like Panchkarma or particular therapy as VamanaKarma for particular Doshas like Kapha can be thought of on a regular basis as a remedy.
ALTERAÇÕES ANTRÓPICAS NA BACIA HIDROGRÁFICA DO ARROIO SAPUCAIA, MUNICÍPIO DE GRAVATAÍ (RS)
Authors: Cattaneo Wagner Costa , Moura Nina Simone Vilaverde
Published: August 2021

A presente pesquisa consiste em uma análise integradora entre elementos naturais e àqueles transformados ou induzidos pelos agentes sociais. A bacia hidrográfica do arroio Sapucaia possui extensão territorial de 129,7 km² e abrange seis municípios da Região Metropolitana de Porto Alegre/RS. Na sub-bacia hidrográfica do arroio Santa Tecla, no município de Gravataí/RS, pode-se identificar a mais extensa cicatriz de mineração, localidade com predomínio de atividades rurais no que se refere ao uso e ocupação da terra, e importante área de nascentes de arroios. Observou-se o quão os empreendimentos mineradores contribuem como força motriz desencadeadora de processos erosivos e assoreamento de canais e banhados. Como suporte metodológico, aplicou-se conhecimentos das ciências geológica e geomorfológica em sua abordagem ambiental, conforme os pressupostos de Chemekov (1983) e Oliveira (1990) na aplicação do conceito de depósitos tecnogênicos de origem fluvial, o emprego de técnicas de análise granulométrica com base na escala de Wentworth e a Lei de Stokes, bem como o uso de ferramentas de sensoriamento remoto para o reconhecimento do terreno e identificação das classes de uso e ocupação da terra. Dessa forma, compreendeu-se que algumas classes de uso da terra exercem maior pressão sobre o ambiente no setor de nascentes, com desdobramentos na rede de drenagem. Pode-se constatar, através de análise sedimetológica em laboratório especializado e observações em trabalhos de campo, a influência da atividade mineradora na disponibilidade de sedimentos ao ambiente e seu reflexo no leito dos arroios, sobretudo na sub-bacia do arroio Santa Tecla, induzindo o assoreamento dos canais.
ANALISIS KEPEMILIKAN ASING DAN NILAI PERUSAHAAN NON-KEUANGAN YANG TERDAFTAR DI BEI
Authors: Taduga Felix Kurniawan , Noval Muhammad
Published: August 2021

This study aims to analyse impact of foreign ownership to value of non-financial companies listed on Indonesia Stock Exchange.The independent variables consist of Total Foreign Ownership, Foreign Institution Ownership, and Foreign Company Ownership. The variables control consist of size, age, dummy director. Variable dependent is Company Value, using Tobins'Q ratio. The research sample is 72 companies with purposive sampling sampling technique. Period of data is 5 years, from 2014-2018. Data panel regression using as data analysis method. The results showed that Total Foreign Ownership and Foreign Institution Ownership positively and still significantly at level of <15%. While Foreign Company Ownership has a positive but insignificant relationship to the value company. Size, Age, dummy director is not influence to value company. Penelitian ini bertujuan untuk menganalisis pengaruh kepemilikan asing terhadap nilai perusahaan pada perusahaan non-keuangan yang terdaftar di Bursa Efek Indonesia. Variabel independen terdiri dari Kepemilikan Asing Total, Kepemilikan Institusi asing, dan Kepemilikan Perusahaan Asing. Variabel kontrol terdiri dari Ukuran perusahaan, Umur Perusahaan, dan dummy Direksi. Variabel dependen adalah Nilai Perusahaan, diukur dengan Tobin’s Q. Sampel penelitian sebanyak 72 perusahaan yang ditentukan dengan teknik purposive sampling. Periode data 5 tahun, yakni dari 2014-2018. Metode analisis data yang digunakan adalah regresi data panel. Hasil penelitian menunjukan Kepemilikan Asing Total dan Kepemilikan Institusi Asing berpengaruh positif dan masih signifikan pada tingkat < 15% terhadap Nilai Perusahaan. Sementara Kepemilikan Perusahaan Asing memiliki pangaruh positif tetapi tidak signifikan terhadap Nilai Perusahaan. Ukuran Perusahaan, Umur Perusahaan, dan dummy direksi tidak berpengaruh terhadap Nilai Perusahaan.