bluuebunny/crossref_metadata_2025 huggingface dataset:
Roles of Secreted Phospholipases A2 in the Mammalian Immune System
Authors: Krizaj Igor
Published: July 2021

Secreted phospholipase A2 (sPLA2) molecules constitute a family of proteins that are involved functionally in many biological processes. In particular, they participate in diverse pathophysiological settings as enzymes that release free fatty acids and lysophospholipids from phospholipids in biological membranes, or as ligands for various cellular receptors. In this review the confirmed or expected functions of sPLA2s in the mammalian immune system are surveyed. Some of the twelve mammalian sPLA2 molecules constitute part of the so-called innate immune system by virtue of their antibacterial, antiviral and antifungal activities. They are also involved in acute inflammation, a protective reaction of the body to infection or injury. The acute inflammation sometimes escapes regulation, becomes chronic and can evolve into a severe pathology. One or more types of sPLA2 are involved in asthma, rheumatoid arthritis, sepsis, atherosclerosis, myocardial infarction, Crohn’s disease, ulcerative colitis and cancer. sPLA2s are thus important therapeutic targets as well as biotherapeutic molecules. Improving the selectivity of inhibitors of sPLA2s to be able to target a particular sPLA2 could therefore be one of the most important tasks for future research.
C-methylation of Organic Substrates: A Comprehensive Overview; Methanol
as a Methylating Agent: A Case of Catalysis Versatility (Part III)#
Authors: Moulay Saad
Published: July 2021

The present account surveys the results of a myriad of works on the C-methylation of organic
substrates with methanol as an eco-friendly methylating agent. The innumerable reports on this
issue reveal the widespread use of a set of solid catalysts such as molecular sieves, zeolites, metal
phosphates, metal oxides and transition metal complexes to accomplish such methylation. One related
facet was the impact of the numbers of Brønstëd acid sites, Lewis acid sites, and Lewis base sites
present in solid catalysts, such as zeolites, their ratios, and strengths that affect the distribution of the
methylation products and their selectivities. Moreover, specific surface area and porosity of some
solid catalysts, such as zeolites, play additional roles in the overall reaction. Not only do these catalyst
properties influence the methylation outcome, the temperature, space velocity (WHSV, LHSV,
GSHV), weight of catalyst per reactant flow rate (W/F), time of stream (TOS), and methanol/
substrate molar ratio also do. The treated substrates herein discussed were aromatic hydrocarbons
(benzene, biphenyls, naphthalenes, toluene, xylenes), alkenes, phenolics (phenol, cresols, anisole), Nheteroarenes,
carbonyls, alcohols, and nitriles. Methylation of benzene affords not only toluene as the
main product but also polymethylated benzenes (xylenes, pseudocumene, hexamethylenebenzene,
and also ethylbenzene as a side-chain product). Furthermore, toluene is sensitive to the reaction conditions,
giving rise to ring methylation and to side-chain one (ethylbenzene and styrene), besides the
formation of benzene as a disproportionation product. A number of results from the methylation of
phenolic compounds bear witness to the interest of different investigators in this special research.
With respect to these phenolics, concurrent O-methylation inevitably parallels the C-methylation,
and the selectivity of the latter one remains dependent on the above-cited factors; ortho-cresol and
2,6-xylenol have been the main C-ring methylated phenols. Methylation of olefins with methanol
over solid catalysts, leading to higher olefins, is of great interest. The chemistry involved in the
methylation of N-heteroarenes, such as pyridines, indoles, and pyrroles, is significant. Application of
the methylation protocols, using methanol as a reagent and transition of metal complexes as catalysts
to ketones, esters, aldehydes, nitriles, and alcohols, ends up with some important molecules, such as
acrylonitrile (a monomer) and isobutanol (a biofuel).
Using Social Media for Peer-to-Peer Cancer Support: Interviews With Young Adults With Cancer
Authors: Lazard Allison J , Collins Meredith K Reffner , Hedrick Ashley , Varma Tushar , Love Brad , Valle Carmina G , Brooks Erik , Benedict Catherine
Published: July 2021

Background

Web-based social support can address social isolation and unmet support needs among young adults with cancer (aged 18-39 years). Given that 94% of young adults own and use smartphones, social media can offer personalized, accessible social support among peers with cancer.

Objective

This study aims to examine the specific benefits, downsides, and topics of social support via social media among young adults with cancer.

Methods

We conducted semistructured interviews with young adults with cancer, aged between 18 and 39 years, who were receiving treatment or had completed treatment for cancer.

Results

Most participants (N=45) used general audience platforms (eg, Facebook groups), and some cancer-specific social media (eg, Caring Bridge), to discuss relevant lived experiences for medical information (managing side effects and treatment uncertainty) and navigating life with cancer (parenting and financial issues). Participants valued socializing with other young adults with cancer, making connections outside their personal networks, and being able to validate their emotional and mental health experiences without time and physical constraints. However, using social media for peer support can be an emotional burden, especially when others post disheartening or harassing content, and can heighten privacy concerns, especially when navigating cancer-related stigma.

Conclusions

Social media allows young adults to connect with peers to share and feel validated about their treatment and life concerns. However, barriers exist for receiving support from social media; these could be reduced through content moderation and developing more customizable, potentially cancer-specific social media apps and platforms to enhance one’s ability to find peers and manage groups.
A Novel Digital Pill System for Medication Adherence Measurement and Reporting: Usability Validation Study
Authors: Baumgartner Susan L , Buffkin Jr D Eric , Rukavina Elise , Jones Jason , Weiler Elizabeth , Carnes Tony C
Published: July 2021

Background

Medication nonadherence is a costly problem that is common in clinical use and clinical trials alike, with significant adverse consequences. Digital pill systems have proved to be effective and safe solutions to the challenges of nonadherence, with documented success in improving adherence and health outcomes.

Objective

The aim of this human factors validation study is to evaluate a novel digital pill system, the ID-Cap System from etectRx, for usability among patient users in a simulated real-world use environment.

Methods

A total of 17 patients with diverse backgrounds who regularly take oral prescription medications were recruited. After training and a period of training decay, the participants were asked to complete 12 patient-use scenarios during which errors or difficulties were logged. The participants were also interviewed about their experiences with the ID-Cap System.

Results

The participants ranged in age from 27 to 74 years (mean 51 years, SD 13.8 years), and they were heterogeneous in other demographic factors as well, such as education level, handedness, and sex. In this human factors validation study, the patient users completed 97.5% (196/201) of the total use scenarios successfully; 75.1% (151/201) were completed without any failures or errors. The participants found the ID-Cap System easy to use, and they were able to accurately and proficiently record ingestion events using the device.

Conclusions

The participants demonstrated the ability to safely and effectively use the ID-Cap System for its intended use. The ID-Cap System has great potential as a useful tool for encouraging medication adherence and can be easily implemented by patient users.
Morocco's National Response to the COVID-19 Pandemic: Public Health Challenges and Lessons Learned (Preprint)
Authors: Barkia Abdelaziz , Laamrani Hammou , Belalia Abdelmounaim , Benmamoun Abderrahman , Khader Yousef
Published: July 2021

UNSTRUCTURED

This report aimed to provide an overview of the epidemiological situation of COVID-19 in Morocco and to review the actions carried out as part of the national response to this pandemic. The methodology adopted was based on literature review, interviews with officials and actors in the field, and remote discussion workshops with a multidisciplinary and multisectoral working group. Morocco took advantage of the capacities already strengthened within the framework of the application of the provisions of the International Health Regulations (IHR) of 2005. A SWOT analysis made it possible to note that an unprecedented political commitment enabled all the necessary means to face the pandemic and carry out all the response activities, including a campaign of relentless communication. Nevertheless, and despite the efforts made, the shortage of human resources, especially those qualified in intensive care and resuscitation, has been the main drawback to be addressed. The main lesson learned is a need to further strengthen national capacities to prepare for and respond to possible public health emergencies and to embark on a process overhaul of the health system, including research into innovative tools to ensure the continuity of the various disease prevention and control activities. In addition, response to a health crisis is not only the responsibility of the health sector but also intersectoral collaboration is needed to guarantee an optimal coordinated fight. Community-oriented approaches in public health have to be strengthened through more participation and involvement of nongovernmental organizations (NGOs) and civil society in operational and strategic planning.
POROUS PLASTIC MATRIX TABLETS OF LEVETIRACETAM FOR ZERO-ORDER CONTROLLED RELEASE: DEVELOPMENT AND FORMULATION OPTIMIZATION
Authors: PARIMI RAVI , VADAPALLI RAMA RAO , PRAVALLIKA K. E.
Published: July 2021

Objective: The prior objective of the current research work was to develop once-daily levetiracetam extended/controlled-release tablets having zero-order release kinetics with the plastic matrix as the release retarding element. For a high water-soluble drug, the formulation of a dosage form so as to have an extended drug release has always been a difficult task.

Methods: In the current work, levetiracetam which is a highly soluble drug was taken as the model drug for which extended-release matrix tablets were developed using varied plastic polymers like Polyvinyl acetate (PVAc), Polyvinyl chloride (PVC), Eudragit RSPO and Eudragit RLPO. PVP was considered as a pore-forming agent and PEG 6000 was taken as a water regulating agent. The porous plastic matrix tablets were prepared by embedding the drug in solvent-activated polymer dispersion followed by drying, sieving, mixing with other excipients and finally compressed. Including physical characterization studies and drug release studies, the tablets were subjected to SEM studies before and after the dissolution studies to analyze the effect of the pore former.

Results: Pre-compression mixtures exhibited good packageability of 81-92% and hence the compressed tablets were strong enough with good tensile strength in the range of 0.78–0.90 N/mm2. Drug release study results showed that the drug release was controlled for a period of 12–24h. PVAc had shown better controlled-release among all the plastic polymers taken. PEG 6000 in combination with PVP produced the desired zero-order drug release.

Conclusion: The levetiracetam porous plastic matrix tablets were developed with zero-order drug release that was effectively controlled for 24hr.
HPLC ANALYSIS OF AMINO ACIDS CONTENT IN CRAMBE CORDIFOLIA AND CRAMBE KOKTEBELICA LEAVES
Authors: SLOBODIANIUK LIUDMYLA , BUDNIAK LILIIA , MARCHYSHYN SVITLANA , SKRYNCHUK OLHA , KUDRIA VICTORIIA
Published: July 2021

Objective: The aim of our study was to establish the content of some primary metabolites, such as amino acids in Crambe cordifolia and Crambe koktebelica. The lack of experimental data induced us to determine these compounds.

Methods: Crambe cordifolia and Crambe koktebelica leaves were selected as the objects of the study. The amino acids in the raw materials were determined by the HPLC method.

Results: The results of the research revealed that the leaves of Crambe cordifolia and Crambe koktebelica contain fifteen and sixteen free amino acids respectively. Among the free amino acids L-histidine was presented in Crambe cordifolia leaves in the greatest amount, its content was 12.19 µg/mg. The content of free L-arginine, L-valine, L-phenylalanine, L-isoleucine was the greatest in Crambe koktebelica leaves, it was 2.23 µg/mg, 2.04 µg/mg, 1.74 µg/mg, 1.50 µg/mg respectively. The content of bound L-glutamic acid, Glycine, L-arginine, L-leucine was the highest in Crambe cordifolia and Crambe koktebelica leaves.

Conclusion: The results of the study showed that Crambe cordifolia and Crambe koktebelica can be considered as a source of highly digestible amino acids that can be used to treat some diseases.
FORMULATION DEVELOPMENT AND EVALUATION OF CHRONOMODULATED DRUG DELIVERY SYSTEM BY ZAFIRLUKAST
Authors: KRISHNA N. SHIVA , JAYANTHI B. , MADHUKAR A.
Published: July 2021

Objective: The main objective of the present study was to formulate and evaluate a time-controlled single-unit oral pulsatile drug delivery system containing Zafirlukast for the prevention of nocturnal asthma attacks. To provide time-scheduled drug release for Asthma disease. It is used for preventing asthmatic attacks at early morning. Pulsatile release dosage form is increasing patient compliance by reducing the dosing frequency, especially in the early morning.

Methods: Core tablets were prepared by incorporating different concentrations of natural and synthetic super disintegrants. Drug-containing core tablets (ZC1-ZC15) with different compositions of natural super disintegrants (Plantago ovata seed powder, Locust bean gum) synthetic super disintegrants (Sodium starch glycolate (SSG), Cross carmellose sodium (CCS), Crospovidone (CP)) were prepared by direct compression technique. The core tablets were subjected to pre-formulation, physicochemical and In vitro drug release studies. The fast disintegrating core tablet formulation was selected and press-coated tablets (P1-P11) were prepared with different compositions of hydrophobic polymers Eudragit RS100, Eudragit RL 100, Ethylcellulose and hydrophilic polymers Hydroxypropyl methylcellulose K4M, K100M. The optimized formulation was selected and quantified based on in vitro drug release profile in simulated gastric and intestinal fluids.

Results: The pre and post-compression parameters of tablets were also found to be within limits. Formulation ZC5 with 16 mg of Locust bean gum showed the least disintegrating time, i.e., 22.13 sec, and was selected as the best immediate release core tablet. The press-coated tablet formulation P8 having 62.5 mg Eudragit RS100 and 62.5 mg of HPMC K4M in ratio 1:1 over the core tablet ZC5 showed rapid and drug release nearly after 4 h lag time and 98.86 % up to 12 h. Accelerated stability studies of the optimized formulation P8 indicated no significant difference in release profile after 3 mo.

Conclusion: The in vitro dissolution study showed that lag time before drug release was highly affected by the coating amount level and nature of coating polymer used. Time-controlled pulsatile release tablets can be prepared using press-coating techniques.
Leveraging Existing Technology: Developing a Trusted Digital Repository for the U.S. Geological Survey
Authors: Hutchison Vivian B. , Norkin Tamar , Langseth Madison L. , Ignizio Drew A. , Zolly Lisa S. , McClees-Funinan Ricardo , Liford Amanda
Published: July 2021

As Federal Government agencies in the United States pivot to increase access to scientific data (Sheehan, 2016), the U.S. Geological Survey (USGS) has made substantial progress (Kriesberg et al., 2017). USGS authors are required to make federally funded data publicly available in an approved data repository (USGS, 2016b). This type of public data product, known as a USGS data release, serves as a method for publishing reviewed and approved data. In this paper, we present major milestones in the approach the USGS took to transition an existing technology platform to a Trusted Digital Repository. We describe both the technical and the non-technical actions that contributed to a successful outcome.We highlight how initial workflows revealed patterns that were later automated, and the ways in which assessments and user feedback influenced design and implementation. The paper concludes with lessons learned, such as the importance of a community of practice, application programming interface (API)-driven technologies, iterative development, and user-centered design. This paper is intended to offer a potential roadmap for organizations pursuing similar goals.
To Do List Web App
Authors: Yadav Sumit Kumar
Published: July 2021

“TO DO LIST is a web application in the classification of Task Management, Project Management, Productivity, Scheduling, and Collaboration. We have a huge assortment of devices to assist us with monitoring day by day commitments. A basic rundown on paper of things "To Do" is sufficient for certain individuals. Others like to utilize programs. Individuals have inclinations about where they monitor errands - with PC utility programming ("thick application"), sites ("meager application"), on telephone ("portable") applications. Some product is extremely broad, with just a basic rundown of assignment names and due dates. Some get more refined with settled errands, where you have to finish the settled undertakings to consider the fundamental assignment complete. Some straightforward records or to oversee complex multi-client ventures. What separates To Do List from most other undertaking the board bundles is the choice to make chains of command of assignments to separate complex errands in to dynamically more basic subtasks until no further disentanglement is required. This application will join the usability with the most effective functionalities that can enable a client to deal with their undertaking and monitor their necessities in the most beneficial manner.”
A Review on Indoor Positioning Technologies and its Principles
Authors: C Pradyumna
Published: July 2021

This paper aims to provide the reader with a review of the main technologies present in the literature to solve the indoor localization problem that is indoor positioning without GPS. Location detection has been implemented very successfully in outdoor environments using GPS technology. GPS has had a great impact on our daily lives by supporting a large number of applications. However, in indoor environments, the availability of GPS or equivalent satellite-based positioning systems is limited due to the lack of line of sight and attenuation of the GPS signal when they pass through walls. The goal of this paper is to provide a technical perspective on indoor positioning systems, including a wide range of technologies and methods.
Extricating Brain Tumor in MRI Images with the aid of MATLAB software
Authors: Mittal Shivam Kumar
Published: July 2021

In the current era of Medical Science, Image Processing is the most evolving and inspiring technique. This technique consolidates some noise removal functions, segmentation, and morphological activities which are the fundamental ideas of image processing. Initially preprocessing of an MRI image is done to ensure the image quality for further processing/output. Our paper portrays the methodology to extricate and diagnose the brain tumor with the help of an affected person’s MRI scan pictures of the brain. MRI pictures are taken into account to recognize and extricate the tumor from the brain with the aid of MATLAB software.
Analysis of Neuromorphic Computing Systems and its Applications in Machine Learning
Authors: Bhat Pranava
Published: July 2021

The domain of engineering has always taken inspiration from the biological world. Understanding the functionalities of the human brain is one of the key areas of interest over time and has caused many advancements in the field of computing systems. The computational capability per unit power per unit volume of the human brain exceeds the current best supercomputers. Mimicking the physics of computations used by the nervous system and the brain can bring a paradigm shift to the computing systems. The concept of bridging computing and neural systems can be termed as neuromorphic computing and it is bringing revolutionary changes in the computing hardware. Neuromorphic computing systems have seen swift progress in the past decades. Many organizations have introduced a variety of designs, implementation methodologies and prototype chips. This paper discusses the parameters that are considered in the advanced neuromorphic computing systems and the tradeoffs between them. There have been attempts made to make computer models of neurons. Advancements in the hardware implementation are fuelling the applications in the field of machine learning. This paper presents the applications of these modern computing systems in Machine Learning.
Voice based E-Notice Board using Android
Authors: Gulhane Dr. S. M.
Published: July 2021

For a long time notice board are a source of displaying important news and messages in educational facilities, hospitals, offices and public places etc. However, the drawback of these notice board was the manual effort was required to erase or take down the old messages in order to put up new ones. Therefore, new technologies where interested based on automatic systems to reduce the efforts and make notice board. We implement automatic e-notice board on wireless standard technology ln our project. We design the system using Arduino. Our e-notice board is totally voice operated. Voice based notice board based on android system is most helpful in various organisation. where emergency announcement can be displayed instantly just by speaking out the entire messages. Emergencies apart, this system has provided to be very user friendly. It also eliminates the option of printing out notice and saving tons of paper which initially used to display information. Another advantage is that messages are disclosed in a matter of seconds once typed without any delay in their transmission. As long as an appropriate networks coverage is maintained. Message can be sent to any area in the world. Morden times brings with modern digital advertisement system too. This means that sophisticated shopping centre and malls etc.
Enhancing the Detection of Metamorphic Malware using Deep Learning
Authors: S B Chandini
Published: July 2021

Malware is the name for a malicious variants. Malware models conatins code generated by cyberattackers, plan to cause distrupt to data and systems or to gain unauthorized access to a network. Malware have been enormously increasing in now a days. Majority of malware utilize obfuscation methods for avoidance and abstruse motive, but they conserve the purpose and malicious behaviour of native Rey. Attackers uses metamorphic techniques to build viruses that change their internal construction all bug. Malware signatures and behaviour samples acquire static and dynamic analysis that are ineffectual in recognising undetermine malwares.In general,these metamorphic viruses are very hard to detect. In this paper, we suggest HMM as a novel solution for metamorphic detection.
VIRO Attack (Covid-19 Syndrome Mapping and Self-Assessment)
Authors: BR Priyanka
Published: July 2021

The new COVID-19 is caused by the virus SARS-CoV-2. The most likely ecological reservoirs for SARS-CoV-2 are bats, but it is believed that the virus jumped the species barrier to humans from another intermediate animal host. This intermediate animal host could be a domestic food animal, a wild animal, or a domesticated wild animal which has not yet been identified. WHO continues to collaborate with experts, Member States and other partners to identify gaps and research priorities for the control of COVID-19, and provide advice to countries and individuals on prevention measures. National food safety authorities have been following this event with the International Food Safety Authorities Network (INFOSAN) Secretariat to seek more information on the potential for persistence of the virus on foods traded internationally and the potential role of food in the transmission of the virus. Experiences from previous outbreaks of related coronaviruses, such as the Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) show that transmission through food consumption did not occur. To date, there have not been any reports of transmission of SARS-CoV-2 virus through food. However, concerns were expressed about the potential for these viruses to persist on raw foods of animal origin.
Experimental Study on Recycling of Bituminous Aggregate in Cement Concrete
Authors: Mishra Manoj Kumar
Published: July 2021

Recycling of bituminous aggregates in cement concrete has been selected for the present study to determine suitability of recycled material in road construction. This will help in achieving economy in road construction as well as saving on environment degradation in term of reduced mining and less pollution. Construction and maintenance of roads and highways involve millions of tonnes of aggregate. Considering the scarcity of fresh aggregate, replacement of part of the fresh aggregate with recycled aggregate is considered in the present study. Construction of the road is quite cost intensive. Material alone cost more than 60% of the total construction cost, out of which aggregate cost component, is approximately 30%. We can use recycled aggregate in place of fresh aggregate in construction of road and provide economy to the project. For making best use of recycled aggregates, it is essential to study the suitability of the same in various pavement components. In the present study recycled aggregate are used in Granular Sub Base (GSB) and Wet Mix Macadam (WMM).
Modeling and Predicting Cyber Hacking Breaches
Authors: Swetha Pelleti
Published: July 2021

Analyzing cyber incident information units is an essential approach for deepening our expertise in the evolution of the chance situation. This is an especially new study topic, and lots of research continue to be done. In this paper, we record a statistical evaluation of a breach incident records set similar to 12 years (2005–2017) of cyber hacking sports that encompass malware attacks. We display that, an evaluation of the findings stated withinside the literature, each hacking breach incident inter-arrival instances and breach sizes must be modeled through stochastic processes, instead of through distributions due to the fact they show off autocorrelations. Then, we recommend specific stochastic procedure fashions to, respectively, shape the inter-arrival instances and the breach sizes. We additionally display that those fashions can expect the inter-arrival instances and the breach sizes. In order to get deeper insights into the evolution of hacking breach incidents, we behaviour each qualitative and quantitative fashion analysis at the records set. We draw a fixed of cyber safety insights, together with that the chance of cyber hacks is certainly getting worse in phrases in their frequency, however now no longer in phrases of the value in their damage.
Carrier based PD and POD PWM Technique for MLI
Authors: Teja B. Ravi
Published: July 2021

This paper presents the design of gate drive circuit for controlling of multilevel inverter (MLI) with Phase Disposition (PD), Phase Opposition Disposition (POD) pulse width modulation (PWM) switching control technique.
Design and Development of Project Set Up for Gas Cutter for Straight Line Cutting
Authors: Patil Nikhil Bhagwan
Published: July 2021

The Gas Profile cutting machine is one of the essential machine tool in the workshop, in this study it has seen that when the high temperature burning flame is in contact with the material particle, the material particle melts and the inter-molecular bonding gets break off to separate the material from each other. In this paper the design of various parts required in gas cutting machine is determined & calculations are interpreted. In this project we have tried to develop a low cost and simple mechanized arrangement for plasma coating on textile rollers.
Image Captioning using Deep Learning for the Visually Impaired
Authors: Chandrashekhar Dr. A. M.
Published: July 2021

Describing the content of an image has been a fundamental problem of Machine learning that connects computer vision and natural language processing. In recent years, the task of object recognition has advanced at an exceptional rate which in turn has made image captioning that much better and easier. In this paper, we have discussed the usage of image captioning using deep learning for the visually impaired. We have used Convolutional Neural Networks along with Long Short-Term Memory to train and generate captions for images along with a text-to-speech engine which makes the experience of visually impaired users who are browsing the internet much smoother. We discuss how the model was implemented, its different components and modules along with a result analysis conducted on a set of outputs peer reviewed by our colleagues, friends and professors.
Profit Maximization for Cloud Broker in Cloud Computing
Authors: Namose Prof. M. S.
Published: July 2021

As cloud computing evolves, more and more applications are moving to the cloud. Cloud brokers are are like Middlemen between cloud service providers and cloud users. Thus, cloud brokers can significantly reduce the cost of consumers. In addition to reducing the cost per user, the cloud broker can also accommodate the price difference between on-demand virtual machines and dedicated virtual machines. The problem with the current system is that if many customers request a large amount of cloud services at once, the cloud service broker cannot purchase enough cloud services from CSP to meet the needs of all customers. Then there is a peak demand problem where the customer cannot complete the job. As a result, dynamic conditions not only lead to financial problems, but can also negatively impact the customer experience. To solve this problem, the system focuses on guaranteed quality of service for all requests, reduces waste of resources, increases security and maximizes revenue. All jobs are scheduled by the job scheduler and assigned to different VMs in a centralized way. Many factors such as market demand, application volume, SLA, service rental cost, etc. are taken into account to formulate an optimal configuration problem of profit maximization.
An Exploratory Data Analysis of Covid-19 Outbreak Situation in India
Authors: Verma Arpit
Published: July 2021

The number of COVID-19 cases in India is increasing expeditiously. The National and native authorities are having a tough time to make a pattern, analyze and forecast the spread of COVID-19 in India. The main focus of this paper is to draw a statistical model for better understanding of COVID-19 spread in India by thoroughly studying the reported cases in the country till 14 March 2020. An Exploratory Data Analysis (EDA) technique is being implemented to review and analyze the reported COVID-19 cases in India. The results of the analysis divulge the impact of COVID-19 in India on daily and weekly manner, analysis of different states of India, analogize India with abutting countries also like the countries who are badly affected.
How Digital Marketing along with Artificial Intelligence is Transforming Consumer Behaviour?
Authors: Khatri Dr. Manas
Published: July 2021

This report highlights the role of AI in digital marketing to change consumer behaviour. It relates the technical aspects of modern technology with digital marketing and their use considering the changes in trends and consumer preferences based on new products and market analysis. Artificial Intelligence is a technology that makes the computers or machines as smart as human being so that they are capable of doing tasks like a human brain. As in this era of technology AI continuous to advance, it is used in almost every field of life. It is combined with digital marketing to make it easier for firms to reach the right customers at the right time. Artificial Intelligence helps the firms to get perception about the customer needs in a very short frame and effectively which boosts their sales and revenues. Some techniques that are used in digital marketing utilizing AI include Big Data analysis, machine learning and customer insights of the specific sector. India has 280 Million facebook users that makes it the top country having the biggest Facebook audience, Inida is second highest based on Instagram audience. The smartphone industry in India is among the develping markets which are adding to the number of middle-income customers and it is estimated that it will reach millions of the cinsumers in future. These analysitics have changed the way marketers make digital marketing strategies and desgin business portfolio in accordance with the products and services available in the market. This report also explain the challenges of ai in digital marketing. Furthermore, it identifies the relevant tools and technologies which help marketer effectively implement the AI in digital marketing.
COVID Safety Measures Alert System
Authors: Devi D. Gayatri
Published: July 2021

The corona virus COVID-19 pandemic is causing a global health crisis so the effective protection method is wearing a face mask and maintaining social distance in public areas according to the World Health Organization (WHO). The COVID-19 pandemic forced governments across the world to impose lockdowns to prevent virus transmissions. Reports Indicate that wearing facemasks and maintaining social distance while at work clearly reduces the risk of transmission. An efficient and economic approach of using AI to create a safe environment in a manufacturing setup. So we are doing a Project on detecting whether a person wears a mask or not, also giving an alert message to the person to wear a mask, and maintain social distance or not. A hybrid model using deep and classical machine learning for face mask detection will be presented for face mask detection, a face recognition model is used to identify faces and an object detection algorithm is used to identify persons and also calculate social distance between each other. We collected face mask detection dataset consisting of mask and without mask images, and person photos to identify the person. We are going to use OpenCV to do real-time face detection from a live stream via our webcam. We will use the dataset to build a COVID-19 face mask detector with computer vision using Python, OpenCV, and TensorFlow and Keras, use a face recognition module to identify faces and a YOLO algorithm to detect objects and calculate social distance. Our goal is to identify whether the person on a video stream is wearing a face mask or not, if not give an alert message to wear a mask and check for social distance between each other with the help of computer vision and deep learning.
Smart Digital Photo Frame Design
Authors: More Prof. Chetan S
Published: July 2021

A Digital Photo frame, also known as a digital media frame. It's a device that displays pictures digitally without the use of a computer or printer. Today’s Digital picture frames comes in a number of designs and sizes, as well as with a variety of extra capabilities. The advent of digital picture frames antecedent all computers commence the dawn of projecting memories digitally. Digital photo frames were originally designed to showcase stationary, slide show of images digitally hence they give a professional look to display images in a frame and due to simplicity in the design, it can be used continuously. You can even run a video containing multiple images with a short display time frame.
Experimental Analysis of Refrigeration Ejector System by using Different Organic Refrigerants
Authors: Wakchaure P. V.
Published: July 2021

This paper presents the experimental analysis performed on ejectors to optimize operating conditions like evaporator temperature, condenser temperature and generator temperature. Using the environmentally friendly working fluid R134a, R152a, R600a, R717 (Ammonia). Parametric analysis was performed to review the effect of blending chamber geometry on ejector performance which has direct impact on coefficient of performance of ejector refrigeration cycles. Results show that operating conditions and thus the effect of the deflection of the primary flow on the secondary flow is set. CFD simulations was performed to identify optimum geometry and optimum operating condition
Fault Diagnosis of Horizontal Axis Turbine with Different Twist Angle to Reduce Stress under Failure Thrust Force
Authors: Suryawanshi Aayushi
Published: July 2021

Five types of configurations of tidal turbine blade including validation model have been considered with different profile tidal turbine blade with twist angle of 9, 10, 10.5, 11, 11.5 and 12 degrees. An optimized model of tidal turbine blades is developed. The simulation of the optimized model i.e. 12 degree twist angle gives minimum value of stress and deformation at different loads i.e. 441, 271, 272 and 610N which has optimized and converged result compared to respected models of tidal turbine blade, it has also been observed that stress and deformation was reduced at static load of 610N in 12 degree twist angle tidal turbine blade with the Zylon, Kevlar and CFRP material, thus the observed fault is diagnosed in this present research work. The configuration of optimized model gives maximum convergence on all parameters amongst all the configurations used.
Twitter Sentiment Analysis Model
Authors: Dubey Pushkar
Published: July 2021

Social networks are the main resources to gather information about people’s opinion towards different topics as they spend hours daily on social media and share their opinion. Twitter is one of the social media that is gaining popularity. Twitter offers organizations a fast and effective way to analyze customers’ perspectives toward the critical to success in the market place. Developing a program for sentiment analysis is an approach to be used to computationally measure customers’ perceptions. .We use natural language processing and machine learning concepts to create a model for analysis . In this paper we are discussing how we can create a model for analysis of twittes which is trained by various nlp , machine learning and Deep learning Approach.
Image Security using Steganography and Cryptography
Authors: . Kavia
Published: July 2021

Cryptography and Steganography could be used to provide data security, each of them has a problem. Cryptography problem is that, the cipher text looks meaningless, so the attacker will interrupt the transmission or make more careful checks on the data from the sender to the receiver. Steganography problem is that once the presence of hidden information is revealed or even suspected, the message is become known . According to my proposed work in which both steganography and cryptography are combine and give good security for data. Firstly, the encrypted images has been hidden using image steganography method. Secondly, the Hash function algorithm has been modified and used to encrypt the stego image by using 128 digit hexa-key. Therefore, two levels of security have been provided using the proposed technique. In addition, the proposed technique provides high embedding capacity and better quality stego images.
Need of Transit-Oriented Development for Raigarh City
Authors: Pradhan Ashish
Published: July 2021

Raigarh city is an expeditious growing industry as well as the populated city in Chhattisgarh (INDIA), spread over an area of 7086 Km2. Raigarh city is classified by its rising Population, Urbanization, Motorization, Pollution, and low per capita income. The rapid rate of Industrialization and Urbanization in the past few decades has led to unprecedented growth in the city population and subsequently in the city limits. A lack of proper planning and land use controls has resulted in fast extending beyond city areas. The objective of the paper is to understand the growth patterns of Raigarh City and the existing transportation networks to plan and phase out a proper TOD network by understanding the present scenario of the traffic condition of the city and identify the parameters necessary for the implementation of TOD at Raigarh City. The proposal of the state government in setting up Naya Raigarh involves the transformation of old Raigarh into a better-planned and laid-out city. Expansion and redevelopment of a city require proper research and planning in laying out the transportation network of the city to ensure equitable access of public transportation to all, bringing in the concept of Transit Oriented Development (TOD).
GIS Based Multicriteria Decision Analysis of Riverine Flooding: A Case Study of Maharashtra Deluge 2019
Authors: Bongale Prof. P. G.
Published: July 2021

Riverine flooding is frequent catastrophic event for Indian subcontinent and prevalent in western ghat region. The south-western monsoonal precipitation escalates the situation to detrimental level in the populous regions along the rivers. The previous studies suggest that the settlements in the vicinity of seasonal rivers are mostly affected during heavy precipitation due to unpredicted event and lack of preventive infrastructure along the bank. Such devastation can be reduced with detailed analysis of river basin and flood recurrence trends. Present study focuses on the flood frequency and settlement patterns in the Krishna River basin of Maharashtra state. The region has cotton soil (clay to loamy dark grey soil) cover, which encourages the agricultural practices. The agriculture being major occupation of the state engaged more than 64% population contributing largely in cotton and cereal production of the country. The discrete pattern of rainfall causes flooding at places, which not only distresses the settlement but also adversely affects the rate of soil erosion resulting elimination of the most fertile layer of surface. The study mainly emphases on the Shirindwad, Kurundwad, Rajapur villages of Shirol taluka of Kolhapur district, where Koyna, Warna, Panchaganga, Tarli, Urmodi, Dudhganga and Hiranyakeshi rivers of Krishna River basin overflowed decade’s water level in August 2019 flooding event. The event put an eternal scar to the inhabitants with pile of flood water over their cotton soil. The devastation of the event would be predicted if spatio-temporal analyses of rainfall and settlement pattern have been done. So, the present study aims to evaluate the impacts of future flooding by the analysis of rainfall pattern and demarcation of settlement clusters under threat. This can be done by scrutinizing ancillary data in GIS (geographical information system) environment with the help of temporal satellite data. The GIS-based multicriteria decision analysis can provide result as demarcation of potential flood risk zones and this can be resourceful for disaster management and town planning practices.
Implementation of XGBoost Ensemble Learning Model for Detecting Money Laundering
Authors: Ramprakash Abarna
Published: July 2021

Money laundering is the illegal process of concealing the origins of money obtained illegally by passing it through a complex sequence of banking transfers. Currently banks use rule based systems to identify the suspicious transactions which could be used for money laundering. However these systems generate a large number of false positives which leads the banks to spend a huge amount of money and time in investigating the false positives. Hence, in this paper, the monitoring of transactions is to be done using XGBoost machine learning algorithm in order to reduce the number of false positives and to increase the probability of identifying true positives.
Key Mental Health Challenges Faced by Covid-19 Warriors
Authors: Bhandari Divya Bharathi
Published: July 2021

The emergence of Covid-19 has led to a drastic change in the world. The purpose of the study is aimed to analyze the psychological problems faced by the Covid-19 warriors. The focus of the study is narrowed to understand the problems faced by doctors, nurses and police.
Implementation of Symmetrical and Unsymmetrical Fault in Power System Network Using Matlab
Authors: Bhardwaj Swapnil
Published: July 2021

The main goal of this study is to provide a MATLAB-based simulation model for three-phase symmetrical and unsymmetrical faults. This paper shows how to deal with MATLAB programming in which a transmission line model is created and various challenges are acted out using a toolbox. Fault analysis for many types of faults has been performed, and the resultant effects may be seen in simulation output such as voltage, current, and control, as well as the positive, negative, and zero grouping parts of voltage and current output as waveforms.
IoT Based Traffic Control System using Image Processing
Authors: Tyagi Mr. Sachin
Published: July 2021

In the current scenario we can see that the traffic jam has become a serious problem in rapidly growing cities (As per their population) of India by which there is increase in air pollution, Fuel consumption as well as vehicular density. So there is a requirement to find a new way for traffic controlling traffic system which will be managed through real time IoT based traffic control system using image processing. This is a smart traffic management system that is designed to control real time traffic system which consist of components of Raspberry Pi, Pi camera. Raspberry pi is the key component which is used to control all performance multitasking. By using cameras, we monitor different lanes constantly. Image processing is used to examine detection and counting no. of vehicles in different lanes. It increases the traffic efficiency and clearance. The signal light will be decided as per the no. of vehicle count using image processing.
Transcriptomics Analysis using Galaxy and other Online Servers for Rheumatoid Arthritis
Authors: Parmar Sourabh
Published: July 2021

Researchers use transcriptomics analyses for biological data mining, interpretation, and presentation. Galaxy-based tools are utilized to analyze various complex disease transcriptomic data to understand the pathogenesis of the disease, which are user-friendly. This work provides simple methods for differential expression analysis and analysis of these results in gene ontology and pathway enrichment tools like David, WebGestalt. This method is very effective in better analysis and understanding the transcriptomic data. Transcriptomics analysis has been made on rheumatoid arthritis sra data. Rheumatoid arthritis (RA) is a systemic autoimmune disease. T cells and autoantibodies mediate the pathogenesis. This article discusses the genes which are differentially expressed between the healthy (n=50) and diseased (n=51) and the functions of those genes in the pathogenesis of RA.
Car Rental System
Authors: Thakur Amey
Published: July 2021

Customers will be able to reserve their vehicles from anywhere in the world due to the Car Rental System. Consumers provide information to this application by filling in their personal information. When a consumer creates an account on the website, he or she can reserve a car. The proposed system is an online system that is fully integrated. It effectively and efficiently automates manual procedures. Customers are aided by this automated method, which allows them to fill in the specifics according to their needs. It contains information on the sort of car they want to hire as well as the location. The goal of this system is to create a website where customers can book their automobiles and request services from anywhere in the world. There are three phases to this car rental system mentioned in the introduction.