bluuebunny/crossref_metadata_2025 huggingface dataset:
A Compendium on the Application of Gender Equity Financing & Budgeting in Covid-19 Mitigation and Recovery Processes: Key Lessons for South Africa
Authors: Sikhosana Nqobile , Iruoma Nzewi Ogochukwu
Published: December 2021

The novel coronavirus has been declared a global pandemic that requires global emergency due to its impacts on the global economy and populations. This article delves into the extent to which public finance management responds to gendered implications that emanate from the COVID-19 contagion. The outbreak of diseases affects men and women differently, and in such pandemics, gender inequalities are more pronounced and efforts to reduce gender gaps are usually thwarted by financing and budgeting methods that are gender-neutral. From this standpoint, the article advances the notion that public expenditure initiatives taken to mitigate the impacts of COVID-19 must be implemented from a gender lens and that the position of heterogeneous groups in society is considered to subdue further inequalities. The article also seeks to contribute to knowledge on gender-responsive budgeting by moving beyond procedural clarifications to highlight it as a critical element that can be adopted to mitigate the impacts of COVID-19. Using discourse analysis, the study examines the extent to which gender-responsive public expenditure initiatives across the globe can be adopted in the South African context to respond to different needs of men and women amidst COVID-19. Evidence reveals that although the country set aside R500 billion to mitigate the impacts of the pandemic, there are still gaps to align the fiscal commitments to gender equity goals.
From Ethnic to National Cloth: The Diverse Nature of the Tshivenḓa Ṅwenda
Authors: Yvonne Ladzani Kanakana , Maitakhole Sengani Thomas
Published: December 2021

In times past, the Tshivenḓa traditional cloth called Ṅwenda was associated with backwardness, stupidity, and had the Vhavenḓa women undermined for being ‘too rural’. Consequently, many dumped their traditional attire for other clothes to march with the times. Recently, Ṅwenda has been drawing attention from both the Vhavenḓa men and women and other ethnic groups because of the uniqueness and beauty of its embroidery. This article aimed to investigate the reason(s) Ṅwenda recently gained prominence and appreciation among the Vhavenḓa and other ethnic groups. The article adopted the qualitative approach and the exploratory design to collect data on the diverse nature and function of Ṅwenda. Semi-structured interviews were conducted with sixteen purposively selected designers from six villages in Venḓa, including the Ṱhohoyanḓou Flea Market in the Limpopo Province and three townships in the Gauteng Province of South Africa. Two tailors of Miṅwenda were selected from each of the aforementioned villages and townships. Undergirded by the Appreciative and Naturalistic Inquiries, the study also relied on the Inductive Thematic Analysis method for data analysis. It was found that Ṅwenda is used for special occasions such as weddings, parties, graduation ceremonies, and other social gatherings. Ṅwenda was also used to cover chairs, tables, and to decorate gowns, cushions, lampshades, bags, bedspreads or duvet covers, among other things. The article recommends the consideration of the role and significance of Tshivenḓa traditional attires in the ongoing discourses on the consolidation and traditionalisation of African identity as well as women’s empowerment initiatives in the postcolonial context.
Considering an Intersectional Lens in Agriculture and Climate Change: A Systematic Literature Review
Authors: C. Garutsa Tendayi
Published: December 2021

BACKGROUND:Climate change has detrimental effects on agricultural productivity and rural livelihoods. Disasters such as droughts, wildfires, floods, changes in intensity and timing of temperatures often cause gendered differential impacts. Furthermore, gendered climate vulnerability increases its impacts over time, threatening rural livelihoods and global food security. Consequently, the most vulnerable sections of the society experience severe effects due to their lack of capacity and opportunities to respond to these clime shocks. PROBLEM:Available literature on climate change, agriculture and gender explore vulnerabilities in rural populations through binary gender lenses, whereby men and women are categorised distinctly in terms of needs, climate adaptation and agricultural practices. These studies utilise a narrow gender analysis. In so doing, indicators like age, household types, income and ethnicity are made analytically invisible. METHODS:This paper utilised a systematic review method. Literature from the 1991 to 2020 was utilised in a comprehensive literature review to show how the concept of gender in agriculture and climate change has evolved in the past three decades. A content thematic analysis was utilised to analyse the data. Results: Findings indicated that without considering social variances between and within genders, policy and programming lacks comprehensive insights in responding to differential climatic impacts. This leads to obscurity experienced in one-size-fits-all approaches taken to address the needs of all vulnerable members of society. RECOMMENDATIONS:This paper recommended that climate change programming and policy frameworks must be informed by comprehensive analysis aimed at developing suitable climate change adaptation strategies within and between genders.
An Image Encryption Technique Based on Logistic Sine Map and an Encrypted Image Retrieval Using DCT Frequency
Authors: Kanakaraju Rajana , Lakshmi V  , Amiripalli Shanmuk Srinivas , Potharaju Sai Prasad , Chandrasekhar R
Published: December 2021

In this digital era, most of the hospitals and medical labs are storing and sharing their medical data using third party cloud platforms for saving maintenance cost and storage and also to access data from anywhere. The cloud platform is not entirely a trusted party as the data is under the control of cloud service providers, which results in privacy leaks so that the data is to be encrypted while uploading into the cloud. The data can be used for diagnosis and analysis, for that the similar images to be retrieved as per the need of the doctor. In this paper, we propose an algorithm that uses discrete cosine transformation frequency and logistic sine map to encrypt an image, and the feature vector is computed on the encrypted image. The encrypted images are transferred to the cloud picture database, and feature vectors are uploaded to the feature database. Pearson’s Correlation Coefficient is calculated on the feature vector and is used as a measure to retrieve similar images. From the investigation outcomes, we can get an inference that this algorithm can resist against predictable attacks and geometric attacks with strong robustness.
A Comprehensive Survey on Aspect Based Word Embedding Models and Sentiment Analysis Classification Approaches
Authors: Agrawal Monika , Moparthi Nageswara Rao
Published: December 2021

Sentiment Analysis includes methods and techniques for businesses to understand and analyze customer reviews, feedback and opinion on a particular product or service. Sentiment Analysis uses Natural Language Processing (NLP) tools to analyze feelings or emotions, attitudes, opinions, thoughts, etc. behind the words. Sentiments such as positive, negative and neutral are associated with a particular product. Sentiment analysis is applicable in multi-domains such as customer feedback for a particular product, movie reviews, social and political comments. This survey basically focuses on different aspect-based word embedding models and aspect-based sentiment classification techniques, where the goal is to extract key features from the sentences and classify sentiment on entities at document level. Aspect Based Sentiment Analysis (ABSA) is a technique that concentrates not only the entire sentence but analyses key terms explicitly to predict the polarity as a whole. ABSA model accepts aspect categories and its corresponding aspect terms to generate sentiment corresponding to each aspect from the text corpus. This article provides a comprehensive survey on different word embedding models under CNN framework for aspect extraction and different machine learning techniques applicable for sentiment classification purpose.
An Automated Music Recommendation System Based on Listener Preferences
Authors: Jitendra Mukkamala. S.N.V. , Radhika Y.
Published: December 2021

Recommender systems play a vital role in e-commerce. It is a big source of a market that brings people from all over the world to a single place. It has become easy to access and reach the market while sitting anywhere. Recommender systems do a major role in the commerce mobility go smoothly easily as it is a software tool that helps in showing or recommending items based on user’s preferences by analyzing their taste. In this paper, we make a recommender system that would be specifically for music applications. Different people listen to different types of music, so we make note of their taste in music and suggest to them the next song based on their previous choice. This is achieved by using a popularity algorithm, classification, and collaborative filtering. Finally, we make a comparison of the built system for its effectiveness with different evaluation metrics.
The Study of Usage of Hyperledger Fabric in Agricultural Ecommerce
Authors: Ray Vivek , Singh Anmol , Singh Mayank , Singh Rishi , Palwe Shushila
Published: December 2021

With the advent of COVID-19, the ecommerce industry in India has seen an inflection point with rise in the demand across all the segments of the industry. Much ecommerce has been started to cater to the supply and demand mismatch in agricultural goods front. In these times, Blockchain is seen to create a trust bridge for all the stakeholder to transact through goods and supplies with minimal risks involved. But, to use this technology the technical, economical and a scalable approach to this technology is still a very prominent requirement for mass adoption. Permissionless Blockchain build on Proof of Work consensus protocol cannot be used due to their slow speed, low scalability, and high energy consumption for network functioning. This paper concludes with the possibility of using a Permissioned blockchain such as Hyperledger Fabric to not only solve the several underlying issues to facilitate efficiency in the Ecommerce architecture, with critical view on the mass adoption.
Conformance Checking Techniques of Process Mining: A Survey
Authors: Kumar Saini Ashok , Kamra Ruchi , Shrivastava Utpal
Published: December 2021

Conformance Checking (CC) techniques enable us to gives the deviation between modelled behavior and actual execution behavior. The majority of organizations have Process-Aware Information Systems for recording the insights of the system. They have the process model to show how the process will be executed. The key intention of Process Mining is to extracting facts from the event log and used them for analysis, ratification, improvement, and redesigning of a process. Researchers have proposed various CC techniques for specific applications and process models. This paper has a detailed study of key concepts and contributions of Process Mining. It also helps in achieving business goals. The current challenges and opportunities in Process Mining are also discussed. The survey is based on CC techniques proposed by researchers with key objectives like quality parameters, perspective, algorithm types, tools, and achievements.
Aero Engine Performance Monitoring Using Least Squares Regression and Spectral Clustering
Authors: Saxena Kunaal , Nene Manisha J
Published: December 2021

Threshold-based flight data recorder analysis techniques have been widely used across the aerospace industry for fault detection and accident prevention. These techniques can detect pre-programmed events but fail to capture unknown patterns in the dataset. This research proposes a machine learning (ML) algorithm to analyze and detect unusual aero engine performance of a turboshaft engine mounted on a single engine rotorcraft. The performance is first modelled from an FDR dataset consisting of hundred flights, using least squares regression (LSR). A technique to scale the model by adding flight data from subsequent flights is thereafter discussed. Spectral Clustering is used for testing and validating the hypothesis derived from the regression model, by employing synthetically generated FDR data for twenty-five flights.
Blockchain Technology: Rising Trend in Various Applications
Authors: Zalte S. S  , Patil P. N  , Deshmukh S. N  , Patil M. G  , Katkar P. S
Published: December 2021

In this tech world, size of block chain is exponentially growing in this covid pandemic year which was not predicted. This pandemic environment causes digital transformation drive in various areas, particularly via the utilization of block chain or distributed ledger technology. To enhance and accelerate business process in various organization and industry showed a growing interest to adopt this technology. This paper summarized various block chain applications which are widely used in number of sectors and also focus on some challenges becomes hurdle while adopting block chain technology.
EyePhone Technology: A Smart Wearable Device
Authors: Kharade K.G. , Kharade S.K. , R. Ghatage S. , Kumbhar V.S. , Nandana Ravishankar T. , Vengatesan K.
Published: December 2021

In the past few decades, wearable sensors and devices have evolved into central technologies that have significantly impacted next-generation healthcare solutions in the previous decade. It is an age of incredibly cut-throat competition, even the youth. This technology is Hand-free, eyephone-operated telephone technology. It measures where the user’s eyes are located on the phone’s display employing a camera attached to the device. The typical work the eye bones assigned to eye tracking, eye blinking, detecting, etc., by way of eye-tracking, users can take care of their email, calendar, phone, etc. The leading technologies in use are a Human-Computer Interface (HCI) and a Human Phone Interface (HPI). It helps those with disabilities greatly. The IT Index is an expanded form of HCI. The use of mobile devices like smartphones and tablets is on the rise, and, to some extent, it could displace the use of desktops and laptops. Human-computer interaction is interested in the interaction between people and the computer system and between software and applications. Our focus is on this revolutionary new type of technology called the eye-phone.
Systematic Study of Video Mining with Its Applications
Authors: Mendagudli Mallappa G. , Kharade K.G. , Nadana Ravishankar T. , Vengatesan K.
Published: December 2021

Effective methods for video indexing will be more valuable as digital video data continues to grow. It has been years since we’ve seen this level of new multimedia research. The content analysis aims to create high-level descriptions and annotations by treating language and facts as data. Data mining is a technique that seeks out previously unknown facts and patterns in large datasets. A video can include several different kinds of data, such as images, visuals, audio, text, and additional metadata. Thanks to its broad application in various disciplines, like security, education, medicine, research, sports, and entertainment, it is often used differently. Data mining aims to discover and articulate exciting patterns that are hidden in a lot of video footage. While video mining is still in its infancy, data mining is more mature. A considerable amount of research must be done to turn the mined video into usable content
Online Attendance Marking System Using Facial Recognition and Intranet Connectivity
Authors: Pant Vibhanshu , Sharma Deepak , Annapurani. K  , Sundar R.
Published: December 2021

Keeping up the attendance record with everyday exercises is a difficult task. The conventional method of marking staff attendance is by tapping their ID card and then using fingerprint scanner. But due to COVID-19 pandemic the attendance system of using fingerprint scanner is stalled and currently not in use. The following system depends on face recognition and intranet connectivity to keep up attendance record of facilities and staff. The paper discusses the attendance marking system that is passive (no direct contact with the scanner or sensor) and restricting the users within certain network. The main goal of this system is divided in two steps, in initial step face is snare from the front camera of the smart phone and it is then recognized in the picture and in the second step these distinguished appearances and features are contrasted with stored information in data set for confirmation.
Implementation of IoT in Agriculture
Authors: Mohamed Arafath Rajack B. , Subramanian N. , Arun Pragadesh N. , Suvanesh R. , Vignesh S.
Published: December 2021

In this modern world agriculture is one of the major booming sectors around the world. In India around 60 percent of GDP comes from agriculture sector alone. Also, around the world there are many technologies showing up in the field of agriculture. In this paper proposed a technology by means of which potential pest attack in the crops can be detected and the respective pesticide is also sprayed as well. Along with these there is a range of sensor employed in the field connected to the controller that will take the real time values from the field and can be displayed in the respective screen (monitor or mobile screen) by means of technology called IOT (Internet of Things). Raspberry-pi is used as the controller to perform IoT. system is linked with an application called “cain” Which allows us to display various values of sensors in the monitor or in mobile application.
Threat Model for Secure Health Care Data Using EMR, EHR and Health Monitoring Devices
Authors: Kamalaeswari Ra. , Ceronmani Sharmila V.
Published: December 2021

The main aim of this project is to propose a threat modeling framework that promotes the security of health care services. The threat model is used to analyze the cyber threats that makes the electronic health monitoring devices vulnerable to a cyber-attack. The model also helps in strengthening the security of the software-based web applications like EMR and EHR used in a health care organization. The information assets are identified and the threat agents are eliminated considering the software, web application and monitoring devices as attack surface. The major goal of this threat model is to analyze and establish the trust boundaries in the OpenEMR that render a secure data transmission. We use a STRIDE threat model and a DFD based approach using the OWASP threat modeling tool. The SIEM tools provide a continuous security methodology to document the process and result.
Fundus Image Classification Using Convolutional Neural Network
Authors: Savitha U. , Lahari Chandana Kodali , Cathrin Sagayam A. , Bhuvaneswari S.
Published: December 2021

Different eye disease has clinical use in defining of the actual status of eye, in the outcome of the medication and other alternatives in the curative phase. Mainly simplicity, clinical nature are the most important requirements for any classification system. In the existing they used different machine learning techniques to detect only single disease. Whereas deep learning system, which is named as Convolutional neural networks (CNNs) can show hierarchical representing of images between disease eye and normal eye pattern.
Firefighter Safety Using IoT
Authors: Jebakumari S Caroline , Aarthi K  , Darshan S  , Karan S
Published: December 2021

From ancient times, firefighter’s faces a high risk of burns which may sometimes lead to death, especially those who enter the burning building first and those who are holding the front end of the nozzle. In order to avoid this kind of risk, an enlightened physical admonition arrangement for firefighter was put forward. Corresponding controller is developed with low power consumption on the display screen terminator which could inspect numerous conflagration in the surroundings and the site where firefighter reside as substantially as their critical bodily data so that the admonition might be provided with a low transmitting error rate. Moreover, the suitable information processing computation is sorted out to assure the preciseness. Consequently, competent firefighter’s individual protection is augmented considerably with strong anti-interference. In addition to this, a buzzer will be there on the side of firefighter like alarm when parameters like temperature, blood pressure, heart rate becomes abnormal so that they might not take the risk considering their body conditions.
IoT Based Solar Panel Tracking System with Weather Monitoring System
Authors: Dinesh K. , Lakshmi Priya. A  , Preethi. T  , Sandhya. M  , Sangeetha. P
Published: December 2021

Solar power is the burgeoning method of continual energy. The assignment is designed and carried out the use of dual axis sun tracker system. In order to maximise power era from solar, it’s important to introduce sun ray monitoring systems into solar electricity production. A dual-axis tracker can boom power through monitoring solar rays from switching photovoltaic cells in various directions. These photovoltaic cells can rotate in all directions. The LDR (Light Dependent Resistor) have been used to feel the depth of mild at 30 degree every or at 180 degree general and ship the information to microcontroller. This assignment also can be used to experience rain drop, temperature and humidity using sensor and they may be displayed on LCD. We can save the Solar energy in battery.
Coronary Illness Prediction Using Random Forest Classifier
Authors: Rekha G  , Shanthini B  , Ranjith Kumar V
Published: December 2021

Heart diseases or Cardiovascular Diseases (CVDs) are the main cause of death on the planet throughout the most recent years and become the most dangerous disease in India and the entire world. The UCI repository is utilized to calculate the exactness of the AI calculations for foreseeing coronary illness, as k-nearest neighbor, decision tree, linear regression, and support vector machine. Different indications like chest pain, fasting of heartbeat, etc., are referenced. Large datasets, which are not available in medical and clinical research, are required in order to apply deep learning techniques. Surrogate data is generated from Cleveland dataset. The predicted results show that there is an improvement in classification accuracy. Heart disease is one of the most challenging diseases to diagnose as it is the most recognized killer in the present day. Utilizing AI algorithms, this paper gives anticipating coronary illness. Here, we will use the various machine learning algorithms such as Support Vector Machine, Random Forest, KNN, Naive Bayes, Decision Tree and LR.
Live Human Detection Robot in Earthquake Conditions
Authors: Kabilan R. , Lakshmi Narayanan K. , Venkatesh M. , Vikram Bhaskaran V. , Viswanathan G.K. , Yogesh Rajan S.G.
Published: December 2021

This report outlines a human searching device that takes the form of a robotic car and serves as a backup mechanism for saving lives in the event of a disaster. The temperature sensor, in general, detects the thermal image of the human body, and there has been extensive research into human searching with the gas and humidity sensor. In the intelligent robot device’s study, achieving accurate and reliable human detection and tracking is a difficult challenge. The architecture of human detection and tracking mechanisms over non-overlapping field of views is examined in this paper. To compensate for their respective flaws, a search method is proposed. The proposed method’s rate and accuracy of human detection was tested in an experimental setting. We may guide the robot’s movement by commanding it to move left, right, forward, or backward. We plan to equip the robot with sensors that will enable us to track and detect humans behind the wall.
Improving Security Using Modified S-Box for AES Cryptographic Primitives
Authors: Sudhakar S. , Akashwar A. , Ajay Someshwar M. , Dhaneshguru T. , Prem Kumar M.
Published: December 2021

The growing network traffic rate in wireless communication demands extended network capacity. Current crypto core methodologies are already reaching the maximum achievable network capacity limits. The combination of AES with other crypto cores and inventing new optimization models have emerged. In this paper, some of the prominent issues related to the existing AES core system, namely, lack of data rate, design complexity, reliability, and discriminative properties. In addition to that, this work also proposes a biometric key generation for AES core that constitutes simpler arithmetic such as substitution, modulo operation, and cyclic shifting for diffusion and confusion metrics which explore cipher transformation level. It is proved that in AES as compared to all other functions S-Box component directly influences the overall system performance both in terms of power consumption overhead, security measures, and path delay, etc.
Assertion Driven Modified Booth Encoding and Post Computation Model for Speed MAC Applications
Authors: Sivasaravanababu S. , Dineshkumar T.R. , Saravana Kumar G.
Published: December 2021

The Multiply-Accumulate Unit (MAC) is the core computational block in many DSP and wireless application but comes with more complicated architectures. Moreover the MAC block also decides the energy consumption and the performance of the overall design; due to its lies in the maximal path delay critical propagation. Developing high performance and energy optimized MAC core is essential to optimized DSP core. In this work, a high speed and low power signed booth radix enabled MAC Unit is proposed with highly configurable assertion driven modified booth algorithm (AD-MBE). The proposed booth core is based on core optimized booth radix-4 with hierarchical partial product accumulation design and associated path delay optimization and computational complexity reduction. Here all booth generated partial products are added as post summation adder network which consists of carry select adder (CSA) & carry look ahead (CLA) sequentially which narrow down the energy and computational complexity. Here increasing the operating frequency is achieved by accumulating encoding bits of each of the input operand into assertion unit before generating end results instead of going through the entire partial product accumulation. The FPGA implementation of the proposed signed asserted booth radix-4 based MAC shows significant complexity reduction with improved system performance as compared to the conventional booth unit and conventional array multiplier.
25 Meter Rifle Shooting Training Kit
Authors: Nikhitha Mavillapalli , Shobana D  , Anne Sylvia S  , Hemasree Batta , Priyadharshini P
Published: December 2021

The goal of this project is to obtain all of the details about the shotgun so that we can correct any mistakes made during practice. With so many undetectable errors made by operators at work, this device aids in locating and adjusting the timing of adjustments in accordance with their errors. This procedure is carried out by detecting deviations from the shooters while shooting from a distance. Following each session, all data is verified, and steps are taken to improve the shooters game and correct their mistakes. This device improves the quality of the archer while also assisting in the improvement of the game. It also appears to be a list of minor blunders that one may deal with. The arduino IDE, which does all mathematical and mathematical operations, is in charge of this device. The light attached to this device indicates the start and stop positions of the shooter, allowing the shooter to be trained to start and stop fire.
A Robot for Combat and Calamities with Encrypted WSN
Authors: Abiraj S , Eeswar Samhithan D , Sanjai Kumar B , Venkatesh Y
Published: December 2021

The needs of search and rescue teams in numerous ways reflect the requirements of the military. They both work in perilous situations, they need to discover ways to gather data while keeping personnel out of hurt, and they are both seeking out for individuals. So, this Robot Commands in manual mode using a Smartphone, Wireless cam for Real-time Broadcast, PIR and Metal detection sensors, GPS & GSM modules, ultrasonic sensor, Gas & Fire sensor, temperature and humidity sensor, Acid gun, RFID and Relay switch, In this wireless sensor networks (WSN) is an Encrypted Network and infrastructure-less wireless networks to Screening physical or natural conditions, such as vibrations, pressures,movement, or toxins and to agreeably transmit their information retrieved by using IOT Server.
Sports Ground Audience Health Monitoring System [For COVID-19] Using Smart Wireless Sensor Network
Authors: Dharshini V  , Aiswarya S  , Ashwin R  , Usha A
Published: December 2021

The recent spread of the COVID-19 has pushed us to a situation to reduce human contacts in crowded areas. The main objective of this work is to protect the audience from the spread of contagious and non-contagious diseases or infections by introducing automation in maintenance and management of sport stadiums. Taking some primary precautions such as social distancing, wearing masks, avoiding crowded areas, cleaning hands, and checking the temperature is very important. This work provides primary check-ups for the audience to pass through, to ensure that no symptomatic person is let inside the stadium. Social distancing is properly maintained using ultrasonic sensors placed inside the stadium, so that nobody sits over the sensor attached seats. To ensure the maintenance of audience data, tickets are being replaced with RFID tags and checking is done automatically through RFID readers. The information is stored and maintained automatically in the server through IoT.
Solar-Powered Improved Full Bridge Resonant Inverter for High-Frequency Industrial Applications
Authors: Sapra Upasana , Sakthivel Aiswarya , Shobana Macdalin X. , Siva Ranjini S.
Published: December 2021

Electrical energy consumption is alarmingly rising, but the availability of conventional sources is limited. To meet the increasing demand; the implementation of non-conventional sources is the need of the hour. Solar energy is the most sustainable alternative for power generation among non-conventional sources families. Resonant inverters are used in low-power high-frequency induction heating appliances. Full-bridge resonant inverters are most commonly used to convert solar received power into the suitable form required for high-frequency application device by providing maximum power to the load at resonant frequency The aim of the paper is to analyze the working of the resonant inverter by taking the input supply from the solar panel and converting the obtained dc input to ac input through the resonant inverter. This obtained output is supplied for the high-frequency industrial application which mainly includes Induction frequency heating Applications. Induction heating is one of the techniques used in casting foundry for the treatment of metals. It involves the heat treatment of the metals namely annealing, hardening tempering method. goes here.
Enhancement of Power Generation in Highway Using Wind Energy Conversion System Integrated with PV
Authors: Kiruba.K  , Deepika.D  , Jaitha.G  , Madhuja.S
Published: December 2021

The rising global population and economic growth, combined with rapid urbanization, will result in a significant increase in energy demand. To solve this problem in the coming years, the world will need significantly more resources, primarily cleanly produced electricity. On the other hand, electricity demand is rising at twice the rate of overall energy consumption, and is expected to more than double by 2040. So, in order to meet the energy demands, the proposed approach includes a concept of a new Vertical Axis Wind Turbine (VAWT) design that generates power from moving vehicles and further integrated with PV for increased power generation. Seasonal variations can be accommodated by the related hybrid scheme. Using a charge controller, the produced power can be stabilized to a 12V output. The generated energy can be stored in batteries or supplied to the grid, acting as an energy storage device for society. The power that has been stored can be used in the future or during non-windy seasons.
Demand Side Management for Commercial Area Using Teaching Learning Based Optimization
Authors: Narayane Dhanshri , Pandey Amarjeet S , Pardeshi D B , Rasal Renuka
Published: December 2021

In Smart Grid Demand side management (DSM) plays a crucial role which permits customers to form educated selections concerning their energy consumption. It allows the strength to companies lessen the height load call for and reshape the burden profile. Most of the present demand aspect management ways utilized in ancient energy management system is with specific techniques and algorithms. In addition, the present ways handle solely a restricted range of governable a lot of restricted varieties of loads. This paper covers a requirement aspect management strategy supported load shifting technique for demand aspect management of future sensible grids with an outsized range of devices of many sorts. The day-in advance load shifting technique is proposed and mathematically formulated as a minimization problem. Teaching Learning Based Optimization (TLBO) is an efficient optimization is proposed. Considering Smart Grid with commercial customer, Simulations has been carried out. The respective results emphasis that the considered demand side management strategy attains substantial savings, whereas suppresses the mark of load demand of the smart grid. The outcome is by improve in sustainability of the smart grid, in addition to reduced standard operational value and carbon emission levels. The proposed algorithms can be easily applied to various optimization problems.
ACR TI-RADS and ATA ultrasound classifications are helpful for the management of thyroid nodules located in the isthmus
Authors: Cao Jianhui , Huang Weiwei , Huang Pintong , Huang Yunlin
Published: December 2021

PURPOSE: To compare the application value of the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) and the American Thyroid Association (ATA) guidelines in the risk stratification of thyroid isthmic nodules. METHODS: A total of 315 patients with thyroid isthmic nodules (315 nodules) confirmed by surgical pathology or fine-needle aspiration biopsy (FNAB) were selected in this retrospective study. The nodules were evaluated and classified according to ACR TI-RADS and the ATA guidelines. Taking pathological results as the reference, receiver operating characteristic (ROC) curves were drawn to evaluate the diagnostic capabilities of the ACR TI-RADS and the ATA guidelines for the risk stratification of thyroid isthmic nodules. The unnecessary biopsy rates and false-negative rates were compared. RESULTS: Multivariate analysis of ultrasonographic features of suspicious malignancies showed that an aspect ratio > 1 was not an independent risk factor for malignant thyroid nodules located in the isthmus (odds ratio: 3.193, 95%confidence interval: 0.882–11.552) (P = 0.077). The area under the ROC curves for diagnosing malignant thyroid nodules located in the isthmus in by the ACR TI-RADS and the ATA guidelines were 0.853 and 0.835, respectively. Under the management recommendations of the ACR TI-RADS and ATA guidelines, the false-negative rates of malignant thyroid nodules were 66.2%(ATA intermediate suspicion), 62.3%(ACR TR 4), 81.8%(ATA high suspicion) and 86.5%(ACR TR 5). CONCLUSION: Both the ACR TI-RADS and the ATA guidelines have high diagnostic capabilities for the risk stratification of thyroid isthmic nodules. For ACR TR 4 and 5 and ATA intermediate- and high-suspicion thyroid isthmic nodules with a maximum diameter < 1 cm, the criteria for puncture should be lowered, and FNAB should be done to clarify their diagnosis.
Association Between Serum Vitamins and the Risk of Alzheimer’s Disease in Chinese Population
Authors: Liu Xi-Xi , Wu Peng-Fei , Liu Ying-Zi , Jiang Ya-Ling , Wan Mei-Dan , Xiao Xue-Wen , Yang Qi-Jie , Jiao Bin , Liao Xin-Xin , Wang Jun-Ling , Liu Shao-Hui , Zhang Xuewei , Shen Lu
Published: December 2021

Background: Alzheimer’s disease (AD) is a chronic and fatal neurodegenerative disease; accumulating evidence suggests that vitamin deficiency is associated with the risk of AD. However, studies attempting to elucidate the relationship between vitamins and AD varied widely. Objective: This study aimed to investigate the relationship between serum vitamin levels and AD in a cohort of the Chinese population. Methods: A total of 368 AD patients and 574 healthy controls were recruited in this study; serum vitamin A, B1, B6, B9, B12, C, D, and E were measured in all participants. Results: Compared with the controls, vitamin B2, B9, B12, D, and E were significantly reduced in AD patients. Lower levels of vitamin B2, B9, B12, D, and E were associated with the risk of AD. After adjusting for age and gender, low levels of vitamin B2, B9, and B12 were still related to the risk of AD. In addition, a negative correlation was determined between vitamin E concentration and Activity of Daily Living Scale score while no significant association was found between serum vitamins and age at onset, disease duration, Mini-Mental State Examination, and Neuropsychiatric Inventory Questionnaire score. Conclusion: We conclude that lower vitamin B2, B9, B12, D, and E might be associated with the risk of AD, especially vitamin B2, B9, and B12. And lower vitamin E might be related to severe ability impairment of daily activities.
Private identity agreement for private set functionalities1
Authors: Kreuter Ben , Patel Sarvar , Terner Ben
Published: December 2021

Private set intersection and related functionalities are among the most prominent real-world applications of secure multiparty computation. While such protocols have attracted significant attention from the research community, other functionalities are often required to support a PSI application in practice. For example, in order for two parties to run a PSI over the unique users contained in their databases, they might first invoke a support functionality to agree on the primary keys to represent their users. This paper studies a secure approach to agreeing on primary keys. We introduce and realize a functionality that computes a common set of identifiers based on incomplete information held by two parties, which we refer to as private identity agreement, and we prove the security of our protocol in the honest-but-curious model. We explain the subtleties in designing such a functionality that arise from privacy requirements when intending to compose securely with PSI protocols. We also argue that the cost of invoking this functionality can be amortized over a large number of PSI sessions, and that for applications that require many repeated PSI executions, this represents an improvement over a PSI protocol that directly uses incomplete or fuzzy matches.
Disease and medication burden of medically complex adolescents seen in an interdisciplinary transitional care clinic
Authors: Bolesta Scott , Berger Andrea , Black Emily , Greskovic Gerard A. , Davis Thomas W.
Published: December 2021

PURPOSE: Transitional care for adolescents with complex diseases, who are entering adulthood, is challenging. The purpose of this study is to quantify the disease and medication burden of this population, who are transitioning though an interdisciplinary specialty clinic. METHODS: This study is a retrospective observational study of all patients seen in a transitional care clinic between July 2012 and March 2015. The main outcomes assessed included disease state and medication burden. Descriptive statistics, along with the paired t-test and McNemar’s test, were used. RESULTS: The study cohort included 216 patients. The median patient age was 20.7 years, and the median number of clinic encounters was 6. Patients had at least 1 of 8 primary diagnoses. On average, patients took medications from 5 classes and used 3 dose forms. Among 163 patients who had medication reconciliation performed, the average number of medication classes increased by 0.44±1.53 (p = 0.0003). There was an average increase of 3.70%(SD±36.31%; p = 0.27) in the number of required medication lab assessments ordered for patients who had medication reconciliation performed. CONCLUSION: There is a high disease and medication burden among adolescent patients with complex disease states who are to transition to adult care.
HOW CAN TOYOTA MOTOR CORPORATION ACHIEVE SUSTAINABLE DEVELOPMENT
Authors: Wang Zongyi
Published: December 2021

For a lean enterprise which aims to construct sustainable development, we set a hypothesis that lean could bring the value of sustainability into the organization and try to explore the traveling process of sustainability value. The completion of this process also relies on the Japanese firm’s unique cultural and historical background. Furthermore, lean can contribute to sustainable development at the corporate level through continuous technology and process optimization. But strong sustainability implies that the enterprise needs to do more only than focus on eco-efficiency, and it depends on the senior management understanding of sustainability to some extent. For moral and practical reasons, realizing sustainable development needs collective decision making for the common good (Ball & Miline, 2005). If they determine their attitudes to ecological systems, natural and energy conservation will be a form topic in the company. Ecological values will become an essential criterion in the appraisement of corporate performance as well as traditional economic criteria. It will assist the firm to have a more reasonable production scale, and the usage of renewable and non-renewable resources will be more brilliant in the production. Finally, it will influence the values of the firm. But it may put the firm in an ethical dilemma caused by the conflicts between profits and future generation’s interest.
STUDY OF THE EFFICIENCY OF CLASSIFICATION METHODS IN FORECASTING IN MACHINE LEARNING TASKS
Authors: Kalinina Iryna , Gozhyj Alexander
Published: December 2021

The article considers the use of classification methods to solve the problem of predicting the aerodynamic properties of materials. The methodology of classification by methods of machine learning is offered and investigated. The following logistic regression (LR), K-nearest neighbors (KNN) method, decision trees (DT) and random forest (RF) were used as classification methods. The methodology consists of the following stages: data collection, exploratory data analysis, modeling, evaluation of model efficiency, and improving model efficiency. To implement the forecasting procedure, preliminary data processing was performed, which consists of stages: Data collection and Intelligence data analysis. The next stage – Modeling, consists of two parts: Preparation and Selection of the model. The accuracy of forecasts is calculated. The analysis examined the prediction results in terms of accuracy, such as response, F-measure, Kappa, performance value (ROC) and error rate measured by the mean absolute error (MAE) and the root mean square error (RMSE). The analysis of forecasting accuracy is carried out.
CONCEPT OF DIGITALIZATION AND RESEARCH IN THE FIELD OF GERT-NETWORKS OF PUBLIC SECTOR PROJECT MANAGEMENT AND PROGRAMS
Authors: Zasukha Ihor
Published: December 2021

The modern world space has long gone beyond the construction of the information society, because digital technologies are absorbing more and more areas of public life, radically changing the forms and methods of their implementation. Therefore, most countries in the world focus on development in the direction of building a "digital economy", using all possible competitive advantages from its implementation. Ukraine is trying to keep up with the development of information technology in various areas of both public sector governance and public life. Some achievements have been made, but the systemic and synergistic effect on the development of the country has not been achieved, despite the significant potential of domestic IT professionals, who are among the top five IT outsourcers in the world. In my opinion, the very use of digitalization in the field of governance in the public sector can be the first impetus for digital transformations for the development of Ukraine's competitive economy. Therefore, they need -analysis of theoretical and practical approaches to a detailed study of the features of digitalization in the public sector of Ukraine during its digital transformation and the development of proposals for their implementation, which was the topic of my research. The word "digitalization" has entered our vocabulary so imperceptibly, but quite thoroughly, that in 2019 it was even recognized as the word of the year. Although the very definition of the concept is still debated not only in the domestic scientific field, but also abroad. The Dictionary of Modern Ukrainian Language and Slang "Myslovo" explains this neologism as a transliteration of the English "digitalization", which means changes in all spheres of public life related to the use of digital technologies, and is a manifestation of the global digital revolution. In my opinion, I agree with my colleagues that the development of digital transformations in the system of public sector management and administration is a potential example for the whole country, which in general also provides significant benefits for private companies - increased productivity and competitiveness, as well as for people. - acquisition of new knowledge and skills, choice of work and expansion of opportunities.
METHOD OF PLANNING THE REGISTER OF STAKEHOLDERS OF AGRO-INDUSTRIAL PROJECTS TAKING INTO ACCOUNT THEIR RISKS AND MENTALITY
Authors: Krol Konrad , Danchenko Olena , Denchyk Oksana
Published: December 2021

The application of the project approach in the agro-industrial complex of Ukraine helps to increase the efficiency of management of agricultural enterprises. Climate change and water scarcity pose significant challenges for the farmers. The introduction of innovations in the processes of agricultural production should be resource-oriented. The success of agricultural projects directly depends on the competencies of the project manager in managing the stakeholders. The stakeholders of agricultural projects have their own characteristics, which are related to the specifics of the projects. In order to reduce the misunderstandings and conflict situations between the project stakeholders, the author proposes to pay attention to the analysis of the mentality of such stakeholders. Knowledge, social position, cultural level, interest, value system, practices and skills of the project stakeholders, as the components of personality mentality, are the most important factors that can have a significant impact on the project. The authors developed a method of planning the register of stakeholders of agro-industrial projects taking into account their risks and mentality, which involves identifying the stakeholders of agro-industrial projects, creating a database of alternatives for the project stakeholders, assessing stakeholders’ impact on the project, identifying and assessing risk, as well as identifying and assessing mentality of each stakeholder. Then the formation of a database of all possible combinations of alternative stakeholders shall be carried out. For each combination, it is necessary to calculate the total risk and calculate the total mentality of such stakeholders, based on such results to select the optimal combination with minimum risk and maximum total mentality. Applying the developed method in counter-risk management of stakeholders of agro-industrial projects will help to increase the efficiency of management of the stakeholders, as well as to reduce the risks associated with them and to reduce the overall risk of the project.