bluuebunny/crossref_metadata_2025 huggingface dataset:
UTILIZAÇÃO DA DVA PARA ANÁLISE DA EVOLUÇÃO DA RIQUEZA SETORIAL GERADA PELAS EMPRESAS LISTADAS NA BM&FBOVESPA E DISTRIBUÍDA AOS SÓCIOS E ACIONISTAS DURANTE OS MANDATOS PRESIDENCIAIS DE LULA (2007-2010) E DILMA (2011-2014)
Authors: Dallabona Lara Fabiana , Koprowski Sirlene , Fernandes Ana Rita Venzon , Oliveira Gabriela Ramos de , Kroetz Marilei
Published: August 2021

O estudo objetivou utilizar a DVA para análise da evolução da riqueza setorial gerada pelas empresas listadas na BM&FBovespa e distribuída aos sócios e acionistas, admitindo como período os mandatos presidenciais de Lula (2007-2010) e Dilma (2011-2014). Realizou-se a coleta e análise das DVAs de 169 empresas listadas na BM&FBovespa e constantes em nove setores econômicos. A pesquisa classifica-se como descritiva, documental e quantitativa. Os resultados demonstraram que durante o governo Lula, seis setores obtiveram a maior distribuição de riqueza para Capitais Próprios no ano de 2010, último ano de governo. Ou seja, percebe-se uma evolução, em sua maioria, crescente no decorrer do referido mandato. Já no mandato de Dilma, quatro setores apresentaram o maior valor de distribuição para os sócios em 2011 (primeiro ano de governo), dois segmentos tiveram este resultado em 2013 e três em 2014. O estudo pretende contribuir com o meio acadêmico, com pesquisas que utilizam a DVA, em relação a sua vertente de distribuição de riqueza aos entes formadores, principalmente os sócios e acionistas, em empresas listadas na BM&FBovespa, possibilitando uma análise dos dados a partir de mandatos presidenciais.
DAS ÁGUAS QUE CONVERGEM AS ÁGUAS QUE DIVERGEM: MERCADORIZAÇÃO DA ÁGUA NA REGIÃO DO CARIRI CEARENSE
Authors: Nobre Francisco Wlirian
Published: August 2021

Considerada por muitos como um oásis no meio do sertão, a região do Cariri representa uma das áreas com maior riqueza hídrica do estado do Ceará. Para os índios Kariris, primeiros habitantes da região, a relação com a água estava ligada as suas próprias condições de existência, mas com a chegada dos colonizadores, no século XVIII, a mercadorização da água foi induzida produzindo uma nova geografia das águas imbuída pelas forças políticas e econômicas que se estabeleceram na região. Objetiva-se nessa pesquisa, através de uma metodologia de análise documental e revisão da literatura, demonstrar um debate teórico sobre o processo de mercadorização da água na região do Cariri cearense. Observamos que a transição das formas de produção do espaço intensificadas com o avanço das políticas neoliberais acentuaram os problemas de degradação e injustiça ambiental representando um sentido de natureza com significado oposto a concepção de mundo dos índios Kariris.
TÓPICOS METODOLÓGICOS PARA A HISTORIOGRAFIA DA GEOGRAFIA
Authors: De Barros Nilson Cortez Crocia
Published: August 2021

O artigo consiste na exposição de alguns tópicos de reflexão considerados relevantes do ponto de vista metodológico para aqueles que se propõem a reconstruir episódios da História da Geografia. O artigo adota uma perspectiva historiográfica sistemática.
DIVERSAS PERSPECTIVAS INVESTIGATIVAS EN ECOLOGÍA POLÍTICA
Authors: Elkisch Mariana
Published: August 2021

El artículo discute procesos fundamentales vividos en nuestro tiempo. Enfatiza la agudización de los mecanismos de acumulación desplazados hacia el campo de la explotación de los recursos biológicos-naturales. Examina de manera analítica los argumentos y datos de la que apuntan en la tendencia actual de la intensificación de la naturaleza y de la vida a escala global.
O PAPEL DA MATEMÁTICA NA FORMAÇÃO DO CIDADÃO E PRINCÍPIOS DE SELEÇÃO DE COMPETÊNCIAS MATEMÁTICAS BÁSICAS NOS CURRÍCULOS VIGENTES
Authors: Dias Marcelo Oliveira
Published: August 2021

O presente artigo tem por objetivo analisar as recomendações prescritas pelos elaboradores nos Parâmetros Curriculares Nacionais (PCN) e a Base Nacional Comum Curricular para o Ensino Fundamental e Ensino Médio, organizados respectivamente nos anos 90 e no presente século XXI para a Educação Básica, no que se refere ao papel que a Matemática exerce na vida do cidadão e os princípios de seleção de competências matemáticas básicas. Na pesquisa de natureza qualitativa, lançamos mão de pesquisa bibliográfica nos documentos curriculares vigentes e da BNCC que se encontra em processo de implementação no país. Constatou-se que as propostas enfatizam recomendações metodológicas que propiciam ao professor e à escola flexibilidade na definição dos conteúdos para a formação e o desenvolvimento de competências, privilegiando os conteúdos conceituais, procedimentais e atitudinais.
O Efeito da Marca de Eventos Musicais com Diferentes Níveis de Congruência do Artista-Celebridade
Authors: Aureliano-Silva Leonardo
Published: August 2021

O principal objetivo desse estudo foi analisar o efeito da marca do evento no comportamento do consumidor de eventos musicais. Para isso foi realizado um experimento com 217 indivíduos, e constatado que uma marca reconhecida aumenta a intenção de compra do ingresso e a percepção de qualidade do evento. A marca reconhecida foi mais bem avaliada quando contou com artista-celebridade de alta congruência com o evento, tanto para intenção de compra do ingresso como percepção de qualidade. A marca não reconhecida foi mais bem avaliada apenas em relação à  percepção de qualidade do evento quando contou com artista-celebridade de alta congruência com o evento.
Transformative Consumer Research and the Visually Impaired: A study on restaurant services
Authors: Faria Marina Dias de , Silva Jorge Ferreira da , Ferreira Jorge Brantes
Published: August 2021

Citizens with disabilities wish and have the right to fulfill all social roles, including the consumer role. Business practitioners and scholars, however, frequently fail to consider these potential consumers. This study aims to analyze if the attributes the visually impaired most value in leisure services and environments are present in restaurants in Rio de Janeiro. Results point to certain fundamental attributes as being valued by people with low or no visual acuity in leisure restaurant outings: menus in Braille; personnel trained to serve ; tables with legs on each of its four corners and without sharp edges; low sound and light intensity; attendant paging devices; and adequate restroom facilities. Observations and interviews show that most restaurants have accessibility issues. Practical and social implications point to mandatory investments in infrastructure and personnel training in order to tend to the needs of the visually impaired according to legal and market requirements.
Influências Contraculturais no Consumo Colaborativo: Insights no contexto do Couchsurfing.com
Authors: Vouga André
Published: August 2021

Este artigo discute parte dos achados de uma imersão netnográfica realizada no Couchsurfing.com, plataforma da web dedicada a trocas de hospitalidade. Nele se mapeiam controvérsias derivadas do choque entre a filosofia de sua constituição, derivada da contracultura, e a práxis ali observada, principalmente quanto: às demandas de densidade dos relacionamentos desenvolvidos, às expectativas de reciprocidade em relação à hospedagem e aos códigos legitimadores da comunidade.
An assessment of the impact of selected construction materials on the life cycle energy performance and thermal comfort in buildings
Authors:   , Haripersad Rajesh
Published: August 2021

South Africa is a developing country with various construction projects that are being undertaken both by government and the private sector. The requirements for the construction of energy-efficient buildings as well as the selection methods for providing construction materials have hence become important. Energy efficiency improvements needs to be implemented in the construction of these buildings in order to decrease energy usage and costs and provide more comfortable conditions for its occupants. Previous studies revealed that most of the focus for improving energy efficiency in buildings has been on their operational emissions. It is estimated that about 30% of all energy consumed throughout the lifetime of a building is utilized as embodied energy (this percentage varies based on factors such as age of building, climate and materials). In the past this percentage was much lower, but with increased emphasis placed on reducing operational emissions (such as energy efficiency improvements in heating and cooling systems), the embodied energy contribution has become more significant. Hence, it is important to employ a life-cycle carbon framework in analysing the carbon emissions in buildings. The study aims to augment energy efficiency initiatives by showcasing energy reduction strategies for buildings. The study assessed the thermal performance of selected construction materials by analysing different buildings using energy modelling program, EnergyPlus and TRNSYS. The parametric study was set in the central plateau region of South Africa and was performed to determine appropriate energy efficiency improvements that can be implemented for maximum savings. A life cycle cost analysis was performed on the selected improvements. The models created are representative of the actual buildings when simulated data is compared to recorded data from these buildings. Results showed a significant variation in energy and construction costs with varying construction materials over the buildings’ life cycle. Findings suggest that there is a significant reduction in energy usage when simple efficiency measures are implemented. The study recommends the use of different energy efficient building materials and the implementation of passive interventions in the constructing of buildings; the thermal performance of a building be optimized to ensure thermal comfort and the developed model be adopted for use in the engineering and construction industry for the reduction of energy consumption.
NGHIÊN CỨU, THỬ NGHIỆM DUNG DỊCH DINH DƯỠNG HỮU CƠ TỪ BÃ ĐẬU NÀNH TRONG TRỒNG RAU ĂN LÁ THỦY CANH
Authors: Hoàng Thị Mai , Nguyễn Thị Thu Phương , Âu Thuỳ Na , Lê Công Hùng
Published: August 2021

Mục đích của nghiên cứu nhằm xác định nồng độ dung dịch dinh dưỡng hữu cơ được sản xuất theo quy trình của Han Kyu Cho và Atsushi Koyama (1997) từ bã đậu nành để trồng rau xà lách, cải ngọt bằng phương pháp thủy canh. Theo đó, dung dịch hữu cơ có thành phần chính gồm  Nitơ tổng số: 1968,23 mg/l, P2O5: 167,53mg/l, K2O: 420,91mg/l được khảo sát ở các nồng độ pha loãng từ 5-20 lần.  Kết quả nghiên cứu cho thấy, nồng độ pha loãng phù hợp cho sự phát triển của rau xà lách, cải ngọt từ 10 đến 15 lần, với khoảng nồng độ này độ Brix của rau sử dụng dinh dưỡng hữu cơ cao hơn dung dịch Knop từ 2,2 – 2,8 % đối với rau xà lách, 0,5 – 1,3 % đối với rau cải ngọt; đặc biệt hàm lượng NO3-  trong rau thương phẩm sử dụng dinh dưỡng hữu cơ thấp hơn 3 lần so với dung dịch Knop.
ẢNH HƯỞNG CỦA TUỔI CÂY, VỊ TRÍ TRÊN THÂN CÂY ĐẾN MỘT SỐ TÍNH CHẤT VẬT LÝ CỦA VẦU (Bambusa nutans Wall. ex Munro) TRỒNG TẠI BẮC KẠN
Authors: Nguyễn Việt Hưng , Nguyễn Thị Tuyên
Published: August 2021

Tuổi cây và vị trí trên thân cây (gốc, thân, ngọn) ảnh hưởng đến tính chất vật lý của Vầu (Bambusa nutans Wall. ex Munro). Trong nghiên cứu này đã tiến hành xác định được sự thay đổi một số tính chất vật lý của Vầu theo tuổi cây và vị trí trên thân cây: khối lượng riêng, độ co rút, độ ẩm sau khai thác. Kết quả nghiên cứu cho thấy, ở các cấp tuổi các tính chất vật lý của Vầu có sự biến động từ gốc đến ngọn: khối lượng riêng cơ bản biến động tăng dần từ gốc đến ngọn, tăng từ tuổi 1 đến tuổi 3 và giảm xuống ở tuổi 5, biến động trong khoảng 0,434 – 0,614 g/cm3, khối lượng riêng ở độ ẩm 12% biến động trong khoảng 0,508 – 0,731 g/cm3. Độ co rút theo chiều xuyên tâm và tiếp tuyến khi mẫu đạt đến độ ẩm 0% biến động tăng dần từ gốc đến ngọn, tăng từ tuổi 1 đến tuổi 3 và giảm ở tuổi 5 lần lượt biến động trong khoảng 4,34 – 9,75% và 3,00 – 7,99%. Độ ẩm biến động giảm từ gốc đến ngọn, giảm từ tuổi 1 đến tuổi 3 và ổn định ở tuổi 5, biến động trong khoảng 68,25 – 96,42%.
NGHIÊN CỨU ẢNH HƯỞNG CỦA CÁC CÔNG THỨC PHÂN BÓN ĐẾN NĂNG SUẤT VÀ CHẤT LƯỢNG GIỐNG NHÃN PH - M 99 -1.1 TẠI TRUNG TÂM THỰC HÀNH THỰC NGHIỆM VÀ CHUYỂN GIAO KHOA HỌC CÔNG NGHỆ TRƯỜNG ĐẠI HỌC TÂN TRÀO, TỈNH TUYÊN QUANG
Authors: Vi Xuân Học , Nguyễn Thị Thu Hiền , Nguyễn Thị Xuyến
Published: August 2021

Nghiên cứu ảnh hưởng của các công thức phân bón đến các yếu tố cấu thành năng suất, chất lượng, hiệu quả kinh tế trên cây nhãn năm 2020 tại trường Đại học Tân Trào cho thấy:  với mức bón phân đạm, 1,2 kg/cây phân kali 1,2 kg/cây, phân lân 2,5 kg/cây đã đạt 165 chùm hoa/cây; số quả đạt 14,5 quả/chùm và đạt năng suất 30,1 kg/cây. Tỷ lệ phần ăn được đạt 61,3%, hàm lượng đường tổng số cao nhất đạt 14,4%, hàm lượng Vitamin C đạt 18,7 mg/100 gam cùi nhãn, độ Brix đạt 18,7%; lãi thuần đạt 356.600đ/cây.
Legal Advocacy For Catfish Cultivation Groups As An Effort To Improve The Economy In Facing The Covid 19 Pandemic In Mojorang Agung Wondayu Village, Sidoarjo, East Java, Indonesia
Authors: Sutrisno  , Mas Anienda Tien F  , Rohmatul Faizah  , Hervina Puspitosari
Published: August 2021

Empowerment of catfish advertising cultivation for the community can increase the income source of rural communities and also as an effort to expand employment opportunities for rural communities through the provision of existing land and water in the village of Mojorangagung Wondayu Sidoarjo, East Java, Indonesia. Fish farming business groups in running their business require a business license as a form of legality. Assistance and roles and cooperation with various related agencies are needed in the progress of fish farming business groups, for example,Cooperation with the Department of Agriculture and Food, Cooperation with Universities, one of which is with the National Development University "Veteran" East Java so that assistance can be carried out in managing its legality and can be carried out assistance in cultivation and marketing as well as various other collaborations with related agencies are also needed. The management of legal entities for fish farming groups is very important, apart from being an obligation some rights can be obtained by fish farming groups that have legal entities including being able to receive assistance from the government in the hope that fish farming business actors in the future can be independent and carry out sustainable fisheries business.
KONSTRUKSI PENDIDIKAN ISLAM DI ERA GLOBAL MENURUT AZYUMARDI AZRA
Authors: WACHIDAH SITI NURUL
Published: August 2021

Sistem pendidikan Islam di Indonesia belum menemukan bentuk yang ideal dalam menjawab tantangan perubahan di era global. Azyumardi Azra menawarkan ide-ide pembaharuan yang menarik untuk dikaji sebagai salah satu alternatif pemecahan problem pendidikan Islam. Problem akademik dalam penelitian ini; Pertama, bagaimana kritik Azyumardi terhadap pendidikan Islam dan bagaimana solusi yang ditawarkan. Kedua, bagaimana kekuatan dan kelemahan tawaran Azyumardi azra terhadap pendidikan Islam dalam Perspektif Filsafat Pendidikan Islam.Tujuan penelitian ini adalah untuk mengetahui kritik Azyumardi Azra terhadap pendidikan Islam dan solusi yang ditawarkannya, serta mengetahui kekuatan dan kelemahan tawaran Azyumardi Azra tentang konstruksi pendidikan Islam di era global dalam perspektif Filsafat Pendidikan Islam. Penelitian ini merupakan penelitian kepustakaan yang bersifat kualitatif. Pendekatan yang digunakan adalah pendekatan filsafat kritis dengan teori Filsafat Pendidikan Islam. Sumber data primer adalah karya-karya Azyumardi Azra yang terkait pembaharuan pendidikan Islam, sedangkan karya lain dijadikan sebagai data sekunder. Metode pengumpulan data adalah dokumentasi. Analisa data menggunakan content analysis. Temuan dalam penelitian adalah ide-ide pokok Azyumardi meliputi kritik epistimologi keilmuan Islam, paradigma pembelajaran, pengembangan Sumber Daya manusia. Kontribusi penelitian ini adalah tawaran Azyumardi Azra bagi konstruksi baru pendidikan Islam di era global meliputi pembelajaran emansipatoris, misi profetis sebagai dasar pengembangan SDM dan menawarkan model alternatif lembaga pendidikan Islam dengan Sekolah Elit Muslim dan madrasah unggul.
INCLUSÃO ESCOLAR DE ALUNOS COM AUTISMO NA EDUCAÇÃO INFANTIL
Authors: Suassuna Janieli de Souza Santos
Published: August 2021

A inclusão escolar tem sido motivo de debates no meio da educação nos últimos anos, nesse sentido esse trabalho de pesquisa se desenvolve em torno do tema “os avanços e as dificuldades no processo da inclusão do autista na educação infantil”. Com o objetivo de investigar e conhecer o Transtorno do Espectro Autista, para formar conhecimentos para futuros educadores e cidadãos, mais especificadamente na inclusão da criança autista na educação infantil. Pois a educação escolar tem se mostrado como um grande desafio para educadores, que se viram em frente a necessidade de ser os responsáveis diretos pelo processo de inclusão escolar, mesmo que não tinham formação e preparo para realizar essa tarefa. Diante do exposto acima esse trabalho de pesquisa se justifica, e acontece através de uma pesquisa bibliográfica em livros, revistas, artigos e na internet, com autores que já se debruçaram sobre o tema inclusão escolar. O presente trabalho se desenvolve ao longo de três capítulos, onde o primeiro é pautado em torno das concepções do Transtorno do Espectro Autista (TEA) e suas definições.
Declines and peaks in NO2 pollution during the multiple waves of the COVID-19 pandemic in the New York metropolitan area
Authors: Tzortziou Maria , Kwong Charlotte Frances , Goldberg Daniel , Schiferl Luke , Commane Róisín , Abuhassan Nader , Szykman James , Valin Lukas
Published: August 2021

Abstract. The COVID-19 pandemic created an extreme natural experiment in which sudden changes in human behavior and economic activity resulted in significant declines in nitrogen oxide (NOx) emissions, immediately after strict lockdowns were imposed. Here we examined the impact of multiple waves and response phases of the pandemic on nitrogen dioxide (NO2) dynamics and the role of meteorology in shaping relative contributions from different emission sectors to NO2 pollution in post-pandemic New York City. Long term (> 3.5 years), high frequency measurements from a network of ground-based Pandora spectrometers were combined with TROPOMI satellite retrievals, meteorological data, mobility trends, and atmospheric transport model simulations to quantify changes in NO2 across the New York metropolitan area. The stringent lockdown measures after the first pandemic wave resulted in a decline in top-down NOx emissions by approx. 30 % on top of long-term trends, in agreement with sector-specific changes in NOx emissions. Ground-based measurements showed a sudden drop in total column NO2 in spring 2020, by up to 36 % in Manhattan and 19–29 % in Queens, New Jersey and Connecticut, and a clear weakening (by 16 %) of the typical weekly NO2 cycle. Extending our analysis to more than a year after the initial lockdown captured a gradual recovery in NO2 across the NY/NJ/CT tri-state area in summer and fall 2020, as social restrictions eased, followed by a second decline in NO2 coincident with the second wave of the pandemic and resurgence of lockdown measures in winter 2021. Meteorology was not found to have a strong NO2 biasing effect in New York City after the first pandemic wave. Winds, however, were favorable for low NO2 conditions in Manhattan during the second wave of the pandemic, resulting in larger column NO2 declines than expected based on changes in transportation emissions alone. Meteorology played a key role in shaping the relative contributions from different emission sectors to NO2 pollution in the city, with low-speed (< 5 ms−1) SW-SE winds enhancing contributions from the high-emitting power-generation sector in NJ and Queens and driving particularly high NO2 pollution episodes in Manhattan, even during – and despite – the stringent early lockdowns. These results have important implications for air quality management in New York City, and highlight the value of high resolution NO2 measurements in assessing the effects of rapid meteorological changes on air quality conditions and the effectiveness of sector-specific NOx emission control strategies.
Social sensing of high-impact rainfall events worldwide: a benchmark comparison against manually curated impact observations
Authors: Spruce Michelle D. , Arthur Rudy , Robbins Joanne , Williams Hywel T. P.
Published: August 2021

Abstract. Impact-based weather forecasting and warnings create the need for reliable sources of impact data to generate and evaluate models and forecasts. Here we compare outputs from social sensing – analysis of unsolicited social media data, in this case from Twitter – against a manually curated impact database created by the Met Office. The study focuses on high-impact rainfall events across the globe between January–June 2017. Social sensing successfully identifies most high-impact rainfall events
present in the manually curated database, with an overall accuracy of
95 %. Performance varies by location, with some areas of the world
achieving 100 % accuracy. Performance is best for severe events and events in English-speaking countries, but good performance is also seen for less severe events and in countries speaking other languages. Social sensing detects a number of additional high-impact rainfall events that are not recorded in the Met Office database, suggesting that social sensing can
usefully extend current impact data collection methods and offer more
complete coverage. This work provides a novel methodology for the curation of impact data that
can be used to support the evaluation of impact-based weather forecasts.
Edge displacement scores
Authors: Melsom Arne
Published: August 2021

Abstract. As a consequence of a diminishing sea ice cover in the Arctic, activity is on the rise. The position of the sea ice edge, which is generally taken to define the extent of the ice cover, changes in response to dynamic and thermodynamic processes. Forecasts for sea ice expansion on synoptic timescales due to an advancing ice edge will provide information that can be of significance for open ocean operations in polar regions. However, the value of this information depends on the quality of the forecasts. Here, we present methods for examining the quality of forecasted sea ice expansion on sub-seasonal timescales and the geographic location where the largest expansions are expected from the forecast results. The algorithm is simple to implement, and an examination of 2 years of model results and accompanying observations demonstrates the usefulness of the analysis.
Note of Remembrance in Honor of Edwin David Lawson (December 23, 1923—July 3, 2021)
Authors: Demsky Aaron
Published: August 2021

This note of remembrance is written for the eminent onomastician Edwin David Lawson.
Use of a Matching Preference Index to Empirically Examine Distribution Imbalances in Beijing Citizens’ Names
Authors: Zhao Ziming , Li Xiaomeng , Chen Qinghua
Published: August 2021

Personal names contain considerable meaningful information about biological and social characteristics of the name-bearer. They also routinely contain important data about cultural preferences in the naming process. Access to this level of information has been limited in the past by a lack of access to large-scale empirical data. As this investigation demonstrates, by utilizing a reliable large-scale sample of Beijing citizens, it is possible to empirically demonstrate onomastic imbalances in the occurrence of Chinese surnames, given names, and full names. In particular, this paper explores the matching imbalance between Chinese surnames and given names, a phenomenon which has as yet received scant attention in onomastic literature. As this article demonstrates, our innovative quantitative approach makes it possible to reveal statistically significant differences between real names and “random-matching names” that reflect a matching imbalance and imply the probable existence of underlying cultural preferences in Chinese naming processes. The key to this approach is generating a matching preference index (MPI) for names in a dataset. Alongside explaining how this approach is used, this paper offers possible reasons to explain why specific names have higher or lower MPI rankings. As this paper argues, one of the main reasons for these empirical differences may be found in special associations name-givers have within Chinese culture.
Data Privacy and Security in Cloud Environment Using Cryptography Approach
Authors: Agarkhed Jayashree , Ashalatha R.
Published: August 2021

Cloud computing environment is a network centered computing technique delivered to the users as a service. It mainly involves computing over the network where the program file or any application, run upon server in various locations at the identical time. Cloud computing accommodates huge data storage and computing capabilities to its users. The cloud storage service is considered to be the best quality cloud maintenance service. Cryptography is known as the skill of securing the confidential information from third party hackers. Both the parties over the insecure network can transfer files with each other by the ways of cryptographic techniques of the sensitive data files for maintaining the security and also privacy. The secrecy and concealment of data are considered an important issue of concern in cloud field.
ARO_EDGE: A Technique to Ensure Data Security in Internet of Things (IoT)
Authors: Vithya Vijayalakshmi A. , Arockiam L.
Published: August 2021

Recently, e-health care, smart home, smart city, smart car and smart car services have been receiving attention all over the world. In smart health care, there are many sensors are communicating between each other and connected to the global network connection. Therefore, there is a problem in securing the data sensed from the various medical IoT devices. Lightweight and efficient way of providing secure communication in the IoT are the need of the hour. To overcome this problem, a technique has been proposed. This paper proposes a confidentiality technique, named ARO_EDGE to secure the data in IoT devices. This proposed confidentiality technique is based on data obfuscation technique to prevent the data from the attackers and unauthorized users.
A Robust Hybrid Algorithm for Image Watermarking
Authors: Singh Sharanjit , Mahant Neha
Published: August 2021

Image watermarking is the mechanism of hiding the critical information on the segment of the image that can either be least significant or most significant in nature. Image watermarking involves multiple images that are merged together to achieve a common image that is transferred over a digital medium. Proposed system uses slant let transformation to achieve better result of image security in terms of accuracy. Accuracy is achieved by minimising mean square error and improving peak signal to noise ratio.
A Survey of Different Steganography Technique using Cryptographic Algorithm
Authors: Agrawal Prakhar , Upadhyay Arvind
Published: August 2021

Steganography and cryptography are two major aspects of data security . In this paper we are going to provide the survey of different techniques of LSB based Steganography that used cryptography algorithms to secure sensitive information. Steganography is used to hide data and Cryptography is used to encrypt the data. Although cryptography and steganography individually can provide data security, every of them has a drawback. Drawback associated with Cryptography is that, the cipher text looks meaningless, so the unintended user can interrupt the transmission or make more careful checks on the information from the sender to the receiver. Drawback associated with Steganography is that when the presence of hidden information is revealed or even suspected, the message is become known[1].By combining these two methods we can solve both of the above problem. First we encrypt the data using any cryptography technique and then embed the encrypted text into the image. Steganography is the process which hides the presence of secure data during communication. On the other hand cryptography is encrypting and decrypting of secure data and information with a secrete key so that no one can be understand the message directly.
IoT Based Access Control Mechanism Using RFID Technology
Authors: Swathika M. , Indirani G.
Published: August 2021

Internet of Things plays a vital role in day to day life of this developing technological world. IoT involves many technologies such as RFID technology, sensor technology, smart technology, Nano technology etc. IoT based RFID technology is studied in this paper. The introduction about IoT is firstly presented. Then, the RFID technology-Radio Frequency Identification Technology and its components are explained. Then, the interfacing of RFID-RC522 with Arduino Uno and the interfacing of wifi module ESP8266 with Arduino Uno are mentioned. Then, the overall procedure of using RFID for security purpose is explained with flow diagram. For this security system, the output of accessing certain number of selected tags and denying all other tags is obtained. Some applications related to IoT based security system using RFID technology are attached. Finally, the output is discussed in conclusion part. We believe that the RFID technology will be developed further and innovated to provide many applications and services for users in the future.
RetinaNet Based Environment Classification
Authors: Balamurugan R. , Arunkumar R. , Mohan S.
Published: August 2021

Environmental classification is very useful for visually impaired persons and Robotic applications. The main objective of this work is to detect and recognize the objects present in a scene and identify the environment based on the occurrence probability of the objects in the scene. Objects from the real-time images are detected and recognized by means of RetinaNet. Occurrence probabilities of the recognized objects are used to identify the environment.
IoT Based Silence Monitoring System
Authors: Esther Devakirubai E. , Indirani G.
Published: August 2021

Internet of Things (IoT) finds application in many fields these days. This paper focuses on the use of IoT based monitoring of Silence which can be used in places where Silence maintenance is important like in libraries and in classrooms of schools. Further this paper proposes a system based on Arduino which involves programming Arduino Uno to achieve the purpose of Silence monitoring.
An Empirical Review on Data Feature Selection and Big Data Clustering
Authors: Maddumala Venkata Rao , Arunkumar R. , Arivalagan S.
Published: August 2021

With the fast advancement of the Big Data, Big Data innovations have risen as a key data investigation apparatus, in which, feature extraction and data bunching calculations are considered as a basic part for data examination. Nonetheless, there has been constrained research that tends to the difficulties crosswise over Big Data and along these lines proposing an exploration motivation is vital to illuminate the examination challenges for bunching Big Data. By handling this particular viewpoint – grouping calculation in Big Data, this paper looks at on Big Data advancements, identified with feature determination and data bunching calculations and conceivable uses. In view of our survey, this paper distinguishes an arrangement of research difficulties that can be utilized as an exploration plan for the Big Data bunching research. This exploration plan goes for distinguishing and crossing over the examination holes between Big Data feature choice and grouping calculations.
A Study on Localization in Wireless Sensor Network Using Neural Network
Authors: . K. Madhumathi , . T. Suresh
Published: August 2021

Wireless Sensor Network consists of large number of autonomous, small, low cost sensor nodes that are spatially distributed in areas of investigation like disaster management, Military, environmental monitoring etc. The main purpose of using those nodes is to collect information from source and process it in destination. But the data received in the destination are useless unless the exact location of source is not known. The task of finding physical coordinates of these sensor nodes in WSNs area is known as localization. One solution for the above problem is manual configuration of sensor but it is unfeasible if the area of deployment is large or inaccessible. Therefore, we use localization techniques which help to capture the location of nodes in wireless sensor network. This study analyses localization algorithms with their pros and cons.
Classification of WSN Routing Protocol Based On Clustering
Authors: . C. Sudha , . D. Suresh , . A. Nagesh
Published: August 2021

Wireless Sensor Networks (WSNs) within the zone time regulate to greater enticing and develop their manner into massive variance of exercise in distinctive domains. Elevation in wireless sensor network technology provide the affability of small and low cost sensor nodes with the adequacy of sensing, processing, computing the physical and surroundings circumstances. Due to inhibition in transmission range, processing and power resources it is considered necessary to design awesome and energy aware protocol to increase network lifetime. Routing strategies are developing to boom life cycle of sensor network and increase throughput performance. This paper gives, an analysis of various routing strategies used in wireless sensor networks in addition importance of cluster based routing, and varieties of cluster, type of cluster based routing are discussed. The observe concludes with the issues and the resent researchers on cluster based routing.
An Efficient Healing and Hole Detection in Mobile Wireless Sensor Network Based on Distributed and Localized Algorithms
Authors: Suresh T. , Anbuananth C. , Prabakaran G.
Published: August 2021

The emerging trends of wireless sensor network (WSN) are estimated to afford a wide range of applications, such as battlefield surveillance, environmental monitoring, and smart spaces and so on. The coverage problem is an essential concern in the WSN. In this paper seeks to address the problem of hole detection and healing in mobile WSNs. This paper discuss the main drawbacks of existing solutions and identify four key elements that are critical for ensuring effective coverage in mobile WSNs: (i) Identifying the boundary of Region of Interest, (ii) Finding the coverage holes and estimating their characteristics, (iii) Identifying the best target locations to relocate mobile nodes to repair holes, and (iv) Dispatching mobile nodes to the target locations while minimizing the moving and messaging cost. This paper proposes a lightweight and comprehensive solution called Holes detection and healing, that addresses all of the aforementioned aspects. HEAL is a distributed and localized algorithm that operates in two distinct phases. First, a collaborative mechanism, called Distributed Hole Detection (DHD), is proposed to identify the boundary nodes and discover holes. Second, this paper presents a virtual force- based hole healing algorithm. Unlike existing algorithms, HEAL algorithm relocates only the adequate nodes within the shortest times with the lowest cost. Simulation results shows that HEAL provide a cost-effective and an accurate solution.
Improving Security on Cloud Based Deduplication System
Authors: Rasina Begum B. , Chithra P.
Published: August 2021

Cloud computing provides a scalable platform for large amount of data and processes that work on various applications and services by means of on-demand service. The storage services offered by clouds have become a new profit growth by providing a comparable cheaper, scalable, location-independent platform for managing users’ data. The client uses the cloud storage and enjoys the high end applications and services from a shared group of configurable computing resources using cloud services. It reduces the difficulty of local data storage and maintenance. But it gives severe security issues toward users’ outsourced data. Data Redundancy promotes the data reliability in Cloud Storage. At the same time, it increases storage space, Bandwidth and Security threats due to some server vulnerability. Data Deduplication helps to improve storage utilization. Backup is also less which means less Hardware and Backup media. But it has lots of security issues. Data reliability is a very risky issue in a Deduplication storage system because there is single copy for each file stored in the server which is shared by all the data owners. If such a shared file/chunk was missing, large amount of data becomes unreachable. The main aim of this work is to implement Deduplication System without sacrificing Security in cloud storage. It combines both Deduplication and convergent key cryptography with reduced overhead.
A Comparative Study on the Feature Selection Techniques for Intrusion Detection System
Authors: Selvamani D. , Selvi V.
Published: August 2021

The Intrusion Detection System (IDS) can be used broadly for securing the network. Intrusion detection systems (IDS) are typically positioned laterally through former protecting safety automation, like access control and verification, as a subsequent line of resistance that guards data classifications. Feature selection is employed to diminish the number of features in various applications where data has more than hundreds of attributes. Essential or relevant attribute recognition has converted a vital job to utilize data mining algorithms efficiently in today world situations. This article describes the comparative study on the Information Gain, Gain Ratio, Symmetrical Uncertainty, Chi-Square analysis feature selection techniques with different Classification methods like Artificial Neural Network, Naïve Bayes and Support Vector Machine. In this article, different performance metrics has utilized to choose the appropriate Feature Selection method for better data classification in IDS.
Eigenfaces Technique, an Improved Face Recognition Approach Using Neural Network
Authors: Ashraf Mohd , Zair Hussain Md.
Published: August 2021

Image analysis and understanding, stands tall amongst all the technologies and face recognition is an eminent part of it. A face database is maintained as a logbook to identify an input face. This is accomplished by mere comparison amongst the face database. There are several face recognition techniques, of which, symmetry, Elastic Bunch Graph Matching (EBGM), and analytic-to-holistic recognition have been explored in this research paper. Other peculiar approaches like image based face recognition techniques like MLP, convolutional neural network, eigenfaces, associative neural networks, recirculation neural network and independent component analysis have been thoroughly discussed. Two vibrant face recognition databases, UMIST and ORL have proved to be extremely important in analyzing the results of face recognition. Eigen Face value approach has been anticipated with the associated analysis of results of face recognition. Another approach in face recognition is optimized multiperceptron, which will be acting as the reference to the optimized eigenfaces approach in this research paper, hence making this study more efficient through comparison.
Document Classification Using Artificial Neural Network
Authors: Tripathi Kshitij , Vyas Rajendra G. , Gupta Anil K.
Published: August 2021

The Document classification system is the field of data mining in which the format of data is based on bag of words (BoW) or document vector model and the task is to build a machine which after successfully learn the characteristic of given data set, predicts the category of the document to which the word vector belongs. In this approach document is represented by BoW where every single word is used as feature which occurs in a document. The proposed article presents artificial neural network approach which is hybrid of n-fold cross validation and training-validation-test approach for classification of data.
Segmentation of 3D Brain Structures in MRI Images
Authors: Narendran P. , Thiagarasu V.
Published: August 2021

The main topic of this paper is to segment brain tumors, their components (edema and necrosis) and internal structures of the brain in 3D MR images. For tumor segmentation, we propose a framework that is a combination of region-based and boundary-based paradigms. In this framework, we first segment the brain using a method adapted for pathological cases and extract some global information on the tumor by symmetry based histogram analysis. The second step segments the tumor and its components. For this, we propose a new and original method that combines region and boundary information in two phases: initialization and refinement. For initialization, which is mostly region-based, we present two new methods. The first one is a new fuzzy classification method which combines the membership, typicality and neighborhood information of the voxels. The second one relies on symmetry-based histogram analysis. The initial segmentation of the tumor is refined relying on boundary information of the image. This method is a deformable model constrained by spatial relations. The spatial relations are obtained based on the initial segmentation and surrounded tissues of the tumor. The proposed method can be used for a large class of tumors in any modality of MR images. To segment a tumor and its components automatically the proposed framework needs only a contrast enhanced T1-weighted image and a FLAIR image. In the case of a contrast enhanced T1-weighted image only, some user interaction will be needed. To refine the initial segmentation, we use a deformable model which is again constrained by the fused spatial relations of the structure. This method was also evaluated on 10 contrast enhanced T1-weighted images to segment the ventricles, caudate nucleus and thalamus.
Novel Approach for Green Cloud Data Center Using IoT Sensor Device
Authors: Sarddar Debabrata , Dutta Gourab , Pandit Rajat
Published: August 2021

Cloud computing provides all the basic level of computing facility to complete the daily needs of a general or public community. In this paper, we concerned about the topic of carbon dioxide and carbon monoxide emission from cloud computing and its environmental effects and how to control it. Due to global warming and greenhouse effect, increasing the temperature of the environment day by day. In this paper, we concerned about how to control the problem of carbon dioxide and carbon monoxide emission from the cloud data center and also try to reduce the reaction cost. We use carbon dioxide and carbon monoxide measuring sensor Internet of Things (IoT) device and a chamber which contain solid sodium hydroxide at 130 °C and 6-8 bar pressure. We set one predefined threshold value into the IoT sensor and when the carbon dioxide and carbon monoxide increase then the value of IoT sensor also increase from predefined threshold value then only the chamber open automatically which contain solid sodium hydroxide at 130 °C and 6-8 bar pressure. Then the reaction occur and produce sodium formate after the reaction with carbon monoxide and also produce sodium carbonate after the reaction with carbon dioxide. Again after the reaction when the IoT sensor value will decrease from predefined threshold value than the chamber automatically closed. In this way, we reduce the problem of carbon emission of the cloud data center and also reduce the reaction cost i.e. reaction occurs when needed.
Prediction of Autism Spectrum Disorder Using Supervised Machine Learning Algorithms
Authors: Lakshmi Praveena T. , Muthu Lakshmi N. V.
Published: August 2021

Autism appears to be a neuro developmental disorder that is visible in the early years. It is a wide-spectrum disorder that indicates that the severity and symptoms can vary from person to person. The Centre for Disease Control found that one in 68 was diagnosed with autism spectrum disorder with increasing numbers in every year. Detection of autism in adults is a cumbersome procedure because in adults, many symptoms can blend with some other mental health, motor impairment disorders so misinterpretation of actual diseases can in turn lead to a terrible life without proper diagnosis and effective treatment mechanisms. Machine learning is a powerful computer tool that supports different application domains Learning complex relationships or patterns from large datasets to draw accurate conclusions. Disease assessment can be done with predictive health data analysis and more appropriate treatment mechanisms that are now a hot area of research. Supervised learning is an important step of Machine learning which uses a rule-based approach by examining empirical data sets to build accurate predictive models. In this paper, decision tree, random forest, SVM, neural networks algorithms are applied on autism spectrum data which have been collected from UCI repository. The results of decision tree, random forest, SVM, neural networks algorithms on autism dataset are presented in this paper in an efficient manner. Analysis performed over these accurate results which will be useful to make right decisions in predicting autism spectrum disorder (ASD) at early stages. Thus, early autism intervention using machine learning techniques opens up a new way for autistic individuals to develop the potential to lead a better life by improving their behavioural and emotional skills.
Data Replication Using Data Mining Techniques
Authors: Elango P. , Kuppusamy K. , Prabhu N.
Published: August 2021

Database Replication is the successive electronic duplicating of information from a database in one PC or server to a database in another with the goal that all clients share a similar dimension of data. The outcome is a conveyed database in which clients can get to information significant to their assignments without meddling with crafted by others. Anyway information replication is an entrancing theme for both hypothesis and practice. On the hypothetical side, numerous solid outcomes requirement what should be possible as far as consistency: e.g., the difficulty of achieving agreement in offbeat frameworks the blocking idea of CAP hypothesis, and the requirement for picking an appropriate rightness foundation among the numerous conceivable. On the pragmatic side, information replication assumes a key job in a wide scope of settings like storing, back-up, high accessibility, wide territory content dissemination, expanding versatility, parallel preparing, and so forth. Finding a replication arrangement that is reasonable in whatever number such settings as could reasonably be expected remains an open test.
FBSC: An Analyzing Sentiments Using Fuzzy Based Bayesian Classification
Authors: Karthica M. , Sudarmani P.
Published: August 2021

The thriving Micro blog service, Twitter, attracts more people to post their feelings and opinions on various topics. Millions of users share opinions on totally different aspects of life on a daily basis. It observing the user’s sentiment options topics in the twitter network. The sentiment classification is comparable to the user’s opinions that are based on dynamic manner. An optimal Fuzzy based Bayesian classification is a capable way that has been proposed to improve the classification accuracy, unless the large amount of information on these platforms make them viable for use as data sources, in applications based on sentiment analysis. The research work developed a Fuzzy based Bayesian sentiment classification (FBSC) based dynamic online twitter search data architecture that ensures truthful positive, negative and neutral results.
Study of Ensemble Classifier for Prediction in Health Care Data
Authors: Sathurthi S. , Kamalakannan R. , Rameshkumar T.
Published: August 2021

Electronic health record systems are adapted in a good deal of health care facility to improve the quality of patient care which is maintained electronically. Developing a disease prediction model for health care system can help us to overcome the problem of medical distress. In this study, we suggest ensemble technology and statistical methods to search through massive amounts of information, analyzing it to predict outcomes for individual patients. Using Weka tool, breast-cancer and diabetes medical datasets have experimented with ensemble classifier.