bluuebunny/crossref_metadata_2025 huggingface dataset:
ELEMENTOS NATURAIS QUE FUNDAMENTAM A CONSERVAÇÃO DAS SERRAS SEMIÁRIDAS DO CENTRO-OESTE CEARENSE
Authors: Gomes Raul Carneiro , Paiva Laura Gomes Girão , Oliveira Vládia Pinto Vidal de
Published: August 2021

Ocorrem, no Centro-Oeste do Ceará-Brasil, maciços estruturais denominados de serras secas que, em meio à degradação do pediplano adjacente, transformaram-se em espaços estratégicos para ao desenvolvimento social e para a conservação dos recursos hídricos, da fauna e da flora. Este estudo objetivou indicar os elementos naturais que fundamentam a conservação das serras secas, pretendendo subsidiar a sua proteção e o seu ordenamento territorial. Assim, executou-se levantamentos bibliográficos, geocartográficos e o reconhecimento dos componentes geoambientais em campo, obtendo dados sobre a flora, a fauna, os relevos, os recursos hídricos e seus processos interativos. Constatou-se que as serras examinadas têm vegetação de caatinga na qual se destaca a aroeira (Myracrodruon urundeuva) e são habitats de espécies faunísticas como: cassaco (Didelphis albiventris), tamanduá-mirim (Tamandua tetradactyla), onça-parda (Puma concolor), tatu (Tolypeutes tricinctus), peba (Euphractus sexcinctus) e veado catingueiro (Mazama gouazoupira) que são predados ou mortos. Os relevos oferecem limitações para a agropecuária devido à ocorrência de vertentes declivosas, às estruturas de fraturas e falhas que propiciam eventos de deslizamento e queda de blocos. Ademais, o desmatamento da caatinga arbórea-arbustiva potencializa a instabilidade das vertentes pela erosão laminar e concentrada nos Cambissolos Háplicos e Neossolos Litólicos, proporcionando o assoreamento de nascentes, rios e reservatórios hídricos.
O movimento dos pequenos agricultores e a luta em defesa das sementes crioulas no Alto Sertão Sergipano, Brasil
Authors: Amorim Lucas Oliveira do , Pereira Mônica Cox de Britto , Curado Fernando Fleury , Oliveira Lanna Cecília Lima de , De Vasconcelos Elielma Barros
Published: August 2021

O presente trabalho tem como objetivo analisar como o Movimento dos Pequenos Agricultores vem organizando sua luta em defesa das sementes crioulas no estado de Sergipe a partir de ações do Território do Alto Sertão Sergipano. As informações que foram analisadas neste trabalho partiram de leituras do Plano Camponês e do Plano Nacional de Sementes Crioula do MPA. Além disto, através da observação-participante, buscou-se vivenciar a realidade do Movimento durante o encontro de agricultores(as) guardiões e guardiãs das sementes crioulas (2016) no município de Poço Redondo/SE. O MPA vem realizando uma luta ampla contra o avanço do agronegócio no Alto Sertão Sergipano. Neste sentido, a defesa das sementes crioulas representa uma simbologia na resistência da agricultura camponesa, ao mesmo tempo que nos remete a um novo paradigma de desenvolvimento do campo baseado nos princípios da Agroecologia. Palavras-chave: Agrobiodiversidade, Movimentos Sociais, Agroecologia, Agronegócio.
Comparison of Mathematical Models for the layout of Granulometric Curves of Brazilian Soils
Authors: Soares Willames Albuquerque , Hammecker Claude
Published: August 2021

The particle size distribution of solid particles (PSD) is critical in determining the potential for compaction, the availability and the redistribution of water in the soil, especially in the areas of building material and soil mechanics, among others. However, many banks of soil data does not contain detailed PSD data, but only some fractions. A mathematical accurate representation of the PSD is required to estimate soil hydraulic properties and texture comparing measurements of different classification systems. The objective of this study was to compare the performance of 12 models, with 2 and 3 tuning parameters proposed in the literature to represent the PSD, and, predict the water retention curve in the soil, from a wide range of Brazilian soils textures. The statistical parameters (NDEs, RD, MS CRM) showed three models tuning parameters proposed by Lima & Silva, Weibull and Fredlund got the best performance, with lower NDE, RD, MS very close to one and CRM values very low. The models Lima & Silva, Weibul, Fredlund and Skaggs, with three tuning parameters, and the models Skaggs end Lima & Silva, with two parameters, proved to be suitable for estimate the water retention curve in the soil, for soils with coarse and fine texture. Keywords: Granulometry; Soil texture; Curve Adjustments.
A GESTÃO DA DISCIPLINA NUMA ESCOLA PORTUGUESA: AS OPINIÕES DOS ALUNOS
Authors: Gomes Carlos Alberto , Da Silva Guilherme Rego , E Silva Daniela Vilaverde
Published: August 2021

Resumo: No presente artigo apresentamos e analisamos um conjunto de resultados de investigação referentes a opiniões e posicionamentos de alunos do ensino básico (ensino fundamental no Brasil) de uma escola pública portuguesa, situada numa pequena cidade, em relação à aplicação do regulamento disciplinar. Os alunos expressaram os seus pontos de vista respondendo a um inquérito por questionário aplicado no final do ano letivo de 2013-2014. Numa leitura global, os resultados de investigação apontam para uma imagem de uma escola com um baixo nível de indisciplina, expressando uma conduta declaradamente convergente da maioria dos alunos em relação às normas (direitos e deveres) estabelecidas no referido regulamento. Todavia, uma leitura mais detalhada dos dados permite relativizar ou matizar a aparente harmonia do conjunto mostrando serem ainda assim bastante significativas as situações de clara inobservância das disposições regulamentares.
POLÍTICA DE INFRAESTRUTURA ESCOLAR: CONCEITO POSSÍVEL DE UM OBJETO EM CONSTRUÇÃO
Authors: Silva Ivanildo Santos da
Published: August 2021

Resultando de pesquisa de mestrado, neste trabalho desenvolvemos uma reflexão sobre o espaço escolar na perspectiva de sua infraestrutura e desta como um elemento central enquanto objeto por meio do qual seja possível desenvolver análises no campo das políticas educacionais. Neste sentido, nosso objetivo consiste em abordar a compreensão do que vem a ser política de infraestrutura escolar, enquanto um conceito que nos permita realizar sua caracterização como objeto de pesquisa. Para tanto, o conteúdo central deste artigo consiste numa discussão teórico-conceitual a partir de três de conhecimento: historiografia, arquitetura e política educacional. Como resultado deste arcabouço teórico, chegamos a uma definição conceitual que nos permite compreender a política de infraestrutura escolar como sendo o conjunto das ações do Estado referentes à dimensão da aquisição, reforma, adequação e construção de prédios escolares, seus equipamentos e mobiliários.
O Estudo de Caso Naturalista na investigação de Arranjos Produtivos Locais (APL) de Tecnologias de Informação e Comunicação (TIC)
Authors: Silva Anderson Diego Farias da , Fernandes Nelson da Cruz Monteiro , Paiva Junior Fernando Gomes de
Published: August 2021

O Estudo de Caso (EC) envolve um cenário conceitual divergente podendo ser utilizado em formas de pesquisa diversificadas no campo dos estudos organizacionais com respeito ao valor e à plausibilidade da aplicação desse método de investigação em Arranjos Produtivos Locais (APL). Neste ensaio teórico-metodológico, discutimos a interpelação conceitual do EC naturalista de Robert Stake em meio as suas possibilidades e limitações de uso, ilustradas por meio da análise do Arranjo Produtivo Local (APL) de Tecnologias de Informação e Comunicação (TIC) e Economia Criativa do Estado de Pernambuco (Brasil), denominado Porto Digital. Ao migrar de uma abordagem fundamentada na lógica da explicação de perspectiva funcionalista de Yin (2005) para o tratamento de Stake (2005), essa visão de estudo de caso naturalista representa a oportunidade para o desenvolvimento de estudos interpretativos que possibilitam o incremento do conhecimento relacionado à ambientes de negócios cooperativos contemplando as novas TIC.
Application of thermostable a-Amylase from Thermomyces lanuginosus ATCC 58157 to nutritionally enhance starch based food
Authors:   , Padayachee Thiriloshani
Published: August 2021

In Sub-Saharan Africa there is an urgent need to sustain and improve the quality of its food resources. Poverty eradication features high on the agenda of a number of world health organisations, while the number of underweight children in Africa continues to increase (Pellet, 1996). Providing nutritionally enhanced foods to the poor will help towards achieving this objective. Protein-energy malnutrition has been identified as one of the most important problems facing Africa, with maize as the staple diet (Nkama et al., 1995). However, a combination of several factors limits availability and the nutritional quality of maize. During starvation, energy and protein intakes decrease by 20-30%, with most of the children in Africa having an average protein intake of only 20 g per day (Igbedioh, 1996). Energy availability also affects protein utilization because of interrelationships of protein and energy metabolism (Elwyn, 1993). The diets of inhabitants in developing regions depend mainly on cereals (maize) for both protein and dietary energy which lacks indispensable amino acids, minerals, vitamins and carbohydrates. In light of these growing concerns an attempt was made to devise a scientific strategy to combat the nutritional shortfalls of maize meal. A multidisciplinary and concerted approach was followed within this project aimed at designing an improved thermostable amylase and applying the enzyme to nutritionally enhance maize meal. It was envisaged that the manipulation of maize meal, by the application of enzyme technology will improve the nutritional status of this staple food. The consequences is that an alternate solution for the eradication of an ailing, poverty stricken and malnourished African population is achievable. It is possible that the boundaries defining the limits of life will extend to even greater extremes through the application of novel technologies.
Assessing milk quality using the electronic nose
Authors:   , Govender Samantha
Published: August 2021

There are many ways for milk and dairy products to develop flavour defects. Sensory evaluation, has been the traditional approach to characterize off flavours. The need for odour sensing devices becomes greater when volatile and semi-volatile organic compounds are present in the product in parts per billion or even in the parts per trillion concentration range that cause off flavours. Today, sophisticated, sensitive instrumental tests such as electronic nose technology coupled with gas chromatography are capable of detecting, identifying and quantifying the specific chemical agents responsible for off flavours. This study focused on the use of the electronic nose as a novel technology for the detection and monitoring of milk quality by testing the effects of heat treatment at 63˚C and shelf life. Microbiological testing, sensory evaluation and gas chromatographic analysis were carried out together with aroma profiling using the electronic nose to determine milk quality.
UPAYA PENINGKATAN MOTIVASI BELAJAR DENGAN MENGGUNAKAN MODEL PEMBELAJARAN KOOPERATIF PENDEKATAN MIND MAPING PADA MATA PELAJARAN MENGGAMBAR TEKNIK DASAR
Authors: SURYANI SURYANI
Published: August 2021

Penelitian ini dilatar belakangi oleh fenomena bahwa mata pelajaran menggambar teknik dasar pada Kelas X Kompetensi keahlian Desain pemodelan dan Informasi bangunan SMK Negeri 2 Bone  memiliki tingkat kesulitan yang cukup tinggi. Selain aspek psikomotorik, yang lebih menyulitkan adalah aspek kognitif pada mata pelajaran tersebut. Banyak siswa yang kesulitan memaknai materi pembelajaran dengan baik. Diduga salah satu penyebabnya adalah karena proses pembelajaran hanya berpusat pada guru, sehingga siswa tidak ikut terlibat secara aktif dalam proses belajar mengajar tersebut. Hal ini berdampak pada rendahnya  interaksi antara guru dan siswa maupun antara siswa.. Penelitian ini bertujuan melakukan perbaikan proses pembelajaran dengan harapan jika proses membaik maka akan terjadi peningkatan prestasi belajar. Penelitian ini berjenis penelitian tindakan kelas, dilaksanakan di SMK Negeri 2 Bone, padal kelas X Kompetensi keahlian desain pemodelan dan informasi bangunan semester ganjil tahun pelajaran 2019/2020.Pada penelitian ini secara faktual terlihar bahwa penggunaan pendekatan model mind mapping terbukti  efektif sebagai pendekatan model pembelajaran untuk membantu siswa dalam memahami konsep konsep dan mengkotekstualisasikan konsep konsep yang dipahami.Hal ini terlihat dari peningkatan berbagai aspek yang diobservasi sepanjang siklus1 hingga siklus 3 dalam penelitian tindakan kelas ini. Aspek kerja sama antar siswa meningkat sebesar 47,5%, aspek interaksi dengan guru meningkat sebesar 60,6%. Pada aspek tanggung jawab mengalami peningkatan 51,52%, dan ikuti penigkatan pada aspek kehadiran sebesar 3.04%. Sebagai konsekoensi logis dari membaiknya proses pembelajaran, rata rata prestasi belajar siswa juga mengalami peningkatan sebesar 29, 14%.
Geometric estimation of volcanic eruption column height from GOES-R near-limb imagery – Part 1: Methodology
Authors: Horváth Ákos , Carr James L. , Girina Olga A. , Wu Dong L. , Bril Alexey A. , Mazurov Alexey A. , Melnikov Dmitry V. , Hoshyaripour Gholam Ali , Buehler Stefan A.
Published: August 2021

Abstract. A geometric technique is introduced to estimate the
height of volcanic eruption columns using the generally discarded near-limb
portion of geostationary imagery. Such oblique observations facilitate a
height-by-angle estimation method by offering close-to-orthogonal side views of eruption columns protruding from the Earth ellipsoid. Coverage is
restricted to daytime point estimates in the immediate vicinity of the vent, which nevertheless can provide complementary constraints on source
conditions for the modeling of near-field plume evolution. The technique is best suited to strong eruption columns with minimal tilting in the radial
direction. For weak eruptions with severely bent plumes or eruptions with
expanded umbrella clouds the radial tilt/expansion has to be corrected for
either visually or using ancillary wind profiles. Validation on a large set
of mountain peaks indicates a typical height uncertainty of ±500 m
for near-vertical eruption columns, which compares favorably with the
accuracy of the common temperature method.
Measurement report: Saccharide composition in atmospheric fine particulate matter during spring at the remote sites of southwest China and estimates of source contributions
Authors: Wang Zhenzhen , Wu Di , Li Zhuoyu , Shang Xiaona , Li Qing , Li Xiang , Chen Renjie , Kan Haidong , Ouyang Huiling , Tang Xu , Chen Jianmin
Published: August 2021

Abstract. Based on source-specific saccharide tracers, the characteristics
of biomass burning (BB) and biogenic emissions of saccharides were
investigated in three rural sites at Lincang, which is 65 % covered with forest in the southwest border of China. The total saccharides accounted for
8.4 ± 2.7 % of organic carbon (OC) and 1.6 ± 0.6 % of
PM2.5. The measured anhydrosugars accounted for 48.5 % of total
saccharides, among which levoglucosan was the most dominant species. The
high level of levoglucosan was both attributed to the local BB activities
and biomass combustion smoke transported from the neighboring regions of
Southeast Asia (Myanmar) and the northern Indian subcontinent. The measured
mono- or disaccharides and sugar alcohols accounted for 24.9 ± 8.3 %
and 26.6 ± 9.9 % of the total saccharides, respectively, and both
proved to be mostly emitted by direct biogenic volatilization from plant
material or surface soils rather than byproducts of polysaccharide breakdown
during BB processes. Five sources of saccharides were resolved by
non-negative matrix factorization (NMF) analysis, including BB, soil
microbiota, plant senescence, airborne pollen, and plant detritus with
contributions of 34.0 %, 16.0 %, 21.0 %, 23.7 %, and 5.3 %,
respectively. The results provide information on the magnitude of
levoglucosan and contributions of BB, as well as the characteristic of
biogenic saccharides, at the remote sites of southwest China, which can be
further applied to regional source apportionment models and global climate
models.
Kinetics and impacting factors of HO2 uptake onto submicron atmospheric aerosols during the 2019 Air QUAlity Study (AQUAS) in Yokohama, Japan
Authors: Zhou Jun , Sato Kei , Bai Yu , Fukusaki Yukiko , Kousa Yuka , Ramasamy Sathiyamurthi , Takami Akinori , Yoshino Ayako , Nakayama Tomoki , Sadanaga Yasuhiro , Nakashima Yoshihiro , Li Jiaru , Murano Kentaro , Kohno Nanase , Sakamoto Yosuke , Kajii Yoshizumi
Published: August 2021

Abstract. HO2 uptake kinetics onto ambient aerosols play pivotal roles in
tropospheric chemistry but are not fully understood. Field measurements of
aerosol chemical and physical properties should be linked to molecular-level kinetics; however, given that the HO2 reactivity of ambient aerosols is
low, traditional analytical techniques are unable to achieve this goal. We
developed an online approach to precisely investigate the lower-limit values of (i) the HO2 reactivities of ambient gases and aerosols and (ii) HO2 uptake coefficients onto ambient aerosols (γ) during the 2019 Air QUAlity Study (AQUAS) in Yokohama, Japan. We identified the effects of individual chemical components of ambient aerosols on γ. The results were verified in laboratory studies on individual chemical components: transition
metals play a key role in HO2 uptake processes, and chemical components indirectly influence such processes (i.e., by altering
aerosol surface properties or providing active sites), with smaller
particles tending to yield higher γ values than larger particles
owing to the limitation of gas-phase diffusion being smaller with micrometer particles and the distribution of depleting species such as transition metal
ions being mostly distributed in accumulation mode of aerosol. The modeling of γ utilized transition metal chemistry derived by previous studies,
further confirming our conclusion. However, owing to the high NO
concentrations in Yokohama, peroxy radical loss onto submicron aerosols has
a negligible impact on O3 production rate and sensitivity regime.
Measurement of Black Carbon Emissions from Multiple Engine and Source Types using Laser-Induced Incandescence: Sensitivity to Laser Fluence
Authors: Yuan Ruoyang , Lobo Prem , Smallwood Greg J. , Johnson Mark P. , Parker Matthew C. , Butcher Daniel , Spencer Adrian
Published: August 2021

Abstract. A new regulatory standard for non-volatile particulate matter (nvPM) mass concentration emissions from aircraft engines has been adopted by the International Civil Aviation Organisation. One of the instruments used for the regulatory nvPM mass emissions measurements in aircraft engine certification tests is the Artium Technologies LII 300, which is based on laser-induced incandescence. The LII 300 has been shown in some cases to demonstrate a variation in response to the type of black carbon particle measured. Hence it is important to identify a suitable black carbon emission source for instrument calibration. In this study, the relationship between the nvPM emissions produced by different engine sources and the response of the LII 300 instrument utilising auto-compensating laser-induced incandescence (AC-LII) method was investigated. Six different sources were used, including a turboshaft helicopter engine, a diesel generator, an intermediate pressure test rig of a single sector combustor, an auxiliary power unit gas turbine engine, a medium-sized diesel engine, and a downsized turbocharged direct injection gasoline engine. Optimum LII 300 laser fluence levels were determined for each source and operating condition evaluated. It was found that an optimised laser fluence can be valid for real-time measurements from a variety of sources, where the mass concentration was independent of laser fluence levels covering the typical operating ranges for the various sources. However, it is important to perform laser fluence sweeps to determine the optimum fluence range, as differences were observed in the laser fluence required, between sources and fuels. We discuss the measurement merits, variability, and best practices in the real-time quantification of nvPM mass concentration using the LII 300 instrument, and compare that with other diagnostic techniques, namely absorption–based methods such as photoacoustic spectroscopy using a photoacoustic extinctiometer (PAX) and a Micro Soot Sensor (MSS), and thermal-optical analysis (TOA). Particle size distributions were also measured using a scanning mobility particle sizer (SMPS). Overall, the LII 300 provides robust and consistent results when compared with the other diagnostic techniques across multiple engine sources and fuels. The results from this study will inform the development of updated calibration protocols to ensure repeatable and reproducible measurements of nvPM mass emissions from aircraft engines using the LII 300.
NEEM to EastGRIP Traverse – spatial variability, seasonality, extreme events and trends in common ice core proxies over the past decades
Authors: Kjær Helle Astrid , Zens Patrick , Black Samuel , Lund Kasper Holst , Svensson Anders , Vallelonga Paul
Published: August 2021

Abstract. Greenland ice cores provide information about past climate. However, the number of firn and ice cores from Greenland are limited and thus the spatial variability of the chemical impurities used as proxies is largely unconstrained. Furthermore, few impurity records covering the past two decades exist from Greenland. We have by means of Continuous Flow analysis investigated 6 shallow firn cores obtained in Northern Greenland as part of the NEEM to EastGRIP traverse in 2015. The oldest reach back to 1966. The annual mean and quartiles of the insoluble dust, ammonium, and calcium concentrations in the 6 firn cores spanning a distance of 426 km overlap, and also the seasonal cycles have similar peaks in timing and magnitude across sites. Peroxide (H2O2) is accumulation dependent and varies from site to site and conductivity, likely influenced by sea salts, also vary spatially. The temporal variability of the records is further assessed. We find no evidence for increases in total dust concentration, but find an increase in the large dust particle fluxes that we contribute to an activation of Greenland local sources in the recent years (1998–2015). We observe the expected acid and conductivity increase in the mid 70’s as a result of anthropogenic contamination and the following decrease due to mitigation. After detrending using the five year average the conductivity and acid records several volcanic horizons were identified and associated with Icelandic eruptions and volcanic eruptions in the Barents sea region. By creating a composite based on excess ammonium compared to the five year running average, we obtain a robust forest fire proxy associated primarily with Canadian forest fires (R = 0.51). We also note that the peak ammonium in the individual firn cores appear more scattered between cores than the peak volcanic layers, suggesting that the forest fire signal is more dispersed in the atmosphere than the acid from volcanic eruptions.
A new sea ice state dependent parameterization for the free drift of sea ice
Authors: Brunette Charles , Tremblay L. Bruno , Newton Robert
Published: August 2021

Abstract. Free drift estimates of sea ice motion are necessary to produce a seamless observational record combining buoy and satellite-derived sea ice motion vectors. We develop a new parameterization for the free drift of sea ice based on wind forcing, wind turning angle, sea ice state variables (concentration and thickness) and ocean current (as a residual). Building on the fact that the spatially varying standard wind-ice transfer coefficient (considering only surface wind stress) has a structure as the spatial distribution of sea ice thickness, we introduce a wind-ice transfer coefficient that scales linearly with thickness. Results show a mean error of −0.5 cm/s (low-speed bias) and a root-mean-square error of 5.1 cm/s, considering daily buoy drift data as truth. This represents a 31 % reduction of the error on drift speed compared to the free drift estimates used in the Polar Pathfinder dataset. The thickness-dependent wind transfer coefficient provides an improved seasonality and long-term trend of the sea ice drift speed, with a minimum (maximum) drift speed in May (October), compared to July (January) for the constant wind transfer coefficient parameterizations which simply follow the peak in mean surface wind stresses. The trend in sea ice drift in this new model is +0.45 cm/s decade−1 compared with +0.39 cm/s decade−1 from the buoy observations, whereas there is essentially no trend in the standard free drift parameterization (−0.01 cm/s decade−1) or the Polar Pathfinder free drifts (−0.03 cm/s decade−1). The wind turning angle that minimize the cost function is equal of 25°, with a mean and root-mean square error of +2.6° and 51° on the direction of the drift, respectively. The residual from the minimization procedure (i.e. the ocean currents) resolves key large scale features such as the Beaufort Gyre and Transpolar Drift Stream, and is in good agreement with ocean state estimates from the ECCO, GLORYS and PIOMAS ice-ocean reanalyses, and geostrophic currents from dynamical ocean topography, with a root-mean-square difference of 2.4, 2.9, 2.6 and 3.8 cm/s, respectively. Finally, a repeat of the analysis on a two sub-section of the time series (pre- and post-2000) clearly shows the acceleration of the Beaufort Gyre (particularly along the Alaskan coastline) and an expansion of the gyre in the post-2000 concurrent with a thinning of the sea ice cover and observations acceleration of the ice drift speed and ocean current. This new dataset is publicly available for complementing merged observations-based sea ice drift datasets that includes satellite and buoy drift records.
A Review Paper on Image Inpainting and their Different Techniques
Authors: Joshi Pranjali , Shrivastav Neeraj
Published: August 2021

Image Inpainting is an art of modifying the digital image in such a way that the modifications are undetectable to an observer who has no idea about the original image. The essential thought behind the system is to consequently fill in lost or missing parts of a picture utilizing data from the encompassing region. It is utilized for rebuilding of old movies and protest expulsion in computerized photos. Different calculations have introduced in the past to accomplish the undertaking of picture inpainting. In this paper we give a survey of various systems utilized for picture Inpainting. We talk about various inpainting systems like Wavelet Transform inpainting, Exemplar based picture inpainting, PDE based picture inpainting, surface combination based picture inpainting.
Reducing the Frequent Switch Over between the Base Stations through Continuous Analysis of Signal Strength
Authors: Regitha M. R. , Paul Varghese
Published: August 2021

As the increase in the number of mobiles and mobile networks, the existing standards and technologies face several issues and challenges. In the mobility management of cellular networks, HO is the important parameter on which these issues and challenges affect drastically. Several research papers have proposed many ideas and schemes to reduce HO latency. As the increase in the number new technologies and networks, the existing ideas are no longer supported efficiently. So a continuous analysis on handover (HO) procedure is required. Signal strength (SS) and quality of service (QoS) are measured at particular time intervals in cellular networks. Results show that the highest value of signal strength has the best quality of service. In this paper, a continuous analysis on signal strength received by the mobile station (MS) is used to monitor the HO process to reduce the HO delay. In this analysis, the parameters user movement pattern, topological position, signal strength and time are used which will be helpful to forecast the HO in advance. Using HO forecast minimum number of frequent switch over between the base stations (BSs) reduces the HO latency in mobile networks.
Information Technology Service Management [ITSM] Research: A Literature Review of Practices, Solutions and Measurement
Authors: Jain Vipul , Wali O. P. , Raveendra Saradhi V.
Published: August 2021

This is a systematic literature review to understand the adopted practices, proposed solutions and measurement models for Information Technology Service Management [ITSM] approaches. This paper extends the existing research and past literature reviews in this area by including recent published research from 2010 to 2018. The review finds that ITSM practices are not uniformly adopted, and some processes tend to be adopted more widely than others. The review also finds many measurement models that are either not validated, or only partially validated, and sees a gap between academic research and practitioner community, who are the primary intended users of these models and frameworks. There are proposed solutions for ITSM integration with other management systems that can benefit from further research for validation. We recommend future researchers to collaborate with practitioners, so that proposed models and frameworks can be incorporated into the relevant standards, where feasible.
Hybrid Privacy Preserving Mechanism: An Approach to ProtectHealth Care Data
Authors: Rameshkumar M. , Lakshmipraba V.
Published: August 2021

With a lot of clinical information produced regularly, efficient methods have to be used to unearth significant data. Securing the information from the unapproved clients is also a major task to be achieved. Though lot of research has been carried out in these areas separately, a Hybrid architecture which combines both the features – efficiency and security is not widely found. The proposed architecture has been built taking these aspects into consideration. A proficient strategy for cross breed information mining method is applied here which incorporates the combination of Navie Bayesian classifier and Homomorphic encryption calculation.
Visual Encryption Using Multilevel Scrambling Followed by Affine Encryption Technique
Authors: Sharma Piyali , Bhatpahri Pramay , Patnaik Ravi Kiran , Shrivastava Ravi
Published: August 2021

In the present paper, we report an effective method of multilevel scrambling followed by affine encryption, which may be used as one of the useful tools in visual cryptography. A sample image is scrambled for six times using a specific algorithm. Toner distributions of scrambled images were studied using their histograms. The results of histogram expressed that the effectiveness of scrambling increased with its increasing stages and it becomes almost ideal when the image after affine encryption is taken. In order to judge the complexity level of scrambling, horizontal & vertical correlation of adjacent pixels and Information Entropy of different scrambled images were also calculated. Values of horizontal & vertical correlation and information entropy reflected that the complexity and randomness of pixels increase with increasing stages of scrambling. It also indicated that the randomness doesn’t change much after the fifth stage of scrambling and affine encryption enhanced the level of security by a large extent.
A Brief Survey on Nature Inspired Algorithms: Clever Algorithms for Optimization
Authors: Sindhuja P. , Ramamoorthy P. , Suresh Kumar M.
Published: August 2021

This paper presents a brief survey on various optimization algorithms. To be more precise, the paper elaborates on clever Algorithms – a class of Nature inspired Algorithms. The Nature Inspired Computing (NIC) is an emerging area of research that focuses on Physics and Biology Based approach to the Algorithms for optimization. The Algorithms briefed in this paper have understood, explained, adapted and replicated the phenomena of Nature to replicate them in the artificial systems. This Cross – fertilisation of Nature Inspired Computing (NIC) and Computational Intelligence (CI) will definitely provide optimal solutions to existing problems and also open up new arenas in Research and Development. This paper briefs the classification of clever algorithms and the key strategies employed for optimization.
Optimization of Microblog Representation Using Deep Learning Approach
Authors: Walse K. H.
Published: August 2021

Microblogging, as a new form of online communication in which users talk about their daily lives, to gather real-time news, opinion about people or share information by short posts, has become one of the most popular social networking services today, e.g. to stay in touch with friends . Finding proper representations of microblog texts is a challenging issue. The overview of microblog included how to extract information from microblog, also discuss about Microblogging and Twitter. This paper included existing research on Optimization of Microblog Representation by using existing techniques and methods as well as microblogging services.Current approaches, for microblog reduction are single indexing. In this work, we have proposed double indexing method for microblog reduction. We have used our own generated dataset for microblog reduction. We have collected tweets from real time twitter for both single and double indexing technique. Also, we have use LDA with Semantic Similarity algorithm. We compared our results with single indexing. Experimental results shows that double indexing gives better performance than single indexing. This may happen because we will show both original and reduced tweets, so it will be known to user which tweet are removed and relevant part shows as output. We have also compared our results with the state-of-art. The proposed double indexing gives better performance than existing 1-ROCA of improved online SVM technique.
Performance of Speaker Verification Using CSM and TM
Authors: Sathiamoorthy S. , Ponnusamy R. , Visalakshi R.
Published: August 2021

In this paper, we presented the performance of a speaker verification system based on features computed from the speech recorded using a Close Speaking Microphone(CSM) and Throat Microphone(TM) in clean and noisy environment. Noise is the one of the most complicated problem in speaker verification system. The background noises affect the performance of speaker verification using CSM. To overcome this issue, TM is used which has a transducer held at the throat resulting in a clean signal and unaffected by background noises. Acoustic features are computed by means of Relative Spectral Transform-Perceptual Linear Prediction (RASTA-PLP). Autoassociative neural network (AANN) technique is used to extract the features and in order to confirm the speakers from clean and noisy environment. A new method is presented in this paper, for verification of speakers in clean using combined CSM and TM. The verification performance of the proposed combined system is significantly better than the system using the CSM alone due to the complementary nature of CSM and TM. It is evident that an EER of about 1.0% for the combined devices (CSM+TM) by evaluating the FAR and FRR values and the overall verification of 99% is obtained in clean speech.
Image Denoising for the Detection of Follicle in Polycystic Ovarian Syndrome Images
Authors: Saravanan A. , Sathiamoorthy S.
Published: August 2021

Polycystic Ovarian Syndrome is an endocrine ailment affecting women of reproductive age. This syndrome is largely found in women whose age is in between 25 and 35. Without knowing the accurate region of a follicle in ovary, the hazard rigorousness of the patient cannot be exposed. Since, super-pixels can be functional on segmentation and image representation, it has turned out to be essential for refining the competence in computer vision systems. Thus, in this paper, a novel image denoising methodology for the detection of a follicle in the PCOS has been suggested by exploring the super-pixel clustering and Fuzzy C means clustering.
Classification of Leukemia Image Using Genetic Based K-Nearest Neighbor (G-KNN)
Authors: Bennet Rajesh M. , Sathiamoorthy S.
Published: August 2021

In medical diagnostic system, classification of blood cell is more vigorous to identify the disease. The diseases which are connected with blood is alienated after the categorization of blood cell. Leukemia, a blood cancer that begins in bone marrow. Hence, it must be cured at initial stage and leads to death if left untreated. This paper introduces median filter for noise removing and Genetic based kNN for classification of Leukemia image datasets and features are extracted using gray-level co-occurrence matrix. The outcome of proposed genetic algorithm based kNN is compared with multilayer perceptron and support vector machine. The experimental outcomes evident that proposed combination performs better than the existing approach.
A Novel Pre-Processing Approach for the Denoising of Alzheimer Disease Image Dataset
Authors: Natarajan M. , Sathiamoorthy S.
Published: August 2021

Medical imaging doing an indispensable part in the area of medicine. Noise in the image is maddening as it worsens the quality of image. Thus, removal of noise is perpetually a problematic work in the images of all domain. Alzheimer’s disease, a neurological dysfunction in which destruction of cells in brain creates mental weakening and memory loss. The distinguished reason for Alzheimer’s disease is low brain activity and low blood flow. We proposed a framework for removal of noise in Alzheimer disease image using histogram equalization, thresholding, open morphological operation and a wavelet transform. This framework reduces the noise and significantly better than the existing methods used for Alzheimer disease images.
E-Era of Jurisdiction:Empowering Traditional Courts Using Various Artificial Intelligence Tools
Authors: Dafauti Balam Singh
Published: August 2021

In Indian scenario, we are still in the transformation phase from manual to electronic data processing. We are in balanced combination of simple, moral, responsive and transparent governance and IT tools and techniques. However a lot of scope is still there to do more and to imply IT in various governmental departments and domains. In the same sequence we can use artificial intelligence along with cloud computing to improve Indian Judicial system. Or we can say that the concept of e-courts can be enhanced by implying AI tools and techniques. The judiciary is in the early stages of a transformation in which AI (Artificial Intelligence) technology will help to make the judicial process faster, cheaper, and more predictable without compromising the integrity of judges’ discretionary reasoning. In this paper I have proposed a solution where judicial system with AI contributes to a process that encompasses such a wide range of knowledge, judgment, and experience. It have two more practical goals: producing tools to support judicial activities, including programs for intelligent document assembly, case retrieval, and support for discretionary decision-making; and developing new analytical tools for understanding and modeling the judicial process.
An Efficient Proposed Approach of Dynamic Clustering for Target Tracing in Wireless Sensor Networks
Authors: Ray Manas Kumar , Roy Gitanjali
Published: August 2021

This paper proposes and evaluates decentralized dynamic clustering algorithm for tracing a movable target. Here firstly we proposed dynamic K mean clustering algorithm. In this algorithm a fixed number of sensor nodes is choose and then cluster is created. When the cluster is created then a cluster head (CH) is active. This active CH sensor nodes will create new cluster and that new cluster is also formed a new mean value of cluster head. But, the newly created cluster is only active when a moving objected is trace. According from the position of cluster head, few sensor nodes is active, where as few sensor nodes are inactive. According from the CH nodes newly cluster is created. So, creation of dynamic cluster is less energy efficient and stability of cluster will more than static cluster with sensor nodes. On the other hand, movable object tracing sensor nodes are familiar with energy utilization of sensor nodes. Here we proposed an energy efficient target tracing approach which follow network stability as well as energy saving. As we use dynamic clustering technique, so optimization of energy each sensor nodes with cluster head is maximum. So all the sensors with cluster head sensor nodes will continue more time for object tracing. In simulation result we show that our proposed dynamic K mean clustering algorithm is more accurate and more stable.
Cisco Secured Virtual Private Networks: A Review
Authors: Khan Yusera Farooq
Published: August 2021

Now-a-days the significance of security has been greater than before because of the fact that data has been accessed and transferred through public network. The data which has been transferred could be sniffed which may be a loss for us. When data is transferred in to public network we need confidentiality, integration and authentication. In this review paper we will discuss all these factors that keep our data safe enough. In order to provide this factor a site-to-site virtual private network has been designed which provide more security to data and made the public network into private network. The virtual private network hides the source and destination address as well as it also hides the internal network so that our network would be safe enough.
Convergence Study of Biogeography Based Optimization
Authors: Mishra D. K. , Shinde Vikas , Wadhwa Kamal , Chaudhary Sanjay
Published: August 2021

Biogeography based optimization BBO is a progressive algorithm. It is induced by Biogeography. BBO is more powerful algorithm among the biology based optimization methods. In this paper examines the convergence of BBO algorithm on some fitness functions. BBO algorithm handles the best solution from one off spring to the next converges to the universal optimum. The convergence rate evaluate of BBO algorithm by simulation for some fitness function. A set of 12 standard benchmark function performance of convergence is studied by BBO algorithm.
Personalization of E-Learning Systems: Determination of Most Preferred Learning Style Using Conjoint Analysis
Authors: Saul Nicholas J. , Sagayaraj Francis F.
Published: August 2021

Identifying user preferences is a very important activity before offering a suggestion or a product. E-learning systems also follow suit in identifying the user preferences of learning style before offering the e-learning contents. There are several methods discussed in the literature for identifying the user preferences for e-learning contents. This paper presents a new method for the same purpose. The core of the new method is Conjoint Analysis, which is based on the type of the contents, preferred volume for each type of content and the ranking for the various combinations of the contents and their preferred volumes. The outcome of this method is the most preferred learning style of an individual learner.
Construction of Lexicons to Perk Up Re-Clustering
Authors: George Louis Raja A. , Sagayaraj Francis F. , Sugumar P.
Published: August 2021

The existing semantic methods cluster the documents based on unabridged or abridged term comparisons. After clustering, these terms are not preserved, costing the cluster operation to be repeated in its entirety upon the arrival of new documents. Hence the semantic clustering methods can be considered as “on the go” methods. Re-clustering becomes unavoidable in all circumstances both in the Iterative and Incremental Clustering Methods. It would be more appropriate to build and evolve a lexicon with the derived keywords of the documents and to refer them in further cluster operations. The rationale is to deny re-clustering upon new documents and refer the Lexicon to formulate clusters until the quality of clusters is intact, and when it breaks above the threshold, the cluster operation can be repeated. Since re-clustering is delayed until a breakeven point, the process of re-clustering becomes faster. This process may incur additional runtime complexity, but would extremely simplify and speed up the process of re-clustering. This paper discusses about the construction of lexicons and its applications in clustering. The Keyword based Lexicon Construction Algorithm (KBLCA) is demonstrated to build lexicons and the breakeven point for re-clustering is proposed and described. The theory of denying re-clustering is briefed, along with experimental results.
Performance Evaluation of VGG models in Detection of Wheat Rust
Authors: Singh Rajwinder , Rana Rahul , Singh Sunil Kr.
Published: August 2021

The agricultural sector is the backbone of Indian economy and social development but due to lack of awareness towards crop management, a large number of crops get wasted each year. Automated Systems are required for this purpose. This paper tries to highlight the efficiency of two existing models of deep learning, VGG16 and VGG19 for proper detection of wheat rust disease in the infected wheat crop. These two models use convolutional neural networks for image classification and which can be used to design an intelligent system which can easily detect wheat rust in crop images. This paper basically presents the comparative analysis of the accuracy and efficiency along with usability to select the best model for systems that can be used for crop safety.
Finding Relationship among Various Students’ Attributes with Sport-Interest using Association Rule Mining Method
Authors: Gour Sanjeev
Published: August 2021

Data mining methods are widely used in educational domain for the purpose of finding useful information from the large student’s database. This information is then used to understand the behaviors of students in respect of their academic and other curricular performance. One of such Data mining methods called Association rule mining is used in this research study to analyze the student’s database of Career College Bhopal using two mining tools called Weka and XLMiner. The database contain records of 212 students with main attributes like Student’s Gender, Category, Subject, name of district where he/she belong and their parent’s/guardian’s occupation/profession and sport-interest. Sport department of any educational institute also need to understand the behavior and psychology of students for their sport interest to make sport-policy for their institute. In this paper, author has found some unknown relationship among these attributes with respect to sport-interest which is a target attribute. This experimental study has generated many association rules that can be used to answer the questions like which student from particular course, district and category will participate in sports? Which sport usually prefer by male and female student most? Which student can be performed better in which sport? In this way sport policy maker can use these mined information about the sport interest of students to make better decisions in sport framework in an educational institute.
Prediction Algorithms: A Study
Authors: Santha Subbulaxmi S. , Arumugam G.
Published: August 2021

Prediction algorithms make a prognosis of the future in a scientific way by analysing the data. They are being applied successfully to the problems in various fields and find good solutions. The objective of this paper is to describe about prediction algorithms and present the literature growth on it. It details the prediction process. It outlines the different types of prediction algorithms and the relevant publications on it. The paper summarizes the advantages & disadvantages of the prediction algorithms and the challenges to be addressed in the prediction field.