bluuebunny/crossref_metadata_2025 huggingface dataset:
Dietary modulation of the human colonic microbiota through plant-derived prebiotic compounds
Authors:   , Kassim Muhammad Arshad
Published: August 2021

The human gut microbiota play a major role in host health, and attempts are being made to manipulate the composition of the gut microbiota-increase the composition of bacterial groups, such as lactobacilli and bifidobacteria that are perceived as exerting health promoting properties. These bacteria defined as food supplements (probiotics) beneficially affect the host by improving the intestinal microbial balance, and have been used to change the composition of the colonic microbiota. However, such changes may be transient, and the implantation of exogenous bacteria therefore becomes limited. In contrast, prebiotics are naturally occurring carbohydrates that are classified as non-digestible oligosaccharides present in edible plants. These carbohydrates enter the colon as intact compounds, elicit systemic physiological functions and act as fermentable substrates for colonic microflora-influencing the species composition and metabolic characteristics of intestinal microflora providing important health attributes. Currently, a widely marketed prebiotic, inulin is extracted from plants of the family Asteraceae. There are many unexploited plants that are regularly consumed and that may have a prebiotic effect or can have very high levels of inulin which could make them commercially viable. In this study, we investigated prebiotic compounds, especially inulin from locally growing, non-commercialised leafy plants. The aqueous extracts of 22 plants from the families Asparagaceae, Alliaceae, Asteraceae, Solanaceae, Cucurbitaceae, Amaranthaceae, Acanthaceae, Polygonaceae, Portulaceae, Fabaceae, Chenopodiaceae, Pedaliaceae and Apiaceae from Kwa-Zulu Natal were investigated for a prebiotic effect using a modified batch-culture technique with Lactobacillus bulgaricus, Lactobacillus lactis, Lactobacillus reuteri and Bifidobacterium longum, four common probiotics and the inulin content of the plants was determined using high performance liquid chromatography. Of the 22 plants studied, Solanum nigrum, Amaranthus spinosus, Amaranthus hybridus, Asystasia gangetica, Senna occidentalis, Cerathoteca triloba, Asparagus sprengeri, Tulbaghia violacea, Sonchus oleraceus and Taraxacum officinale exhibited a prebiotic effect. The prebiotic effect of the Taraxacum officinale, Sonchus oleraceus and Asparagus sprengeri extracts on L. lactis and L. reuteri was higher than or equivalent to inulin-a commercial prebiotic. In this study, Sonchus oleraceus exhibited the best prebiotic effect-was the only plant to stimulate all the probiotics including B. longum. Of all the plants analysed, Asparagus sprengeri tuber contained the highest amount of inulin (3.55%).
The evaluation of liquid hydrocarbon contamination of soil around petrochemical tank farms at a Durban refinery
Authors:   , Ramluckan Krishan
Published: August 2021

The primary objective of this study was to determine the levels of liquid hydrocarbon contamination present in the soil within the SAPREF refinery. The secondary objective arising from this was the development of a gas chromatographic (GC) method using a fifty metre PONA (Paraffin, Olefin, Naphthalene and Aromatic) capillary column and the split injection technique, for the analysis. Toluene was the solvent selected, with the Standard method for the BÜCHI extraction system, to extract the hydrocarbons present in the soil samples taken at the five different tank farm sites in the refinery. The main purpose of the analysis and evaluation was to enable the refinery to establish environmental control measures to reduce the contamination of the soil in the area.
HIỆN TRẠNG SẢN XUẤT VÀ XỬ LÝ CHẤT THẢI TRONG CHĂN NUÔI GÀ TẠI HUYỆN PHÚ LƯƠNG, TỈNH THÁI NGUYÊN
Authors: Hoàng Thị Thanh Hương , Hà Minh Tuân , Liêu Thanh Hùng , Phạm Thị Hương , Dương Hồng Việt , Trần Hải Đăng , Bùi Ngọc Sơn
Published: August 2021

Nghiên cứu này được triển khai nhằm đánh giá thực trạng chăn nuôi và xử lý chất thải chăn nuôi gà tại huyện Phú Lương, tỉnh Thái Nguyên. Nghiên cứu được triển khai trong tháng 10/2020 thông qua phỏng vấn trực tiếp cá nhân đối với 90 hộ dân tại hai xã Phấn Mễ và Động Đạt. Kết quả nghiên cứu cho thấy, quy mô chăn nuôi gà của các hộ là quy mô nhỏ, khoảng 1.200 con/hộ và chuồng trại chăn nuôi chủ yếu nằm trong khu dân cư. Đa số các hộ có áp dụng biện pháp xử lý chất thải chăn nuôi gà nhưng hiệu quả chưa cao, gây ô nhiễm môi trường và có ảnh hưởng xấu tới sức khỏe người dân. Các biện pháp xử lý chất thải chăn nuôi gà phổ biến nhất là phun chế phẩm sinh học xử lý mùi hôi vào chuồng nuôi và sử dụng đệm lót sinh học. Người dân tiếp cận thông tin về các biện pháp xử lý môi trường chăn nuôi phần lớn thông qua tập huấn. Kênh học hỏi thông qua nhóm sản xuất và thông qua công ty liên kết là rất thấp. Kết quả nghiên cứu sẽ là căn cứ hữu ích để các cơ quan liên quan và người chăn nuôi có hành động phù hợp nhằm bảo vệ môi trường, sức khỏe của người chăn nuôi và vật nuôi tại địa phương.
NGHIÊN CỨU ĐẶC ĐIỂM DỊCH TỄ BỆNH CÚM GIA CẦM VÀ XÁC ĐỊNH TỶ LỆ TIÊM PHÒNG VACXIN H5N1 NAVET-VIFLUVAC CHO ĐÀN GIA CẦM TẠI TỈNH QUẢNG NINH
Authors: Nguyễn Quang Tính , Trần Trường Thái
Published: August 2021

Kết quả nghiên cứu cho thấy, trong giai đoạn 2015-2020 tỉnh Quảng Ninh luôn xảy ra dịch cúm gia cầm; tuy nhiên, các ổ dịch chỉ xảy ra với quy mô nhỏ lẻ tại 1 số huyện, thành, thị. Dịch chủ yếu xảy ra vào vụ Đông - Xuân với 91,46% số gia cầm mắc cúm và 90,71% số gia cầm chết và tiêu hủy do cúm đều ghi nhận trong mùa vụ này; chỉ có 8,54% số gia cầm mắc bệnh và 9,81% số gia cầm chết và tiêu hủy do cúm vào vụ Hè – Thu;  tỷ lệ mắc dịch cúm gia cầm thay đổi theo loại gia cầm, trong đó tỷ lệ nhiễm cao nhất ở gà  là 64,98% và thấp nhất chim cút tỷ lệ là 2,54%. Hằng năm, kết quả tiêm phòng cúm cho đàn gia cầm của tỉnh Quảng Ninh luôn đạt mức cao trên 90%. Theo dõi 1.550 gia cầm sau tiêm phòng tại 5 huyện, thành, thị thuộc tỉnh Quảng Ninh thấy, vắc xin sử dụng phòng bệnh an toàn với gia cầm; 95,10% số gia cầm không có phản ứng phụ sau tiêm; số còn lại xuất hiện một vài phản ứng nhẹ, không gây ảnh hưởng lớn đến sức khỏe gia cầm.
NGHIÊN CỨU THÀNH PHẦN LOÀI VÀ PHÂN BỐ ĐỘNG VẬT ĐÁY VÙNG BỜ BIỂN TỈNH NINH BÌNH
Authors: Nguyễn Thanh Bình , Nguyễn Cao Văn
Published: August 2021

Nghiên cứu thành phần loài và phân bố động vật đáy cho vùng bờ biển tỉnh Ninh Bình được tiến hành tháng 11 - 12/2020. Kết quả đã xác định 82 loài, thuộc 69 giống, 52 họ, 28 bộ và 6 nhóm đại diện (Crustacea, Bivalvia, Gastropoda, Polychaeta, Chordata và Arthropoda). Trong đó nhóm Giáp xác (Crustacea) có thành phần loài phong phú nhất, có 28 loài (chiếm 34,15%); Thân mềm Chân bụng (Gastropoda) có 25 loài (chiếm 30,49%); Hai mảnh vỏ có 23 loài (chiếm 28,05%); Polychaeta có 5 loài, Arthropoda có 2 loài và Chordata có 1 loài. Từ kết quả cho thấy, khu vực vùng bờ tỉnh Ninh Bình có thành phần loài tương đối đa dạng, thành phần chủ yếu là Crustacea, Gastropoda, và Bivalvia chiếm khoảng 97,56% tổng số loài đã xác định.
Phân bố của các nhóm động vật đáy ở hệ sinh thái ven biển phụ thuộc vào khả năng thích ứng sinh thái rộng hay hẹp của từng loài hay nhóm loài: Vùng bãi bồi cửa sông ven biển có các loài sống thường xuyên ở vùng nước mặn và các loài nước lợ (Portunidae); Thường xuyên ở hệ sinh thái nền đáy (Nassariidae, Naticidae, Arcidae, Ostreidae, Veneridae, Grapsidae, Ocypodidae); Nhóm di nhập tạm thời (Amphibalanus amphitrite). Chỉ số đa dạng sinh học ở khu vực vùng bờ Ninh Bình có chỉ số đa dạng sinh học ở mức độ thấp (H’ = 2,43).
NGHIÊN CỨU THỬ NGHIỆM MỘT SỐ LOẠI QUẢ LÀM MỒI THU BẮT TRƯỞNG THÀNH RUỒI VÀNG VÀ TRƯỞNG THÀNH MỘT LOÀI THUỘC BỘ CÁNH VẢY GÂY HẠI CÂY TRỒNG NÔNG NGHIỆP
Authors: Phạm Thị Mai Trang , Vi Xuân Học
Published: August 2021

Trong những năm gần đây ruồi vàng là một trong những loại gây hại nghiêm trọng đối với cây ăn quả, rau ăn quả nói chung và cây dưa chuột nói riêng, sự gây hại của ruồi vàng làm ảnh hưởng lớn đến năng suất, chất lượng của sản phẩm. Nếu gây hại ở mật độ cao có thể gây thiệt hại lớn về kinh tế của bà con nông dân, để phòng trừ tác hại của ruồi vàng hiện nay trên thị trường có nhiều loại bẫy, bã để thu bắt tuy nhiên một số loại giá thành cao, một số loại vẫn phải dùng thuốc hóa học do đó ảnh hưởng đến chi phí sản xuất cũng như độc hại cho con người và môi trường sống. Từ những lý do trên nghiên cứu này đã được thực hiện để khác phục những hạn chế nêu trên, kết quả nghiên cứu cho thấy: Trong vụ Xuân - Hè mồi bẫy quả Dứa chín với độ dày 10cm thu bắt trưởng thành ruồi vàng có hiệu quả cao nhất đạt 189,8 con/bẫy và thu bắt trưởng thành bộ cánh vẩy có hiệu quả cao nhất đạt 19,8 con/bẫy. Mồi bẫy Mít chín có kích thước 10cm2 thu bắt được trưởng thành ruồi vàng cao nhất 144,0 con/bẫy, thu bắt được trưởng thành bộ cánh vẩy cao nhất đạt 15,8 con/bẫy. Trong vụ Thu - Đông mồi bẫy quả Dứa chín với độ dày 10cm và 5cm thu bắt trưởng thành ruồi vàng có hiệu quả cao nhất đạt 202,4 con/bẫy và 177,4con/bẫy, thu bắt trưởng thành bộ cánh vẩy có hiệu quả cao nhất đạt 20,0 con/bẫy và 15,4con/bẫy, mồi bẫy Mít chín có kích thước 10cm2 thu bắt được trưởng thành ruồi vàng cao nhất 166,2 con/bẫy, thu bắt được trưởng thành bộ cánh vẩy cao nhất đạt 14,6 con/bẫy.
Memoriam: Edwin D. Lawson (1923-2021)
Authors: Gasque Thomas
Published: August 2021

In Memoriam: Edwin D. Lawson (1923-2021)
Security Analysis of XOR Based Ciphered Image
Authors: Sharma P. , Shrivastava R. , Sarthi V. K. , Bhatpahri P.
Published: August 2021

In the present paper, we report security analysis of an effective method of scrambling i.e. XOR technique, which may be used as an important component in visual cryptography. Histogram of scrambled or encrypted images expressed that pixel values are distributed quite uniformly. This implies that nothing can be guessed about the original image using the encrypted image. For analyzing the complexity of encrypted images, information entropy, the correlation coefficient of adjacent pixels values were also calculated. Values of horizontal correlation, vertical correlation, and information entropy reflected that the complexity and randomness of pixel values are quite high for XOR cipher. Now a day’s differential attack has been very common. Keeping the same in the mind, we have calculated Unified Average Changing Intensity (UACI) and the Number of Pixels Change Rate (NPCR), to exhibit the ability of encrypted image using XOR cipher to resist the differential attack. So we can say that XOR cipher is useful for secure transmission of an image.
MCA Degree in 1 to 5 Years: An Investigation of Private Universities in India
Authors: Paul P. K. , Aithal P. S. , Shivraj K. S. , Maheswari D.
Published: August 2021

Computer Application (CA) is a branch of study responsible for the creation of software and applications. It is primarily focused on software technologies and allied areas. Computer Application is available as an academic program and professional area to become industry professionals. The field started during the 1980s and gradually developed in different higher educational institutions in India. Moreover, the branch Computer Application started and still offered in India only. Initially, the branch was started as an alternative field of existing Computer Science. Computer Science is purely concentrated on theoretical areas and mathematical concentration but Computer Application was started with a primary focus on software technologies and development. Initially, Computer Application branch started with Master’s program rather Bachelors program. It has started with three years program for Bachelor’s degree in any stream rather typical criteria of Bachelor’s Degree in concerned/ related/ allied field of study. Computer Application is today offered in different duration with different eligibility criteria. This paper discusses in general, an overview of Computing and Information Technology emphasizes on Computer Application. Paper highlighted the multiple entry options in MCA program with multiple durations in Indian universities with special emphasis to the Private universities.
Water Bodies Extraction and Terrain Analysis for Finding Critical Water Scarcity Locations using Elevation Data
Authors: Kodge B. G.
Published: August 2021

The present study is aimed to create some new methods for extraction of water bodies (Rivers and Reservoirs) and analyze the land formation of terrain using elevation data. The digital elevation models (DEM) are used to extract water bodies and create terrain contours for finding water scarcity locations. Further this work also used some geospatial villages related data to obtain and analyze how many villages are suffering from critical water scarcity problems under the found water scarcity locations. The village’s data also highlights all village’s in which they fell under critical water scarcity regions and facing agriculture and drinking water problems, with respect to their elevation data and available nearby natural water resources.
Virtual Private Cloud and Authentication: A Review
Authors: Deep Gaurav , Mohana Rajni , Kaur Paramroop
Published: August 2021

Cloud computing can be called as service through which computer resources could be used online. It helps to eliminate the need of usage of physical hardware rather it offers to use them on the cloud server. Different Types of cloud service models and deployment models make the cloud access to its users. The cloud supports characteristic such as on demand services, resource pooling, elasticity .While authentication plays important role in the security as it protects the data from the unauthorized people and helps to achieve trust between the service provider and the user. In this Paper, we’ve reviewed the existing work so as tounderstand the concept of cloud computing, virtual private cloud and proposed a multifactor authentication technique which uses biometric trait along with the identity password and MAC address as its factors.
C-Band Line of Sight Communication for analysis to Compact Microstrip Patch Antenna Using Parasitic Technique
Authors: Ravinayak Dharavat
Published: August 2021

The investigation of microstrip fix radio wires has gained awesome ground as of late. Contrasted and ordinary reception apparatuses, microstrip fix recieving wires have more points of interest and better prospects. They are lighter in weight, low volume, ease, low profile, littler in measurement and simplicity of manufacture and similarity. Besides, the microstrip fix reception apparatuses can give double and round polarizations, double recurrence activity, recurrence spryness, wide band-width, feedline adaptability, shaft checking unidirectional designing. In this paper we examine the microstriprecieving wire, kinds of microstrip reception apparatus, sustaining methods and use of microstrip fix radio wire with their favorable position and detriments over ordinary microwave radio wires.From this paper, design of small Microstrip patch antenna using parasitic technique for range of sight communication is proposed, having hexagonal condition ground plane. The recommended antenna has slots in the patch to obtain wideband. The antenna model is simulated using Finite component method at the rate of recurrence 2. 65 GHz to 4. 57 GHz. The antenna design demonstrates desired features for wireless communication
Optimizing the Software Metrics for UML Structural and Behavioral Diagrams Using Metrics Tool
Authors: Singh D. , Sidhu H. J. S.
Published: August 2021

In this paper, we have proposed an efficient way to calculate the software metrics of structural and behavioural diagrams of unified modelling language (UML) with the help SD Metrics as a tool. This method is applied to measure the internal quality of attributes and functions of structural and behavioural diagrams of unified modelling language (UML). The SD metrics tool collect the information after parsing the XMI format generated by UML compiler of structural and behavioural UML diagrams. The object-oriented design made by structural and behavioural diagrams holds the important part of designing in the development process of the software. Early the measurement of metrics will lead to good quality of the software from coding, but now using the design metrics we calculate the cohesion, coupling and other metrics with easy and effective with the fewer efforts which improve the quality of software to be developed at the design phase.
Identifying the Most Effective Model for Understanding the Growth Rate of Government e-Transactions: Brown’s Model of Exponential Smoothing
Authors: Roy Abhishek , Dutta Gautam , Das Prabir Kumar
Published: August 2021

The purpose of this study is to investigate the current status of e-transactions time series growth rate in the state of Jharkhand from January 2013 to 20th May, 2018 to understand the citizen adoption pattern of various e-government services. Government spends lots of money in developing and implementing e-services, but despite spending huge money the adoption rate is low. This study will analyze the adoption rate by using time series models and find the adoption pattern to improve the future adoption rate of e-services. Besides this, the paper will help us to understand whether current e-transaction methods are user friendly or not. Therefore, identify the best model to evaluate the growth rate of e-transactions in the context of government electronic transactions. In this regard, various existing time series models have been evaluated to obtain the result of this study. The paper draws-up the emergent model derived from the analysis. Finally, a framework is suggested to select Brown’s Exponential Smoothing Model as an ideal model for evaluating the growth rate of government e-transaction for the state of Jharkhand. This will help government to recommend and strategize better e-services plan for the state. This research can be used in policy making, strategizing and finding the key to user acceptance of innovation in technology in government electronic transaction with the help of Brown’s Exponential Smoothing as it can reduce the impacts of seasonal factors.
Performance Analysis of Parallelized Bioinformatics Applications
Authors: Pant Dhruv Chander , Gupta O. P.
Published: August 2021

The main challenges bioinformatics applications facing today are to manage, analyze and process a huge volume of genome data. This type of analysis and processing is very difficult using general purpose computer systems. So the need of distributed computing, cloud computing and high performance computing in bioinformatics applications arises. Now distributed computers, cloud computers and multi-core processors are available at very low cost to deal with bulk amount of genome data. Along with these technological developments in distributed computing, many efforts are being done by the scientists and bioinformaticians to parallelize and implement the algorithms to take the maximum advantage of the additional computational power. In this paper a few bioinformatics algorithms have been discussed. The parallelized implementations of these algorithms have been explained. The performance of these parallelized algorithms has been also analyzed. It has been also observed that in parallel implementations of the various bioinformatics algorithms, impact of communication subsystems with respect to the job sizes should also be analyzed.
Reinforcement Learning Based Clock Synchronization in WBAN
Authors: . Pallvi , Gupta Sunil Kumar , Bedi Rajeev Kumar
Published: August 2021

Wireless Body Area Network (WBAN) is an application of wireless sensor network (WSN). WBAN therefore forms a comprehensive collection of devices that are not only capable of providing continuous information about the health status of a person but also offers helpful details about the activities and environment of the person. In this paper, we have evaluated TDMA based MAC protocol performance through several metrics and TDMA approach is used to avoid packet collision which leads to higher packet loss rate. Reinforcement Based Clock synchronization is the solution of problem like packet collision. After clocks of WBAN sensor nodes are synchronized, data can be transferred between sensor nodes and sink efficiently and rapidly. Reinforcement learning iteratively optimizes the clock synchronization technique. Experimental results indicate that the proposed algorithm is more efficient than existing techniques.
A Perspective on Open Source Software Development Movement
Authors: Singh Amitpal , Gupta Sunil Kumar , Singh Hardeep
Published: August 2021

The paper presents a thorough analysis of the Open Source Software Development (OSSD) movement. The main focus of this paper is to understand this movement right from its beginning. OSSD models proposed by various researchers are studied to get an insight into the practices and processes followed for OSSD. In order to determine the advantages and disadvantages of open source software (OSS), its strengths and weaknesses are also analysed. Various challenges associated with the development of Open Source Software (OSS) are highlightened. In future, this study will assist in the development of a framework in which OSSD teams can work in coordination for the development of quality software.
Vulnerability Analysis of Existing Distributed Denial of Service (DDoS) Defense Frameworks
Authors: Gupta Shaveta , Grover Dinesh , Bhandari Abhinav
Published: August 2021

The world is quickly moving towards an era of digitization. Scope and volume of the network are becoming vast that makes these machines more prone to cyber-attack due to vulnerabilities of the network. There are various types of cyber-attacks but most common and equally impactful is DDOS attack. A foolproof defense mechanism is need of the hour. Analysis of various existing defense mechanism frameworks has been done and their shortcomings have been reported by us. This analysis will help to define a framework which can provide better accuracy, lesser detection time and reduced false negative and positive rates. It will further ensure better response and mitigation against the attack.
Speech Recognition using Cross Correlation Algorithm Intended for Noise Reduction
Authors: Kaur Gagandeep , Baghla Seema
Published: August 2021

Biometrics is presently a buzzword in the domain of information security as it provides high degree of accuracy in identifying an individual. Speech recognition is the ability of a machine or program to identify words and phrases in spoken language and convert them to a machine-readable format. Rudimentary speech recognition software has a limited vocabulary of words and phrases, and it may only identify these if they are spoken very clearly. The research work is intended to build a GUI environment which would provide provisions to record the speech and would assist in multiplying the database. The research work is primarily focused to implement a system capable of recognizing a user’s speech and creating audio files that can be added up to create a dynamic template or database. The research work emphasizes on directly recording the spoken words avoiding the problems with use of microphone. On appropriate recording and removal of the noise, the best matched audio file from the template is recognized when an input is provided externally on the basis of graphs created by considering correlation.
Automated Secured Data Delivery for Next Generation Optical Networks
Authors: Swarup Kumar J. N. V. R. , Suresh D.
Published: August 2021

The present cloud benefit measurements truly are stunning. By one year from now 80% of all new programming will be accessible as a cloud benefit, 58% of all Internet activity is guage to be video in only two years and before the decade’s over, 20 billion brilliant gadgets will be associated with the system. There is no uncertainty this will make difficulties wherever in the system. However, with this test, there regularly comes chance to go into the new optical system; never again is it only an asset for transporting bits. What’s more, it’s more than expanding limit. What’s new is the requirement for specialist organizations’ optical systems to end up increasingly “coordinated” and “consumable” enabling them to understand the undiscovered capability of their system. It ought to be a basic element of the developing cloud framework associating clients to their substance and applications. Security is a basic necessity for the system in light of the fact that the touchy data can be gotten to remotely and this makes the whole framework helpless against pernicious assaults. This paper exhibits the AES-256 calculation with respect to FPGA and the Very High Speed Integrated Circuit Hardware Description language (VHDL) for a secured information transmission in the Agile Optical Networks (AON).
A Survey on Security Models for Data Privacy in Big Data Analytics
Authors: Satya Sai Kumar Avula , Mohan S. , Arunkumar R.
Published: August 2021

As emerging data world like Google and Wikipedia, volume of the data growing gradually for centralization and provide high availability. The storing and retrieval in large volume of data is specialized with the big data techniques. In addition to the data management, big data techniques should need more concentration on the security aspects and data privacy when the data deals with authorized and confidential. It is to provide secure encryption and access control in centralized data through Attribute Based Encryption (ABE) Algorithm. A set of most descriptive attributes is used as categorize to produce secret private key and performs access control. Several works proposed in existing based on the different access structures of ABE algorithms. Thus the algorithms and the proposed applications are literally surveyed and detailed explained and also discuss the functionalities and performance aspects comparison for desired ABE systems.
Deep Learning Analysis: A Review
Authors: Rajendra Kumar P. , Ravichandran Suban , Satyala Narayana
Published: August 2021

Deep learning is a rising territory of machine learning (ML) inquires about. It includes different shrouded layers of fake neural systems. Deep learning (DL) is a part of machine learning dependent on an arrangement of calculations that endeavor to show abnormal state reflections in information. It is utilized by Google in its voice and picture acknowledgment calculations, by Netflix and Amazon to choose what you need to watch or purchase straightaway, and by specialists at MIT to anticipate what’s to come. Profound Learning is utilized in different fields for accomplishing various levels of deliberation like sound, content; pictures highlight extraction and so forth. The Deep learning philosophy applies nonlinear changes and model reflections of abnormal state in extensive databases. With Deep learning capacity to make forecasts and groupings taking the upside of huge information, it can be a creative answer for issues and issues that have been never thought to be understood in such a simple way. Then again, it makes numerous difficulties on the researchers who are endeavoring to convey such another methodology. The accompanying audit sequentially shows how and in what real applications profound realizing calculations have been used. We have completed a broad writing audit and reviewed the utilization of profound learning methods on different fields.
Comprehensive Review on Effectual Information Retrieval of Semantic Drift using Deep Neural Network
Authors: Uma Maheswari A. , Revathy N.
Published: August 2021

Semantic drift is a common problem in iterative information extraction. Unsupervised bagging and incorporated distributional similarity is used to reduce the difficulty of semantic drift in iterative bootstrapping algorithms, particularly when extracting large semantic lexicons. In this research work, a method to minimize semantic drift by identifying the (Drifting Points) DPs and removing the effect introduced by the DPs is proposed. Previous methods for identifying drifting errors can be roughly divided into two categories: (1) multi-class based, and (2) single-class based, according to the settings of Information Extraction systems that adopt them. Compared to previous approaches which usually incur substantial loss in recall, DP-based cleaning method can effectively clean a large proportion of semantic drift errors while keeping a high recall.
Survey on Energy Efficiency in Cloud Computing
Authors: Digra Lakshmi , Singh Sharanjeet
Published: August 2021

Data centers are serious, energy-hungry infrastructures that can run large scale Internet based services. Energy ingesting representations are essential in designing and improving energy-efficient operations to reduce excessive energy consumption in data centers. This paper presents a survey on Energy efficiency in data centers, importance of energy efficiency. It also describes the increasing demands for data center in worldwide and the reasons for data centers energy inefficient? In this paper we define the challenges for implementing changes in data centers and explain why and how the energy requirements of data centers are growing. After that we compare the German data center market at international level and we see the energy consumption of data centers and servers in Germany from 2010 -2016.
Information Security Awareness among Non-Academic Staff in the University of Ibadan, Nigeria
Authors: AbdulRahman H. T. , Oladipupo S. O.
Published: August 2021

This study applied the established factors from the existing literatures on information security awareness to investigate information security awareness among non-academic staff in the University of Ibadan, Nigeria. The objectives of this study are; to identify the factors that influence information security awareness and to determine the level of information security awareness among non-academic staff. This study employed a survey design. Stratified random sampling technique was utilized to select the respondents for the study. The study participants consist of non-academic staff in the University of Ibadan. A field survey of 300 respondents was carried out using questionnaire as the main instrument. Descriptive statistics was used for data analysis. Findings of this study revealed that information security awareness is significantly influenced by policy of information security, education of information security, knowledge of technology, and non-academic staff’s behavior. Furthermore, findings show that the level of information security awareness among non-academic staff in the University of Ibadan was high. Finally, findings were discussed and recommendations for the future research were also addressed.
An Experimental Analysis on Rough Set Mean, Median, Mode Method of Dependency Values for Feature Selection in Medical Databases
Authors: Devi S. , Sasirekha V.
Published: August 2021

The problem of imperfect knowledge has been tackled for a long time by philosophers, logicians and mathematicians. Recently it became an important issue for scientists, particularly in the area of Artificial Intelligence. Their square measure several approaches to the matter of the way to perceive and manipulate imperfect information. The most successful approach is based on the rough set notion proposed by Z. Pawlak in the article [1]. The proposed method to find the quick reduct in medical data set using the roughest theory. This method has applied in many classification algorithms and find the measures to calculate the accuracy of this proposed method.
Attack Impact Discovery and Recovery with Dynamic Bayesian Networks
Authors: Rajeshwari T. , Thangamani C.
Published: August 2021

The network attacks are discovered using the Intrusion Detection Systems (IDS). Anomaly, signature and compound attack detection schemes are employed to fetch malicious data traffic activities. The attack impact analysis operations are carried out to discover the malicious objects in the network. The system objects are contaminated with process injection or hijacking. The attack ramification model discovers the contaminated objects. The dependency networks are built to model the information flow over the objects in the network. The dependency network is a directed graph built to indicate the data communication over the objects. The attack ramification models are designed with intrusion root information. The attack ramifications are applied to identify the malicious objects and contaminated objects. The attack ramifications are discovered with the information flows from the attack sources. The Attack Ramification with Bayesian Network (ARBN) scheme discovers the attack impact without the knowledge of the intrusion root. The probabilistic reasoning approach is employed to analyze the object state for ramification process. The objects lifetime is divided into temporal slices to verify the object state changes. The system call traces and object slices are correlated to construct the Temporal Dependency Network (TDN). The Bayesian Network (BN) is constructed with the uncertain data communication activities extracted from the TDN. The attack impact is fetched with loopy belief propagation on the BN model. The network security system is built with attack impact analysis and recovery operations. Live traffic data analysis process is carried out with improved temporal slicing concepts. Attack Ramification and Recovery with Dynamic Bayesian Network (ARRDBN) is built to support attack impact analysis and recovery tasks. The unsupervised attack handling mechanism automatically discovers the feasible solution for the associated attacks.
A Survey on Traffic Sign Detection Techniques Using Text Mining
Authors: Murugan S. , Karthika R.
Published: August 2021

Traffic Sign Detection and Recognition (TSDR) technique is a critical step for ensuring vehicle safety. This paper provides a comprehensive survey on traffic sign detection and recognition system based on image and video data. The main focus is to present the current trends and challenges in the field of developing an efficient TSDR system. The ultimate aim of this survey is to analyze the various techniques for detecting traffic signs in real time applications. Image processing is a prominent research area, where multiple technologies are associated to convert an image into digital form and perform some functions on it, in order to get an enhanced image or to extract some useful information from it.
Network Security Based on Component for Information Network
Authors: Aruljothi A. , Prabhu N. , Mallika N. M.
Published: August 2021

It is a difficult building to ensure the security of data arrange, so it is important to consider out a new security control design and model in the viewpoint of foundational control. As indicated by the attributes and security requests of data net, another security control viewpoint and its engineering dependent on parts is proposed, the security control framework is made-up, and insights regarding the structure of control system, its different kinds, and capacities and spread methods of security control parts are presented, at that point the highlights of the control framework are outlined at last.
A Review on Biometrics Authentication System Using Fingerprint
Authors: Sureshbabu P. , Sakthivadivu M.
Published: August 2021

Technology based on Biometric identification and verification is one leading research area. It deals with the concept analyzing the human body characteristics through Biometric devices for various authentications process. There are many Biometric authentication systems are available for verification process. This paper discusses the role of Fingerprint authentication. FP recognition is highly used biometric technique, because of abundance sources (i.e. ten fingers) availability for collecting data. Discussion on Fingerprint matching techniques, recognition methods and their performance analysis are made in the paper.
Social Media Analysis through Big Data Using Map Reduce Algorithm
Authors: Lingeswari S.
Published: August 2021

Few years back the Internet usage was very low when compared now-a-days. It has become a very important part in our day to day life. Billions of people are using social media and social networking every day all over the world. Such a huge number of people generate a large number of data which have become a quite difficult to manage. Here solving these types of problem by using a term called Big Data. It refers to the huge number of datasets. Data may be structured, unstructured or semi structured. Big data is defined by three Vs such as Volume, Velocity and Variety. Big Data use an algorithm known as Map Reduce algorithm. Large number of datasets is very difficult to manage. This problem has been solved using Map Reduce algorithm. In this paper, we focus to analyze social media through big data using Map Reduce algorithm.
Study and Analysis of Data Mining Algorithms for Identifying the Students’ for Psychology Motivation
Authors: Peerbasha S. , Mohamed Surputheen M.
Published: August 2021

The development of many educational institutions is based on the performance of students learning and understanding capabilities. Here, we analyzed their academic profile with their grades and various cumulative attributes. The academic performance in learning their subjects could be improved by motivational approach. The analysis of student performance is carried out through knowledge-based data mining process. But, the problem is arrived by a probability of information prediction accuracy from student data set which is not accurate. Here, we propose a novel machine learning algorithm based on subspace clustering and multi-perspective classification techniques to identify psychological motivation required students. Also, the extraction of relational patterns to form enhanced clustering classes is done. This discovers the innovative relations between students and their educational performance in the various attributes using surf scale nested clustering approach based on an intelligent predicting system from soft computing processing tasks. This improves the data prediction rate by considering the time factor analysis and complexity to design and develop an efficient clustering algorithm which maximizes the clustering and classification accuracy for improving academic performance.
File Fragmentation to Improve Security in Cloud Using Graph Topology Grid Algorithm: A Survey
Authors: Abdul Saleem S. , Ramya N.
Published: August 2021

Cloud computing is an emerging patterning that provides computing, communication and storage resources-as-service over a network. In existing system, data stored in a cloud is unsafe due to the eaves dropping and hacking process. To overcome the drawbacks of earlier approaches, Division and Replication of Data in the Cloud for Optimal Performance and Security (DROPS) methodology is used. The node selection is ensured by means of Graph Topology Grid Algorithm and also data is encrypted here for security. In this process, the common data are divided into multiple nodes and replicate the fragmented data over the cloud nodes. Each data is stored in a different node as fragments in individual locations. In case of any attackers attack a node, no meaningful information will expose to them. The controlled replication of the file fragments is ensured and each of the fragments is replicated only once for the purpose of improved security and minimal retrieval time. In this survey, various relevant approaches were studied and analyzed. Furthermore the DROPS with Graph Topology Grid Algorithm give the better way of security in cloud environment over the earlier approaches.
Identification of Virus in Microscopic Image Using Genetic Algorithm
Authors: Senthilkumaran N. , Preethi R.
Published: August 2021

In this paper describes a several techniques of effective edge detection by using image segmentation. The image segmentation provides various techniques to detect the edges on image. The paper mainly focused on edge detection using matlab parameters and solved the many problems. Edge detection techniques have a several type of techniques. We have taken microscopic image, which affects the human body by making diseases through viruses and bacteria’s. Now analyze only about the major techniques: a.) Roberts edge detection, b) sobel edge detection, c) prewitt edge detection, d) log (laplacian of gaussian) edge detection, e) genetic edge detection and f) canny edge detection. We have applied above five techniques which are used in edge detection and got a result on microscopic images. Hence, we scope this paper defines and compares the variety of techniques and demand assures the genetic algorithm provides a better performance on edge detection using microscopic image.
An Enhanced Approach to Mine Maximal Frequent Itemset using Maximal Frequent Itemset Prima Algorithm (MFIPA)
Authors: Smeeta Mary R. , Perumal K.
Published: August 2021

In data mining finding out the frequent itemsets is one of the very essential topics. Data mining helps in identifying the best knowledge for different decision makers. Frequent itemset generation is the precondition and most time-consuming method for association rule mining. In this paper we suggest a new algorithm for frequent itemset detection that works with datasets in distributed manner. The proposed algorithm brings in a new method to find frequent itemset not including the necessitate to create candidate itemsets. The proposed approach could be implemented using horizontal representation for transaction datasets and allocating prime value. It explores all the frequent itemset that is present in the input and according to the support the maximum frequent itemset is identified. It was applied on different transactions database and compared with well-known algorithms: FP-Growth and Parallel Apriori with different support levels. The try out showed that the proposed algorithm attain major time improvement over both algorithms.
Segmentation Images Using Improved Genetic Algorithm
Authors: Leelavathi Kailasam , Sudha T.
Published: August 2021

With the expanding openness to new advancements, the principle issues in locale acknowledgment of remote detecting pictures are: (1) arrangement techniques are reliant on the division quality; and (2) the choice of delegate tests for preparing. The significant test is that the examples shown by the client are not in every case enough to characterize the best division scale. Besides, the sign of tests can be expensive, since it regularly requires visiting considered places in loco. The choice of delegate tests, then again, was bolstered in this work by the improvement of another intelligent characterization approach based on dynamic learning. Critical commitments were likewise acquired concerning the depiction of areas in remote detecting pictures by methods for: an assessment investigation of 19 descriptors; and two new methodologies for accelerating highlight extraction from a progressive system of sectioned districts.
An Efficient Closed Maximal Pattern Sequences Mining on High Dimensional Datasets
Authors: Krishna J. , Haritha M.
Published: August 2021

Previous methods have presented convincing arguments that mining complete set of patterns is huge for effective usage. A compact but high quality set of patterns, such as closed patterns and maximal patterns is needed. Most of the previously maximal pattern sequences mining algorithms on high dimensional sequence, such as biological data set, work under the same support. In this paper, an efficient algorithm Closed Maximal Pattern Sequences (CMPS-Mine) for mining closed maximal patterns based on multi-support is suggested. Careful exhibitions once Beta-globin gene sequences have exhibited that CMPS-Mine expends less memory utilization and run time over Prefix Span. It generates compacted outcomes and two kinds of interesting patterns.
Machine Learning Algorithms for Spam Detection in Social Networks
Authors: Nagaramani K. , Vandanarao K. , Mamatha B.
Published: August 2021

Most of the web based social systems like Face book, twitter, other mailing systems and social networks are developed for users to share their information, to interact and engage with the community. Most of the times these social networks will give some troubles to the users by spam messages, threaten messages, hackers and so on.. Many of the researchers worked on this and gave several approaches to detect the spam, hackers and other trouble shoots. In this paper we are discussing some tools to detect the spam messages in social networks. Here we are using RF, SVM, KNN and MLP machine learning algorithms across rapid miner and WEKA. It gives the better results when compared with other tools.
Big Data Analytics Implications for Smart Tourism Destinations Towards the Enrichment of Content Tourism
Authors: Padmaja N. , Sudha T.
Published: August 2021

Smart tourism has huge amount of Social Big data available from tourists can cherish the value conception process for a Smart Tourism Destination. Applying a multiple-case study analysis, a set of regional tourist experiences related and destination, to derive patterns and opportunities of value creation generated by Big Data in tourism. Near conclusions and data in terms of improving decision making, creating marketing strategies with more personalized offerings, transparency and trust in dialogue with customers and stakeholders, and emergence of new business models, exploitation of Big Data in the context of information-intensive industries and mainly in Tourism. Smart Tourism Destination today is the front line of study in the tourism field and is a promising area from various research perspectives in terms of models, tools and strategies to keep up the process of intelligent configuration of destinations.
Agro Informatics Emphasizing its Potentiality as a Full-Fledged Degree Programs: International Context and Indian Potentialities
Authors: Paul P. K. , Sinha R. R. , Aithal P. S. , Saavedra Ricardo , Aremu Bashiru
Published: August 2021

Agricultural Informatics or Agricultural Information Science is the combination of two major and important subject’s viz. ‘Agricultural Science’ and ‘Informatics/Information Science’. This is an interdisciplinary subject and importantly the two major branches from which this is evolved is also bearing interdisciplinary nature. The uses of IT, Computing, or general scientific Documentation is common in almost all the areas and subjects; and as far as agriculture is concerned the documentation and general information management principles were common initially. Gradually like other subjects, Agricultural Informatics also become developed as a field of practice to cater to the need of Agricultural sectors by providing information, IT and technological support. There are various reasons for the introduction of Agricultural Informatics. Initially, it was responsible for information management activities related to the Agriculture and allied areas. Gradually this is become more applied and with diverse in nature. In pre-production activities to postproduction, Agricultural Informatics today become an important practicing field and as well as a field study in major international universities. Even in many developing countries like in India also Agricultural Informatics become a field of study. The field is available with this nomenclature and in other allied nomenclatures. In some context it is noted that the field is available only in some of the streams viz. science or technology, and in some context as a specialization. However, there is a potentiality in offering the field Agricultural Informatics as a branch in other areas, both Indian and International context. This paper is conceptual in nature and deals with such potentialities with a brief overview on Agricultural Informatics including evolution, features and role, and importance.