bluuebunny/crossref_metadata_2025 huggingface dataset:
The Circumcision Dress
Authors: Klein Warren
Published: December 2020

This paper will explore the origins of the circumcision dress worn by Jewish male infants during their brit millah (ritual circumcision). With no requirements according to Jewish law on what is to be worn during this ceremony, how does early textual evidence point to our understanding and use of the dress? An examination of visual representations of circumcision ceremonies during the Early Modern period in manuscript and print culture points to the adaptation and use of a jacket worn by the infant during this time. This is then paired with extant examples of the period in museum collections. Lastly, as Jews began to assimilate and adapt practices of their host cultures in the nineteenth century, we see the rise of the practice of a dress worn by the infant, with an examination of infant costume and materials of the period.
Debasing the Deity
Authors: Arya Rina
Published: December 2020

This article considers cases in the media of the cultural appropriation of Hindu symbols by Western fashion designers. Hinduism has a rich tradition of visual and material culture and designers are attracted to the aesthetic and symbolism of Hindu imagery. This has led to protests by Hindu groups who have objected to the uses to which their religion has been put. This article addresses the issues that have caused offence as a way of understanding what is sacred to the aforementioned group and of establishing greater understanding about what is deemed to be acceptable.
China’s Policy and Rule-Making Activities on Outer Space: The Case of Preventing Arms Race from the Global Commons Perspective
Authors: Li Bin
Published: December 2020

As China is rising as a space power, it intends to be more active in participating international rule-making activities. International legal rules are needed for the purpose of preserving peaceful order, which is the minimum condition of the outer space as a global common. Under the Conference of Disarmament, China, together with Russian Federation, advanced a draft treaty on the issue of prevention of arms race in outer space. For raising consents among states in the process of international rule-making, China’s policy and rule-making activities have to supply clear solutions to the divergent core issues including arms race, space weapons, use of force and threat of force in outer space, etc. Furthermore, as trust and confidence are imperative to any meaningful norm-setting agenda in international community, China can significantly improve the endeavour in international rule-making through strengthening its credibility.
The Internet Commons: Encroached and Disputed Domain Names
Authors: Chaisse Julien
Published: December 2020

This article analyses the impact of China and, even more importantly, Chinese individuals on the governance of domain names, which form the fundamental structure of the Internet commons. Many commons exist in physical space, but increasingly, commons in digital space will be overexploited, and that is why the Internet and its interconnections, made of an unlimited number of domain names, need to be carefully regulated. Internet domain names are true economic assets which raise important legal issues in China and in the rest of the world. This article reviews the key developments in case law over the last decade with a focus on China. Interestingly, at least 35% of domain name disputes involve a Chinese responding party. The article shows that, despite being a major provider of users, China was never involved in the regulation and design of the Internet. In fact, China has rather emerged as a rule-shaker, given the large involvement of Chinese cybersquatters in the domain names case law. Fundamentally, this article shows that there is a tension between Internet control in China and global interconnection, which has had direct consequences for China’s engagement with ICANN and other institutions in charge of DNS globally.
Transboundary Fisheries Management
Authors: Zou Keyuan , Wang Jiayi
Published: December 2020

The United Nations Convention on the Law of the Sea created the exclusive economic zone regime, which makes more than 90 per cent of the world’s commercial fish stocks under the national jurisdiction of coastal States. The biological characteristics of fish demonstrate that the long-term sustainability of fisheries can only be achieved through cooperation and coordination among States, especially for the conservation of transboundary fish stocks. However, the ocean may have more than 1,500 transboundary fish stocks, only a limited number are subjected to effective cooperative management. This article provides an overview of the international legal framework on transboundary fisheries and China’s practice on shared stocks and distant water fisheries, and argues that current bilateral fisheries agreements are not sufficient enough to manage transboundary fish stocks and China still has much to do on regulating distant water fisheries.
Sharing Fish: The Philippine Experience
Authors: Espenilla Jacqueline Joyce F.
Published: December 2020

Straddling and highly migratory fish such as tuna are the subject of immense interest from countries like the Philippines, whose populations are highly dependent on the oceans for both sustenance and livelihood. As these fish are transboundary by nature, they are deemed as “shared resources” that need to be cooperatively managed by country stakeholders in order to safeguard against depletion. This is the primary reason for the increasing number of international fisheries agreements as well as in the sudden prominence of regional fisheries management organizations (RFMO s). In that context, this article presents and analyzes the domestic drivers as well as the various international legal considerations that helped shape the current Philippine framework for the governance of shared fish, and reflects on how the twin goals of consumption/exploitation and conservation figure in the country’s fisheries policy.
United States Law and Policy for Sharing Transboundary, Highly Migratory, and Straddling Stock Fishery Resources
Authors: Telesetsky Anastasia
Published: December 2020

This article describes the United States approach to shared fisheries management highlighting efforts to manage tuna, halibut, salmon and other transboundary species. The article concludes with a recommendation for factoring climate change into U.S. standards for fisheries management.
再論殷墟甲骨文中的“其”
Authors: 張 玉金
Published: December 2020

甲骨文中的“其”大都是副詞，有兩個意義，一是表示將要、將會的意思，二是表示命令的語氣。前一種意義的“其”很常見，而後一種意義的“其”很少見。
殷墟卜辭“其”字及其搭配和對舉
Authors: 黃 天樹
Published: December 2020

以往講殷墟卜辭“其”字的論著，大都討論單音虛詞“其”字，對“其”字跟其它虛詞（或實詞）的搭配和對舉討論較少。本文重點討論跟語氣副詞“其”字有關的搭配和對舉。本文認為語氣副詞“其”字主要表示以下四種語氣：第一，表將要語氣；第二，表疑惑語氣；第三，表不願意語氣；第四，表能否應驗的語氣。于省吾（1979）認為：“甲骨文的其字除去用作句首發語詞外，其餘的均作助動詞的該字用。”從卜辭內容看，難以成立。同時，本文討論了“‘其’字規則”、“驗辭無‘其’規則”。
Ovid
Authors: Martelli Francesca K.A.
Published: December 2020

In this volume, Francesca Martelli outlines some of the main contours of recent, current and future research on Ovid. Her study looks back to the rehabilitation of Ovid’s oeuvre in the 1980s, and considers the post-modern aesthetic prerogatives and post-structuralist theoretical concerns that drove the critical recuperation of his poetry throughout that decade and in the decades that followed. But it also looks forward, by considering how the themes of this poet’s oeuvre answer to a variety of new materialist concerns that are now gaining currency in the humanities and social sciences. It highlights the ecopoetic sensibility of the Metamorphoses, for example, and unpacks the environmental narratives that this poem yields when read in dialogue with the discourses of critical posthumanism. And it closes by considering the hauntological aesthetics of Ovid’s exile poetry as a comment on the effects of the principate on time, space, media, and art.
A List of the Caddisflies (Insecta: Trichoptera) from Kyrgyzstan, with a New Record (Triaenodes reuteri McLachlan 1880)
Authors: KÜÇÜKBASMACI İBRAHÝM , CANBULAT SAVAŞ
Published: December 2020

The Trichoptera include more species than any of the other primarily aquatic orders of insects, which are usually found in clean fresh water. Distribution of the species of an order based on geography can provide guidance for researchers working in the field. In the current study, for the first time, a list of known Trichoptera species in Kyrgyzstan is given along with a new record. The list is prepared based on the relevant literature between 1875 and 2020 and a study conducted in 2012. Literature search revealed that 21 known species of caddisflies of 13 genera and 8 families have been reported from Kyrgyzstan; our research found that Triaenodes reuteri McLachlan 1880 is also present in Kyrgyzstan. We also re-illustrate the male genitalia of T. reuteri and provide a detailed redescription. Based on literature search and our observations, the Kyrgyzstan caddisfly fauna has been poorly studied; it is expected that new records and new species will be found in Kyrgyzstan through further research.
A Literature Survey on Early Detection of Malignant Tumor Through Computerized Technique
Authors: Shwetha S. V. , Dharmanna L.
Published: December 2020

Computer based initial stage classification and detection of breast cancer tumor must be taken as one of the most important parameter to detect cancer in order to assist radiologist. In this paper an overview of current development of computer based detection system has been reviewed.
The abnormalities identification and classification based on texture feature and shape of tumor, statistically diagnostic parameters (mean, mode, standard deviation, median etc.), Entropy based, Elliptical Normalized Circumference (ENC), C-means, K-means, Watershed Transformation, Ratio of
Perimeter:Area (P :A), Ratio of major axis:minor axis (L:S) and Content Based Image Retrieval (CBIR) have been presented. In this paper the accuracy of the result obtained by various techniques such as texture based classification (80%), statistical parameters based classification (70%), shape
based classification (86%), CBIR based classification (60%), etc. are presented. The various imaging techniques and dedicated databases publicly available for the cancer research work have been listed, discussed and reported in this paper.
Image Deduplication in DriveHQ Cloud
Authors: Vinoth Kumar S. , Kruthika L. , Pooja K. , Priyanka H. J. , Rachana N. R.
Published: December 2020

Basically, a cloud is used to store some personal information like images, videos and files etc. and it is secure and user can back up their data. There are different types of cloud like Google drive, Drop box, Amazon drive, Mega etc. It can be accessed anywhere at any time, but the
user needs to have internet access. In this paper, the importance is given to image de-duplication method in cloud as images take more storage in the cloud. If we upload similar images twice it takes more storage in the cloud. So, to overcome this problem, images are divided into rectangular
blocks. Each block will generate hash value using MD5 algorithm in DriveHQ. DriveHQ is a website, offers optimized photo and video viewing features. If we upload similar images it will generate blocks and each block is checked with hash value. If hash value is similar, that is near identical
images then only once the image is stored in cloud so more storage will be available to the user. We provide detailed analyses in proposed work.
Software Defined Networks—A Network Programme and Its Dynamic Services
Authors: Vineetha B. , Sumana M.
Published: December 2020

As network component is increasing, the managing and controlling systems from a central based control system becomes very complex. The technology used to resolve this is called Software Defined Networks (SDN) which helps to manage and control the system through programs. SDN stands
as a developing technique that divides single network as data and control plane. The benefit of SDN are provides more performance, managing the packet flow through diverse dealer’s organization components. The complexities continued to raise when implementing network services both from
technical and organizational views. Here in this paper generally focuses on how organizations can deal with the challenge of introducing service chaining and developing critical network services by using the technology SDN and also delivering diverse services of network to user in one system
thus customers can fulfill their desire of services based on requests. The “Service Function Chaining” facility of SDN provides services like Load Balancing, Video Optimizing and Firewall.
Comparison Between Non-Linear Autoregressive and Non-Linear Autoregressive with Exogeneous Inputs Models for Predicting Cardiac Ischemic Beats
Authors: Niranjana Murthy H. S.
Published: December 2020

The prediction accuracy and generalization ability of neural models for forecasting Myocardial Ischemic Beats depends on type and architecture of employed network model. This paper presents the comparison analysis of recurrent neural network (RNN) architectures with embedded memory,
Non-linear Autoregressive (NAR) and Non-linear Autoregressive with Exogeneous inputs (NARX) models for forecasting Ischemic Beats in ECG. Numerous architectures of the NAR and NARX models are verified for prediction and the performances are evaluated in terms of MSE. The performances of NAR
and NARX models are validated by using ECG signals acquired from MIT-BIH database. The results have depicted that the NARX architecture with 2 neurons in hidden layer and 1 delay line outperformed with least Mean Square Error (MSE) of 0.0001 for detecting the ischemic beats in ECG.
A Block Chain Approach for Privacy Preserving and Data Security in Internet of Things
Authors: Harish Kumar N. , Deepak G.
Published: December 2020

Internet of Things has been increasing its usage and recognition in vast sectors like Defence, Business, Industries, and Hospitals. The data disruption is strictly unacceptable in a number of these sectors because it could end up in serious Loss or Damages to the entire system. As of
now, IOT is using a central cloud storage system for information storage and transactions. However, some examples already verified that Central cloud storage information might be hacked and changed by the specialists. This paper presents an IoT system having localized block chain storage which
works on real time data and manipulates with narrowness of data interruption and modification and its recovery.
Design of a New Technology to Evaluate the Rocket Forecast Path of a Real-Time Object Under a Multi-Dimensional Graphic Scheme
Authors: Gohatre Umakant Bhaskarrao , Ram Singla C.
Published: December 2020

This article provides a quick and precise algorithm for improving the accuracy of the ballistic path forecast. In order to assess projectile approach corners in every measurement moment the algorithm is focused on the six degree freedom path rules (6DOF). The algorithm uses DFP to fix
the nonlinear equations and Doppler trajectory sample data comprising the projectile only location cords to rebuild the linear data. The radar data can therefore be obtained via the projectile. At the end of the radar measurement, “position coordinates of the test” and “angular
reconstruction displacements” serve as the initial value for the track calculation for the extrapolation of the path impact. The numerical simulations validate the technique suggested and show that the projected effect value is very consistent with the actual technique. Moreover, other
algorithm artillery trajectory can be anticipated, and the suggested algorithm can also be used with other trajectory designs such as 4DOF or 5DOF.
Game Theory Based Routing Protocols and Their Efficiency in Improving the Lifetime of a Wireless Sensor Network
Authors: Ashwini  , Guruprasad N.
Published: December 2020

The advances in the Internet and communication technology, has set the scene for a new era of inexpensive sensors and actuators which are capable of performing sensing and controlling tasks. A sensor network contains a group of sensors that perform sensing, computing, and communicating
data to the sink or the base station (Arampatzis, T., et al., 2005. A Survey of Applications of Wireless Sensors and Wireless Sensor Networks. IEEE International Symposium on, Mediterrean Conference on Control and Automation Intelligent Control, Limassol, Cyprus. pp.27–29). The sensing
elements (sensors) have limited battery power and thus pose a limitation with respect to energy consumption. To maintain the longevity of a sensor network there is a need to employ several optimization techniques in order to utilize battery power efficiently. This paper focuses on efficient
game theory routing protocols to optimize power consumption in the sensor nodes.
Application of NoSQL Technology to Facilitate Storing and Retrieval of Clinical Data Using IndexedDb in Offline Conditions
Authors: Nagarakshitha B. R. , Lohith K. S. , Aarthy K. P. , Gopkumar Arjun , Ranjan Uma Satya
Published: December 2020

Data collection is a very important aspect of any research, especially while dealing with the collection of clinical data. This paper presents a way to collect and manage clinical data using a web application with offline functionality. The whole application is an end-to-end PWA providing
an interface to collect the data, store, and query. The available data is very huge and it is unstructured. To store it, a NoSQL database such as Cassandra is most suitable. The data will mostly be used for an OLAP system for querying the data, cleaning and performing analysis on it. In the
process of collection of data, the application has to work under low or no bandwidth conditions for which a NoSQL system provided by most web browsers called IndexedDB, can be used to locally store data under offline conditions.
Social Balance Theory Based Hybrid Movie Recommendation System
Authors: Priscilla S. , Naveena C.
Published: December 2020

Suggesting people exactly according to their likeness is most challenging in today’s generation. Present websites fail to provide the recommendation that is appropriate for people. There are several reasons such as there is either inadequate information about people or absence
of feedback from the movies that they have watched. In this Situation considering those few/Sparse scores that are given that are collected from the people a socially balanced concept came into picture. Socially balanced theory Concept (hybrid) uses a integrated recommendation by combining
both substance—oriented and community organized approach i.e., recommends based on both on viewers as well as movie. Socially balance theory helps to get better suggestion even when there is less information or inappropriate content by finding the opponent for the end users later discover
the end users companion i.e., “opponents opponent is a companion” rule in social balance theory. So that suggestions can be based on both customer as well as goods based. For this, initially grouping the community is required to find the similarity between them. Finally the workability
of integrated—recommendation is evaluated by considering film lens dataset – 10 M.
Enhancements in Decision Making Through Sentiment Analysis of Twitter Data
Authors: Kallimani Jagadish S. , Ajeya S. H. , Keerthana D. , Shet Manoj J. , Hegde Prasada
Published: December 2020

All trades and business run predominantly on customer satisfaction and serves as the key to success. Usually, the decisions made by people is largely dependent on others’ perspectives. Hence, it becomes important to have reviews in your favor to sustain and outperform competitors
in the market. Collecting reviews and predictions and analyzing them is an effective method to get insights on how the product, service or subject is accepted by the public. It also helps us discover the fields or aspects that needs to be improved. This comes under the field of Sentiment Analysis
which refers to the computational identification of views, perspectives, opinions and emotions from text and speech through Natural Language Processing. With the emergence of the internet, blogging and social-networking sites are a rage. Twitter is one of the popular and ubiquitous sites and
acts as a reliable source of feedback. In this paper, we seek to detect the emotion portrayed in a given tweet with significant accuracy. We propose the use of Word2Vec model and Count Vectorizer to extract features from pre-processed data. The output is fed to trained Multi-Layer Perceptron
classifier to detect the emotion behind the sentence.
Deep Learning in Historical Kannada Document
Authors: Ravi P. , Naveena C. , Sharath Kumar Y. H.
Published: December 2020

Kannada is one of the famous ancient languages of the India and the official language of the State of Karnataka, which has a very large heritage. The digital analysis of these historical Kannada documents will provide us information about the culture and traditions that were practiced.
Retrieving such information from paper documents, palm leaves or from stone carvings will enhance our knowledge. Investigating Historical document isn’t straight advance procedure because of low quality, differentiation, contrast and covering of characters. In this analysis, the authors
propose a novel Scale invariant Feature Transform (SIFT) with deep learning classifier to recognize Historical kannada characters. To begin with, the character is divided utilizing Connected Component Analysis and later the Different SIFT Features are detached. At long last, form a powerful
convolutional neural system classifier to recognize the Historical kannada archives. Proposed tale schemes during the preprocessing stage to guarantee strong, precise and constant grouping. They assess their strategy all alone datasets their characterization results surpass 97% on all datasets,
which are superior to the cutting edge in this space.
Performance Analysis of Batch Jobs in Cloud Environment
Authors: Sujatha K. , Jagannatha S.
Published: December 2020

The complexity of running batch jobs in cloud environment is increasing day by day due to huge volume of back end data increasing dynamically in different formats, growing number of online or offline requests from various environments or availability of system resources. This paper
explores the various behaviors of batch jobs from production cluster and the following observations are made: (i) The number of user jobs submitted at offline are high thereby increasing the wait time and processing time. (ii) Each job submitted with huge volume of data causing increase in
queue size, job failure and errors on completion. (iii) Server utilization is unbalanced during the peak time thereby causing the server crash.
Design of New Access Control Approach for Provenance Based on Digital Consortium Decision Making via Secret Sharing
Authors: Kumar Kukatlapalli Pradeep , Chowdary Cherukuri Ravindranath
Published: December 2020

Access control is one of the important element in providing confidentiality to the secured data. Access specifiers helps us understand degree of rights given to the users in utilizing data records in a right manner. Tampering the records by unauthorized parties is a high concern in
secure communication. Tamper detection plays an important role in trouble shooting an issue associated with network/host intrusion scenario. In this regard we propose a new mechanism for securing the data using majority voting concept. We apply this majority voting for securing the provenance
data. Provenance data is data of origin, genesis data and often observed as sensitive data. Provenance is a record of events, timestamps, versions, transformation occurred for the data of interest. Access control and issuing appropriate authorization is on provenance data.We integrate concepts
of secret sharing and provenance to provide an indigenous solution for confidentiality, integrity and availability. The same is experimented with a simulation and results are compared for better understanding and validation.
Global Data Fusion versus Local Pattern Fusion in Mining Multiple Databases: A Comparative Review
Authors: Muley Abhinav
Published: December 2020

With the emergence of big data, mining distributed databases has become a critical task in the domain of discovery of knowledge from databases. Many of the traditional multiple-database mining methods developed until now have emphasized mining the mono-database, which is a pool of all
the local databases merged at a central site; local patterns discovered at local sites are not analyzed in mono-database mining. However, in real-world applications, data collected from multiple databases may be duplicitous and unreliable. Therefore, developing methods to discover reliable,
high-quality knowledge from multiple databases is a challenging task when mining multi-sourced data. This paper scrupulously reviews all the existing methods for mining multiple and distributed databases based on global data fusion and local pattern fusion techniques. The research issues and
recently developed methods, which involves local pattern analysis in multi-database mining, are also discussed.
Performance Analysis of Open Source Optical Character Recognition
Authors: Kallimani Jagadish , Prasad Chandrika , Keerthana D. , Shet Manoj J. , Hegde Prasada , Ajeya S. H.
Published: December 2020

Optical character recognition is the process of conversion of images of text into machine-encoded text electronically or mechanically. The text on image can be handwritten, typed or printed. Some of the examples of image source can be a picture of a document, a scanned document or a
text which is superimposed on an image. Most optical character recognition system does not give a 100% accurate result. This project aims at analyzing the error rate of a few open source optical character recognition systems (Boxoft OCR, ABBY, Tesseract, Free Online OCR etc.) on a set of diverse
documents and makes a comparative study of the same. By this, we can study which OCR is the best suited for a document.
Analysis and Prediction of Higher Education Learners’ Mindset Using Data Mining Tool and Techniques
Authors: Begum Safira , Padmannavar Sunita S.
Published: December 2020

With advent of smart-phones and internet first approach, large amounts of data is generated and collected everyday which is considered as Big Data. Analyzing and making sense out of such data is very important but challenging as well, due to its complexity. The knowledge is hidden in
the data and can be extracted through Data mining techniques. The purpose of this descriptive research study is to evaluate and predict the mindset of rural and urban students with text analytics and visualization capabilities in the Orange tool. As part of the study a group of undergraduate
students from different regional backgrounds participated in a survey for analyzing their mindset being growth mindset and fixed mindset along with a range in-between. The respondents’ data was used as training dataset for the classification model, which was then used to train the prediction
model in the Orange tool. The results showed 75% accuracy in predicting the mindset.
Comparative Analysis Between Recurrent Convolutional and Convolutional Neural Networks for Horizon Detection
Authors: Srinarasi Shreya , Jahagirdar Seema , Renganathan Charan , Mallika H.
Published: December 2020

The preliminary step in the navigation of Unmanned Vehicles is to detect and identify the horizon line. One method to locate the horizon and obstacles in an image is through a supervised learning, semantic segmentation algorithm using Neural Networks. Unmanned Aerial Vehicles (UAVs)
are rapidly gaining prominence in military, commercial and civilian applications. For the safe navigation of UAVs, there poses a requirement for an accurate and efficient obstacle detection and avoidance. The position of the horizon and obstacles can also be used for adjusting flight parameters
and estimating altitude. It can also be used for the navigation of Unmanned Ground Vehicles (UGV), by neglecting the part of the image above the horizon to reduce the processing time. Locating the horizon and identifying the various obstacles in an image can help in minimizing collisions and
high costs due to failure of UAVs and UGVs. To achieve a robust and accurate system to aid navigation of autonomous vehicles, the efficiency and accuracy of Convolutional Neural Networks (CNN) and Recurrent-CNNs (RCNN) are analysed. It is observed via experimentation that the RCNN model classifies
test images with higher accuracy.
Techniques and Issues in Text Mining
Authors: Noronha Perpetua F. , Bhan Madhu
Published: December 2020

Digital data in huge amount is being persistently generated at an unparalleled and exponential rate. In this digital era where internet stands the prime source for generating incredible information, it is vital to develop better means to mine the available information rapidly and most
capably. Manual extraction of the salient information from the large input text documents is a time consuming and inefficient task. In this fast-moving world, it is difficult to read all the text-content and derive insights from it. Automatic methods are required. The task of probing for relevant
documents from the large number of sources available, and consuming apt information from it is a challenging task and is need of the hour. Automatic text summarization technique can be used to generate relevant and quality information in less time. Text Summarization is used to condense the
source text into a brief summary maintaining its salient information and readability. Generating summaries automatically is in great demand to attend to the growing and increasing amount of text data that is obtainable online in order to mark out the significant information and to consume
it faster. Text summarization is becoming extremely popular with the advancement in Natural Language Processing (NLP) and deep learning methods. The most important gain of automatic text summarization is, it reduces the analysis time. In this paper we focus on key approaches to automatic text
summarization and also about their efficiency and limitations.
Web Page Recommendation Using Genetic and Feed Forward Association Rule on Web-Log Features
Authors: Pavithra B. , Niranjanamurthy M.
Published: December 2020

As websites are increasing day by day, so user behavior analysis for improving the website performance attracts many researcher. This paper introduces the web page recommendation model using web log feature of web mining. Here work has introduce Feed forward counter model (FFC) for
identifying the association rule with single data iteration technique. Hence execution time for this gets reduced. Work has introduced the Particle swarm optimization algorithm for the selection of appropriate page from given user path as recommendation page. This work involves support of
the association rule as fitness value. Experiment was done on real dataset obtained from project tunnel website. Results shows that by the use of Feed forward association rule with PSO for next page recommendation system has improve various evaluation parameters like precision, coverage, m-metric.
Technological University and Its Affiliated Engineering Colleges Event Tracking System Using Blockchain Technology
Authors: Niranjanamurthy M. , Niveditha N. M. , Amulya M. P. , Namitha A. R.
Published: December 2020

Now a day’s people getting all information’s through web applications. The objective of this work is to develop a system that will provide the details of Engineering colleges and Universities in Karnataka and the complete information of all the events happening in different
colleges. Events like conference, fest etc. All the details will be provided in this system. In TUECETS Users or visitors can easily get to know currently happening events and events which are to be held later. Universities and affiliated Engineering colleges administrator can post the details
of the events in this system through BC. Administrator will be responsible to maintain all the posts and events details. Events can be posted in the system only after the approval of the administrator through Blockchain. It will be very useful to all users to know the events and activities
details of particular university.
Compact Modeling of Capacitance Based 14 nm Triple Gate FinFET Using Verilog-A
Authors: Anjani Devi N. , Lokesh T. , Tejomurthy H. S. P. , Ijjada Sreenivasa Rao
Published: December 2020

Technology down scaling process divulges, the unveiled short channel effects (SCEs), which disrupts the behavior of bulk CMOS technology. In order to overcome these unveiled effects, the single gate controlling mechanism should be replaced with multiple gate mechanism to enhance the
control of gate over the conducting channel. FinFET is a promising technology, which provides efficient gate controlling over the channel by multiple gates. Some of the multi gate FinFET devices are Double gate FinFET (DG-FinFET), Triple gate FinFET (TG-FinFET). In this paper, a charge based
capacitance model has been proposed for modeling of TG-FinFET. The behavior and structure of the proposed device has been described in Verilog-A scripting language. IV characteristic of the proposed device has been observed, a three stage ring oscillator circuit is implemented with the proposed
device to generate 1 GHz signal for testing purpose.
Field Programmable Gate Array Implementation for Highly Secured Palm Print Authentication
Authors: Shrivastava Rajeev , Javeed Mohammad , Mallesham G.
Published: December 2020

To guarantee individual ID and profoundly secure recognizable proof issues, biometric innovations will give more prominent security while improving precision. This new innovation has been done lately because of exchange misrepresentation, security breaks, individual ID, and so on. The
excellence of biometric innovation is that it gives an exceptional code to every individual and can’t be duplicated or manufactured by others. So as to conquer the withdrawal of finger impression frameworks, this paper proposed a palm-based individual distinguishing proof framework,
a promising and new research region in biometric recognizable proof frameworks in light of their uniqueness, adaptability and a quicker and wide scope of high speeds. It gives higher security on biometric unique mark frameworks with rich highlights, for example, wrinkles, constant brushes,
mainlines, details focuses and single focuses. The fundamental motivation behind the proposed palm unique finger impression framework is to actualize a framework with higher exactness and speed up palm unique finger impression acknowledgment for some clients. Here, in this we presented an
exceptionally ensured palm print recognizable proof framework with intrigue extraction territory (ROI) with a morphological procedure utilizing a two-way un-crushed or course vector (UDBW) change to separate low-level palm fingerprints enrolled capacities for its vector work (FV) and afterward
after correlation is by estimating the separation between the palm transporters and the capacity of the palm and the capacity of the enlisted transport line and palm control. The after effects of the recreation show that the proposed biometric recognizable proof framework gives more noteworthy
precision and solid distinguishing proof speed.
Efficacy of a Novel Cloud-Centric Internet of Things Based Framework for Victim Localization in Context of Disaster Situation in Large Commercial Complexes
Authors: Brar Preetinder Singh , Singh Jaiteg
Published: December 2020

This work presents an early concept of a framework that is suitable for emergency response teams engaged in indoor rescue/evacuation operations in post-disaster scenarios. Such a concept warrants availability of information regarding the count of persons trapped inside the buildings
at different locations, and at different floors of a large commercial building. Although appreciable research has been done to improve disaster management using Internet of Things (IoT), yet most of those studies are aimed at disaster management in open spaces usually spanning the large geographical
areas ranging from a city to several hundreds of miles. This paper presents a framework that relies on IoT devices to transmit data to the cloud, based on which the rescue operations can be initiated without any considerable time lag. The systems based on the proposed framework could also
be used to assist the rescue teams during the rescue operations by providing the real-time updates of the vital parameters inside the disaster-struck buildings.
The Aspects of Artificial Intelligence in Software Engineering
Authors: Mudita  , Gupta Deepali
Published: December 2020

Software Engineering is the fundamental methodology used in the process of developing the software. Software Development Life Cycle (SDLC) is the backbone of software engineering. SDLC is emerging in several forms to support software development at different phases. SDLC plays as a
role of guide for engineers that are involved from traditional desktop application development to much trending development. The new emerging technologies accelerate the process of software engineering, resulting in saving time and resources and enhance the quality of software systems. This
paper focuses on technologies used to accelerate the process of software engineering in solving problems associated with its phases. The first section of this paper contains an introduction to Software Engineering (SE) and Artificial Intelligence (AI). The next section describes the aspects
of emerging technologies in software engineering. After this, the role of AI in SE is discussed followed by a conclusion in the last section.
Border Detection of Malaria Infected Cells in Microscopic Images for Diagnosis: A Computer Vision Approach
Authors: Somasekar J. , Padmanabha Reddy Y. C. A. , Ramesh G.
Published: December 2020

A computer vision approach is presented for border detection of malaria infected cells in microscopic blood images for accurate diagnosis. First, the microscopic 24-bits RGB color blood image converted in to 8-bits gray scale image for a single channel procesing. The poroposed two-stage
thresholdingmethod used for segmentation of malaria infected cells. Regarding border irregularities, the chosen descriptor is the perimeter factor and 4-connected neighbourhood. The experimental results on benchmark dataset that comprises around 300 images show that the proposed method successfully
detects borders of malaria infected cells with no prior knowledge of the contents of the image without parameter tuning. The proposed one compared with other existing methods and results are discussed.
A Robust Approach to Authentication of Handwritten Signature Using Voting Classifier
Authors: Kumari Kamlesh , Rana Sanjeev
Published: December 2020

This research paper’s main motive is to improve the recognition rate of Offline Signature Verification system. In our research, decisions of three classifiers i.e., Multilayer Perceptron, Random Forest Classifier and Naive Bayes are combined using voting classifier to determine
the output. The softwares used for this research are WEKA and Matlab. Performance of this approach is tested on CEDAR dataset for writer dependent model. Overall recognition rate of whole dataset of 55 users is 91.25%. Out of the dataset, the recognition rate of 45 users is above 85%.
Applications of Nanoparticles in Heavy Metal Removal for Wastewater Treatment at Brahmani River
Authors: Rath Himanshu Sekhar , Das Mira , Rath Smita , Dash U. N. , Tripathy Alakananda
Published: December 2020

The goal of this research is to determine the current standard of water quality along the Brahmani River stretch in terms of physico-chemical parameters. The River Brahmani receives a substantial amount of industrial waste in the identified study area and is witness to a large amount
of human and agricultural activities. Nowadays Ninety percent of Brahmani’s required water is secured with groundwater resources and it is essential to forecast pollutant content in those resources. Hence, this research aimed at using of nanoparticles such as Activated Carbons (ACs)
for removal of heavy metal such as nickel and zinc in Brahmani river using the Langmuir approach. Adsorption seems to be the most widely used method for heavy metal recovery due to its low cost, easy installation and the presence of alternative adsorbents. In addition, the process of adsorption
can also be made in use to recover heavy metal ions from wastewater. Despite these advantages, adsorption is hard to commercialize. Due to the strong absorption capacity, high number of pores and wide, common area, nanoparticles are treated as the effective method in removal of heavy metals
in rivers. Comparative analysis shows that seventy-one percent of heavy metals can be removed using the nanotechnology model.
Propagation of Torsional Surface Waves in Heterogeneous Half-Space with Irregular Free Surface
Authors: Selim Mahmoud M.
Published: December 2020

This study is an attempt to show the impacts of free surface irregularity on the torsional surface waves propagating in heterogeneous, elastic half-space. The surface irregularity is taken in the parabolic form at the surface of the half-space. The governing equation and corresponding
closed form solutions are derived. Then, the phase velocity of torsional surface waves is obtained analytically and the influences of surface irregularity are studied in detail. Numerical results analyzing the torsional surface waves propagation are discussed and presented graphically. The
analytical solutions and numerical results reveal that, the surface irregularity and heterogeneity have notable effects on the torsional surface waves propagation in the elastic half-space. Since the Earth crust is heterogeneous medium with irregular surface, thus it is important to consider
the effects of heterogeneity and surface irregularity on velocity of torsional surface waves propagating in the Earth medium.
Use of Power Transform Mixing Ratios as Hydrometeor Control Variables for Direct Assimilation of Radar Reflectivity in GSI En3DVar and Tests with Five Convective Storm Cases
Authors: Chen Lianglyu , Liu Chengsi , Xue Ming , Zhao Gang , Kong Rong , Jung Youngsun
Published: December 2020

When directly assimilating radar data within a variational framework using hydrometeor mixing ratios (q) as control variables (CVq), the gradient of the cost function becomes extremely large when background mixing ratio is close to zero. This significantly slows down minimization convergence and makes the assimilation of radial velocity and other observations ineffective because of the dominance of the reflectivity observation term in the cost function gradient. Using logarithmic hydrometeor mixing ratios as control variables (CV logq) can alleviate the problem but the high nonlinearity of logarithmic transformation can introduce spurious analysis increments into mixing ratios. In this study, power transform of hydrometeors is proposed to form new control variables (CVpq) where the nonlinearity of transformation can be adjusted by a tuning exponent or power parameter p. The performance of assimilating radar data using CVpq is compared with those using CVq and CV logq for the analyses and forecasts of five convective storm cases from the spring of 2017. Results show that CVpq with p = 0.4 (CVpq0.4) gives the best reflectivity forecasts in terms of root-mean-square error and equitable threat score. Furthermore, CVpq0.4 has faster convergence of cost function minimization than CVq and produces less spurious analysis increment than CV logq. Compared to CVq and CV logq, CVpq0.4 has better skills of 0–3-h composite reflectivity forecasts, and the updraft helicity tracks for the 16 May 2017 Texas and Oklahoma tornado outbreak case are more consistent with observations when using CVpq0.4.
Composing Her Growing Identities as a Mexican American
Authors: Zhou Xiaodi
Published: December 2020

This article studies the growing and changing cultural identifications of one early adolescent Mexican American girl as represented by her engagements with literacy. Her writing behaviors in particular manifested a changing cultural identity that reacted to and represented her response to a changing world. Her bilingualism and biculturalism manifested a dialogic innervation of distinct voices and truths, particularly set in the Trump-era United States. Through a theoretical framework of cultural hybridity and bordered identity, this study analyzes the complex linguistic, developmental, and cultural identities of a young Mexican American woman in the rural South.
Nursing Home Staff Members’ Experiences With and Beliefs About Unusual End-of-Life Phenomena
Authors: Claxton-Oldfield Stephen , Richard Natalie
Published: December 2020

Twenty-two members of a nursing home took part in a study examining their experiences with and beliefs about unusual end-of-life phenomena (EOLP). Nearly all the staff members had witnessed and/or been told about residents holding on for someone to arrive or for a specific event to occur before dying (95% and 91%, respectively). Other commonly witnessed/reported EOLP included residents having sudden, unexpected moments of lucidity, sensing or feeling the presence of deceased residents, residents’ dreaming about deceased relatives, friends or pets, and deathbed visions. More than three-quarters of the staff members regarded EOLP as transpersonal experiences, as comforting to dying residents and their family members, and as part of the dying process. Fourteen staff members described experiences they had had with EOLP in the nursing home. The most frequently described experiences involved the appearance of apparitions. Seventy-seven percent of the staff members expressed an interest in learning more about EOLP.
Relatively Easy Criteria for Success Enhances Motor Learning by Altering Perceived Competence
Authors: Iwatsuki Takehiro , Regis Claude J.
Published: December 2020

The purpose of this study was to examine whether enhancing success expectation by providing relatively easy criteria for success would, in turn, enhance motor learning outcomes. Thirty university student participants threw soft-golf balls towards a circular target, using their non-dominant arm; they performed seven blocks of 12 trials from a distance of 5.5 meters on Day 1, and one block of 12 trials on separate retention and transfer tests on Day 2. After the first block on Day 1, participants were randomly assigned to one of two groups in which they practiced the remaining six blocks of 12 trials: (a) one with relatively easy success (RES) criteria or (b) one with difficult success (DS) criteria. After the practice, we administered a perceived competence scale, a sub-scale of the Intrinsic Motivation Inventory (IMI). On Day 2, participants in the RES group outperformed those in the DS group on both the retention and transfer tests, showing enhanced motor learning. The RES group also self-reported higher perceived competence than the DS group, indicating that the mechanism for benefiting from easier success criteria may have been an alteration in participants’ perceived competence.
Hospitality at community wells: The life-giving waters of John 4:7–15
Authors: Bolden Cindy
Published: December 2020

Jesus’s encounter with the Samaritan woman at the well is a paradigmatic text for the Church, showing new possibilities for how the Church can engage the world, specifically engagement through invitational conversation and acts of charity at modern-day community wells. A Place at the Table is a pay-what-you-can café in Raleigh, North Carolina. Patrons can pay the suggested price, less than the suggested price, redeem a token worth the cost of a meal, or pay by volunteering at the café. Patrons who are able to “pay it forward” can further support the mission by tipping or buying meal tokens for others. At this café, a space reminiscent of an ancient “community well,” thirsty travelers receive the life-giving waters of acceptance, connection, and sustenance. The custom of hospitality is a life-giving and transformational practice for the Church, a viable and tangible way to connect with its neighbor and draw all persons into the experience of God’s love.