Reviewerly/exHarmony huggingface dataset:
STRETCHED PEBBLE ANALYSIS OF THE CHEAHA QUARTZITE IN THE ALABAMA SOUTHERN APPALACHIAN MOUNTAINS

Deformation in the Southern Appalachian Mountains is typically correlated with one of three phases of Paleozoic orogenesis: the Ordovician Taconic, the Silurian-Devonian Acadian/Neoacadian, and the Pennsylvanian-Permian Alleghenian. The age and sequence of structural development in metamorphic rocks in the Appalachian Piedmont may be more complex than previously hypothesized. Geologic mapping and structural analysis on Porter Gap and Clairmont Springs 7.5-minute quadrangles in east central Alabama, is expected to establish a relationship between early Mississippian metamorphism and thrust faults containing the Talladega Group. Currently, metamorphism in the area is bracketed to Late Devonian -Mississippian in age. It is currently unknown if thrust fault juxtaposition occurred at depth around the same time as metamorphism or if the faulting post-dates metamorphism and thus deformed previously metamorphosed rock units. To test these models, we present structural data, including stretched pebble conglomerate measurements, to assess the relative ages of metamorphism, deformation, and uplift compare to those age estimates for orogenesis in the southern Appalachians. Clasts are roughly aligned E-W, which does not vary across strike changes along a map scale oroclinal bend. We interpret a previously unmapped regional thrust fault that may be responsible for clast elongation and records thrust fault transport during early Alleghenian deformation.
Cataloging E-Journals at the University of Texas at Austin: A Brief Overview

The late 1970s at the University of Texas at Austin's General Libraries were exciting. The early 1980s brought a new reality to Technical Services at the University of Texas. Serials Cataloging looked for ways to cope with its reduced staffing while at the same time meeting its cataloging and serials maintenance responsibilities. Once the online catalog, UTCAT, was implemented in 1988, Serials Cataloging was deluged with requests to undo full microform cataloging for titles cataloged in earlier years and bring them under the Back-Up-to-Paper policy. With no assurances of additional staffing, the Back-Up-To-Paper policy was raised as a possible solution. At the forum on e-journals, organized and presented by collection development staff, the audience sat in rapt attention as speaker after speaker extolled the benefits of and demonstrated access to e-journals by way of UT Library On-line, the General Libraries Web page.
Symmetric Encryption and Scatter/Gather I/O Using KAMWEB

Recent advances in optimal algorithms and vir-tual configurations are always at odds with write-ahead logging. After years of unfortunate research into 32 bit architectures, we show the evaluation of sensor networks. In order to solve this grand challenge, we concentrate our efforts on validating that virtual machines and sensor networks can agree to realize this objective.
Introduction

In this chapter some prerequisites for ordinal analysis are explained such as one-sided sequent calculi, recursion-theoretic prerequisites, and the definition of the proof-theoretic ordinal. Our base theory, the elementary (recursive) arithmetic EA, is introduced, and the Kripke–Platek set theory KP is also defined. These materials are scattered in textbooks on logic.
Understanding Angular and ASP.NET Core MVC

This book is about using Angular and ASP.NET Core MVC together to create rich applications. Individually, each of these frameworks is powerful and feature-rich, but using them together combines the dynamic flexibility of Angular with the solid infrastructure of ASP.NET Core MVC.
String

A string is a series of characters that can be stored in a variable. In PHP, strings are often delimited by single quotes.
Maneuvering Your Serials Troops Through the Mine Fields of Change

This workshop allowed participants to assess their current means of dealing with change. It provided methods for planning the process of change, suggestions for handling the psychological aspects of organizational change, and opportunities for sharing positive and negative experiences related to change. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address: &lt;docdelivery@haworthpress.com&gt; Website: &lt;http://www.HaworthPress.com&gt;]
An efficient medical image watermarking technique using integer wavelet transform and quick/fast response codes

Securing the medical images to make it tamper free is a terribly difficult task. With the advanced digital watermarking (DWM) technique, we are able to protect the medical images by evaluating validation, dependability, privacy and integrity. The DWM is implemented in two main domains: transform and spatial. The DWM is mostly implemented using the transform techniques such as singular valued decomposition (SVD), discrete cosine transform (DCT), discrete wavelet transform (DWT), integer wavelet transform (IWT) and combination of these techniques. One of the foremost challenges in these technologies is information embedding capability and this parameter is considered for evaluation of the system. One of the possible ways to reduce the number of embedding bits in information is to use quick response code (QR). The proposed DWM system uses: IWT, bit plane and QR code.
Web-based network design learning system

Web-based learning system offer a better learning environment for computer science students. This paper presents a web-based learning system that helps students understand the essential knowledge about networking design. The aim of the web-based learning system is to simplify the process of network designing by using a user-friendly interface.
Features of the education organisation for the students from Turkmenistan, future teachers of physico-mathematical disciplines

Ushynsky University has been actively developing the international sphere of activity for a long time, in particular, attracting foreign students to study in it. In this regard, the urgent task for the university is to organise an effective learning process for foreign students in order to ensure high quality educational services within their chosen specialties. Experimental research work on the organisation of education for the students from Turkmenistan was carried out in the process of profession-centred training targeted to the future teachers of physical and mathematical disciplines. Theoretical analysis of the problem and practical methods were used as research methods: questionnaires, observations, certification to identify the conditions for adaptation and the features of the education organisation for the students from Turkmenistan. The factors influencing the adaptation of students to the conditions of education at Ushynsky University have been determined, the motives for their choice to study at the Faculty of Physics and Mathematics have been identified. It was found out that the most influential factor hindering the adaptation of foreign students to living and studying in Ukraine are household difficulties. However, the factors such as interpersonal and pedagogical communication were not identified as the ones which hinder their adaptation. This result testifies to the significant potential and positive prospects of the profession-centred training targeted to citizens of Turkmenistan. The results of the survey showed that the most influential motives for obtaining pedagogical education were as follows: foreign students' desire to obtain a diploma of higher pedagogical education and work as a teacher, the prestige of higher education in Turkmenistan, which indicates the conscious choice of most students to study at a pedagogical institution of higher education. The creation of a multimedia educational and methodological complex provided the delivery of information in an interactive mode for distance learning, which had a positive impact on the learning outcomes and was especially relevant in the online framework of the educational process. The prospects for further research are seen in the implementation of the developed methodology in the development of further sections of General Physics.
A Blockchain-Based Scalable Approach to Protecting Electronic Voting from Central Authority Attacks

In order to have a trustworthy electronic voting system, the system is required to protect voter privacy, ensure election integrity, and provide means of verifiability in a trusted and secure manner. Recently, blockchain has been used to improve election integrity significantly. The use of blockchain has significant benefits for both universal and individual voter verifiability due to the property of immutability of the blockchain. However, it can quickly run into scalability problems when protecting voter eligibility qualification and voter privacy. Some existing scalable electronic voting approaches are subject to attacks from central authorities. In this paper, a scalable approach to protecting electronic voting from central authority attacks is presented. The biased blind multisignature is developed and used to improve the scalability of our approach. It is shown that this approach is substantially better than the existing approaches.
Educational process in the system of distance trainings

The article analyzes the problem feld of the distance education system. To determine the popularity of distance learning in Moscow universities among teachers and students, a sociological survey was conducted, which allowed us to identify an increasing trend in the number of students who would prefer distance learning to traditional with a strict schedule and draw conclusions about the prospects for distance education in Russian higher education institutions. The article presents a model of the educational process in the distance learning system with a brief description of each block. The model includes all the stages that a student goes through when entering, studying and graduating from a higher educational institution before receiving a diploma confrming the appropriate level of education. Each of the blocks contains descriptions of the actions required to pass this stage, as well as recommendations for improving and extracting the maximum result for both teachers or educational institutions, and for the students themselves. Alternative options are provided if one of the stages is stopped or impossible to overcome. Conclusions are drawn, in which cases the presented model of the educational process is applied, and the prospects of distance education in General are considered.
Check out our improved NBA website

Our secure website, wileyonlinelibrary.com/journal/nba , provides subscribers with access to all of our Nonprofit Business Advisor content online at no additional charge.
Ranking of Cloud Service Providers using Multi Layered TOPSIS

Cloud computing is one of the popular technological advancement in the current IT industry. The multifaceted benefits of cloud computing has attracted huge number of public and industrial customers. There are numerous cloud service providers available with variations in type and cost of resources. This makes it very difficult to select a suitable service provider. The Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) is a popular method used of ranking service providers. However it reuires parameters that belong to a same category and rating scale. In this research we propose M-TOPSIS (Multilayer TOPSIS), a technique for ranking of service providers based on different categories with multiple parameters having different rating scales. The proposed technique applies TOPSIS for each category of input. The ranking of service provider in each category is then used to rank the available service providers, based on the overall performance. The efficiency of the proposed technique is compared with the existing models and the experimental results proved that the M-TOPSIS is able to rank service providers more accurately than the other existing models like E-FPROMTHEN.
Abstract 4945: Project Survival: Engineering a phenomic and artificial intelligence driven precision medicine biomarker pipeline for pancreatic adenocarcinomas

Pancreatic cancer is a complex and dynamic disorder necessitating a comprehensive clinical design integrated with robust OMICS technologies and AI analytics to identify potential molecular and clinical signatures of diagnosis, progression, and treatment outcomes. Project Survival is a multisite prospective longitudinal study currently in the 4th year of a 6 year initiative of sampling and analysis of subjects in 6 categories: healthy volunteers with a first degree relative with pancreatic cancer (N=39), pancreatitis (N=34), pancreatic cystic neoplasm (N=52), suspicious pancreatic masses with pathology other than pancreatic cancer (N=22), early stage (N=66), locally advanced (N=123), and metastatic pancreatic cancer (N=99). All diseased patients are longitudinally sampled multiple times per year for sera, plasma, buffy coat, saliva, urine, and tumor/adjacent normal tissue. The BERG Interrogative Biology® platform is employed for multi-omic mass spectrometry analysis (metabolomics, lipidomics and proteomics) and applies artificial intelligence (bAIcis®, BERG Artificial Intelligence Clinical Information System) technologies. bAIcis® is harnessed to align the multi-omic profiles with longitudinal clinical information to infer probabilistic cause-and-effect relationships among molecular and clinical variables in a network-based model. Multiple longitudinal time points continue to be collected during the course of the six-year timeline enabling dynamic modeling. The value of this longitudinal study is in the epidemiological assessment of patient type progression to more advanced stages and identification of biomarkers and clinical features that align with the shifts observed in the patient populations. Collectively, we are incorporating patient progression with longitudinal sampling to investigate predictive signatures of disease advancement. Biomarker panels with AUC > 0.7 will be pursued in a further prospective clinical study with a larger subject number. The integration of multi-omic analysis with artificial intelligence has identified several biomarker panels that meet numerous unmet needs for the identification and clinical stratification of pancreatic adenocarcinoma.Citation Format: Eric Michael Grund, Michael A. Kiebish, Viatcheslav R. Akmaev, Rangaprasad Sarangarajan, John J. Crowley, Amy Stoll-D'Astice, Tori Singer, Corinne Decicco, Wendy Hori, Abena Darkwah, Lixia Zhang, Valerie Bussberg, Leonardo O. Rodrigues, Emily Y. Chen, Tomislav Dragovich, Manuel Hidalgo, Niven R. Narain, A James Moser. Project Survival: Engineering a phenomic and artificial intelligence driven precision medicine biomarker pipeline for pancreatic adenocarcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4945.
Rule Based Extractive Summarization a nd Title Generation

Text summarying is a process by which the most important information from the source document is precisely found. It stands for the information condensed to a longer text. Text summary is broken down into two approaches: extractive summary and abstractive summary. The proposed method creates an extractive summary of a given text and generate an appropriate title for the generated summary. Extractive summary is generated through sentence selection by using Rule-based concept. Eight different features are considered to rank each sentence according to its importance. Ranking assigns a numerical measure to each sentence. After ranking, sentences that has high rank compared to others will be selected to form the summary. The frequently occurring bi-gram is selected as the title for the summary. The system performs better than existing extractive summarization techniques like Graph-based system and achieved a precision of 0.7
KNN-based ensemble selection for imbalance learning

Classification of imbalance datasets is one of the crucial issues in the field of machine learning. Since the distribution of imbalance dataset is extremely skew, the traditional classifications often come up with a disappointed performance. Different with the traditional methods, this paper reconsiders class imbalance problem from the viewpoint of ensemble learning. However, many ensembles tend to build base classifiers not perfectly; some bad performed classifiers which are helpless to improve the generalised ability of ensemble would be produced. To solve this problem, a novel method named ensemble algorithm named NNES (k-nearest neighbour based ensemble section) was proposed in this paper. To evaluate the local properties of an unlabeled instance, NNES tends to pay more attention to minority and improve its performance on imbalance datasets. Experimental results show that NNES can improve the classification performance of the imbalance datasets effectively. Moreover, this improvement would be strengthened when the sampling techniques were introduced in.
Parsing XML Documents with SAX

Java provides several APIs for parsing XML documents. The most basic of these APIs is SAX, which is the focus of Chapter 2 .
Human behavior classification based on CEEMDAN-WT denoising and cascade forest

Human Behavior Recognition (HAR) is a hot research topic in the fields of machine learning, human-computer interaction and pattern recognition, which has a wide range of social application value. Considering poor generalization ability of machine learning model and the long training time of deep learning model, a human behavior classification method based on cascade forest model is proposed. Firstly, original data set is screened and divided into several segments by using human behavioral acceleration data set provided by wireless data mining laboratory of Fordham University. Then, the filtering process is completed by combining complete EEMD with adaptive noise(CEEMDAN) and wavelet transform. Taking 10s as the window size, the average composite acceleration, grouping proportion and various statistics are extracted from the triaxial acceleration data as features. The six behaviors (walking, jogging, upstairs, downstairs, sitting, standing) are classified by using the Cascade Forest Algorithm in comparison with traditional machine learning method and Deep Neural Network (DNN) algorithm. Experimental results indicate that the classification indexes of cascade forest are above 96%, which is better than traditional machine learning and deep neural network algorithm and shows the proposed model effectiveness for human behavior recognition.
A combined hierarchical algorithm of mammograms registration using mutual information and a point based matching approach

Mammographic image registration is an important process in the comparative analysis of mammograms that aims to correctly interpret them. In this paper, we proposed a combined hierarchical framework for a non-rigid mammograms registration. So, the conjoint use of the multi-resolution and the multigrid hierarchical strategies allows to increase progressively the warp complexity with a fixe size of the manipulated data contributed then to a finest registration with acceptable computing cost. To perform registration process, a hybridisation of an intensity-based registration method using mutual information and a point-based matching approach using the Thin Plate Spline approach is achieved. This hybridisation allows not only to outperform the registration accuracy by using the mutual information as a similarity measure adapted to not similar images but also to decrease the algorithm convergence time. Registration performance has been evaluated by aligning mammograms from the MIAS database and results demonstrate the effectiveness of the proposed algorithm for mammograms registration.
The Upshot of Omniscient Strategies on Steganography

The ramifications of versatile systems have been broad and unavoidable. Such a theory from the start appears to be unforeseen however upheld by related work in the field. Following quite a while of doubtful investigation into forward-mistake remedy, we demonstrate the examination of DHTs. At-tal, our new application for the reenactment of the maker customer issue, is the answer for these issues
Secure session between an IoT device and a cloud server based on elliptic curve cryptosystem

The internet of things (IoT) has brought the properties of convenience, intelligence, and manageability into our daily lives. Nevertheless, it also gives malicious attackers lots of opportunity to compromise our private information. Hence, the security issue over IoT has become an emergent and crucial research topic. Kalra and Sood (2015) proposed an authentication scheme for IoT device and cloud server. Unfortunately, Chang et al. (2017) have pointed out the weaknesses of Kalra and Sood's scheme and provided proper improvements. However, we have found that the improved version still exist potential risks. Thus, we aim to develop a brand-new ECC-based authentication mechanism for offering a secure session between an IoT device and a cloud server. In particular, the new method is proved secure under the examination of AVISPA, which is a formal verification tool.
How Journals Are Made: Real World Workflows, Real Work

Most people–including many information professionals–do not realize how much work goes into producing a journal. The most significant misunderstanding is that most of the costs go away when print goes away. Small scholarly publishers like societies have an especially hard time in this environment. When journals were published only in print, the manufacturing process hid the details; authors wrote articles, publishers edited them and then turned them over to printers who did the rest. Most larger publishers–and smaller publishers working with larger vendors–now use electronic manuscript tracking and peer review systems to help with this work. Most people are shocked at how much a good copy editor changes in an author’s “finished” manuscript. The process of copy editing is also increasingly done electronically. Coding really gets complicated in the composition and page layout process. Most vendors use expensive, complex composition systems to do all this.
Configurable Beam Splitting of Single Photon in Cold Atoms

We demonstrate a dynamically configurable beam splitter (BS) for single photon wavepacket via electromagnetically-induced-transparency storage in cold atoms. This quantum-memory based controllable BS may have applications in a quantum information processing network.
Sign Language Recognition-A Survey of Techniques

Sign language is the only method of communication for the hearing and speech impaired people around the world. Most of the speech and hearing-impaired people understand single sign language. Thus, there is an increasing demand for sign language interpreters. For regular people learning sign language is difficult, and for speech and hearing-impaired person, learning spoken language is impossible. There is a lot of research being done in the domain of automatic sign language recognition. Different methods such as, computer vision, data glove, depth sensors can be used to train a computer to interpret sign language. The interpretation is being done from sign to text, text to sign, speech to sign and sign to speech. Different countries use different sign languages, the signers of different sign languages are unable to communicate with each other. Analyzing the characteristic features of gestures provides insights about the sign language, some common features in sign languages gestures will help in designing a sign language recognition system. This type of system will help in reducing the communication gap between sign language users and spoken language users.