Reviewerly/exHarmony huggingface dataset:
A Robust Technique of Face Recognition Algorithm for Automated Attendance Management System

We recommend a robotized participation the board framework in this paper. This framework, in view of face identification and acknowledgment calculations, naturally distinguishes the understudy when he enters the homeroom and, by remembering him, denotes the participation. This paper depicts the framework design and calculations utilized in each stage. To assess the presentation of various face acknowledgment frameworks, diverse constant situations are considered. This paper likewise proposes the procedures to be utilized to manage dangers, for example, parodying. This framework spares time contrasted with conventional participation markings and furthermore helps screen the understudies.
Grundfos opens digital showroom in Dubai

Grundfos has officially opened its iFoss Lab in Dubai, the company's digital showroom and regional hub for cloud enabled water solutions.
Enhancing the Semantic Web of Things: A fog-centric Architecture and a Geospatial Indexing Method

The deployment of interoperability, mobility, security and scalability mechanisms is essential for IoT.While, these mechanisms are resources consumers, IoT devices are resources constrained.This dilemma requires the use of an IoT architecture capable of meeting compute and storage needs while remaining close to data sources.In this article, we propose a distributed IoT architecture based on Fog computing.This architecture does not marginalize the cloud and edge computing.But, tries to balance the role of each paradigm according to the resource needs dictated by the IoT challenges.Besides, we propose a distributed indexing structure constructed by encoding the loT resource locations in form of geohashes that we use in conjunction to the Prefix Hash Tree (PHT) structure to index and store the semantic description of the IoT resources in the fog layer.The features of our index are many: (1) it allows to aggregate resources with similar geohash in order to reduce the size of the index.(2) it takes advantage of the flexibility of the P2P structure.(3) it improves the speed and accuracy of the discovery leveraging the performance of the PHT structure.Last but not least, the index allows the efficient discovery of the mobile objetcs.
Connected Machine Learning and Networked AI

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Signature Recognition using 2D Discrete Wavelet Transforms

Signature recognition is one of the most secure techniques used for person identification. Wavelet transforms possess an extra time localization property over Fourier transforms, despite both are frequency localized. That is why; it is more useful to analyze the one dimensional and two dimensional signals both. First of all the features of a signature are extracted and then matching is performed. We have proposed feature extraction technique using discrete wavelet transforms level-1 and matching of signatures are performed using some statistical parameters of discrete wavelet coefficients using matching percentage, sum of absolute difference, mean square error and city block distance.
Data Centric Access Security- an Improvised Technique to Achieve Security in Cloud Environment

Cloud computing innovation has now turned into a good substitute to traditional computing technological developments This advancement of technology offers a new concept of a charge-per-use access resource model based primarily on virtualization technology. Because of the numerous advantages they offer, cloud computing concepts are achieving rapid adoption. This would comprise price-efficiency, time involved, and effective use of assets in computation. Given these advantages, there are many barriers to the widespread acceptance of this emerging technology, particularly data privacy and security issues. In extension to the conventional security hazards faced by internet-connected computer systems, cloud systems have relevant privacy and security problems due to the virtualization and multi-tenancy environment of the cloud. A further research target is focused on principles of Trust Computing (TC). Although these techniques offer users with mechanisms for evaluating and assessing security, they do not yield enough controlling functionality for users. In addition, Data Centric Security (DCS) is an evolving strategy intended to protect the data itself against migration towards the cloud.
Causal relation extraction and network construction of web events

The explosive increase of news data on the web has created a mass of causal knowledge, which explains the causal relation between two events that effect event will occur following the occurrence of cause event. Analysis of causal knowledge has gain lots of attentions due to its widespread applications, such as question answering, event prediction, generating future scenarios, and commonsense causal reasoning. However, few researches are based on Chinese news corpus, and no effective causal template is proposed for extracting Chinese causal relationship. Therefore, the method for extracting causal relation and building network of causal events from Chinese news corpus is proposed. First, we propose a method to obtain complete cue phrases set and present four common causal patterns to extract causal relations. And then we merge the same events by similarity calculation of causal events. At last, a network of causal events is constructed. Experiments on the datasets show the effectiveness of the proposed approach.
An Ensemble Stacked four Layered Architectures for Image Retrieval

It becomes possible to use large image server rapidly increasing. Content-Based Image Retrieval (CBIR) is an effective method for conducting its management and retrieval. This paper suggests the benefit of the image retrieval system based on content as well as innovative technologies. Compared to the shortcoming that the present system uses only a certain feature, this paper establishes a method that integrates color, texture and shape for image recovery and shows its additional benefit. Content Based image retrieval is a program that retrieves multiple images from an extensive collection of databases. The paper starts by explaining CBIR's fundamental aspects. Image Retrieval features such as color, texture and form will be addressed first. They address the similarity tests depending on which games are made and images are retrieved for a short time. The technique uses a four-layer structure that combines the characteristics of advancing inquiry and involves a combination of gabor and ripplet transition. Two image sets are obtained in the essential layer using the gabor and ripplet-based recovery techniques individually, as well as the top identified and critical images from the grapples of the top up-and-comer structure diagrams. The graph grapples use each individual part to recover six image frames from those in the image server as a demand for an increase in the next layer. The images throughout the six frames of images are analyzed for positive and negative information age in the third layer, and simpleMKL is correlated with acquiring expertise with proper examination subordinate variation loads to achieve the final result of image recovery. User interaction with the recovery system is critical for content-based image recovery, as dynamic request creation and adjustment can only be accomplished by including the user in the recovery process.
Multiple Parenting Phylogeny Relationships in Digital Images

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
The Gold Rush: Mining Bitcoin

Mining is a key operational concept in understanding how the Bitcoin protocol functions. It refers to a decentralized review process performed on every block of the blockchain to reach consensus, without the need for a central authority to provide trust. In other words, mining is the computational equivalent of peer review in a decentralized environment where neither party involved trusts the other. We will continue our discussion of the hash function here in more depth, as it refers to mining and solving proof-of-work functions. Then, we will integrate the concepts of block target values and network difficulty with mining and how mining has evolved to keep up with the increasing network difficulty. This will lead us further into talking about the different types of hardware mining that have been developed recently. We will end the chapter with an analysis of startups that began selling dedicated hardware for mining, leading to the Bitcoin mining arms race and the startups’ eventual failure.
Spline Subspaces

In this chapter we introduce discrete periodic splines and study their fundamental properties. We establish an extremal property of the interpolation splines. In terms of splines we offer an elegant solution to the problem of smoothing of discrete periodic data. We construct a system of orthogonal splines. With the aid of dual splines we solve the problem of spline processing of discrete data with the least squares method. We obtain a wavelet expansion of an arbitrary spline. We prove two limit theorems related to interpolation splines.
The Functions ifelse() and switch()

The two functions ifelse() and switch() execute flow control within a function or script. The function ifelse() evaluates a logical expression and chooses one of two values based on the result. The function switch() takes a value as an argument and returns another value based on the value of the first argument.
Fake Soft Drinks Detector using IOT

In a market, a lot of soft drinks are available, and to get more profit, the organizations sell the lapsed soft drinks, by basically changing the expiry date. For recognizing the lapsed soft drinks we can utilize the Fake Soft beverages finder by estimating the PH estimation of the Soft beverages. It assists with staying away from human medical problems like kidney issues, stomach torment. It is useful for ordinary citizens who expend soft drinks routinely. It can identify synthetic or profoundly harmed lethal substances included soft drinks. Right now, counterfeit soft drinks are identified utilizing PH esteem.
Authorship Verification

In the previous chapters, methods to address two authorship problems, i.e., authorship identification and authorship characterization, were proposed. This chapter discusses the third authorship problem, called authorship verification. The proposed approach is applicable to different types of online messages, but in the current study, the focus is on e-mail messages.
Solar resource assessment in Ireland, comparison of satellite data versus ground measurement

&amp;lt;p&amp;gt;Accurate solar resource assessments are essential to project a solar photovoltaic (PV) plant&amp;amp;#8217;s energy production &amp;amp;#8211; and ultimately forecast its revenue.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Solar resource assessments are the bedrock of the &amp;amp;#8216;Revenue&amp;amp;#8217; line in PV financial models. In today&amp;amp;#8217;s competitive financing environment, the assumptions underlying solar resource assessment often have make-or-break impact on project valuations. It&amp;amp;#8217;s critical that investors trust the numbers provided.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;To quantify solar resource, industry typically compares different irradiation databases derived from multiple physical sources &amp;amp;#8211; whether measurements or satellite images. There is always some level of scatter; in Western Europe this is often around 3%, after excluding outliers.&amp;amp;#160; Satellite database are never as good as accurate ground measurement.&amp;amp;#160; And the rather narrow variation observed is due to past calibration of satellite derived model with data from weather stations.&amp;amp;#160; The reality can be different when it comes to Ireland.&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The solar sector is currently experiencing a rapid development in the Republic of Ireland, making the yield assessment and by extension the solar resource estimation key for the bankability of the projects.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The aim of our work was the validate the accuracy of different databases, available in Ireland.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The first step of this analysis will be to qualify our data sources. Everoze and Brightwind have access to measurement campaigns from multiple solar projects in Ireland. All the gathered dataset will be processed, applying state of the art quality control, to retain only trustable information. &amp;amp;#160;The quality check will also include the sensors themselves, with a verification of the accuracy and calibration certificates of the different pieces of equipment.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In a second step, the qualified datasets will be used to compare satellite derived data.&amp;amp;#160; We plan to use CAMS, SolarGIS and Meteonorm.&amp;amp;#160; The intention is to categorise our results in regions, classified based on the difference in annual irradiation between different databases in order to reduce uncertainty &amp;amp;#8211; and ultimately boost investor confidence in energy yield assessments.&amp;lt;/p&amp;gt;
Getting Started with Java

Android apps are written in Java and use various Java application program interfaces (APIs). Because you’ll want to write your own apps, but may be unfamiliar with the Java language and these APIs, this book teaches you about Java as a first step into Android app development. It provides you with Java language fundamentals and Java APIs that are useful when developing apps.
Oppdagelse og navngivning

There is a fundamental enthusiasm and curiosity that drives our attitude towards experimentation. Free basic research is the fundament for all new apprehensions. Each production leads us into new landscapes. Experimentation is artistic immersion.The concept of risk and possible failure is a natural part of this experimentation.Without taking risk, art would remain stagnant, and the creative spirit would be wasted on our own fears. In this exposition we will elucidate some of the many fields of interest and tools for expression we have worked with during the development of our latest production – HANNAH – which premiered September 2017 at Henie Onstad Art Center in Oslo in connection with the Ultima Festival. In HANNAH Verdensteatret works with elaborate spatial compositions that provokes a state of absorption in an immersive audio-visual space. These compositions consists of material generated in an electronic feedback system. This material forms a sedimentation process that unfolds as a fixed attention towards exhaustion and the act of observing slow changes. Like a physical object slowly affect its surroundings. A production from Verdensteatret is a glimpse of a present, a state of transitions and passages through phenomenons. The present is a memory in motion. At the same time, there has never been so much past as right now.
Orebody Characteristics and Deposit Genesis Analysis of the Ore Cluster I of Qunli Iron Mine in Golmud, Qinghai Province, China

Qunli Iron Mine is in the mixed petrified gneiss interbedded with marble and skarn strata of the Lower Rock Formation of the Jinshuikou Group formed in the Lower Proterozoic, and it belongs to a skarn deposit related to migmatization.The regional tectonic structure is located in the central and western sections of the Qimantag-Dulan orogenic belt.The metallogenic belt belongs to the Qimantag-Dulan Hualixi iron, cobalt, bismuth, lead, zinc, copper and silver metallogenic belt.The area has experienced many complicated and strong tectonic movements, and the structural traces of different scales and mechanical properties are well developed.In particular, the northwest-westward compressive and torsional faults constitute the main structural framework in the region, which plays an important role in controlling the distribution of strata, magmatic rocks, metamorphism and mineral resources in various periods.
Medical Applications using Blockchain and Machine Learning

Blockchain was particularly used in Cryptocurrency technologies. Prior to 20th century there was no other technologies for determining the health of a person naturally. At the dawn of the 21st Century machine learning played a vital role in determining the health of a person using various algorithms and natural language processing techniques. Now for every machine learning technique to work for it needs data. Data is very important as far as providing information is concerned. Data sharing plays a vital role in improving accuracy of techniques involved. Along the blockchain technology plays a vital role in this aspect. Thus, the merging of these two techniques involve provides highly accurate results in terms of machine learning with privacy and reliability of Blockchain technology. This technique uses natural language processing techniques which focuses basically mainly on healthcare techniques such as cancer detection, prediction of machines used in healthcare etc. Prior to healthcare which is used in blockchain it was used in cryptographic techniques only. Also, this technology can be used to provide medical suggestions to the doctors based on the condition of the patient. The accuracy of this method can be increased more using providing as much data as we can. This combination of Blockchain and machine learning algorithms can be used widely in healthcare, where the data is highly secured and there is no fear of data loss. This paper involves how combining these two technologies can be helpful in healthcare.
Netspeak in China: features and impact on standard Chinese language

In order to explore the impact of Netspeak on the modem standard Chinese language, this study investigates the features and sources of Netspeak and then examines two anxieties that prevail around Chinese society: (1) Can the English elements in Netspeak be regarded as a sign of "English Invasion" and destroy the purity of Chinese language or even blemish Chinese cultural sovereignty? (2) Can "Netspeak confuse people's perception of what standard Chinese language should be so as to have negative impact on Chinese language? Related literatures both in China and in the western countries are examined. Some linguistic theories are applied or verified. Quantitative research method is used to verify my hypothesis that Netspeak will not have a deeply negative impact on Modem Standard Chinese in the long run, although it has already become a popular social dialect in the China"--From introduction, page 4.
An Outline Implementation for Habitual Production of Ontology from RDF To Medical Data

Information on the web is extremely growing in current years with a quicker velocity.This enormous or capacious data has driven intricate troubles for information recovery and information organization.As the data resides in a network with numerous forms, knowledge management on the web is a challenging task.Here the novel 'Semantic Web' concept may be used for understanding the web contents by the machine to offer intelligent services efficiently with a meaningful knowledge representation.The information recovery in the conventional web source is centered on 'page positioning' strategies, though in the semantic web the information recovery forms depend on the 'idea based learning'.The proposed work is gone for the improvement of another system for programmed age of cosmology and RDF to some continuous system information, removed from numerous storehouses by following their URLs and Text Documents.The enhanced altered ordering method is connected for the cosmology age and turtle documentation is utilized for RDF documentation.A program is composed for approving the extricated information from different archives by expelling undesirable information and considering just the report segment of the website page.
Abstract 1648: Deep learning tissue "fingerprints" to identify patients and predict clinical subtypes of breast cancer from digital pathology images

Abstract Inspired by facial recognition, we define an analogous problem in digital pathology called tissue matching. The objective is to match histology image patches to the patient. Unlike many classification problems in pathology, tissue matching comes with its own ground truth, and does not require subjective annotation. Using tissue-matching via deep neural networks, we developed strategies to overcome common sources of noise in histology data, including H&amp;E and slide scanner variability. We demonstrate that the typical approach of increasing the training set size, in the current study up to 12,000 tissue cores, yields only moderate gains in test accuracy, while including a loss term promoting style-invariance cooperatively improves the impact of scaling training set size. Our best neural network learned features that matched patients from the test set of H&amp;E image patches with 93% accuracy (n=104 patients, baseline accuracy &amp;lt;1%). Leveraging this network’s identification ability, we applied its internal representation as a feature vector (tissue fingerprint) to apply to other problems in pathology. We found that a fingerprint-based classifier could predict estrogen receptor status from breast cancer whole-slides on two separate cohorts with high accuracy (AUCROC=0.89), a sizeable improvement over previous approaches. This work presents a novel, scalable, and transparent approach to train neural networks to identify distinctive features of pathology images. These features have demonstrated utility in classifying biomarkers from morphology and have the potential to assist in a number of difficult tasks in pathology, including tissue subtype classification and patient tumor similarity assessments based on morphometry. Citation Format: Rishi Rawat, Fei Sha, Darryl Shibata, Daniel Ruderman, David Agus. Deep learning tissue "fingerprints" to identify patients and predict clinical subtypes of breast cancer from digital pathology images [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 1648.
Design and Implementation of Image Watermarking Scheme based on Exponential Function

In this paper, exponential transformation based watermarking of multimedia images has been proposed. The principle behind the scheme is anticipated in frequency domain to elevate robustness and big data entrenching capacity. In the anticipated approach, the secrete image is first imperiled for compression using exponential function and then entrenched onto the cover data. Statistical analysis of resultant data proves better robustness in par with other existing methodologies.