Reviewerly/exHarmony huggingface dataset:
Attention Based GRU Network for Domain Adaptation in Sentiment Classification

Domain adaptation in sentiment classification, as a worthwhile research area, aims to use the available labeled data of a source domain to classify the unlabeled data in the target domain. This approach saves costs and efforts and also improves the efficiency of sentiment classification. This paper proposes the attention based GRU network for domain adaptation in sentiment classification (AGN). This algorithm learns the semantic meanings of the text based on GRU or Bi-GRU, and makes hierarchical mapping from words to sentences and then to the document. The Attention layer is added to capture the core emotional words and sentences. Then, the adversarial idea is brought in, that is, auxiliary domain classification task and sentiment classification task are performed to jointly learn feature representations. Review datasets of five domains on the Amazon online platform are used, and an experiment is performed with 20 pairs of data. The result indicates that the proposed algorithms are able to improve the accuracy of sentiment classification. Finally, the AGN algorithms are interpreted by visualizing the Attention layer.
A new method of combining colour, texture and shape features using the genetic algorithm for image retrieval

Semi-automatic or automatic image indexation emerged because manual image indexation is slow and tedious. Generally, this first indexation is used as part of a content-based image retrieval system (CBIR). To have a powerful CBIR system, it is necessary to be concerned with three main facets: 1) the choice of the descriptors (based on shape, colour and texture and/or a combination between them); 2) the process of indexation and finally; 3) the retrieval process. In this work, we focus mainly on an indexing based on genetic algorithm and particle swarm optimisation (PSO) algorithm. We chose an optimal combination of colour, shape and texture (PCM: powerful combination method) descriptors. The fruit of our research work is implemented in a system called image search engine (ISE) which showed a very promising performance. In fact, the performance evaluation of the PCM method of our descriptors combination showed upgrades of the average precision metric from 66.6% to 89.30% for the 'food' category colour histogram, from 77.7% to 100% concerning CCV for the 'flower' category, and from 44.4% to 87.65% concerning the co-occurrence matrix for the 'building' category using the Corel dataset. Likewise, our ISE system showed much more interesting performance compared to what was shown in previous works.
Information processing for Similar Source code using LSH Algorithm

In this study, we propose a method to quickly search for similar source files for a given source file as a method to examine the origin of reused code. By outputting not only the same contents but also similar contents, it corresponds to the source file that has been changed during reuse. In addition, locality-sensitive hashing is used to search from a large number of source files, enabling fast search. By this method, it is possible to know the origin of the reused code. A case study was conducted on a library that is being reused written in C language. Some of the changes were unique to the project, and some were no longer consistent with the source files. As a result, it was possible to detect the source files that were reused from among the 200 projects with 92% accuracy. In addition, when we measured the execution time of the search using 4 files, the search was completed within 1 second for each file.
System of Cryptographic Protection of Information Based On Deterministic Chaos

In this paper we present a software system for cryptographic information protection based on deterministic chaos. The program system functionality includes encryption and decryption of text and graphic information on the basis of a random number generator, which is played by the Lorentz attractor. The use of an attractor in this program system guarantees randomness and absolute randomness when issuing numbers, limited only by the initial parameters. It is also necessary to transfer encryption parameters, excluding the possibility of its interception, because Encryption parameters are used in the program as decryption keys. After the process of text encryption, the program performs a frequency analysis of the input and output files. Accordingly, the frequency of a certain group of letters, which is vulnerable to frequency analysis, must be clearly expressed in the input file. In the output file, the frequency should be stable and uniform, thereby proving the effectiveness of encryption.
Solutions: Calculus

This textbook is a comprehensive introduction to the key disciplines of mathematics - linear algebra, calculus, and geometry - needed in the undergraduate physics curriculum. Its leitmotiv is that success in learning these subjects depends on a good balance between theory and practice. Reflecting this belief, mathematical foundations are explained in pedagogical depth, and computational methods are introduced from a physicist's perspective and in a timely manner. This original approach presents concepts and methods as inseparable entities, facilitating in-depth understanding and making even advanced mathematics tangible. The book guides the reader from high-school level to advanced subjects such as tensor algebra, complex functions, and differential geometry. It contains numerous worked examples, info sections providing context, biographical boxes, several detailed case studies, over 300 problems, and fully worked solutions for all odd-numbered problems. An online solutions manual for all even-numbered problems will be made available to instructors.
Review of &amp;quot;ClimateNet: an expert-labelled open dataset and Deep Learning architecture for enabling high-precision analyses of extreme weather&amp;quot;

Review of GMD-2020-72 ClimateNet: an expert-labelled open dataset and Deep Learning architecture for enabling high-precision analyses of extreme weather
TriAG:Answering SPARQL Queries Accelerated by GPU

In this paper, we present a new RDF engine accelerated by GPU, named TriAG, to query the RDF graph efficiently.Firstly, to improve the processing efficiency of SPARQL on RDF, new storage models of RDF systems is proposed.Then we use query decomposition to further reduce the query response time; at the same time, a cost model based on machine learning is used to determine the granularity of query decomposition.After this, we develop a MapReduce-based algorithm to join solutions of SPARQL subqueries in a parallel way.Finally, we implement TriAG and evaluate it by comparing it with two popular SPARQL query engines, namely, gStore and RDF3X on the LUBM benchmark.The experiments demonstrate that TriAG is highly efficient and effective.
Arrays

An array is a data structure used for storing a collection of values that all have the same data type.
Heaps

This chapter will introduce heaps. A heap is an important data structure that returns the highest or lowest element in O(1) time. This chapter will focus on explaining how heaps are implemented as well as how to work with them. One example is heap sort, which is a sorting algorithm based on heaps.
Preface: TALENTA-International Conference on Science and Technology 2019

Distinguished guests and participants, Assalamualaikum Warahmatullahi Wabarakatuh. Good Morning Ladies and Gentlemen. Welcome to Medan, a fascinating city, and welcome to USU. On behalf of the Organizing Committees, we would like to express a warm welcome to all delegates and participants to the TALENTA-International Conference on Science and Technology (TALENTA-ICST) 2019. It is a great honor for all faculties and departments at Universitas Sumatera Utara (USU) to support the conference. I believe that this conference is an important forum for exchange of information and research results among us, who come from different countries, different educational and research institutes, and different research interest. But we are one in the same room today for all of us have a same target to achieve our goals, i.e. to support our competitive advantage TALENTA. As we know USU has a competitive advantage named TALENTA, namely Tropical Science and Medicine, Agroindustry, Local Wisdom, Energy (sustainable), Natural Resources (biodiversity, forest, marine, mine, tourism), Technology (appropriate) dan Arts (ethnic). Thus, I hope that the contacts established during the conference may bind us in one vision. A vision is achieving better tomorrow together. Wish that we may strengthen close relationship among TALENTA-ICST members, develop more join research project, and very importantly we have a strong commitment to support the TALENTA-ICST events. In closing, I would like to thank the Rector of USU and also the Ministry of Research, Technology and Higher Education of the Republic of Indonesia, for supporting the research climate at USU. I would also like to thank all contributors for your good cooperation. Special thanks for TALENTA-ICST Organizing Committee members for their hard work and patience. Your Sincerely, Prof. Dr. Tulus, Vor.Dipl.Math., M.Si Chair of the Talenta-ICST 2019
Simple IoT simulation

While analyzing iot projects it is very expensive to buy a lot of sensors , corresponding processor boards, power supplies etc. Moreover the entire process is to be replicated to cater to large topologies. The whole experiment is to be planned at a large scale before we can actually start to see analytics working. At a smaller scale this can be implemented as a simulation program in linux where the sensor data is created using a random number generator and scaled appropriately for each type of sensor to mimic representative data. This is them encrypted before sending it over the network to the edge nodes. At the server a socket stream now continuously awaits sensor data Here the required sensor data is retrieved and decrypted to give true time series data. This time series is now given to an analytics engine which calculates the trends and cyclicity and is used to train a neural network. The anomalies so found are properly deciphered. The multiplicity of the nodes can be characterized by having several client programs running in separate terminals. A simple client server architecture is thus able to simulate a large iot infrastructure and is able to perform analytics on a scaled model
Challenges Analysis Security for Cloud Computing

The Web has become an imperative prerequisite for existence, and cloud computing is a new innovation that has gotten to be the center of the research since of its capacity to decrease the costs related to cloud computing.And everybody presently works beneath the cloud computing environment, social media, companies, government offices, and clients.But at the same time, this sort of innovation faces security challenges that incorporate data confidentiality, data integrity, and availability.For that, numerous control included inside the cloud, and in case we are not arranged together, we don't understand the advantages.Cloud computing disposes of the require of having a total Foundation of equipment and software to meet clients necessities and applications.This paper points to explain types of cloud, security models of cloud, essential challenges of the cloud, the advantages of the cloud, analysis protection and security for the cloud.
Genetic Programming for Multiclass Texture Classification Using a Small Number of Instances

© Springer International Publishing Switzerland 2014. The task of image classification has been extensively studied due to its importance in a variety of domains such as computer vision and pattern recognition. Generally, the methods developed to perform this task require a large number of instances in order to build effective models. Moreover, the majority of those methods require human intervention to design and extract some good features. In this paper, we propose a Genetic Programming (GP) based method that evolves a program to perform the task of multiclass classification in texture images using only two instances of each class. The proposed method operates directly on raw pixel values, and does not require human intervention to perform feature extraction. The method is tested on two widely used texture data sets, and compared with two GP-based methods that also operate on raw pixel values, and six non-GP methods using three different types of domain-specific features. The results show that the proposed method significantly outperforms the other methods on both data sets.
Distance learning: challenges of mass transition to online earning education

Discussed is the problem of some range of challenges, specific for the Russian system of education on the way to massive distant learning in the first half of 2020. The article raises two main questions. The first is the question of providing the conformity of technical requirements, needed for functioning of programs, applying for distant learning, with technical capabilities of computers and other gadgets, that students use to get access to online education programs. Author concludes, that this problem may be partially solved by optimization programs for distant learning for using with low end technic. The second question is the way to make impossible student’s cheating while the attestation including fake technical problems (such as non-working web-camera). The author makes the conclusion about necessity of adding to the distant learning complex special addon for monitoring student’s gadgets during the intermediate certification: its operability, using programs and apps in time of exam.
Herald Your Reserve Fund

The Major Gifts ReportVolume 23, Issue 7 p. 7-7 Brief Herald Your Reserve Fund First published: 31 May 2021 https://doi.org/10.1002/mgr.31749Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume23, Issue7July 2021Pages 7-7 RelatedInformation
Portrait Analysis of Distribution Platform Based on Internet of Things Cloud Platform

In order to describe the operation condition of the distribution station area in an all-round way, and to generate the optimization strategy automatically for the problem station area, and to provide guidance to the operation and maintenance personnel, the portrait analysis technology of the station area based on the cloud platform of the Internet of things is studied. The portrait of the station area can help the operation and maintenance personnel to accurately control the load characteristics and the low voltage users' deactivation characteristics, which is of great significance to excavate the operation status of the station area and to analyze the different business scenarios synthetically. This paper introduces the system architecture of the Internet of things cloud platform, analyzes the data sent on the intelligent terminal, and combines the portrait label system of the station area to label the station area. Finally, the optimization strategy of the problem area is put forward through the application of the actual scene.
Bayesian saliency using the spectral form of Relaxation aid cuts 

In the form of this simple formula has been extended to allow modeling of the differences and many Priors. The new framework in a form easily integrated into a training set.In proposed system, a group of local features are submitting sparse subspace collection system and to compute the saliency map of rough bumps on the front part of the study results are superpixels. The feature of Bayesian saliency for each pixels the observation likelihood based on the use of visual of shape based images assume that the hull to compute. Our state-of-art algorithms that work in the favor of comprehensive tests in a large data set the protrusion of the Bayesian model based saliency cuts.
Personality Trait Analysis by Graphology Technique using Machine Learning

Graphology is a technique for analyzing an individual’s personality based on the given sample of their handwriting. Graphology considers the fact that the movement of our hand is directly related to the state of our brain. This paper implements the techniques of graphology using machine learning. The pre-defined data about the analysis of handwriting is given as learning data set for the machine. An image of a handwritten text document in jpg format is given as input to this machine. The processed output gives the personality of the individual corresponding to the input handwriting.
TECHNIQUES HOW TO ENHANCE VISUAL DATA ANALYSIS AND ITS DESCRIPTIONS

This article discusses the essential techniques in writing visual data such as graphs, process writing and map descriptions.Moreover, in this article 3 types of visual data description are analyzed. Examples are also given for each type of the visual data in this research work.
Implementation of Security Access Service using SHA-2 Algorithm

Advanced vehicles are not just a machine-like device; modern vehicles are continuously controlled, as well as monitored by using many digital computers, also called electronic control units (ECU).Advancement in modern automobiles mainly concentrates on the security and safety of these devices, thereby providing a safe driving environment to a driver.Radar is one of the important parts of the advanced driving assistance system, providing some important features like blind spot detection, cross traffic assistance, safe door opening etc.It is important that information coming from the Radar should be safe and it cannot be accessed by the third party.Aim of this paper is to implement the security access service to protect information coming from the Radar sensor.Application layer of the Autosar will allow the bidirectional communication between the client and the server.Implementing this service in application layer will reduce the time and it also provides increased level of security to the system.This paper comprise of implementation of this security access service using Unified diagnostic service (UDS) protocol.
Tagungen: Vakuum in Forschung und Praxis 6/2019

Vakuum in Forschung und PraxisVolume 31, Issue 6 p. 52-53 Magazin Tagungen: Vakuum in Forschung und Praxis 6/2019 First published: 02 December 2019 https://doi.org/10.1002/vipr.201970607AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume31, Issue6Special Issue: Superlative der VakuumtechnikDecember 2019Pages 52-53 RelatedInformation
An auction mechanism for cloud resource allocation with time-discounting values

Group-buying has emerged as a new trading paradigm and became more attractive. Through it, both sides of the transaction will benefit from the group-buying: buyers enjoy a lower price and sellers receive more demanding orders. In this paper, we investigate an auction mechanism for cloud resource allocation with time discounting values via group-buying, called TDVG. TDVG consists of two steps: winning seller and buyer selection and pricing. In first step, we choose winning seller and buyer in a greedy manner according to some criterion, and calculate the payment for each winning seller and buyer in second step. Rigorous proof demonstrates that TDVG satisfies the properties of truthfulness, budget balance and individual rationality. Our experiment results show that TDVG achieves better total utility, matching rate and commodities utilisation than the existing works.
Security knowledge representation of e-government data centre through ontology

Security knowledge is the heart of an e-government data centre. The knowledge refers to information gained through learning and experience. It is well known that security requirements of a community data centre are changing rapidly which are mostly formless and lack formal representation yet. It is therefore, felt essential to have a model for a community data centre that can support knowledge sharing and reuse in an explicit and mutually agreed manner. We have developed a security knowledge-based, ontology-centric framework for e-government data centre. Our framework that demonstrates correlation between high-level policy statements based on information system security standards and deployable security controls which are implementable and the objectives are achievable. This framework may support security expert activities with respect to security requirements, application and management of respective security controls and their countermeasures. We have tried to implement our model in a neutral manner.
Encryption Technique to Optimize Information Leakage in Multi Cloud Storage Services

Multicloud is one such aspect which is considered as the vision of the future. It includes distribution of data for the user automatically by means of cloud storage providers (CSPs) which in turn provides a considerable degree of control over information leakage. Due to the process of unplanned distribution of data chunks will result in disposing the crucial information while using multiple clouds. A storage system named Storesim is introduced in Multicloud to store syntactically relevant data on the assigned cloud, thereby limiting the intensity of leakage of information across those clouds. During this survey it has been identified that few CSP’s of some Multicloud services got compromised under coercion. In this paper, we made use of the Ultramodern Encryption Standard (UES) into storesim thereby avoiding unauthorized access to the information present in the Multicloud ensuring better level of security to CSP’s implicating reduced information leakage
Ingredient Scanner using Visa Tool

It is an Application which is to gauge the calorie of nourishment, which was shifted relying upon its fixings and capacity in each cookery time and it is mandatory to ascertain calories of sustenance earlier it gets expended. In light of nourishment information, fixings that are parts of sustenance surely have various calories. This rag suggests a technique for fixing created nourishment admission guess utilizing sustenance learning and warm information. In this strategy, a duplicate of the sustenance is first perceived as the kind of nourishment, and afterward, the elements of the realized sustenance are recovered from the database with their nourishment information. At the same time, the picture is then sectioned into limits of fixing applicants, and every one of those limits is then characterized into fixings utilizing LabVIEW dependent on the fixings level which is fitting for each age classifications. The ordered fixings from all limits are at last determined for all-out calories dependent on zone proportion and sustenance information. The presentation of our proposed technique indicates satisfactory outcomes contrasting and the calories set up by the regular ruinous strategy.