Reviewerly/exHarmony huggingface dataset:
Blockchain-Based Insurance

To date, the insurance industry’s interest in the blockchain has focused largely on the possibility of recording insurance entitlements in a transparent way. While the blockchain may produce significant efficiencies of this sort, it has considerably greater transformative potential. Smart contracts could serve as a substitute for insurance companies, conventionally conceived. Such contracts could perform the function of deciding whether claims should be paid, without the need for or possibility of judicial intervention. The blockchain and smart contracts are difficult to regulate, because ownership and decision making can be decentralized. Blockchain-based insurance may successfully provide a means of avoiding expensive regulation and could have a competitive advantage over regulated insurance. This chapter discusses how blockchain-based insurance might work and identifies some technical challenges and other obstacles that it may face.
Proficient Recovery Over Records using Encryption in Cloud Computing

Secure record stockpiling and recovery is one among the most blazing examination bearings in distributed computing. Notwithstanding the way that various available cryptography plans are orchestrated, few of them bolster conservative recovery over the archives that are encoded upheld their traits. Amid this paper, a positioned characteristic based cryptography topic is at first intended for a report grouping. A gathering of reports will be encoded together in the event that they share partner coordinated access structure. Contrasted and the figure content arrangement trait based cryptography (CP-ABE)plans, each the figure content cabinet reality costs of encryption/unscrambling are spared. At that point, partner record structure named trait based recovery alternatives (ARF) tree is made for the report variety upheld the TF-IDF demonstrate and in this manner the archives' characteristics. The ARF tree depends on the various levelled processing encryption plot(HABE).A significance first look algorithmic program for the ARF tree is proposed to enable the chase to control that can be additional improved by parallel handling. Beside the archive accumulations, our subject will be conjointly connected to various datasets by changing the ARF tree marginally. The modification plot is called as HABE. An extreme examination and a movement of preliminaries are executed for example the security and force of the masterminded subject.
Video steganography using 3D distance calculator based on YCbCr color components

Steganography techniques have taken a major role in the development in the field of transferring multimedia contents and communications. Therefore, field of steganography become interested as the need for security increased significantly. Steganography is a technique to hide information within cover media so that this media does not change significantly. Steganography process in a video is to hide the information from the intruder and prevent him access to that hidden information. This paper presents the algorithm of steganography in the video frames. The proposed algorithm selected the best frames to hide the message in video using 3D distance equation to increasing difficulty onto the intruder to detect and guess the location of the message in the video frames. As well as selected the best frames in this algorithm increased the difficulty and give us the best stego-video quality using structural similarity (SSIM). Also, the hash function was used to generate random positions to hide the message in the lines of video frames. The proposed algorithm evaluated with mean squared error (MSE), peak signalto-noise ratio (PSNR) and SSIM measurement. The results were acceptable and shows that is the difficulty of distinguishing the hidden message in stego-video with the human eye.
The development of the visual culture of design students in shaping the spatial environment

The article presents the results of a study devoted to the development of studentsdesigners' visual culture of shaping the subject -spatial environment.Visual culture is considered as a combination of means of artistic -design expressiveness and visual experience, influencing the nature of the shaping of the subject -spatial environment.The development of visual culture will be effective if it is understood as a culture of aesthetic interaction of a person with visual artistic images and consists of three interrelated links: the perception of visual information, the expression of personal evaluation, the creation of expressive visual images.To diagnose the development of visual culture, we have proposed an interpretation method.In the methodological literature, it is treated as a solution to the problem in an unexpected way -in a different style, in a strange manner, "working in a masked wizard" -"if Le Corbusier had done the same project."Based on the proposed assignment, the purpose of which was to study various stylistic and plastic techniques in the creative activities of famous designers -to create an image of the interior in the style of the master.As a result of a comparative analysis of diagnostics of the null and control stage of the creative work of the experimental group, we obtained quantitative and qualitative data that comprehensively characterize the level of development of the visual culture of students according to the selected criteria: readiness for design -communication, readiness for perception and analysis, interpretation ability, ability of reflection.The reliability of the evaluation of the results obtained was determined using mathematical and static data processing.
Optimal bag-of-features using random salp swarm algorithm for histopathological image analysis

Histopathological image classification is a prominent part of medical image classification. The classification of such images is a challenging task due to the presence of several morphological structures in the tissue images. Recently, bag-of-features method has been used for image classification tasks. However, bag-of-features method uses K-means algorithm to cluster the features, which is a sensitive algorithm towards the initial cluster centres and often traps into the local optima. Therefore, in this work, an efficient bag-of-features histopathological image classification method is presented using a novel variant of salp swarm algorithm termed as random salp swarm algorithm. The efficiency of the proposed variant has been validated against 20 benchmark functions. Further, the performance of the proposed method has been studied on blue histology image dataset and the results are compared with 5 other state-of-the-art meta-heuristic based bag-of-features methods. The experimental results demonstrate that the proposed method surpassed the other considered methods.
IOT Based Gesture Recognition for Smart Controlling

Internet of things (IOT) analyzing network things embedded with software, sensors, n/w etc. IOT extend to internet connectivity with flexible devices. IOT makes life easier and makes smart with improving networks and power of data correlations. Major fundamental component of IOT systems are sensors, connectivity, data processing, active engagement and user interface. User interface make comfort between computer and human interaction. Human interaction as consider in form of command and computer interpret that commands. This paper presents user interface with internet of things (IOT) more effectively with comparing different techniques on recent review base.
Recognition of Off-Line Handwritten Rajasthani Characters using Generalized Feed Forward Classifier

The offline handwritten identification in the area of pattern recognition was a heavy and difficult task. Because of its application in different areas, a set of work is being done and the results are continuing to be strengthened by different methods. We suggested in this paper a handwritten model for individual character recognition using generalized neural networks for feed forward. We take 17 character samples handwritten in scanned image format for experimental purposes; Rajasthani knows 850 different samples of handwritten characters. HOG extraction methods are used to construct pattern vectors for all training sets. These features are recognition classifier for generalized feed forward. We obtained an overall classification with GFF classifier accuracy rate of 85.21% from the proposed scheme for the identification of Rajasthani characters.
Optimization of educational process as pedagogical problem

The article emphasizes a thought that level of efficiency of teaching and educational process of higher school depends on level of professional training of teachers. Opportunities of process of optimization of teaching and educational work with students in their personal-social and professional self-realization are shown. The article analysis criterions of efficiency of process of optimization and emphasis an importance of study of real educational intellectual opportunities of students and zone their nearest development too. In the article is spoken about connection between efficiency of process of optimization of teaching and educational work with students and level of professional training of teachers of higher school is given necessary 66 recommendations for increasing of level of efficiency of process of optimization. The creation of the most effective conditions for the continuity of the personal and social self-realization of students, an increase in the level of their professional training and the demand from the state is intended to form student youth as a constructive and creative social factor that requires the higher school to seriously consolidate its educational and educational capabilities in order to dynamically increase the level the effectiveness of the entire educational process.
Measurement of sentence similarity based on constituency parsing and dilated convolution

Measurement of sentence similarity is widely used in the field of natural language processing, the current mainstream method is based on neural network similarity model. In actual application, the method of neural network has some disadvantages. On the one hand, when sentences are input to the neural network, the problem of semantic loss is caused by the interception and zero-filling operation of the sentence that is too long or too short. On the other hand, ignore the semantic relation between interval words. Thus, this paper proposes a method of measuring sentence similarity based on constituency parsing and dilated convolution. It uses constituency parsing to design rules to reduce unimportant semantic component of long sentences and supplement important semantic component of short sentences. In addition, the receptive fields in sentence dimension and word vector dimension are dilated to capture the semantic association of the two-dimensional interval words. Finally, the method is verified on two data sets.
AMAZON PRODUCT REVIEW SENTIMENT ANALYSIS USING MACHINE LEARNING

As online marketplaces have been popular during the past decades, online sellers and merchants ask their purchasers to share their opinions about the products they have bought. As a result, millions of reviews are being generated daily which makes it difficult for a potential consumer to make a good decision on whether to buy the product. Analyzing this enormous amount of opinions is also hard and time-consuming for product manufacturers. But in this prospering day of machine learning, going through thousands of reviews would be much easier if a model is used to polarize those reviews and learn from it. This thesis considers the problem of classifying reviews by their overall semantic (positive, negative, or neutral). To conduct the study different supervised machine learning techniques, Support Vector Machine, Naive Bayes, Decision Tree, Random Forest, and Logistic Regression have been attempted on products review dataset from Amazon. Their accuracies have then been compared.
Realm for Metamorphose Management in Software Requirements for global Software progress Environment

Recent outsourcing /off-shoring software development practices testify that any development done without a proper sharing mechanism leads to the generation of inconsistent information, which further results in an undesired, error-prone software. Further, with the business process automation, a significant way to minimize human effort involves various development, support and maintenance activities to reuse available information. Thus, reusing and sharing information in a standardized way is the key operative challenges which foster the need to identify and exploit novel knowledge-based frameworks. Those recommended research gives a tool-based answer for mechanize those programming documentation transform utilizing ontologies. This multi-phase schema need in general six stages the place every period yield contributes of the last robotized documentation. Should assess the degree for robotized documentation it is looked at utilizing spare and more open wellspring programming known as WCopyfind of the existing manual documentation to an after effect administration framework research endeavor. Preliminary Outcomes indicate a most noteworthy mechanization from claiming 60 percent, which will be plainly foremost.
An Efficient and Effective Framework to Track, Monitor, and Orchestrate Resource Usage in an Infrastructure as a Service

The development of Infrastructure as a Service system brings new chances, which additionally goes with new difficulties in auto scaling, asset allotment, and security. A key test supporting these issues is the persistent following and checking of asset utilization in the framework. This paper, we will in general present ATOM, a proficient and compelling structure to naturally follow, screen, and coordinate asset use in a framework which is generally utilized in cloud foundation. We utilize novel following technique to constantly follow significant framework use measurement, and build up a Principal Component Analysis based way to deal with persistently screen and consequently discover oddities dependent on the approximated following outcomes. We tell the best way to powerfully set the following limit dependent on the identification results, and further, how to change following calculation to guarantee its optimality under unique remaining tasks at hand. We show the flexibility of ATOM over virtual machine (VM) bunching. In conclusion, when likely peculiarities are recognized, we will in general use thoughtfulness devices to perform memory legal sciences on VMs guided by examined comes about because of following and checking to distinguish malignant conduct inside a VM. We assess the presentation of our structure in a framework.
On the properties of the classifier in case of maximal deviations of blood parameters from the norm

A mathematical model is described and implemented, intended for the numerical study of the ability of the statistical classification method to interpolate and extrapolate. The classifier developed by the authors is based on the polynomial-regression approach and has probabilistic estimates. It is used to assess the state of human health based on the parameters of laboratory analysis of peripheral blood. The blood base is considered with a maximal deviation from the norm.
Secured Information Sharing in Mobile Cloud Computing using Access Controls

Presently usage of smart mobiles increasing, due to internet availability most of users outsourcing their data to cloud but it is untrusted, so a security mechanism needed in this work proposing Homomorphic cipher text policy-Attribute based encryption (HCP-ABE), it derived from classic ABE. “Mobile cloud computing are combinations of mobile computing and cloud computing”, mobile applications are designed and hosted in cloud computing without verifying about mobile environment. Security models are constructed using Perturbation methods as per literature. These models are not secure compared to cryptographic techniques. When perturbation methods are used, Data reconstruction becomes a significant challenge. Hence computations are complicated to perform. Furthermore, this method suffers a trade-off between accuracy and privacy and most of the research work focused on key management issues and static access policies but due to user dynamic the access control mechanism should design for proactive strategies. To support dynamic access control and operations HCP-ABE scheme intended. In this paper we identify challenges associated with mobile cloud-based security system and possible provide solutions to understand existing research work conducting compressive review on different access control mechanisms.
Multi Robot Path Planning Based on Cuckoo Search and with PSO Algorithm in the Complex and the Unknown Environment

For an efficient operation of and autonomous robots or agents optimization of the path is an essential feature. In my proposed paper I will discuss about the CS Algorithm its parameter analysis and how it is applied on the mobile robot in an intricate environment with numerous amount of static obstacles. Taking the concept from the flight behavior of the cuckoo this meta-heuristic algorithm is designed.[1] We will show the different parameters of traversing by agents in terms of coverage, time, movement and energy between its targets and obstacles, based on these parameter we can identify the target seeking behavior and obstacle avoidance of the robot, then the comparison will be made between path planning with PSO algorithm and Cuckoo search[2] algorithm depending on various parameter analysis. With the help of both the algorithm which is the Cuckoo Search and PSO algorithm we will try to show how robot avoids the obstacle and proceed towards the target, when the robot reaches its goal we shall be able to justify that it has followed the smooth optimal trajectory within the frame or the desired environment.
An Algorithm for Determining SIFT Matching Score for Dorsal Vein Recognition System

Vein pattern recognition has been an increasingly biometric branch nowadays. This technology has many advantages over other biometric technologies. This technology works only on alive person. Vein pattern of every person is unique even in case of twins. Whole procedure of registration for verification of a person gives a hygienic opportunity. Vein pattern of a person remains constant throughout the life until and unless, physically damage. Recognition through veins cannot be affected from aging, color and physical environment because veins are present underneath the skin. NIR cameras of wavelength of 700 nm to 1000 nm are used to capture the images of vein patterns. When infrared radiation falls on the veins, these get illuminated in dark color due to the absorption of radiation by the hemoglobin present in the veins. The SIFT (Scale-Invariant Feature Transform) algorithm has given very good results in feature extortion and matching but it does not provide matching score of features. In this work, we proposed an algorithm to determining the matching score of pattern matched through SIFT algorithm. For experimental purpose, we performed image acquisition, pre-processing, feature extraction and filtering to eliminate noise from the images. We tested our algorithm on the database of 160 persons and we calculated performance of our algorithm in terms of FAR and FRR 2.7% and 4.5% respectively
Guideline for the Selection of Requirement Prioritization Techniques in Agile Software Development: An Empirical Research

Prioritization is an essential process in any software development. Moreover in Agile, Requirement Prioritization (RP) needs more formal process because it is difficult to maintain priority after requirement change. Changes in the priority list are a continuous process in Agile Software Development (ASD) hence, the ignorance of critical requirements during prioritization will result several problems like unsatisfied client and poor quality of product. Moreover, there is little empirical knowledge on the state of the practice and contemporary problems exist in choosing best prioritization technique after the requirement change in Agile. To achieve this objective a guideline for the selection of RP technique is needed. Hence, the empirical research is used as a methodology for the evaluation of the requirement prioritization techniques practiced in Agile. The aim of this study is to determine RP techniques used in software industry and identify aspect or evaluation criteria to choose the best RP technique according to the environment. This study conducts an empirical study of requirement prioritization after requirement change in Agile, based on the responses from 137 Agile software practitioner representing around 31 organizations in Pakistan. The results reveal the main decision makers in the process of RP, prioritization technique after requirement change in Agile with the evaluation criteria and aspects to perform requirement prioritization. These findings will serve as a foundation to provide a guideline for selecting suitable requirement prioritization techniques in Agile which can help software practitioners to choose appropriate prioritization techniques during the process of requirement change in Agile.
Comprehensive Models Towards for Feature Extraction and Recognition in Machine Learning

The scientific study of algorithms and statistical Models is often referred to as Machine learning that computer Systems use to perform specific tasks without using explicit Instructions, relaying patterns and interfaces instead. Ongoing Improvements in data frameworks just as computerization of Business forms by associations have prompted a quicker, simpler and progressively precise information investigation. Information Mining and AI procedures have been utilized progressively in the Examination of information indifferent fields extending from Medication to fund, training and vitality applications. Artificial Intelligence procedures make it conceivable to deduct important additional data from that information handled by information mining. Such important and noteworthy data causes associations to build up their future arrangements on a sounder premise, and to increase significant points of interest as far as time and cost. This investigation applies grouping calculations utilized in information mining and AI methods on that information got from people during the professional direction procedure, and attempt to decide the most suitable calculation. In this paper we study all methods and techniques used in data mining and machine learning and decide the best algorithm for machine learning
Data Integrity, Data Privacy and Data Confidentiality Issues in Multi-User Cloud

Cloud computing was one of the most significant computational models that help to handle the vast amount of data in a flexible and secure environment. In the current scenario, the amount of data being shared and the number of users or group in the cloud has been continuously increasing. The rise in the usage of the clouds had instigated the need to provide the security to the data that were transmitted among the user and owner through a cloud server. The data in the cloud most commonly endure in issues related to the integrity, privacy, and confidentiality (IPC). This paper was the accumulation of extensive research works to resist the issues in the clouds. Many researchers had indulged in the process of enhancing the security of the cloud data by generating the keys, performing the cryptic mechanisms, auditing, de-duplication techniques, enhancement in handling the queries and many more approaches. The outcomes from the some works are discussed with other approaches to understand the objective accomplished by each work over the other. The general IPC issue and challenges exist in the cloud environment were listed and it was identified that there is a necessity for the better methodology to accomplish the robust cloud environment