Reviewerly/exHarmony huggingface dataset:
Augmented Reality for CAD-CAM Training Featuring 3D Interactive Geometric Transformations

A semantic model difference identification (MDI) solution can be defined as an MDI solution that identifies and represents the differences between two compared models in terms of meaningful engineering information.Semantic representation of the differences between 3D CAD models is especially challenging due to the variety of modeling solutions used across industries, the non-uniqueness of modeling sequences and the use of low-level information, e.g.B-rep STEP files, in engineering communications.This work proposes an MDI method that represents the differences between 3D CAD models based on engineering semantics through features.Brake-and hydro-formed aerospace sheet metal parts are used as the application domain in which to propose and illustrate the proposed method.This method consists mainly of a pose registration stage and a difference identification stage.The pose registration method considers that all the features of a part serve specific functions, some of which are fundamental to the part's essential functionality, and that they are intertwined with the design intent of the part, which is particularly true for aerospace sheet metal parts.This provides the opportunity to semantically register feature-based 3D CAD models according to the unique purpose of the features in this specific domain of application.Difference identification is approached by primarily identifying and segregating the commonality between the compared 3D CAD models and then identifying the differences.The differences between 3D CAD models are classified as added, removed or differed features.Differed features are those features that are of the same type, but whose definition varies.As an outcome, the proposed method describes a way to fully pose-register 3D CAD models and identify their differences semantically based solely on their features, and, by extension, their design intent.
Artificial Intelligence Markup Languange for Interactive Service HR Department

Along with the development of information and communication technology systems in the era of free digitalization, people are asking for comfort and convenience by supporting their activities. One of them is easy to find artificial intelligence technology in various ways to support human activities. Artificial intelligence technology or often called Artificial Intelligence (AI) can be processed into various forms so that according to the adjusted method. Application of Artificial Intelligence Markup Language (AIML) with UML (Unified Modeling Language) design as an interactive media for personnel and employee services. The UML (Unified Modeling Language) design method is expected to help the personnel department in providing information to employees at PT. Dimensions of Indonesian Data. The information collected will be made into frequently asked questions and then adjusted to the AIML pattern.
Transforming Academic Library Instruction

"Transforming Academic Library Instruction." Journal of Electronic Resources Librarianship, 31(3), pp. 215–216
Automatic Solar Panel Tracking System

Solar Energy is the one of best renewable source of alternative energy. The efficiency of the solar panel can be improved more by tracking it in such way that it always faces perpendicular to the sun-rays throughout the day rather than it is kept fixed at an angle. At present, there are three methods for solar tracking, out of which refrigerant method is found to be more efficient as it is of a passive type and requires no external power source for its operation. In this project we have used R-134a [Tetrafluoroethene (CF3CH2F)] as the refrigerant medium for tracking the panel. To store the refrigerant, we have made use of two canisters and a copper conduit for connecting the canisters. The tracking system works on the principle of Differential Pressure Controlled system where high-pressure refrigerant from one canister to other flows and due to imbalance in the weight of canisters, the panel will tilt in the direction of the side where the weight is high due to gravity. Thus, our main objective is to harvest more solar energy at a much lower cost than the available trackers.
1237 Published By: Blue Eyes Intelligence Engineering and Sciences Publication Retrieval Number: B3727079220/2020©BEIESP DOI:10.35940/ijrte.B3727.079220 Journal Website: www.ijrte.org Impact of Artificial Intelligence on Customer Experience

With the increasing competition in the market today, the customers have a variety of options to choose from. The biggest challenge faced today by any business is to understand and deliver the exact requirements of the customers to retain the existing customer base and acquire new customers. The key to this is meeting and surpassing customer expectations leading to the goal of customer satisfaction through enhanced customer experiences. Upcoming technologies like Artificial Intelligence provide widespread opportunities to understand dynamic customer behavior and trends. However, not much exploration is done in academic research as to what factors primarily impact customer experience and the emerging significance of AI in this domain. Hence, the objective of this study is to understand the impact of artificial intelligence on customer experience. The paper adopts a quantitative approach wherein a survey was conducted across 207 participants to understand the impact of AI-enabled chatbots to deliver better personalization, quality of service, and hassle-free service to achieve better customer experience. The study provides implications to academicians as it contributes to the literature on the impact of AI on customer experience, helps practitioners in exploring and analyzing the various useful aspects of such emerging technologies in reshaping market trends, the companies and the society at large by providing a better experience to the customers, thus enabling a healthier customer relationship.
Design Of Hand Gesture Controlled Robot Using Arduino Lilypad

This paper proposes a style of hand gesture controlled automaton victimization Arduino Lilypad. The model projected is controlled through a motion device that is mounted on the hand gloves. This style helps physically challenged folks and additionally for sure tasks educated by human. the most aim of this style is to manage the automaton victimization hand gesture. measuring device utilized in the planning senses the direction of hand movement and sends an indication to Arduino Lilypad. Four main Hand gesture movements like FORWORD, BACKWORD, LEFT and RIGHT area unit detected and enforced.
FPGA Implementation of Smart Cryptography Algorithm

Mceliece algorithm is one of the simplest algorithm which is widely used in cryptography application for encrypting and decrypting the data. In the proposed work, mceliece algorithm able to allow an infinite number of characters, but for every nine characters, it considered as one iteration due to the fixed length of matrix size (3*3). Findings: This mceliece application running over micro blaze processor, and this processor implemented on Spartan-3E FPGA. The entire experimental setup is implemented using Xilinx platform studio 14.3 and targeted on Spartan 3E-1600E FPGA.
A dynamic and QoS-effective resource management system

This paper presents the design and implementation of HASEX, which supports a dynamic resource provisioning during application run-time and provides effective quality-ofservice (QoS) resource management system for QoS- and deadline-driven applications. The most important feature of HASEX is the ability to serve high performance and distributed applications with minimal infrastructure and operating costs. The resource provisioning management is controlled by a 'rental' mechanism which is supported by a pool of computing resources that the system may rent from external resource owners/providers in times of high demand. HASEX differentiates the roles of application management, job scheduling, and resource provisioning tasks. This approach significantly reduces the overhead of managing distributed resources. We demonstrate the effectiveness of HASEX to rent groups of resource nodes across geographically disparate sites. We then perform performance comparison of HASEX with OpenNebula cloud system to demonstrate its performance, scalability, and QoS-effectiveness.
Writer Independent Manipuri Offline Signature Verification using Transfer Learning Technique of Convolutional Neural Network

Automatic Signature Verification system is used to verify whether a signature is genuine or forged. Forged Signatures are those signatures that a person produced by imitating the signature of another person. Automatic Signature Verification is very important as a person’s handwritten signature is used everywhere to authenticate themselves and there is not very much difference between a genuine signature and the imitation of it, i.e. a forged signature. In this work, signature verification is done using different pre-trained Convolutional Neural Networks (CNNs). Convolutional Neural Network has powerful learning ability, and it can be used to distinguish between a genuine and a forged signature automatically. In this experiment, Manipuri signature dataset was used, the dataset was prepared originally and it contains 729 genuine signatures and 243 forged signatures. Features were extracted from pre-trained networks and classification was done using binary Support Vector Machine (SVM) classifier and the performances of the networks were compared. And according to the experiment we achieved a classification accuracy of 84.7 using VGG19 features, accuracy of 86.8 using VGG16 features and accuracy of 81.9 using Alexnet features.
Implementation of Pixel Likeness Weighted Frame (Plwf) Filter Technique Based Digital Image Denoising for DSP Applications

Digital images are often corrupted by contaminated display and information quality noise. Images can be corrupted at any stage during which they are acquired and transmitted through the media. Image denoising is a basic function designed to eliminate noise from naturally corrupted images. This work proposes a fixed-point discrete wavelet transform (DWT) architecture that uses a nonlinearly modified pixel-like weighted frame (PLWF) technique to denoise the high-throughput of adaptive white Gaussian white noise (AWGN) images. The linearized state to be based on the neighboring pixel unity is that the state model noise is used to improve the peak signal to the sound rate (PSNR). The proposed architecture is employed in two different stages - consistent and conditional sorting output selection unit. The detailed result of the proposed architecture shows the size and display quality of any state-of-the-art performance and some recently introduced work. For further evaluation of the denoising capability, the algorithm is compared to some state-of-the-art algorithms and experimental results on simulated sound images and captured images of low-light noise especially large image processes Low noise light picked up by the test results. The performance of the proposed method is compared to wavelet thresholds, bilateral filters, non-local averaging filters, and bilateral multi-resolution filters. The study found that the draft production plan is smaller than the wavelet threshold, the bilateral filter, and the non-local means of filtering and larger superior/similar to the method, visual quality, PSNR and image index noise bilateral multi-resolution filter quality.
Generalized Canonical Polyadic Tensor Decompositions for Streaming Data.

streaming context by deriving a GCP optimization problem to be solved as new tensor data is observed, formulate a tunable history term to balance reconstruction of recently observed data with data observed in the past, develop a scalable solution strategy based on segregated solves using stochastic gradient descent methods, describe a software implementation that provides performance and portability to contemporary CPU and GPU architectures and integrates with Matlab for enhanced usability, and demonstrate the utility and performance of the approach and software on several synthetic and real tensor data sets.
Research on Power Customer Relationship Management System and Architecture Design

With the development of market economy, the demand of power enterprise customers is getting higher and higher. Achieving a win-win situation between the company and its customers is a new topic for power supply companies. This paper firstly analyzes the background of development and design of power customer relationship management system, and the theoretical basis of customer relationship management. Then it introduces the organizational structure and function analysis of power customer relationship management system, and finally gives some insightful conclusion.
Re-Ranking Images Retrieval: Combined Multiple Features Method

Content-Based Image Retrieval (CBIR) grown rapidly in multimedia field, image retrieval, pattern recognition, etc. CBIR provides an effective way of image search and retrieval from the pool image databases. Learning effective relevance measures plays a critical role in improving the performance of image retrieval systems. In this paper present a Combined multiple features method which is two key parameters (i) Feature extraction, (ii) Similarity metrics for content-based image retrieval method. Feature extraction and similarity metrics important role in Content-Based Image Retrieval. We define hybrid feature extraction and similarity method for finding the most similar images retrieved. Combined features extraction using the various image features. These papers explain some important distance metrics such as Euclidean distance and City block distance. The experiments are performed using the various kinds of databases such as WANG Database, Corel Dataset. The experimental result shows that the proposed method is proved more effective than existing methods.
Measuring Energy Efficiency of Cloud Datacenters

In today’s technology driven world, use of cloud technology is ever increasing. To sustain the increasing demand, new data centers are coming up quite fast. Also, the equipment in these data centers is scaling up. Energy consumption by these data centers has opened a new front of research. Not only the energy consumption has to be minimized, but the carbon footprint needs to be arrested to minimize the environmental hazards. Energy usage and dissipation takes place in different forms. Customized metrics are required to evaluate the performance of these centers. We have classified the major efficiency metrics according to their importance in a given scenario. Different scenarios have been identified for the suitability of these metrics along with the formulae to calculate these metrics. Two new metrics namely Energy Eat by Servers and Switches (EESS) and Energy Eat and SLA violation Factor (EESF) have been proposed.
Managing sensor data streams in a smart home application

A challenge in developing an ambient activity recognition system for use in elder care is finding a balance between the sophistication of the system and a cost structure that fits within the budgets of public and private sector healthcare organisations. Much activity recognition research in the context of elder care is based on dense networks of sensors and advanced methods, such as supervised machine learning algorithms. This paper presents the data processing aspects of an activity recognition system based on a simpler, knowledge-based unsupervised approach, designed for a sparse network of sensors. By structuring sensor data management as a streaming system, we provide a simple programming model for the application logic, which facilitates building a fault-tolerant system with the potential for distributed data management within the sensor network. The system, evaluated by a public sector healthcare organisation, constitutes an example of a system that is useful and has a sustainable cost structure.
Algebraic Properties on ω-Fuzzy Translation and Multiplication in BP– Algebras

In this paper, we first define Fuzzy BP-sub algebra then explain the idea of –Fuzzy Translation and Multiplication in BP– Algebras. More over , we generalized the Fuzzy BP- ideal and we consider, new notion discussed –Fuzzy Translation and Multiplication in BP– Algebras and investigate some of related algebraic properties.
False-positive free transparent and optimal watermarking for colour images

Digital image watermarking serves as a tool for protection of ownership of the media shared on common platform. This paper presents a robust, blind watermarking technique for colour images based on singular value decomposition (SVD) and discrete wavelet transform (DWT). Watermark is embedded in mid-frequency sub-bands of two-level DWT. These sub-bands are divided into non-overlapping blocks of size 4 × 4, each of which undergoes SVD. The singular values (SV) are updated based on watermark bit and using Lagrange's optimisation principle using two keys. Experiments show that the proposed technique is imperceptible with PSNR > 40 dB. Also, the technique can resist general image processing operations (attacks) on the images with the structural similarity index measure (SSIM) nearly 1 and sufficiently high bit correct ratio (BCR).
Research of the Gibbs Phenomenon under Periodic Signals with Discontinuities of the First Kind on Basis of the LabViewComplex

The development of laboratory practical work in the electrical engineering course is due to the use of the control-measuring LabVIEW complex that combines technical means of measurement and control, software and standard computer technologies. An essential advantage of the LabViewis the ability to control the measurement process in automatic or interactive mode. The contemporary technology of the virtual measuring devices, which are a part of the LabVIEW complex, enables to operate with the means of supervision, measurement and control, to treat the results of researches. The advantages of the LabViewcomplex are illustrated with the example of the Gibbs phenomenon investigation under periodic signals with discontinuities of the first kind described by the truncated Fourier series. The methods of smoothing of the truncated Fourier series and improvement of convergence are represented. A discussed question is important in electrical engineering, radio engineering, microelectronics, biomedicine, etc.
N-Gram Language Model based Continuous Voiced Odia Digit Recognition

With the enormous improvement in the area of signal processing, speech processing systems are creating a massive impact in recognizing the voices, controlling the commands and making as communication interfaces. A continuous speech recognition system is essential for voice identification hands free system used as a voice dialer, voice originated security systems and voice based automatic electronic machines. The proposed work suggests a finest speaker independent continuous voiced digit recognition for Odia language. The model integrates the concept of Mel Frequency Cepstral Coefficient (MFCC) and continuous density Hidden Markov Model (HMM), relating to speech parameterization and recognition respectively. The performance of the model is explored for different levels of HMM like word-level and phoneme-level. Further the model output is evaluated using different N-Gram approaches of the language model. Finally it is shown that the model using phoneme-level HMM with a tri-gram language model is superior to other methodologies.
Freedom of Press and Media Ethics: A Comparative Study

If there is a first stage of freedom in any country, then it is the freedom of expression.If the person will not have the freedom to speak, then surely there is no other freedom for him.The right to express itself gives birth to all other rights.The whole world looks at the media to have access the true and correct information.But with the increase of Paid News and Yellow Journalism, the legitimacy of information given by media is vulnerable.As the unethical characters are coming out of the media industry and forced the policy makers to think about it to introduce new laws and regulations to maintain its place in the hearts of common man.Section 19-1 (a) of constitution tells us about the freedom of speech but one has to be very clear about the use of these rights given.If we fail to do so then needs arise to put cap on that, which is inhuman and unethical as this deprives one to access its rights.
MagnetOnto: modelling and evaluation of standardised domain ontologies for magnetic materials as a prospective domain

Ontologies are information processing entities that are used for modelling, representing, and reasoning domain knowledge owing to the complexity in the relationship between different terms within a domain, there needs to be a logic in which they are pragmatically related. Ontology modelling is the best strategy to represent conceptual and domain-specific knowledge which makes it feasible for information systems to understand and interpret the relationship between various terms. In this paper, a detailed investigation of magnetic materials as a domain is carried out and the relationship between terms in the domain is represented as machine-interpretable ontological entities. A detailed OWL ontological model that comprises 123 classes with six distinct levels has been proposed. A detailed qualitative analysis using a semiotic approach using several parameters and quantitative analysis has been carried out. MagnetOnto is strictly a concept-oriented ontology with minimum deviations from the parent domain. An overall reuse ratio of 95.1% has been achieved by MagnetOnto, which makes this a best-in-class and also the first ontology to model magnetic materials.
E-learning for the development of critical thinking: A systematic literature review

E-learning is increasingly frequent, with greater emphasis since COVID-19, which generated a high migration to virtual learning environments, requiring educational innovation with ICT to continue guaranteeing the development of life skills, such as Critical thinking (CT), Given this, the present systematic review of literature in Scopus and Web of Science, aimed to systematize scientific production on E-learning and CT. The PRISMA methodology was used for the identification, selection, eligibility, and inclusion of articles, based on systematization criteria. The main results show two groups of studies: theoretical (4) 19% and empirical (17) 71%. Empirical studies have been carried out at secondary level (2), Senior High School (2) and university level (13); of these 62% is quantitative, 30% qualitative 30%, and 8% mixed. Scientific evidence confirms the positive impact of E-learning on the CT development of students. It was found that from COVID-19 the amount and variety in this type of study is ascending, however, this type of research is very scarce in Latin America, which calls for the generation of research in and from the contexts and educational actors of this region. It is also necessary to promote studies that consider a relationship between specific E-learning proposals and CT specific skills: interpretation, analysis, evaluation, inference, explanation, self-regulation, among others. Finally, an epistemological void is revealed in the epistemic approach of teaching competences in E-learning environments for the teaching critical thinking, its treatment being necessary to dynamize the hybrid classrooms in the fulfillment of the training objectives.
RDFS-Plus

Enterprises have made amazing advances by taking advantage of data about their business to provide predictions and understanding of their customers, markets, and products. But as the world of business becomes more interconnected and global, enterprise data is no long a monolith; it is just a part of a vast web of data. Managing data on a world-wide scale is a key capability for any business today.