Reviewerly/exHarmony huggingface dataset:
Multi-Core Processing Cloud Eclat Growth

Data mining is a lively process used in many leading technologies of this information era. Eclat growth is one of the best performance data mining algorithms. This work is indented to create a suave interface for Eclat growth algorithm to run in multi-core processor-based cloud computing environments. Recent improvements in processor manufacturing technology make it possible to create multi-core high performance Central Processing Units (CPUs) and Graphics Processing Units (GPUs). Many cloud services are already providing accessibility to these high-power processor virtual machines. The process of blending these technologies with Eclat Growth is proposed here in the name of “Multi-core Processing Cloud Eclat Growth” (MPCEG) to achieve higher processing speeds without compromising the standard data mining metrics such as Accuracy, Precision, Recall and F1-Score. New procedures for Cloud Parallel Processing, GPU Utilization, Annihilation of floating point arithmetic errors by fixed point replacement in GPUs and Hierarchical offloading aggregation are introduced in the construction process of proposed MPCEG.
An Efficient Qos-Based Ranking Model for Web Service Selection with Consideration \of User's Requirement

The power of Web services to address the incompatibility issue of standalone systems, has led them to play a major role in business application development. Adopting an efficient and effective method to locate and select desired services among thousands of available candidates is an important task in the service-oriented computing. As part of a Web service discovery system, the ranking process enables users to locate their desired services more effectively. Many of the existing approaches ignore the role of user's requirements which is an important factor in the ranking process. In this thesis we enhance a vector-based ranking method by considering user's requirements. The vector-based model is chosen because of its simplicity and high efficiency. We evaluate all Web services in terms of their similarity degrees to the optimal or the best available values of each quality attribute, and penalize the services that fail to meet the user's requirements. Through our extensive experiments using real datasets, we compare the improved algorithm with other approaches to evaluate it in terms of efficiency (the execution time to return the result) and quality of the results (accuracy). Cherie Ding
Automatic Vehicle Turn Indicator using Speech Recognition

Voice-controlled innovation is an energizing region of research that is utilized to help people in the mechanical control of manual frameworks. It is a part of human-communication that builds the advances in programmed discourse acknowledgment or ASR with the inventive advances of characteristic language handling or NLP. Wise frameworks, for example, Automatic Vehicle Signaling Systems, can likewise take into consideration adaptability in manual activities. In late investigations, analysts have investigated regular language control of manual tasks. In this paper we will research interfacing voice control activities with Arduino-based equipment stages that are utilized to structure the programmed sign highlights in a vehicle. The control system includes a voice recognition circuit for activating turn signal devices within the vehicle. The voice recognition circuit takes in input from the voice from the Google maps voice assistant. In some formats, a wireless hardware is provided while in other embodiments original equipment manufacture is accommodated.
Elliptic Curve based Collaborative Group Key Management for Cloud Data Sharing in Ciphertext Policy Attribute based Encryption

Ciphertext policy attribute based encryption (CPABE) is one of cryptographic procedure that coordinates data information encryption with authenticated admission management for guaranteeing data information security in Cloud. The cloud computing where the application administrations using the Internet. In numerous applications, especially in Group Communication in cloud data information offering to various clients data information proprietors require to conceal undisclosed data information like encryption key. The effective key management system conventions are essential for giving security to this data information. Since, it is extremely difficult to provide security to group's secret data information particularly with various mechanisms of assurance. The effectiveness issue of CP-ABE is as yet accessible that corrupt the computation overhead on the grounds that bilinear pairing is exorbitant in such huge numbers of utilizations of ABE, so by supplanting the bilinear pairing utilized in the attribute coordinating with straightforward scalar multiplication on Elliptic Curves, accordingly diminishing the general computation just as communication overhead. And plan another key dispersion can considered in order to legitimately renounce a client or a characteristic without refreshing the other clients' keys during the property repudiation phase. By utilizing the Shamir's Threshold secret sharing designs access structure to develop the expressiveness of the entrance arrangement. Security and execution examination demonstrate that in this plan improving the general effectiveness just as guarantee the security of the cloud data information
Sentimental Analysis And Lsi Similarity Measure For Efficient Page Ranking

Supplementary factor to the general pagerank calculation which is utilized by Google chrome to rank sites in their web index results is tended to in this paper. These extra factors incorporate couple of ideas which expressly results to build the precision of evaluating the PageRank value. By making a decision about the likeness between the web page content with the text extracted from different site pagesresulted in topmost search using few keywords of the considered page for which the rank is to be determined by utilizing a comparability measure. It results with a worth or rate which speaks to the significance or similarity factor. Further, in a similar strategy if sentimental analysis is applied the search results of the keywords could be analysed with keywords of the page considered, it results with a Sentimental Analysed factor.In this way, one can improve and execute the Page ranking procedure which results with a superior accuracy.Hadoop Distributed File System is used to compute the page rank of input nodes. Python is chosen for parallel page rank algorithm that is executed on Hadoop.
Professional Competencies Formation In Art And Pedagogical Education: A Process Approach

The article deals with the issues of the timely forming relevant professional competencies in art and pedagogical education.The author draws attention to the need to apply approaches, with the help of which it is possible not only to successfully form, but also to timely identify professional competencies, the demand for which may be caused by changes in the field of the graduate's professional activity which occur during training under bachelor's or master's programs.The importance of formulating the professional competencies and their indicators achievement in the context of the design of basic educational programs and educational-methodical complexes based on the state standard is noted.The article examines the process approach application in art and pedagogical education at the university, with the help of which it is possible to efficiently organize the process of identifying and forming relevant professional competencies.The author cites the results of surveys made by students, graduates, employers and teachers of the "Fine arts and additional education: arts and crafts" specialty at the Yaroslav-the-Wise Novgorod State University.The surveys were conducted from 2003 to 2009 and from 2012 to 2018.The author of the article offers some recommendations for optimizing the design process of the specialty's main educational program and work programs, taking into account the timely identification and formation of relevant professional competencies.
Analysis of Error Using Simple Past Tense on Recount Text Class VIII B Students of SMP Pelita Ngabang in the Academic Year 2019/2020 Landak District

This research aims at investigating the errors using simple past tense that is often done by students in the activity of writing sentences in simple past tense on the recount text of class VIII B of junior high school PELITA Ngabang in the academic year 2019/2020 Landak Regency. The study uses a qualitative research design. The research was carried out at junior high school PELITA Ngabang on November 22nd, 2019. The research subjects were VIII B amount of 20 students. After analyzing the errors of the 20 past forms in the recount text that were finished by 20 students there were 73 errors. Finally, the authors concluded that the past form errors in the recount text were the types of errors omissions, 19, 17%, type of errors addition 26, 02%, types of errors misformation 27, 39%, types of errors misordering 27, 39%.
Fuzzy Cross Domain Concept Mining

E-Learning has emerged as an important research area. Concept maps creation for emerging new domains such as e-Learning is even more challenging due to its ongoing development nature. For creating Concept map, concepts are extracted. Concepts are domain dependent but big data can have data from different domains. Data in different domain has different semantics. So before applying any analytics to such big unstructured data, we have to categorize the important concepts domain wise semantically before applying any machine learning algorithm. In this paper, we have used a novel approach to automatically cluster the E-Learning concept semantically; we have shown the cluster in table format. Initially, we have extracted important concepts from unstructured data followed by generation of vector space of each concept. Then we used different similarity formula to calculate fuzzy membership values of elements of vector to its corresponding concepts. Semantic Similarity is calculated between two concepts by considering repeatedly the semantic similarity or information gain between two elements of each vector. Then Semantic similarity between two concepts is calculated. Thus concept map can be generated for a particular domain. We have taken research articles as our dataset from different domains like computer science and medical domain containing articles on Cancer. A graph is generated to show that fuzzy relationship between them for all domain. Then clustering them in based on their distances
Automated Detection of Acute Lymphoblastic Leukaemia from Microscopic Images based on Human Visual Perception

Microscopic image analysis plays a significant role in initial leukaemia screening and its efficient diagnostics.Since the present conventional methodologies partly rely on manual examination, which is time consuming and depends greatly on the experience of domain experts, automated leukaemia detection opens up new possibilities to minimize human intervention and provide more accurate clinical information.This paper proposes a novel approach based on conventional digital image processing techniques and machine learning algorithms to automatically identify acute lymphoblastic leukaemia from peripheral blood smear images.To overcome the greatest challenges in the segmentation phase, we implemented extensive pre-processing and introduced a three-phase filtration algorithm www.videleaf.comto achieve the best segmentation results.Moreover, sixteen robust features were extracted from the images in the way that haematological experts do, which significantly increased the capability of the classifiers to recognize leukaemic cells in microscopic images.To perform the classification, we applied two traditional machine learning classifiers, the artificial neural network and the support vector machine.Both methods reached a specificity of 95.31 %, and the sensitivity of the support vector machine and artificial neural network reached 98.25 and 100 %, respectively.
A Master Slave Parallel Genetic Algorithm for Feature Selection in High Dimensional Datasets

Feature Selection in High Dimensional Datasets is a combinatorial problem as it selects the optimal subsets from N dimensional data having 2N possible subsets. Genetic Algorithms are generally a good choice for feature selection in large datasets, though for some high dimensional problems it may take varied amount of time - few seconds, few hours or even few days. Therefore, it is important to use Genetic Algorithms that can give quality results in reasonably acceptable time limit. For this purpose, it is becoming necessary to implement Genetic Algorithms in an efficient manner. In this paper, a Master Slave Parallel Genetic Algorithm is implemented as a Feature Selection procedure to diminish the time intricacies of sequential genetic algorithm. This paper describes the speed gains in parallel Master-Slave Genetic Algorithm and also discusses the theoretical analysis of optimal number of slaves required for an efficient master slave implementation. The experiments are performed on three high-dimensional gene expression data. As Genetic Algorithm is a wrapper technique and takes more time to find the importance of any feature, Information Gain technique is used first as pre-processing task to remove the irrelevant features.
Sentiment Analysis of Social Network Feeds for Threat Protection

Social Network becomes widely accepted by the users and active communication tool in 21st century. In this paper, we use test data of Twitter, for sentiment analysis. Users may post vulnerable tweets which can result in threats; hence we analyze these tweets to determine threat warnings from specific group of users or organizations. We discuss brief literature review and present our methodology for doing sentiment analysis. We find several users most active and regularly mentioning other users. Based on our results, we present our analysis in the paper. Dataset was requested from Kaggle for research purposes.
Digital Food ordering system based on Spring Framework

As people nowadays engage themselves in busy schedules they skip their meals just because they have to go somewhere for food. So to avoid these, applications like Zomato, swiggy,and foodpanda need to be efficient and be able to order multiple items from multiple restaurants in a single order. Food orders from mobile devices are common nowadays, and they can help consumers order food more easily and efficiently. It can also give manufacturers and consumers full benefit. This allows the consumer to get the advantage of delivering food online. This research used a quantitative approach with 187 respondents to find out what stimulus variables important people in the online supply order.In existing systems, only order is placed in a single grocer. With this system we can place orders for multiple grocers.Apps are limited to mobile phones where this web application is accessed across various devices like mobile phones, PC , PDA ,tablets etc.
Motorized Tripod for Smart Phones

Press people attend technical events and other recreational events for covering the happenings of the event. Also, during functions in educational institutions and similar places, it involves live streaming of those events on social Medias. Smartphones help a lot in streaming these events live on social Medias. Often this live coverage is shaky and results in poor quality of the coverage. Hence, a portable motorized tripod with controller for smartphones is proposed. The smartphone is mounted on the tripod. The tripod consists of few predefined motion patterns, which can be enabled through controller on an app. The app is installed on a phone and then the tripod relates to the phone through Bluetooth. Thus, this product will enable the user to record and stream live without shake and the motion pattern will provide a standard video output. Apart from the motion patterns, the position of the smartphone can be changed as per the user needs using the app.
Financial Innovation Solutions from Blockchain Technology in the Perception of Financial Market Agents

The phenomenon of financial innovation (FI) found, in the fast-contemporary technological advance, the possibility of disseminating solutions that are intended to fill market gaps, promoting profound changes in the traditional financial structure. This finding can be explained by the perceptible movement of different agents interested in exploring the applications of blockchain technology in recent years. Considering this scenario of changes and expectations the present work aims to analyze perceptions of financial market agents about the possibility of blockchain technology influence in the creation of FI solutions. From the point of view of the research strategy, it constitutes a field research. We operated through interviews with the participation of twelve managers of institutions that operate in the financial environment. The results point to blockchain impacting the financial environment of organizations, whether in its technology platforms, investments, internal structures, people, governance, business conceptions. Likewise, by the existence of opportunities to solve market problems, affecting, through deeper changes in the financial system, from the disintermediation. It reveals the emergence of new business models and the possibility of consumers and managers less dependent on a centralized financial environment.
Alchemy &amp;amp; algorithms: perspectives on the philosophy and history of open science

This paper gives the reader a chance to experience, or revisit, PHOS16: a conference on the History and Philosophy of Open Science. In the winter of 2016, we invited a varied international group to engage with these topics at the University of Helsinki, Finland. Our aim was to critically assess the defining features, underlying narratives, and overall objectives of the open science movement. The event brought together contemporary open science scholars, publishers, and advocates to discuss the philosophical foundations and historical roots of openness in academic research. The eight sessions combined historical views with more contemporary perspectives on topics such as transparency, reproducibility, collaboration, publishing, peer review, research ethics, as well as societal impact and engagement. We gathered together expert panellists and 15 invited speakers who have published extensively on these topics, allowing us to engage in a thorough and multifaceted discussion. Together with our involved audience we charted the role and foundations of openness of research in our time, considered the accumulation and dissemination of scientific knowledge, and debated the various technical, legal, and ethical challenges of the past and present. In this article, we provide an overview of the topics covered at the conference as well as individual video interviews with each speaker. In addition to this, all the talks, Q&amp;amp;A sessions, and interviews were recorded and they are offered here as an openly licensed community resource in both video and audio form.
Enhanced Recommendation System for E-commerce Applications

Recommendation algorithms play a quintessential role in development of E-commerce recommendation system, Where in Collaborative filtering algorithm is a major contributor for most recommendation systems since they are a flavor of KNN algorithm specifically tailored for E-commerce Web Applications, the main advantages of using CF algorithms are they are efficient in capturing collective experiences and behavior of e-commerce customers in real time, But it is noted that , this results in the phenomenon of Mathew effect, Wherein only popular products are listed into the recommendation list and lesser popular items tend to become even more scarce. Hence this results in products which are already familiar to users being discovered redundantly, thus potential discovery of niche and new items in the e-commerce application is compromised. To address this issue , this paper throws light on user behavior on the online shopping platform , accordingly a novel selectivity based collaborative filtering algorithm is proposed with innovator products that can recommend niche items but less popular products to users by introducing the concept of collaborative filtering with consumer influencing capability. Specifically, innovator products are a special subset of products which are less popular/ have received less traction from users but are genuinely of higher quality, therefore, these aforementioned products can be captured in the recommendation list via innovator-recognition table, achieving the balance between popularity and practicability for the user
The contents and structure of the professional mobility of the teacher

Academic mobility in professional education has been defined as the ability of participants of educational process to implement various educational trajectories, it also foreseens their ability to learn, teach, train, hold scientific research in other higher educational establishments or abroad.Бочарникова Т. Зміст і структура професійної мобільності викладача Актуальнi питання гуманiтарних наук.Вип 37, том 1, 2021 198 ПедагогiкаThe notion of 'professional mobility' has been specified as an integrative feature and personal ability to master key professional competencies in a quick and qualitative way, to improve these competencies constantly in various kinds of professional activity, to successfully develop a personal trajectory of professional development.Learning the essence and structure of the professional mobility of the teacher has allowed to conclude that the majority of modern researchers agree that it is one of tendencies of world development, predefining significant changes in the educational system.It is also a quality, which is necessary for a person for successful adaptation in modern professional activities.It is featured in educational standards which, in their turn, create opportunities for its development in higher educational establishments.This mobility is also directed for the development and improvement of professional competence and a specialist's personal qualities with a view of self-determination in a modern professional structure of the society.
Key Validity Using the Multiple-Parameter Fractional Fourier Transform for Image Encryption

As a symmetric encryption algorithm, multiple-parameter fractional Fourier transform (MPFRFT) is proposed and applied to image encryption. The MPFRFT with two vector parameters has better security, which becomes the main technical means to protect information security. However, our study found that many keys of the MPFRFT are invalid, which greatly reduces its security. In this paper, we propose a new reformulation of MPFRFT and analyze it using eigen-decomposition-type fractional Fourier transform (FRFT) and weighted-type FRFT as basis functions, respectively. The results show that the effective keys are extremely limited. Furthermore, we analyze the extended encryption methods based on MPFRFT, which also have the security risk of key invalidation. Theoretical analysis and numerical simulation verify our point of view. Our discovery has important reference value for a class of generalized FRFT image encryption methods.
MULTISPECTRAL IMAGE COMPRESSION USING WAVELET TRANSFORMS

Compression plays a key role in reducing transmission and storage requirements.Compression of Multispectral data is important as it demands lots of memory space for storage.In the present work, the paper proposes transform coding techniques such as different Discrete Wavelet Transform (DWT) for compressing the multispectral data.The transform coding techniques are applied for multispectral input data and are compared with respect to Compression Ratio (CR) and Peak Signal to Noise Ratio (PSNR).The technique proposed is implemented individually on various bands of multispectral image.