Reviewerly/exHarmony huggingface dataset:
Unsupervised Selective Rank Fusion for Content-based Image Retrieval

The CBIR (Content-Based Image Retrieval) systems are one of the main solutions for image retrieval tasks. These systems are mainly supported by the use of different visual features and machine learning methods. As distinct features produce complementary ranking results with different effectiveness performance, a promising solution consists in combining them. However, how to decide which visual features to combine is a very challenging task, especially when no training data is available. This work proposes three novel methods for selecting and combining ranked lists by estimating their effectiveness in an unsupervised way. The approaches were evaluated in five different image collections and several descriptors, achieving results comparable or superior to the state-of-the-art in most of the scenarios.
The 4th International Conference on Science, Technology and Interdisciplinary Research (IC-STAR 2018)

PREFACE The 4 th International Conference on Science, Technology and Interdisciplinary Research (IC-STAR 2018) was organized by University of Lampung, in Tanjung Pandan, Belitung, Indonesia, on August, 29 th - 30 th 2017. Following the successful of previous events, IC-STAR 2018 shared and highlighted the original and novel ideas, significant advances, the technological state-of-the-art, current status, and future challenges on all aspects related to the research and development in the field of science, engineering and technology, and their inter-discipline cross-linked. IC-STAR 2018 accomplished as a forum for information dissemination, gathering, and networking for academia, researchers, engineers, and professionals within the areas. The conference also provided advanced orientation and understanding for related industries and academia to looking across industrial partnerships, business strategic, and policy and regulations, including the environmental awareness and the mitigation of natural disasters. One of the most important outcomes of IC-STAR 2018 was the understanding to emphasize Krakatau and its potential disaster as a common issue and interest. List of Editorial board, IC-STAR 2018 Committee and Conference Photographs are available in this pdf.
Social-Psychological Features of Leadership Manifestation Within the Environment of the Work Team

The effectiveness of a police officer’s professional performance depends on many social processes and phenomena, on socially-oriented and/or person-oriented communication with colleagues, different categories of citizens, on the level of organisation of this activity in general, on leadership and management processes. These days, such areas of psychology as communication between work colleagues, leadership in the circle of colleagues, and other factors impacting professional efficiency remain insufficiently covered. The authors have already touched on the issue of leadership and communication in our research, however, the authors have not carried out a specific study. The study is mainly aimed at the theoretical-methodological and empirical research into the phenomenon of leadership in the workplace team environment. Main research methods: observation, testing, mathematical-statistical analysis and socio-psychological influence methods. Key results: the scientific concept of ‘leadership’ and specificity of its manifestation in the service team was revealed; the problem regarding the lack of methods and techniques for the study of leadership and management processes in the service team was noted; in order to characterise the service team as an integrated system of interpersonal relations the indices of mutual acceptability/unacceptability, cohesion, coherence, etc. were calculated; the results of communicative activity and expression of leadership personality and management style, etc. were obtained; recommendations on how to organise joint activities and develop leadership skills are given. It is also noted that in order to develop leadership qualities in the workplace, it is advisable to develop the readiness of the individual to make responsible decisions, skills and abilities to quickly and correctly assess the personality, the situation, the socio-psychological climate of the workplace team, etc.
Fundamentals

In this thesis we will consider two main areas of application for machine learning namely classification and regression. In the so-called training phase the machine learning algorithms parameters need to be adapted with respect to the problem. Let us define a set of n training samples xi with class labels yi together called the training set.
Determining the semantic orientation of opinion words using typed dependencies for opinion word senses and SentiWordNet scores from online product reviews

Opinion words express the information regarding the like and dislike of a user on the target entities such as products and product aspects present in the online reviews. The polarised information collected from the reviews is analysed by calculating the orientation of the adjectives. The synonymy relation graph is a way to determine the orientation of the adjectives present in the product reviews dataset. It considers the minimum path length between the adjectives under analysis using WordNet synsets. The synonymy relation graph cannot determine the orientations of all the opinion words present in the dataset. In order to evaluate opinion orientation of all the adjectives from the dataset, the synonymy relation graph of WordNet is to be replaced with the SentiWordNet scores of the opinion words. These scores are provided to the opinion words by finding the contextual clues surrounding the opinion words to disambiguate their sense. The contextual clues are finalised based on the typed dependencies grammatical relations. The distance between the opinion word and the context insensitive seed term (good/bad) is computed by calculating the difference between these scores. This paper addresses advantages of using SentiWordNet scores. This improves the accuracy of the determined opinion word orientations.
Make Virtual Meetings More Exciting for Attendees

Special Events GaloreVolume 20, Issue 8 p. 1-1 Virtual Meetings Make Virtual Meetings More Exciting for Attendees First published: 13 July 2020 https://doi.org/10.1002/speg.31394Read 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 onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume20, Issue8August 2020Pages 1-1 RelatedInformation
Dynamic energy-saving approaches in mobile cloud computing: issues, challenges and approaches

The use of mobile devices is ubiquitous in the current information era. However, there is a critical need for the technical integration of mobile computing with cloud computing to enhance the performance of mobile devices. Mobile cloud computing mechanism promises efficient ways of handling various constraints such as energy consumption, data transmission, bandwidth utilisation, weak network connectivity, and user mobility. This paper addresses these issues and discusses the benefits of integrating mobile communications with cloud computing. and the main focus is on computation offloading into the cloud as an effective technique for overcoming the energy constraints of mobile devices. The characteristics and implications of various computation offloading techniques are explored.
Data Ingestion using a Novel Method: H-Stream Framework

Current huge volumes of data is generated from wide variety of data sources and there is lot of demand for processing, this data. Apache Hadoop is designed for batch processing. Though Hadoop is used for batch processing there is lot of requirement for real time stream processing and querying on unstructured data. Data ingestion tools of Hadoop are playing a key role in processing of streamed log data. With the increase of volume of the data performance of data ingestion tools goes down linearly. In this paper we discuss solutions for performance issues of data ingestion tools, capturing and processing of streamed multimedia data along with real-time stream processing with the help of frame work known as H-Stream framework. (Abstract)
A Gist Warning of Sighting in Face Classification and Recognition

Face classification and recognition is the fastest growing, challenging area in real time applications. A large number of algorithms are there in the network to recognize the face. It is the important part of the biometric traits and it not only contributes to the theoretical insights but also to practical insights of many algorithms. Conversely, the first face recognition in the main reckons on a priori in a row of hurdle folks and might not free itself from human intervention. Until the looks of high-speed, better-quality computers, the face recognition methodology makes a big disintegrate through. Face recognition has been a quick growing, difficult and mesmerizing space in real time applications. Facial classifications and recognition becomes an interesting research topic. A large range of face classification and recognition algorithms are developed in last decades. In this paper a attempt is created to review a good vary of strategies used for face recognition expansively. This paper contributes a huge survey of varied face detection and feature extraction techniques. At the moment, there are loads of face classification and recognition techniques and algorithms found and developed round the world.
Support Forward Secure Smart Grid Data Deduplication and Deletion Mechanism

With the vigorous development of the Internet and the widespread popularity of smart devices, the amount of data it generates has also increased exponentially, which has also promoted the generation and development of cloud computing and big data. Given cloud computing and big data technology, cloud storage has become a good solution for people to store and manage data at this stage. However, when cloud storage manages and regulates massive amounts of data, its security issues have become increasingly prominent. Aiming at a series of security problems caused by a malicious user's illegal operation of cloud storage and the loss of all data, this paper proposes a threshold signature scheme that is signed by a private key composed of multiple users. When this method performs key operations of cloud storage, multiple people are required to sign, which effectively prevents a small number of malicious users from violating data operations. At the same time, the threshold signature method in this paper uses a double update factor algorithm. Even if the attacker obtains the key information at this stage, he can not calculate the complete key information before and after the time period, thus having the two-way security and greatly improving the security of the data in the cloud storage.
Data Sharing Toolkit

Data sharing, particularly of potentially sensitive information, is not always straightforward. This Data Sharing Toolkit has been developed to collate practical information and resources related to the topic. The Data Management Basics section includes explanations covering different aspects of working with data, from a list of free version control tools, through explanation of metadata, to real-life examples of data problems encountered by data managers handling clinical data. The Data Sharing Steps provide an overview of the core elements of the process of depositing your data into a repository. The Repository Finder has been developed in order to aid users in choosing a suitable repository to submit to. The toolkit also included an extensive collection of resources linked to working with and sharing data.
Cloud Based User Analytics and Dynamic Page Refreshment Application for Web Portal

Dynamic web development [1] is one of the emerging fields in computer science. Dynamic updation [2] without disturbing the user environment is a challenging task. The modern technologies provide more support for dynamic web content development. The social network, user customization are the needful buzz words for a successful business on the web. The standard colors and static design with dynamic operations may get bored. Online bookselling and reading are one of the leading business industry in the world. The book readers are interested to know the feedback of a book before going to read or purchase. Today social media gives background information about anything in this world. For selling or buying well in digital medium every user needs some relevant information about the product. The searching and buying products based on the customer reviews are become increased. For that Web 2.0 and other new techniques and models are used to assist users during the search, promote products during the requirement and very useful in decision making. This work is extending the existing functionality to support the analytics. The proposed web analytics approach enables users to know about the same interest groups in the web portal and enables to collaborate. The new portal should be a social media platform for the readers. In the new portal, the end-user is not only a user of the application but also a participant by social networking, tagging, etc.
Let’s Be Logical!

In arithmetic we learned how to perform arithmetical operations (addition, multiplication, taking negatives, etc.) on numbers; then, in algebra, we generalized arithmetic using variables instead of numbers. Similarly, we can build compounded statements from simple statements and we can study their general structures. The branch of mathematics dealing with the structure of statements is called logic. Logic A study of the rules of logic is essential when one studies correct reasoning.
Bi lingual Information Retrieval System for English and Italian Tweets using Python

Bi-lingual text analysis is competent in present scenario as the information gathered in various languages is flattering. The bi-lingual text classification is yet an obscure area whereas the text classification in a single language is well known. The concept of bi-lingual text has been left in a shell, apart from the lame stream of both theory as well as practical. The use of social media is increasing day by day and thus the amount of data too in increasing with a rapid rate. So, it is an alarming stage to analyze the big data and extract the useful information. In this paper, we are developing a dynamic information retrieval model and extricating the sentiments of people on global warming of English and Italian tweets and corresponding to it its heat map and affinity map are generated as it produces the output after harmonizing different objects which diverge in the rung of relevancy to the question.
An Improved Methodology for Data Hiding In Images Using Haar Transformed, LSB Replacement Method and Modified PVDMF 1

Steganography is a technique of concealing secret text or image within another image.In this paper, abetterand efficient steganography methodfor hiding imagesand/or text into a color image is proposed. The proposed techniqueis based on two irreversible methods of spatial domain Least Significant Bit (LSB) and Pixel Value Differencing and Modulus Function (PVDMF 1) and one Haar Wavelet Transformation of the frequency domain. The proposed method works in four stages: at the first stage, Haar Wavelet Transformation is applied on the input image and transformed Haar coefficients are obtained. At the second stage, Haar coefficients and secret image are converted into binary form, before applying the LSB replacement method on the green channel by replacing the first two Most Significant Bits (MSB) of the input image withthe last two LSB bits of the secret image. Inthe third stage, modified PVDMF 1 is applied on intermediate stego imagesafter hiding the image by dividing the image into two non-overlapping consecutive pixels of pixels for hiding text. Inthe fourth stage, Inverse Haar Wavelet Transformation is applied to get the stego image. The proposed method offers high hiding capabilitywith goodvisual quality. The visual quality of the stego image is measured by using three widely used objective quality assessment matrices PSNR, RMSE,and SSIM. Furthermore, Regular/Singular (RS) analysis is applied on stego imagesto check theirresistanceagainst RS attack. The hiding capacity and quality assessment results are compared with some existing methods. It is evidentfrom the comparison that the proposed processis superior in termsof visual quality and hiding capacity.
Removing Speckle Noise in Synthetic Aperture Radar Images using Linear Filters

Speckle is a granular aggravation, typically demonstrated as a multiplicative noise that influences Synthetic aperture radar (SAR) pictures, just as every single cognizant picture. In the course of the most recent three decades, a few techniques have been proposed for the decrease of spot, or despeckling, in SAR pictures. The examination begins with the linear filtering, non-linear filtering, adaptive filtering, and hybrid filtering. In spite of the fact that the old style straight separating strategies have lower execution similarly, the hybridization between them beats than the as of late proposed techniques. Be that as it may, the cautious determination of such filters and their impacting request exceptionally influences the presentation of such filtering methodologies. In this paper, Hybrid filtering is proposed for SAR despeckling, which involves the improved variants of frost, median and mean filters. The presentation of the proposed framework is broke down and contrasted and the as of late SAR despeckling strategies. The outcomes demonstrate that the hybrid filters are focused as they can despeckle the SAR pictures superior to the current methods
Task Trail Based Enhanced User Experience in Customer Facing Website using Automatic Facet Construction Techniques.

World Wide Web is the indispensable source for millions of millions user. The primary goal of the www is provide the most relevant, valid and right information for the end user to who is looking for the information. In this paper we conducted study on various term extraction method used recently by the researchers and we have made a comparative study of various term extraction techniques used in past. Finally we proposed a novel method of improving end user search experience by combining the task trail based user behavior and Automatic facet searching. Also this approach can be further taken forward by enhancing the facets search by referencing the well done Wikipedia for the descriptive based user search goal. The scope of the Automatic facets searching can be further enhanced for the product based product standard specification. Our scopes of work will predominately combining the Automatic facets with the user behavior from the task trail and adding product based standardization to improve the end search experience.
Common Knowledge in Epistemic Logic With Hypotheses

We recall the epistemic logic S5r for reasoning about knowledge under hypotheses and we investigate the extension of the logic with an operator for common knowledge. The logic S5r is equipped with a modal operator of necessity that can be parameterized with hypotheses representing background assumptions while the extension with the common knowledge operator enables us to describe and reason about common knowledge among agents with possibly different background assumptions. We present an axiomatization of the logic and prove Kripke completeness and decidability results.
The security survey

A security survey is the formal process used to review specific areas, applications, or processes of a business or residence to document risk and security vulnerabilities and/or validate the program in place. In this chapter, the purpose of a security survey, defining security survey goals, and building survey program/components of a security survey is reviewed. Also discussed is the use of an appropriate checklist or reference survey document, tailored to a particular sector, industry, or event; and the components necessary in reporting security survey results.
Implementation of Statistical Data Analytics in Data Science Life Cycle

The paper focussed on showing how the data science life cycle can be implemented with the real time data. Rain fall data is used in this research to show how to apply data science life cycle. The dataset consists of multivariate data were visualization has become easier and effective. The data description is shown in the table for better understanding. The various visualization like bar graph, tree map, line graph are shown by using tableau software.
Serverless Stream Processing with Elastic Multi-M/M/s/K Queue System

The high throughput - low latency stream processing systems are required to be elastic enough to scale for varying load spike on-demand. However, in the current stream processing systems, the load shedding is observed which impacts the final accuracy. In order to get rid of this issue, the elasticity can be implemented in all kinds of resources involved in the stream processing systems. This paper focuses on providing the elastic scalability in queues and Serverless functions for the event stream processing systems. First, we explain the need of elastic multi-queue with Serverless function in detail for event stream processing, and then will propose an algorithm for elastic scalability of multi-M/M/s/K Queuing with Serverless functions for the efficient stream processing. The experiment result shows that the system scales very well in short span of time with the help of our proposed algorithm. The increased availability in turn helps improving the high processing throughput in low latency.
A Probabilistic and Deterministic based Defect Prediction through Defect Association Learning in Software Development

Software development is a multitasking activity by an individual or group of team. Every one activity engages diverse tasks and complication. To accomplish quality improvement, it is essential to make every activity task free of defects. But locating and correcting defects is more expensive and time-intense. In the past, many potential methods have been used to predict potential drawbacks in the program based on the theory of probability facts. Because the probability method applies a random variable and probability distributions to find a solution, the result is always in a possible range that can be true at some time or may also be wrong. Therefore, an additional calculation method coupled with the probability of making it more accurate and new in predicting the defect of the program. In this paper, we propose a Probabilistic and Deterministic based Defect Prediction (PD-DP) through Defect Association Learning (DAL). The PD-DP implements a Probability association method (PAM) and Deterministic association method (DAM) to predict the software defect accurately in software development. The experimental evaluation of the PP-DP in compare to existing prediction methods shows enhancement in prediction accuracy.
Some Thoughts about Profile Types

Abstract How the way the cane is distributed along and across the reed’s vibrating blades contributes to tone quality as well as ease in playing. Several variations are explored.