Reviewerly/exHarmony huggingface dataset:
Disquisition of Sentiment Inquiry with Hashing and Counting Vectorizer using Machine Learning Classification

With the rapid growth in technology, analysis of feedback and reviews by the customers in companies and industries becomes a major challenge. The profit of the company mainly depends on the customer satisfaction. The view of the customer can be analyzed only through feedback. The review analysis can be utilized for the prediction of current sales and future sales of the company. With this overview, the paper aims in performing the sentiment analysis of the movie review. The Type of comment given by the customer is predicted and categorized into classes. The sentiment Analysis on movie Review dataset taken from the KAGGLE leading Dataset repository is used for implementation. The categorization of sentiment classes is achieved in five categories. Firstly, the target count for each sentiment is portrayed. The Resampling is done for equalizing the target sentiment count. Secondly, the extraction of sentiment feature words for each target is displayed and the data cleaning is done with Term Frequency Inverse document Frequency method. Thirdly, the resampled dataset is then fitted with the various classifiers like Multinomial Naives Bayes Classifier, Logistic Regression Classifier, KNearest Neighbors Classifier, Bernoulli Naives Bayes Classifier, Complement Naives Bayes Classifier, Nearest Centroid Classifer, Passive Aggressive Classifier, SGD Classifier, Ridge Classifier, Perceptron Classifier. Fourth, the feature extraction is done with Hashing Vectorizer and Counting Vectorizer. The vocabulary features are also displayed from the dataset. Fifth, the Performance analysis of clasifier is done with metrics like Accuracy, Recall, FScore and Precision. The implementation is carried out using python code in Spyder Anaconda Navigator IP Console. Experimental results shows that the sentiment prediction and classification done by Ridge classifier is found to be effective with Precision of 0.89, Recall of 0.88, FScore of 0.87 and Accuracy of 89%.
The last book of the scientist

The article reviews the book of the famous archaeologist Lev Klein “Dialogues. Theoretical archeology and not only, “summed up the results of the author’s multifaceted activities in science.
THE QUANTIFICATION OF URBAN LITTER LOAD AT GROSS POLLUTANT TRAP ALONG SUNGAI BATU, SELANGOR

The massive amount of urban litter in Malaysia is influenced by rapid population growth, development, economic growth and unsustainable lifestyles. Few studies have assessed the amount of urban litter load and its composition at gross pollutant trap (GPT), significantly contributing to lack of historical data. This study is aimed to assess the amount of urban litter load in wet basis condition at individual GPTs along Sungai Batu, Selangor in 2015. The urban litter collection data at each GPT in 2015 were sourced from Department of Irrigation and Drainage (DID). Samples were manually collected once a month, stored in plastic bag and immediately weighed and recorded by following the ASCE standard method. The result shows that the total amount of urban litter load in 2015 was 3761.72 kg/year (Mean ± SD; 313.4767 ± 141.9105 kg/year). In such situations, further study on urban litter load and its composition trapped at GPTs is urgently required as it is crucial to establish baseline data information during the decision making process, holistically improving stormwater management and urban litter management in Malaysia.
Structure and functions of forming legal competence in the educational process of professional training

This paper discusses aspects related to the formation of professional and legal competence in the process of scientific and educational process of training bachelors of engineering and technical profile. A modern professional should be not only qualified literate, but also socially competent, and also often legally literate, be able to coordinate, manage and obey himself, resolve conflicts and be able to make decisions within the existing legal framework, etc. For this, it is advisable for a future bachelor know legislative and other regulatory legal acts, be able to use them productively in practical professional work. Purpose of the study: to determine the essence and properties of the structural components of the formation of legal competence of bachelors in the process of vocational training. When solving particular problems of theoretical research, methods were comprehensively used such as analysis of methodological, philosophical, sociological, psychological, pedagogical literature on the problem of research, study of legislative and regulatory acts on higher education and the functioning of technical institutions, synthesis and generalization of information received on subject of research. The structure of legal competence, as well as objective and subjective properties of legal competence are revealed. Legal competence is presented as a complex, integrative education, consisting of a complex system of knowledge, abilities, skills and individual qualities of a future bachelor of engineering and technical specialties. Moreover, the content of legal knowledge should be adequate to the professional activity of the future bachelor, and only if this condition is met this knowledge will contribute to the improvement of his legal competence.
Employer Has No Remedy Against Employee's Profanity

Can an employer fire an employee who yells “F** you,” at a manager during a confrontation? Yes, no, and maybe can be correct answers.
PROVIDING POST TRUTH ERA: SOCIAL MOVEMENT OF CADRE TEAMS IN RESOLVE THE HOAX OF HEALTH INFORMATION

The post truth era has become a new vocabulary for cadres who never give up in following the times. But who would have thought that the post truth era would also lead to a dilemma that never ended after unsettling the cadre team in Cibeusi village. The cadre team that was incorporated from 3 RWs including RW 06, RW 014, and RW 015 also showed their dedication through regular social activities. Therefore, the authors use a qualitative approach through data collection techniques in the form of observation and interviews. The results obtained show the following; 1) designing social movements as an effort made by the Cibeusi cadre team in overcoming health information hoaks and the post truth era; 2) the Cibeusi cadre team's social movement implementation consists of 3 words, namely active, innovative, and creative; 3) cadre team social movements include communication programs in the form of counseling and training involving academics or related medical personnel as the main sources in providing literacy movement training programs; 4) Evaluation of the ongoing literacy movement as part of the success of the government health program output.
Drawing faults

Faults are commonly encountered during geology fieldwork and are frequently the subjects of sketches in the field. This chapter introduces simple field sketches using faults as an example. It considers how best to draw faults in the field and the important features of these structures to record. Two worked examples of field sketches are given and focus on the techniques employed to draw their geometries accurately. The rules introduced in Chapter 2 are revisited, as are the techniques of blocking-in, adding key features, and the importance of labels and scale. Both simple faults and complex fault zones are considered in the chapter. Common mistakes made in geological sketches are also described.
Filtering Content Distributed via BitTorrent over Hidden Networks

This article addresses the problem of distributing copyrighted thematic content to increase the possibilities for restricting access to such content. The analysis of existing solutions in this area is carried out, highlighting the shortcomings of these solutions, options for applying these methods to limit the distribution of thematic content in hidden parts of the Internet. A new approach is proposed to limit access to thematic content that is distributed using the BitTorrent protocol in hidden networks. The proposed approach also uses the disadvantages and advantages of the network in which thematic content is distributed. An experiment is described for applying this approach to Darknet resources. The results of the experiment highlighted the pros and cons of the proposed approach. The final part contains conclusions about the possibility of using the proposed approach in hidden networks.
Parameters, Factors and Criteria of Evaluation of Professional Development by Heads o f Schools

The article considers parameters, factors and criteria of evaluation of professional development of teachers by heads of school. It was determined that evaluation of professional development of a teacher of the general educational institutions is implemented according to the following parameters: the readiness of a teacher of the general education institution for pedagogical activity, the content of the activity of the teacher of the general education institution, and the result of educational work of the teacher of the general educational institution. It was highlighted that the parameter “The readiness of a teacher of the general education institution for pedagogical activity” consists of the following factors: continuing education and personal qualities of a teacher. It was revealed that the parameter “The content of the activity of the teacher of the general education institution” is determined by such factors as professional duties and creative pedagogical activity. It was also specified that the parameter “The result of pedagogical activity of the teacher of the general educational institution” implies the factor of a teacher`s social activity. The article reveals the results of diagnostics of teachers` professional development evaluation by school administrators via the level of the readiness for pedagogical activity, the content and the result of educational work of a teacher of the general education institution
Scalable keyword-based search and data manipulation on encrypted data

Cloud-based services increase productivity and reduce infrastructure cost industries which attract researchers and individuals outsource data to the remote cloud servers. However, cloud servers pose several security issues and the most prominent issue is privacy. Although encrypting the data before outsourcing preserves the data privacy, it does not support data usability such as searching with keywords on encrypted data. Searchable symmetric encryption (SSE) is found to be an efficient solution and in this paper, we construct an SSE method which enables search operation on encrypted data and allows various data operations on encrypted data. We perform document clustering and construct index tree-based secure search scheme. The index and queries are constructed with vector space model and are encrypted using secure k-NN computation method. We defined two encrypted searchable schemes based on two security models. We perform thorough experiments to justify the efficiency of the proposed model.
Luster Sampling to Improve Classifier Accuracy for Numeric Data

Clustering is one of the essential techniques to group similar data. Improving model accuracy is still a challenge for all variety of data. Training and testing a classifier on entire data is not possible for large scale of data. Sampling of the data is necessary for any modeling and is an important aspect in data mining. All models train and test on different samples taken by traditional techniques like random forest ensemble method. In this paper, we propose cluster sampling which is superior to any other sampling methods in improving classifier accuracy. Sampling the data from usual methods cannot cover all variety of data from the original. Cluster sampling is a two-step approach. First it clusters the entire data, second it selects samples from each cluster. These samples consists all verity of data with equal proportion. Cluster sampling leverages the tree based ensemble to handle categorical, numerical and mixed type of data. Classifiers modeled on cluster sampling samples shown superior in accuracy than modeled on other sampling techniques.
Pattern Recognition Referees 2018–2019

As a new human-computer interaction way, in-air handwriting allows users to perform gesture-based writing in the midair. However, most existing in-air handwriting systems mainly focus on recognizing either isolated characters/words or only a small number of texts, making those systems far from practical applications. Instead, here we present a 3D in-air handwritten Chinese text recognition (IAHCTR) system for the first time, and construct the first public large-scale IAHCT dataset. Moreover, a novel architecture, named the temporal convolutional recurrent network (TCRN), is proposed for online HCTR. Specifically, the TCRN first applies the 1-dimensional convolution to extract local contextual features from low-level trajectories, and then it utilizes the recurrent network to capture long-term dependencies of high-level outputs. Compared with the state-of-the-art architecture, the TCRN not only avoids the domain-specific knowledge for feature image extraction, but also attains higher training efficiency with a more compact model. Empirically, this TCRN also outperforms the single recurrent network with faster prediction and higher accuracy. Experiments on CASIA-OLHWDB2 & ICDAR-2013 demonstrate that the TCRN yields the best result in comparison to the state-of-the-art methods for online HCTR.
Hiding an Image in Its Small Segment by Mixing the Segments

Blending mechanism and segmentation procedures are used for the hiding process. By blending the segments of an image forms a single segment. The whole image is hiding in this single segment. The proposed work attempted to split an image into eight segments and mixing the segments by performing arithmetic operations between the segments. The original image is hiding in the one of eight segment of the image. By the reverse process, the original image can be extracted.
DOE releases $20M for AI, machine learning tools

Federal Grants & ContractsVolume 43, Issue 10 p. 1-1 Article DOE releases $20M for AI, machine learning tools First published: 16 April 2019 https://doi.org/10.1002/fgc.30375Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume43, Issue1018 April 2019Pages 1-1 RelatedInformation
Feature-Based Opinion Mining and Managed Machine Learning with Sentiment Classification Models

Sentiment Analysis is individuals' opinions and feedbacks study towards a substance, which can be items, services, movies, people or events. The opinions are mostly expressed as remarks or reviews. With the social network, gatherings and websites, these reviews rose as a significant factor for the client’s decision to buy anything or not. These days, a vast scalable computing environment provides us with very sophisticated way of carrying out various data-intensive natural language processing (NLP) and machine-learning tasks to examine these reviews. One such example is text classification, a compelling method for predicting the clients' sentiment. In this paper, we attempt to center our work of sentiment analysis on movie review database. We look at the sentiment expression to order the extremity of the movie reviews on a size of 0(highly disliked) to 4(highly preferred) and perform feature extraction and ranking and utilize these features to prepare our multilabel classifier to group the movie review into its right rating. This paper incorporates sentiment analysis utilizing feature-based opinion mining and managed machine learning. The principle center is to decide the extremity of reviews utilizing nouns, verbs, and adjectives as opinion words. In addition, a comparative study on different classification approaches has been performed to determine the most appropriate classifier to suit our concern problem space. In our study, we utilized six distinctive machine learning algorithms – Naïve Bayes, Logistic Regression, SVM (Support Vector Machine), RF (Random Forest) KNN (K nearest neighbors) and SoftMax Regression.
Avatarme: digital avatars in a theme park queue creating a better experience and an emotional connection

Research has shown that through customization, a user can create a longer and more meaningful connection with their avatar. This research harnesses this emotional bond in order to create a more engaging experience in the queue at theme parks. Two methods were used to collect information. The first was an online survey about queuing, Bitmoji, and theme park behavior. The second was an on-site observational study to gain a more detailed look into guest behavior in a theme park queue. This research concludes with mockups and documentation for implementing a park-wide avatar system for alleviating queue boredom for the end user. Queues are not only for holding guests in a fair line, but for on-boarding, for the immersive story and background, and for entertainment. By personalizing and customizing the experience for the guest, a more enriching and emotional connection can be made to the attraction, and the park itself.
An Integrated Software Development Method with built-in Software Process Improvement Framework

The concept of a startup is growing around the world where innovation is the major driving force. Managing such a small startup company from both technical and administrative perspective is a challenging issue. Though several approaches for software development, like the waterfall model, agile model, SCRUM model are available, it is difficult to implement such a model with full features due to limited number of resources, lack of experienced resources and lack of enough financial capability. The scopes of software process improvement are even narrower in a situation where they hardly manage or adapt a methodology. As a result, small companies suffer and work without a good quality framework model. Companies struggle to produce quality software. In this work, we have suggested an integrated software engineering methodology, in which, the process improvement framework is a built-in phenomenon. Our system is dubbed as 3D model, where the Ds stand for Design, Develop and Deploy. Design indicates the design of the product making as well as the process design. Develop and Deploy is also hinting to the product and process. The process improvement is managed through observation and management, which are fed back into the system through proper documentation. We did some client surveys, organization surveys, and observed work patterns of a group of human resources for a period. We measured some of the parameters before and after the implementation of 3D model. We found that implementation of 3D model gives an improved process and product development environment with no extra manpower or extra costing.
Critical Review: Current Research Issues on Crypto-currency and its Application in Financial Sectors

This research article is based on the current research issues on crypto-currency and its application in financial sectors. The researcher stated that crypto- currency attracted a significant attention and has been adopted in numerous applications, such as smart grid and Internet of Things (IoT) have a high scalability barrier for block-chain which limits its ability to support services with frequent transactions. In this research paper the researcher emphasized that some of the significant research issues on decentralized, peer to peer financial networks face risks such as fraud and suspicious trading, volatile price fluctuations, regularity uncertainty, and instability in financial sectors. This research study shows the huge growth of online users, virtual word concept which are created a new business phenomenon to facilitate financial activities such as buying, selling and trading. This research article analyzed the user&amp;rsquo;s expectation of future of crypto-currency in financial sectors at different significant level. In addition to this the researcher also discussed a statistical report which is adopted from the Statistic to provide a future direction of money regulatory in financial sector.
Data Acquisition From Mobile Phone using Mobiledit

Mobile forensic is a subsidiary of digital forensic that is flourishing constantly. As per current scenario, mobile phones not only mean traditional mobile phones that were developed and used in late 1990s but also include smart phones that offer an array of functionality. Mobile phones developed in 1990s also known as feature phones provided limited functionality such as calling and messaging as they were subjected to provide communication facility. But at present, mobile phones are used not only for communication but also for executing face to face interactions, shopping using various applications, trading and internet surfing, etc thus making mobile more feature-variant and making them smart. Since, mobile phone market is constantly rising because of increased and improved features; usage of mobile phones in criminal activities or illegal activities has also increased. The crime scene can be re-created by identifying the series of actions that has taken place when crime was committed by using compatible mobile forensic tools. Current attack could not be prevented, but the investigator can attain all crucial evidences present on the crime scene in order to reduce similar kind of attacks in future. The capturing and recording of crime scene, collecting and analyzing the evidence and finding the culprit and reason of committing crime is the art of mobile forensics. In this paper, we are going to discuss the implementation of proposed framework by using tool MOBILedit
LibraryVPN

Describes the state of the LibraryVPN project. This is an IMLS funded project (LG-36-19-0071-19) to develop VPN software that libraries can host for their patrons. This will allow patrons to secure their internet traffic from wherever they are using their local library's VPN.
An Improved Stream Processing Access

Migration of Legacy applications into modern Cloud, IOT architecture are challenging tasks and many researchers are showing interest to build modern Real time cloud and IOT based applications like smart cities, Video mining, Health care, Industrial event monitoring and many more for modern human life. Such applications should require efficient online data streaming techniques to process large amount of unstructured online data streams instead of offline. Modern customer centric applications with different verticals are looking for distributed and horizontal data streaming approaches. Many real time streaming approaches are emerging to utilize or process large real-time data by replacing legacy centralized scenarios which are causing more memory utilization, delay and fault tolerance. In this paper we present common models and architectures for real time utilization of cloud and IoT based application stream processing. Utilization of the real-time data of IoT/Cloud applications are possible with collective streaming techniques of network, data processing. In this paper we are focusing on improving stream processing techniques, limitations and future research directions for real-time stream processing