Reviewerly/exHarmony huggingface dataset:
Sentiment Analysis on Restaurant Review using Hybrid Approach

Sentiment analysis describes the overall sentiment behind the document or Sentence. SA is a field of NLP to analyze insights from social media mostly from Twitter, Amazon, Zomato, Trip Advisor, etc. Sentiment analysis of document or sentence generally categories as Positive, Negative, or Neutral. There are some drawbacks in machine learning and dictionary-based sentiment analysis, to overcome these issues hybrid approach works. In this research work, we discover a hybrid model for classification which is a combination of both machine learning and dictionary-based approach to enhance overall performance and accuracy and reducing the time and human effort required to manually labelling. In this paper, we performed labelling of the dataset according to their sentiment score using VADER lexicon-based technique and also evaluated multiclass classification using machine learning on restaurant reviews. This prediction can help to improve business service. This article also presents the study of several sentiment analysis classifier, tools and techniques and to perform sentiment analysis and provide future scope.
Mobile Robots in Particle Swarm Optimizers: A Novel Paradigm for Effective Swarm Optimization and Collaboration

A Particle Swarm Optimizer (PSO) and mobile robot swarm are two widely studied subjects. Many applications emerge separately while the similarity between them is rarely explored. When a solution space is a certain region in reality, a robot swarm can replace a particle swarm to explore the optimal solution by performing PSO. In this way, a mobile robot swarm should be able to efficiently explore an area just like a particle swarm and uninterruptedly work even under the shortage of robots or in the case of unexpected failure of robots. Furthermore, the moving distances of robots are highly constrained because energy and time of robots can be costly. Inspired by such requirements, this presentation discusses a Moving-distance-minimized PSO for a mobile robot swarm to minimize the total moving distance of its robots while performing optimization and collaboration. The distances between the current robot positions and the particle ones in the next generation are utilized to derive paths for robots such that the total distance that all robots move is minimized, hence minimizing the energy and time for a robot swarm to locate the optima. Experimental results on optimizing 28 CEC2013 benchmark functions show the advantage of the proposed method over the standard PSO. By adopting it, the moving distance of robots can be reduced by more than 40% while offering the same optimization effects. The implication is enormous since all population-based optimization algorithms can be potentially benefited from such replacement of their individuals with mobile robots, thus leading to their moving-distanceminimized variants.
Quality in translation through the combination of CAT tools and CohLitheSP

There have always been long-winded discussions on the role played by both human and MT in quality translation processes. Which one is better? Or, should they be used in combination to achieve a quality translation? The present paper provides an answer to these matters bymeans of the calculation of several evaluation metrics to study the quality offered by MT compared to human translation. Moreover, there is a implementation of a new tool (CohLitheSP) based upon the comparison between a reference model text with a text translated by humans, with some indexes including Narrativity, Readability, Referential Cohesion, Deep Cohesion, and Concreteness. All mention technology has been applied to the final year dissertations on tourist translation of one student who have already finished a degree in translation and interpreting but have never used this technology before
The Strategy Of Training High Level Educational And Practical Skilled Young Information Technology Generation

Creating the digital industry of the future requires the launch of the country's digital transformation by increasing the level of development of human capital, the rapid digital transformation of education. At the same time, it will be possible to actively use a research-based approach in the educational process, thereby developing students' skills in research and shaping their creative abilities and creative thinking based on IT competencies. This paper examines the strategy of training high-level IT professionals and its positive aspects of the education system of the younger generation based on kids’ programming course experiences and observations.
A differential privacy protection query language for medical data: a proof-of-concept system validation

Abstract Objective: Medical data mining and sharing is an important process in E-Health applications. However, because these data consist of a large amount of personal private information of patients, there is the risk of privacy disclosure when sharing and mining. Therefore, ensuring the security of medical big data in the process of publishing, sharing, and mining has become the focus of current research. The objective of our study is to design a framework based on a differential privacy protection mechanism to ensure the secure sharing of medical data. We developed a privacy protection query language (PQL) that integrates multiple data mining methods and provides a secure sharing function. Methods: This study is mainly performed in Xuzhou Medical University, China and designs three sub-modules: a parsing module, mining module, and noising module. Each module encapsulates different computing methods, such as a composite parser and a noise theory. In the PQL framework, we apply the differential privacy theory to the results of the computing between modules to guarantee the security of various mining algorithms. These computing devices operate independently, but the mining results depend on their cooperation. In addition, PQL is encapsulated in MNSSp3 that is a data mining and security sharing platform and the data comes from public data sets, such as UCBI. The public data set (NCBI database) was used as the experimental data, and the data collection time was January 2020. Results: We designed and developed a query language that provides functions for medical data mining, sharing, and privacy preservation. We theoretically proved the performance of the PQL framework. The experimental results show that the PQL framework can ensure the security of each mining result and the availability of the output results is above 97%. Conclusion: Our framework enables medical data providers to securely share health data or treatment data and develops a usable query language, based on a differential privacy mechanism, that enables researchers to mine information securely using data mining algorithms.
Evolving Attention with Residual Convolutions

Transformer is a ubiquitous model for natural language processing and has attracted wide attentions in computer vision. The attention maps are indispensable for a transformer model to encode the dependencies among input tokens. However, they are learned independently in each layer and sometimes fail to capture precise patterns. In this paper, we propose a novel and generic mechanism based on evolving attention to improve the performance of transformers. On one hand, the attention maps in different layers share common knowledge, thus the ones in preceding layers can instruct the attention in succeeding layers through residual connections. On the other hand, low-level and high-level attentions vary in the level of abstraction, so we adopt convolutional layers to model the evolutionary process of attention maps. The proposed evolving attention mechanism achieves significant performance improvement over various state-of-the-art models for multiple tasks, including image classification, natural language understanding and machine translation.
MSM Library: Status Codes in the Catalog: A Guide

As you search the catalog, for each publication you'll see a box show Format, Call Number, and Status. This is a guide to what the language in the last category means.
Perancangan & Analisis User Manager Restoran Menggunakan Mikrotik

Rumah Makan Nusantara is a restaurant in Bandung that has Wifi facilities as an advantage. The problem is that theadvantages are often used by some visitors only to use wifi and only order 1 type of food or drink with a duration that exceeds thenormal limit. Meanwhile, other visitors who recently visited did not get seats due to the limited space during lunch and eveninghours. So indirectly the restaurant experiences losses due to problems with visitors who only use the facilities excessively. Anotherproblem arises when visitors use wifi to download files which causes other visitors to experience a decrease in speed. The purposeof this user manager design is so that visitors in and out are efficient and will have an impact on income. This project uses aMikrotik router that has the RouterOS operating system with the Winbox program and for designing a user manager using theMikhmon application. The methods used for bandwidth management are Simple Queue and Queue Tree, for Firewall security,Scheduller for bandwidth scheduling, and Scripts etc. as supporting features. The final results will be seen from the results of thesatisfaction survey and sales results which are expected to continue to increase after this project is achieved.
Authorship Weightage Algorithm for Academic Publications: A New Calculation and ACES Webserver for Determining Expertise

Despite the public availability, finding experts in any field when relying on academic publications can be challenging, especially with the use of jargons. Even after overcoming these issues, the discernment of expertise by authorship positions is often also absent in the many publication-based search platforms. Given that it is common in many academic fields for the research group lead or lab head to take the position of the last author, some of the existing authorship scoring systems that assign a decreasing weightage from the first author would not reflect the last author correctly. To address these problems, we incorporated natural language processing (Common Crawl using fastText) to retrieve related keywords when using jargons as well as a modified authorship positional scoring that allows the assignment of greater weightage to the last author. The resulting output is a ranked scoring system of researchers upon every search that we implemented as a webserver for internal use called the APD lab Capability &amp; Expertise Search (ACES).
키워드를 활용한 중국 법령의 한국어 번역 연구

This paper conducts keyword analysis for Chinese-to-Korean translated statutes in comparison with untranslated original Korean statutes to analyze whether Chinese-to-Korean translated statutes are following rhetorical conventions of untranslated original Korean statutes. The conventional approach in legal translation focuses on the fidelity and achievement of equivalence between the source text and the target text. However, there has been a shift in legal translation. As an act of communication within the mechanism of the law, legal translation has its main emphasis on text reception. Against this backdrop, this paper adopts a more reader-oriented approach in legal translation. The translation of statutes, as a part of public-sector translation is aimed at providing information and focuses on the understanding of recipients. Therefore, it can be expected that translated statutes will follow rhetorical conventions of the same genre in the target culture. The investigation of five style keywords revealed that adequacy to the Skopos is not fully attained in the Chinese-to-Korean translated statutes.
Book review: Patrick Masiyakurima, Copyright Protection of Unpublished Works in the Common Law World (Hart Publishing, Oxford 2020) 240 pp.

In this timely and trenchant monograph, Dr Patrick Masiyakurima deals with an often neglected but important issue – the protection of unpublished works. He provides a systematic analysis of the certain crucial differences in the way published and unpublished works are treated in the contemporary copyright law in the common law world, most notably in the UK and the US. Starting with the way published and unpublished works qualify for protection, he maps the difference in the extent of protection, going on to reveal the disparity in the defences available against the infringement of published as opposed to unpublished works,
PENGOPERASIAN DAN PERAWATAN POMPA PEMADAM KEBAKARAN DARURAT DI KM. BHAITA PERKASA PT.CAKRA BAHANA JAKARTA

On the freighter with a gross tonnage of 1000 tons or more if there is a fire in one of the bagiam any room that could result in the cessation of the pump, there must be a means to provide replacement water to extinguish the fire. On the freighter with a gross tonnage of 2000 tons more means of replacement over the emergency pump must be installed permanently and stand alone. The emergency pumps should be able to issue a second spray jet is adequate for a fire suppression. Ditempartkan emergency fire pump in the front alcove that distance can be up to 300 meters from the accommodation space, or at the stern of the shielded room is full and has a driveway from the open deck at the stern.Emergency fire pump should be tested every week and recorded in the diary of the deck on the ability of suction and pressure pump. Head of the engine room shall ensure that the emergency fire pump inspected by a competent engineer each time before it is turned. This examination includes checking the presence of water in the fuel tank and the system.Therefore to pengoprasian maximum fire pump, by way of maintenance of the components of the pump must always be carried out periodically to components and systems for diesel engines on the damage.Keywords: fire pump.
Language, Vision and Action are Better Together

Much of what we do today is centered around humans — whether it is creating the next generation smartphones, understanding interactions with social media platforms, or developing new mobility strategies. A better understanding of people can not only answer fundamental questions about “us” as humans, but can also facilitate the development of enhanced, personalized technologies. In this talk, I will overview the main challenges (and opportunities) faced by research on multimodal sensing of human behavior, and illustrate these challenges with projects conducted in the Language and Information Technologies lab at Michigan.
Validity-Based Sampling and Smoothing Methods for Multiple Reference Image Captioning

In image captioning, multiple captions are often provided as ground truths, since a valid caption is not always uniquely determined.Conventional methods randomly select a single caption and treat it as correct, but there have been few effective training methods that utilize multiple given captions.In this paper, we propose two training techniques for making effective use of multiple reference captions: 1) validity-based caption sampling (VBCS), which prioritizes the use of captions that are estimated to be highly valid during training, and 2) weighted caption smoothing (WCS), which applies smoothing only to the relevant words the reference caption to reflect multiple reference captions simultaneously.Experiments show that our proposed methods improve CIDEr by 2.6 points and BLEU4 by 0.9 points from baseline on the MSCOCO dataset.
FACE MASK DETECTION USING CONVOLUTIONAL NEURAL NETWORK

COVID-19 pandemic originated by novel coronavirus is continuously spreading up to all over the world. The effect of COVID-19 has fallen on most of the development sectors. The eye system goes through a crisis. Many preventive measures are taken to reduce the unfold of this illness where carrying a mask is one among them. Here, the approach of Deep Learning for investigating faces with and whereas not masks were good trendy observations. Numerous latest algorithmic rules square measure are to come up with utilize the convolutional architectures to form the rules faultless at most possibility. The convolutional architectures had generated it realistically to bring out the component characteristics. The objective is to draft a binary face classifier that will note the human face at mean time in the figure with all of its position. Aboard this, it's bootable to notice one facial mask in each figure. The evolutions will be performed on retrieved human dataset to urge micro level accuracy for the sectional face masks. The leading benefit of convolutional neural networks (CNN) when comparing to its predecessors is that it ceaselessly detects the primary choices with the non-human management.
Improved Learning of Combining LBP and Original Image Datasets for Feature Extraction and Classification Using CNN

Face Recognition System is a computer application technology and it senses, tracks recognizes, or authenticates human appearances from any seized image or video via digital camera. Even though a ton of progress has been made in face detection, identiﬁcation, and security recognition, but issues are preventing the advancement to reach or outperform human-level exactness in human facial appearance, such as noise in face images, divergent illumination circumstances, pose scale. LBP is used in this paper to perceive characteristics of facial texture to diminish the inﬂuence of lighting up and disposition. CNN and skip affiliation are used to lessen the training time for parallel convolution processing and progress the accurateness of classiﬁcation. The proposed approach predominantly considers the FR reliant on parallel automatic extraction of features from LBP image dataset and original image dataset and classify the data using Deep Convolutional Neural Networks (DCNN). In the first part, LBP is utilized first to examine the texture of the information from the image dataset, later, the training dataset of combining the original image data set and LBP image dataset is applied to the CNN for automatically further extraction of features and lastly classification is performed. The proposed methodology achieved training accuracy 99.99%, validation accuracy 99.77%, and finally achieved test accuracy of 99.28% in 10 epochs. The investigational results proved that the projected methodology outperforms compared standing methodologies.
Symbol Grounding and Task Learning from Imperfect Corrections

This paper describes a method for learning from a teacher's potentially unreliable corrective feedback in an interactive task learning setting.The graphical model uses discourse coherence to jointly learn symbol grounding, domain concepts and valid plans.Our experiments show that the agent learns its domainlevel task in spite of the teacher's mistakes.
Quantum hardness of learning shallow classical circuits.

In this paper, we study the quantum learnability of constant-depth classical circuits under the uniform distribution and in the distribution-independent framework of probably approximately correct ...
DESIGN AND DEVELOPMENT OF LUGGAGE WRAPPING MACHINE WITH FACILITY OF SANITIZATION

Due to the pandemic scenario of covid-19 luggage safety is important, it is necessary that luggage is not contacted with harmful virus and dust, so protecting our luggage from this virus is important not only in an airplane traveling but bus, train traveling also by implementing 'luggage wrapping and sanitization machine ‘the safety of luggage against this virus is improved, it consists of a frame on which a circular table provided which can be run by low rpm gear motor mechanism, on rotating table luggage is mounted then sanitizer is sprayed on it with help of the spraying nozzle. Then the table is rotated by a motor so a thin plastic film wrap is wrapped around it. by covering all sides of the luggage and again sanitizer is sprayed on it.
A Systematic Review of Augmented Reality in English Language Learning

The use of technology in education has rapidly developed and various technological tools are implemented in the classroom.One of the technological tools which currently takes place in the interest of technology in education is augmented reality (AR).Hence, this study provides a systematic approach to explore how AR is practiced in English language learning (ELL), the benefits and limitations of using AR.This study employed comprehensive analysis and synthesis of 20 articles including peer-review journal articles and full-text articles within the period of 2016 to 2020 from three databases namely Google Scholar, ScienceDirect and Eric.Results of this study show that quantitative was mostly used in exploring the use of AR in ELL.This review also explores the features of AR mostly practiced in ELL and the positive impacts on ELL.Besides that, it analyses the constraints and limitations of using AR in teaching and learning.Overall, the results of this study show that all the studies agreed that AR can bring positive impacts towards ELL despite some limitations and constraints found in the integration of AR in learning.
Realities and complexities of RII analytics and assessment

Chapter 9 is devoted to a critical analysis of our case study material, where we point out the analytical strengths and shortcomings of university self-appraisal reporting on RII. There is not only a case to be made for embracing the notion of RII for organisational learning processes, but also for engaging in RII self-assessment for universities and its stakeholders – including funders. We advocate the use of external assessments to incorporate the external user perspective. The complementarity of self-assessment and external assessment offers a more comprehensive view and better understanding of RII profiles and performance levels. Implementation of assessment frameworks depends on the objective at stake; it ranges from light-touch ‘descriptive’ self-appraisal reporting about a university’s RII potential to a more exhaustive ‘evaluative’ self-assessment of its RII performance. It could be a straightforward self-assessment application with a tool kit of customized indicators, or a sophisticated mixed-method, multi-stakeholder review by an expert panel.