Reviewerly/exHarmony huggingface dataset:
Failure of Control Environment of Daewoo Shipbuilding &amp; Marine Engineering Co., Ltd.

In July 2015, one of the biggest shipbuilding and marine engineering companies in Korea, Daewoo Shipbuilding &amp; Marine Engineering Co., LTD (DSME), suddenly reported operating losses of 2.73 billion USD, resulting in chaos and frustration of investors and market participants. The announcement of this huge loss was the result of an accounting fraud conducted by the management team. Adam Kim, the former CEO of the company, concealed 4.5 billion dollars of losses by manipulating the accounting performances. This case exemplifies the results of the weak control environment. This paper examines the consequences of the weak control environment and ineffective monitoring activities of DSME.
Training Teaching Staff as the Key Factor for Primorsky Region Economic Development

Nowadays, the Russian government pays special attention to the problems of education system development. This is due to the fact that the global development has reached such a level where the educational capital plays a crucial role in the production of tangible values. Uneven regional distribution of production forces and their nature raise varying demands to the structure of activities of educational institutions in different regions. The main challenge to the local power authorities is to lay the groundwork for education development in accordance with the local demands. This article reveals the economic problems of education in Primorsky Region of the Russian Federation, as well as offers possible solutions.
Deriving overloaded success type schemes in Erlang

Erlang is a programming language which brings together the features of functional programming and actor-based concurrency. Although it is a dynamically-typed language, there exists a tool (Dialyzer) that analyses Erlang programs in order to detect type discrepancies at compile-time. This tool is based on the notion of success types, which are overapproximations to the actual semantics of expressions, so that the evaluation of an ‘ill-typed’ expression will eventually fail at runtime. Dialyzer allows programmers to provide their own type specifications. Although such specifications can be polymorphic and overloaded (i.e., reflecting different executing branches) for documentation purposes, the type analysis disregards the information provided by polymorphic type schemes and so does, in some cases, with overloaded types. In this paper we introduce: (1) a type system that allows us to obtain polymorphic overloaded success type schemes for programs, (2) a semantic definition of this kind of types, and (3) correctness results that prove that the adequacy of the obtained types w.r.t. the semantics of expressions.
IMAGE STITCHING BASED ON PARAMETRIC TRANSFORMATIONS

Transformation functions play a major role in mosaic images of different geometry. In this article, parametric global transformations, such as the similarity model, affine model and perspective projection model (projective model) are explored, and their performance in the mosaic of images with geometric differences are compared with respect to the execution time and registration quality. The approaches under study are tested on different types of images to deduce a scientific interpretation of results.
Segmentation and Edge Extraction of Grayscale Images Using Firefly and Artificial Bee Colony Algorithms

This chapter proposes an unsupervised grayscale image segmentation method based on the Firefly and Artificial Bee Colony algorithms. The Firefly Algorithm is applied in a histogram-based research of cluster centroids to determine the number of clusters and the gray levels, successively used in the initialization step for the parameter estimation of a Gaussian Mixture Model. The coefficients of the linear super-position of Gaussians can be thought of as prior probabilities of each component. Applying the Bayes rule, the posterior probabilities of the grayscale intensities are evaluated and their maxima are used to assign each pixel to clusters. Subsequently, region spatial information is extracted to form homogeneous regions through ABC algorithm. Initially, scout bees are moving on the search space describing random paths, with food sources given by the detected homogeneous regions. Then onlooker bees rush to scouts' aid proportionally to unclassified pixels enclosed into the bounded boxes of the discovered regions.
Methodology to Develop Military Students’ Foreign-Language Communicative Competence

The research objective includes development and justification of pedagogical methodology to form military students’ foreign-language communicative competence on the basis of the integrative-developmental approach. The research task is as follows: to optimize this process on the basis of the authors’ original methodology focused on creating pedagogical conditions to develop military students’ foreign-language communicative competence. Relevance of the study lies in the fact that the authors describe pedagogical conditions to develop military students’ foreign-language communicative competence on the basis of the integrative-developmental approach. Scientific originality of the paper includes development of the authors’ original methodology to form military students’ foreign-language communicative competence on the basis of the key principles (integrity, integration and development) of the innovative integrative-developmental approach.
Performance Analysis of the Classifiers for Optical Character Recognition

A brain can easily able to recognize handwritten words which computers are still struggling to figure out what they are. This amazing power of the brain requires to be transferred to a computer for automatic digitalization of handwritten texts and manuscript. The work proposed in this paper tried to make a model which is able to recognize and predict different Hindi character which can be further used to identify and digitalize the whole page or text. Our model uses different approaches like a base-line neural network, convolutional neural network, and a simple logistic regression model.
Fuzzy output system on the basis of the modified fuzzy Petri nets

The development of information technologies requires improvement of simulation methods and mathematical apparatus. The mathematical apparatus of Petri nets is used for simulation of parallel asynchronous systems and has a broad scope. The modified fuzzy Petri nets expand the modeling capabilities of Petri nets by combining the properties of different extensions. Modified extension can serve for construction of models with a complex structure and logic of operation with the use of fuzzy logic apparatus for control on the basis of the system of production rules.
Malaria Parasite Recognition in Thin Blood Smear Images using Squeeze and Excitation Networks

Malaria is a blood disease that is caused by the Plasmodium parasites transmitted through the bite of female Anopheles mosquito. To detect the existence of this parasite, the experts usually examine the thin blood smears. However, this requires considerable expertise in order to precisely make a distinction between the two categories. The result is that methods fail when the task of classification is largely-scaled. In recent times, researchers have started using machine learning techniques which require careful analysis of morphological, textural, and positional variations of the region of interest (ROI) in order to extract hand-engineered features. In this study, we tend to present an advanced method to automate the above process based upon the pre-trained CNN based model, SeNet. This model acts as a feature extractor towards classifying parasitized and uninfected cells. To carry out the process, we have used the dataset of microscopic images of red blood cells provided by United States National Library of Medicine. Our results show that the model achieved an accuracy of 97.24 % in identifying the malarial parasite in red blood cells. The AUC/ROC score (Area under Curve) came out to be around 0.97. The training loss was calculated using Categorical Cross-Entropy which was around 0.075. Statistical validation of the outcomes reveals the use of pre-trained CNNs as a favorable tool for feature extraction for this purpose.
Construction and Empirical Analysis of the Content System of Vocational Education Teachers' Information Technology Ability Training

Based on the information technology competence standards of foreign vocational teachers, this paper analyzes in detail the information technology content of vocational education teacher training in China, and combines the "National Training" project carried out by Gansu Province to provide information technology skills for 300 vocational teachers in cities and counties of Gansu Province. The investigation was carried out, and the principal component analysis method was used to analyze the factors of 42 competences. Finally, six competency factors were extracted, and the content system of information technology competency training for vocational teachers was constructed. The differences in information technology ability of vocational teachers in different backgrounds were analyzed. Finally, relying on the "National Training" project to conduct an empirical analysis of the training content system and verify the training effect.
Techniques of Filming and Audio Recording in 360-Degree Ambiences

Education has always been an important factor of life, being continuously analysed, in the attempt to improve its delivery in today’s classrooms. Although much has been done to give education more interesting ways of delivery, yet there are several generic instances when educational techniques used in today’s classrooms are deemed as outdated, both by educators and their students. Subjects, which are meant to enhance the knowledge and appreciation of a culture’s heritage, can at times not be exposed to students in the most exciting way possible, so as to enhance learning and maximise understanding. A country’s heritage is the map to its history. The accumulation of its languages, including its artistic endeavours and representations, stand as a reminder of our ancestors who have toiled hard to create the story that we are nowadays striving to keep alive and further enrich through contemporary means. Technology has become a tool which stands alongside the brushes and rasps of the artists and sculptors of antiquity. Today, computers and their burgeoning peripherals have given art newer twists and further methods of expression, which can in turn augment the way students are drawn into the magical world of their country’s heritage. This project is endeavouring to capture film languageFilm language and transpose it into a 360-degree film360-degree film environment, which combined with the enrapturing use of spatial soundSpatial sound will recreate an epic moment in the fairly unknown initial stages of the Great Siege of Malta. This immersion is aimed not only to excite the young minds of students through the narrative techniques used, but further create compassion through an increased sense of empathy.
Infrared Image Super-Resolution Enhancement Based on Convolutional Neural Network

With the rapid development of modern scientific research, the research of infrared technology has achieved a lot of results, and infrared detectors and other devices have also been widely used. However, infrared images have characteristics such as low contrast, unclear information, and blurred edges, which seriously affect the observation effect of infrared images. In order to better achieve observation and monitoring, it is necessary to optimize and enhance the acquired images. In this paper, the infrared image acquired by FLIR-Tau camera is taken as the research object. According to the characteristics of infrared image and the structure of convolutional neural network, an improved super-resolution convolutional neural network algorithm is proposed to train the algorithm model for infrared image. The infrared image is enhanced by the learning characteristics of the convolutional neural network, which is better than the traditional algorithm in contrast enhancement and detail information enhancement.
A Permutation-Based 3D-Sudoku Model for Image Steganography

In this paper, we propose a novel 3D-sudoku model for image steganography. Our 3D-sudoku table is constructed using a 8×8 random table. We propose a procedure to permute the elements in the 2D table. Then, different permutation versions are piled up to form a 8×8×8 3D-Sudoku table. Based on our permutation scheme, the resulting 3D-sudoku table can hide secret data with a good performance in both hiding capacity and the PSNR value.
Business Intelligence Application of Enhanced Learning in Big Data Scenario

The arrival of the era of big data has made the type and distribution of business data structure change qualitatively. In some scenarios, traditional business intelligence tools have been unable to meet the needs of modern enterprise intelligent decision-making. This paper introduces the background of zero inventory case and the current situation of zero inventory, and then validates the specific application process of reinforcement learning method in business intelligence by analyzing the application example of zero inventory in enterprises.
Beginning with Shakespeare

The Introduction first outlines the grounds for the collection’s dating parameters for ‘early Shakespeare’. It then discusses what a category such as ‘early’ or ‘late’ might mean for someone with Shakespeare’s long career, and how such temporally bound categories can condition critical responses. Next, it considers the many variables in play in Shakespeare’s early canon, discussing these with relation to the value ascribed to these works. The chapter then reflects upon how most readers of Shakespeare begin somewhere in the middle of the collected works, with super-canonical works like Twelfth Night and Hamlet, before, if ever, working to the margins of the canon where the early works reside. It concludes with brief summaries of each of the chapters in the collection, noting how contributors shed significant new light upon the formative part of Shakespeare’s career.
РОЛЬ НОВИХ ЕЛЕКТРОННИХ ЗАСОБІВ У ФОРМУВАННІ ВІЗУАЛЬНИХ КОМУНІКАЦІЙ ВИЩИХ НАВЧАЛЬНИХ ЗАКЛАДІВ УКРАЇНИ

&#x0D; &#x0D; &#x0D; The article focuses on the necessity of forming the brand of a higher educational institution (HEI) with the use of more electronic means, while it is substantiated that the main tools of modern promotion are so- called new media and the use of mobile application development platforms, which are becoming increasingly popular due to the development of information of society.&#x0D; &#x0D; &#x0D;
Enhancing sentiment analysis using rule mining and dual processing

Sentiment analysis is a widely researched area in computer science that have been attracting researchers since the past few decades. Shift in polarity is a problem that exists in sentiment classification. Another problem is the difficulty in handling inconsistent sentiment polarity between a phrase and its constituent words. For solving both, we perform dual sentiment analysis using an original dataset and its reversed version. We use a sentiment classification approach for classifying the sentiments of the reviews in both the original and reversed sets. This approach is based on segmenting the sentences and then using the segmentation results to find the polarity of the sentences. Then rules are mined to correctly classify the reviews. When this approach is applied on a product review dataset taken from amazon.com, it shows good precision, recall and f1-score values.
Language Modeling with Transformer

To date, the main method of language modeling is based on recurrent neural networks or convolutional neural networks. We show that two simple models which get inspiration from Transformer [1]. Compare to other attention network, the Transformer which just use self-attention and FFN (feedforward network) are highly efficient in training. We apply the idea which from the mechanism of Transformer to language module. We predict the future elements by the long-term dependence of context words which through the ANN (average attention network) and self-attention mechanism. We test our model on WikiText-103 where our model achieves 22.13 perplexity and on the Google Billion Word benchmark, which we achieve 26.31 perplexity.
Large-Scale Ubiquitous Learning Design and Practice Basing on Data-Driven Approach

Currently, data-driven extensive learning extends to K12 disciplines. However, the existing research mainly focuses on the field of higher education, lacking of datadriven large-scale ubiquitous learning teaching research in K12 field. This paper introduces the design and practice of three closed-loop systems of large-scale ubiquitous learning driven by "Zuoyebang Yike" data and hierarchical and efficient interactive classroom.
Simplified Wavelet Filter Implementation for Real-Time Signal Recognition

This article describes a simple implementation of wavelet filters for recognizing the shape of pulsed signals in real time. The proposed approach allows implementing a multi-level wavelet transform both in a discrete form based on microcontrollers and in a discrete-analog form using simple operations of addition and multiplication by a constant. The article describes a simple algorithm for calculating wavelet coefficients, estimates its speed and accuracy for performing calculations with a fixed point. The paper presents the calculation of the required number of memory cells for the implementation of the modified algorithm and shows that with a small filter length, some memory savings are achieved compared to the classical implementation. The article provides a simple implementation of an analog adder with accumulation of the result and proposes a functional diagram of a wavelet filter based on unified modules. The paper considers a practical example of the recognition of pulse signals based on the working alphabet of two classification criteria, which are approximating and detailing wavelet coefficients.
Indian sign language recognition using AlexNet

Sign language is the language which people with hearing problems used to communicate. The problem will be more complicated if the listener is does not understand the sign language. Here in this project we made use of image based hand gesture recognition techniques for identifying the sign language. The input sequence of images are captured with a digital camera. It is then passed through a sequence of preprocessing steps for the removal of background noise. The image is segmented based on the skin colour and is later on edge segmented to obtain the exact shape of the detected skin pixel. Canny edge detector is used for this purpose. The recognition of hand or body with surroundings is done by comparing the brightness information in HSI colour model. The colour thresholded image is then given to the AlexNet and the gesture signaled is identified in to a particular category and the label is extracted.
Robust Feature Combination for KNN Classification to Obtain Classification Accuracy

A popular method for acquiring the electrical activity of muscle is called Electromyography (EMG). It is widely used for the detection and treatment of neuromuscular disorders. EMG has been in use in medical field for the diagnosis of neuromuscular disease for several years. Neuromuscular disorder that affects the peripheral nervous system includes Myopathy and Amyotrophic Lateral Sclerosis (ALS). Primary goal of this paper is to classify normal, ALS and myopathy EMG signals based on the features being extracted. Different combinations of frequency domain, time domain and time- frequency domain features were obtained and analyzed for the best result. About 97% classification accuracy was achieved when the feature set comprising of standard deviation and Willison amplitude was classified using K-Nearest Neighbor (k- NN) classifier.
Inland Stream Placers

A synthesis of data reveals that resource-base for yttrium was identified during 1970s in Chhottanagpur Granite Gneiss Complex (CGGC) terrain in Siri river and its tributary in Kunkuri area, central India. Consequent to demand for Y-rich mineral concentrates by IREL (India) Limited during 1980s, not only flow sheet was developed and a recovery plant was set up near Kunkuri to win xenotime-rich concentrates, but simultaneously also exploration efforts were intensified to augment resource base already known then. This effort led to discovery of several xenotime-bearing riverine placers along the courses of several streams draining through CGGC terrains mainly in parts of Jharkhand and Chhattisgarh. Streams draining Godhra granitic rock terrain in western India offers scope for exploration inputs for xenotime-bearing riverine placers in Gujarat and adjoining areas. Although in Bastar craton REE resources are identified, they are of low grade and localized nature along certain low order streams draining through Darba-Paliam granitic rocks in Bastar and adjoining Koraput. Localized, but encouraging HREE bearing soils/placer are present in ephemeral streams of low orders in the vicinity of younger potassic granites in parts of Telangana State. Alkali granites and associated soils offer opportunity for exploration for REE resources, particularly for HREE in south India. Locally high concentrations of REE in quartz veins in Mincheri, Raichur district, Karnataka opens a new geological domain for REE exploration. It is apparent that bulk of the HREE resources are restricted to stream placers along the courses/banks of selected streams draining through granitic terrain mainly in parts of Eastern and Central, with some in Western and Southern India.
ФУНКЦІОНАЛЬНА МОДЕЛЬ ЗАБЕЗПЕЧЕННЯ ПРОФЕСІЙНОГО САМОВИЗНАЧЕННЯ УЧНІВСЬКОЇ МОЛОДІ В УМОВАХ ОСВІТНЬОГО ОКРУГУ

&#x0D; &#x0D; &#x0D; The article is devoted to the consideration of the functional model of providing professional self-determination of pupils in the conditions of the educational district. It contains a description of the organization of the respective activities of the subjects of vocational guidance activities, which is provided with all available resources of educational districts and takes place in a complex way during the periodic, extra-curricular and extracurricular subject-transformation activities, during the pre-school preparation and profile education of the students of youth. According to the author, the model proves that the professional self-determination of students in the educational district occurs as a process of purposeful and consistent self-modification of the individual, which is carried out under the influence of the vocational guidance activity of the subjects of educational districts coordinated by the only structural unit determined by them in its composition.&#x0D; &#x0D; &#x0D;
A Novel Method to Recognize Shapes based on ANN and Allotting Numbers to Shapes

This paper presents a new method to correctly identify objects based on their 2D shapes. Hitherto, the best method to correctly determine the identity of a particular 2D shape has been using artificial neural networks (ANNs). But ANNs suffer from the drawback that in order to correctly identify a particular 2D shape as a particular object, the ANN has to be extensively trained with images of the object in all possible shapes and sizes and also at various orientations with respect to the observer. It would be so much better if a method can be devised which allots a number to a particular 2D shape of the object as viewed by an observer so that, this way, the shapes of the object as seen from different angles and having various sizes can be represented by a range of consecutive numbers. Now, if the number allotted to a random shape by the method is found to be falling within that range, the shape can be correctly identified as the object. The present paper illustrates such a method to correctly identify shapes. It is shown that the training requirement for the method is minimal. Also, the efficacy of the method is shown by way of various examples.