Reviewerly/exHarmony huggingface dataset:
Influence of Product Diversification on Financial Performance of Commercial Banks Involved in Mergers and Acquisitions from the Year 2010 in Kenya

With the fast-changing business environment and increasing significance of long-term financial viability, an increasing number of firms today have diversified their business into new product segments or global markets to gain a competitive advantage over rival firms.The strategic importance and financial implications of corporate diversification have been widely studied in the strategic management literature.As a firm-level strategy, corporate diversification is expected to exert a universal influence on many aspects of operations (Qian, 2018).Diversification is the entry of a corporation into new lines of action through a process of internal development or through acquiring, which entails changes in its system, administrative structure or other management procedures (Sissy, 2015).As a corporate strategy, diversification has been a vital growth tool for corporations.Furthermore, strategic management research acknowledges diversification effects on firm performance as one of the primary topics.Diversification seeks to increase profitability through higher sales volume obtained from new products and new markets.It involves venturing out into a new business, new products, or new markets to increase profits.It is a form of growth strategy involving a significant increase in the performance objectives beyond past performance records (Andreas, 2009) as cited by Alengo et al, (2019).Product diversification refers to the expanding strategy into new product markets.From the Resource-Based View (RBV) point, product diversification provides a firm with an opportunity to deploy its core resources and competencies in new areas.Additionally, by expanding into new product segments, a firm may be able to develop new resources and capabilities, which can facilitate subsequent expansion.Other researchers propose that poor prospects in extant markets also stimulate a firm to exploit growth potential in a new market.The potential benefits from product diversification have
ARTEMIS: parsing non-peripheral complex sentences in ASD-STE100

The simulation of natural language understanding is one of the main objectives of natural language processing (NLP). Within the different applications designed for this purpose, the ARTEMIS prototype follows the paradigm of unification grammars, and unlike other trending computational resources, it is theoretically grounded in Role and Reference Grammar (RRG). The syntax-to-semantics linking algorithm proposed in this functional grammar lies at the basis of a parsing process that starts with a natural language sentence, extracts its morphosyntactic features and provides a representation of these in terms of the so-called layered structure of the clause (LSC). The Grammar Development Environment (GDE) in ARTEMIS is a major component where feature- based production rules (syntactic, lexical and constructional) are stored and ready to allow the generation of the enhanced layered structure of the clause of natural language expressions. Syntactic rules that account for phrasal constituents and simple sentences have already been described, but it is now turn to focus on the study of non-peripheral complex sentences. In an attempt to validate these syntactic rules and to avoid some of the common problems that may arise in parsing applications, our research will concentrate on the analysis of RRG’s juncture-nexus combinations as found in a controlled natural language (CNL) such as ASD-STE100 (Aerospace and Defence Simplified Technical English).
Exploration of the Teaching System of Basic Education in the Era of Artificial Intelligence

Artificial intelligence technology is a strategic technology produced by the information age. It is the key technology to lead scientific and technological innovation, promote industrial transformation and accelerate economic development. The development and application of artificial intelligence has provided a good opportunity and technical support for the reform and innovation of basic education in China. In this context, it is necessary to accelerate the reform of basic education curriculum teaching system and adapt to the development of the era of artificial intelligence. This paper briefly introduces artificial intelligence, points out its role in promoting basic education curriculum teaching in China, and discusses the reform of basic education curriculum teaching system from different perspectives, which has guiding and reference significance.
Analysis of the visual aid effectiveness in engineering education

The article is devoted to the analysis of the effectiveness of the use of modern electronic visual aids (Trello virtual whiteboard, Core platform, Mind Maps, interactive books) in the engineering training of future specialists. The growth of digitalization and the abundance of information in all areas of life, including education, offer teachers and students to solve most educational problems using digital technologies and visual aids. The quality of the educational information received and processed by students, as well as the insufficient development of the use of relevant electronic visual means at the present stage of the development of the educational system makes our research relevant. The empirical basis of the study was the teaching of one of the disciplines of the Master's program of engineering training of the National Research University "MEI" of the Department of Philosophy, Political Science, Sociology named after G.S. Arefieva. In the 2020/21 and 2021/22 academic years, a pedagogical experiment was conducted as part of teaching the second-year masters of the discipline "Organizational Behavior": part of the groups studied traditionally, the other part — with the use of new educational resources. During the study, visual learning aids (Mind Maps and interactive books), the peculiarities of information perception, including educational ones, were examined in detail, the domestic and foreign experience of using visual aids in teaching humanities disciplines was studied, the effectiveness of using several modern aids and services in engineering education at a technical university was tested. The article describes the features of the experiment, presents its results and analysis, and formulates recommendations for the effective use of modern visual aids for university training.
IMPLEMENTATION OF WEBSITE PERFORMANCE EVALUATION WITH SIMILARWEB ON ACADEMIC WEBSITES

Trunojoyo University Madura is a state university in Indonesia. The Trunojoyo Madura University website is used for information delivery media. The website can be accessed by anyone and used to make announcements for both students and outsiders. Based on this, the desired website quality must have high performance, usability, mobile friendliness, accessibility, SEO (Search Engine Optimization), connected to social media, and safe. This study was conducted to determine the level of usability through evaluating the performance of the academic website of Trunojoyo Madura University. Therefore, this study evaluates the performance of the website by using an automatic evaluation tool, namely SimilarWeb. This tool checks the level of popularity of a website both in terms of ranking and the number of visitors who access the website. In addition, measurements from the usability side were taken to determine the usability of the website obtained from the responses of students and visitors who have accessed the website. The results showed that by using SimilarWeb website traffic was obtained at a good level. Usability measurement has been carried out, as many as 58 respondents have answered 15 questions.
HOMOMORPHIC ENCRYPTION IN 5IRE BLOCKCHAIN

With the advent of blockchain technology, decentralized system is gaining huge popularity as it provides a new solution for data storage and sharing as well as keeping privacy in place. Blockchains are of two categories; public and private. Public blockchains are permissionless, mostly used for exchanging and mining cryptocurrency, where anyone can join and thus exposed to the risk of a privacy breach. If the content is the transaction information, one might opt for not sharing these data in the public domain. One solution could be to encrypt the information, but that comes at the cost of losing the usability of the data. This paper investigates the security problem related to this passive adversarial activity and proposes a new technology that leverages the best parallel chain architecture of 5ire blockchain and homomorphic encryption (HE) so as to retain the advantages of a public blockchain without compromising the privacy of transaction information. We have coined the term 5ireHE for this encryption architecture. We achieve the security protection and integrity check of wallet data by enforcing the 5ireHE which is efficient.
The influences of Interest rate volatility on banking sector development: Evidence from cross countries in the MENA region

This study investigates the dynamic relationship between a set of banking sector development indicators and interest rate volatility for 12 emerging market countries during the period of 1980-2019. For this purpose, the bounds testing within autoregressive distributed lag (ARDL) methodology is employed. The empirical results reveal that the interest rate volatility has negative impacts on the majority of the banking sector development indicators which also play a significant role in dampening the banking sector development path in the long-run. These findings suggest that the banking sectors of emerging countries are vulnerable to interest rate risks. Thus, the results have important implications for policymakers to improve the banking system and to promote economic growth of emerging economies.
Empirical Perspectives on One-Shot Semi-supervised Learning

One of the greatest obstacles in the adoption of deep neural networks for new applications is that training the network typically requires a large number of manually labeled training samples. We empirically investigate the scenario where one has access to large amounts of unlabeled data but require labeling only a single prototypical sample per class in order to train a deep network (i.e., one-shot semi-supervised learning). Specifically, we investigate the recent results reported in FixMatch for one-shot semi-supervised learning to understand the factors that affect and impede high accuracies and reliability for one-shot semi-supervised learning of Cifar-10. For example, we discover that one barrier to one-shot semi-supervised learning for high-performance image classification is the unevenness of class accuracy during the training. These results point to solutions that might enable more widespread adoption of one-shot semi-supervised training methods for new applications.
Logic of fusion

The starting point of this work is the observation that the Curry-Howard isomorphism, relating types and propositions, programs and proofs, composition and cut, extends to the correspondence of program fusion and cut elimination. This simple idea suggests logical interpretations of some of the basic methods of generic and transformational programming. In the present paper, we provide a logical analysis of the general form of build fusion, also known as deforestation, over the inductive and the coinductive datatypes, regular or nested. The analysis is based on a novel logical interpretation of parametricity in terms of the paranatural transformations, introduced in the paper.
(Im)possible Traces

In this article, I argue that when movement maps onto a λ-bound variable (a “trace”), that variable must be of an individual semantic type, such as type e or type d. Thus, even though natural language has expressions of higher types, these expressions cannot be represented as traces. When an individual-type trace would not be able to semantically compose in the launching site of movement, the moved element is forced to syntactically reconstruct. The motivation for this constraint on traces comes from a detailed investigation of how DPs in their different semantic guises—entities, properties, and generalized quantifiers—are interpreted when they move. I then argue that strong definite descriptions exhibit the same type-based restriction—namely, they cannot occur in higher-type positions, which I take as evidence for the theory that traces are definite descriptions.
Fast Bayesian Uncertainty Estimation and Reduction of Batch Normalized Single Image Super-Resolution Network

Convolutional neural network (CNN) has achieved unprecedented success in image super-resolution tasks in recent years. However, the network's performance depends on the distribution of the training sets and degrades on out-of-distribution samples. This paper adopts a Bayesian approach for estimating uncertainty associated with output and applies it in a deep image super-resolution model to address the concern mentioned above. We use the uncertainty estimation technique using the batch-normalization layer, where stochasticity of the batch mean and variance generate Monte-Carlo (MC) samples. The MC samples, which are nothing but different super-resolved images using different stochastic parameters, reconstruct the image, and provide a confidence or uncertainty map of the reconstruction. We propose a faster approach for MC sample generation, and it allows the variable image size during testing. Therefore, it will be useful for image reconstruction domain. Our experimental findings show that this uncertainty map strongly relates to the quality of reconstruction generated by the deep CNN model and explains its limitation. Furthermore, this paper proposes an approach to reduce the model's uncertainty for an input image, and it helps to defend the adversarial attacks on the image super-resolution model. The proposed uncertainty reduction technique also improves the performance of the model for out-of-distribution test images. To the best of our knowledge, we are the first to propose an adversarial defense mechanism in any image reconstruction domain.
Home Automation through Hand Gestures Using ResNet50 and 3D-CNN

This paper talks about using hand movements for the operations of electrical equipment at home. With the use of the much-advanced algorithms - 3D-CNN and ResNet50 to increase the accuracy in detecting the hand gesture to correctly predict the right motion for the functioning of the electrical device. Eventually, the project focuses on the comparative study between different architectures so that we can determine the best-suited model for these kinds of image detection. We aim to bring about a good accurate model for detecting the hand signals.
Digital Preservation and Presentation of Institution Photo Archives: the Anhui University Memory Project Experience

Institution photo archives are important digital resource with a large proportion of old photos, which makes them of great value in aspects of history and culture. Based on OAIS (Open Archival Information System) Model, the Anhui University Memory Project (AMP) designed and realized a Long-term Preservation Process, which included a series of standard procedures for lifecycle management. Then digital resource repository and digital memory site were developed according to demands of Anhui University for constructing and presenting memory. This paper aims to introduce the architecture and achievements of AMP, as well as the design and implementation of long-term preservation process and two distinctive ways of resource organization and memory presentation.
Automatic Identification of Domain Terms: An Approach for Italian

The problem of creating a fully automated specific-domain thesaurus is very topical. The paper presents a novel method to address this problem in the Italian language. The main feature of this approach is the integration of different methods: machine learning classification methods working on the semantic representation of candidate terms, word embeddings models, able to capture the semantics of words, and a computation of the degree of specialization of a term. The work is in progress and results obtained so far are promising.
Game Environment and Design Thinking Approach for New Digital Careers

To compete with today’s rapidly changing labour market one has to continuously self-adapt towards new attitudes and mindset. To assist such an endeavor the combination of entrepreneurship and STEM (Science, Technology, Engineering and Mathematics) skills is considered favorable. Following these basic premises, the paper presents a European project, TEAM_STAR, focused on developing a 3D game environment to promote these new skills in secondary school students for new digital careers.
An Approach to Developing Internet of Things (IoT) － Based Services for Smart Museums

The aim of each museum is to present its exhibits in a way that enhances the visitor experience, satisfaction and knowledge. This objective is difficult to achieve, especially in museums with a very large number of exhibits and visitors. One possible solution is to use the modern Internet and mobile technologies in order to implement a service for personalized information delivery. The content that is delivered to visitors should be consistent with their preferences and free time. The paper presents an Internet of Things (IoT) － based solution for delivering personalized content to museum visitors, which includes: (1) Mobile app for visitors and curators; (2) Sensor network; and (3) Edge Computing Gateway. The main advantages of this solution are the following: platform independent service thanks to its full-stack JavaScript architecture; the service allows visitors to use it in multiple museums, not just in a particular museum; the service does not require permanent Internet access to operate; ability to deliver personalized content during the movement of visitors along the exhibits; relatively low price of the service thanks to the used hardware and open source software. Preliminary experiments in simulated and real environments show that proposed solution can be successfully used to create personalized content delivery services in smart museums.
Using Conditional Probability for Discovering Semantic Relationships between Named Entities in Cultural Heritage Data

This paper introduces a method for extracting information from various cultural heritage data sources using word embedding with feature extraction from the sentence and structured representation of the sentence. The focus is on discovering the named entities’ relations including part of speech tags and positons tags by the means of conditional probability.
Java Prolog Interface

There are many initiatives in presents-days for interaction between Java and Prolog programming languages. These initiatives allow combine two programming paradigms, Object Oriented Programming and Logic Programming. Every proposed interface has specifics features depending of the final use. The present paper introduces a new Java Prolog Interface to be use for Prolog persistence interacting from Java side and functional programming from Prolog side. To support this interaction, the most advanced solutions implements interlanguages data type mappings between Java objects and Prolog terms. Java Prolog Interface is a modern solution that take the best features from existing solutions and combine all in one. It' s more flexible, adaptive and have an Application Provider Interface (API) easy to use. JPI implement the javax.script interface include in Java from version 1.6. The project like existing solutions have an implementation for the most popular open source Prolog Engines. Is hosted on GitHub source code management at Prolobjectlink repository and deploy the resulting artifacts on Maven Central repository. The project have a web page too hosted on GitHub.
Emotional value technology of foreign-language education for the development of speech communication abilities

The problem for the research. The focus of civilization on the priority of humanistic values implies a change in the way of thinking and actions of modern man. This requires from an individual new skills and value orientations. Not without reason, today in the methodology of teaching foreign languages, much attention is paid to the involvement of the emotional value component in the process of foreign-language education. The search for the means to implement it forced us to turn to the emotional value technology. The purpose of the research is to characterize the emotional value technology of foreign-language education and prove its effectiveness at the stage of development of foreign-language speech abilities. Methods of investigation. The experiment involved 64 students of the 5th and 6th grades of schools in Kirov. To obtain the data, the following methods were used: of calculating the success rate, based on the criteria and levels of evaluation the results of mastering by secondary school students the content of foreign-language education in combination of “intellectual” and emotional value components; of mathematical statistics (standard deviation, F-criterion). The findings of the study. The results of the final check displayed that the level of mastering the components of foreign-language education (“intellectual” components + the emotional value component) increased in 88% of students; it did not change in 12%. Differences are explained not by random factors, but by experimental training (F = 2,47; p &lt; 0,05). These data prove the effectiveness of the emotional value technology at the stage of development of students’ foreign-language speech abilities. Conclusions. In the process of adapting the model of the emotional value technology of foreign-language education, it turned out to be capable to function in the conditions of the development of speech communication abilities. The result was a contribution to the formation of the student’s linguacultural personality. This personality is characterised by foreign-language speech abilities in listening, speaking, reading, written speech, emotional and sensory recognition of cultural values and inner comprehension of their meaning.
The Effect of Layer Batch Normalization and Droupout of CNN model Performance on Facial Expression Classification

One of the implementations of face recognition is facial expression recognition in which a machine can recognize facial expression patterns from the observed data. This study used two models of convolutional neural network, model A and model B. The first model A was without batch normalization and dropout layers, while the second model B used batch normalization and dropout layers. It used an arrangement of 4 layer models with activation of ReLU and Softmax layers as well as 2 fully connected layers for 5 different classes of facial expressions of angry, happy, normal, sad, and shock faces. Research Metodology are 1). Data Analysis, 2). Preprocessing grayscaling, 3). Convolutional Neural Network (CNN), 4). Model validation Testing, Obtained an accuracy of 64.8% for training data and accuracy of 63.3% for validation data. The use of dropout layers and batch normalization could maintain the stability of both training data and validation data so that there was no overfitting. By dividing the batch size on the training data into 50% with 200 iterations, aiming to make the load on each training model lighter, by using the learning rate to be 0.001 which works to improve the weight value, thus making the training model work to be fast without crossing the minimum error limit. Accuracy results in the classification of ekp facial receipts from the distance of the camera to the face object about 30 cm in the room with the use of bright enough lighting by 78%.