Reviewerly/exHarmony huggingface dataset:
What Determines Innovativeness of Micro and Small Enterprises (MSEs) in Ethiopia? Evidence from Debre Berhan Town, Ethiopia

Innovation is considered to be the driving force of competitiveness and growth of firms as well as countries.However, most of MSEs in Ethiopia particularly in Debre Berhan town they were not innovative.Thus, the aim of this article was to identify determinants of innovativeness of MSEs in Debre Berhan town.Data were obtained using questionnaires primarily.The sample consists of 326 MSEs, but the response rate was 90.18%.Both stratified and simple random sampling techniques were employed in the study.Both descriptive statistics and econometric analysis were employed.From descriptive statistics percentage and frequency and chi-square test and from econometric analysis, binary logistics analysis was used.The binary logistics results confirmed that competition in the market (OR=0.035,P<.01) and engagement in research (OR=0.126,P<.001), access to finance (OR=0.190,P<.005) respectively found to be major factors of innovation.However, vocational training and consultancy service did not have statistically significant influence on innovation behaviour.Based on the findings of the study, possible solutions were recommended to the concerned government bodies to enhance innovativeness of MSEs in the study area.
Introduction to the Fifth ENRI International Workshop on ATM/CNS (EIWAC2017)

In this chapter, an overview of the fifth ENRI International Workshop on ATM/CNS (EIWAC2017) is provided, together with summaries of presentations at keynote sessions and special speeches. This chapter also explains the approach of the Electronic Navigation Research Institute toward the organization of EIWAC. In this workshop, various aspects of air traffic management (ATM) and its enablers in the fields of communication, navigation, and surveillance (CNS) were discussed. EIWAC2017 was held in Nakano, Tokyo, from November 14 to 16, 2017.
Tansy: Extensible, Concurrent Communication

The cryptoanalysis approach to the partition table is defined not only by the understanding of infor-mation retrieval systems, but also by the intuitive need for the Ethernet. In fact, few cyberinformati-cians would disagree with the evaluation of hash ta-bles [13]. Here, we use stable configurations to val-idate that semaphores and Lamport clocks can col-lude to surmount this grand challenge
Evolutionary computer vision

tutorial Evolutionary computer vision Share on Author: Dr. Gustavo Olague CICESE CICESEView Profile Authors Info & Claims GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference CompanionJuly 2020 Pages 1101–1113https://doi.org/10.1145/3377929.3389861Online:08 July 2020Publication History 0citation97DownloadsMetricsTotal Citations0Total Downloads97Last 12 Months47Last 6 weeks5 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Identification of Least Risk Path using GA-SVM for the Software Project Management

Risk management is an important part of the development cycles for high quality applications. Most specific threats are incidents that may adversely affect the plan or organizational climate growth. The major risk factors contains time, budget and resources can affect adversely by events. Important considerations such as plan, time and cost are generally impacted. Essentially, risk assessment includes recognizing, assessing, preparing and monitoring incidents that affect the atmosphere of the project. Risk is the danger of volatility, lack of knowledge regarding events, activities and lack of appropriate technologies for managing measures and activities. Therefore, both exogenous and endogenous influences contribute in the venture risks and uncertainties. The high task failure rates due to poor planning of project which can limit the teams and future wealth creation, while project managers should allow for the plan being to anticipate potential risks when preparing their project achievements based on their own past experiences. This paper addresses the Supervised Learning mechanism with multi-label Support Vector Classifier (SVC) to predict the project risks and apply Genetic algorithm for providing avoidance action as recommendation.
Introduzione

This paper is an introduction to the volume, that collects the contributions presented at the 2019 annual Conference of the Associazione Italiana per la Terminologia (Ass.I.Term), hosted at the Accademia della Crusca. This paper aims to present the importance of the reflection that touches the comparison between terminology and lexicography, through which technology and science can show their positive function for the development and growth of the Italian language, helping it to keep up with the times, in an era in which most of the specialized words, in various disciplines, now come only from English.
MEMS Design Techniques and Performance Estimation in Connected Cars

In order to design the complex structure, devices , systems of electronic products under the level micrometers the micro-electromechanical and micromachining system (MEMS) are mostly preferred. Micro machining techniques are initially lent directly from electronic integrated circuit (IC) industry. But now there were many techniques proposed with wide variety of transduction directly. Ample variety of MEMS transduction process can be used to convert real-world signal from one to another form. The process of conversion can be can be enabled by combining different sensors, actuators and Microsystems. Due to the process of partial consistency and a growing technology, the complex designs of sophisticated MEMS are produced. The combination of integrated circuits with MEMS can improve performance, but at the rate of development cost, complexity and time. With the fact &amp; fast development and growth in the area of automotive electronics, IoT, cloud computing, artificial intelligence and machine learning technologies prompted us to have higher potential market to make the successful products which can impact the social and economic growth. In addition to this, MEMS are well appropriate for automation, medical electronics, and agriculture and space exploration. Thus will play an important and major role in future mission both in private and public sectors. The major problem in India and other developing countries are safety and security. This paper describes the optimal solution &amp; design methodology to control the user end application using MEMS senso., where the controlling of the machineries can be done by MEMS sensor to control communicate via wireless communication
A SENSOR-LITE ANXIETY DETECTOR FOR FOREIGN LANGUAGE LEARNING

Foreign language learners face cognitive and emotional interference which reduces their learning acquisition.Foreign language anxiety (FLA) is one of the impediments to learning a new language.It hinders cognitive processes, interferes with attention, and reduces working memory capacity.Detecting foreign language anxiety is the first step toward reducing and eventually overcoming it.Here we present a novel design to detect foreign language anxiety in the context of an e-learning system using sensor-free and sensor-lite metrics.By adopting the Foreign Language Classroom Anxiety Scale (FLCAS) as a pre-test along with language difficulty self-report, system difficulty self-report, and score, we are predicting the current anxiety level of the learner when learning English as a second language using an e-learning system.We found that some components of the FLCAS can effectively predict FLA for listening and speaking exercises.Additionally, FLCAS plus the self-reports and the score are effective in detecting the learner's current anxiety level for all exercise types.
From PINNs to DeepOnets: Approximating functions, functionals, and operators using deep neural networks

We will present a new approach to develop a data-driven, learning-based framework for predicting outcomes of physical and biological systems, governed by PDEs, and for discovering hidden physics from noisy data. We will introduce a deep learning approach based on neural networks (NNs) and generative adversarial networks (GANs). We also introduce new NNs that learn functionals and nonlinear operators from functions and corresponding responses for system identification. Unlike other approaches that rely on big data, here we "learn" from small data by exploiting the information provided by the physical conservation laws, which are used to obtain informative priors or regularize the neural networks. We will also make connections between Gauss Process Regression and NNs and discuss the new powerful concept of meta-learning. We will demonstrate the power of PINNs for several inverse problems in fluid mechanics, solid mechanics and biomedicine including wake flows, shock tube problems, material characterization, brain aneurysms, etc, where traditional methods fail due to lack of boundary and initial conditions or material properties.
OOFFMM: A Size Estimation Model for Real Time Application

A lot of Size Estimation technique has been previously proposed for estimation of the effort of object oriented software projects. After reviewing several object oriented metrics we found that FFP is most excellent right metrics for real occasion application. We took FFP metric for estimating the size. There control functions will helps to calculate those complex, scientific or real time process that were not easily estimated by FP or any other metrics. This research job mostly focus on formative the functional_size of Real-time application at early stage. We define the rules to identify logical files from UML diagrams on different models of OMT. This proposed model is completely base on OOD Methodology owing to the version of the Function_Point Analysis to Object_Point Analysis .We also presented the result obtained by applying the model in a Case study. The result has proven that discovered OOFFA metric and Effort estimation model (OOFFMM) is the best model and metric suite for object oriented MIS applications as well as real time applications.
Design Technologies for Wheeled and Tracked Vehicles

The conference “Design Technologies for Wheeled and Tracked Vehicles” is held annually at Bauman Moscow State Technical University. The conference is organized by the Department of “Wheeled vehicles” and the Department of “multi-purpose tracked vehicles and mobile robots”. Every year, representatives of various scientific, educational and industrial organizations in Russia and other countries come to us with reports and speeches. The main topics of the reports are issues related to the design of wheeled and tracked vehicles. We are glad to see scientists from all countries and organizations in the field of education, science and industry at our conference. Sincerely, A. Protopopov
A Structural Model for Leadership and Employee Satisfaction in UAE Public Sector

In today's work environment, employees constitute an important resource for organizations and a key determinant of corporate success, with employees' creativity, motivation and energy driving company performance. It is critical, therefore, to harness these employee potentials for the pursuit of company goals. Effective leadership has been suggested to constitute one of the most relevant success factors in this respect. This paper aimed to investigate the impact of leadership on employee satisfaction in UAE public sector. Quantitative research was employed and SPSS and AMOS software were employed to analyze the collected data in this paper.
Designing and Implementation of Rating Prediction

Recommender system is one of indivisible parts in web business areas. Recommender system construes the system which underwrites things for the client who wish to purchase things .One of the real inconveniences that, figuratively speaking, stays in recommender system is the virus begin problem(inactive things) which can be seen as an obstruction that spurns the cool begin things from the present things. In this paper, we want to move beyond this farthest point for cold-begin clients/things by the help of existing things. It is developed by utilizing Elo Rating system. The Elo system is widely gotten in chess competitions; we propose a novel rating association technique to get settled with the profiles of cold-begin things. The purpose of assembly of our Strategy is to give a fine-grained View on the shrouded profiles of cold-begin clients/things by inspecting the separations between nippy begin things and existing Products. To uncover the limit of methodology, we instantiate our technique on two typical strategies in recommender systems, i.e., the structure factorization based, and neighborhood based pleasing sifting. Starter assessments on five genuine instructive documents embrace the amazing quality of our methodology over the present procedures in virus begin situation.
Seismic Soundoff

The following is an excerpt from SEG's podcast, Seismic Soundoff. On this episode, Heloise Lynn discusses Leon Thomsen's famous deck of cards, the controversy surrounding her recently published paper, how anisotropy can be understood by all geophysicists, what would happen if azimuthal P-P seismic measurements reached their full potential, and more. Listen to the full episode at https://seg.org/podcast/post/7481 .
Modal Algebras

Semantical study of modal logics have been developed successfully already by using Kripke semantics. In the present chapter, we will discuss an algebraic approach to modal logics. Since our algebraic approach has many parallels with what we explained already in the previous chapters of Part II, it will be explained rather briefly. After introducing modal algebras, we present Jónsson-Tarski theorem which is an extension of Stone’s representation theorem to modal algebras. Jónsson-Tarski theorem will explain how Kripke semantics can be viewed from algebraic point of view, and hence clarify a link between algebraic semantics and Kripke semantics. In the last section, we will give an algebraic proof of the Gödel translation of superintuitionistic logics into modal logics over $${\mathbf{S4}}$$ .
Research on Plant Growth Environment Control System Based on BP Neural Network

As an advanced stage of modern facility agriculture development, plant factory is an efficient agricultural production system that realizes optimal plant growth by regulating plant growth environment.It mainly complies the automatic control of environmental factors such as temperature, humidity, illuminance and CO 2 concentration during plant growth.With the application of neural network in nonlinear and strong coupling control systems, this paper establishes a plant growth environment control system based on LabVIEW.Depend on this platform, we study and establish an environmental state model based on BP neural network, and achieve precise plant growth environment control.The experimental result proves that the system runs stably and reliably and meets the design requirements.
Engaging Learners: Differential Equations in Today's World (full issue)

Today's world is global.However, despite increasing numbers and diversity of participants in Study Abroad programs, only 10% of U. S. college students get that experience.There is an ever-growing need for students to become aware of and experience other cultures, to understand why others think and act differently.Internationalization is the conscious effort, begun nearly 40 years ago, to integrate an international, intercultural, and global dimension into the purpose, functions, and delivery of post-secondary education.Albany State University began a Global Program Initiative in the 1990s.In 2016, we extended into mathematics the curriculum innovations of this program.The result has engaged students in a serious way, both in mathematical modeling and in cultural research.We have introduced students to new skills of research and presentation.For the past few years we have offered one section of Calculus II in traditional mode and one in internationalized mode, and we have compared results.In this article, we give details of the process and highlight the success of the program.We end with more recent examples from Spring 2020.
Biometric Authentication in Cloud Environment based on Statistical Modeling

With the advancements in the area of science and technology, the usage of multimedia applications have raised enormously. This raise in data has led towards different issues such as storage and confidentiality. Lot of devices and techniques has been embarked to compact the data so as to safeguard the information. Recently, cloud computing is considered to be one of the notable innovations having advantages with respect to reduction in cost, increase in throughput and flexibility in usage. However there are certain security hinges that are associated with this regard. The literature reviewed showcased several techniques coined towards the safeguard of data in cloud environment. In this article, a novel biometric authentication system is developed for the ease of computing and distributing the data without any security issues.
Software brings design benefits

When designer and manufacturer of magnets and associated technology Eclipse Magnetics was looking to improve its design and production capabilities it chose computer aided engineering software from EPLAN. Here we look briefly at the suite of software solutions chosen.
ЦЕННОСТНЫЕ ОРИЕНТАЦИИ СТУДЕНЧЕСКОЙ МОЛОДЁЖИ КАК ФАКТОР ПСИХОЛОГИЧЕСКОЙ БЕЗОПАСНОСТИ В УСЛОВИЯХ ИНФОРМАЦИОННОЙ СРЕДЫ

Introduction. The paper addresses the influence of modern mass media on the young audience and analyzes the main negative consequences of this influence. The research aims to examine the value orientations of student youth as a factor of psychological security in the information environment. Materials and methods. The empirical research applied quantitative and qualitative methods. The methods employed in the study are questionnaire-based survey, Schwartz Value Survey, and Sacks Sentence Completion Test. Statistical processing of the data obtained relied on the Fisher’s Angular Transform – the φ * criterion. Research results. The research identified two main types of motivation for the use of the media by students. The respondents were divided into two groups based on the predominance of one motivation type or another. The value orientations of representatives of two groups were studied. A definite difference was revealed in strategies for overcoming psychological discomfort in respondents with different motivations for using the media and different value orientations. Conclusion. The data obtained in this research allow studying value orientations as a factor of informational and psychological security of a person.
Image Steganography using Improved Lsb-Mapping Technique with Enhanced Recovery Speed

In recent days, for sending secret messages, we require secure internet. Image steganography is considered as the eminent tool for data hiding which provides better security for the data transmitted over internet. In the proposed work, the payload data is embedded using improved LSB-mapping technique. In this approach, two bits from each pixel of carrier image are considered for mapping and addition. Two bits of payload data can be embedded in one cover image pixel hence enhanced the hiding capacity. A logical function on addition is applied on 1st and 2nd bits of cover image pixel, and a mapping table is constructed which gives solution for data hiding and extraction. Simple addition function on stego pixel is performed to extract payload data hence increases the recovery speed. Here the secret data is not directly embedded but instead mapped and added with a number using modulo-4 strategy. Hence the payload data hidden using proposed approach provide more security and it can resist against regular LSB decoding approaches. The proposed work is implemented and tested for several gray scale as well as color images and compared with respect to parameters like peak signal to noise ratio and MSE. The proposed technique gives better results when compared and histogram of cover and stego images are also compared.
Applying Library Values to Emerging Technology: Decision-Making in the Age of Open Access, Maker Spaces, and the Ever-Changing Library

"Applying Library Values to Emerging Technology: Decision-Making in the Age of Open Access, Maker Spaces, and the Ever-Changing Library." Journal of Web Librarianship, 13(1), pp. 88–89
Measuring source code conciseness across programming languages using compression

Welcome to the 21st IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2021)! We hope that you enjoy the conference and that it will inspire you in your future research. Should you require a certificate of participation please contact Alexander Serebrenik, the general chair of SCAM, at a.serebrenik@tue.nl. For questions related to the Morressier virtual platform please contact support@morressier.com.
Preface

This special issue of Journal of Physics: Conference Series contains the Proceedings of the 2 nd International Conference on Recent Advancements in Science and Technology (ICoRAST2019). The conference was held in Putrajaya, Malaysia from 28-30 October 2019. This conference is the biennial event organized by Faculty of Science and Technology, Universiti Sains Islam Malaysia (USIM). Previous meetings were held in Melaka, Malaysia in 2017. The aim of the conference is to bring together a variety of new developments and challenges in the field of science and technology. Its primary mission is to meet the country’s needs through the sharing of technology and dissemination of knowledge through strong relationships with industry researchers, scientists and academics. It aims to bring together leading academics, scientists, researchers, scholars and students to exchange and share knowledge, experience and research on aspects of progress in various disciplines of science and technology of the latest and advanced. The conference had been attended by almost 50 participants from various countries. Out of them, 15 papers were selected to be published as the proceedings. This meeting provided a very useful forum for the exchange of ideas and results among scientist with various applied sciences backgrounds. This conference also provides an opportunity for the establishment of new networks and discuss the practical challenges encountered and the various solutions adopted to date in their fields worldwide. The organizers of the conference are very grateful to the university and faculty for the substantial help received and for sponsoring the conference. Finally, it is a pleasure to acknowledge the work of committee members and colleagues, who helped to run the conference smoothly. Editor
Correlation Based Low Complex Video Frame Interpolation

Frame Interpolation is one of the main stages in video processing. Video coding standards skip some in-between frames for efficient compression and coding. At decoder the common approach to reconstruct the skipped frame using Motion Compensated Frame Interpolation (MCFI)methods. In MCFI, computational complexity is very high as calculation of Block Matching Algorithm, Motion Vectors (MV), Motion Estimation(ME) and Prediction logic of objects in motion between the frames, increases the complexity in MCFI method. A more feasible approach with minimum computational complexity using block level correlation is proposed in this paper. Errored MV at the decoder results in holes, occlusions, blurring and edge deformations in the interpolated frame. This proposal minimizes afore mentioned effects along with minimum complexity. The results are simulated in terms of peak-signal-to-noise-ratio (PSNR) and structural similarity index (SSIM).