Reviewerly/exHarmony huggingface dataset:
COVID 19 Conflicts and Emerging Leadership Characteristics: A Qualitative Study

COVID-19 has resulted to global changes that have continued to instigate conflict in the hotel industry. This single exploratory qualitative case study purpose was to examined COVID 19 conflicts and emerging leadership characteristics during COVID 19 period at the Safari Park Hotel and Casino in Kenya. The target population of 20 departmental managers and sections from where a sample of seven participants was purposively drawn. In-depth interviews were conducted with participants from all departments and the data analyzed thematically. The findings revealed that conflicts were evident at individual, departmental, organizational, and externally with stakeholders. Finding further indicated that COVID 19 conflicts revolved around loss of income, employee relations, customer complaints and constrained resources. It was also found that leadership characteristic such as authentic, collaboration, innovation, and perseverance are critical during conflict. Unique contribution to theory, practice and policy is leadership development programs to incorporate conflict management, open and candid communication across the business, business leaders to balance between business needs and staff welfare as well as leaders to be provided with in service support that can complement their competencies in these critical leadership roles.
A Hierarchical Provable Massive Data Migration Method under Multicloud Storage

Now, many users have stored files on multiple clouds, and sometime, a large number of files are migrated between clouds. Because cloud providers and cloud servers are not entirely trusted, the corruption of user’s files event occur from time to time during the processes of storage and migration. Therefore, integrity verification must be performed, and the time verification overhead should be as low as possible. The existing provable data migrate methods still have the issue of high time overhead when a large number of files are migrated. Aiming at this problem, this paper proposed a hierarchical provable data migration method, which can provide the efficiency of data transfer integrity verification when moving large number of continuous files between clouds. In this paper, the proposed method is described in detail as well as the security analysis performance evaluation. The results proved that the proposed method can significantly decrease the detection latency of files transfer between clouds.
Global horizontal irradiation: spatio-temporal variability on a regional scale in the south of the Pampeana region (Argentina)

The objective of this work is to analyze the spatio-temporal distribution of Global Horizontal Irradiation (GHI) on a regional scale and its relationship with frequent synoptic situations in the south of the Pampeana region (Argentina). It was verified that the latitudinal pattern of distribution of the GHI is modified in the region by cloud cover, which is in turn determined by the seasonal dynamics of action centers and the passage of fronts in summer and winter. The South America Monsoon System (SAMS) defines differential situations of cloudiness and rainfall in the region, which affect GHI. GHI increased successively between the decades 1981–2010, a factor associated with the variability of rainfall that characterizes the region.
CNN-Based Modulation Classification for OFDM Signal

Automatic modulation classification (AMC) is one of the important parts in cooperative and noncooperative contexts. This paper approaches the AMC problem by using deep learning. We propose a convolutional neural network (CNN)-based AMC to classify the modulation type of received orthogonal frequency division multiplexing (OFDM) signal and analyze its classification performance. CNN model is trained by using received OFDM signals for different modulation types and signal-to-noise ratios, and then classification accuracy is validated through computer simulations.
Competency Characteristics of Graduates Viewed from User Satisfaction Using Nonhierarchical Clusters

This study aims to classify graduates based on the similarity of competency characteristics by referring to the indicators of graduate user satisfaction. The indicators are implementation of Islamic values; integrity, ethics, and morals; expertise based on knowledge (professionalism); foreign language skills; ability to use ICT; communication; teamwork; and self-development. The survey was aimed at graduates of five study programs totaling 211 people. Determination of respondents using the purposive sampling technique. Data was collected through a questionnaire containing statements about the eight indicators. Data analysis uses descriptive and multivariate statistics with the non-hierarchical cluster method or K-Means cluster analysis, assisted with SPSS (Statistical Package for Social Science) software. The results show that based on the similarity of competency characteristics, graduates are grouped into three clusters, namely Cluster 1 with 13.27% with characteristics of graduates with low competence, Cluster 2 with 32.7% with characteristics of graduates with high competence, and Cluster 3 with 54.03% with the characteristics of graduates with moderate competence. Thus, a strategic program that is systematic, comprehensive, and continuous is needed to develop human resources to shape the quality mentality and competence of students and to be competitive with students and by the needs of the workforce or users. For this reason, it is necessary to develop an e-tracer system that is integrated with the campus web and to strengthen synergistic cooperation with stakeholders, including users.
The Usage of Musical Works in the Internet within the Russian Law: a Comparative Analysis within the Law of US and EU

The article analyzes the "making available" power presented in Russian
Asia Pacific

Its size and complexity, cloud externalization is considered for enhancing security in API. Nonetheless, cloud storage API has two key problems that allows user usability to be effectively functioning and that securely update cipher text in cloud through a new access policy for data owner. This paper recommends an effective secure access update algorithm based on an optimum cryptographic algorithm for API in cloud. Proposed method uses an optimal homomorphic Encryption (OHE) algorithm for secure storage. With Adaptive Salp Swarm Optimizations (ASSO), key values for the OHE algorithm are optimally selected. The proposed project also allows cloud server to efficiently update cipher text and monitor updates against cloud misbehaviors when a new access policy has been mentioned by data owner. It enables data proprietor and skilled users to effectively monitor legitimacy user data access and allow the user to verify that information provided by others is correctly recovered in plaintext. For that, the suggested method utilizes the attribute based access control model. Its analysis reveals how the policy reform program is formulated accurately, completely, safely and efficiently. The performance of the method proposed is measured by differentiating data and the cluster size due to its memory and execution times. Unlike the existing systems with a secure update in the access policies, this approach consumes minimum memory and time. The proposed process is introduced in cloud handset to Hadoop Map Reduction Framework.
Mapping 3D road model to 2D street-view video using Image and Semantic Feature Matching

We propose a novel method to estimate the mapping between the 3D road model and the 2D street-view video. Our results show that our method can perform a high- quality 2D-to-3D mapping on various street-view videos.
Morphological and Numerical Variations in WBC Distribution Pattern during Differential Count Estimation from Buffy Coat Smears

The white layer of nucleated cells that appears between the red sediment layer at the bottom and the plasma at the top after centrifugation of anti-coagulated blood is also called buffy coat.A WBC differential provides information about percentage or absolute value of the different types of white blood cells (Neutrophils, Eosinophils, Basophils, Lymphocytes and Monocytes) and is usually performed in a peripheral blood smear.Differential count can also be performed on buffy coat smears in case of leukopenic patients.The aim of this study is to determine and compare the WBC differential count estimated in smears prepared from peripheral blood and buffy coat from 20 normal healthy individuals.The number of neutrophils and lymphocytes were higher in buffy coat smear compared to peripheral smear.Cells in buffy coat smear showed morphological distortion and clustering in a dirty background with cell debris.The leukocyte distribution and morphological appearance is different in buffy coat smear when compared with traditional peripheral smears.
Clinico-hematological study of leukemias in a hospital-based setup

Background: Leukemia, the malignant proliferation of hematopoietic cells, accounts for a major portion of cancer globally. Types of leukemia are necessary for effective therapy as prognosis, and survival rates are different for each type of leukemia. The objective of the study was to know the relative incidence of leukemia in Silchar Medical College and Hospital, Assam. This study also aims to know the clinical manifestations of leukemia and their hematological correlation.Methods: It was a retrospective study of 60 patients carried out in the Department of Pathology in SMCH, Assam, over a period of 2 years from April 2019 to March 2021. Diagnosis was based on peripheral blood count, peripheral blood smear and bone marrow examination for morphology, along with cytochemistry study whenever required.Results: In this study, acute leukemia was more prevalent than chronic leukemia. The most common form was CML followed by AML, ALL and then CLL. Male predominance was observed in this study with male: female ratio = 1.7:1. Conclusions: In our study, Acute leukemia was more prevalent than chronic leukemia. Leukemia affected male more than female. In this study, the frequency of AML is more than that of ALL but number of cases of CML exceeds that of AML.
Accusation Theory

Accusations play a pivotal role in human communication. There seems be be some changes in the contemporary political situation. However, there is a lack of a philosophical conceptualisation that is necessary for appropriate descriptions of accusations and further philosophical scrutiny. Accustation Theory (AT) is proposed as such a theoretical framework. This paper aims (1) to present some general tools for the description of accusations as speech acts, (2) will try to understand fundamental features of accusations, (3) understand some elements of the practice of accusing, (4) will present a short overview of relevant literature and (5) outline some possible lines of further research.
Community Input Drives Superfund Research

Researchers identified geochemical tracers for lead and investigated Oklahomans’ concerns at the Tar Creek Superfund site.
The Development of a Self-leadership Model for Students’ Creativity at Universities in Yunnan Province, China

In a knowledge-based economy, creativity is important for maintaining a country’s competitiveness. As the main educational institution that provides fresh blood to the nation’s talent pool, universities need to find appropriate ways to nurture creative minds to enhance the nation’s competitiveness. The purpose of this study was to develop a self-leadership model to increase students’ creativity at universities in Yunnan Province, China. The research methodologies used in this study were literature synthesis, descriptive statistics, regression analysis, focus group discussion, and paired-samples t test. Through such a combination of qualitative and quantitative research, this model was developed with students’ self-leadership skills as the key, with activities for creativity, supervisor leadership and organizational structure as supporting factors for creativity development. After a four-week intervention, the model was proven to be effective in enhancing students’ creativity. The researcher recommends that university administrators in Yunnan Province, China, consider using this model as a means of increasing students’ creativity.
Nonlinearity, Multilinearity, Simultaneity

This paper addresses three paradigms in epistemological structures that could serve as preliminary classifications enabling a systematic approach to past and current media phenomena such as hypertext, diagrams and ubiquitous computing. Nonlinearity is discussed by Vilém Flusser in the context of "technical images." In his own approach to go beyond linear text, Flusser and his publisher created a digital version of his book Die Schrift on a floppy disk (1987), enabling the reader to jump between chapters or to rewrite the text. Multilinearity is a concept that is revived within the diagrammatology discourse, transcending linearity through topographical ways of reading. Current examples can be found in arts and narratives such as Chris Ware's comics, who uses diagrammatics to blur the lines between the reader and the author. Simultaneity as a technological attribute is essential to current ubiquitous and pervasive technologies and services and draws heavily on Heideggerian concepts such as readiness-to-hand and background. In this epistemological shift, the information is instantaneously organized according to the user's needs. Each of these epistemological structures offers a different idea about receiving and creating knowledge, information and communication, paving the way for narrative and media strategies that are more and more determined by a 'reader' becoming a 'user' and a 'text' becoming a 'service.' Image Credit: Chris Ware’s Diagram on the interior of the dust-jacket from Jimmy Corrigan, The Smartest Kid on Earth.
Development of methods for generation of digital watermarks resistant to distortion

Active attacks and natural impacts can lead to two types of image-container distortions: noise-like and geometric. There are also image processing operations, e.g. scaling, rotation, truncation, pixel permutation which are much more detrimental to digital watermarks (DWM). While ensuring resistance to removal and geometric attacks is a more or less resolved problem, the provision of resistance to local image changes and partial image deletion is still poorly understood. The methods discussed in this paper are aimed at ensuring resistance to attacks resulting in partial image loss or local changes in the image. This study's objective is to develop methods for generating a distortion-resistant digital watermark using the chaos theory. This will improve the resistance of methods of embedding the digital watermark to a particular class of attacks which in turn will allow developers of DWM embedding methods to focus on ensuring the method resistance to other types of attacks. An experimental study of proposed methods was conducted. Histograms of DWMs have shown that the proposed methods provide for the generation of DWM of a random obscure form. However, the method based on a combination of Arnold’s cat maps and Henon maps has noticeable peaks unlike the method based on shuffling the pixels and their bits only with Arnold’s cat maps. This suggests that the method based only on Arnold’s cat maps is more chaotic. This is also evidenced by the value of the coefficient of correlation between adjacent pixels close to zero (0.0109) for color DWMs and 0.030 for black and white images.
Azure Resource Manager Insights

In this section, we’ll be examining the Azure Resource Manager or “ARM” platform management layer in Microsoft Azure. We’ll talk about what it is, how it works, what you can do with it, and tips and tricks for how to use it effectively in your Azure ARC deployment and other implementation projects in Azure.
Implementasi Metode Algoritma Certainty Factor Dalam Mendiagnosa Gejala Infeksi Bakteri Salmonella

The world of health is growing rapidly as well as many types of diseases that appear over time. Several levels of mutated disease are based on new symptoms found by researchers in their respective fields of expertise, one of which is salmonella bacterial infection. Most patients often do not recognize the symptoms of disease that often arise due to the bacterial infection so that it can aggravate the disease when bacteria have multiplied in the body. Therefore, with the implementation of the certainty factor algorithm method as a solution to diagnose the symptoms of salmonella bacterial infection and to make it easier for doctors to diagnose patients with the use of the system and time efficiency at work. The results of the application of the certainty factor algorithm method based on this study get a percentage of 80% and are included in the feasible category.
Spatial Transformer Network-Based Automatic Modulation Recognition of Blind Signals

Modulation recognition of communication signals plays an important role in both civil and military uses. Neural network-based modulation recognition methods can extract high-level abstract features which can be adopted for classification of modulation types. Compared with traditional recognition methods based on manually defined features, they have the advantage of higher recognition rate. However, in actual modulation recognition scenarios, due to inaccurate estimation of receiving parameters and other reasons, the input signal samples for modulation recognition may have large phase, frequency offsets, and time scale changes. Existing deep learning-based modulation recognition methods have not considered the influences brought by the above issues, thus resulting in a decreased recognition rate. A modulation recognition method based on the spatial transformation network is proposed in this paper. In the proposed network, some prior models for synchronization in communication are introduced, and the priori models are realized through the spatial transformation subnetwork, so as to reduce the influence of phase, frequency offsets, and time scale differences. Experiments on simulated datasets prove that compared with the traditional CNN, ResNet, and the CLDNN, the recognition rate of the proposed method has increased by 8.0%, 5.8%, and 4.6%, respectively, when the signal-to-noise ratio is greater than 0. Moreover, the proposed network is also easier to train. The training time required for convergence has reduced by 4.5% and 80.7% compared to the ResNet and CLDNN, respectively.
A note on the applications of one primary function in deep neural networks

By applying fundamental mathematical knowledge, this paper proves that the function [Formula: see text] is an integer no less than [Formula: see text] has the property that the difference between the function value of middle point of arbitrarily two adjacent equidistant distribution nodes on [Formula: see text] and the mean of function values of these two nodes is a constant depending only on the number of nodes if and only if [Formula: see text] By them, we establish an important result about deep neural networks that the function [Formula: see text] can be interpolated by a deep Rectified Linear Unit (ReLU) network with depth [Formula: see text] on the equidistant distribution nodes in interval [Formula: see text] and the error of approximation is [Formula: see text] Then based on the main result that has just been proven and the Chebyshev orthogonal polynomials, we construct a deep network and give the error estimate of approximation to polynomials and continuous functions, respectively. In addition, this paper constructs one deep network with local sparse connections, shared weights and activation function [Formula: see text] and discusses its density and complexity.
QUALITY OF SATELLITE COMMUNICATION IN SELECTED MOBILE ANDROID SMARTPHONES

Today, thanks to mobile devices, satellite communication is available to anyone and everywhere. Gaining information on one’s position using GNSS (Global Navigation Satellite Systems), particularly in unknown urban environments, had become an everyday activity. With the widespread of mobile devices, particularly smartphones, each person can obtain information considering his or her location anytime and everywhere. This paper is focused on a study, considering the quality of satellite communication in case of selected mobile terminals. It describes a measurement campaign carried out in varying urban environments, including a set of Android-powered smartphones coming from different manufacturers. Based on this, respective conclusions and remarks are given, which can aid consumers as well as device manufacturers and application developers.
Organizing Cybersecurity in Action: A Pragmatic Ethical Reasoning Approach

This paper contributes to the literature on cybersecurity governance by suggesting an approach based on pragmatism. As Jeffrey Sachs in his The Age of Sustainable Development, 2015, reminds us: “The essence of sustainable development in practice is scientifically and morally based problem solving”. Cybersecurity deals with problem solving in complex socio-technical settings where ethics and organizational learning are tightly related. The paper draws on pragmatism because from its earliest formulation, pragmatist thought was anchored to a dual interest in ethics and science. Under this lens, pragmatic ethics cannot exist as a set of rules or principles, but rather requires a cyclical, empirical process whereby ethical principles and context interact to promote justice among stakeholders in the research of reliable solutions during the unravel of critical events. As a result, an Ethically oriented Cybersecurity Approach (ECA) based on Pragmatic Ethical Reasoning (PER) is proposed for managing unexpected critical events when organizations must learn on-the-fly and improve their security profiles.
Low-Rate Speech Coding Using Radial Neural Networks

This article considers methods of low-speed speech coding using neural networks for communication and voice storage applications. It analyzes the use of radial neural networks to solve the problems of low-speed signal coding in multichannel systems of voice information transmission by reducing its dynamic range and increasing the energy efficiency of systems without deteriorating the quality of communication. It describes the construction of a codec model using radial neural networks as a compressor and decompressor for multichannel systems in MatLab and evaluates the codec delay for signal processing depending on the number of channels in the communication system.
A Criminological Study on Trends of Cybercrimes Against Financial Institutions in Sri Lanka

Cybercrimes are virtual crimes that evolved according to nature and the intention of the culprit. Numerous cyber-attacks have been led by several anonymous groups to establish the censorship of information. As the technology used for any activity in the banking industry is continuously upgrading with monetary values as well as with information of clients, it is necessary to have a piece of updated knowledge on both cyber-attacks and technology for both clients and employees of the banking industry. Furthermore, it is crucial to study the nature, techniques and impact of cybercrimes as its techniques are continually evolving with technology. Moreover, it would be possible for individuals to assume that their confidential data and transactions are secured with the bank. This study investigated trends of cybercrimes against Sri Lankan financial institutions using seven Licensed Commercial Banks and uncovered its nature, techniques, impact and strategies that were applied by institutions for the protection of its clients.