Reviewerly/exHarmony huggingface dataset:
Mozambique Islamic State Claims First Presence

Africa Research Bulletin: Political, Social and Cultural SeriesVolume 56, Issue 6 p. 22338C-22338C National Security Mozambique Islamic State Claims First Presence First published: 14 July 2019 https://doi.org/10.1111/j.1467-825X.2019.08939.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume56, Issue6July 2019Pages 22338C-22338C RelatedInformation
When the Bad Is Good and the Good Is Bad: Understanding Cyber Social Health Through Online Behavioral Change

Following the Special Issue on Cyber Social Health: Part 1 in the January/February 2021 issue, in this issue, we highlight another five papers that were accepted based on the quality of the analysis, results, and presentation. In “Towards Hate Speech Detection at Large via Deep Generative Modeling,” the authors developed an approach to improve supervised hate speech detection on social media by creating a large dataset of hate speech from a small seed set. They introduced a big ground truth dataset and assessed the generalizability of models to the variability in communications with hate speech. This work attempts to overcome the lack of diversity and improve coverage in the input dataset, and the data imbalance. The authors employ GPT-2 fine-tuned on the existing labeled datasets, to generate a larger diverse hate speech dataset. They also perform a comparative analysis on the inductive biases of DL methods during training on individual hate-speech datasets.
Efficient variant transaction injection protocols and adaptive policy optimisation for decentralised ledger systems

For decentralised cryptocurrency systems, it is important to provide users an efficient network. One performance bottleneck is the latency issue. To address this issue, we provide four protocols to utilise the resources based on the traffic in the network to alleviate the latency in the network. To facilitate the verification process, we discuss three variant injection protocols: Periodic Injection of Transaction via Evaluation Corridor (PITEC), Probabilistic Injection of Transactions (PIT) and Adaptive Semi-synchronous Transaction Inject (ASTI). The injection protocols are variants based on the given assumptions of the network. The goal is to provide dynamic injection of unverified transactions to enhance the performance of the network. The Adaptive Policy Optimisation (APO) protocols aim at optimising a cryptocurrency system's own house policy. The house policy optimisation is translated into a 0/1 knapsack problem. The APO protocol is a fully polynomial time approximation scheme for the decentralised ledger system.
An Empirical Investigation of the Perceived Benefits of Agile Methodologies Using an Innovation-Theoretical model

There is little doubt that agile software development (ASD) methods have gained widespread acceptance in industry. Despite the attention these methods have received, there is little empirical affirmation of the benefits that accrue to those who use agile methodologies. Grounded in the conceptual foundations of innovation diffusion and agile philosophy of development, the authors' study validates a model to assess the perceived advantage of an iterative approach to software development. Consistent with their predictions, the results suggest that evolutionary development - the cornerstone of agile development – is perceived to be less complex and more compatible with the work habits of developers. Further, the findings support the hitherto unsubstantiated claim that iterative development yields benefits to software developers. However, process flexibility, yet another important characteristic of agile development, had no significant impact on complexity, compatibility, and relative advantage. The implications of the study for academics and practitioners, and directions for future research are discussed.
FY2020 Small Business Innovation Research Phase II (DOC)

Federal Grants & ContractsVolume 44, Issue 18 p. 6-6 Grants Alerts FY2020 Small Business Innovation Research Phase II (DOC) First published: 17 August 2020 https://doi.org/10.1002/fgc.31251Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume44, Issue1820 August 2020Pages 6-6 RelatedInformation
Full Issue

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 56, Issue 4 p. I-I Full Issue Full Issue First published: 02 June 2019 https://doi.org/10.1111/j.1467-6346.2019.08873.xAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume56, Issue4June 2019Pages I-I RelatedInformation
Evaluation Study of Different Techniques in Diagnosis of Acute Leukemia in Adults and Children Patients

Cytomorphology and cytochemistry are combined with immunophenotype by flow cytometry (FCM) to diagnosis and management the acute leukemia.The present study was designed to compare between the cytomorphology, cytochemistry and immunophenotype by flow cytometry at diagnosis and classification of acute leukemia to suggest a number of antibodies that can be adopted in the diagnosis by flow cytometry.The study included (160) cases were newly diagnosed (100 adults, 60 children).Morphological analysis was depended on peripheral blood smears examination by Leishman stain, cytochemical analysis with PAS and SBB stains and immunophenotype analysis used multiparameter.the results of this study shown that 60% of adult cases were AML, and 40% ALL.The mean age of adults was 48.45 years for AML cases and was 32.59 years for ALL adult cases.In children AML the mean age was 5.23 years and was 6.44 years in children ALL cases.Our Conclusion Also that the B.ALL was more commonly than T.ALL in both adults and children cases.Immunophenotypic detection by flow cytometry recorded (100%) successfully diagnosis in ALL cases, but it was successfully in (75%) of detected the subtypes of AML cases.
Assisted Living

This chapter will address the roles that smart house technology, telecare and telehealth can play in supporting people with disabilities to live more independently. It defines assisted living in terms of the advanced technologies that are able to fulfil such roles. It describes the evolution of the technologies behind home automation, and provides examples of such technology in practice, while highlighting their issues and strengths.
A Computer Numerical Cooperation Depth Index Using the Analytic Hierarchy Process and Big Data Technology

This paper constructs an evaluation model for a fishery trade cooperation depth index based on big data, which includes four factors: cooperation policy, infrastructure, economy and trade, and technology and humanities. In addition, 14 secondary indicators are set up under four first-level indicators. The big data of the 14 secondary indicators of 34 regional representative countries along the Maritime Silk Road were selected as samples to be calculated, and their scores for the fishery trade cooperation depth index were calculated by using the analytic hierarchy process (AHP) in order to evaluate their fishery trade cooperation achievements. This paper uses big data to put forward relevant policy recommendations to help China participate in international trade cooperation and avoid trade risks effectively.
GUINEA BISSAU: Deadlock Broken?

Africa Research Bulletin: Political, Social and Cultural SeriesVolume 56, Issue 6 p. 22323C-22324A Internal Developments GUINEA BISSAU: Deadlock Broken? First published: 14 July 2019 https://doi.org/10.1111/j.1467-825X.2019.08914.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume56, Issue6July 2019Pages 22323C-22324A RelatedInformation
Flooding

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 56, Issue 4 p. 22536A-22536A Policy and Practice Flooding First published: 02 June 2019 https://doi.org/10.1111/j.1467-6346.2019.08888.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume56, Issue4June 2019Pages 22536A-22536A RelatedInformation
FEATURE FUSION BASED ON AUDITORY AND SPEECH SYSTEMS FOR AN IMPROVED VOICE BIOMETRICS SYSTEM USING ARTIFICIAL NEURAL NETWORK

In today's world, identifying a speaker has become an essential task.Especially for systems that rely on voice commands or speech in general to operate.These systems use speaker-specific features to identify the individual, features such as Mel Frequency Cepstral Coefficients, Linear Predictive Coding, or Perceptual Linear Predictive.Although these features provide different representations of speech, they can all be considered as either auditory system based (type 1) or speech system based (type 2).In this work, a method for improving existing voice biometrics system is presented.A method fusing a type 1 feature with a type 2 feature is implemented using artificial neural network and evaluated on in-campus recorded data set.The obtained results demonstrate the potential of our approach in improving voice biometrics system, regardless of the underlying task being speaker identification or verification.
Research on Novel Clustering Algorithm Based on Convolutional Variational Auto-encoder

In this era of rapid technological development, the information that people come into contact with has increased exponentially. Every corner of human society has accumulated a variety of data. In this context. how to organize and utilize unlabeled data effectively becomes an urgent problem to be solved. This has promoted the development of a research hotspot in artificial intelligence, clustering. Recently, clustering algorithm based on auto-encoders have attracted widespread attention because of their excellent performance. However, when the data dimension is very high and its structure is relatively complex especially facing image data, the clustering method based on auto-encoder cannot get satisfactory clustering results. Meanwhile, these methods also have the disadvantage of not being able to directly learn the clustering results. To address the above issues this paper proposes a clustering algorithm based on the convolutional variational auto-encoder called Conv-VAE. Through the joint optimization learning of convolutional network and variational auto-encoder, the method can better process high-dimensional image data. The category-encoder embedded in the network can directly obtain the clustering results, avoiding complicated post-processing. Experiments on real image data sets demonstrate that our proposed algorithm is superior to related algorithms proposed in recent years in terms of clustering performance.
Satellite-derived sunshine duration data in the CM SAF SARAH-3 climate data record&amp;#160;

&amp;lt;p&amp;gt;Sunshine Duration (SDU) is an important parameter in climate monitoring (e.g., due to the availability of long term measurements) and weather application. The exceptional sunny years in Europe since 2018 have raised also the attention of the general public towards this parameter.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The definition of SDU by WMO via the threshold of 120 W/m&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt; for the Direct Normal Irradiance (DNI) allows the estimation of sunshine duration from satellite-derived surface irradiance data. Sunshine duration is part of the climate data record (CDR) &amp;amp;#8220;Surface Solar Radiation data set &amp;amp;#8211; Heliosat&amp;amp;#8221; (SARAH-2.1, doi: 10.5676/EUM_SAF_CM/SARAH/V002_01) by EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF), which is based on observations from the series of Meteosat satellites. The provided temporal resolutions are daily and monthly sums with a grid space of 0.05&amp;amp;#176;; the data are available from 1983 to 2017 at www.cmsaf.eu. This climate data record is temporally extended by the so-called SARAH-ICDR (Interim Climate Data record) with an average timeliness of 3 days to allow climate monitoring. An updated, improved, and extended version of the SARAH-2.1 CDR is currently being developed and will be made available in early 2022. The SARAH-3 CDR of sunshine duration, covering 1983 to 2020, will be improved compared to the current version, in particular during situations with snow-covered surfaces.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Here, the algorithm, improvements compared to SARAH-2.1 and a first validation will be presented for sunshine duration, especially for Germany and Europe. The validation is based on station data from Climate Data Center (CDC) for Germany and European Climate Assessment &amp;amp; Dataset (ECA&amp;amp;D) for Europe.&amp;lt;/p&amp;gt;
Autonomous Databases

As you know already, Oracle has delivered a few decades of data management systems and innovation for on-premise, cloud, and hybrid type of deployment. The latest cloud version of the database is called the Autonomous Database (ADB). This system combines concepts like self-driving, self-securing, and self-repairing by redefining the database management tasks using machine learning and automation. This dramatically reduces the needs of human labor, costs, and manual tuning and then reduces the risk and human errors. This way, your system is more stable, more efficient in terms of performance but also in terms of cost.
Error Analysis

Error Analysis was a fruitful methodology in the 1970s to study the errors made by learners when acquiring a second language. In the first stage, the error-tagging system and the error annotation type are selected. One of the first decisions to make is what error-tagging system to use to error-tag a learner corpus. The recommended error-tagging system is the one that comes with an error-tagging manual. Advances have been made to automatize error identification and correction in learner language. The information contained in the error-tagging ship’s log is validated throughout the error-tagging process. This chapter discusses two methodological decisions that are to be made before starting the error-tagging process: full error-tagging and problem-oriented error-tagging. The number of error-tagged learner corpora is increasing nowadays, with more attention being paid to oral learner language and target languages other than English. The description of error-tagging systems should include information on the learner corpora in which they have been used.
News on patent, trade mark and design databases on the Internet

• New Ukraine IP database. • More case law data available from the USA. • Historic EPO sequence data now available on The Lens.
Self-adaptive wolf pack algorithm based on dynamic population updating for continuous optimisation problems

Wolf pack algorithm (WPA) is a relatively new swarm intelligence-based algorithm for solving complex continuous optimisation problems as well as real-world optimisation problems. The basic WPA and its variants are prone to trap into local optima and premature convergence when tackling multi-modal functions due to diversity loss problem and imbalance between exploration and exploitation. Inspired by the idea of integrating the heuristic information and stochastic strategies to balance exploration with exploitation, we propose a self-adaptive WPA based on dynamic population updating (SWPA-DU) strategy. First, the self-adaptive chaotic scouting behaviour is designed to develop the global exploration of scout wolves. Second, a novel Cauchy perturbation operator is proposed to generate a few mutation besieging wolves, which not only enhances the capability of jumping out of local optima but also improves local exploitation. Third, a dynamic population updating strategy is invented to improve diversity. Numerical experiments with a suit of benchmark functions and practical applications are performed to verify the effectiveness and advancement of the proposed algorithm. The experimental results indicate that SWPA-DU obtains superior performance on both multi-modal and high-dimensional problems over the compared algorithms.
The Effect of Health Information Technology on Time and Cost Saving in Remote areas of Iran

The present study aims at investigating the effect of health information technology on time and cost saving in the perspective of users of teaching hospitals in in remote areas of Iran.This is an applied study with a descriptive-analytical and cross-sectional method conducted on users of hospitals in remote areas of Iran using stratified random sampling.Data collection instrument was a selfmade questionnaire, the face validity and reliability of which were confirmed by Cronbach's alpha 0.94.Data were collected in person and analyzed by SPSS software V. 21 and descriptive and analytical statistics.Based on the Chi-square test results, there was a significant relationship between the effects of health information technology on time saving as well as cost saving.The results of Kruskal-Wallis test showed no significant relationship between education level, age and work experience and time and cost saving as well.User satisfaction is one of the most important aspects of the success of information systems, therefore, it is recommended that senior managers pay attention to the individual aspects of the employees working in the organization, provide them with necessary training before implementing the information systems, and involve them in the decisions in using such technologies.
Sequence Mining

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts. New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning.
The Declaration of the Establishment of the International Society for Formal Ontology

On the occasion of the international conference "Quo Vadis, Metaphysics?Dedicated to Peter van Inwagen to commemorate his 75th birthday", which took place in Warsaw from 26 to 29 September 2017, 41 philosophers representing 17 countries have decided to establish the International Society for Formal Ontology (ISFO) based in Poland.
The Degree of Practicing Knowledge Management Concept among Public Secondary Schools’ Principals in Kuwait from Their Point of View

The present study aimed at identifying the degree of practicing knowledge management concept among public secondary schools' principals in Kuwait from their point of view.The study population consisted of community consisted of public secondary schools' principals in Kuwait for the first semester (2020/2021).Whereas the study sample consisted of (60) public secondary schools' principals.Descriptive Surveying approach was developed, in which the questionnaire consisted of (40) statements.It was found that the degree of practicing knowledge management concept among public secondary schools' principals in Kuwait was moderate.It was also found that there were significant differences that can be attributed to gender, it came in favor of males and there were no significant differences that can be attributed to academic qualification.Based on the results, it was recommended to re-consider the implementation of knowledge management concept
Artifacts in Histopatholohy – A Microscopic View

Histopathological examination is considered a gold standard procedure for reaching a final diagnosis of various human body lesions.However, it is limited by a number of changes in normal morphological and cytological characteristics that occur as a result of presence of artifacts.The purpose of preparing a biological specimen for microscopic studies is to obtain sufficient and reliable diagnostic knowledge which is a true representation of the specimen, whether it is for study or diagnosis.These objects may occur during procedures for surgical removal, fixation, tissue processing, embedding, and microtomy, and staining and mounting.They contribute to misinterpretation of the diagnosis of histopathology but often they bring the limelight into the diagnosis.This article discusses the common artifacts which we commonly encountered during slide examination
UNIX

This book introduces the field of data science in a practical and accessible manner, using a hands-on approach that assumes no prior knowledge of the subject. The foundational ideas and techniques of data science are provided independently from technology, allowing students to easily develop a firm understanding of the subject without a strong technical background, as well as being presented with material that will have continual relevance even after tools and technologies change. Using popular data science tools such as Python and R, the book offers many examples of real-life applications, with practice ranging from small to big data. A suite of online material for both instructors and students provides a strong supplement to the book, including datasets, chapter slides, solutions, sample exams and curriculum suggestions. This entry-level textbook is ideally suited to readers from a range of disciplines wishing to build a practical, working knowledge of data science.