Reviewerly/exHarmony huggingface dataset:
Towards big services composition

Recently, cloud computing has been combined with big data processing leading to a new model of services called big services. This model addresses the customers' complex requirements by reusing and aggregating existing services from various domains and delivery models, and from multiple cloud availability zones. Existing web/cloud service composition approaches are not adequate for the big service context due to many reasons, including the large volume of data, the cross-domain and cross-cloud interoperability issues, etc. Considering the aforementioned facts, we provide a solution to the big service composition issue, by taking advantage of relational concept analysis (RCA), as a clustering method, and composite particle swarm optimisation (CPSO), as an optimisation technique. RCA is used to model the big service environment, whereas CPSO helps continuously optimising the quality of big service composition. The implementation and experimental studies on our approach have proven its feasibility and efficiency.
The Role of the University Library in educating ecological culture in students (awareness of specially protected natural areas)

The experience of the University Library is discussed. The problems related to the young adults’ ecological culture are revealed. The poster lecture: «The natural resources and specially protected natural areas in Nizhny Novgorod region» was presented to the students to support their awareness of the natural resources and ecological problems of the region. The soils, water, land and forest resources with the specially protected natural areas, in particular, Kerzhensky Natural Reserve in Nizhny Novgorod Region are characterized.
Retrieval Window (Advanced Mode)

The entries concerned by whatever query are by default presented on the interface in a text mode based on our deciphering, editing and correction of the original text. In the retrieval window (left half of the interface), the entry headwords are always automatically added (in capital letters) except for full text queries. The strings of the query are subordinated to the headwords and appear in boldface. The selected element is marked by a vertical stroke left of it. In the entry window (on the right), the elements searched for are highlighted. Here the main units of the entry come in different colours: the headwords in black (they are capitalised again), the parts of speech in red, the dialects in brown and so on. The text is presented without the original line-breaking of words by hyphens and without other layout details that are liable to ‘confuse’ the computer, but with the (frequent) complemented units of complex lexemes abbreviated in the original by hyphens (and now marked by a light grey), moreover with the (rare) necessary emendations.
Teachers’ Teaching Reading Strategies at Public Elementary Schools in Haripur District

The growing importance of English as an international language globally demands the students in Pakistan to be proficient in English especially reading skills. Thus, the objective of the study was to identify which reading strategies were taught by the English teachers to elementary pupils. In order to achieve the research objective, quantitative research design was employed in this study. Data were collected through random sampling of 100 teachers from 50 public schools which offer English as a subject using a set of questionnaires. The data were analysed using SPSS. The data are presented in percentages and frequency. The major findings indicate that the majority of the teachers have many problems in teaching English reading strategies to elementary students. It is hoped that the findings could help the education department officers in developing a suitable module to conduct training for elementary English teachers. Such measure is vital in order to improve the teaching capabilities of the English teachers in teaching reading strategies as to enhance the pupils’ reading comprehension.
Spark of Life

Chemistry & IndustryVolume 85, Issue 5 p. 26-29 Science & Innovation Spark of Life First published: 25 May 2021 https://doi.org/10.1002/cind.855_8.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 onEmailFacebookTwitterLinked InRedditWechat Volume85, Issue5May 2021Pages 26-29 RelatedInformation
State-of-the-Art

Several languages and frameworks have been proposed in the domain of goal oriented requirements engineering that try to capture and model the requirement specifications of the system being developed. Some well documented articles have been published that compare and contrast these approaches and stress on the analytical capabilities of each approach [1–4]. For the purpose of this book, we provide a brief summary of the current state-of-the-art in the requirements engineering domain in Sect. 2.1.
Administrasi Layanan Khusus

This article about a special service of learners includes guidance and counseling services, library services, a cafeteria service / kafetarian, health services, transformation services schools, service hostel,, laboratory services, and security. A special service was held in the school with a view to facilitate the implementation of teaching in order to accomplish the goals of education in schools.
Natural Images Allow Universal Adversarial Attacks on Medical Image Classification Using Deep Neural Networks with Transfer Learning

Abstract Transfer learning from natural images is well used in deep neural networks (DNNs) for medical image classification to achieve computer-aided clinical diagnosis. Although the adversarial vulnerability of DNNs hinders practical applications owing to the high stakes of diagnosis, adversarial attacks are expected to be limited because training data — which are often required for adversarial attacks — are generally unavailable in terms of security and privacy preservation. Nevertheless, we hypothesized that adversarial attacks are also possible using natural images because pre-trained models do not change significantly after fine-tuning. We focused on three representative DNN-based medical image classification tasks (i.e., skin cancer, referable diabetic retinopathy, and pneumonia classifications) and investigated whether medical DNN models with transfer learning are vulnerable to universal adversarial perturbations (UAPs), generated using natural images. UAPs from natural images are useful for both non-targeted and targeted attacks. The performance of UAPs from natural images was significantly higher than that of random controls, although slightly lower than that of UAPs from training images. Vulnerability to UAPs from natural images was observed between different natural image datasets and between different model architectures. The use of transfer learning causes a security hole, which decreases the reliability and safety of computer-based disease diagnosis. Model training from random initialization (without transfer learning) reduced the performance of UAPs from natural images; however, it did not completely avoid vulnerability to UAPs. The vulnerability of UAPs from natural images will become a remarkable security threat.
The Case for Remedial Germline Editing—The Long-term View

“We conclude that so long as heritable genome editing interventions are consistent with the welfare of the future person and with social justice and solidarity, they do not contravene any categorical moral prohibition.” Nuffield Council on Bioethics (2018)
ANALISIS KANDUNGAN YODIUM DALAM GARAM BERYODIUM PADA WADAH PENYIMPANAN PLASTIK DAN KACA SELAMA 6 HARI PENYIMPANAN

ABSTRACT Every year there are 39 million of infant newborn at risk of being born with low intellectual capacity due to iodine deficiency. Meanwhile, there are 5 percen of pregnant women who have increased TSH and TPO-Ab level.The consequences of Iodine deficiency can be prevented if pregnant women in adequate iodine intake early. Abundant and inexpensive source of iodine is salt iodization. Unfortunatelly, iodine concentration in salt iodization can be decreased due to time and conditions of storage, and type of salt. The aim of this study is to determine iodine content in Salt iodization that stored in different containers for six days of storage. The type of study was descriptive study. Sample is salt iodization were obtained from the grocery store by taking randomly and brands that are widely used in Palu city and its surroundings. Storage container of salt iodization consist of two namely plastic and glass jar. Each container consist of transparent and non transparent jars. Storage of sample is carried out for six days and analysis of iodine content was carried out on day 0, day 2, day 4 and day 6 of storage. The result of study showed that both glass and plastic container decreased iodium content in salt. The largest median of percentage reduction in iodine content occurred in transparent plastic and glass container, in 9,49 and 4,74% respectively. However, median of percentage reduction in non-transparent plastic and glass container, in 4,99 and 3,18%, respectively. For 2 days of storage, the largest median of percentage reduction in iodine content found in transparent plastic container which is 4,77%. Conclusion: The best storage of iodization salt is it in non-transparent container.
2020–2021 Production Period—Acknowledgement of Reviewers

Politics & PolicyVolume 49, Issue 6 p. 1275-1281 ANNOUNCEMENT 2020–2021 Production Period—Acknowledgement of Reviewers First published: 12 October 2021 https://doi.org/10.1111/polp.12444Read 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 onFacebookTwitterLinked InRedditWechat Volume49, Issue6Special Issue: Global Korea Scholarship: Empirical evaluation of a non‐western scholarship program from a public diplomacy perspectiveDecember 2021Pages 1275-1281 RelatedInformation
Analysis of Various Credit Card Fraud Detection Techniques

Data mining is a technique that is applied to mine valuable information from the rough data. A prediction analysis is an approach that has the potential for forecasting future possibilities based on the recent data. The CCFD is the challenge of prediction in which fraudulent transactions are predicted based on certain rules. There are several stages included in the detection of fraud in credit cards. Various classification algorithms are reviewed with respect to the performance analysis in order to detect fraud in the credit card. The performance is measured with regard to precision.
Preimage Attacks on Reduced Troika with Divide-and-Conquer Methods

Troika is a recently proposed sponge-based hash function for IOTA's ternary architecture and platform, which is developed by CYBERCRYPT and is now used in IOTA's blockchain. In this paper, we introduce the preimage attack on 2/3 rounds of Troika with a divide-and-conquer approach. Firstly, we propose the equivalent conditions to determine whether a message is the preimage with an algebraic method. As a result, for the preimage attack on two-round Troika, we can search the preimage only in a valid smaller space and efficiently enumerate the messages which can satisfy most of the equivalent conditions with a guess-and-determine technique. Our experiments show that the time complexity of the preimage attack on 2-round Troika can be improved to 379 from 3243. For the preimage attack on 3-round Troika, the MILP-based method is applied to achieve the optimal time complexity, which is 327 times faster than brute force.
Satellite Image Compression using RICE Algorithm

Processing of satellite images is time-intensive owing to the large surface of the earth and the necessity for high resolution. Compression algorithms are an active research topic since there is no single algorithm which can achieve the best compression at the highest speed. Different compression algorithms need to be explored to enhance the speed of the analysis. Here, a lossless compression scheme using RICE algorithm is implemented using Matlab and Verilog on a satellite image according to the CCSDS (Consultative Committee for Space Data Systems) recommendation. The RICE algorithm uses a set of variable length codes. The architecture comprises of a Pre-processor, Adaptive entropy coder, Postprocessor and an Inverse mapper. The design has been implemented using Xilinx
Modal Types

Modal logic flourished throughout the twentieth century. Kripke provided a semantics in terms of possible world recognized by mathematicians to be an example of varying sets. This allows a formulation in terms of monads generated by adjunctions. Modal homotopy type theory adds the radical idea that modalities apply to all types, not just propositions, so as to make sense of <italic>possible</italic> steps and <italic>necessary</italic> ingredients. The proximity is shown between the structures discovered by modal logicians and common ideas in mathematics of stability under variation. We can then reformulate many ideas in current philosophical metaphysical uses of modal logic, such as rigid designators, counterparts, the de re/de dicto distinction, and so on. Worlds are understood as extended contexts, allowing a formulation of counterfactuals. A form of temporal logic is also easily generated in the same vein.
Evolution of higher education institution websites in India: a longitudinal study

This paper undertakes a longitudinal study to assess the evolution of Indian higher education institutions (HEIs) websites over three years. In December 2015, websites of the top 300 higher education institutions in India were analysed to understand their maturity level: informational, interactional, transactional. The same websites were revisited and analysed in June 2019. The source code of these academic websites was studied as well. A significant shift has been noticed. In three years, universities have moved from low-level interactional websites to a transactional level, viz., stakeholders can make the payment on the institutional website. Demonetisation in India in November 2016, played a vital role. 40% of higher education institutions have attached web analytic tools to their websites. Implications are indicated. The study provides academics with useful insights to better meet their user needs by effectively applying digital technologies.
Genetic Algorithms

The first part of the book is about neural networks, a computational metaphor about how the brain operates. This chapter, the first of the second part of the book, focuses on evolution. In particular, it will cover genetic algorithms, a computational metaphor for how genetic information is recombined and passed through generations. This algorithm focuses on the pillars of how evolution naturally happens.
RGB Image Cluster Evaluation for Human Blood Group Identification by MLP Classification

Image processing is helping researchers to reach their goals in many ways, especially in medical fields. Blood organization is very important when it comes to receiving a blood exchange. The most important blood group identification method is ABO blood group system and the RhD blood group system. Blood groups are defined by the occupancy or preoccupied of a specific agglutinate on the get around of a red blood cell. Identifying the blood group is very important for medical treatment in pathological tests, at some point it gives us an inaccurate and also expensive result, therefore, to overcome these problems an efficient and optimal solution is required. The need for accurate detection is high in a disaster situation where there are no laboratory people or experts available to detect the type of it. In the proposed method, we have collected 50 blood sample images for each of 8 blood groups, total 400 blood sample images are considered for experimentation. In preprocessing, the median filter is used to eliminate noise from the blood images. Then these images are converted from RGB to grayscale conversion and also resizing of the images is carried out. Region based segmentation by using two methods Markov Random Field and Region Adjacency Graph are used for segmentation, texture, color, and shape features are extracted from segmented images. Hence this paper proposes a pixel cluster based analysis of the blood type based on the pixel analysis features. The overall accuracy of blood group determination is 93.85%.
Regression Test Suite Study using Classic Statistical Methods and Machine Learning

This work is inter disciplinary in nature. This work tries to apply latest discoveries in Artificial Intelligence to classic testing methodologies. Machine Learning which is the field of Artificial Intelligence is explored in this work. Thework demonstrates that provided the test team maintains the required data, Machine Learning Algorithms can aid in deciphering patterns from the test data. Patterns of interest are the relation between testers experience in the project and bugs uncovered, relations between the testers experience and the efficiency of test case with respect to code coverage and test execution time. Relation between testers experience and efficiency of test case with respect to code coverage and executiontime, relation between testers experience and bugs uncovered are explored using classic statistical techniques and clustering Machine Learning Algorithms. This clustering can be of immense help in test selection, prioritization, pruning and Regression test execution time reduction.
Bowing out …

Systems Research and Behavioral ScienceVolume 38, Issue 1 p. 3-4 EDITORIAL Bowing out … Michael C. Jackson, Corresponding Author M.C.Jackson@hull.ac.uk Search for more papers by this author Michael C. Jackson, Corresponding Author M.C.Jackson@hull.ac.uk Search for more papers by this author First published: 19 January 2021 https://doi.org/10.1002/sres.2773Read 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 onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume38, Issue1January/February 2021Pages 3-4 RelatedInformation
KNN Classification Based Nonlinear Noise Delineation in Color Image using Optimized BM3D Filter

Image enhancement using optimized methods along with optimized filters is need of current era. A novel technique is proposed in this paper, which have KNN based pixels classifications strategy. This classification is used to identify noise level and only noisy pixels are processed using optimized BM3D using particle swarm optimization. The outside group pixels are brought back into group thereby removing the noise. The process is further followed by resolution enhancement and Retinex for dynamic presentation purpose. The experimentation results are also included in the paper which shows optimum performance.
The evolution model for big data storage structure of online learning behaviour based on parallel algorithm

In order to overcome the heavy task of big data storage structure evolution computation, this paper proposes a parallel algorithm based network learning behaviour big data storage structure evolution model. This method introduces parallel algorithm, divides the whole dataset into several non overlapping data subsets randomly, mines the local frequent itemsets in the network learning behaviour big data in parallel and hierarchically, and connects the local frequent itemsets. Frequent itemsets can get all candidate sets. The actual support degree of different candidate sets is calculated by scanning datasets, and the evolution model of big data storage structure of network learning behaviour is established. The experimental results show that the operation efficiency of the proposed evolutionary model is as high as 99%, the cost is significantly lower than the other three evolutionary models, and the storage space consumption is the lowest.
Towards a deep augmented reality medical images diagnosis generation

Augmented reality (AR) and deep learning (DL) are promising areas. In this paper, we present the impact of such assortment (AR/DL) on the enhancement of generating textual and oral descriptions from a target medical image. The main purpose is to assist medical practitioners to make an accurate decision about a generated diagnosis. Automatic medical image report generation (textual and vocal) is used up as a diagnostic aid system for disease diagnoses depend strongly on visual properties. In this paper, we will describe how we develop an augmented report for the X-ray image target. Primary results using prototypes are promising. Doctors, learner's task are more efficient and feedbacks are encouraging.
Focault's Pendulum: An Introductory Analysis

An introductory analysis of the Focault Pendulum: Simple Pendulum approach, inclusion of Coriolis and centrifugal forces, and modelling of the Earth's model.
Using R

This chapter discusses how the best way to learn R is to use it. One should start by using it as a simple calculator, and keep on exploring what one gets back by inspecting the size, shape, and content of what one creates. R is available from CRAN, the Comprehensive R Archive Network. A nice interface to R is RStudio, which is a commercial product, but RStudio has a free open source license that allows one to have a very good and handy interface to R for free, including the possibility of writing reports using Rmarkdown, Sweave, or knitr. The chapter then looks at the two main graphics systems used in R: base graphics, which is an integral part of any R distribution, and ggplot2 (gg referring to grammar of graphics). Data from large epidemiological studies are often summarized in the form of frequency data, which record the frequency of all possible combinations of values of the variables in the study.
Administrasi hubungan masyarakat

Abstract — In the world of education,there are several components of educationthat are very instrumental in supportinglearning activities both directly andindirectly. One of the most importantcomponents is educational facilities andinfrastruncture. Administration ofeducational facilities and infrastructure isa very supportive thing for achieving thegoals of education. The teaching andlearning process will be more succesful ifeducational facilities and infrastucture areadequate. Education infrastructure andfacilities must always be complete. Thegovernment must always strive tocontinuously aquip aducational facilitiesand infrastructure for all levels and levelsof education. this article aims to determinethe administration of educational facilitiesand infrastructure in Indonesia along withthe obstacles faced and the efforts taken toovercome these obstacles. This research isa descriptive study with a qualitativeapproach. Data collection is done by themethod of observation, interviews anddocumentation. The data analysistechnique in this study is an interactiveanalysis consisting of data reduction, datapresentation and conclusion drawing.Check the validity of the data using sourcetriangulation and method triangulation