Reviewerly/exHarmony huggingface dataset:
Primary Rights and the Inequalities of E-Book Access

The e-book landscape is in a constant state of flux. More recent developments include new acquisition models, advances in platform usability and navigation, more lenient DRM provisions, and improvements to simultaneous user access licenses. However, what has not been addressed recently are the inequalities in e-book access for libraries across the world due to ‘primary rights.’ Territorial rights versus world rights is a licensing issue affecting libraries globally, and yet little is being done to address the inequalities of access. Join our discussion that will examine the ‘unavailable in your country’ message libraries often see alongside e-book purchase options, review documented inflation and deflation in e-book prices over time, and learn about the delayed or limited e-book offerings for global libraries. Explore how we can ensure equal access to electronic books for libraries across the globe. Hear perspectives from libraries inside and outside of the U.S., as well as publisher thoughts on the topic, including the continued drawbacks for library e-book access they believe will continue. Where do these discussions need to occur and who can we educate on the importance of including international access clauses in licenses or publishing agreements? Although this issue may not be widely known by librarians in the U.S., the exclusivity of electronic content based on the geographical location or status of a country is a sharp contrast to many of the inherent beliefs that are foundational to our profession.
Single Page Application: Architecture and Application

This study describes about the recent research on the topic ‘Single Page Application (SPA)’ which are in boom now days. SPAs are web apps that are loaded as single HTML page and their updations are carried out as the user interacts with the application. SPAs use AJAX and HTML5 to create fluid and responsive web apps, without constant reloading of pages. However, this means that much of the work happens on the client side, in JavaScript. This application mainly works on backend. This application works dynamically which is an important fact. In this study, we will talk about application, working process and also the future aspects. Keywords : SPA, server, web application, server-sent events, web shocks Cite this Article Reecha Sood, Gurpreet Singh, Sunil Kumar Chawla. Single Page Application: Architecture and Application. Recent Trends in Programming Languages 2019; 6(1): 27–30p.
Mapping groundwater hardness in wells as a source of drinking water for the people

Herce Farida Solossa 20.2018.2.00117 Mapping of Groundwater Hardness Distribution of Drinking Water for Bangkalan District Community, in 2019. Thesis, Department of Environmental Engineering, Faculty of Civil Engineering and Planning, Adhi Tama Institute of Technology Surabaya, Advisor Dr. Yulfiah, ST., Msi. Water hardness is the content of certain minerals in water, generally calcium (Ca) and magnesium (Mg) ions in the form of carbonate salts and this content if it exceeds quality standards can have an impact on human health. The purpose of this study is to map the distribution of groundwater hardness as a source of water supply in Kab. Bangkalan. The sample of this study is shallow wells with a depth not exceeding 20 m. This type of research is a descriptive study with a qualitative and quantitative approach. The research sample was taken as many as 18 following the number of subdistricts in Kab. Base Samples taken are water source wells used by the community. Sampling time is the dry season. Samples taken are stored in bottles and immediately taken to the laboratory for examination. Sampling locations are made in the form of maps with the ArcGis application. The conclusion of this research is that the level of hardness in groundwater in Kab. Base has moderate value - maximum. The distribution of hard water is also evenly distributed throughout the Kab. Base with the maximum distribution from east-west to east and east-east while the hardening is starting from north and northeast to south, southwest and west. This suggestion that can be made is that residents who use shallow wells should use a filter and cook it first for drinking needs. Keywords: Mapping, hard groundwater, drinking water sourcesKeywords: Mapping, hard groundwater, drinking water sources.
Switching Hybrid Method Based on User Similarity and Global Statistics for Collaborative Filtering

Collaborative filtering (CF) is a technique used in recommender systems to provide meaningful suggestions based on known feedback obtained from like-minded users. The measure of similarity plays a critical role in the performance of neighborhood-based CF methods. However, conventional similarity measures suffer from limitations because they only consider the direction of the rating vectors. We propose a novel similarity measure that considers the semantic nuances of the ratings; in particular, it weights the contributions of ratings in proportion to the users' degree of indifference towards the items. Additionally, to address the sparsity problem that affects the performance of CF techniques, we propose a switching hybrid method that predicts user ratings based on either our custom similarity measure or through user and item biases. We evaluated the proposed method on six different datasets and compared it with other CF methods. The results show that the proposed recommender consistently outperforms those using conventional similarity measures when the sparsity of the dataset is high.
Using apps for contact tracing in response to Covid-19: the controversies

We need to find ways for scientific knowledge to inform policymakers who must make choices on behalf of society, writes Edgar Whitley
FreeBSD as a compute node in OpenStack

At the moment, the demand for Infrastructure as a Service (IaaS) is higher than ever, as many companies from industry and open-source communities are focused on improving virtualization solutions. The aim of such a system is to provide virtual instances in a timely manner, persisting in quality and swiftness, while remaining simple and accessible for users. This paper proposes a model for a heterogeneous environment that offers services of IaaS using OpenStack as a cloud computing platform with Linux as a controller node and FreeBSD as a compute node. bhyve, the FreeBSD's hypervisor, will be used to create the virtual instances.
Application for Calculating Psychological Pressure in the DASS (Depression, Anxiety, and Stress Scale) Scale Using the Certainty Factor Method

Psychological stresses such as depression, anxiety, and stress often experienced by students can affect academic performance, physical health, and psychosocial well-being. The purpose of this research is to build a facility in the form of a website-based application for students in particular and the general public in order to know the level of psychological pressure they are experiencing. The psychological scale used is the DASS-21 (Depression, Anxiety, and Stress Scale) and the calculation uses the Certainty Factor method. In carrying out this research, there are three main stages that are carried out, namely; The first stage, looking for literature studies related to research. Second stage, conducting interviews with experts to get a certainty value on the scale that the researcher uses. Then, build an expert system using prototype development methods and web-based applications. The third stage, implementation was carried out by getting Computer Technology student respondents. This research is a new domain for the NSC Surabaya Polytechnic which will implement an expert system by utilizing the Certainty Factor method in analyzing student stress levels through intelligent applications that will be implemented in the form of a website, with the calculation of Certainty Factors, the application can produce evidence or analysis that can be used. in changing the learning system.
Impact of Current Phishing Strategies in Machine Learning Models for Phishing Detection.

Phishing is one of the most widespread attacks based on social engineering. The detection of Phishing using Machine Learning approaches is more robust than the blacklist-based ones, which need regular reports and updates. However, the datasets currently used for training the Supervised Learning approaches have some drawbacks. These datasets only have the landing page of legitimate domains and they do not include the login forms from the websites, which is the most common situation in a real case of Phishing. This makes the performance of Machine Learning-based models to drop, especially when they are tested using login pages.
A Mixed Reality Telepresence System for Dissimilar Spaces Using Full-Body Avatar

We present a novel mixed reality (MR) telepresence system, which enables a local user to interact with a remote user through full-body avatars in their own rooms. If the remote rooms have different size and furniture arrangement, directly applying the user's motion to the avatar leads to mismatch of placement and deictic gesture. To overcome this problem, we retarget the placement, arm gesture and head movement of the local user to the avatar in remote room to preserve the environment and interaction context of the local user. This allows avatars to utilize real furniture and interact with the local user and shared objects as if they were in the same room.
Genetic Programming-Based Selection of Imputation Methods in Symbolic Regression with Missing Values

Data incompleteness represents a serious issue in real-world applications of machine learning. Imputation methods are algorithms for restoring missing values in the data based on other available entries. Imputation methods have an influence on the learning performance on incomplete data. Therefore, the choice of a right imputation method has an important role when constructing prediction models. It is common to use one imputation method to impute all the incomplete features. However, the imputation method that works well for some features might not be suitable for others, hence, it would be more useful to select the right imputation method for each feature. In fact, selecting an imputation method for the whole data set is still a challenging issue, let al one selecting different imputation methods for all incomplete features. Therefore, this work proposes the use of genetic programming to search for the right combination of imputation methods for symbolic regression. The role of GP is to select imputation methods for incomplete features and evolve symbolic regression. It incorporates a heterogeneous set of imputation methods as part of the symbolic regression process. The results show that the proposed method can automatically find the most effective combination of imputation methods for a variety of incomplete regression data sets.
Digital Enforceable Contracts (DEC): Making Smart Contracts Smarter

The combination of smart contracts with blockchain technology enables the authentication of the contract and limits the risks of non-compliance. In principle, smart contracts can be processed more efficiently compared to traditional paper-based contracts. However, current smart contracts have very limited capabilities with respect to normative representations, making them too distant from actual contracts. In order to reduce this gap, the paper presents an architectural analysis to see the role of computational artifacts in terms of various ex-ante and ex-post enforcement mechanisms. The proposed framework is assessed using scenarios concerning data-sharing operations bound by legal requirements from the General Data Protection Regulation (GDPR) and data-sharing agreements.
A FORCED MIGRATION DUE TO COVID19 FROM A FACE-TO-FACE UNIVERSITY EDUCATION SERVICE TO A TOTAL ONLINE LEARNING MANAGEMENT SYSTEM SUPPORT: UDELAS-PANAMÁ STUDY CASE

A FORCED MIGRATION DUE TO COVID19 FROM A FACE-TO-FACE UNIVERSITY EDUCATION SERVICE TO A TOTAL ONLINE LEARNING MANAGEMENT SYSTEM SUPPORT: UDELAS-PANAMÁ STUDY CASE
WHO PERFORMS BETTER IN ESSAY WRITING, INTROVERTS OR EXTROVERTS? A CASE STUDY OF 3RD SEMESTER EFL STUDENTS

This research will investigate whether there are any significant differences between Introvert and Extrovert students on their Essay Writing performance. The object of this research will be the 3rd semester of EFL students in a private university in Surabaya academic year 2019-2020. This study will use ex post facto design with quantitative approach. For the data collection, this research will use questionnaire and documentations as the instruments. The students are all will have Writing III as the subject on that semester, totally 22 students will be the sample. This research also discuss the factors related such as what are the things influence this two types of personality in writing an Essay
Fast recognition method of text features in dynamic video images

In order to improve the text recognition ability of dynamic video image, a fast text feature recognition method based on block area contour detection is proposed. The fuzzy video feature analysis method is used to collect the text features of the dynamic video image, reorganise the frame structure, and extract the edge features of the text features of the image. The collected text features are fused into multi-dimensional information, and the edge contour feature information of dynamic video image is matched by block matching method. In this paper, a packet fusion model of Chinese text feature in dynamic video image is established, and the corner detection of text feature is carried out by surf algorithm to realise the fast recognition of Chinese text feature in dynamic video image. Simulation results show that the maximum SNR of the image text feature recognition output is 44.8 dB, and the recognition accuracy is high.
Ontology-Based Liability Decision Support in the International Maritime Law

In this paper, we present an ontology-based liability decision support task in the international maritime law, specifically the domain of carriage of goods by sea. We analyze the liabilities of the involved legal agents (carriers and shippers) in case of loss or damage of goods. Thus, a well-founded legal domain ontology, named CargO-S, is used. CargO-S has been developed using an ontology-driven conceptual modeling process, supported by reusing foundational and legal core ontologies. In this work, we demonstrate the usability of CargO-S to design and implement a set of chained rules describing the procedural aspect of the liabilities legal rules. Finally, we employ these rules in a liability rule-based decision support task using a real case study.
ONNX-Scala: typeful, functional deep learning / Dotty meets an open AI standard (open-source talk)

ONNX (Open Neural Network eXchange) is an open standard for machine learning interoperability, supported by the most widely used tools and frameworks. ONNX-Scala (https://github.com/EmergentOrder/onnx-scala) brings full support for the ONNX specification, and hence for state-of-the-art deep learning models as well as numerical computing more generally to the Scala ecosystem. Backed by the optimized native CPU/GPU backend ONNX Runtime, with a Scala.js backend coming soon, it offers 2 APIs: A) For off-the-shelf models / performance-critical scenarios, a simple black-box API, B) for everything else (pre/post processing, model customization, internal parameter streaming, etc.) a fine grained API that exposes each ONNX operator as a pure function with type-level encoding of, and constraints on, shapes, axis semantics and data type for each input and output tensor / ndarray. The latter API synthesizes recent progress toward more typeful and functional approaches from across the (Python-dominated) AI ecosystem, implemented using a variety of new features in Dotty / Scala 3 and forms the basis of NDScala (https://github.com/SciScala/NDScala), a NumPy-like API enabling seamless interoperation between ONNX-Scala and other JVM-based offerings via an ndarray type class.
Reference Mutability for DOT.

Reference mutability is a type-based technique for controlling mutation that has been thoroughly studied in Java. We explore how reference mutability interacts with the features of Scala by adding it to the Dependent Object Types (DOT) calculus. Our extension shows how reference mutability can be encoded using existing Scala features such as path-dependent, intersection, and union types. We prove type soundness and the immutability guarantee provided by our calculus.
Best practices for ecological model evaluation I

The Nansen Legacy workshop on best practices for ecological model evaluation, chaired by Benjamin Planque (IMR) was held in Tromsø on the 6-7th November 2018. The objective of the workshop was to develop recommendations for best practice in evaluation of the performance of food-web simulation models (deliverable 4-4.1.1 of the Nansen Legacy project).
Implementation of Camshift Target Tracking Algorithm Based on Hybrid Filtering and Multifeature Fusion

In recent years, the Mean shift algorithm has extensive applications in the field of video tracking. It has some advantages of low cost, small memory, and good tracking effect. However, there are some shortcomings in the existing algorithm; for example, it cannot produce adaptive changes as the target size changes. And when there are similar objects, it is prone to target positioning errors and tracking failures caused by occlusion. In this paper, an improved method of continuous adaptive change Mean shift (Camshift) for high-precision positioning and tracking is proposed. The traditional Camshift method only uses hue components in HSV to extract features. This paper uses the combination of H and S components in HSV space to build a two-dimensional color feature histogram and with the image’s LBP feature histogram to increase tracking accuracy. Meanwhile, for the sake of target occlusion and nonlinear changes in the tracking process, this paper introduces a Gaussian-Hermit particle filter that is updated by the Kalman filter. Experimental result demonstrates that the real-time performance of the proposal in this paper is better than Mean shift, Camshift, simple particle filter, and Kalman filter.
Label-Efficient Training for Next Response Selection

This paper studies label augmentation for training dialogue response selection.The existing model is trained by "observational" annotation, where one observed response is annotated as gold.In this paper, we propose "counterfactual augmentation" of pseudo-positive labels.We validate that the effectiveness of augmented labels are comparable to positives, such that ours outperform state-of-the-arts without augmentation.
Investigating Sensitivity of Nonlinear Classifiers by Reducing Mean Square Error (MSE)

In this paper a new method is presented for handling the problems of Artificial Neural Networks (ANNs) in a Self-Organizing Map (SOM), the problems are the presence of noise and missing in datasets.Based on a robust and speedup of the investigation of a nonlinear classifications in SOM and Adaptive Linear Neuron ANNs (Adaline) algorithms that dealing with missing or noise data a new model proposed.the main objective of the proposed model is to contribute the advantages of all methods (SOM with Adaline) in rising the quality of SOM to handle the noise and missing value to improve its sensitivity of our model using combing the advantages of all methods (SOM with Adaline) in anew algorithm abbreviation (ADA-SOM).Simulation results show that the algorithm ADA-SOM achieved better performance and higher sensitivity to accurate MSE (Mean Square Error) than other standard classifiers, our model gets accurate benchmark results.
AWS Pricing and Cost Management

In the previous chapter, we looked at some concepts of cloud computing and explored a few of the important services provided by AWS. In this chapter, we will look at how AWS charges us for the services it provides and how we can get the best out of AWS with the least amount of burden on our pocketbooks as possible.
SISWA SD MENGGUNAKAN SMARTPHONE DALAM PEMBELAJARAN ONLINE

The use of smartphones at the age of elementary school (SD) students can have a negative effect on the growth of knowledge and learning activities. However, with the implementation of home learning and online learning in Indonesia today, elementary students have a lot of time using smartphones to study or using smartphones in a positive way. The purpose of this study was to determine the use of smartphones for elementary students in online learning. This study used a quantitative approach to survey methods and selected a random sample of 124 respondents who lived in urban areas, elementary school students in grades 3-6 and had given answers to a questionnaire given in the form of google form. The research instrument was adapted from several literatures. The instrument is made in 10 question items. The study was analyzed with quantitative statistical descriptions using SPSS version 24. The results found that 31 students had smartphones and 94 students used smartphones belonging to their parents, siblings and other people in online learning. The time spent studying is between 5-6 hours. Elementary students use smartphones in the good category to study, do and collect assignments, a tool to explore electronic and digital learning resources, are able to discuss with peers and all feel satisfied using smartphones in online learning process activities. Suggestions for future research are to use attitude, behavior and impact variables of smartphone use for students who have their own smartphones.
Issues in Information Management and Effects Towards Organisational Performance

This study identifies the crucial issues in information management that affect organisational performance.The paper is based on the perusal reading of the authors based on several articles.The study identifies that the managing information as an important asset will help to change organisational operation by dominant the conception and development of information, reduction in operation cost, rising skillfulness and productiveness and precaution essential information.It also reassessment propose that organisations might start to create an information management scheme that has a modality of agree with the various systems into an ordinary system and this intent outcome in strategically benefit.The study was conducted based on several articles regarding the issues in information management.The lack of the latest research about the issues limits the findings for the sake of this writing.The recommendation and suggestion have been mention on this research for better study by the researcher on this area.
Design, construction, and analysis of ukuleles as a method for teaching on the acoustic properties of stringed instruments

This presentation will discuss an undergraduate course taught at Catholic University where the primary learning objective was for the students to understand how the design characteristics of a stringed instrument effects its acoustic properties. Previous student-led design projects have researched the acoustic properties of stringed instruments, notably guitars and five-string banjos, but no formal course has ever been offered on the subject. Further, all previous investigations utilized commercially available instruments as the test subjects, and thus, were limited in the design characteristics available to test. The course combined hands-on education about the construction of ukuleles, with subsequent measurement and analysis of the acoustic properties. Ukuleles were chosen as the test subject due to their simplicity compared to other stringed instruments, which allowed students with various levels of shop experience to participate in relevant aspects of lutherie. The ukuleles featured both conventional and non-conventional design characteristics, and were constructed with both traditional and non-traditional methods. Upon completion of the course, the students constructed nine different ukuleles, collected a large set of acoustic data, and completed preliminary analyses of the various instruments. Interest in the subject has persisted beyond the course, and several research projects on the subject have resulted.