Reviewerly/exHarmony huggingface dataset:
Colour Fidelity in Spectral Reconstruction from RGB Images

Spectral reconstruction (SR) aims to recover high resolution spectra from RGB images. Recent developments - leading by Convolutional Neural Networks (CNN) - can already solve this problem with low errors. However, those leading methods do not explicitly ensure the predicted spectra will re-integrate (with the underlying camera response functions) into the same RGB colours as the ones they are recovered from, namely the 'colour fidelity' problem. The purpose of this paper is to show, visually and quantitatively, how well (or bad) the existing SR models maintain colour fidelity. Three main approaches are evaluated - regression, sparse coding and CNN. Furthermore, aiming for a more realistic setting, the evaluations are done on real RGB images and the 'end-of-pipe' images (i.e.rendered images shown to the end users) are provided for visual comparisons. It is shown that the state-of-the-art CNN-based model, despite of the superior performance in spectral recovery, introduces significant colour shifts in the final images. Interestingly, the leading sparse coding and the simple linear regression model, both of which are based on linear mapping, best preserve the colour fidelity in SR.
Explainability via Responsibility

Procedural Content Generation via Machine Learning (PCGML) refers to a group of methods for creating game content (e.g. platformer levels, game maps, etc.) using machine learning models. PCGML approaches rely on black box models, which can be difficult to understand and debug by human designers who do not have expert knowledge about machine learning. This can be even more tricky in co-creative systems where human designers must interact with AI agents to generate game content. In this paper we present an approach to explainable artificial intelligence in which certain training instances are offered to human users as an explanation for the AI agent's actions during a co-creation process. We evaluate this approach by approximating its ability to provide human users with the explanations of AI agent's actions and helping them to more efficiently cooperate with the AI agent.
LITERATURE STUDY OF THE RELATIONSHIP OF DINING AND BREAKFAST PATTERNS WITH LEARNING ACHIEVEMENT IN BASIC SCHOOL CHILDREN

School children are the nation's next generation. Therefore, it is necessary to improve human resources from an early age. Providing good nutrition, will affect the growth and development of a child. The purpose of this study was to determine the relationship between eating and breakfast patterns and learning achievement of elementary school children. The type of research used is quantitative research with a literature study design. The literature used is literature published from 2013 to 2020. The results of data analysis show that there is a relationship between eating and breakfast patterns and learning achievement of elementary school children. The results of data analysis showed that there were 3 research locations, namely in Java 60% (6 articles), Sulawesi 30% (3 articles), Kalimantan 10% (1 article). Using correlation research 50%, analytic survey research 20%, and 30% other research. Data analysis was made in univariate and bivariate ways. The variables used in each study were diet, breakfast, and learning achievement. From this research, it can be concluded that there is a relationship between eating and breakfast patterns and learning achievement of elementary school children. So further research is expected to develop other factors that can affect student achievement.
Using reading while listening in English as a foreign language (EFL) learning context

The benefits of reading while listening for English as a Foreign Language (EFL) learners have been investigated in different EFL learning contexts. Some studies found that simultaneous reading while listening promotes positive impacts on students’ reading and listening skills. It also helps L2 learners’ fluency and comprehension of reading and listening. Moreover, it can assist L2 learners in acquiring new language input in a new learning environment. Hence, this article reviews some research papers related to the implementation of reading while listening (RWL) program in EFL learning context. Furthermore, to answer the research questions: 1) What is reading while listening?; 2) What are the effects of using reading while listening for EFL learners? How to apply the reading while listening program within the EFL classroom? To answer these questions, this article examines the use of RWL for EFL learners based on the research methodology, subject, instrument used, result and suggestion, including the principles of implementing simultaneous reading and listening within the EFL classroom. &#x0D; HIGHLISGHTS&#x0D; Highlights&#x0D; &#x0D; Reading While Listening (RWL)simultaneously can support students with low reading or listening fluency rate.&#x0D; Simultaneous reading while listening affects students reading and listening skills for a long period of time.&#x0D; A guideline of RWL program implementation based on ER/EL principles is discussed thoroughly.&#x0D;
Graph embedding using multi-layer adjacent point merging model

For graph classification tasks, many traditional kernel methods focus on measuring the similarity between graphs. These methods have achieved great success on resolving graph isomorphism problems. However, in some classification problems, the graph class depends on not only the topological similarity of the whole graph, but also constituent subgraph patterns. To this end, we propose a novel graph embedding method using a multi-layer adjacent point merging model. This embedding method allows us to extract different subgraph patterns from train-data. Then we present a flexible loss function for feature selection which enhances the robustness of our method for different classification problems. Finally, numerical evaluations demonstrate that our proposed method outperforms many state-of-the-art methods.
Adoption of BioPortal's Ontology Registry Software: The Emerging OntoPortal Community

A key BioPortal deliverable has been the Virtual Appliance, which any community can deploy to create their own repository of ontologies and vocabularies. Adoption of the Virtual Appliance has increased significantly, with many developers, operators, and end users adopting and improving the code. We now present this software stack as OntoPortal, and release it as the OntoPortal Virtual Appliance.
Study on Difficulties and Response Strategies of the Career Development of Young Teachers in Sichuan University of Arts and Science

As the main human resource factors of education and teaching, young teachers in colleges and universities have heavy teaching and research tasks, encounter difficulties such as difficult professional title evaluation, economic income lower than expected value and long-term physical and mental sub-health.The solving of these problems is related to the scientific, healthy and long-term development of colleges and universities.This paper first analyzes the current situation of teaching and development difficulties of young teachers in Sichuan University of Arts and Science, explores the strategies to overcome the teaching development difficulties of young teachers in the university, and proposes that young teachers should influence students with excellent personality charm and the university should establish a more reasonable, perfect and fair salary and professional title evaluation system, so as to improve the interest and enthusiasm of young teachers in our university in teaching and scientific research and promote their healthy growth.
The effects of organizational learning on the security of bankings information system in Indonesia

Organizational learning improves the security of information system.This study aimed to test and prove whether organizational learning had an effect on the security of information system.Data was gathered through survey, by administering questionnaires to public banks in Indonesia, and was tested using SEMPLS.This study employed explanatory research methodology.The findings showed that insecure information system was found to be the result of unoptimized organizational learning.In other words, organizational learning is a determining factor for a sufficient information system security.
Importing, manipulating and displaying DICOM data in MATLAB

This chapter discusses working with Digital Imaging and Communications in Medicine (DICOM) images in MATLAB, with primary focus on: importing, writing and displaying DICOM data, ways to anonymize data in MATLAB, extracting meta data and techniques on rendering images and volumes. A volume data set can either be a multidimensional vector volume data or scalar volume data. A vector volume data contains two or more values per voxel, defining the components of the vector. A scalar volume data set contains a single value per voxel. A typical DICOM volume data set is a scalar volume, which can be visualized in MATLAB using various plotting functions, such as: volshow, isosurface, slice and contourslice. The volume data can be imported either from file, from a DICOM folder containing DICOM images, or also from workspace.
Effectiveness of BME Strategy in Improving Writing Skills among Low Proficiency English Language Learners

This study investigates the effects of Beginning-Middle-End (BME) strategy on the improvement of English writing skills among the lower proficiency language learners in a secondary school located in the state of Kedah.Utilising the BME within language classroom is seen as a valuable approach which offers assistance to lower proficient learners to progress in their English writing skills.Writing is a common issue affecting most second language learners (ESL) as these would lead the learners to lose motivation in learning writing in English.Although writing is without doubt the most challenging proficiency to be acquired, it is a vital skill to measure learners' level of proficiency in English language.The objective of this study is to assess the effectiveness of BME strategy in improving writing skills among secondary school learners.This quasiexperimental study was conducted within a 4 month period where twenty seven samples were given one writing lesson per week involving an in-depth BME intervention.Data was collected via the pre-and post-test.The post-test scores indicate that learners have developed better writing skill with the intervention of BME strategy.The findings identified that participants improved significantly in their writing skills.Implementation of BME to improve writing skill is a worthy strategy which ought to be adopted in teaching lower proficiency English language learners.
Ultranarrow spectral line and non-Gaussian feature of the radiation in double qubit-cavity ultrastrong coupling system

We investigate the ultranarrow spectrum and non-Gaussian feature of a circuit QED system with two qubits ultrastrongly coupled to a single-mode cavity. By adjusting the frequency of the driving field to resonate with the cavity frequency at the point of avoided-level crossing, we can get an equivalent four-level dressed state model. The vacuum-induced quantum interference between two transition pathways couples the slow decaying incoherent components of the density matrix into the equations of the sidebands, thereby an ultranarrow peak appeared at the line center of the cavity emission spectrum. This result provides a possibility for the study of quantum interference effect in the USC system. Moreover, the two metastable states with electronic shelving in the nondegenerate four-level system enhance the effect of spectral line narrowing. Finally, we also explore the intensity-amplitude correlation of the system, and the non-Gaussian feature of the ultrastrong coupling system can be identified, indicating that the system has broad application prospects in the field of nonlinear optics and preparation of non-classical states.
Visual Task Characterization for Exploratory Search

Humans are living in the age of big data, advanced analytics, and human information interaction. The tremendous growth of ‘the data' presents enormous challenges to information-seeking. A naïve user adapts several strategies (e.g., analytical search, search by analogy, etc.) to aggregate the knowledge. Augmented visualization plays a pivotal role via visual cognitive support in user searches (i.e., simple visual search, visual exploration, etc.). Though it is hard for a user to look for specific tasks or visual metaphors, as evaluation of visual task is rarely undertaken, it is unclear what role, if any, information visualizations play in the user search. In this paper, a visual taxonomy is adopted to systematically review key visualization tools to understand the visual tasks and inherent functions and viability. The key contribution is to trace the current trends and advancements on the dimensions (i.e., visual accomplishments and visual implications) and to assert that annotations will provide a vision on the state of exploratory visual analytics, evolving frameworks, and tools.
Subjectivity Reducing In Software Version Criticity Classification With The Support Of An Expert System

&lt;p&gt;In the software version release management process, there is a need, on the part of human specialists, to classify the criticality of each software version However, the subjectivity of this classification may be present according to the experience acquired by specialists over the years. In order to reduce subjectivity in the process, an Artificial Intelligence technique called the Expert System (ES) can be applied to represent the knowledge of human specialists and use it in problem solving. &lt;a&gt;Thus, the aim of this paper was to reduce the subjectivity in the criticality classification of the software version with the support of the Expert System. &lt;/a&gt;To this end, a questionnaire was developed with the objective of obtaining the criticality opinions classified as High, Medium and Low in each specialist's software version to assist in the preparation of the ES production rules. ES generated 17 production rules with a 100% confidence level applied to a production database. The results of the classification carried out by the ES corresponded to the classification carried out by the specialists in the production base, that is, the ES was able to represent their knowledge. Then, another questionnaire was applied to the specialists in order to verify the perception of satisfaction regarding the use of the ES with a result obtained of 4.8, considered satisfactory. It was concluded, then, that the ES supported the reduction of subjectivity in the classification of the criticality of software version.&lt;/p&gt;
Masterminding change by combining secure system design with security risk assessment

This track introduction presents the results of the Workshop on Security practices for Internet of Things, SPIoT held at ETAPS in Prague in April 2019. For this Special Issue of STTT, we have selected, invited and edited three distinguished papers. We briefly recall the aims, summarize the workshop held in Prague and introduce the selected papers.
Sampling-Decomposable Generative Adversarial Recommender

Recommendation techniques are important approaches for alleviating information overload. Being often trained on implicit user feedback, many recommenders suffer from the sparsity challenge due to the lack of explicitly negative samples. The GAN-style recommenders (i.e., IRGAN) addresses the challenge by learning a generator and a discriminator adversarially, such that the generator produces increasingly difficult samples for the discriminator to accelerate optimizing the discrimination objective. However, producing samples from the generator is very time-consuming, and our empirical study shows that the discriminator performs poor in top-k item recommendation. To this end, a theoretical analysis is made for the GAN-style algorithms, showing that the generator of limit capacity is diverged from the optimal generator. This may interpret the limitation of discriminator's performance. Based on these findings, we propose a Sampling-Decomposable Generative Adversarial Recommender (SD-GAR). In the framework, the divergence between some generator and the optimum is compensated by self-normalized importance sampling; the efficiency of sample generation is improved with a sampling-decomposable generator, such that each sample can be generated in O(1) with the Vose-Alias method. Interestingly, due to decomposability of sampling, the generator can be optimized with the closed-form solutions in an alternating manner, being different from policy gradient in the GAN-style algorithms. We extensively evaluate the proposed algorithm with five real-world recommendation datasets. The results show that SD-GAR outperforms IRGAN by 12.4% and the SOTA recommender by 10% on average. Moreover, discriminator training can be 20x faster on the dataset with more than 120K items.
Challenges affecting the Effective Implementation of Community-Oriented Policing in Abuja Municipal Area Council, Nigeria

This article examines the challenges affecting the implementation of community-oriented policing in Abuja Municipal Area Council, Nigeria. Over the years policing in Abuja has been confronted with problems like increased crime, terrorism and general insecurity. Despite, the adoption of community-oriented policing in April 27th, 2004 which was a welcomed strategy to deal with the crime trend, yet the crime is still on the increased. Community-oriented policing as a strategy is a proactive philosophy that promotes problem-solving, and problem oriented policing in tackling the crime and insecurity that affect the quality of life, and citizens fear of crime. It entails identifying, analysing and addressing the community problems at their roots. It also involves partnership between the police and members of public as co-producers of safe community. The method employed was survey; multi-stage sampling was used, while questionnaire and oral interview were used as instruments of data collection for 400 respondents.  The study revealed that, community-oriented policing implementation in Nigeria is faced with series of challenges. These include misconception of the core value of community-oriented policing, police-public perceptions, and inadequate fund from the government, inadequacy equipment and technology to support services, corruption, and so on. The study recommends that it is pertinent for all the stakeholders to have a proper training in order to understand the concept of community-oriented policing for effective delivery of the strategy in the reduction of crime and fear of crime, for safety and security in Abuja Municipal Area Council.Keywords: Challenges, Community policing, Crime prevention, partnership, safety, security, strategy.
Analisis Problem Based Learning dan Discovery Learning menggunakan Macromedia Flash pada materi Termokimia

This study aims: (1) to find out wheter the average value of student learning outcomes taught by PBL and DL models is greater than the KKM value (2) to find out whether there is class interaction and motivation on the value of student learning outcomes. This research is type of One-Group pretest-posttest Design research. The analysis technique used is: (1) One sample t-test; (2) Two Way Anava. From the analysis of the learning outcomes data obtained (1) differences in student learning outcomes (80.47 8.3336) taught by applying PBL models using macromedia flash and student learning outcomes (78.269 9.994) are taught by applying the DL model using macromedia flash where a t test of 1.684 is obtained; (2) There a Fhit price of 6.235 &gt; Ftable 4.00 and a sig value of 0.015 &lt; 0.05 meant that the factor A was real; inter-row results (B) have a Fhit price of 0.025 &lt; Ftable 4.00 and a sig value of 0.975 &gt; 0.05 means that the factor B is not real; interaction results (AB) has a Fhit price of 3.860 &gt; Ftable 3.45 and a sig value of 0.027 &lt; 0.05 means that the factor AB is real.
Research on the Application and Influence of Computer Information Retrieval Technology in Library and Information

Abstract From the beginning of computer information technology to now, the computer technology as the core of information retrieval technology has been widely used in various fields of life. At the same time, with the increasing demand of information users, the application of information retrieval technology in Library and information is gradually explored. It is also found that the application of computer technology in information retrieval can quickly and accurately search out all kinds of books and information needed by users [1] . This paper briefly analyzes the current situation of information retrieval, the evaluation of Library and information research, the application and advantages of information retrieval in Library and information. Finally, the corresponding conclusions are drawn.
The Application of Read-Answer-Discuss-Explain-and Create (Radec) Models to Improve Student Learning Outcomes in Class V Elementary School on Human Respiratory System

This study aims to improve the learning outcomes of students of class V SDN Sukaraja I related to the concept of human respiratory system through the RADEC model. The research subjects consisted of 34 students. The research method used is Classroom Action Research. The instruments used were tests and non-tests. The test instrument was arranged to measure student learning outcomes. Non-test instruments are used to determine the feasibility of learning. The data obtained consisted of qualitative and quantitative data. Qualitative data were analyzed descriptively while quantitative data were analyzed by finding averages and percentages of achievement in each cycle. This research was validated using triangulation techniques. The results showed that RADEC was able to improve student learning outcomes on the topic of the human respiratory system. This is evidenced by the change in the achievement of students' learning outcomes. In the preliminary data, around 40% or as many as 14 students have reached completion. In the first cycle, an increase in completeness reached 65%, or as many as 22 students achieved completeness. In the second cycle there was also an increase in completeness which was around 90% or as many as 31 students had reached completeness
STRATEGIC INFORMATION SYSTEMS PLANNING AND INFORMATION TECHNOLOGY FOR SCHOOL

As a foundation, At-Thoat school has a routine agenda every year, namely the Admission of New Students (ANS). Even though they have implemented by online, they have not been able to realize one day service. The speed and automation of ANS services greatly helps the acquisition of new students. Because competition for new students is competitive. In addition, the number of new students at At-Thoat has also greatly influenced the survival of the school. The solution offered in this study for this problem is to compile a strategic design for Information Systems (IS) and Information Technology (IT) using the Ward and Peppard method, which are design methods capable of producing IS / IT strategies that are in line with business strategies. The first stage in applying this method in this research is the analysis of current conditions, both the organization as a whole and the IS / IT aspect. The next stage is an analysis of IS / IT needs in the future. The final stage is the preparation of IS / IT strategic steps. To analyze each of these stages, analysis tools are needed, namely: SWOT, critical success factor. The implementation of the Ward and Peppard methods and their analytical tools were able to identify and recommend IS / IT needs at At-Thoat School for the next 5 years. However, the resulting recommendations must be adjusted to the priority scale, because of the various limitations faced.