Reviewerly/exHarmony huggingface dataset:
Performance Evaluation of Biharmonic Function-Based Image Inpainting Approach

Image inpainting states to restoring misplaced procedure or damaged regions in an image. Image inpainting is a procedure of returning corrupted and old images. The major intention of this research is to analyze and justify the effectiveness of the image inpainting technique. Accordingly, performance analysis of image inpainting model is performed through Biharmonic functions. Moreover, the analysis is done by varying domain size in the Biharmonic function based on the percentage of images. Here, the performance of Biharmonic functions is evaluated using Structural Similarity Index Measure (SSIM), peak signal to noise ratio (PSNR), universal image quality index (UQI), second-derivative-like measure of enhancement (SDME), multi-scale structural similarity (MS-SSIM), and Mean Square Error (MSE). Thus, from this analysis, it is shown that the Biharmonic functions obtained better performance for the image inpainting process.
IMPLEMENTASI PROGRESSIVE WEB APPS PADA MARKETPLACE

Marketplace is a website or online application that facilitates the buying and selling process from various stores. One of the reasons why the marketplace is famous is because of the ease and convenience of use. Many describe online marketplaces as department stores. The next problem experienced by users, because every smartphone has limitations in installing applications, so the choice to install native applications is considered due to limited resources and can cause smartphone performance to be slow. Using Progressive Web Apps (PWA) can be a solution to overcome the problem where PWA can run like a native application installed on a smartphone. The implementation of the resulting system can help users in online transactions that save smartphone memory and market place applications have been tested on smartphones, resulting in screenshots of the application running as expected.
Generations Rising

Three co-cases convey the voices of generations rising. Feven Girmay compares African immigrants and Detroit students, revealing barriers and opportunities. Jon Reidel chronicles the voices of students, educators, and community activists engaged in uplifting rural communities with high poverty. Dorothea and James Brady share voices of rising generations from students’ essays submitted for a contest in Washington, DC, over three decades. Across chapters, the co-writers exemplify social action, making the world around them a bit better. These co-cases, along with the others in preceding chapters, depict challenges and social action across communities, educational institutions, and nations, creating space for communication and informed action, rather than standardized practice, tested in isolated experiments, and promoted with technological controls. Creating and using these means of engaged co-learning is crucial to empower Gen Z as they face the challenges of promoting equity and ensuring sustainability.
The Influence of Human Capital on Organizational Performance

Currently, the economic downturn in various parts of the world has made human capital increasingly important with increasing globalization and the saturation of the job market.In order to increase economic growth by giving more time and effort, both developed and developing countries place an emphasis on human resource development.To enter the international arena, human resource development is one of the basic solutions.For this, companies need to invest the necessary resources to develop human resources that have a greater impact on performance.This paper reviews the effects of human capital having a direct impact on firm performance from various critical perspectives.Company performance in terms of financial and non-financial performance.Finally, this paper proposes an initial model that explains the relationship between human capital and firm performance.
An Overview of Indian Language Datasets Used for Text Summarization

In this paper, we survey text summarization (TS) datasets in Indian languages (ILs), which are also low-resource languages (LRLs). We seek to answer one primary question—is the pool of Indian language text summarization (ILTS) dataset growing or is there a serious resource poverty? To answer the primary question, we pose two sub-questions that we seek about ILTS datasets—first, what characteristics—format and domain do ILTS datasets have? Second, how different are those characteristics of ILTS datasets from high-resource languages (HRLs) particularly English. The survey of ILTS and English datasets reveals two similarities and one contrast. The two similarities are—first, the domain of dataset commonly is news (Hermann et al. in Adv. Neural Inf. Process. Syst. 28:1693–1701, 2015, [19]). The second similarity is the format of the dataset which is both extractive and abstractive. The contrast is in how the research in dataset development has progressed. ILs face a slow speed of development and public release of datasets as compared with English. We conclude that the relatively lower number of ILTS datasets is because of two reasons—first, absence of a dedicated forum for developing TS tools; and second, lack of shareable standard datasets in the public domain.
An Analysis for the Characteristics of Mathematics Subject in IB DP Theory of Knowledge and Extended Essay Curriculum

This study analyzes the theory of knowledge and the extended essay curriculum of the IB DP curriculum in order to derive implications for the reflection of characteristics of subjects in the cross-curricular curricula. In the IB DP curriculum, the theory of knowledge and the extended essay curriculum are core areas with academic characteristics that can be connected to multiple subjects. The theory of knowledge curriculum was analyzed from the perspective of the nature and ethics of mathematics. The extended essay curriculum was analyzed from the perspective of mathematical inquiry. The theory of knowledge curriculum provides knowledge questions related to mathematics so that students can experience various perspectives on the nature and ethics of mathematics. The extended essay curriculum provides procedures, methods, and cases for students to experience mathematical inquiry. This analysis can be used as basic data for developing curriculum documents and textbooks that can reflect the characteristics of individual subjects in the cross-curricular curricula.
Make It Talk to Other Languages

Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. “Try This!” exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specific homework problems across the sciences and engineering.
Recursion

Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. “Try This!” exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specific homework problems across the sciences and engineering.
AlGaAsOI Photonics and Low-Loss Links for High-Speed Entanglement-Based Quantum Key Distribution

We report a record-high detected entangled-photon pair coincidence rate from an AlGaAs-on-insulator microring resonator with raw coincidence rates &gt; 19 kHz that is capable of time-bin entanglement-based QKD with an estimated secure key rate of 1.4 kbits/second.
Secure Services for Standard RISC-V Architectures

In systems security Trusted Execution Environments have been developed as a mean to offer additional security to existing complex system designs. In the past multiple vulnerabilities have affected TEE implementations like ARM TrustZone and Intel SGX, which is why the research community has been looking to identify and solve existing design flaws. Another branch of computer science looks at RISC-V, a modern processor architecture that allows everyone to use and extend it.
Text Clustering in Python

In this chapter, we learn about clustering and how document and text clustering can be performed. This chapter explains the real-time applications of text clustering and the differences between soft and hard clustering types. The clustering algorithms, including KNN, hierarchical and Fuzzy clustering, were used . Fuzzy clustering or soft clustering types can add better value performance-wise than the other two clustering algorithms. Besides, we also presented how to conduct text clustering in python using unsupervised machine learning techniques. To explain this in detail, the IRIS dataset is considered famous in UCI Machine learning Repository and well presented with python script.
Images Compression using Combined Scheme of Transform Coding

Some problems want to be solved in image compression to make the process workable and more efficient.Much work had been done in the field of lossy image compression based on wavelet and Discrete Cosine Transform (DCT).In this paper, an efficient image compression scheme is proposed, based on a common encoding transform scheme; It consists of the following steps: 1) biorthogonal (tab 9/7) wavelet transform to split the image data into sub-bands, 2) DCT to de-correlate the data, 3) the combined transform stage's output is subjected to scalar quantization before being mapped to positive, 4) and LZW encoding to produce the compressed data.The peak signal-to-noise (PSNR), compression ratio (CR), and compression gain (CG) measures were used to perform a comparative analysis of the performance of the whole system.Several image test samples were used to test the performance behavior.The simulation results show the efficiency of these combined transformations when LZW is used in the field of data compression.Compression outcomes are encouraging and display a significant reduction in image file size at good resolution.
"Comparable Recipes"

Recording high-quality textual recipes is effective for documenting food culture. However, comparing the quality of various recipes is difficult because recipe quality might depend on a variety of description styles and dishes. Therefore, we constructed the following "Comparative Recipes" dataset. First, each of the 64 writers described five recipes after watching five home cooking videos. A total of 318 recipes were created. For each dish (video), there were 15.9 recipes on average, and each recipe was described by a different writer. Next, 335 recipe readers evaluated the quality (i.e., the reproducibility and completeness) of each recipe. A morphological analysis that used this dataset revealed that the amount of description per cooking step affects recipe quality. Furthermore, the effects of cooking procedures being integrated into cooking steps on recipe quality tended to be dependent on the reader's skill. The results suggest a need for description support that appropriately integrates cooking procedures into cooking steps according to the skills and preferences of the reader.
Analysis of the Relationship Between Teachers' Teaching Methods and Middle School Students' Self-Concept, Career Maturity, and Creative Thinking Ability

This study analyzed the structural relationship between teachers' teaching methods and middle school students' self-concept, career maturity, and creative thinking ability, and verified the mediating effect of self-concept and career maturity on the relationship between teachers' teaching methods and creative thinking ability. For this purpose, data from the second year of middle school in the 4th year of 「Korean Educational Longitudinal Study 2013」 of the Korean Educational Development Institute was used. To verify the structural relationship between the variables, a total of 6,326 data were analyzed using the structural equation modeling, and the mediating effect was verified through bootstrapping. As a result of the study, the direct effect of the teacher's teaching method on self-concept and career maturity was statistically significant, but the direct effect of the teacher's teaching method on creative thinking ability was not statistically significant. On the other hand, the teacher's teaching method was found to have a statistically significant indirect effect on creative thinking ability through self-concept and career maturity. These results suggest that there is a limit to improving students' creative thinking ability only with the teacher's teaching method, and creative thinking ability can be improved through students' personal characteristics such as self-concept and career maturity. Therefore, in order to improve students' creative thinking ability, teachers' teaching methods need to be designed in consideration of students' self-concept and career maturity.&#x0D;
Analysis of the Potential Benefits from Using Quantum Computing for Aerospace Applications

This paper discusses the benefits that can be enjoyed from the possible application of quantum computing to the aerospace sector. It discusses these benefits for various tasks and applications such as artificial intelligence, cryptographic key distribution and simulation. The challenge of determining what aerospace application computations will be best allocated to quantum devices is also discussed. The method for best utilizing quantum computing for aerospace applications is considered and the benefits of a grid-based implementation of computational resources are discussed. The grid model of having a collection of network-connected heterogenous devices could be used as a way to make effective use of computational resources. It could be used for the operations and development of simulations as well as machine learning and other software applications. This paper also presents a summary of potential use-cases, as well as a discussion of the work necessary to expedite the process of quantum computing development.
DECISION SUPPORT SYSTEM BY USING MULTIPLE ATTRIBUTE DECISION MAKING WITH SIMPLE ADDITIVE WEIGHTING METHOD (MADM-SAW) METHOD IN SELECTING THE BEST BROMELAIN

Bromelain is a protease enzyme obtained from pineapple. In choosing bromelain only pay attention to its chemical analysis and there is no rank yet. Therefore, research has been carried out in making the best bromelain decision using the Multiple Attribute Decision Making with Simple Additive Weighting Method (MADM-SAW) method based on the shelf life of pineapples. The basic concept of this method is to find the weighted sum of the performance branches for each alternative (treatment) of all attributes so that the best alternative will be obtained in the selection of crude bromelain enzymes based on pineapple storage. The results showed that the best pineapple fruit was with storage of day 0 as rank 1, with a total value was 0.9025.&#x0D;
New Payment Method by Blockchain: Potential Value of Cryptocurrency Bitcoin Platform

In succession to have an care of the potency depletion of cryptocurrency, it is far-reaching to rudimentary tell the difference the diligence behind the cryptocurrency platform, Blockchain.rudimentary created by Satoshi Nakamoto in 2008, Blockchain is the theatrical of the non-centralized depletion development platform.The contemporary destination was to establish an electronic depletion development backed on cryptanalytic verification as an additional of trustingness.The considerables potency of victimisationing Blockchain is that additional to tally to methamphetamine up a discrete, transparent, and each the bounteous tomfool proof.On the administration of Google statistics, bitcoin searches through examine nailed down contemplate are insurrection in 2017 in severals political entity on each sides flanks of the world.Furthermore, sea-chart characteristic particulars that bitcoin purchasers methamphetamine up two-folded every amplitude on explanation of 2013.Currently, sea-chart fundamental make evident a brobdingnagian comparative relation of searches through examine nailed down contemplate are principally stemming from neighbourhoods all the more as Africa and the Baltic region.The interestingness of cryptocurrency and digital omnipotent buck has dilated to nonindustrial political entity in Asia, all the more as severals political entity in partnership that tally pretence modifications and legality of digital assets property dimethyl ketone transactions, there are each the bounteous whatever political entity that methamphetamine up officially if tractableness for their human beings to legitimately exploitation the digital assets.
A Regional Logistics Demand Forecasting Method using KPCA-GA-ELM

Logistics demand forecasting works as a basis for well operated city governance especially for e-commerce industry. Yet, how to accurately predict the local logistics demand remains further improvement. To deal with it, this paper proposed an KPCA-GA-ELM approach which firstly introduces an extreme learning machine (ELM) approach to build the forecasting model, then incorporate both kernel principal component analysis (KPCA) and genetic algorithm (GA) into it. Taking Shanghai's regional logistics demand prediction as an example, two principal components affecting regional logistics demand are extracted by KPCA, ELM is then used to develop a regional logistics demand forecast model, and the genetic algorithm was applied to make the ELM model arguments be better to avoid the impact of strong randomness in parameter selection on model prediction performance and generalization ability. The results indicate that the accuracy is significantly improved comparing it with other two models. Such model then can be used as the demand forecasting and estimation approaches to estimate the demand of other industries in a region.
Leveraging Backend Servers

In this chapter, we will introduce a more sophisticated and scalable way of designing web applications. Specifically, this chapter will present the process to offload the overhead associated with managing databases from the Streamlit server and onto an independent backend server as it should be in a full-stack environment. To that end, this chapter will walk the developer through the entire process of provisioning a backend server in Python that acts as the middleman between the database and the frontend. And finally, the developer will be acquainted with the workings of a highly modular, versatile, and secure architecture with additional security layers between the application and database.
Supplemental Material: Quantifying controls on the occurrence of nonmarine fossils

&lt;p&gt;Data files and R scripts needed to generate the graphs seen in Figures 3 and 4: ‘fossilCounts.csv’ contains data used to calculate the probability of occurrence; ‘probabilityOfOccurrenceFunctions.txt’ contains the R code for helper functions used in figure creation; ‘probabilityOfOccurrenceGraphs.txt’ contains the R code workflow used for calculations and for generating Figures 3 and 4. &lt;/p&gt;
Review of enterprise data management infrastructure, and policies of the Korea National Park Service

Based on the results of the recent〝4th Korea National Park Service Information Strategy Plan〞 establishment and related laws and policies, we want to understand the current level of data management in Korea National Park Service. As a result of confirming the level of enterprise-wide data quality management using the data profiling technique, it is difficult to secure data standard or structural consistency, and the basis for data quality management such as guidelines, manuals, organization and budget is insufficient. The company-wide data of the National Park Service should be managed to ensure accuracy, consistency, timelessness, and completeness, and to realize this, an implementation plan is established according to the data quality management framework.&#x0D;
Searching Top-K Similar Moving Videos

The application of sensors enables mobile devices to generate amounts of content-aware data, such as trajectory, gyro, and video data. Moving video is an emerging new type of moving object that can provide a potential source for geo-referenced applications. Measuring the similarity of moving videos is widely used in traffic management, tourist recommendations, and location-based advertising. Our prior work proposed two similarity measures, the Largest Common View Subsequences can accurately calculate similar moving videos, and the View Vector Subsequences can fast calculate similar moving videos. In this paper, we proposed the searching top-k similar moving videos (K-SSMV). First, we give the problem definition of searching top-k similar moving videos. Then, we illustrated the strategy of searching for moving videos. Specifically, we sorted the video pairs by the most similar videos. Since the similar videos would be less than k, we first calculated the similarity of moving videos by the Largest Common View Subsequences algorithm, if the number of similar videos is less than k, we will adopt the View Vector Subsequences algorithm to compute the similarity of moving videos. Next, we mixed the candidate videos calculated by the Largest Common View Subsequences and the View Vector Subsequences algorithms, the searching top-k similar moving videos algorithm picked the top-k similar videos from candidate videos. Finally, we evaluated the performance of our proposed algorithms on the accuracy and computational cost. The experiments verified that our algorithms can efficiently search top-k similar moving videos.
Empathy Mapping

The empathy map canvas is a great tool to use for capturing thoughts while thinking about your users.
Research on In-Memory Database and Technology Selection

Technology serves business. The selection of in-memory database should first follow the requirements of business scenarios. Service characteristics determine the application characteristics of data, including the amount of data, concurrency, read/write characteristics, consistency, response time, operation complexity, and service continuity, and the technical requirements for database consistency, fault tolerance, scalability, and security. Before selecting the memory database, it is recommended to sort out the business requirements and quantify them. Then map the core data application characteristics to database technical requirements; finally, select the type according to the selected technical requirements.