Reviewerly/exHarmony huggingface dataset:
The Impact of Training and Development on Organizational Performance

The purpose of this study is to determine the impact of training and development on organizational performance in order to figure out how the training and development (on-the-job training, off-the-job training, job rotation) can give an impact on organizational performance. The study has been conducted at three selected departments in a government office, which are Management Services, Corporate, and Human Resources Management. The quantitative approach has been adopted, in which a questionnaire has been used to collect and analyze data. 103 questionnaires have been distributed by using Google Form to respondents and returned to the researchers with complete information. The reliability and validity have been checked by using the SPSS and the results have been evaluated. The findings indicate that all the three hypotheses are accepted.
Problems and Countermeasures of the Internal Control of Monetary Funds: A Case Study of Foshan Lighting

Monetary fund is the most fundamental element for enterprises to engage in production and lucrative business activities, which has an impact on the operation process and outcomes. Therefore, enterprises must regard fund management as one of their key management links and establish an effective and practical internal control system. However, sensational cases such as the collapse of Barings Bank have exposed many problems existing in the internal control of monetary funds. Moreover, the high liquidity of funds itself engenders them as the target of embezzlement and self-interest, which will eventually threaten the company’s wealth. Therefore, it is significant to analyze the problems existing in the internal control of monetary funds and provide corresponding solutions to them.
Operational entanglement-based quantum key distribution in real-field

We present a fully operational, real field quantum key distribution link based on entanglement over 3 sites in the city of Nice for a total distance of deployed optical fiber of 50.0km.
Computing Maximal Covers for Protein Sequences

A partial cover of a string or sequence of length n, which we model as an array , is a repeating substring u of x such that “many” positions in x lie within occurrences of u. A maximal cover u*—introduced in 2018 by Mhaskar and Smyth as optimal cover—is a partial cover that, over all partial covers u, maximizes the positions covered. Applying data structures also introduced by Mhaskar and Smyth, our software MAXCOVER for the first time enables efficient computation of u* for any x—in particular, as described here, for protein sequences of Arabidopsis, Caenorhabditis elegans, Drosophila melanogaster, and humans. In this protein context, we also compare an extended version of MAXCOVER with existing software (MUMmer's repeat-match) for the closely related task of computing non-extendible repeating substrings (a.k.a. maximal repeats). In practice, MAXCOVER is an order-of-magnitude faster than MUMmer, with much lower space requirements, while producing more compact output that, nevertheless, yields a more exact and user-friendly specification of the repeats.
Frequency-bin Bell state generation via successive single and dual spectral-line pumping

We demonstrate a simple and versatile scheme to generate all four two-dimensional frequency-bin Bell states using single and dual spectral-line pumps and passive filtering. Experimentally, we measure ≥ 97% fidelity for all states.
Cross-Gain Modulation-Based Reservoir Computing Using Membrane SOAs on Si-MZI

We solve the Santa-Fe prediction task with reservoir computing utilizing cross-gain modulation in membrane semiconductor optical amplifiers (SOAs). SOAs are heterogeneously integrated on each arm of Si-based Mach-Zehnder interferometer to spatially separate the input/output ports.
Bioinspired Multi‐Transformability of Superhydrophobic Nano‐Magnetite Swarm for Adaptive Object Transportation (Adv. Funct. Mater. 32/2022)

Adaptive Materials In article number 2204681, Mizuki Tenjimbayashi and Masanobu Naito develop a superhydrophobic nano-magnetite swarm that imitates a fire ant superorganism. The swarm at the liquid–air interface is transformed from a dispersed state into a 2D raft and a 3D bivouac by magnetic field gradient. The swarm can adaptively transport small objects irrespective of their state (gas/liquid/solid) by switching their state.
Amgen Foundation expands commitment to science education

Corporate Philanthropy ReportVolume 37, Issue 9 p. 3-3 News Briefs Amgen Foundation expands commitment to science education First published: 08 August 2022 https://doi.org/10.1002/cprt.31361Read 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 No abstract is available for this article. Volume37, Issue9September 2022Pages 3-3 RelatedInformation
Installing MariaDB and Creating a Simple Web Application

In Chapter 5 , you deployed three of the four pieces necessary for your LAMP stack, and you learned how Apache and PHP can work together on a Linux host to serve up dynamic content. In this chapter, you’ll add the database component: MariaDB. The simple application you’ll create will read some information from a database table and show it in a browser.
Vacant Car Parks Detection Using Digital Image Processing Methods

Long car queues are often encountered in some public facilities because visitors should be around to find an empty parking space. One way to minimize this case is to use a parking information system that shows the location of the parking lot that is empty or occupied with their amounts. This research presented two digital image processing methods for detecting empty space occupied in the image of the car parking area. There are vehicle detection and edge detection method. Vehicle detection is the method used to detect objects in the image by subtracting the parking area image, an empty parking lot, from the image containing the car. In contrast, the edge detection method detects the object's edge. The results from these two methods were then compared using the AND function to obtain the condition of an empty or occupied box for each box in the parking lot. Threshold values affect the determination of the parking lot. In this research, the data used are images of open car parks in the Malang Town Square (Matos) shopping center, Mall Olympic Garden (MOG), and data sourced from journals with similar topics [16]. The test results show that the best detection results are obtained in detecting occupied parking spaces in the parking lot in Malang Town Square (Matos), with a threshold of 10 and an accuracy of 99.4% with a threshold of 10.&#x0D;
Compliance Against Computer Crimes

The new systems of legal persons criminal responsibility represent, despite its controversial nature, useful tools to engage the companies in the crimes prevention. However, these systems can also encourage many companies to establish some preventive measures, such as the permanent monitoring of all the Internet activities of their workers, or the automatic erase of any information seeming illegal published from their servers, that not only can avoid many possible criminal behaviours, but also can get in direct conflict with some fundamental rights and warranties of citizens. In these cases, numerous and difficult legal problems are set out. Problems that this essay attempts to bring to the light in order to look for solutions for them.
The Fourth Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2022)

Adversarial learning methods and their applications such as generative adversarial network, adversarial robustness, and security and privacy, have prevailed and revolutionized the research in machine learning and data mining. Their importance has not only been emphasized by the research community but also been widely recognized by the industry and the general public. Continuing the synergies in previous years, this third annual workshop aims to advance this research field. The AdvML'22 workshop consists of four tracks: (i) open-call paper submissions; (ii) invited speakers; (iii) rising star awards and presentations; and (iv) panel discussion on AdvML. The full details about the workshop can be found at https://sites.google.com/view/advml.
Preparation of entanglement coherent states based on bimodal QED

We have theoretically investigated the physical realization of entangled coherent states using cavity quantum electrodynamics. Specifically, a protocol of the cyclic three-level atoms interacting with bimodal cavity QED is proposed. The results show that the entanglement degree of the entangled state can be maintained at a high level under certain conditions.
Problem-driven Understanding in Augmented Reality: The Effects on Learning Engagement and Writing Achievement

To solve a series of problems arising from the application of augmented reality in writing teaching, this study designed a problem-driven comprehension teaching strategy and used an empirical research method to explore the effects of problem-driven understanding teaching and instructional teaching in an augmented reality environment on elementary school students' learning achievement and learning engagement in Chinese writing, as well as teachers' and students' satisfaction with problem-driven understanding teaching in an augmented reality environment. The study found that problem-driven understanding instruction in augmented reality can alleviate the problem of low student learning engagement caused by the application of augmented reality in teaching to a certain extent; and can promote students' learning achievement in writing, especially in the three dimensions of completeness, correctness.
Research on the Impact of Virtual Reality Environment on Primary School Students’ Classroom Interaction Behavior from the Perspective of Double-Cycle Theory

There are lack of problems in traditional writing teaching for real context experience and perception, and the virtual reality (VR) to support students support students' participation in enthusiasm and writing literacy. Therefore, the article has passed the use of quasi-experimental research, incorporates the double-cycle teaching concept, and randomly distributes 97 primary school students as experimental groups and control groups, in VR, PPT learning environment, and uses the lag sequence analysis method. Differences in the Interactive Effect of Classroom Teachers and Students in Different Learning Environments. The research results show that the VR-based writing learning environment can promote students' class interaction; the integration of dual cycle teaching concept has promoted VR in writing classroom applications, making teaching models and teaching technologies.
CartelChain: A Secure Communication Mechanism for Heterogeneous Blockchains

In this work, we propose &#x2013; "CartelChain" &#x2013; for the secure communication of blockchains (BCs) and achieving opti-mal throughput. With the advancement of BC technology, many industries are adopting it to maintain a secure, immutable, and decentralized system. Industries such as IoT, supply chain, and finance apply BC technology to maintain a decentralized database and automate different activities using smart contracts. However, storing data of different scenarios from the Industrial Internet of Things (IIoT) in separate BCs (multi-chains) leads to isolated data islands. This results in difficulty for these multi-chains to interact with one another efficiently and credibly. For the seamless operation of industries, it is of significant importance to achieve interoperability among different BCs. Toward achieving this, we propose a solution that utilizes smart contracts for enabling data exchange among various BCs. Further, for secure and reliable communication, we use encryption and an access control mechanism that makes the same more credible and reduces the latency compared with multi-chains sharing the data sequentially. Through experimental results, we demonstrate that the proposed method can utilize the resources more efficiently and reduce CPU as well energy usage by 8% and 6%, respectively. Apart from this, the throughput of the proposed method is 900 tps at 200 requests.
Badge: Blockchain-Assisted Secure Authenticated Data Transmission in Mobile Edge Computing

In mobile edge computing (MEC) systems, data is frequently transmitted between MEC servers and mobile devices for supporting related services. However, critical threats towards data confidentiality and authenticity are raised, where adversaries always attempt to extract data content from the transmission and impersonate others to spread malicious data for profits. In this paper, we propose a blockchain-based authenticated data transmission scheme, dubbed Badge, to establish secure channels between MEC servers and mobile devices. Badge is based on a blockchain-based authenticated hybrid encryption mechanism, which frees MEC servers from maintaining devices’ certificates and allows them to encrypt/decrypt a large volume of data in a highly efficient way. We present security analysis to demonstrate that Badge achieves data confidentiality and authenticity. We conduct a comprehensive evaluation to demonstrate that Badge is efficient and practical to deploy.
The Role and Value of Research Outputs in Coproducing Research With Communities

Coproduced research aims to bring university researchers, community members, and organizations together to create new knowledge, share findings, and develop meaningful research outputs. While there is a growing body of work exploring the processes and methods of coproduction, little attention has been paid to the role and value of the outputs of coproduced research. This article addresses this gap in the literature by considering the value and role of a range of outputs developed via a coproduced community history research project. This article suggests that research outputs fulfill a number of key functions in addition to disseminating findings. Research outputs help collaborators make sense of a project and support the development of research skills and knowledge. Developing outputs also provides space to recognize individual interests and skills, build a collective vision, and help people recognize their own expertise. The article argues that research outputs are fundamental to the process of coproducing research, not simply its end result, and suggests that coproduced research outputs should be viewed as a site of research practice and knowledge production.
User Requirements and Usability Testing on a Mobile Application for Food Ordering Canteens

Introduction: In today’s competitive world, people are rushing for meals between work. A long-time queuing to wait for orders is not a good option. Furthermore, the pandemic situation has forced people to avoid crowds or close physical contact, resulting in the demand for food ordering applications. Existing applications, however, lack customization to specific consumer demands, such as the unique requirements for school students during a pandemic. Furthermore, there is currently little to no evidence-based information accessible about their quality. Thus, this study was conducted to identify requirements to cater for the supply and demand for food and beverages during school hours. Methods: In order to assess quality, a usability assessment was conducted using 15 usability test questions with school students and canteen operators (n=50). The testing protocol comprised pre/post-test surveys, a structured interview and task-performance (n=9) observation. Results: The Efficiency test shows most tasks were more than 90% of the time completed successfully with minimal errors. With a threshold of 78%, eight out of nine tasks were considered effective. Also, a score of more than 85% dominates the satisfaction tests, with an average mean of 4.54. An average score of 91% on the usability scale demonstrated excellent perception of the application’s usability. The result also provides several recommendations for improvement. Conclusion: The ultimate design of the application is targeted to receive good acceptance and meet the users’ demand. This will promote an efficient supply and demand system and improve the quality of life for consumers and canteen operators.
Error Mitigation Methods in Track Reconstruction of ICARUS [Poster]

new deep learning models for reconstructing tracks using space-point data arranged as sequences or connected graphs. In the first set of models, Recurrent Neural Networks (RNNs) are used to extrapolate, build, and evaluate track candidates akin to Kalman Filter algorithms. Such models can express their own uncertainty when trained with an appropriate likelihood loss function. The second set of models use Graph Neural Networks (GNNs) for the tasks of hit classification and segment classification. These models read a graph of connected hits and compute features on the nodes and edges. They adaptively learn which hit connections are important and which are spurious. The models are scaleable with simple architecture and relatively few parameters. Results for all models will be presented on ACTS generic detector simulated data.
Study of clustering methods of Linac outages: K-Means vs G.M.M [Poster]

kind of intermediate form which provides some measure of data compression. Traditional image segmentation algorithms treat pixels independently and cluster the pixels according only to their spectral information. This neglects the implicit spatial information that is available in the image. We will suggest a simple approach; a variant of the standard k-means algorithm which uses both spatial and spectral properties of the image. The segmented image has the property that pixels which are spatially contiguous are more likely to be in the same class than are random pairs of pixels. This property naturally comes at some cost in terms of the compactness of the clusters in the spectral domain, but we have found that the spatial contiguity and spectral compactness properties are nearly orthogonal, which means that we can make considerable improvements in the one with minimal loss in the other.
PENERAPAN MEDIA GAMBAR DALAM PEMBELAJARAN PAI PADA ANAK USIA DINI

This study has the potential to enrich educational information, especially in the field of educational technology, and determine visual media and their strategic value for teachers, parents, students, and education practitioners in the school itself. . This type of survey is a qualitative field survey using a descriptive survey method. The data collection method was obtained by using: 1). Observation, 2). Job interview, 3). documentation. Although the data analysis method used is descriptive qualitative. The results showed that the visual media used in PAI learning at RA Nurul Mu'minin Bojonggenteng were still images in the form of posters, caricatures, and cartoons. Video media that are films and VCD images are combined with television. Visual media RANurul Mu'minin Bojonggenteng is used to make teaching methods more communicative and effective. The application of visual media in PAI PAI learning at RA Nurul Mu'minin Bojonggenteng has been successfully implemented.
HEALTH CARE CHATBOT

Chatbots mimic human speech to make the software more user-friendly or just for amusement purposes. NLP (Natural language Processing) and AI (Artificial intelligence) are new emerging technologies that can be utilized to improve the capacity of chatbots to stimulate a more natural and free-flowing conversation. Chatbots can be used to offer customers support and services as more and more mobile device users switch to more frequent use of texts and messaging Healthcare chatbots provide a customized experience to each user in ways that may be more practical and effective than humans are capable of. By communicating with consumers in a human like manner, a medical chatbot enhances the work of a healthcare professional and aids in enhancing their performance. Medical chatbots are conversational AI-powered tools that facilitate communication between patients, insurance providers, and health care professionals. These bots can be quite useful in providing timely access to pertinent healthcare information to the appropriate parties. We discuss current chatbot research and uses in the fields of medical and health care education, our main areas if concentration includes the use of virtual patients in medical education patient education regarding healthcare issues, and the use of chatbots as course assistants to improve the curriculum for healthcare professionals. Because of their mobility and affordances, chatbots are increasingly being used into the teaching and learning processes in the field of healthcare education. Clients of this application have discussions with the wellbeing chatbot likewise to how they would have discussions with different clients. Through a series of questions, the health chatbot helps people identify their symptoms in order to assist them decide whether or not to see a doctor. People who are unsure of whether their symptoms are temporary or call for further testing from a doctor may find this.
TOPOLOGICALLY ENTANGLED ENERGY AS A MODEL OF ELEMENTARY PARTICLES

Despite the fact that many mathematical models of elementary particles have already been created in theoretical physics, this question still remains open, because a model of an elementary particle that would meet all the requirements and experimental data has not yet been found. We decided to propose another model of elementary particles, which in our opinion is one that correlates well with the results of observations. Our model is that an elementary particle is an energy that takes on a topologically entangled shape. Elementary particles differ not in the energy that makes them up, but in the form in which this energy circulates. If this topological form can unravel under some circumstances, then the particle will not be elementary. If this form is such that it is impossible or very difficult to unravel it under any circumstances, then this particle will look stable as a result of our observation in experiments.
ANALYSIS OF DATA EXCHANGE BETWEEN ENTERPRISES BY USING BLOCKCHANE TECHNOLOGY IN INFORMATION SYSTEMS

Nowadays information systems for productions and shipments management become more complicated with the further development of international and domestic trades, increase of complexity of production and supply chains and etc. Therefore, the task of researching and designing new approaches for supply chains and logistics information systems becomes relevant for the solution. In this paper possible pros and cons of using blockchain technology in logistics and supply chain systems are reviewed. Blockchains can help to simplify and make more transparent the processes of monitoring and managing production and movement of goods between different entities. But also, there are several challenges which need to be solved such as software upgrades possibilities in smart-contracts and tasks of designing the complete blockchain-based system which will actually solve important problems in this area in the most effective way without critical problems.