Reviewerly/exHarmony huggingface dataset:
Accounting Information System for Non-Subsidized Fertilizer Sales at PT Petrokimia Gresik

Nowadays, knowledge is essential in all aspects of human life. Decisions need to consider information. The higher the quality of knowledge, the more effective the decision-making. The objectives this study are to analyze the accounting information system of on-subsidized fertilizer sales Petrokimia Gresik. This study uses a qualitative method, and the scope of analysis focuses on the non-subsidized fertilizer sales accounting information system. The data acquired from observation and documentation. The data collection from preliminary surveys, literature studies, and field surveys, then analyzed using flowcharts. The results of this research propose a new flowchart that uses an input-process-output method for the non-subsidized fertilizer sales accounting information system. This research shows that in other organizations with unique characteristics, the suggested systematic approach can be applied.
Extension of measurement area of stereo deflectometry

Stereo deflectometry can specify the position of a workpiece and reduce the difficulty of geometrical calibration. But the measurement scope is limited, and this issue is especially severe for the measurement of complex surfaces. A method is proposed to extend the measuring scope of stereo deflectometry. The nominal model of the surface under test is aligned with the overlapped measurement area of the stereo vision system, and the other areas outside overlapped region are measured using the monoscopic SCOTS approach with each camera, respectively. This method effectively combines the advantages of stereo and monoscopic deflectometry, and the measuring accuracy and flexibility can be improved.
ADHAAR: A reliable Data Hiding techniques with (NNP2) Algorithmic Approach using X-ray images

The technique which is most important for the Reversible Data Hiding (RDH) is Prediction Error Expansion (PEE) through this we can hide large messages into digital media with little distortion.The Nearest Neighborhood Pixel Prediction (NNP2) algorithm which goes under the process of the Rhombus prediction and Chinese Remainder Theorem (CRT).In which these several methods are used for the prediction errors, variation of prediction and pixel are used to embed data.The combined Chinese Remainder Theorem as well as Rhombus prediction provides better quality output rather than traditional one.For embedding several bits into one embeddable pixel the size have to be modified and adjusted using Chinese Remainder Theorem (CRT).The distortion level is reduced by Histogram Shifting (HS).The performance of proposed method is evaluated using PSNR for number of medical images.The simulation results provide the best encoded capacity as well as good image pattern than ancient techniques.
A Visualized Analysis of the Research Literature on Early Childhood Family Education in China

As the most important place for preschool children to grow and learn, family has a great impact on the physical and mental development of preschool children.What is the development process and current status of early childhood family education in China?It is very necessary to visually analyze research status, hotspots and trends of Chinese early childhood family education research field.The quantitative and visual atlas of research literature provide an effective analytical approach for the development of research field.The research data is from CNKI which is the largest and most authoritative literature database in China.The research tool CiteSpace analysis software is used to conduct quantitative analysis on the source data and calculate the core authors, institutions, research hotspots and frontier.Research hotspots and frontiers in the field of early childhood family education in China calculated by CiteSpace software include home-kindergarten cooperation research, rural preschool left-behind children family education research, preschool floating children family education research and preschool children parental education research.Literature content analysis as a qualitative research method makes an in-depth interpretation of research hotspots and frontiers on the basis of quantitative analysis, in order to understand the status quo of Chinese early childhood family education.
A New Method for OTP Generation

Nowadays, one time passwords (OTPs) are very important for many authentication applications, whether it is financial transactions, e-commerce, or anything like that. It has been observed that sometimes OTPs become predictable and the security of the entire system becomes vulnerable. Keeping this problem in mind, we present a new OTP generation scheme using Vigenère cipher. We know that randomness and unpredictability are the strength of any OTP. We show that the generated OTPs from the proposed method are highly random and extremely difficult to predict and hence useful in various applications. The reason for selecting Vigenère cipher is that we want to prove a point that very simple old algorithms (keeping computational overheads as low as we can) can also be used to generate random OTPs that are impossible to find.
Know (all!) your assumptions, investigate the sensitivities: Towards more rigorous thermal history modeling practices

Earth and Space Science Open Archive PosterOpen AccessYou are viewing the latest version by default [v1]Know (all!) your assumptions, investigate the sensitivities: Towards more rigorous thermal history modeling practicesAuthorsKendraMurrayiDNathanNiemiiDSee all authors Kendra MurrayiDCorresponding Author• Submitting AuthorIdaho State UniversityiDhttps://orcid.org/0000-0003-4008-1645view email addressThe email was not providedcopy email addressNathan NiemiiDUniversity of MichiganiDhttps://orcid.org/0000-0002-3380-3024view email addressThe email was not providedcopy email address
Cybercrime in the Economic Space: Psychological Motivation and Semantic-Terminological Specifics

The article reveals the essence of cybercrime, approaches tounderstanding this concept, classification of cybercrime, and otherillegal acts in this area. The concept of cybercrime has multidiscourse nature and a certain legal uncertainty. Cybercrimes, theirforms and types are analyzed in the economic context. Theresearch vocabulary of the economic industry is defined. Thescope and content of concepts denoted by the terms of the spherecovered by cybercrime are studied, and its types and forms areanalyzed. The article studies problems, achievements, andprospects of resisting and combating cybercrime during thedevelopment of the civil information society and Ukraine's entryinto the global information space. The study focuses on theeconomic motivation of most cybercrimes since some materialbenefit from the fact of cyber offenses is assumed directly orindirectly
Local risk managers’ and disaster volunteers’ awareness of, attitudes toward, and intention to use a local government-developed disaster information system: A Case study of SIKK Magelang

Abstract SIKK (Sistem Informasi Kebencanaan Kabupaten or Regency Disaster Information System) Magelang is a disaster information system developed by local government in Magelang Regency to support disaster management. Despite having useful features, as with many e-government services, it shows a low adoption rate. This paper aims to explore the barriers impeding the adoption of SIKK Magelang from the perspective of local risk managers and disaster volunteers. Preliminary data were gathered by scrutinizing related disaster management documents and SIKK Magelang reports and interviewing the information system’s operators. Next, a half-day workshop was conducted with the help of BPBD (Badan Penanggulangan Bencana Daerah) of Magelang Regency to assess local risk managers’ and disaster volunteers’ awareness of, intention to use, and attitudes toward SIKK Magelang. Of the 150 people invited, 112 attended the workshop; however, 107 participants could be analyzed. We found that participants had a low awareness of SIKK Magelang and were unfamiliar with the disaster information system. After the trial session, however, they had positive attitudes toward the information system and were willing to use it in the future, especially in the context of supporting their disaster-related tasks. Our findings indicate that SIKK Magelang has the potential to be more widely used by local risk managers and disaster volunteers. More effort should be put into promoting SIKK Magelang, such as producing a clear tutorial.
Developing an inkjet printer III: Multibit CMY halftones to hardware-ready bits

Nowadays, inkjet printers are widely used all around the world. But how do they transfer the digital image to a map that can control nozzle firing? In this paper, we briefly illustrate that part of the printing pipeline that starts from a halftone image and end with Hardware Ready Bits (HRBs). We also describe the implementation of the multi-pass printing method with a designed print mask. HRBs are used to read an input halftone CMY image and output a binary map of each color to decide whether or not to eject the corresponding color drop at each pixel position. In general, for an inkjet printer, each row of the image corresponds to one specific nozzle in each swath so that each swath will be the height of the printhead [1]. To avoid visible white streaks due to clogged or burned out color nozzles, the method called multi-pass printing is implemented. Subsequently, the print mask is introduced so that we can decide during which pass each pixel should be printed.
A Survey of the Proof-Theoretic Foundations of Logic Programming

Abstract Several formal systems, such as resolution and minimal model semantics, provide a framework for logic programming. In this article, we will survey the use of structural proof theory as an alternative foundation. Researchers have been using this foundation for the past 35 years to elevate logic programming from its roots in first-order classical logic into higher-order versions of intuitionistic and linear logic. These more expressive logic programming languages allow for capturing stateful computations and rich forms of abstractions, including higher-order programming, modularity, and abstract data types. Term-level bindings are another kind of abstraction, and these are given an elegant and direct treatment within both proof theory and these extended logic programming languages. Logic programming has also inspired new results in proof theory, such as those involving polarity and focused proofs. These recent results provide a high-level means for presenting the differences between forward-chaining and backward-chaining style inferences. Anchoring logic programming in proof theory has also helped identify its connections and differences with functional programming, deductive databases, and model checking.
How Organizational Climate Mediates Employee Innovative Work Behavior among Food Manufacturing Industries in COVID-19 Pandemic: Implications to Business Economics and Management

In this context, the study explored the relationship between organizational climate and employee innovative work behaviour among food manufacturing industries in Malaysia. The study is a descriptive correlational survey research design where data is sourced out from a total of randomly sampled 260 employees. Results revealed that a favourable organizational climate on innovation, proactivity, and risk-taking is prevailing among the companies. A very high level of innovative work behaviour is emanating among the employees on idea exploration, generation, championing, and implementation. Test of differences showed that employee gender, position, unit, and years of service spelt significant differences in the perception of the employees on organizational climate and innovative work behaviour. A meaningful relationship surfaced between organizational climate and employee innovative work behaviour, suggesting that for food manufacturing industries to sustain innovative and competitive advantages, there is a need to promote a nurturing and encouraging entrepreneurial organizational climate. Finally, a congruency among the domains of organizational climate and employee innovative work behaviour emerged. It suggests that when higher positive organizational climate surfaces, the more likely the employee's manifest innovation work behaviour. This study addressed the gap by providing organizational climate and employee innovative work behaviour among food manufacturing industries in Malaysia.
Utility-based Scheduling Solution for Scientific Workflow on Cloud

Cloud computing has emerged as a promising platform to execute scientific workflows. The size of such workflows could reach up to thousands of tasks, which have data dependency constraints. Accordingly, optimising the utilisation of the used resources is an essential factor in reducing the execution time and cost. This paper presents a Utility-based Algorithm (UBA) that works by assigning tasks to VMs based on a utility function that aims to minimise the execution cost and time. The results showed that the UBA had a significant impact on reducing the execution cost and makespan.
Analysis of Various Boosting Algorithms Used for Detection of Fraudulent Credit Card Transactions

The finance sector has a major role to play in present-day generation, where almost every individual has to deal with banking either physically or online. New advances in e-commerce have made the credit card the easiest mode of payment, thus showing steep rise in fraudulent transaction as well. This is now a major point of concern as it can result in an annual loss of billion of dollars to banking sector. With the advent of Internet, technology studies are conducted that utilize various machine learning models to detect and analyze fraud. Therefore, this leads to the development of efficacious model for the prediction of fraudulent transactions. This paper analyzes the standard models of machine learning and then boosting algorithms (ensemble technique) are analyzed to find out which perform more accurately and precisely to predict fraudulent transaction. On analyzing the outcome, it was examined that boosting algorithms gives better results.
Malicious URL Detection System Using Combined SYM and Logistic Regression Model

In this paper, we have discussed our skills in training and testing of a malicious uniform resource locator detecting system. there have been many trends in the technology and security which inspire our analysis. First, being online has grown to be a progressively dangerous place for many people. In 2011, according to Symantec, there is an increase in internet attacks by 36%. This interprets into roughly 4,500 attacks on a daily basis. Second, there is a vital growth in personal and enterprise use of mobile for the internet. In 2012, according to the State of quality Survey by Symantec, it was noted that after principally proscribed by IT, mobile phones are getting used currently by much immeasurable staff throughout the planet. Online vulnerabilities are on the rise with the employment of smart phones and devices for every personal and skilled usage. This research targets machine learning answers to identify malicious uniform resource locators employing a combination of URL lexical options, payload size, and python supply options. we tend to use Support Vector Machine with a polynomial kernel and logistic regression to attain an accuracy of 98%.
An Image Segmentation method based on improved CV Mode

Grey scale value inside and outside the contour curve approximates as a constant in CV model. For the target with unever gray scale, the global approximation method can't reflect the change of image gray scale and it is difficult to obtain a satisfactory segmentation results for this kind of image. In this paper the improved CV model is put forward and it overcomes some defects of the original, through the experiment in this paper, the improved algorithm is simpler than LBF algorithm in terms of computational complexity. Better segmentation results can be obtained by using LBF model and ILBF model, but the iterations of ILBF model are less than that of LBF model, and the time consuming of ILBF model is less than that of LBF model.
REPERCUSSÕES DA PANDEMIA DA COVID-19 NO SERVIÇO SOCIAL DO HOSPITAL AREOLINO DE ABREU

In order to analyze the repercussions of the measures to fight the Covid-19 pandemic on the Social Work of the Hospital Areolino de Abreu, the experience report of the social workers and trainee of the Social Work Course at the Federal University of Piauí was used.base, in addition to the memory of the experience, also the Social Work logbook, from the hospital shift, covering the period from March 2020 to July 2021.The results show intense impacts on the work of social workers at Hospital Areolino in Abreu, tending to centralize the actions in individual care from the social duty, aggravating the social isolation of the person with mental disorder with impediments to visits and group actions.
An Abstract Model for Branch-and-Cut

Branch-and-cut is the dominant paradigm for solving a wide range of mathematical programming problems—linear or nonlinear—combining intelligent search (via branch-and-bound) and relaxation-tightening procedures (via cutting planes, or cuts). While there is a wealth of computational experience behind existing cutting strategies, there is simultaneously a relative lack of theoretical explanations for these choices, and for the tradeoffs involved therein. Recent papers have explored abstract models for branching and for comparing cuts with branch-and-bound. However, to model practice, it is crucial to understand the impact of jointly considering branching and cutting decisions. In this paper, we provide a framework for analyzing how cuts affect the size of branch-and-cut trees, as well as their impact on solution time. Our abstract model captures some of the key characteristics of real-world phenomena in branch-and-cut experiments, regarding whether to generate cuts only at the root or throughout the tree, how many rounds of cuts to add before starting to branch, and why cuts seem to exhibit nonmonotonic effects on the solution process.
Seeking the source of vocal fold lesions towards measuring contact pressures during phonation with a pressure-sensing-matrix at hemi-larynx experiments

During phonation, the vocal folds execute a complex movement. Related to the subglottal pressure and tension of the vocal folds themselves, this movement may differ, furthermore depending on the kind of phonation a collision between both vocal folds may occur. If the vocal folds are overstrained, this can cause lesions. To gain knowledge about the vocal folds movements and the way of their collisions, a high-speed evaluation unit for a pressure-mapping sensor was developed. The sensor brings along a local resolution of 27.6 measure points per square centimeter and with the developed unit an adjustable framerate up to 1 kHz can be realized. Due to a sensor thickness of about 0.2 mm, an integration into hemi-larynx flow experiments is quite simple without vigorous changes on the setup. Because of an unrestricted field of view it is possible to record the movements with a high-speed camera. These recordings will be correlated with contact pressures in the post processing. During these experiments, different flowrates of the excitation air and various abduction and elongation steps on the hemi-larynx are obtained to study the effect of those manipulations.
<i>FEBS Open Bio</i>: past, present and future

In celebration of the 10th anniversary of FEBS Open Bio, we spoke to some of the key figures of the journal's genesis, development, and its future direction, and recount here their thoughts and experiences. Prof. Félix. Goñi discusses the role of the FEBS Publication Committee in the journal's beginnings, Dr Mary Purton relates her experiences as the journal's Executive Editor, Prof. László Fésüs explains how the journal developed during his tenure as Chair of the Publication Committee, and Prof. Johannes Buchner looks forward to the future of FEBS Press and academic publishing. Finally, Prof. John (Iain) Mowbray describes his "Friday afternoon thought" to start a new journal.
Sistem Informasi Pengelolaan Data Alumni Pada UPT SMK Negeri 1 Musi Banyuasin

This research was conducted to create an Alumni data management information system at UPT SMK Negeri 1 Musi Banyuasin. This system designed specifically for managing alumni data is expected to make it easier for staff to manage alumni data and make it easier for alumni to fill in alumni data without having to come to school. The focus in this research is to create a system using programming languages ​​that have been widely used, namely PHP and MySQL and to report the data using FPDF. Data Collection Methods in this study are about the Alumni data management information system at UPT SMK Negeri 1 Musi Banyuasin. This study shows the results that to present information on the Alumni of UPT SMK Negeri 1 Musi Banyuasin which includes the presentation of alumni data. As well as other information that is deemed necessary to be presented when needed, such as facilitating the search for old or new alumni. The development of this web-based information system will make it easier to handle changes in data, be it adding, subtracting or searching for data.
Short-Term Solar Irradiance Forecasting Using Long Short Term Memory Variants

Efficient solar irradiance forecasting influences consistent operation and better planning to yield revenue-generative means for photovoltaic (PV) installer. Solar irradiance-based applications and their functional ability profoundly reliant on irregular variations of solar irradiance. Accurate prediction of solar power output needs precise forecasting of one of the critical factors, solar irradiance. In this work, variants of long short term memory (LSTM) are used in global horizontal irradiance (GHI) (W/m2) forecasting. Variants of LSTM with stateless stacked (LS-I) and MLP-Auto-encoder (HLS-I) are designed and verified on Benchmark data (Source: National Renewable energy laboratory (Denver, Colorado). Correlation analysis is performed for suitable auxiliary feature selection. We observe enhanced performance of LS-I and HLS-I with R score 0.971 and 0.970 respectively, better than traditional LSTM (0.962) and LSTM-MLP (0.964) on lag hour-12. HLS-I shows better precision values on RMSE for complicated weather conditions (cloudy and partially cloudy) than LS-I in most of the cases. The number of critical days is proven to be different for two successive (May, June) months. Hence, clustering-based weather classification becomes necessary, for better model evaluation on unknown test observations. In addition, the clearness-index is used to identify the weather types and threshold ranges of observed climatic dissimilarity.