Reviewerly/exHarmony huggingface dataset:
USEFULNESS OF ACCOUNTING INFORMATION SYSTEMS FOR BUSINESSES

Accounting information systems have an important role for the progress of a company. Accounting information systems produce financial information. Financial information is also referred to as financial statements. The accounting information system collects data in the form of transactions that occur in companies such as purchase transactions, sales transactions, cash disbursements transactions and cash receipt transactions. Information in company financial reports is needed by both internal and external parties. The financial statements must meet the requirements, that is, have quality characteristics. To run an Accounting Information System (AIS), elements are needed so that the system can run properly and correctly. namely: (1) Human resources (HR) who have been trained; (2) Financial Data Form; (3) Hardware; (4) Software; (5) Procedure; (6) communication technology network; (7) database. The quality characteristics of financial statements consist of comprehensiveness, relevance, materiality, reliability, honest presentation, substance outperforming form, neutrality, sound judgment, and completeness. The accounting information system functions to oversee all the company's financial activities and collect and store data on the company's financial activities or transactions.
Spatial effects induced by a sound centrifuge

If revolutions of sound in space go beyond a certain barrier of revolutions per second, they become something else” explained Karlheinz Stockhausen during a conversation with Jonathan Cott in 1971. This observation gave birth to a series of controlled scientific experiments we have conducted at CIRMMT since 2008. We first estimated perceptual thresholds for auditory motion and velocity perception and later investigated the influence of reverberation, spatialization techniques and loudspeaker configurations. Throughout this process, new tools based on a hybrid spatialization method combining numerical propagation and angle-based amplitude panning, were developed to move sounds around the listener at very high velocities. The revolution frequency can be in the same order of magnitude as audible frequencies. In this demonstration, spatial audio effects will be presented parametrically as core elements of spatial studies based on velocity
Study of Electrocardiographic Findings in Severe Anaemia

BACKGROUND Anaemia is a worldwide problem which has major consequences on human health. It also poses a huge social and economic burden. World Health Organisation defines a haemoglobin level of less than 8 gm / dL as severe anaemia. It affects multiple organs, cardiovascular system being one of them. The clinical features of anaemia are a result of diminished oxygen carrying capacity of the blood. The clinical presentations vary depending on the age of the patient, rapidity of onset of anaemia and its severity. The cardiac changes are reflected as electrocardiographic abnormalities. In clinical practice such electrocardiographic findings simulate those of ischemic heart disease leading to a battery of investigations. METHODS This was a retrospective study. Forty five anaemia patients admitted in medicine wards of S. Nijalingappa Medical College and HSK hospital over a period of 6 months from 1st July 2019 to 31st Dec 2019 were studied. Complete hemogram and electrocardiography were obtained and analysed. RESULTS Anaemia was more common among females who constituted 30 (66.66 %) patients as compared to males constituting 15 (33.33 %) patients. 31 patients (68.88 %) with severe anaemia showed ECG changes. Most common finding was sinus tachycardia seen in 17 (37.77 %) of patients followed by T inversions 11 (24.44 %) and ST depressions 4 (8.88 %). Anaemia was most commonly seen in the age group of 15 - 30 years constituting 23 (51.11 %) patients. ECG findings were more common in females as compared to males. 22 (73.33 %) of female patients had ECG changes as compared to 9 (60 %) in males. CONCLUSIONS ECG abnormalities are common in patients with severe anaemia more so in females. These mimic changes seen in patients with ischemic heart disease. KEYWORDS Severe Anaemia, Electrocardiographic Findings, Sinus Tachycardia
PENGARUH MOTIVASI INTRINSIK, LINGKUNGAN BELAJAR, DAN DUKUNGAN KELUARGA TERHADAP SEMANGAT BELAJAR MAHASISWA PROGRAM PASCASARJANA SEKOLAH TINGGI ILMU EKONOMI PARIWISATA INDONESIA

This study aims to determine the effect of intrinsic motivation, learning environment, and family support on students' enthusiasm for learning at the Postgraduate Program at the Indonesian Tourism Economics College (STIEPARI) Semarang.The population used in this study were 98 students in the Postgraduate Program.The sample is determined using a saturated sampling technique so that all members of the population are treated as a sample of 98 people.The results showed that intrinsic motivation had a negative effect on enthusiasm for learning, the learning environment, had a positive and significant effect on enthusiasm for learning, and family support had a positive and significant effect on enthusiasm for learning.
Causal Inference Using Linear Time-Varying Filters with Additive Noise

Causal inference using the restricted structural causal model framework hinges largely on the asymmetry between cause and effect from the data generating mechanisms. For linear non-Gaussian noise models and nonlinear additive noise models, the asymmetry arises from non-Gaussianity or nonlinearity, respectively. Despite the fact that this methodology can be adapted to stationary time series, inferring causal relationships from nonstationary time series remains a challenging task. In this work, we focus on slowly-varying nonstationary processes and propose to break the symmetry by exploiting the nonstationarity of the data. Our main theoretical result shows that the causal direction is identifiable in generic cases when cause and effect are connected via a time-varying filter. We propose a causal discovery procedure by leveraging powerful estimates of the bivariate evolutionary spectra. Both synthetic and real-world data simulations that involve high-order and non-smooth filters are provided to demonstrate the effectiveness of our proposed methodology.
Do We Need Improved Code Quality Metrics?

The software development community has been using code quality metrics for the last five decades. Despite their wide adoption, code quality metrics have attracted a fair share of criticism. In this paper, first, we carry out a qualitative exploration by surveying software developers to gauge their opinions about current practices and potential gaps with the present set of metrics. We identify deficiencies including lack of soundness, i.e., the ability of a metric to capture a notion accurately as promised by the metric, lack of support for assessing software architecture quality, and insufficient support for assessing software testing and infrastructure. In the second part of the paper, we focus on one specific code quality metric-LCOM as a case study to explore opportunities towards improved metrics. We evaluate existing LCOM algorithms qualitatively and quantitatively to observe how closely they represent the concept of cohesion. In this pursuit, we first create eight diverse cases that any LCOM algorithm must cover and obtain their cohesion levels by a set of experienced developers and consider them as a ground truth. We show that the present set of LCOM algorithms do poorly w.r.t. these cases. To bridge the identified gap, we propose a new approach to compute LCOM and evaluate the new approach with the ground truth. We also show, using a quantitative analysis using more than 90 thousand types belonging to 261 high-quality Java repositories, the present set of methods paint a very inaccurate and misleading picture of class cohesion. We conclude that the current code quality metrics in use suffer from various deficiencies, presenting ample opportunities for the research community to address the gaps.
Enhancing Pre-trained Language Model with Lexical Simplification

For both human readers and pre-trained language models (PrLMs), lexical diversity may lead to confusion and inaccuracy when understanding the underlying semantic meanings of given sentences. By substituting complex words with simple alternatives, lexical simplification (LS) is a recognized method to reduce such lexical diversity, and therefore to improve the understandability of sentences. In this paper, we leverage LS and propose a novel approach which can effectively improve the performance of PrLMs in text classification. A rule-based simplification process is applied to a given sentence. PrLMs are encouraged to predict the real label of the given sentence with auxiliary inputs from the simplified version. Using strong PrLMs (BERT and ELECTRA) as baselines, our approach can still further improve the performance in various text classification tasks.
INCREASING ELEMENTARY SCHOOL EDUCATION QUALITY THROUGH COMMITTEE SCHOOL PARTICIPATION APPROACH

The aim of study was to find out the approach of to develop of community participation in improving the quality of education process. Community had the important role in education because the community gave the impact on education quality progress. The research used descriptive qualitative approach. Data collection techniques consisted of observation, interviews, and documentation. Data analysis was carried out in two stages, namely (1) data analysis in single or individual cases and (2) cross-case data analysis. The results of the study concluded that the approach of community participation in the implementation of elementary school education programs in Mataram is the school as a community center. The implication of the results is the concept of developing the community in the process of elementary school education in Mataram and increasing awareness of all parties in formulating the concept of education process.
DIVERSIFICATION OF THE CONTENT OF EDUCATION IN THE VOCATIONAL TRAINING OF FUTURE SPECIALISTS

The article is devoted to certain aspects of diversification of the content of professional training of future specialists in the therms of university education. It is noted that the concept of “diversification” has found its application in interdisciplinary areas - linguistics, politics, education; It is shown that in education sphere the term “diversification” covers diversity, diverse development, expansion of educational services, mastery of new activities not previously inherent in this industry. The authors proved that the construction of a new educational system of vocational training is possible provided that the principles of diversification are integrated into the educational process, in particular: humanization of education as a process and result of individual inculturation; democratization of education as an opportunity to realize a free, creatively active personality; creative nature of education as a necessary condition of spiritual and moral and socially significant personality; availability of the educational system; continuity of education. It is emphasized that the main elements of the diversification system of higher education in the socio-cultural sphere are the goals and content of education, methods, technologies, organizational forms, content and structural links of educational levels and their interaction.
Survey on Risk Classification in Agile Software Development Projects in Latvia

Abstract Software development method, which does not have any faults or gaps in project implementation, has not been elaborated so far. Due to this reason, the authors have decided to perform this study to make it easier for the companies, which use one of the agile development methods, to better foresee potential risks and to deal with their consequences. The aim of the research is to identify and classify risks in agile software development methods and the related projects based on the obtained survey data. To achieve the goal, the authors have developed evaluation criteria, as well as implemented practical questionnaire in various software development companies. From the obtained survey data, the risks are classified according to various factors, i.e., the changing highest and lowest priorities and needs in various projects. Thus, the obtained research results can be applied in various areas of project development, changing the order of priority factors.
Communicating Collections: Strategies for Informing Library Stakeholders of Collections, Budget, &amp; Management Decisions

A challenging aspect of the collection management process is effectively communicating with stakeholders about library resources. Communication can range from obtaining patron feedback integral in collection planning to effective messaging elaborating on collection budgets and cancellation decisions. It has also become increasingly necessary to explain the various acquisition models that affect the landscape of library content and use of electronic resources. In this paper, the University of South Florida will present the results of a survey of the approaches used in academic library websites to communicate collection policies along with related considerations, statistics and data, justifications, and factors affecting selection practices. Information about the important elements used to construct a dialog with faculty and administration in order to demonstrate the costs and value of library resources to those in the academic community is included. A case study demonstrating the practical implementation of these communication principles at the Arthur Lakes Library at the Colorado School of Mines will be discussed. The study will show how the Library was able to break free from a cycle of collection stagnation, which was perpetuated by a lack of effective communication. The result was that the Library was able to tell a story with data in order to communicate a message, as well as strengthen their partnerships with faculty regarding collection management.
Discovering Textual Structures: Generative Grammar Induction using Template Trees.

Natural language generation provides designers with methods for automatically generating text, e.g. for creating summaries, chatbots and game content. In practise, text generators are often either learned and hard to interpret, or created by hand using techniques such as grammars and templates. In this paper, we introduce a novel grammar induction algorithm for learning interpretable grammars for generative purposes, called Gitta. We also introduce the novel notion of template trees to discover latent templates in corpora to derive these generative grammars. By using existing human-created grammars, we found that the algorithm can reasonably approximate these grammars using only a few examples. These results indicate that Gitta could be used to automatically learn interpretable and easily modifiable grammars, and thus provide a stepping stone for human-machine co-creation of generative models.
Job Satisfaction and Relationship with Organizational Commitment among Nurses

Background- Nurses’ job satisfaction is one of the most important factors affecting organizational commitment. Aim- The study aimed to identify the relationship between job satisfaction and Organizational Commitment among nurses. Methods and Materials- A descriptive, correlational and cross-sectional study design carried out between (5th/September/2017 till 30th of May/2018) at five hospitals in Mosul/Iraq. Depending on the convenience sampling method and Non-probability sampling technique, a sample of (317) nurses were selected. Two instruments were used to collect data via an interview method with each subject (Minnesota Job Satisfaction Questionnaire “JS” and Organizational Commitment Questionnaire “OC”). To measure the content validity of the questionnaires, they exposed to five experts in the nursing field, whereas, the reliability of them was checked by Cronbach’s alpha. The results of the study were demonstrated by descriptive statistic through (mean standard and deviation), and by inferential statistic through (stepwise regression). Findings- Total JS and its domains had significant relationships with total OC and its Affective and Normative domains, while they hadn’t any significant relationships with total OC.
Extraction of Real-World Objects in the Environment through Computer Vision

For the past decade, there has been a surge of interest in self-driving vehicles. This is because of leaps in the field of deep learning especially Artificial Neural Networks which are trained to perform tasks that regularly require human intervention. Genetic algorithms (GA) apply models to identify patterns and features in the environment making them desirous in cases of uncertainty. In this project we have trained an evolving Neural network by using Genetic Algorithms in Unity Game Engine using the ML-agents provided by them. By repeated simulation of the agent in the environment, using this we have created an agent which learns unique features from the environment based on its input and generates a forecast permitting the vehicle to drive without requiring external commands from the player.
The Use of Describing Picture in Teaching Speaking Skill

This study aims to determine the use of picture descriptions in teaching speaking English and to determine the progress of students' ability in speaking English after being taught using picture description media. The population of this research is the eleventh-grade students of religion two MA Al Amiriyyah Blokagung Banyuwangi. Describing pictures can motivate students to learn English and can also help teachers to make students interested and comfortable in learning, especially in speaking, according to Killer and Huebner, As a learning medium, pictures can help teachers to make students interested and comfortable learning. especially English. What's more, pictures can present real situationsâ€. It is expected that students can improve their speaking skills. Also, describing pictures can be used to stimulate their imagination and motivation to learn English, especially in speaking skills. This study uses the Qualitative method. Data collection techniques using observation, interviews, and documentation.
Physical Interface for Robotic Marionette Camera (RMC): Hardware Controlling Platform for Robotic Videography Motion Design

This project-based research is an investigation on controlling robotic videography/camera through an interactive physical interface.Here referred to as Robotic Marionette Camera (RMC), this research project is enabling designers and videographers to design precise robotic videography scenarios and camera-paths in the physical world with similar qualities to the digital design environments.Using the ideas of a "digital" camera in design software platforms, RMC looks at concepts such as aiming, zooming in and out, panning, orbiting, and other motions/operations borrowed from cinematography, such as tilting, rolling and trucking amongst others.As a physical/hardware interface, RMC enables real-time interaction with an industrial robot arm through a custom-made hardware controller.Using a tangible interface, RMC users can design, edit, and program the robotic videography paths interactively without a need for programming knowledge.
Semi-Supervised Dependency Parsing with Arc-Factored Variational Autoencoding

Mannual annotation for dependency parsing is both labourious and time costly, resulting in the difficulty to learn practical dependency parsers for many languages due to the lack of labelled training corpora.To compensate for the scarcity of labelled data, semi-supervised dependency parsing methods are developed to utilize unlabelled data in the training procedure of dependency parsers.In previous work, the autoencoder framework is a prevalent approach for the utilization of unlabelled data.In this framework, training sentences are reconstructed from a decoder conditioned on dependency trees predicted by an encoder.The tree structure requirement brings challenges for both the encoder and the decoder.Sophisticated techniques are employed to tackle these challenges at the expense of model complexity and approximations in encoding and decoding.In this paper, we propose a model based on the variational autoencoder framework.By relaxing the tree constraint in both the encoder and the decoder during training, we make the learning of our model fully arc-factored and thus circumvent the challenges brought by the tree constraint.We evaluate our model on datasets across several languages and the results demonstrate the advantage of our model over previous approaches in both parsing accuracy and speed.
ON NEW EXOTIC ATTEMPTS TO QUESTION THE RELATIONSHIP BETWEEN CITEDNESS FIGURES AND THE USE / VALUE OF CITED SCIENTIFIC DOCUMENTS

The objective of the present paper was to analyze a number of concepts related to the scientometric method "citation index". Some experts still interpret “negative citations” and “disproportionately large share of self-citations” as “shortcomings” of the “citation index” scientometric method. In the author’s opinion, the reason is an indelible belief in the “normative theory of citation”, which implies a conscious choice of citations, a conscientious selection of the best quality works for the reference-lists, and a “desire to return the intellectual debt” to the cited authors. But there are also new attempts to question the adequacy of the “citation index” method. For example, one of the publications of the year 2020 questions the causal relationship between the citations to the scientific documents and their use, and between their use and their value; the reason why this fundamental pattern is called into question is mainly based on the actions of some people who do not meet ethical standards and may be arbitrarily directed against its manifestation. The mentioned paper claims, in particular, that very common are the following phenomena: deliberate refusal to use the necessary scientific documents; refusal to cite the documents used (including plagiarism and restraint from citing for technical reasons); practice of evaluating little-known and inaccessible documentary sources as not valuable enough (value is confused with quality in this case); fake citing to unread works. The present article refutes the interpretation of these phenomena as indicating the absence of the considered causal relationship and tries to demonstrate that, on the contrary, some of them are involuntary confirmation of the adequacy of the “citation index” method.
Correction to: Web Information Systems and Technologies

In the originally published version of the book there was an error in the first name of the second volume editor: “José Francisco Domínguez Mayo” should have been “Francisco José Domínguez Mayo”. This has now been corrected.
Venses @ HaSpeeDe2 & SardiStance: Multilevel Deep Linguistically Based Supervised Approach to Classification

In this paper1 we present the results obtained with ItVENSES a system for syntactic and semantic processing that is based on the parser for Italian called ItGetaruns to analyse each sentence. In previous EVALITA tasks we only used semantics to produce the results. In this year EVALITA, we used both a fully and mixed statistically based approach and the semantic one used previously. The statistic approaches are all characterized by the use of n-grams and the usual tf-idf indices. We added another parameter called the Kullback-Leibler Divergence to compute similarities. In addition we used emoticons and hashtags. Results for the two runs allowed have been fairly low – around 40% F1-score. We continued producing other runs on the basis of the statistical approach and after receiving the gold-test version and the evaluation script we discovered that in one of these additional runs - the fourth - we improved up to 54% macro F1 for HaSpeeDe2 task and up to 48% macro F1 for Sardines.