Reviewerly/exHarmony huggingface dataset:
Sistem Informasi Akuntansi, Efektivitas Pengendalian Internal, Asimetri Informasi dan Moralitas Individu terhadap Kecurangan Akuntansi

The purpose of this research is to examine the influence of accounting information systems, the effectiveness of internal control, information asymmetry and individual morality on accounting fraud in . The population of this study were employees of PT. Petrokimia Gresik and the sampling technique used in this research is saturated sampling with a total sample of 100 employees of PT. Gresik Petrochemicals. Data was collected by giving questionnaires to respondents in departments related to accounting information systems. The data analysis technique used is the PLS Model with the help of Warp PLS 8.0 software which includes three stages in its measurement, namely outer model analysis, inner model analysis and hypothesis testing. The results of this study indicate that partially accounting information system variables, the effectiveness of internal control, and individual morality have a significant negative effect on accounting fraud. Meanwhile, information asymmetry has a significant positive effect on accounting fraud.
Screening Risiko Terjadinya Deep Vein Trhombosis

This study aimed to examine several studies on early screening and prevention of the risk of developing Deep Vein Thrombosis (DVT). The method used in this literature review consists of 4 stages: (1) identification of the search for journal articles; (2) identification of literary works based on title, abstract, and purpose; (3) inclusion criteria; (4) complete and specific texts are available according to the purpose of the review. The process of searching for journal articles using Google Scholar, ScienceDirect, DOAJ, Scopus, ProQuest, Ebsco and Pubmed. The results showed that most early DVT screenings used ultrasound as a non-pharmacological DVT detection and prevention tool, the most frequently used was compression stockings. In conclusion, compression stockings are more effective in preventing DVT.&#x0D; Keywords: Early Detection, DVT, Bed Rest
Automating FDLP eXchange Withdrawal Lists

The Penn State University Libraries (University Libraries) is a large academic research library comprising twenty-four locations and thirty campus libraries across the Commonwealth of Pennsylvania. The University Park campus is the main campus and has five libraries with many different departments that often act independently. As an example, in the main Pattee-Paterno Library, there are four libraries: George and Sherry Middlemas Arts and Humanities/Social Sciences/Education, Life Sciences (part of STEM libraries), William and Joan Schreyer Business, the Donald W. Hamer Center for Maps and Geospatial Information (Maps and GIS). As a large institution, the scope of projects can be substantial and create opportunities for departments to share their technical skills. These partnerships often manifest as technological innovations that can improve workflow across the organization and be shared with the greater library community.
An Efficient Method for Finding Mislabeled Samples of Similar Chinese Characters

Convolutional neural networks for offline handwritten Chinese character recognition require a large number of samples to train the model, the mislabeled samples in the training set will reduce the recognition accuracy of the model, while similar Chinese character samples are the most prone to be mislabeled. In this paper, we propose a method to find the mislabeled samples of similar handwritten Chinese character pairs by differential features based recognition combined with manual verification, which can significantly reduce the time required to find the mislabeled samples. The method was applied to the similar character pair of E-B” whose handwritten samples are easy to be mislabeled. The experiments show that the proposed method can narrow down the scope of candidate mislabeled samples and improve the efficiency of manual verification, and find four times more mislabeled samples than convolutional neural network based method.
INFORMATION SYSTEM FLOW DESIGN LIBRARY WEBSITE BASED SMKN 8 BANDUNG “THE ULTIMATE DIGITAL LIBRARY”

Digital Library Smkn 8 Bandung has constraint in data management and efficiency service borrow and return the book made by the officer library. Data Collection library, visitor data, and transactions loan need needs will use technology webbased system information for simplify the process of performance in the Library of SMKN 8 Bandung. Study this aim build system information library web -based that will could help library data management and improve quality service to transaction borrowing from the library. Method used in development system information on research this is which waterfall method at which stage this there is design and implementation apply pattern model view controller (MVC) design. While the testing process carried out there is a number of Step testing by sequentially namely unit tests, integration tests, validation tests, reliability tests, compatibility tests, and acceptance tests. Unit tests using base path technique show results from system that has simple structure, very easy understood and implemented. Integration test using white box method shows valid results. Validation testing using black box method shows that 25 function walk with good. Reliability test with use nelson calculations show that system could walk with consistent. Compatibility test shows system could used with good on 4 types of browsers. And the acceptance test shows that all function succeed run with good and have accepted by SMKN 8 Bandung.
DESIGN BUILD LIBRARY INFORMATION SYSTEM BASED FOR SANTA MARIA 2 HIGH SCHOOL BANDUNG

Data collection is generally done manually, but this manual method has drawbacks, namely data collection becomes ineffective, not neatly arranged, and searching for data takes a lot of time. Likewise with library management at Santa Maria 2 High School Bandung, data collection is still manual so there are often many errors , therefore an information system is needed that can manage book collection data, library member data, book borrowing data, book return data and fines data for members who are late in returning books, which aims to improve the performance of library managers to be more effective in managing library data, and also to increase the reading interest of library members, namely Santa Maria 2 Bandung High School students themselves. The research method used is research and development with the sql website development method. The data collection methods used were interviews and observations. The interview method is to determine user needs, while the observation is for testing aspects of performance efficiency. The results of this study are (1) the system is proven that the level of feasibility of a web-based library information system using PHP and a MYSQL database server. (2) The test results prove that the level of feasibility of a web-based library information system in the aspect of usability for small groups is 8 1.22 % with very feasible criteria and large groups 9 0.2 % with very feasible criteria , and aspects of performance efficiency 9 6.64 with grade A.
Vehicle Detection in UAV Remote Sensing Image Based on Improved YOLOv5

Aiming at the problem of vehicle detection in UAV remote sensing images, adaptive anchor frame calculation is used to seek the optimal initial value anchor frame, the loss function of YOLOv5 algorithm which only uses the length width ratio of the bounding box and cannot reflect the real difference between the width and height of the bounding box and its real value, is improved. It eliminates the problem of slow convergence caused by the failure to reflect the real difference in width and height. Using this improved YOLOv5 algorithm for training and detection, the effectiveness of the algorithm for vehicle detection in UAV aerial images is verified.
Application of Mixed Reality Object Recognition Technology in Aircraft Maintenance Manual

With the gradual application of digital technology in the aviation maintenance industry, Mixed Reality (MR) technology, as an auxiliary technology, can combine equipment maintenance models, real world and relevant aircraft maintenance manuals. This can improve the efficiency of maintenance personnel, reduce maintenance errors and improve maintenance quality. In order to achieve an effective application of MR in the verification of electronic technical publications, a method is proposed which is based on the Vuforia SDK developed by Qualcomm for image matching for marker recognition and Mixed Reality Toolkit (MRTK) for functional interaction. The developed content can then be displayed through HoloLens glasses for mixed reality output. Finally, the developed content is experimented and verified through rectifier cone disassembly experiments. Combined with the case study it can be concluded that the method can be well applied to the validation process of electronic technical publications.
Online Teaching Practice of Computer Network Course

Due to the impact of the COVID-19, online teaching has become a common teaching method at present, and in-depth research on online teaching methods is of great practical significance. In the computer network course, we organize the online teaching process according to the BOPPPS model combined with online teaching tools such as DingTalk and Rain Classroom. We use Rain Classroom to seize the pre-class preview and use DingTalk to achieve participatory online interactive teaching and complete homework correction and online Q&A. The results of the questionnaire show that the above-mentioned teaching organization method can enable students to actively participate in interactive teaching, and students' approval of online teaching is relatively high.
Investigation and research countermeasures of students' subjectivity in mathematics classroom teaching in junior middle school

Our country makes great efforts to develop quality education, in which the cultivation of students' subjectivity is the key. This paper studies the present situation of students' subjectivity in junior middle school mathematics class, finds out students' problems in learning mathematics, and puts forward some countermeasures to improve the teaching and learning of mathematics. By using the method of SPSS investigation and analysis, this paper makes an overall analysis of students' subjectivity and analyzes their gender differences and their correlation with mathematics scores, and draws a conclusion that junior high school students' subjectivity is good and there is still room for improvement in mathematics class. There is no significant difference in students' gender, and there is a significant correlation between subjectivity and mathematics achievement. Finally, the paper puts forward the relevant strategies on how to cultivate the subjectivity of junior high school students, hoping to be of some help to teachers and students.
COGNITIVE VALUE OF SCIENTIFIC CONCEPT

The article studies the essence of scientific theory and scientific concept.It is clarified what the concept is and how it differs from other forms of holistic knowledge, and what criteria the concept must meet in order to be called scientific.It was determined that the closest philosophical branch to science is the philosophy of science, as well as another discipline adjacent to linguistics -the philosophy of language.The philosophy of language is a research branch of philosophy that elucidates the role of language and speech in cognitive processes and structures of consciousness.The role of methodology as a transitional type of intellectual activity that combines the subjectpragmatic nature of the philosophy of science and the object-argumentation nature of science is outlined.The first scientist who explicitly and unambiguously made linguistic research dependent on methodology was Ferdinand de Saussure.Saussure did not use such a term, but spoke of «point of view».It is proposed to consider the essence of scientific knowledge in the formation of methodically conceptualized and logically reasoned knowledge.And if the formal conceptualization of scientific knowledge concerns its existence as a theory or concept, then the essential conceptualization concerns the very nature of such knowledge, the degree of its objectivity or subjectivity.The essential aspect of scientific knowledge also reveals a relationship to nomotheticity or idiographicity in the understanding of the object and problem, and deductiveness or inductiveness of scientific analysis.Methodological integrity and pragmatism are defined as the most essential characteristics of a scientific concept.The analysis of a scientific concept should consist, first, of understanding the methodological foundations on which it is built by the author of such a linguistic concept, in particular, his understanding of: the ontology of the researched object, the epistemology of linguistic research, the system of research methods.Only after that, the texts, individual utterances, statements, or remarks of the author of the scientific text, his followers or opponents, can be perceived adequately, and their critical assessments can acquire cognitive value.
A fine-grained image classification method combining YOLOv7 and bilinear multi-level feature fusion

Fine grain image is an important research field of image recognition, which can classify objects in more detail. Image feature extraction is usually implemented by bilinear network, which can meet the desired effect of feature extraction, but also discard some detailed feature information. In this study, a fine-grained classification optimization algorithm that combines the target detection method YOLOv7 and multi-feature fusion bilinear network is proposed to achieve fine-grained image classification. In the method, YOLOv7 is used to locate the target, and the recognition content is extracted according to the image detection frame; Then, the improved bilinear convolutional neural network structure is used to fuse the features of different channels and different levels of convolutional layers in the bilinear network, so as to obtain more feature information and improve the precision of fine-grained classification. Experimental results show that the classification results of this algorithm are better.
Impact of the Type of a Post on the Engagement Rate of It

Within the last six years, influencer marketing market has grown by 700%, and within the last two years sales have doubled. Absolute majority of marketing professionals consider it effective. The main target audience of marketers using influencer marketing in Europe is youth, since 90% of them are actively using social networks. A steady growth can also be observed among those who use it as a news outlet and source to find out more about products and services. At the same time, not many digital content creators are honest with their audience, openly labelling collaboration. There are still the ones hiding it. The situation with influencers mainly followed by adolescents is especially dangerous, as the level of advertising literacy is not yet sufficiently advanced, and they are more easily impressed than adults. One of the possible reasons for hiding the fact that the content is actually an advertisement, is the fact that influencers are afraid that their engagement rate will decrease, which is detrimental, since the engagement rate is one of the criteria demonstrating the success of cooperation. The purpose of this study is to analyse whether advertorial posts really cause fewer reactions than regular posts. For this purpose, Latvian influencers who had more than 1500 followers and whose followers at the time of the performance of study were mostly adolescents (11–18 years old) from Latvia were selected. During 2021, the posts on the social media platform Instagram mentioning brands and/or having the relevant labelling regarding cooperation with the brand were selected. The engagement rate for 654 posts was compared with the engagement rate for regular posts. As a result, it was found that the difference varies from 1% to 2%. Since the difference is considered insignificant, we can conclude that there is no reason to hide paid collaboration from the audience.
An AHP based Task Scheduling and Optimal Resource Allocation in Cloud Computing

Cloud systems by virtue characterize ultimate resource utilization with ever evolving user requirements facilitating adaptivity.With a scope of enhancing the QoS needs of user applications, numerous factors are considered for tunning among which Task scheduling promises to grab focus.The Task Scheduling mechanism ascertains improvement by distributing the subtasks to specific set of resources pertaining to prevailing Quality models.The work emphasizes the need for effective task scheduling and optimizing resource allocation by modelling a modified AHP (Analytical Hierarchy Process) driven approach.The proposed method guarantees the functionality in two phases pertaining to Task ranking and pipelined with Optimized scheduling algorithms resulting in maximization of resource utilization.The former phase of task ranking is aided by improved AHP with substantial usage of fuzzy clustering followed by an enhanced CUCMCA (Chimp Updated and Cauchy Mutated Coot Algorithm) algorithm for optimal resource allocation of cloud applications.The contributed model promises leveraged performance of 32% for memory usage, 33.5% for execution time, 29% for makespan and 18% for communication cost over pre-existing conventional models considered.
Cloud Task Scheduling using the Squirrel Search Algorithm and Improved Genetic Algorithm

With cloud computing, resources can be networked globally and shared easily between users.A range of heterogeneous needs are met on demand by software, hardware, storage, and networking.Dynamic resource allocation and load distribution pose challenges for cloud servers.In this regard, task scheduling plays a significant role in enhancing the performance of cloud computing.With the increase in the number of users and the capability of cloud computing, cloud data centers are experiencing concerns regarding energy consumption.To leverage cloud resources energy efficiently and provide real-time services to users, a viable cloud task scheduling solution is required.To address these problems, this paper proposes a new hybrid task scheduling algorithm based on squirrel search and improved genetic algorithms for cloud environments.The proposed scheduling algorithm surpasses existing scheduling algorithms across multiple parameters, including makespan, energy consumption, and execution time.
Bisayan Dialect Short-time Fourier Transform Audio Recognition System using Convolutional and Recurrent Neural Network

Speech is a form of oral communication that reinforces thoughts and ideas that have general purpose and meaning.In the Philippines, Filipinos can speak at least three languages.English, Filipino, native language.The Philippine government says the Philippines has more than 150 regional native languages, one of which he says is Cebuano.This research aims to implement automatic speech recognition (ASR) specifically for the Bisayan dialect, and researchers use machine learning techniques to create and operate the system.ASR has served its purpose in recent years not only in the official language of the Philippines, but also in various foreign languages.The required datasets were collected throughout the study to train and build the models selected for the speech recognition engine.Audio files are recorded in waveform file format and contain Visayan phrases and sentences.Audio was captured through hours of recorded audio and process using Tensorflow short time Fourier transform (STFT) algorithm to ensure the accurate representation.In order to analyze the audio data, the recordings were specially converted to digital format, specifically .wavand making it sure all records are uncorrupted with only one channel, and finally have a sample rate of 22050kHz.A data mining process was carried out by integrating CNN layers, dense layers, and RNNs to predict the transcription of speech input using multiple layers that determine the output of the speech data.The researchers used the JiWER Python library, which was used in parallel when evaluating WER.This is because the trained scripted data set contains at least 500 time recordings totaling 61.78 minutes.Overall, the WER output is at best 99.53% and the percentage of records used is acceptable.
Emotional and Cognitive Trust in Social Conversational Agents: An Abstract

A Conversational Agent (CA) is a computer program that can generate dialogues to interact with human beings. It can assume a physical manifestation, such as a robot, or take the format of an avatar, or can be merely embedded within a website or a smartphone application (app) without any human-like appearance. Both text and voice-based CAs are being increasingly accepted in our daily life: smart home products such as Alexa and Google Home have achieved commercial success; smartphone voice assistants like Siri and Cortana are being used as a productivity tool. However, because of the human-like conversing skills CAs manifest, they also sometimes assume a unique social role under special circumstances. While a number of studies have considered the consumption intention of CA products from a trust perspective, no research, to our knowledge, has considered the human-CA relationship as a source of the emotional trust. Trust has been included in many previous CA acceptance and use studies. However, very few researchers have differentiated between the cognitive and emotional trust in CA studies. To address this gap, we interviewed 14 existing users of the AI companion app Replika as a pilot study to understand users’ perceptions about interacting with the app. Because of the newness of the phenomenon, we did not assume a theoretical framework in the pilot study Instead, the grounded theory approach was adopted to capture a variety of perspectives, such as trust, privacy, satisfaction, and dissatisfaction. The content analysis of the interview transcripts revealed separate sources of cognitive and emotional trust. Based on the results, this study proposed a theoretical model of the effects of emotional and cognitive trust on intentions to continue using social conversational agent products. Furthermore, the study uniquely included the perception of relationship strength as an antecedent of emotional trust. Practically, this study may be appealing to marketing practitioners who are interested in understanding consumer behaviors toward similar products, such as chatbots, voice assistants, and social robots. It may also offer insights to policy makers regarding the mechanism of trust building toward artificial intelligence agents and potential privacy risk reduction measures.