Reviewerly/exHarmony huggingface dataset:
Guided Music Synthesis with Variable Markov Oracle

In this work the problem of guided improvisation is approached and elaborated; then a new method, Variable Markov Oracle, for guided music synthesis is proposed as the first step to tackle the guided improvisation problem. Variable Markov Oracle is based on previous results from Audio Oracle, which is a fast indexing and recombination method of repeating sub-clips in an audio signal. The newly proposed Variable Markov Oracle is capable of identifying inherent datapoint clusters in an audio signal while tracking the sequential relations among clusters at the same time. With a target audio signal indexed by Variable Markov Oracle, a query-matching algorithm is devised to synthesize new music materials by recombination of the target audio matched to a query audio. This approach makes the query-matching algorithm a solution to the guided music synthesis problem. The query-matching algorithm is efficient and intelligent since it follows the inherent clusters discovered by Variable Markov Oracle, creating a query-by-content result which allows numerous applications in concatenative synthesis, machine improvisation and interactive music system. Examples of using Variable Markov Oracle to synthesize new musical materials based on given music signals in the style of Jazz are shown.
Statistical Analysis of Morphometric Data for Pottery Formal Classification: Variables, Procedures, and Digital Experiences of Medieval and Postmedieval Greyware Clustering in Catalonia (Twelfth–Nineteenth Centuries AD)

Abstract Formal analysis of pottery is a commonplace for most archaeologists regardless of the area or period of study. The typological study of utilitarian earthenware is complex and has often been neglected in pottery studies devoted to the analytical characterization of vessels. Certainly, a low degree of variability and standardization can jeopardize a definition of vessel typologies with some sense of universality. Despite this, a global approach dealing with the function or technology of the vessels should also include typological aspects, since they are relevant at the microscale levels and have significance in determining technical choice or distribution. In the last decade, we have analysed and quantified a vast amount of medieval greyware pottery assemblages. The generation of datasets of morphometric variables and their investigation via principal component analysis, among other statistical approaches and graphical representations, has led us to the identification of regional typologies with chronological meaning among these coarse, plain, and highly functional vessels fired under reducing conditions. Clusters resulting from a combined study including up to four diameters, wall thickness, absolute, preserved or reconstructed height, and vector profile measurement allowed us to determine the degree of breakage and to consider this variable in the typological definition.
Factors Affecting Employment Intention and Student Satisfaction in Accounting Internship: A Case of International Private University

This research aims to examine the relationship between accounting student-interns evaluation, their supervisor evaluation and student satisfaction toward internship, and employment intention. Questionnaires were used to collect data from 98 accounting student-interns and 98 of their supervisors The collected data was analyzed in terms of Cronbach's alpha coefficient analysis, factor analysis, composite reliability, average variance extracted, and multiple regression analysis. The results reveal that (1) student evaluation is significantly related to student satisfaction toward the internship program but not to employment intention and (2) supervisor evaluation is significantly related to employment intention but not to student satisfaction toward internship.
PENGEMBANGAN MEDIA FLIPBOOK PADA PEMBELAJARAN BAHASA INDONESIA MATERI FABEL PADA SISWA KELAS IV SEKOLAH DASAR

The background in the wwriting of this study is that less effective learning takes place in those schools and less teching media. Researchers also perfom a tet based analysis of the student book that outlines only tet at the fable story study. the reseach objective are (1) to product learning media flipbook theme 4 in subtheme 1 in the first learning process in Indonesian language subject. The fabel is a form of narration, or fairy tales whose characters use animals that talk and behave like humans. (2)to find the advisability of learning media flipbook by validity out come of advisability validator. In this reseach used developer research with 4D model wich developer by Thiagarajan. The model adapted by 3 steps. The media wich developed in this research validated by 3 validator the result of research in this advisability flipbook media: Validator 1 from media expert get the result based on 88% in category golden, validator 2 from a material expert get the result 92% in category golden, validator 3 from linguists get the result 80% in category good. Based on the result before media wich developed in this research declared appropriate to use in the learning process.
A Spectral Algorithm for Decoding Systematic BCH Codes

A novel method of spectral decoding for systematic BCH codes has been proposed. This method has a simple description and a small computational complexity.
The Impact of Language Syntax on the Complexity of Programs: A Case Study of Java and Python

Programming is the cornerstone of computer science, yet it is difficult to learn and program. The syntax of a programming language is particularly challenging to comprehend, which makes learning arduous and affects the program's testability. There is currently no literature that definitively gives quantitative evidence about the effect of programming language complex syntax. The main purpose of this article was to examine the effects of programming syntax on the complexity of their source programs. During the study, 298 algorithms were selected and their implementations in Java and Python were analyzed with the cyclomatic complexity matrix. The results of the study show that Python's syntax is less complex than Java's, and thus coding in Python is more comprehensive and less difficult than Java coding. The Mann-Whitney U test was performed on the results of a statistical analysis that showed a significant difference between Java and Python, indicating that the syntax of a programming language has a major impact on program complexity. The novelty of this article lies in the formulation of new knowledge and study patterns that can be used primarily to compare and analyze other programming languages.
A Rule-Induction Approach for Building an Arabic Language Interfaces to Databases

In the field of Natural Language Interfaces for Databases (NLIDB), most of the solutions considered for translating natural language queries into database query language is based on linguistic operations. The application of these operations makes it possible to translate the natural language queries into an unambiguous logical interpretation. However, this task is extremely complex and requires excessive time. While nowadays emphasis is placed on the use of machine learning approaches to automate the operation of natural language processing systems. From this, the automation of the natural language queries translation process into a logical interpretation is interesting and remains a major challenge in the field NLIDB. Also, it can have a direct impact on reducing the complexity of the operation of NLIDB. In this study, we focused on applying a new approach to automate the operation of NLIDB. In this approach, we applied a supervised learning technique to induce rules that transform natural language queries into unambiguous expressions.
Supporting Online Toxicity Detection with Knowledge Graphs

Due to the rise in toxic speech on social media and other online platforms, there is a growing need for systems that could automatically flag or filter such content. Various supervised machine learning approaches have been proposed, trained from manually-annotated toxic speech corpora. However, annotators sometimes struggle to judge or to agree on which text is toxic and which group is being targeted in a given text. This could be due to bias, subjectivity, or unfamiliarity with used terminology (e.g. domain language, slang). In this paper, we propose the use of a knowledge graph to help in better understanding such toxic speech annotation issues. Our empirical results show that 3% in a sample of 19k texts mention terms associated with frequently attacked gender and sexual orientation groups that were not correctly identified by the annotators.
AGFNet: Attention Guided Fusion Network for Camouflaged Object Detection

The camouflaged object detection (COD) task is challenging because of the high similarity between target and background. Most of the existing COD methods are based on the transfer learning of salient object detection (SOD) network, which is not efficient for the COD task. It is also difficult to accurately capture the edge information of the object after the coarse-grained localization of the camouflaged object. In this paper, we propose a novel network: Attention Guided Fusion Network (AGFNet), for the task of COD. We use low-level and high-level features to extract edge and semantic information. To solve the problem of discriminating and localizing the camouflaged object, we adopt a dual-attention module, which can selectively determine the more discriminate information of the camouflaged object. In addition, our method applies a module to fuse edge and semantic information for refinement to generate sharp edges. The experiments demonstrate the effectiveness and superiority of the proposed network over state-of-the-art methods.
BrowVis: Visualizing Large Graphs in the Browser

A recent stream of research focuses on building high-performance data analysis and management systems that run completely in the browser. Indeed, today personal devices offer non-trivial amount of computing power, while the latest Web browsers provide powerful JavaScript engines. On the other hand, the use of visualization to present and analyze networks is taking a leading role in conveying information and knowledge to users that operate in multiple domains. In this scenario, the aim of our research is to explore the scalability limits of a system that executes the full graph visualization pipeline entirely in the browser. In this paper, we present BrowVis, a self-contained system to compute interactive visualizations of large graphs in the browser. Experiments show that, on a common laptop, BrowVis can visualize graphs with thousands of elements in seconds, as well as graphs with millions of elements in minutes. Once the initial visualization has been computed, BrowVis makes it possible to interactively explore the represented graph by following a details-on-demand paradigm. The use of BrowVis in practice is demonstrated by a case study dealing with a real-world scientific collaboration network.
Village Complaints Application System Based On Android Webview

Many residents in the village of Entalsewu, Buduran District, Sidoarjo Regency, often complain about the situation in the village. Complainants do not know where to go to convey their complaints in the village environment. For example, roads that are damaged and have potholes due to frequent vehicles and extreme rainy weather along the roads in Entalsewu village and also the dead and dim public street lighting (PJU) have not been repaired so that road users experience accidents at night, many residents' houses flooded water that enters the house. Therefore, to overcome this problem, the author designed a village complaint application system based on android webview with a case study of village development. Which aims to make it easier for the public to make complaints in the village of Entalsewu, Buduran District, Sidoarjo Regency. This android application can be used by the public to make complaints online. This application can also make it easier for the village government to respond to community complaints. In this study, the author uses the Waterfall method as a process or flow of research results.
FedBC: An Efficient and Privacy-Preserving Federated Consensus Scheme

The capacity of federated learning (FL) to tackle the issue of “Data Island” while maintaining data privacy has garnered significant attention. Nonetheless, semi-trusted cloud platforms can infer the actual data distribution of local users via intermediate characteristics such as gradients. The blockchain proposal has resolved the challenge of consistency in decentralized data sharing. It is difficult to guarantee the accuracy of the block’s data based on the existing study. To address this issue, we present a federated consensus mechanism that is both efficient and protective of privacy (FedBC). This approach can effectively limit the impact of Byzantine nodes on consistency and accuracy. During this procedure, crucial intermediate parameters, such as the gradient of the data owner, will not leak. Specifically, we proposed a gradient-similarity-based secure consensus technique (SecPBFT) to minimize Byzantine gradients. All nodes transmit the DO sub-gradients during each consensus round and cluster and partition the sub-gradients in the consensus with care. Then, the dynamic elimination of Byzantine gradients in each round of the consensus procedure is accomplished. Theoretically, we demonstrated the scheme’s security and confirmed the scheme’s efficacy. FedBC’s attack success rate is at least 50% lower than if no defense mechanisms were in place.
Evaluation of the Quality of Service of Delivery Applications and its Influence on Consumer Loyalty

The objective of this study is to evaluate the quality of service of delivery applications, in order to have knowledge of which factors are most important for consumers when making their online purchase process and how much influence these factors have on the purchase process. consumer loyalty. Therefore, a quantitative study was carried out through a survey that uses several measurement models such as ESQUAL. This survey was applied online to 319 residents of the city of Guayaquil who use delivery applications. In th e analysis of the results, the data was divided into three groups: "General", "Uber Eats" and "Other apps", to evaluate the behavior of the variables of each group by estimating a Structural Equation Model. Among the main results, it is highlighted that the variables Guarantee, Personalization, Relationship with the brand and Traceability have a positive and significant effect on the loyalty of users of delivery apps and that "Uber Ea t s"is the market leader despite that its users consider that the shipping cost is somewhat high.
On Line Monitoring System of Power Optical Fiber Transmission Network Under Internet of Things Technology

The traditional OTD power optical fiber transmission network online monitoring system takes a long time to monitor the network data, and the monitoring effect increases. Therefore, the power optical fiber transmission network online monitoring system under the Internet of things technology is designed. The sensor and microcontroller are designed in hardware. Analyze the functional requirements of on-line monitoring system in software; The data acquisition module of power optical fiber transmission network is established based on the Internet of things, and then the system software function is realized. By means of comparative experiment, it is verified that the online monitoring effect of the new system is better and has great popularization value.
Using Artificial Intelligence Applications For Teaching and Learning Foreign Language: Facts and Solutions

In this research, the author will analyze specifically the facts of using artificial intelligence (AI) technology in teaching Foreign Language around the world today. From there, the author will propose some solutions to further improve the effectiveness of using AI technology in teaching and learning English in particular and foreign languages in general in Vietnam in the next period. To do this research, the author uses many kinds of methods such as collecting and analyzing data, making survey and polls, referring related documents, etc.
Performance Analysis in HyperFlex and vSAN Hyper Convergence Platforms for Online Course Consideration

With the ubiquity of high-speed networks and cloud technologies, hyper-convergence (HC) has become commonplace and satisfies flex allocation requirements. This study compared the VMware virtual storage area network (vSAN), which has the largest market share, with Cisco HyperFlex, released by Cisco for high-level network applications, to assess the performance of various HC technologies in running virtual machines in most virtualized environments. The experiments consider the benchmark (HCIBench) to evaluate the platform’s performance. The benchmark provides objective performance scores. Thus, the performance results derived by HCIBench could be applied to discuss the appropriate scenarios for both VMware vSAN and Cisco HyperFlex. The experiments simulate common application scenarios to discover good HC platforms for real-world requirements. The VMware vSAN demonstrated more robust overall performance (about 38.18% and 22.72% improvement for IOPS and transmission speed, respectively), the HyperFlex Data Platform provided better performance wrote latency (about 20.32% improvement) when few virtual machines were used, and the write load was heavy. The difference in CPU usage between the two platforms is not too much (about 2.565%). The vSAN is recommended for general purposes, while HyperFlex performs better in areas with high write requirements (such as the data center).
Pengaruh Model Pembelajaran Problem Based Learning Terhadap Kemampuan Menulis Teks Prosedur pada Siswa Kelas XI SMK Swasta Jambi Medan

One of the writing activities contained in learning Indonesian at SMK 2013 curriculum is writing procedure text. The selection of the problem based learning model in this study was based on the idea that the problem based learning model could stimulate students' enthusiasm to be actively involved in their learning experience. The problem-based learning model requires students to think, understand and find the steps that must be taken correctly in writing procedure texts. The results of the research that have been explained that between X1 and X2 obtained from the work of students writing procedural texts from class XI-1, totaling 35 students, obtained a satisfactory assessment or there was an influence that occurred in the learning process. In the learning process at the first meeting, students still used the lecture method with a total score of 2,354 while using the problem based learning model, the students got an overall score of 2,842, in this case there were differences in the process or results in learning to write students' explanatory texts. After getting the overall results, as explained in the description of the research results and hypothesis testing using the steps or formulas used and obtaining the overall value, n = 35 and = 0.05, then the t = 1.692 value is obtained. Because tcount &gt; t table or 33.54 &gt; 1.692 then Ho is rejected. These results provide an explanation that in using the problem based learning learning model there is an influence in the applied learning.
The effect of immersive virtual reality-based learning activities on students critical thinking skills

The increasing development of immersive technology has provided students with greater opportunities to be actively involved in learning. However, there were few empirical studies that explore the effect of Immersive Virtual Reality (IVR) based activities on students’ critical thinking skills. To address this gap, this study develops a series of IVR-based multivariable calculus lessons and further examines the effects of these lessons on critical thinking skills. This study used a quasi-experimental approach where pretest and posttest were carried out to measure critical thinking skills. A total of 90 third-year mathematics education students from two classes were randomly assigned to the experimental and control groups. Students in the experimental group were taught by IVR-based learning activities, while students in the control group were taught by regular practical teaching. The results showed that students who participated in learning with IVR-based activities developed much higher critical thinking skills than students who took lessons with traditional teaching methods. This study provides empirical evidence for the use of IVR in improving critical thinking skills.
Informatization of Constructive English Learning Platform Based on Artificial Intelligence Algorithm

In recent years, intelligence is the new direction of today's social development, and it is also a new feature of the development of informatization. With the rapid development of technologies such as artificial intelligence, the Internet of Things, big data and cloud computing, smart products and devices such as smart homes, smart robots, smart toys, and smart buildings have emerged, which have brought great changes to people's life and work styles. Through the constructive research on artificial intelligence algorithms, this paper designs a relevant information-based English learning platform, which can greatly improve the efficiency of English learning in the traditional textbook mode, and cultivate the interest and enthusiasm of college students to learn English. Through the research of artificial intelligence algorithm, this paper finds that informatization of constructive English learning platform focuses on building the ecological environment of students' autonomous learning, which can greatly improve students' autonomous learning ability, it take the student as the center, to provide learning resources and learning methods, at the time let the students actively constructing autonomous learning awareness, respect and encourage students to have different progress and development. The final results of the study show that the number of students who choose learning interaction is the largest, accounting for 41%, followed by the number of students who choose independent learning, accounting for 31%. It can be concluded that students attach most importance to learning interaction, which can greatly improve students' enthusiasm and initiative in learning.
SYNCHRONOUS AC CHOPPER FOR UNIVERSAL MOTOR SPEED CONTROL USING FUZZY LOGIC

The use of Universal type motors is very commonly used, both in daily life and in research activities. The universal motor can be used as prime mover generator PMSG (Permanent Magnet Synchronous Generator), which in its application there are obstacles, namely the difficulty of stabilizing the speed due to the influence of changes in the load connected to the PMSG, this affects the output voltage generated by the system. In this case, a speed stabilizer system is needed to stabilize the output voltage generated based on the load given to the system. AC Chopper is one of the circuits that can be applied in a speed control system that functions as an AC-AC voltage regulator which is the input of the Universal motor. Synchronous AC Chopper is one type of AC Chopper circuit which according to previous research has better performance in terms of efficiency than Basic AC Chopper. As for this control system, Fuzzy Mamdani logic is flexible and has a tolerance on existing data with control results having a settling time of ±15 seconds and an average efficiency of 84.99%.