Reviewerly/exHarmony huggingface dataset:
Research on the Learning of University Students Majoring in Mathematics in China

Recently, the China government has increasingly attached importance to the development of basic science. As the reserve talents to promote the development of mathematics, university students majoring in mathematics have received the attention of researchers for their mathematics learning. At present, there are many studies on students majoring in mathematics, however, few complete reviews and sorting in this aspect. In this paper, the literature analysis method and statistical method are adopted to review the relevant research literature from 2003 to 2022. The following conclusions are drawn: (1) There are three main research aspects about mathematics learning of college students majoring in mathematics: the current situation, the influencing factors, and strategies to help them. (2) Regarding the situation, there is more research on the problems of students majoring in mathematics and a lack of analysis and research on the causes. (3) About the influencing factors, scholars have explored ample influencing factors, and have a certain research basis and depth. But the complete influencing factors and the mechanism of the factors influencing them are still a blank spot. (4) The strategies are mainly aimed at universities and teachers, and the research has put forward some commonly recognized strategies. However, these strategies are broad and general, lacking pertinence for students majoring in mathematics. It is necessary to analyze the causes of problems existing and put forward more targeted suggestions for the students majoring in mathematics to make research more comprehensive and in-depth.
Augmented reality for visualization of complex vibroacoustic data sets

As technical solutions become more and more complex, analyzing and understanding them must become easier. Especially abstract or perception-biased fields, such as acoustics, can benefit from displaying the behavior of a noise radiating structure in an understandable manner. How can the acoustic properties of a technical component or a system be displayed in such an understandable way? Due to the current advances in technology regarding the mixed reality spectrum, the HoloLens2 was chosen as the hardware component to run an application and display structural properties visually. The application is required to display enough data to convey the information without impeding user experience. The application is divided into subprojects. Each subproject is developed and tested in a separate environment. After verification the subprojects were implemented. AR-visualization reduces the necessary effort to understand the structure's acoustic behavior. Furthermore, explicit knowledge of acoustics is not required to understand the application. In the future, this application can be expanded with additional features such as auralization or a live feed of structures.
SIGLOG Monthly 233

An annual award, called the Alonzo Church Award for Outstanding Contributions to Logic and Computation, was established in 2015 by the ACM Special Interest Group for Logic and Computation (SIGLOG), the European Association for Theoretical Computer Science (EATCS), the European Association for Computer Science Logic (EACSL), and the Kurt Goedel Society (KGS). The award is for an outstanding contribution represented by a paper or by a small group of papers published within the past 25 years. This time span allows the lasting impact and depth of the contribution to have been established. The award can be given to an individual, or to a group of individuals who have collaborated on the research. For the rules governing this award, see https://siglog.org/alonzo-church-award/, https://www.eatcs.org/index.php/church-award/, and https://www.eacsl.org/alonzo-church-award/.
Students’ perceptions and how to teach at postgraduate engineering programs

This article shows an insight about the quality of the teaching in the engineering programs, specifically in the master and PhD programs. It identifies the most important aspects to determine the quality of the professors in advanced academic contexts. In order to do so, research is done with students from master and PhD programs about the dimensions of teacher‘s performance. For the methodology, a discriminant analysis is used to determine the most considered aspects by students when choosing the most important one when judging the high quality of a professor
Unsupervised and Categorical Sentiment Segmentation of Customer Product Reviews

In Consumer Review Analysis (CRA), identification of the context of reviews holds paramount importance. In this purview, it is the responsibility of all businesses to suffice their underlying sectors with a structured and classified list of consumer feedback, available on various online platforms. However, generally, reviews and feedbacks are available in a very unorganized manner and need to be tagged and distributed properly to appropriate sectors. To address the problem, we propose a comprehensive model, employing sequential Clustering, Sentiment prediction and subsequent ranking of reviews. To validate the proposed model, data from a Samsung smartphone manufacturing firm was used. The robustness and stability of our model have been examined through different performance indices-Silhouette Index (SI), Davies-Bouldin Index (DBI) and Calinski Harabasz Score (CHS) Score. Our analysis shows a distinct categorization of reviews based on their contexts with minimal noise in the classification measures. Our custom declared coefficient, Relevant Voting Score (RVS) has been found to rank the reviews in an accurate priority list thereby helping the sectors to contemplate only the most important customer feedback.
Evaluation method of airport pavement partition coverage detection based on human-robot interaction

The coverage detection of airport pavement is the premise to ensure civil aviation safety. Due to the hard requirements of ultra-high security of the airport itself, the application of robots to unmanned coverage detection in the airport is not accomplished overnight, but a process of step-by-step and continuous technical iteration. Therefore, for different application stages of the robot in the airport, an appropriate method should be given to guide airport maintenance engineers to flexibly adjust the partition coverage operation mode. In this paper, we design an evaluation index named Partition Quality Function (PQF) to evaluate the quality of partition coverage. In PQF, the degree suitable for human-robot interaction, the efficiency of coverage planning and the coverage failure area are taken into account. And the proportion of factors can be adjusted through the weight coefficient. Then, in order to facilitate engineering application, we design six kinds of rectangular partition templates and use genetic algorithm to optimize PQF. Finally, through simulation research, we discover PQF partition law under different weight coefficients, and gave the PQF setting of the robot in different application stages of the airport. It is an important step to promote the actual landing of robot coverage detection technology in the airport.
Design and implementation of automatic test system for multi-cabin joint test of space station

In order to solve the problems of information interaction, instruction transmission and joint interpretation in the multi-cabin configuration of space station, an automatic test system supporting multi-cabin joint test is designed. The general design of automatic test system is given. To standardize the interface and protocol for information transmission in each cabin. Design multi-dimensional interpretation platform to realize multi-cabin data comparison and interpretation. Developing comprehensive analysis platform to realize multi-cabin information association analysis. The application results show that the multi-cabin joint test of the space station is realized automatically and intelligently through the test case design, test program execution, data interpretation, test result analysis and report generation. It supports the ground test and verification work under various configurations of the space station, and has high engineering application value.
Temporal Enhance and Spatial Gated Network for Group Activity Recognition

The main goal of Group Activity Recognition(GAR) is to analyze the group behavior in a multi-actors scene. It is a challenging task that integrates group activity features from individual actors who frequently interact with each other. However, existing state-of-the-art methods do not consider temporal information and take full advantage of spatial relations. Moreover, existing methods utilize max-pooling operation to generate group activity features, which introduces noise into group activity features and leads to bad performance. To tackle these problems, a temporal enhance and spatial gated network is proposed. To fully utilize the rich temporal features and spatial features, two branches are set up to extract temporal features and actor interactive relations, respectively. Then, a feature aggregation module is used to generate group activity features, which can decrease the noise introduced by the max-pooling operation. We conduct a series of experiments on two stand datasets. Experimental results on these benchmarks demonstrate that the proposed approach achieves state-of-the-art performance. Compared with previous work, the recognition accuracy increases by 0.5%~1.0%.
Outlier Detection Algorithm Based on Fuzzy CMeans and Self-organizing Maps Clustering Methods

Data mining and machine learning methods are important areas where studies have increased in recent years.Data is critical for these areas focus on inferring meaningful conclusions from the data collected.The preparation of the data is very important for the studies to be carried out and the algorithms to be applied.One of the most critical steps in data preparation is outlier detection.Because these observations, which have different characteristics from the observations in the data, affect the results of the algorithms to be applied and may cause erroneous results.New methods have been developed for outlier detection and machine learning and data mining algorithms have been provided with successful results with these methods.Algorithms such as Fuzzy C Means (FCM) and Self Organization Maps (SOM) have given successful results for outlier detection in this area.However, there is no outlier detection method in which these two powerful clustering methods are used together.This study proposes a new outlier detection algorithm using these two powerful clustering methods.In this study, a new outlier detection algorithm (FUSOMOUT) was developed by using SOM and FCM clustering methods together.With this algorithm, it is aimed to increase the success of both clustering and classification algorithms.The proposed algorithm was applied to four different datasets with different characteristics (Wisconsin breast cancer dataset (WDBC), Wine, Diabetes and Kddcup99) and it was shown to significantly increase the classification accuracy with the Silhouette, Calinski-Harabasz and Davies-Bouldin indexes as clustering success indexes.
Communication challenges in distributed student projects

Student projects have been widely adopted in software engineering education. Project teams are composed of students in the same institution, and students can meet and communicate face-to-face regularly. The Covid-19 pandemic, however, forced the student projects to rapidly transition to remote mode and adapt to the virtual team. Virtual teams in distributed environments face challenges due to distance factors that separate collaborators from each other. This study aims at investigating the communication challenges student teams encountered and managed to overcome. We report on an analysis of data collected from reports and interviews in the software project course delivered in fall 2020. There were 57 participants, forming 10 project teams in the study. The results show that remote work negatively affects the social aspects of project teams, especially early communication difficulties in a project. The teams were able to handle most identified challenges but had less interest in tackling those that they did not see as a risk to project completion, which would have most likely caused problems in real-world projects. This study improves understanding of communication challenges in student project teams and the findings serve as a resource for course teachers to design student project courses in the context of virtual teams.
Family of CV states of definite parity and their metrological power

Abstract We introduce a new family of continuous variable (CV) states of definite parity originating from the single mode squeezed vacuum (SMSV) state by subtracting an arbitrary number of photons from it. A beam splitter with arbitrary transmittance and reflectance parameters redirects input photons in an indistinguishable manner to the output and measuring modes followed by probabilistic measurement, thereby converting the initial SMSV photon distribution into a new one after we know the number of registered photons. The family of the measurement-induced CV states is solely determined by the SMSV parameter which inevitably decreases when generating the CV states. We show that the quantum state engineering of CV states of definite parity by subtraction of multiphoton state from input SMSV state can significantly enhance their nonclassical properties (more squeezing, larger value of quantum Fisher information) compared to the initial state from which they originate, which, combined with a significant gain in brightness, makes them attractive for ultra-precise measurements. The potential of the new family of CV states of a certain parity, to which original SMSV, no doubt, belongs, can become decisive for a new push to implementation of optical quantum metrology protocols.
Different strategies to improve isochrone voyage optimization algorithm

Voyage optimization can be essential in ship routing for autonomous and intelligent operations.Various optimization algorithms were proposed to search for optimal ship routing with minimized fuel consumption and accurate arrival time.In this paper, the Isochrone method, which is well-known for its robustness and efficiency, is further improved by different strategies to inherit the original capability of computation efficiency, and overcome its incompetence of multi-objective optimization, reliable convergence for approaching destination and feasibility for practical navigation.Especially an innovative way of searching at a late stage is proposed, as well as a flexible evaluation of cost functions according to different optimization objectives.The improved Isochrone method can fast optimize a shipping route with multi-objective purposes, such as accurate expected time of arrival and minimum fuel consumption.The effectiveness and efficiency of different improved Isochrone methods are verified by several North Atlantic voyages collected by a chemical tanker.
THE ROLE OF RISK MANAGEMENT IN ACHIEVING SUSTAINABLE DEVELOPMENT IN MUNICIPALITIES

Risk management is of particular importance at the present time, and it constitutes a new trend in the Jordanian municipalities.All industries have witnessed acceleration and great changes in recent years.Introducing risk management in municipalities to raise the level of efficiency of performance and work procedures and improve the method of performance of risk management in the municipality, and how to deal with risks in terms of frequency, severity and coping strategies, by avoiding risks or transferring them to another party or reducing or retaining them and accepting their results.The research concluded with a number of recommendations, the most important of which is the use of a risk management department that carries out its management tasks, within the organizational structure as an independent department.
Sistem Pengambilan Keputusan Pemberian Kredit Pemilikan Rumah Menerapkan WASPAS

Decision Support System (DSS) is an interactive information system that provides information, models and manipulates information, or helps someone make accurate and targeted decisions. So a decision support system is needed to determine the eligibility of customers to take home equity loans (HPR). In this study, the Comprehensive Assessment Method or WASPAS is used to determine the eligibility of prospective mortgage holders. Several criteria are used to make decisions, including age, income, debt, occupation, and credit rating.
Klasifikasi Mutu Pembelajaran Hybrid berdasarkan Algoritma C.45, Random Forest dan Naïve Bayes dengan Optimasi Bootsrap Areggating (Bagging) pada masa COVID-19

This study aims to find the best model from the 3 (three) models chosen, namely Random Forest, Naïve Bayes and C4.5 against the classification of hybrid learning quality held at SMK Cendekia Cirebon City during the COVID-19 period. The research method is carried out by referring to the approach or technique of machine learning with the stages of data collection, data preparation, data transformation, modeling and evaluation. The final results of this study are measured by the level of accuracy of hybrid learning quality aspects, namely teachers, subject matter, integrity, student motivation, and technology resources with bad, sufficient, good and very good categories.. Based on the experiments that have been carried out, the accuracy results for the Random Forest algorithm were obtained by 93.92%, Naïve Bayes by 93.22% and C4.5 by 77.16%. Thus this study recommends the best classification algorithm model based on dataset processing to measure this hybrid learning quality model is Random Forest
Identifikasi Kematangan Buah Menggunakan Metode Gray Level Co-occurence Matrix pada Citra Digital

In the current era of information technology, the use of images is widely applied in various aspects of life. Some of the uses of image processing include the fields of military, medicine, education, agriculture and so on. One example of the use of image processing that will be discussed in this study is in the agricultural sector. Farmers can take advantage of technology in selecting fruit with the appropriate maturity level. In terms of selecting fruit based on the level of maturity, some fruit farmers still use the conventional method or with the human sense of sight, namely the eye. Therefore, this study was conducted for preliminary research that can change the conventional method into system that uses technology that makes a computerized way of identifying fruit maturity levels. The system that will be used to identify fruit maturity uses the Gray Level Co-occurance Matrix method on digital images and Euclidean Distance as a classification method. This application is built using MatLab 2019a programming. The test results show that the Gray Level Co-occurance Matrix and Euclidean Distance methods can be used to identify the ripeness of guava, oranges, bananas, papayas and mangoes into three categories, namely raw, unripe and ripe. The Gray Level Co-occurance Matrix and Euclidean Distance classification methods succeeded in identifying fruit maturity with an overall success rate of 87%.
Chroma Key untuk Mengubah Warna Pakaian dengan HSV dan Morfologi pada Citra Digital

Currently, Indonesia is still under the influence of the COVID-19 virus. Indonesian people buy necessities of life on the online market. Clothing is a daily necessity that people often buy online. This has an impact on increasing online clothing sales, but not all clothes are according to the tastes of buyers. Therefore we need an application that is used to speed up changing the color of clothes according to the needs of buyers. The chroma key application that is used to change the color of the clothing image uses the HSV and morphology classification methods. Edge detection and median filters are used to improve the quality of color shift results with HSV. This application is built using MatLab 2015a programming. The test results show that the HSV classification method is better at changing the color of the clothing image than the morphological method. The HSV classification method was successful in changing the color of clothes well with a 100% success rate. While the morphological method succeeded in changing the color of the clothes with a success rate of 60%.
Design, Development And Usability Analysis of Pre-Loved Goods Trading Application With Agile Approach

Preloved goods are used goods that are still of good quality. When cleaning the house sometimes found a number of Preloved items, where these items are only used once or not used at all and stored for quite a long time at home. Used goods that accumulate in the house make the room in the house even narrower. Therefore, Preloved items are more profitable if they are sold rather that being thrown away or stored. Besides that, selling Preloved items can get extra money and help in environmental preservation. So the writer got an idea how to use a website as a marketplace to sell Preloved goods in Batam city, namely the Batam Preloved Shop. Batam residents get information on Preloved items they want to buy through this marketplace. The method used in designing and developing the Batam Preloved Shop is Agile. Next, test the system by testing the Black Box and System Usability Scale (SUS). The results of the Black Box test show that the Batam Preloved Shop system is running as expected and an analysis of user satisfaction using the System Usability Scale (SUS) obtains an average value of 81, so it can be concluded that the Batam Preloved Shop system has been running well according to its functions and uses
Penerapan Metode Multi Attribute Utility Theory Pada Sistem Pendukung Keputusan Seleksi Bantuan Untuk Madrasah

Madrasah is one form of religious education that has contributed greatly to the development of the nation. Through madrasas, they are able to give birth to a generation of Islamic character and national insight, but the selection process for madrasa aid recipients in the city of Gorontalo is currently not optimal in terms of determining madrasa aid recipients, this occurs due to inaccuracies between recipient data and existing requirements, the selection process for recipients of assistance requires a long time, lack of accuracy between the criteria and requirements of the beneficiary so that it is vulnerable to manipulation. The research objective is to design a Madrasah Assistance Selection Decision Support System applying the Website-Based Multi-Attribute Utility Theory Method so that the selection process for providing madrasah operational assistance can be carried out optimally and measurably using decision-making methods so that it is expected to determine more precise selection results. This study uses whitebox and blackbox testing. Whitebox testing is testing with testing techniques on program flow, logical structure and program procedures by mapping flowcharts, then calculating the number of edges and nodes. The black box testing method focuses on the functional importance of the software. Therefore, blackbox testing allows software developers to create a set of input conditions that will train all functional requirements of a program whether it runs as expected or vice versa. Based on the results of whitebox testing on one of the processes in this system, namely the value data module with balanced results, namely Cyclomatic Complexity (CC) = 4, then this system is declared to be running well. While the results of the blackbox test system can run as expected and efficient