Reviewerly/exHarmony huggingface dataset:
Research on Personal Credit Risk Assessment Based on Combination Weight and Shap Interpretable Machine Learning

With the continuous promotion of e-commerce platform installment payment and P2P credit platform, personal credit risk assessment is becoming more and more important for e-commerce and users Taking the data of Tianchi competition platform as a sample, this paper constructs an index system for personal credit risk assessment, and calculates the combined weight of each index through the critical method and entropy weight method, and weights it to obtain three factors: basic information, credit information and lending behavior information.Based on the quantified three indicators and the unbalanced sample algorithm, XGBoost and lightGBM are used to predict credit risk, it is found that the performance of these two methods is basically the same.This paper uses the SHAP-values interpretable machine learning method to explain the importance of these three factors.The empirical results show that the accuracy of XGBoost and lightGBM is higher than 80%, and the order of the importance of the three factors is: "basic information" is higher than "lending behavior information" and higher than "credit information".Finally, this paper puts forward relevant suggestions for the stable development of enterprise risk control and credit industry.
Speech Instruction Recognition Method based on Stacking Ensemble Learning

In the field of speech instruction recognition, deep learning technology can significantly improve recognition performance, which has become a new research hotspot. However, due to the increasing scale of data, it is difficult to achieve the ideal classification effect using a single model. Aiming at this problem, a speech instruction recognition method based on Stacking ensemble learning is proposed. This method combines deep learning with ensemble learning and applies it to the task of speech instruction recognition. Perform preprocessing and feature extraction on speech data to extract different audio features; build multiple deep models as primary classifiers, and input different audio features into different primary classifiers for training. A secondary classifier is constructed based on the SoftMax regression model, the output of the primary classifier is used as the input of the secondary classifier, and the stacking ensemble algorithm is used for learning to obtain the final recognition result of the speech instruction. The effectiveness of the method is demonstrated through speech instruction recognition experiments on large-scale datasets.
Organizers

List of organizers of the Musical Metacreation 2014 AIIDE Workshop.
The Construction of Multi-Teaching Modes of Higher Vocational Mandarin Training Courses

As one of the working languages of the United Nations, mandarin is the way for China to face the world and go to the world.A fluent standard of Mandarin is very important for students in higher vocational colleges.Today, when the Ministry of Education continues to promote the quality education of higher vocational students, teachers and schools must fully implement the era of teaching and educating people, building morality, and cultivating all-round development.The teaching goal of newcomers is to improve the comprehensive level of oral communication and communication of vocational college students, and to help vocational college students overcome many difficulties and pass the mandarin proficiency test.
Informatization of Educational Management in Colleges and Universities

With the rapid development of today's social science and technology, network information technology has been widely used in all walks of life, and education, as an important pillar of the national economy, must also be reformed and developed.In this context, schools must carry out informatization construction and use modern scientific and technological means to improve the level of teaching management.At the same time, it can also effectively improve the level of school-running management, thereby promoting the improvement of the market position of colleges and universities.The purpose is to let students establish a correct learning concept, clear learning direction, strong learning motivation, and have a love for learning and a willingness to learn.Interests and hobbies to study scientific and cultural knowledge, and have the will to not be afraid of hardships, setbacks, and perseverance.Learning strategy education, including how to make a study plan, how to preview before class, how to take each class well, how to review and summarize knowledge.The purpose is to let students understand the general process of learning and characteristics, grasp the general mode and principle of learning.
PWL for the Twenty-First Century Academic Philosopher

In this essay, I sketch a third possibility between teaching PWL solely as history of philosophy (which seems to inescapably pull against its own conception of philosophizing), and the fascinating recent attempts by scholars to experiment with introducing modes of teaching and assessment which would reactivate ancient spiritual exercises within the modern university. This third way takes for granted that, for the foreseeable future (and if academic philosophy widely survives the twenty-first century’s recalibration of the university), it will do so as a primarily theoretical discipline. Nevertheless, it proposes that insights from PWL’s re-conception of philosophy as a situated, social as well as ethical activity can and ideally should be integrated into such modern syllabi. This can be done by introducing and teaching (a) capstone unit(s) for advanced students which would reflect critically on what it is to be an academic philosopher today and the ways that the fact that philosophy is institutionalized as a professional discipline in neoliberal universities creates pressures towards particular forms of intellectual and ethical vice and sophistry. Based on a course taught at the author’s home university, it examines how Plato’s Republic, Bacon’s Novum Organum, and Kivisto’s Vices of Learning prompt students, respectively, to consider the place of the philosopher in the “city,” their own (and everyone’s) propensities towards forms of epistemic bias and partiality, and the ways that institutionalized competition for status can promote forms of pride, vanity, and misanthropy in scholars. Encountering and discussing these texts, it is argued, can prepare students for the realities of philosophizing in the professional universities of the twenty-first century, helping them to identify ways philosophers can go wrong, and helping them to identify chastened, more Socratically self-aware ways of thinking, reading, arguing, and understanding what philosophers do.
Using Machine Learning classification methods to detect COVID-19 Status in Selangor District

Recently, Covid 19 pandemic has been recognized as a public health emergency of international concern. According to global COVID-19 infection data, the total number of cases is over 147 million, with over 3 million fatalities. Common model that use to predict binary outcome is Logistic regression model. However, the majority of the models have not been implemented widely by using ML approaches. Thus, the interest of this study has been coined to the Covid 19 cases prediction model that influence the extend of risk to urge Covid 19 infection. Therefore, this study addressed how to use four ML algorithms offered by Rapid Miner software tools to identify the optimum classification model. The results show that Decision Tree has been very promising to produce a high percentage of accuracy rate of 75.47% compared to other models. Further research on the data structure is necessary to be conducted in order to address problems like bias and an unbalanced dataset. In addition, new factors like vaccination status should be incorporated into the model to determine whether the respondent is at risk of contracting COVID 19 or not.
Prototype of a decision support system in medical diagnostics based on a statistical approach

A statistical approach is proposed for the preliminary diagnosis of human diseases by blood parameters as a system for supporting medical decision-making. The authors have developed a classifier based on polynomial regression and generating probabilistic estimates. Applications have been implemented that allow both diagnosing the patient's condition from practically healthy to the maximum degree of damage (oncology) for a particular body system, and determining the area of tumor localization in oncological disease.
MEANINGFUL INDICATORS IN THE EVALUATION OF PEDAGOGICAL PROCESSES AND RESULTS OF PROFESSIONAL AND PEDAGOGICAL ACTIVITY

The indicators of the pedagogical activity effectiveness are identified and analyzed: the conditions of its implementation, the All-Russian tests, worldwide study and PISA, a demonstration exam and an independent qualification assessment in secondary vocational education, employment of graduates of vocational schools and communication with employers. The article considers economic assessment tools and the degree of their influence on pedagogical processes. The article identifies how results of pedagogical and professional-pedagogical activities influence the meaningful performance indicators of secondary vocational education teachers. The results of the study can be used in the formation and development of modern training system of qualified pedagogical personnel of secondary vocational education.
Predicting prostate cancer in early stage using adaptive randomized tree

Precise and early diagnosis is crucial for the cancer patients to get optimal care. Tools available to predict cancer in advance remains deficient and also there are considerable false positive rates. In order to avoid this, the proposed work focuses on Clinical Data analysis and Image analysis of Ultra sound images to predict cancer at initial stages. In this analysis, Adaptive Randomized Tree (ART) uses clinical data such as percentage of unbound Prostate Specific Antigen (PSA), bound PSA, age, PSA density and PSA velocity and intensity extracted from Ultra sound images as metrics to predict carcinoma. Hence ART has a better prognostic performance than other diagnostic indicators for prostate cancer. This gives the preliminary evidence that ART can be used as an effective diagnosis tool for other type of cancers with appropriate metrics.
A survey of methods for encrypted network traffic fingerprinting

Privacy protection in computer communication is gaining attention because plaintext transmission without encryption can be eavesdropped on and intercepted. Accordingly, the use of encrypted communication protocols is on the rise, along with the number of cyberattacks exploiting them. Decryption is essential for preventing attacks, but it risks privacy infringement and incurs additional costs. Network fingerprinting techniques are among the best alternatives, but existing techniques are based on information from the TCP/IP stack. They are expected to be less effective because cloud-based and software-defined networks have ambiguous boundaries, and network configurations not dependent on existing IP address schemes increase. Herein, we investigate and analyze the Transport Layer Security (TLS) fingerprinting technique, a technology that can analyze and classify encrypted traffic without decryption while addressing the problems of existing network fingerprinting techniques. Background knowledge and analysis information for each TLS fingerprinting technique is presented herein. We discuss the pros and cons of two groups of techniques, fingerprint collection and artificial intelligence (AI)-based. Regarding fingerprint collection techniques, separate discussions on handshake messages ClientHello/ServerHello, statistics of handshake state transitions, and client responses are provided. For AI-based techniques, discussions on statistical, time series, and graph techniques according to feature engineering are presented. In addition, we discuss hybrid and miscellaneous techniques that combine fingerprint collection with AI techniques. Based on these discussions, we identify the need for a step-by-step analysis and control study of cryptographic traffic to effectively use each technique and present a blueprint.
On Perfectly Secure Two-Party Computation for Symmetric Functionalities with Correlated Randomness

A multiparty computation protocol is perfectly secure for some function f if it perfectly emulates an ideal computation of f. Thus, perfect security is the strongest and most desirable notion of security, as it guarantees security in the face of any adversary and eliminates the dependency on any security parameter. Ben-Or et al. [2] [STOC ’88] and Chaum et al. [5] [STOC ’88] showed that any function can be computed with perfect security if strictly less than one-third of the parties can be corrupted. For two-party sender-receiver functionalities (where only one party receives an output), Ishai et al. [9] [TCC ’13] showed that any function can be computed with perfect security in the correlated randomness model. Unfortunately, they also showed that perfect security cannot be achieved in general for two-party functions that give outputs to both parties (even in the correlated randomness model). We study the feasibility of obtaining perfect security for deterministic symmetric two-party functionalities (i.e., where both parties obtain the same output) in the face of malicious adversaries. We explore both the plain model as well as the correlated randomness model. We provide positive results in the plain model, and negative results in the correlated randomness model. As a corollary, we obtain the following results.
Didattica immersiva nell’Ingegneria Agraria. Un caso d’uso nel Laboratorio di Agricoltura Digitale e di Alta Tecnologia

The chapter describes experiences of 360° videos use by the Agrismart Lab Group of the University of Florence. The Agrismart Lab Group focuses on the technological transfer of information obtained during the research phase to provide the greatest possible diffusion and dissemination of discoveries regarding the technological-digital revolution in the agricultural sector. Dissemination, applications, and teaching are the main outcomes of our research activities, and we have fully utilized the SEPA360 project's resources. In particular, the student will be able to see smart farming examples both in the field and in the immersive teaching lab having clearer theoretical notions by 360° viewers. Two case studies (tractor 4.0 and Agrobot) are included in the interactive videos, which are utilized both for learning and verification.
Understanding Security Issues based on App Comment Analysis

Mobile Applications (App) security issues occur in sync with the progress of information technology. User comments serve as a valuable source of information for evaluating a mobile app, for both new users and developers. However, previous works rarely rely on existing comments to provide a detailed summarization of the app's security issues. We present a novel comment summarization framework, SBR-Miner(Security Bug Related-Comment Miner). It first extracts the security-related sentences from the comment sentences using a classification model, then extracts the aspect, opinion, misbehavior of the sentences using a deep learning model, and assigns security issues categories to the triads, and finally visualizes the comment summaries using a radar plot. Our evaluation of the manually labeled dataset shows that SBR-Miner can provide a clearer and more comprehensive aspect than the state-of-the-art, with an average F1 score of 0.92, higher than AR-Miner (0.80) and SUR-Miner (0.81). 92% of developers agree that the SBR-Miner summaries are beneficial, according to feedback from relevant practitioners.
Introducing acoustics as music in the interdisciplinary and inclusive classroom through ski-hill graph pedagogy to teach the meter fundamentals as sound (psychoacoustics)

Although music is sound (acoustics) and listeners experience the physics of acoustics as music, the meter of most music textbooks is the notated meter signature and group of beats notated in ‘measures’ on the page with vertical bar lines. Notation-based representation of the meter is antiquated music theory because new research in acoustics, cognitive neuroscience, and critically music theory (Cohn, 2020) informs otherwise. Cohn’s modern meter theory, a distillation of contemporary meter theory from North America, is the first comprehensive meter theory that acknowledges the meter's psychoacoustic experience and augments notation-based understandings of the meter through the meter the fundamental mathematics of the Ski-hill graph. This paper is a music teacher’s response to the availability of modern meter theory’s Ski-hill graph to represent the meter's psychoacoustic (mind and body) experience. The paper illustrates how listeners articulate their quantification of low meter frequencies such as the duple meter in sets of pulses in ratio 2:1 initiated by 1.2 hz and 2.4 hz experienced concurrently. Also, the triple meter sets of pulses in ratios 3:1 0.8 hz and 2.4 hz (Nozaradan et al., 2011).
Dampak Model Pembelajaran dan Kebiasaan Membaca Terhadap Kemahiran Menulis Bahasa Inggris (Studi Pada Kelas VIII Semester 1 di MTs Muhammadiyah Curup)

The purpose of the study was to describe the effect of learning models and reading habits on English writing skills in class VIII semester 1 at MTs Muhammadiyah Curup. The method used in this research is quasi-experimental. This study involved 60 students of class VIII MTs Muhammadiyah Curup. The data were obtained with a questionnaire instrument and a test instrument. The results of the test data analysis showed that there were differences in the English writing skills of students who participated in the Moodle-based blended learning model with students who participated in conventional learning models. Then, there are differences in the English writing skills of students who have high reading habits and students who have low reading habits. Furthermore, there is no interaction effect between learning models and reading habits on English writing skills.
Teacher Strategies in Teaching Listening During Online Classes

This research discusses the teacher’s strategies in teaching listening at a Vocational High School in Indonesia during online class. The aims of the research are to know the strategies teacher in teaching listening and how the implementation of those strategies especially in situation which online class must be conducted in a Vocational High School in East java, Indonesia. The method used by the researchers is descriptive qualitative research method. The subject of the research is the English teacher in the Vocational High School while the methods of data collection were Observation checklist, interview guidline, and documentation. The data analysis techniques used data collection and documentation. The result of this study indicates that the teaching strategies used by the teacher was Planning, Monitoring, Evaluating, Cognitive, Metacognitive. The implementation of teacher strategies was the teacher looked at the syllabus with the lesson plan, material to teach in the lesson plan must match the class to be taught, the instructions in the listening learning process, then the teacher played the video in learning process. Hopefully, this study might be useful for other researchers as well as teachers who teach English in general and listening in particular.
An Efficient Approach of Security Risk Mitigation in Cloud

Cloud computing is the emerging fields.It has been emerged with new dimensions because of the various services and computing reference model.In serverless architecture, the server is executed by the cloud provider and also manages the resource allocation dynamically.Many organization has adopted the serverless architecture for their work.Product functionality has been concentrated more on serverless architecture.It is a new era of cloud computing technologies and also gives the maturity in the cloud computing.Organization does not have the job of security patches due to the serverless computing in the OS and application servers.Scalability, flexibility, and reduced cost are the benefits of serverless computing.Purchasing, provisioning, and managing backend servers are the worries are not needed by the serverless architectures.The scope of this research is to analyse security flaws in traditional architecture and mitigate those flaws by using serverless architecture, and to implement security in it.
International Panorama of Blended Learning in Science Education: a Systematic Review

Recently studies of technology on science education is mainly related to innovative environments and Blended Learning, combined models of online and face-to-face instruction. Therefore, the Systematics Literature Reviews are tools that provides detailed surveys and discussions methodologicals before their implementation. We carry out an sistematic review through the Parsifal® platform, a website with pre-defined operations. Were analyzed studies published in IEEE Xplore Digital Library, SciELO, Scopus and Springer Link, allowing the identification of 1996 studies, 79 selected according to the inclusion and exclusion criteria of our research. The findings presented specific contents in Virtual Learning Environment, Learning Management System, methodologies not originally used in Blended Learning were also incorporated, with predominance of quantitative analyzes and few reflections on theoretical-methodological aspects. Therefore, the motivation and the reports of the subjects involved in the actions were little considered when using the tools.&#x0D;
A novel encryption method combining software algorithm and spatial light modulator

Images can convey information and needs to be protected, which is usually done by encryption. Traditional image encryption methods usually use software or hardware encryption, which has improvement approach in terms of better safety and robustness. And the study arouses sympathy to researchers based on both software and hardware encryption. This paper proposes an encryption method that combines software algorithm encryption and hardware encryption using a spatial light modulation (SLM) and 4f optical system. Firstly, the image is chaotically encrypted using the chaos encryption algorithm. Secondly, the discrete cosine transform (DCT) is adopted for further encryption based on chaos encryption picture. Thirdly, the cipher text image is transformed into the 4f system using SLM, which performs a random amplitude on the image to achieve hardware encryption. Finally, the simulation and experiment are performed to verify that the scheme, which shows that the method can realize the encryption and unencryption under the combination of software and hardware encryption. The proposed method has application value to guarantee the higher security of information.