Reviewerly/exHarmony huggingface dataset:
A Summary of Speech Pronunciation Research based on the Electropalatograph

This paper mainly introduces and summarizes the current status of electropalatograph research. The research on speech pronunciation based on the electropalatograph mainly uses the pronunciation physiology equipment—electropalatograph instrument to obtain the point-like image recording data when the tongue touches the upper palate during the process of speech pronunciation, and then carries out data analysis and modeling research. The electropalatograph mainly records the contact state of the tongue and palate, which can record and describe the process of speech pronunciation more accurately, objectively and scientifically. It can enrich the relevant theories of experimental phonetics and improve the traditional interpretation of speech pronunciation. Pronunciation mechanism provides reference data.
CONDITIONS OF FORMATION OF INTEREST IN EDUCATIONAL EXPERIMENTAL WORK IN GRADUATES PEDAGOGICAL GYMNASIUMS

The formation of the research interest may by effective enough if the close connection of the educational-cognitive and educational-research activities of pupils. Depending on the profound, process and reasons side of educational-research work didactic conditions must by organized by considerations of opportunities, abilities, and experience of pupils educational-cognitive activities,
DEFYN - A DEFI PORTFOLIO MANAGER

DeFi is short for “decentralized finance,” is a financial application which is highly secured. Decentralized Finance (DeFi) for transferring and managing crypto assets similar to managing fiat assets at present i.e., bank accounts. It gives us exposure to the global markets and alternatives to the currency we use or banking options. DeFi is connected with blockchain, which is decentralized, immutable, and that enables all computers (or nodes) on a network to hold a copy of the history of transactions. DeFi helps us to control and visibility over your money. There is no single entity that has control over, or can alter, that ledger of transactions. It also replaces the bankers and brokers that are enforcing laws against money laundering, creating an unknown economic environment that the regulators would have to traverse and DeFi can address many of the flaws in the existing financial systems, including giving the unbanked access to the financial system. DeFi is distinct as a result of it expands the utilization of blockchain from easy price transfer to complex financial use cases. DeFi products open up financial services to anyone which requires internet connection and they're largely owned and maintained by their users all over the world. So far billions of dollar’s worth of crypto has flowed through DeFi applications and it's expanding day by day. DeFi will be the future which will replace all kinds of transactions. Keywords: DeFi, Blockchain, Money laundering
EVALUATION OF DRAINAGE NETWORK ON GAYA MOTOR ROAD OF SUNGAI BAMBU SUB-DISTRICT TANJUNG PRIOK

&lt;p&gt;Drainage is a way to dispose of excess water that is not in an area. In other words, this drainage also works in controlling checked areas, puddles, and also flooding. Flooding is an event when excessive water flows overland. North Jakarta is an example of the city area in Indonesia that often experiences such flooding events with a repeated frequency every year. With low topographic conditions and also located in the northern coastal area of Java Island, resulting in a large flow of water through North Jakarta. One of the areas that always experiences flooding is Jalan Gaya Motor, Sungai Bambu Village Tanjung Priok sub-district. Flooding in this area caused major losses in economic mobility in North Jakarta because the road is the main access to an s considerable automotive factory area in the Jakarta area. Drainage systems in the area need to be designed to accommodate water discharge especially when it is raining. Drainage capacity needs to be accounted for to accommodate existing water discharge. From the results of the analysis obtained the amount of channel capacity value of 0.46 m&lt;sup&gt;3&lt;/sup&gt;/s, then bulk discharge flood plan in the period of-2 Years 22.95 m&lt;sup&gt;3&lt;/sup&gt;/s, for 5 Years 34.26 m&lt;sup&gt;3&lt;/sup&gt;/s, for 10 Years 41.75 m&lt;sup&gt;3&lt;/sup&gt;/s. With the flooded value of the plan, it was concluded that the capacity of the existing channel could not accommodate rain at the peak discharge of the plan, so the area always experienced flood events. Also, drainage channels in the area were affected by the high rise in water levels due to the influence of tides with an average increase of 0.6 m with an average elevation of water level of 0.607.&lt;/p&gt;
The Relationship between Indonesian Language Learning and the Environment

The environment has a very important role for life. To be able to protect the environment we need understanding and knowledge about the environment. According to Ramadhan et.al (2019) in Indonesia environmental education is not a compulsory subject in schools.
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning

Semi-supervised Learning (SSL) has witnessed great success owing to the impressive performances brought by various methods based on pseudo labeling and consistency regularization. However, we argue that existing methods might fail to utilize the unlabeled data more effectively since they either use a pre-defined / fixed threshold or an ad-hoc threshold adjusting scheme, resulting in inferior performance and slow convergence. We first analyze a motivating example to obtain intuitions on the relationship between the desirable threshold and model's learning status. Based on the analysis, we hence propose FreeMatch to adjust the confidence threshold in a self-adaptive manner according to the model's learning status. We further introduce a self-adaptive class fairness regularization penalty to encourage the model for diverse predictions during the early training stage. Extensive experiments indicate the superiority of FreeMatch especially when the labeled data are extremely rare. FreeMatch achieves 5.78%, 13.59%, and 1.28% error rate reduction over the latest state-of-the-art method FlexMatch on CIFAR-10 with 1 label per class, STL-10 with 4 labels per class, and ImageNet with 100 labels per class, respectively. Moreover, FreeMatch can also boost the performance of imbalanced SSL. The codes can be found at https://github.com/microsoft/Semi-supervised-learning.
discrete region inferred differential evolution feature selection architecture for human face recognition

Face Recognition has received a lot of attention in wide variety of the security application employing face based biometric authentication due to its non intrusive data acquisition. Especially artificial intelligence play important role in face recognition. Numerous researches have been carried out using machine learning technique in order to accuracy of the recognition. In this paper, a novel technique titled as Discrete Differential Evolution (DDE) architecture has been proposed. The proposed architecture will employed after set of the primary image processing steps such as preprocessing, feature extraction and feature selection. Initially preprocessing of the images is performed with image normalization technique and image enhancement technique. Preprocessed image will explored to Linear Discriminant Analysis technique to extract the features of the image. Extracted features will contain some redundant and irrelevant information of the images, it has to eliminate and optimal feature has to be selected to the recognition task. Discrete Region Inferred Differential Evolution architecture is employed to feature selection. Extracted features will be consider as search space, objective function of the DDE generates the optimal features solutions with respect to fitness criteria. Finally recognition task is performed with optimal features using support vector machine.
Flood Reduction Modelling of Mahakam Cascade Lake towards the Mahakam River - East Borneo - Indonesia

Lake is a water source that has decreased its function and has damaged the ecosystem. The Mahakam cascade lake in the East Borneo-Indonesia consists of Jempang Lake, Semayang Lake, and Melintang Lake, which have the sedimentation problem caused by the land-use change. The sedimentation can cause floods in the Mahakam River. However, the Mahakam River that correlates with the Mahakam cascade lake cannot reduce the happened flood. This study intends to optimize flood reduction modeling of Mahakam Cascade Lake towards the Mahakam River in the Muara Kaman outlet. According to the optimization model, this research aims to simulate the flood reduction modeling due to the 3 discharge conditions: Q25, Q50, and Q100. The food reduction modeling uses the Linear Programming Model, and the model is built integrated due to the Cascade Lake. The methodology consists of a linear programming optimization model due to the 3 scenarios (Q25, Q50, and Q100). However, the analysis of the design flood uses the Nakayasu Synthetic Unit Hydrograph in the watershed and the Rational Method for the discharge in the lake. The capacity of Mahakam Cascade Lake due to the bathymetry data and AWLR is as follow: 1) Jempang Lake: 519,958,550.36 m3; 2) Melintang Lake: 696,012,192.74 m3; and 3) Semayang Lake: 1,195,593,435.86 m3. The optimization model result of flood reduction in the Muara Kaman is as follow: a) Scenario-1 (Q25): Qmuara Kaman = 32,729.80 m3/s; b) Scenario-2 (Q50): Qmuara kanam = 37,432.36 m3/s; and c) Scenario-3 (Q100): Qmuara kanam = 39,777.80 m3/s.
Environmental Links to Indonesian Languages Learning

The environment plays a very important role in learning Indonesian. Not only roles, the environment also provides many benefits for learning Indonesian. This was evident when the respondents considered the role and benefits of the environment in learning Indonesian to be important. Students who are the main respondents of the questionnaire are very aware that the environment plays an important role in learning Indonesian.
A Review on Text Summarization Techniques

Abstract: In recent years, an enormous amount of text data from diversified sources has been emerged day-by-day. This huge amount of data carries essential information and knowledge that needs to be effectively summarized to be useful.We first introduce some concepts related to extractive text summarization and then provide a systematic analysis of various text summarization techniques. In particular, some challenges in extractive summarization of single as well as multiple documents are introduced. The problems focus on the textual assessment and similarity measurement between the text documents are addressed. The challenges discussed are generic and applicable to every possible scenario in text summarization. Then, existing state-of-the-art of extractive summarization techniques are discussed that focus on the identified challenges. Index Terms: Summarization, Graph based summarization, Meta-heuristic based summarization, Maximal marginal relevance based summarization, Evaluation
Effect of Internet Utilization, Learning Media, and Satisfaction Level on Online Learning Process during the COVID-19 Pandemic (Case Study of Management Students, Universitas Prima Indonesia)

This research aims to find out how effect of internet utilization, learning media, and satisfaction level on online learning process during the COVID-19 pandemic in case study of Management Students, Universitas Prima Indonesia. Researchers use this type of quantitative research. The population in this study were Management Students in semester 2 and 4 in the morning at Universitas Prima Indonesia. Semester 2 there are 7 classes with a total of 232 students, while in semester 4 there are 10 classes with a total of 350 students, so the total population of semesters 2 and 4 is 582 students. The sample used after the calculation using the Slovin formula is 237 samples from 582 populations. Multiple linear regression test consists of partial test (t), simultaneous test (F), and coefficient of determination test (R2). The results of partial test (t) show that internet utilization has significant effect on online learning process during the COVID-19 pandemic in case study of Management Students, Universitas Prima Indonesia. Learning media has significant effect on online learning process during the COVID-19 pandemic in case study of Management Students, Universitas Prima Indonesia. Satisfaction level has significant effect on online learning process during the COVID-19 pandemic in case study of Management Students, Universitas Prima Indonesia. The results of simultaneous test (F) show that internet utilization, learning media, and satisfaction level have significant effect on online learning process during the COVID-19 pandemic in case study of Management Students, Universitas Prima Indonesia. The results of the coefficient of determination test (R2) show coefficient value is 0.205. This value means that internet utilization, learning media, and satisfaction level effect on online learning process during the COVID-19 pandemic in case study of Management Students, Universitas Prima Indonesia by 20.5%. While 79.5% is influence by variables outside this study. Keywords: Internet Utilization, Learning Media, Satisfaction Level, Online Learning Process During COVID-19 pandemic.
Analysis of Character-related Research Trends according to School Level

The purpose of this study was to compare and analyze whether there were differences in character-related research trends according to school level in order to find out the current status of character-related research, provide basic data for follow-up research, and to point out the direction of character-related research in the future. To this end, 1,057 papers on character published in Korea from 1995 to 2020 were used for analysis. The collected data was analyzed through descriptive statistics and using an &lt;i&gt;x&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt;-test. The major findings of this study were as follows. First, most studies were conducted at all school levels from 2016 to 2019, followed by kindergarten and university (graduate school) from 2014 to 2015, and elementary and secondary schools from 1995 to 2009. Second, as for the research topic, many studies were conducted in the area of character education effect analysis and character education programs in kindergarten, while in elementary, secondary, and university (graduate school), character education effect analysis and theoretical basic research were conducted. Third, regarding the educational method (whether or not class time is used), studies using class time were high in kindergarten and university (graduate school), whereas there was no significant difference between the two in elementary and secondary schools. The significance of this study is as follows. First, this study is the first study to compare and analyze character-related research trends according to school level. Second, significant differences were found in thesis types, research years, number of researchers, research topics, educational methods, and research methods by school level. Third, this study can be used as the basis for future quantitative meta-analyses or qualitative meta-analysis studies. Finally this study is significant in that it found that character-related studies revealed that curriculum changes and educational policies are influental.
Challenges for Teaching Online in Higher Education

The aim of this paper is to assess the adoption rate of online classes and to highlight the required changes of existing resources of higher education adopted by Akaki Tsereteli State University (ATSU) in Kutaisi, Georgia amid the COVID-19 pandemic. The conducted research manifests the insights and perceptions of teachers and students on online modes of teaching and learning. The paper explores and examines the challenges and drawbacks of online courses at the university based on the analysis of the questionnaire handed to students and it also discusses the needs to completely implement digital learning/teaching process with its new sources and assessment strategies, thus indicating the way forward in the years to come.
Research on the Mechanism of Blockchain Technology Investment's Impact on Audit Fees

This paper selects the financial data of China's A-share listed companies from 2016 to 2020, and analyzes the impact of blockchain technology investment on company audit expenses. The results show that there is a significant positive correlation between the blockchain technology investment and the company's audit expenses, that is, the more the company invests in blockchain technology, the higher the audit expenses will be. This is because the application of blockchain technology in listed companies will make auditors face higher risk of significant misstatement and audit risks, and then increase the related audit procedures, thus increasing the audit expenses. Conclusion The above results are still valid after robustness test and endogenous treatment. In this paper, the research on blockchain technology investment from the perspective of audit fees will help the theoretical circle to fully understand the potential effects of blockchain technology investment on social and economic development.
Reachability Constrained Reinforcement Learning

Constrained reinforcement learning (CRL) has gained significant interest recently, since safety constraints satisfaction is critical for real-world problems. However, existing CRL methods constraining discounted cumulative costs generally lack rigorous definition and guarantee of safety. In contrast, in the safe control research, safety is defined as persistently satisfying certain state constraints. Such persistent safety is possible only on a subset of the state space, called feasible set, where an optimal largest feasible set exists for a given environment. Recent studies incorporate feasible sets into CRL with energy-based methods such as control barrier function (CBF), safety index (SI), and leverage prior conservative estimations of feasible sets, which harms the performance of the learned policy. To deal with this problem, this paper proposes the reachability CRL (RCRL) method by using reachability analysis to establish the novel self-consistency condition and characterize the feasible sets. The feasible sets are represented by the safety value function, which is used as the constraint in CRL. We use the multi-time scale stochastic approximation theory to prove that the proposed algorithm converges to a local optimum, where the largest feasible set can be guaranteed. Empirical results on different benchmarks validate the learned feasible set, the policy performance, and constraint satisfaction of RCRL, compared to CRL and safe control baselines.
DESIGN AND DEVELOPMENT OF ANTI-LOCK BRAKING SYSTEM FOR ELECTRIC VEHICLE

Abstract—Recently, privacy-preserving association rules mining algorithms have been proposed to support data privacy. However, the algorithms have an additional overhead to insert fake items (or fake transactions) and cannot hide data frequency. In this paper, we propose a privacy-preserving association rule mining algorithm for encrypted data in cloud computing. For association rule mining, we utilize Apriori algorithm by using the Elgamal cryptosystem, without additional fake transactions. Thus the proposed algorithm can guarantee both data privacy and query privacy, while concealing data frequency. We show that the proposed algorithm achieves about 3-5 times better performance than the existing algorithm, in terms of association rule mining time. Keywords- association rule mining; Apriori algorithm; encrypted data; cloud computing; Elgamal cryptosystem;
Application Research in Computer Vision Signature Encryption System of Enterprise Contract Economic Management

This paper mainly proposes a nonrepudiation digital signature authentication scheme based on an enterprise contract computer vision system. Based on the RSA algorithm and MD5 message-digest algorithm, a digital signature scheme of enterprise economic contract based on IC card is proposed. The method realizes digital signature and ensures the confidentiality of the transmitted data. Finally, this paper proposes a concrete digital signature experiment system implemented in Java. The results of this study show that the computer vision signature encryption system helps to improve the reliability of the system.
Multilingual text classification using deep learning

Every living organism shares a common property to interact whether it is other animal or human being. To interact everyone use some kind of language. It might be a direct language like English, Marathi, Hindi or it can be signed language which includes some symbols or signs or gestures. Moral of the discussion is that for any type of communication the most important channel is language and for interchanging the information the most important thing recognition and understands of the language. Today with the help of technology human have made the non-living things like machines able to interact and speak. Mostly, the languages which are universally acceptable like English can be considered for normal mode of recognition by the machine which we can call it as Monolingual understanding or recognition but when we consider the diversity of languages that is used in entire world, we can imagine the complexity of the implementation. The main concern of proposed title is to focus on exploration of multilingual classification for regional languages like Marathi, Hindi; English to a better extend by using one of the most powerful ways of deep learning.
Retrodictive Quantum Computing

Abstract Quantum evolution is time-reversible and yet little advantage is gained from this in the circuit model of quantum computing. Indeed, most quantum algorithms expressed in the circuit model compute strictly from the present to the future, preparing initial states and proceeding forward with unitary transformations and measurements. We may call this predictive computation. In contrast, retrodictive quantum theory, retrocausality, and the time-symmetry of physical laws all suggest that quantum computation embodies richer --untapped-- modes of computation, which could exploit knowledge about the future for a computational advantage. We demonstrate that by using symbolic partial evaluation, retrodictive reasoning can indeed be used as a computational resource that exhibits richer modes of computation at the boundary of the classical/quantum divide. Specifically, instead of fully specifying the initial conditions of a quantum circuit and computing forward, it is possible to compute, classically, in both the forward and backward directions starting from partially-specified initial and final conditions. Furthermore, this mixed mode of computation (i) can solve problems with fewer resources than the conventional forward mode of execution, sometimes even purely classically (de-quantization), (ii) can be expressed in a symbolic representation that immediately exposes global relational properties of the wavefunction that are needed for quantum algorithms and (iii) reveals that the entanglement patterns inherent in genuine quantum algorithms with no known classical counterparts are artifacts of the chosen symbolic representation.