Reviewerly/exHarmony huggingface dataset:
Measuring the distortion of speech by a facemask

Most prior research focuses on the reduced amplitude of speech caused by facemasks. This paper argues that the interaction between the acoustic properties of a facemask and the acoustic properties of the vocal tract contributes to speech distortion by changing the formants of the voice. Speech distortion of a number of masks was tested by measuring the increase in damping of the first formant. Results suggest that masks dampen the first formant and that increasing the distance between the mask wall and mouth can reduce this distortion. These findings contribute to the research studying the impact of masks on speech.
Comparing Clustering Techniques on Brazilian Legal Document Datasets

The Brazilian justice system is one of the largest and most virtualized in the world. However, the country suffers from severe system congestion. Clustering is a machine learning technique that can increase the speed of the system by automating daily tasks in addition to helping to ensure legal certainty. However, choosing the right model for clustering is not a simple task. This work makes an empirical evaluation of six different approaches to the clustering of Brazilian legal documents. K-Means, Mini Batch K-Means and HDBSCAN algorithms were tested in different hyperparameters and together or not with the Kohonen’s Map as a pre-clustering technique. The work also proposes a new NLP-oriented framework for the specific evaluation of textual clusters. Two databases of Brazilian legal documents were used. The results demonstrate that K-means and Mini Batch K-Means are the best choices, and the use of the Kohonen’s map can increase the overall clustering performance.
Some aspects of the children-friendly school with holistic approach

This paper reviews the characteristics of a good school, emphasising the role of human relationships in the learning process and how relationships can be developed.It highlights the importance of taking human needs into account at school and the importance of the teacher's personality in creating a quality classroom atmosphere and education.It concludes with the idea that a good school takes a holistic view of the child's personality and needs, and that teachers can provide for this.
A Comparative Study on the Sentence Expression of Causative in Qingwen Zhiyao Manchu and Chinese Versions (in Chinese)

Manchu causative sentence is formed by the affix “bu” after the verbal root. The causee has objective case mark “be” or dative case mark “de”, and constitutes causative sentence formed as “S+N+be/de+V(-bu-)”. This research discusses the expression of the affix "bu" in the translation of Manchu into Chinese in QingWenZhiYao Manchu and Chinese versions. It is found that in Manchu causative sentence, the absence of causee, marked or not, and animacy hierarchy directly lead to three strategies in Chinese translation: explicit causation, implicit causation and non-causation. The transitivity of verbs affects the choice of causation or permission in Chinese translation. This shows the affix “bu” is a prominent feature in Manchu causative sentence. The early Chinese version was greatly influenced by Manchu. The rewriting of Beijing Mandarin followed the basic characteristics of the causative sentence pattern and was more inclined to the oral expression of northern Chinese in the late Qing Dynasty.
IMAGE CAPTION USING CNN IN COMPUTER VISION

It is profoundly alluring yet testing to create picture captions that can portray novel articles which are inconspicuous.In this test, no extra picture caption preparing information other than Subsequently, customary Vision-Language Pre-preparing (VLP) strategies can't be applied.picture caption preparing information in VLP, VIVO [ref 1] can use huge measures of matched picture label information to become familiar with a visual jargon pre-prepared model for picture captioning.The outcomes show that our model cannot just create familiar picture captions that depict novel articles, yet in addition huge scope pre-preparing techniques for learning cross-modular portrayals on picture text sets are getting famous for vision-language also, text highlights as contribution to the model to be pre-prepared and utilize self-thoughtfulness regarding learn picture text semantic arrangements in the wild in this paper.
The Active Sensing Testbed

The Active Sensing Testbed (AST) is a novel framework for research in machine perception and world-view rea-soning. The AST supports exploratory development of perception systems that can build internal models of the world by combining multi-view and multi-modal analyt-ics, utilize these models to form hypotheses about a sce-ne, and potentially take action to fill in gaps in knowledge or make predictions about future world states. As a modular software framework, the AST is in-tended to lower the barrier to entry for researchers and developers in applying state-of-the-art computer vision techniques to real-world problems.
Penerapan Metode Pembelajaran Survey, Question, Read, Recite, Review (Sq3r) untuk Meningkatkan Keterampilan Membaca Pemahaman

The purpose of this research are: to describe the results of the application of the Survey, Question, Read, Recite, Review (SQ3R) method which can improve reading comprehension skills in third grade students of SD Negeri 1 Cangkreplor for the 2020/2021 school year. This type of research is classroom action research (CAR) which is carried out in two cycles. Each cycle consists of four stages, namely planning, implementing actions, observing, and reflecting. The subjects of this study were the third grade students of SD Negeri 1 Cangkreplor, totaling 28 students. Data collection techniques using test, interview, observation and documentation techniques. Inter-cycle reading comprehension skills increased from the initial condition (pre-cycle) which was 35.7% to 53.6% in the first cycle and then to 89.3% in the second cycle.The conclusion of this study is that the application of the SQ3R learning method can increase the value of reading comprehension skills in third grade students of SD Negeri 1 Cangkreplor Purworejo 2020/2021.
PERMODELAN INVERSI PEREDAM MAGNET-REOLOGI BERBASIS JARINGAN SARAF TIRUAN UNTUK SISTEM KENDALI

The application of artificial neural network (ANN) models in magnet-rheological damper modeling is of great interest in recently challenges. Therefore, this study aims to propose a solution to overcome this problem by conducting inverse modeling using an artificial neural network. This inverse model is applied to a meandering magnet-rheological valve damper to predict the current to produce the appropriate damping force. The simulation scheme is selected with current as output and damping force, velocity, and displacement as input. The best model is formulated by varying the architecture of the artificial neural network. The best artificial neural network architecture is obtained after doing these variations. The data is divided into 80% training data, 10% validation data, and 10% test data. The activation function used is a logsig function using three hidden layers with the number of neurons in each layer [30-20-30]. The algorithm used in the chosen architecture is Levenberg-Marquardt. The regression value of 0.991 and the MSE value of 0.001 were obtained from the modeling results. The required damping force is ensured that it can be predicted well using the selected artificial neural network. The test proves that the results of the regression constant are 0.999 and the MSE value is 0.0005 when the current output value is inverted to the damper artificial neural network.
Approaches of Steganography &amp; its Applications

Steganography is a science of hiding the presence of data so that it remains safe from intruders. In modern communication scenarios, the use of steganography is very valuable. It can protect the insecurity of wireless communication channels and having enough capability to surprise intruders. In this paper, a brief introduction of steganography along with its association to cryptography is discussed and we believe that it will be very helpful in the development of security protocols for various applications.
Blockchain in Data Science with Cryptography

Today, the wide use of the internet has made a huge quantity of data that needs high security to prevent its misuse. The data is collected at a large scale which is collectively termed Big Data. It is used for various administrative and business analytical purposes. Data science helps to accurately analyze and improve the weak areas. However, the problems of network security and data privacy threat have been a major hindrance in this path. The technique of Blockchain secures the data with the help of cryptography and makes it difficult for the attacker to break the security. Here in this paper, we will have a close look over the binding force of the trinity of data science, blockchain, and cryptography.
Design Of Transaction Information System And Data Storage At Ahza Abadi Pharmacy In Makassar

Ahza Abadi Pharmacy Makassar is one of the businesses in the field of drug sales. In some data processing processes, there are problems due to manual recording of data into an archive book so that unwanted things often happen, such as what happened in the record book or damage to the book, while selling and buying transactions carried out without evidence. transactions thatoften occur between employees and buyers. This study aims to create an information system design to overcome problems in conducting transactions and storing data so that employees can easily input data and print receipts for buyers as proof of transactions. This research uses the prototype method in designing information systems that focus on the presentation of input and output in the form of use case diagrams and activity diagrams. The results of this study are the design of a transaction information system and data storage into a transaction information system and data storage
Utilization of Info BMKG Application as a Medium for Disaster Risk Communication in Jakarta, Indonesia

The presence of Info BMKG (National Agency for Meteorology and Climatology) Application is intended to be accessible by the public.This study aims to investigate whether Info BMKG Application can act as a medium for disaster risk communication and to identify its utilization for disaster risk communication.This study advanced mixed methods with the sequential explanatory design and have involved more than 100 respondents for quantitative and qualitative data analysis.The data were first analysed quantitatively using descriptive statistics and were filtered and selected to be investigated qualitatively at the second stage in order to obtain further deepened results.The result of study showed that Info BMKG Application that contains risk information can trigger cognitive, affective, and behavioural changes; which is in line with the aim of successful risk communication; especially in the context of dealing with climate-related disasters risk information and disaster risk reduction.
Model design to develop online web based questionnaire

This research aims to create a web-based application for sharing questionnaires. The developed features are creating questionnaires, sharing questionnaire in the dashboard, filter the questionnaire as the requested criterias, exchange the rewarded coins for gifts, export questionnaire data to a document, set a limit for the questionnaire for each device. The development will be using data collecting using questionnaire and literature study. Then, software development life cycle (SDLC) waterfall research methodology will be used for the website system development. Result of this research will be a website application that will be used for questionnaire maker so that they can reach the respondent count target, have a suitable respondent (minimize respondent who does not meet the criteria), and also can collect more validated data.
A Few-Shot Inductive Link Prediction Model in Knowledge Graphs

Link prediction aims to predict the missing facts in knowledge graphs. Most previous work focuses on the transductive link prediction, which cannot predict unknown entities. However, knowledge graphs are evolving in practical scenarios and new entities are constantly added. A graph neural network based on subgraph structure can effectively make predictions on a knowledge graph composed of unknown entities. Based on this method, we propose a new inductive link prediction model MILP, which uses meta-learning to predict unseen entities on few-shot data. Specifically, MILP divides the training data into four tasks according to the relation types and constructs a subgraph structure of each triplet, and then trains each task sequentially through the meta-learning framework which uses graph neural network to score the triplets. Experiments are carried out on the benchmark inductive link prediction datasets, and the results show that in most cases the proposed model achieves better results than the baseline models, proving the effectiveness of MILP.
An approach to improve argumentation-based epistemic planning with contextual preferences

Current approaches to argumentation-based planning represent an interesting proposal where defeasible argumentation is used as a practical mechanism suitable for reasoning with potentially contradictory information in dynamic environments. In many real-world planning scenarios, the development of formalisms allowing explicit preference specification over pieces of knowledge turns out to be an essential task—however, despite its importance, existing planning systems are not provided with the possibility of dynamically changing these preferences when a plan is being constructed. This paper presents an argumentation-based approach to deal with the handling of preferences when a plan is formulated; in particular, we propose using conditional expressions to select and change priorities regarding information upon which plans are constructed. Our aim is not to improve the efficiency of current planning systems, but to enhance the resulting plan itself by introducing an approach capable of representing and handling multiple preferences over defeasible knowledge. This approach will contribute to the strengthening of existing argumentation-based epistemic planning systems, providing a useful tool that the user could exploit. Finally, we also present a running-time analysis and several complexity results associated with our approach.
Estimation of Direct Solar Radiation on High Mountain Region, Jomson, Nepal

The main aim of the study is to estimate direct solar radiation over high mountain region of Jomsom (Nepal) (28.47 °N, 83.83 °E, 2,700 m above sea level) for a period of year 2012. Aerosol optical depth (AOD) and total ozone column data are derived from NASA website. Daily atmospheric transmittance due to different parameters for direct solar radiation is calculated. The effect of different parameters on the direct solar radiation was analyzed. The maximum and minimum monthly average of direct solar radiation values were found 1208 ± 22 W/m2 in January and 1021 ± 46 W/m2 in June respectively. Annual average of direct solar radiation is 1106 ± 70 W/m2. Result of this research work is beneficial for the further identification, impact and analysis of direct solar radiation at different places, agriculture, energy harvesting.
Research on Countermeasures of Improving Postgraduate Training Quality in Post-Epidemic Period in China

Postgraduate education in China is at an essential stage of transformation from a big country to a powerful nation. Improving the quality of training is an inevitable choice to serve the strategic adjustment of the country, to cope with the changes of international competition and the law of things’ development. The epidemic’s impact has caused a more complicated external environment, which has a long-term effect on graduate education, which means that the improvement of graduate training quality in the post-epidemic period will have more practical significance. In the post-epidemic period, the “new normal” of postgraduate training will accelerate reconstruction. However, at present, problems such as insufficient international influence, involution, structural imbalance, and imperfect training mechanism of postgraduate education in China may restrict the improvement of training quality in the post-epidemic period. This paper suggests that the country, schools, graduate students, and teachers should take multiple measures to improve the quality of postgraduate training and help China’s high-quality development and reshape the international pattern.
Identification of POS Tags for the Khasi Language based on Brill’s Transformation Rule-Based Tagger

Khasi is a Mon-Khmer language that belongs to the Austro-Asiatic language family. Khasi language is spoken by the indigenous people of the state Meghalaya in the North-Eastern part of India. The main purposeof this paper is to develop Part-of-Speech (PoS) tagger for the Khasi language using a Rule-based approach. To work on POS tagging, one needs a grammatically tagged corpus. However, the Khasi language does not have a standard corpus for PoS tagging. Therefore, another aim or purpose of this paper is to develop a Khasi lexicon or POS corpus and using the Rule-Based Brill’s Transformation to automatically tag the given Khasi text. While anticipating the challenges in building such acorpus, this paper has brought out an analysis based on the Khasi corpus of around 1,03,998 words in its initial phase. We also show in this paper how the Khasi corpusis created. By using Brill’s Transformation rule-based learning on the created corpus in this preliminary study, accuracies of 97.73% and 95.52% were obtained on validating data and testing data respectively. This workis the first attempt to investigate POS tagging using the rule-based model with the designed Khasi POS corpus.
A Mamdani Type-Fuzzy Inference - Alignment Matrix Method Aimed to Evaluate Competencies Acquired by Students Enrolling at the Mexican Higher Middle Education System I: Formulation and Explanation Based on Simulation, and A Real but Incomplete Data Set

The last reforms at the Mexican educational system attempt to modify graduates' traditional profiles to enable them to investigate, develop and propose solutions to various problems, think more assertively, form opinions, interact with multidisciplinary groups of people, and ultimately assume a proactive role in the community. The implementation of curricula promoting the development of competencies becomes essential in achieving envisioned goals. The alignment of competencies to study plans and the evaluation of the development of related skills becomes critical at the scheme's implementation. Currently, relating duties mainly depends on the teacher's will, but the lack of a systematic protocol to achieve involved endeavors promotes designs based on subjectivity. On top of this, concurring student's performance grading scheme relies on a thorough alphabetic character rating approach, thereby masking objective scoring. Assessment at the Mexican educational system realm conceives upon criteria designed abroad. Thereby linking particularities are left behind at performing evaluation tasks. This contribution proposes a method based on a fuzzy inference approach that aims to provide a formal structure that allows teachers to achieve the alignment of competencies and evaluate their development by students relying on a quantitative paradigm. We offer a comprehensive display of the formalities of the proposed fuzzy method. Explanation of its functionality relies on both simulated and real data. The aim here is on addressing the student-teacher aspect of alignment and evaluation procedures. Extension to other precincts within the whole Mexican educational system also contemplates and intends to appear in further contributions.
A New Bayesian Structural Equation Modeling Approach with Priors on the Covariance Matrix Parameter

Bayesian inference for structural equation models (SEMs) is increasingly popular in social and psychological sciences owing to its flexibility to adapt to more complex models and the ability to include prior information if available. However, there are two major hurdles in using the traditional Bayesian SEM in practice: (1) the information nested in the prior distributions is hard to control, and (2) the MCMC iterative procedures naturally lead to Markov chains with serial dependence and the diagnostics of their convergence are often difficult. In this study, we present an alternative procedure for Bayesian SEM aiming to address the two challenges. In the new Bayesian SEM procedure, we specify a prior distribution on the population covariance matrix parameter $\mathbf{\Sigma}$ and obtain its posterior distribution $p(\mathbf{\Sigma}|\text{data})$. We then construct a posterior distribution of model parameters $\boldsymbol{\theta}$ in the hypothetical SEM model by transforming the posterior distribution of $\mathbf{\Sigma}$ to a distribution of model parameter $\boldsymbol{\theta}$. The new procedure eases the practice of Bayesian SEM significantly and has a better control over the information nested in the prior distribution. We evaluated its performance through a simulation study and demonstrate its application through an empirical example.
Construction and Application of Curriculum System of Design Major Integrating Environmental Protection and Big Data

Design subject curriculum system is a major subject in the field of design education. The gap between ideal and reality makes the design of the curriculum system of design discipline a serious and urgent problem. Facing the “integration of industrialization and industrialization,” we can explore the professional curriculum system of environmental design and construction. And the method of constructing the corresponding system is initially proposed. The fuzzy comprehensive evaluation method is used to evaluate and analyze the comprehensive effect of the model. According to the suggestions of experts and teachers, the designed indicators include 4 first-level indicators and 16 corresponding second-level indicators. The primary indicators include classroom response, teacher satisfaction, teaching effectiveness, and teaching environment. According to the fuzzy comprehensive evaluation steps and corresponding calculation methods, the final evaluation results are obtained.
Personality of College Students related with Religious Values

Abstract: Education plays a vital role in the programme of nation building. Education also emancipates the human beings and leads to liberation from ignorance. It is also said that in the twenty first century-a nation’s ability to convent knowledge into wealth and Religious good through the process of innovation is going to determine its future, according twenty first century is also termed as century of knowledge. Education is a principal instrument in awakening the child to cultural values in preparing him/her for later professional life and adjustment in their Religious life. Education is a goal oriented and continuous process that develop the adjustment ability in the child. India is a power house of software and human resources however the availability of electronics in country has not been up to the requirement for the service to its citizens. In the college students situation regular students are more successful than private students on the factors of Religious values. Boys are showing the high tendency performance than girls. Rural boys and girls students reveal low tendency than urban boys and girls. Effect of personality traits on environment (i.e. rural and urban) and sex (I,e boys &amp; girls) are not equal on factors of Religious values.