Reviewerly/exHarmony huggingface dataset:
Info_PCA: A Hybrid Technique to Improve Accuracy by Dimensionality Reduction

Principal Component Analysis and Shannon Entropy are some of the most widely used methods for feature extraction and selection. PCA reduces the data to a new subspace with low dimensions by calculating the eigenvectors from eigenvalues out of a covariance matrix and thereby reduces the features to a smaller number capturing the significant information. Shannon entropy is based on probability distribution to calculate the significant information content. Information gain shows the importance of a given attribute in the set of feature vectors. The paper has introduced a hybrid technique Info_PCA which captures the properties of Information gain and PCA that overall reduces the dimensionality and thereby increases the accuracy of the machine learning technique. It also demonstrates the individual implementation of Information gain for feature selection and PCA for dimensionality reduction on two different datasets collected from the UCI machine learning repository. One of the major aims is to determine the important attributes in a given set of training feature vectors to differentiate the classes. The paper has shown a comparative analysis on the classification accuracy obtained by the application of Information Gain, PCA and Info_PCA applied individually on the two different datasets for feature extraction followed by ANN classifier where the results of hybrid technique Info_PCA achieves maximum accuracy and minimum loss in comparison to other feature extraction techniques.
Adaptive Mixed Component LDA for Low Resource Topic Modeling

Probabilistic topic models in low data resource scenarios are faced with less reliable estimates due to sparsity of discrete word cooccurrence counts, and do not have the luxury of retraining word or topic embeddings using neural methods.In this challenging resource constrained setting, we introduce an automatic trade-off between the discrete and continuous representations via an adaptive mixture coefficient, which places greater weight on the discrete representation when the corpus statistics are more reliable.The adaptive mixture coefficient takes into account global corpus statistics, and the uncertainty in each topic's continuous distribution.Our approach outperforms the fully discrete, fully continuous, and static mixture model on topic coherence in low resource monolingual and multilingual settings.
BLOCKCHAIN FOR INDIAN AGRICULTURE: A REVOLUTION

The most challenging problem before the world is providing enough food for the gigantic leap in population. There are numerous reasons for the shortage of food and technological innovations in agriculture are required to overcome the shortages in food supply. Sustainable Development goals (SDGs) provides the futuristic vision and ICT along with other latest technologies will help achieve these development goals at a brisk speed. Recent technological developments as use of mobile-broadband access devices, Internet of Things (IoT), Specialized Robots, Drones, big data analytics and Artificial Intelligence has given farmers tools and technologies to scale agricultural production and marketing of their agricultural products.&#x0D; In this paper, we will discuss how Smart Agriculture is changing the face of agriculture in Budaun, a small city in Uttar Pradesh. Smart agriculture coupled with block chain technology is being used to achieve sustainability in agriculture growth. The production/yield has risen by over 20% and the profits have increased by over 30% with the new technology.
Analisa Proyek Pengembangan Sistem Informasi Perpustakaan Umum Menggunakan Unified Modeling Language

The library is an important facility as a source of information, especially in the world of education to support learning activities for students and knowledge seekers to add insight and knowledge. To facilitate and accelerate library services, a Library Information System is needed in order to increase productivity, effectiveness and efficiency in the library. For the development stage of the library information system using the Unified Modeling Language (UML) as a tool for modeling and documenting the Library Information System. With the Public Library Information System Development Project Analysis Using the Unified Modeling Language, it is hoped that it can improve service, productivity, effectiveness and efficiency in libraries to increase reading interest for students and facilitate and speed up the transaction process of borrowing and returning books to the library.
A Preliminary Study on Cultivating Practical Talents in College Computer Teaching

Because the market economy is constantly developing, the market demand for talents is becoming more and more, computer talents are one of the most needed talents in the information age, but because there are still many loopholes in the training of computer professionals in colleges and universities, the effect of talent training is not very ideal.In order to provide more computer professionals with applied talents, colleges and universities must reform the mode of computer education and teaching, and change the direction of training computer professionals to improve the effectiveness of computer education and teaching.
Do we read what we hear? Modeling orthographic influences on spoken word recognition

Theories and models of spoken word recognition aim to explain the process of accessing lexical knowledge given an acoustic realization of a word form.There is consensus that phonological and semantic information is crucial for this process.However, there is accumulating evidence that orthographic information could also have an impact on auditory word recognition.This paper presents two models of spoken word recognition that instantiate different hypotheses regarding the influence of orthography on this process.We show that these models reproduce human-like behavior in different ways and provide testable hypotheses for future research on the source of orthographic effects in spoken word recognition.
The bodily challenges of augmented vision applied to firefighting activity

While there is an ever-increasing number of Augmented Reality (AR) technologies that are starting to be used in different fields of activity, few studies have explored their impact on the dimensions perceived by users during their activities. Taking a research project that aims to develop a thermal-imaging AR device for firefighters, we studied the perceptual dimensions at work in an AR-mediated activity. Using an original methodology that combines the anthropotechnological approach with embodied cognition, we studied the role of thermal imaging as it is used today in firefighting interventions and the sensory dynamics involved, before presenting the results of realistic scenarios performed with a prototypical device. These simulations allowed us to observe new forms of behaviour with the device in environments close to reality and to develop hypotheses on the transformation of perceptual dynamics and more broadly of the engagement of bodies in action, generated by augmented vision.
Self-Assessment on Information Literacy Competency of Students in Indonesia-Papua New Guinea Border Area During The COVID-19 Epidemic

COVID-19 requires students to be able to study independently, supported by information literacy skills.The purpose of this study is to conduct a self-assessment on the information literacy competency of students that they apply in learning activities during the COVID-19 outbreak in terms of gender and ethnicity.Respondents conduct a selfassessment of their information literacy competency.The total number of respondents are 200 from four tertiary institutions in the Indonesian-Papua New Guinea border area.In general, students have a moderate level of information literacy competence.Based on the findings of this study, females of non-Papuan ethnicity had the best level of information literacy among the other categories of respondents.The results suggest the following action that requires particular policies that are expected to improve this ability.The blended learning model is assumed to be most suitable for students in Papua who have limited infrastructure for learning activities during the COVID-19 epidemic.
Features of professional well-being of representatives of different professional groups

The article is devoted to a review of the results of the study of the features of professional well-being among representatives of various professions.The following main indicators of the study were used: indicators of professional well-being, subjective economic well-being, occupational psychological well-being, professional demand for personality, professional motivation, work engagement, life satisfaction, subjective social well-being, meaningfulness of life, psychological capital, job satisfaction, psychological climate.The study involved 403 representatives of various professional groups: economists, engineers, police inspectors, cook-confectioners, managers, unskilled manual workers, medical representatives, salesmen, police investigators.The hierarchy of professional groups by mean indicators of professional well-being was revealed.The strength of the relationship between the general indicators of the study and professional well-being in each professional group is determined.Possible reasons for differences between groups for each indicator were explained.The predictors of professional well-being for different professional groups were identified.The results of the study confirmed that the structure of predictors of professional well-being can differ significantly for representatives of different professional groups.The differences between the groups are related to the hierarchy of predictors of professional well-being within a single semantic field.In addition, it was found that the scales of general indicators can contribute to the differences between professional groups, which requires additional study of the features of professional well-being, at the level of the items behind each general indicator.KeywOrdS: predictors of professional well-being, work engagement, professional motivation, job satisfaction, meaningfulness of life. AnotacijaStraipsnyje apžvelgiami skirtingų profesijų atstovų profesinės gerovės tyrimo rezultatai.
CAPACITY OF SUNTER C RIVER IN NORTH JAKARTA

Sunter C river is located on Yos Sudarso street at coordinates 6°8'32,63" South Latitude, 106°53'25,78" East Longitude and downstream Sunter C river is located on Sunter Barat river street coordinates 6°8'24,78" South Latitude, 106°51'24.68" East Longitude. In area around the Sunter C river, there are still frequent floods every time the rainy season arrives because of the narrowing of canal section in upstream area of Sunter C river and Sunter C river water can’t flow gravitationally to Sentiong river because the base elevation of Sentiong river is higher than Sunter C river. From the above conditions, it’s necessary to analyze the problem of flooding in Sunter C river area to find out whether Sunter C river can still accommodate water discharge based on rainfall in the last 10 years and does the Sunter C river need normalization. Based on the results of manual calculations and HEC-RAS application, the Sunter C river can’t accommodate water discharge based on rainfall for the last 10 years of 15.88 m3/s. At point 0 - point 3 it is necessary to normalize by widening the cross-section from 3.6 m to 8 m and at point 4 from 4.8 m to 8 m.
AN IMPROVED PATTERN BASED LDA TOPIC MODELING FOR BUSINESS INTELLIGENCE

Topic models give a helpful strategy to dimensionality decrease and exploratory data analysis in huge text corpora. Most ways to deal with topic model learning have been founded on a greatest likelihood objective. Proficient algorithms exist that endeavor to inexact this target, yet they have no provable certifications. As of late, algorithms have been presented that give provable limits, however these algorithms are not down to earth since they are wasteful and not hearty to infringement of model presumptions. In this work, we propose to consolidate the statistical topic modeling with pattern mining strategies to produce pattern-based topic models to upgrade the semantic portrayals of the conventional word based topic models. Using the proposed pattern-based topic model, clients' inclinations can be modeled with different topics and every one of which is addressed with semantically rich patterns. A tale information filtering model is proposed here. In information filtering model client information needs are made in terms of different topics where every topic is addressed by patterns. The calculation produces results similar to the best executions while running significant degrees quicker.
Disease Identification System using Image Analysis

Artificial Intelligence (AI) and Sensor Technologies making a point-of-care delivery possible which was considered impossible. The human body shows early indicators of disease manifestation before actual clinical symptoms appear. These indicators can be picked up by analyzing the optical face image, which can be used for rapid and cost-effective screening of life-threatening health conditions. This article focuses on how health status can be tracked using optical image analytics. Early identification of disease plays a vital role in therapeutics of a patient. In accordance with review of secondary data available in literature, this article proposed a model to rapidly screen the health conditions at point-of-care. The patterns in the optical image have the potential to act as digital disease markers.
Matrix Law of Current

In this study, the current is defined over matrix. The proposed matrix law of current corresponds with the existing Ohm’s law of current. Thus, the new law of current comprises with the characteristics of matrix. The matrix representation of current provides the compact law for both the types of current, i.e. Alternative Current (AC) and Direct Current (DC). The element of matrix represents the position of electron. Thus, the corresponding application of both the type of currents lies with the properties of matrix. An efficient supply of current is the key advantage of the proposed theory of current. This is achieved by rank of the matrix. The binary representation of the current sets to computational operation. The security is another advantage of this theory. The security of the proposed law of current interacts with the problem of simultaneous system of algebraic equations (linear and non-linear both). Without Ohm’s law, current is defined in this study. The probabilistic study of voltage is used to present the current. The functional representation of current is defined for studying the current over the computation domain. This research work presents the study on the invisibility of current under the context to visible correspondence for establishing the discrete characteristic of electromagnetic waves with respect to the time. The current is defined by the function of discrete and continuous probability.
Perancangan Sistem Telemetri Deteksi Bencana Banjir Berbasis Web Server Dan Sms Gateway

AbstractIndonesia is one of the areas prone to disasters, especially floods. The impact of flooding can be reduced if the community is better prepared to face the coming flood. Therefore we need an early flood detection tool that can give a signal to the community through early warning so that the community can be more alert in facing flood disastersThe results of this design make two systems, the main control system and the receiving system. The main control system consists of an ultrasonic sensor, SIM800L module and NodeMCU Wi-Fi module. The receiving system consists of a SIM800L module and a siren. The results showed that the ultrasonic sensor used has a good level of accuracy with an error value &lt;1%. The results of SMS testing have a delay until the SMS to the recipient is around 5-10 seconds. The test results also show that 4G network technology has 100% delivery accuracy and 3-4 seconds delivery delay per data. The final result shows thatthe system is able to work as desired and is able to be well connected to the web server.Keyword:Flood Disasters, SIM800L, Ultrasonic sensor, Web Servers, SMS
Discussion on the Methods of Improving Computer Teaching

Want to improve the students' computer learning efficiency, first of all is the key to stimulate students interest in computer learning, let the students enthusiasm for learning computer, so that they can give full play to the ability of autonomic learning to active learning, if teachers computer classroom teaching as their own centralized, it is difficult to make students produce strong interest in computer, so under the new education idea, the teacher should learn to the initiative back to student, should give priority to in order to guide students to learn, in the process of students' learning support.In order to improve the quality and efficiency of computer teaching, it is also necessary to discuss the methods of computer teaching.Therefore, this paper mainly focuses on the methods that can effectively improve computer teaching.
Analisis dan Perancangan Sistem Informasi Panduan Kesehatan Balita

Immunization, nutritional support for food vitamins and nutritional content from food are important components to support good children's growth and development. However, the number of malnutrition and malnutrition in Indonesia is still high, causing many children under five to experience stunting during the golden age. Through this research, analysis and design of mobile-based information systems that can be accessed anywhere and anytime as needed is carried out. The design of this information system can be used as a guide for young mothers regarding child health information needed, especially during the growth and development period of toddlers by monitoring growth curves and providing health recommendations through the calculation of the Body Mass Index (BMI) in toddlers and can also be used as a reminder and recording of immunization data in children under five.
Analysis of Least Significant Bit Method Using Sequential Encoding-Decoding in Steganography Digital Image

The method of steganography commonly used to hide data or information is Least Significant Bit (LSB) method. One of the relevant research is LSB using sequential Encoding - Decoding by David Pipkorn and Preston Weisbrot. In this research, an analysis of the LSB method using Sequential Encoding - Decoding by doing some testing. The tests are on the aspect of message security using tools StegSpy and enhanced LSB algorithm, testing on image quality by calculating the Peak Signal to Noise Ratio (PSNR) value and see the image histogram, testing on robustness of message by doing some image processing operations on stego image, like cropping, rotating, and etc, and then testing on capacity to check size of cover image and stego image and calculates the maximum size of data that can be hidden. From the testing process, we know that there are deficiencies in the aspects of security, robustness and capacity of a message. And then in this research we try to change the location of messages that are hidden in the image bits, which previous research used the 8th bit of each bytes, changed to the 7th bit. To be able to correct deficiencies in the security aspect. After repairing and testing like before, obtained better results in the security aspect. This can be seen from the image of the enhanced LSB algorithm process, the message is not detected, but unfortunately the image quality is reduced, with the low PSNR value generated.
Domain Expert Platform for Goal-Oriented Dialog Collection

Today, most dialogue systems are fully or partly built using neural network architectures.A crucial prerequisite for the creation of a goaloriented neural network dialogue system is a dataset that represents typical dialogue scenarios and includes various semantic annotations, e.g.intents, slots and dialogue actions, that are necessary for training a particular neural network architecture.In this demonstration paper, we present an easy to use interface and its backend which is oriented to domain experts for the collection of goal-oriented dialogue samples.The platform not only allows to collect or write sample dialogues in a structured way, but also provides a means for simple annotation and interpretation of the dialogues.The platform itself is language-independent; it depends only on the availability of particular language processing components for a specific language.It is currently being used to collect dialogue samples in Latvian (a highly inflected language) which represent typical communication between students and the student service.
Design Color Sorting with Conveyor and Robot Arm Using Lego Mindstorms NXT

Lego Mindstorms education robot is an interactive robot because it can be used to design various kinds of robot applications. This robot can be used to design sorting robots before they are applied to real robots. Many sorting techniques are in the form of colorful objects, but only for one-time sorting. This research will design and implement a color sorting robot with 2 detection stages, namely the conveyor and the robot arm, the initial sorting is carried out by the conveyor for sorting color objects, the next sorting uses the robot arm. to move the selected color object to a place that matches the desired color. The results obtained in sorting color objects using 1 color sensor and Bluetooth for communication between the conveyor and the robot arm via Bluetooth works well where three objects in red, blue and green can be moved according to the desired color object.
Dokdo Education Teaching and Learning Model Development of Korea Geography Textbooks in the 2015 Revised National Curriculum

The reality is that Japan's territorial provocation is getting worse and Korea and Japan have not still found any solutions about the issue. Territorial provocations are also appearing on an educational level. Accordingly, research on the necessity and direction of territorial education has been carried out continuously. Presenting the direction of territorial education based on precedent research on territorial education is as follows. Firstly, territorial education requires harmony among cognitive, affective, and functional areas. Secondly, it is necessary to cultivate the geographical thinking and analytical power not from the emotional aspect of education derived from exclusive nationalism but from the transnational level. Furthermore, we need move toward fostering problem-solving skills for coexistence and prosperity. Finally, it is necessary to develop teaching and learning models for how and what to teach in actual classes. In this study, the content system of Korea geography and three kinds of textbooks in the 2015 Revised National Curriculum are analyzed. According to the results, a teaching and learning model on Dokdo education has been proposed. According to the model, knowledge-centered, value-centered, and function-centered teaching and learning guidelines which can be implemented in actual classes are developed and proposed. When developing these guidelines, they are classified by three factors: knowledge, value, and function. Moreover, these guidelines should not be based on the emotional education from exclusive nationalism. Rather, it focuses on developing geographical analysis capacity and critical thinking skills through objective data and improving decision-making and problem-solving abilities at a transnational level.