Reviewerly/exHarmony huggingface dataset:
Prediction of Spatial Distribution of Organic Carbon in Lower Brahmaputra Active Floodplain Soils of Bangladesh

Soil acts as a large reservoir of Organic Carbon (OC) but the amount varies significantly with space and time. Thus, soil analysis and interpretation of spatial variability of Soil Organic Carbon (SOC) are keys to site-specific management. The study aimed to characterize the spatial variability of SOC in an active floodplain. Soil samples were collected in three major landform categories (natural levee, back slope, marsh land) from the lower Brahmaputra River floodplain and then analyzed for SOC measurement in the laboratory. The measured data were then analyzed for spatial variability interpretation using descriptive statistics and geo-statistical analysis. The study found that the amount of SOC varies with landform variation, soil texture and distance between sample points. The topsoil of marsh land has the highest (1.41%), back slope holds a moderate amount (1.15%) and the natural levee has the lowest (0.75%) amount of SOC. The amount of clay particles at the top layer was found to be positively correlated to the SOC whereas in the same layer of sand and silt showed a negative correlation. The geo-statistical analysis illustrated the nugget effect. Low (&lt;1%) SOC is commonly found in the agricultural soils of Bangladesh which was corroborated in this study; moderate (1.1%) SOC was found in the floodplain. This study aimed to provide an insight into spatial variability to assist in predicting SOC in the active floodplain; consequently, the interpretation of spatial variability analysis can be implemented for site specific management strategies and to calculate carbon stock in floodplain soils.&#x0D; The Dhaka University Journal of Earth and Environmental Sciences, Vol. 8(2), 2019, P 33-40
Trends in COVID-19 Publications: Streamlining Research Using NLP and LDA

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Analisis Fitur dan Convolutional Neural Network pada Pengenalan Aksen Ucapan

Each country has its characteristics and culture, one of these characteristics is the accent of speech. By listening to someone's accent, we can identify the country of origin of the speaker. Research on accent recognition includes Automatic Speech Recognition (ASR) Technology which is currently being developed, an example of ASR technology, namely Virtual Assistant, the development of this research can be more intelligent Virtual Assistant because it can provide an accent from a speaker. In this study, the authors tried to classify accents from various countries (5 classes), namely English, Spanish, Mandarin, French and Arabic. The dataset used in this study consists of English 627 audio, Spanish 220 audio, Mandarin 132 audio, French 80 audio, and Arabic 172 audio, where all sentences are the same sentence in English. In this study, the audio features used are Mel - Frequency Cepstral Coefficients (MFCC), Zero Crossing Rate (ZCR), and Energy (in librosa it is called RMS). Audio feature extraction generates an array of each audio, the result of audio feature extraction will be the Convolutional Neural Network (CNN) Method input for classifying the accent. This research resulted in 51.30% accuracy for the MFCC feature, 48.05% for the ZCR feature, and 51.95% for the Energy feature. The Energy feature gets good accuracy, followed by the MFCC and ZCR features.
Lecturers’ Perspective on Inclusion: Inclusive Education Service for Students with Disabilities in University

The purpose of this study was to analyze how lecturers' perspectives are on the inclusive education model in higher education.This research used a qualitative descriptive method which was conducted on 32 lecturers consisting of four universities in the city of Padang.Each lecturer is asked to fill out an Inclusivity Instrument questionnaire regarding Inclusive Education in Higher Education in Padang City.Based on the results of the study, data shows that inclusive education services in the city of Padang have been implemented properly based on the results of the instruments that have been filled in by lecturers.However, there are several different treatments in the teaching and learning process in the classroom.This difference results in different teaching methods for each lecturer and different absorption of information for these students.
Design of Automatic Feeder for Shrimp Farming Based on Internet of Things Technology

&lt;p class="02abstracttext"&gt;In shrimp farming, feeding is an important activity to achieve good shrimp growth. Manual feeding manually using hand is less effective due to unequal food distribution. Thus, an automatic feeder is required to dispense feed at predetermined time. The advantages of automatic feeder are cost-effective, low labour requirement, and can be applicable for large volumes of feed. Design of automatic feeder machine can influence the capacity and time controlling of the feeder. In this research, the automatic feeder was designed using a controlling time system based on Internet of Things (IoT) technology. During plant trial, The automatic feeding was scheduled at 7 am, 11 am, 4 pm, and 8 pm. This machine could throw shrimp food homogeneously up to 10 m far for 2,500 m&lt;sup&gt;2&lt;/sup&gt; pond area. In shrimp farming, distribution of shrimp food in predetermined time becomes an important rule to achieve good shrimp growth.&lt;/p&gt;
School Principal's Of Educational Resources, Geographic Conditions, Demographic Conditions, Economic Conditions, Population Capaticy on Junior High School Gross Participation Rate

This study attempts to explain (1) the creativity of the principal affects human resources to explore school financial resources, (2) the invention of the principal drives human resources to explore school financial resources, and (3) the strategy of the principal to engage in raising funds with the group. This analysis uses a qualitative descriptive technique. The results showed the principal's creativity affects human resources to explore the school's integrated financial resources in subjects that can inspire students to think creatively, work hard, and enable students to be autonomous in identifying sources of funds to be used in different activities.
INDEXING AND RETRIEVAL SYSTEM FOR SPEECH ANNOTATED DIGITAL IMAGES

The abundant growth in use of digital camera and mobiles for picture has created huge storage requirements. The problem can be solved by constantly transferring it to hard drive of a computer or cloud. But indexing and retrieval system for digital pictures has become a known and vital problem. Most recently, automatic voice recognition technology, speech gloss and retrieval have given an option to retrieve them. Also predictable strategy for existing photograph ordering, recovery methods and repetitive work of manual writing is supplanted. Image annotation to enhance web photo search and image control is most preferred nowadays. In speech annotation and retrieval, a hybrid mechanism is utilized to assimilate picture like styles, syllables, words and characters. In the proposed system, speech annotated technique is used to provide the appropriate image for more number of search results. This technique has two processes to perform: firstly, offlineprocess where words are trained using volume package and these trained words are stored in database, secondly, online process, content based refining is done on color, shape and texture.
FAST-ADAM in Semi-Supervised Generative Adversarial Networks

Unsupervised neural networks have not caught enough attention until Generative Adversarial Network (GAN) was proposed. By using both the generator and discriminator networks, GAN can extract the main characteristic of the original dataset and produce new data with similar latent statistics. However, researchers understand fully that training GAN is not easy because of its unstable condition. The discriminator usually performs too good when helping the generator to learn statistics of the training datasets. Thus, the generated data is not compelling. Various research have focused on how to improve the stability and classification accuracy of GAN. However, few studies delve into how to improve the training efficiency and to save training time. In this paper, we propose a novel optimizer, named FAST-ADAM, which integrates the Lookahead to ADAM optimizer to train the generator of a semi-supervised generative adversarial network (SSGAN). We experiment to assess the feasibility and performance of our optimizer using Canadian Institute For Advanced Research – 10 (CIFAR-10) benchmark dataset. From the experiment results, we show that FAST-ADAM can help the generator to reach convergence faster than the original ADAM while maintaining comparable training accuracy results.
Implementasi Proxy dan Snort Sebagai Gateway Antivirus

Technology and internet networks are two things that are always related, because in today's era the internet has become a much-needed medium for learning, communicating, exchanging data, and even playing. With the activity of using the internet network, a problem will arise, namely network security. Network security is a very important aspect as a defense in a network, to minimize the risk of data theft and unwanted access in an internet network. The purpose of this study is to implement the control and security of internet use in an agency with minimal costs. namely using the Linux operating system Ubuntu Server 18.04, Proxy Server, and Snort. The result of the system that has been created has a function to perform caching so that it can save bandwidth and can function as filtering content to minimize unwanted things on the network. In addition, the system created is very helpful for network admins to monitor the network in real-time, even can also enforce rules to protect the network.
Interoperable Visualization Framework Towards Enhancing Mapping and Integration of Official Statistics

The aim of this research is to introduce a new interoperable visual analytics framework Towards Enhancing Presentation of Official Statistics.This paper aims to investigate how data integration and information visualization could be used to increase readability and interoperability of statistical data.Statistical data has gained many interests from policy makers, city planners, researchers and ordinary citizens as well.from an official statistics' point of view, data integration is of major interest as a means of using available information more efficiently and improving the quality of a statistical agency's products, we implemented and proposed statistical indicators schema and mapping algorithm which is conceptually simple and is based on hamming distance and edit (Levenshtein) distance mapping methods in addition to the ontology.Also we build GUI to import the indicators with data values from different sources.The performance and accuracy of this algorithm was measured by experiment, we started to import the data and indicators from different sources to our target schema which contains the indicators, Units and Subgroups.during the data import using our algorithm, the exact matched indicators, units and subgroups will be mapped automatically to the indicators, units, and subgroups in the schema, in case that we import not exact matched indicator, units or subgroups the algorithm will calculate the edit distance (minimum operations needed) for mapping the imported indicator with the nearest indicator in the schema, the same thing will happen for units or subgroups, the results showed that the accuracy of the algorithm increased by adding ontology, ontology matching is a solution to the semantic heterogeneity problem.
An Automated Testing Framework for Gesture Recognition System using Dynamic Image Pattern Generation with Augmentation

In the field of information technology, the gesture recognition system plays a very essential role. As it has achieved vast importance, it is mandatory to test the recognition system to ensure the quality of the system by identifying the bugs in the software. In our research, we suggested a dynamic testing method for gesture recognition software. using dynamic image pattern generation with augmentation. The automated software testing framework is a set of processes to create new test cases for properly testing a image processing software. The research intention for generate automated testing cases by following a standard process which helps to increase the performance and efficiency of the gesture recognition system. We have built the framework to give proper testing and give result (accuracy and defect) for which gesture recognition system already in the market. our research, the team strongly following and adding two software testing standard. First one is ISO/IEC/IEEE/291129-3 to define the process for testing software. And the second one is ISO/IEC/IEEE/291129-5 to implement the techniques for software testing. We proposed this framework with major five parameters by noise, rotation, background, contrast, and scale. Which are the most use with every gesture recognition system. Our developed framework’s phase is used to generate new testing cases based on the existing gesture recognition system’s data. There are we work with five systems, commonly with the gesture recognition for experiments. We provide the testing report with total accuracy and defect by comparing existing well-known system’s data. At the final result, our system suggested an analysis report based on the testing result. And tell what are the improvement needs for the existing system to consider noised images or different scaled images to build a robust system.&#x0D; GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 7, Dec 2020 P 42-50
Has Albania's Economic Development Stalled? Investigating the Role of Institutional Factors in Albania's Economic Performance

This study focuses on the institutional factors of Albania's economic development, from a comparative, dynamic, and regional European perspective. We use longitudinal data for the years 2002, 2014, and 2019 and a small selection of 13 countries in the region and some EU member states. Descriptive statistics, graphical representation, and econometric modeling are used for data analysis. The purpose of the study is to discuss, in real and comparative terms with the region and beyond, the economic growth of Albania based on the GDP per capita indicator, as well as to identify and evaluate dynamically the role of institutions in the country's development through important institutional factors, such as the effectiveness of government, rule of law, corruption, etc. The analysis shows that Albania's economic performance is weakover the last two decades. This is reflected in the insufficient relative growth of GDP per capita, the small increase in per capita income, and especially in the low increase in income for every 1% of relative growth. In these indicators, Albania continues to be consistently in the lowest positions in the region and beyond. The study highlights the strong link between economic growth and the effectiveness of government, the rule of law, and weak control over corruption. Improving corruption control by one unit in the range (-2.5 to 2.5) is expected to improve GDP per capita by an average of about 2.2 times. Improving the rule of law by one point is expected to improve GDP per capita on average by about 2.4 times. The country's sluggish economic performance is mainly attributed to weak institutions.&#x0D; &#x0D; Received: 4 March 2021 / Accepted: 6 May 2021 / Published: 8 July 2021
A novel method for measuring the timing website reconstructions

This research method contributes to the literature by measuring commensurably the Timing of Website Reconstructions (TWR) for Web-based research studies. TWR deepens the understanding the functionality of online media by focusing on specific web metrics to make the usage of this type of media efficient for disclosure function. This method helps establishing a new methodological pathway by providing chronological map of website reconstructions. The inputs of new method are originally based on publicly available data and it can be applied through 3 consecutive steps. Accordingly, this method is applicable to assess disclosure function for any web-based research study. In sum, this method presents. The inputs of TWR method are publicly available data. This method is applicable for variety web-based research studied regardless of the applied methodological approach (e.g., qualitative, quantitative).
Evaluation of reading pleasure character in SMPN 19 and SMP Adhyaksa 1 of Jambi City

This study was conducted to determine the reading pleasure of junior high school students through four indicators. The research was conducted with a total sample of 281 students from grades VII, VIII, and IX in junior high schools. The sampling technique used was purposive sampling. The research design used is an explanatory design. The quantitative instrument in the form of a reading pleasure instrument consists of 40 statements, while the qualitative instrument is in the form of interviews with ten students, four teachers, and two heads of the library. The data collection technique was carried out by survey (field research). The results of this study indicate that the indicators of general attitudes towards reading are on a neutral scale, the indicators of reading preferences are on a neutral scale, the indicators of the effects of reading on ability are on the agreeing scale, the indicators of students' negative views on reading are on the disagree scale. The results of interviews with the teacher can be seen that the teacher has reminded students always to read books other than in face-to-face activities in class, then the results of interviews with the head of the library can be seen that junior high school students have high enthusiasm for reading and borrowing books in the library, the results of interviews with male students and female students show that female students have better reading pleasure than male.
Securing Student Data Privacy using Modified Snake and Ladder Cryptographic Algorithm

Transformed by the advent of the Digital Revolution, the world deals with a gold mine of data every day.Along with improvement in processing methods for the data, data security is of utmost importance.Recently, there was a noticeable surge in online learning during the pandemic.Modifying their workflow strategies, the educational institutions provided courses for students designed to suit the need of the hour.This opened up the avenue for a greater number of students to take part in the online learning.With the increase in number of students registered, there exist a substantial repository of data to deal with.Hackers have been targeting student data and using it for illegal purposes.In this research paper, an attempt has been made by modifying the classic Snake and Ladder game to perform encryption on short text student data to ensure data privacy.The Novel algorithm maintains simplicity yet produces a strong cipher text.The algorithm stands strong against the brute-force attack, cipher-only attack, etc. Decryption also uses same key as used for encryption, the key being symmetric in nature.New variable keys are generated every time the algorithm is used.
TRAINING INSTITUTIONS FOR TEACHERS OF PRIMARY CLASSES OF POLTAVA REGION OF THE END OF XIX EARLY XX CENTURIES

The article deals with the activity of teacher training institutions of Poltava region, features of their activity and foundation, characterizes the organization of the educational process. Emphasis is placed on the role of zemstvos in the activities of these educational institutions. In the second half of the 19th century, much attention was paid to the training of public school teachers. Public organizations (zemstvos, societies) and, in contrast to the previous time, the Ministry of Public Education played an important role. Thus, in 1865 in each educational district (except Kyiv) “at one of the county schools…, at the discretion of the trustee,… before the establishment in the future… special teacher’s seminaries” were established pedagogical courses. A year later their number doubled Kyiv educational district since 1862 at the University of St. Vladimir there was a “pedagogical school for the training of teachers of folk schools in the south-western provinces”). Teachers’ seminaries are secondary pedagogical educational institutions for the training of teachers of public primary schools. They had a 3- and 4-year course of study.Young people at least 16 years old of all classes and religions were admitted after passing the entrance exams according to the program of two-grade primary schools. Preparatory classes were opened for entrants. Maintained at the expense of state and zemstvo funds. Taught: the law of God, Russian and Church Slavonic languages, arithmetic, geometry, Russian and general history and geography, science, drawing, calligraphy, basics of pedagogy, gymnastics, singing, music, pedagogical practical classes, handicrafts. Extracurricular activities were practiced. Teachers were graduates of universities, teachers’ institutes, gymnasiums.
Implementasi Metode Simple Additive Weighting Dalam Sistem Pendukung Keputusan Penerima Bantuan Program Sembako

Pahandut Seberang Village has an average middle to the lower level of economy in the community, so most of the people still need assistance from the government. In Pahandut Seberang Village, the selection of recipients of the Smbako program assistance is still the old way by using from paper. The assessment process is still not transparent in nature and the selection process is very slow and receipt of Sembako programs assistance are not being on target. Therefore, to overcome this problem, a Decision Support System (SPK) is created to help the Pahandut Seberang Village in selecting the recipients prospective of Sembako program assistance&#x0D; In designing and building the system are using 2 development methods, namely the Waterfall method as a software development method and the Simple Additive Weighting (SAW) method as a decision support system method in its calculations. Where the saw method has 4 stages, namely determining the criteria, determining the suitability, making a decision matrix based on the criteria and normalizing the. The final result is obtained from the ranking, namely the sum of the normalized matrix multiplication R with the weight vector so that the largest value sas a solution.&#x0D; This system testing uses a Black-box testing system. The test results show that the system created has been running according to the expectations of the researcher. This research produces a decision support system for selection of the recipients prospective that can provide recommendations for the recipients prospective the Pahandut Seberang village.
Financial Deepening, Stock Market, Inequality and Poverty: Some African Evidence

This paper presents evidence about the relationship between private credit, stock market indicators, income inequality and poverty, using the annual data that ranges from 1992 to 2018 on nine African economies.We applied the estimation method of Autoregressive Distributed Lag (ARDL) to model the long-run effect.In Addition, we used Dumitrescu and Hurlin Panel causality to check the direction of causality.The results of long-run estimates show that the stock market indicators have a significant positive impact on income inequalities, but have a negative and significant impact on poverty.Further, our findings show that private credit adversely reduces income inequalities.Our results also establish significant short-run causalities among stock market indicators, private credit, income inequalities, and poverty.