Reviewerly/exHarmony huggingface dataset:
Analysis of flood peaks using the mean annual flood (MAF) method, case study of the Kedang Pahu river, East Kalimantan

The Kedang Pahu river is one of the tributaries of the Mahakam river. The research plan is located in Damai District, West Kutai Regency, East Kalimantan province. Recently, the Damai Kota and Damai Seberang areas have flooded activities that have caused the surrounding settlements to flood to residential areas and block existing road access. Planning analysis and knowing the annual flood elevation is very necessary. The analysis uses the method of calculating the mean annual flood (MAF) as the search for the average annual flood discharge data and the search for the average annual elevation. Data validation using simple linear regression method produces a correlation coefficient of 58.67% or R value = 0.5867. The analysis results in the value of Q1 or the 1st year period, the mean annual flood rate of the average annual flood discharge is 2576.0695 m³/second and the value associated with the magnifying factor (GF) is the average annual flood discharge rate of Q5=3014,00 m³/ sec, Q10 = 3529.22 m³/sec, Q20 = 4095.95 m/sec, Q50 = 5049.10 m³/sec, Q100 = 5847.68 m³/sec, Q200 = 6852.34 m³/sec, Q500 = 8423.75 m³/sec &amp; Q1000 = 9917.87 m³/sec. The results of the analysis at HEC-RAS 5.07 based on manning analysis showed the elevation values were Q1=18.47m, Q5=18.85m, Q10=18.86m, Q20=19.18m, Q50=19.74m &amp; Q100=19.99m. Researchers only show elevations up to Q100 or the 100th year because of limited data and the accuracy of the data reviewed.
Information Retrieval in Text-Based Document using Boyer Moore Algorithm

The Language Development Center (LDC) is a language laboratory that annually serves more than 1000 participants in activities such as standardized tests and language courses for students and lecturers. This activity generates a lot of data which is still managed ineffectively and causes several problems in data retrieval, archiving, and monitoring. Therefore, this research was made with the aim of creating a system so that data management in LDC becomes more effective. In designing and building this system, the writers uses the Waterfall method and also implements the Boyer Moore algorithm in the data search process. Boyer moore algorithm helps the data search process more effectively and can search for words in several text-based files at once. The result of this research is a web-based data management information system that makes the data management process becomes more effective and efficient.&#x0D; Keywords: information system, data management, data retrieval, Boyer Moore algorithm
Sentiment analysis using Hierarchical Multimodal Fusion (HMF)

The rapid rise of platforms like YouTube and Facebook is due to the spread of tablets, smartphones, and other electronic devices. Massive volumes of data are collected every second on such a platform, demanding large-scale data processing. Because these data come in a variety of modalities, including text, audio, and video, sentiment categorization in various modalities and emotional computing are the most researched fields in today's scenario. Companies are striving to make use of this information by developing automated systems for a variety of purposes, such as automated customer feedback collection from user assessments, where the underlying challenge is to mine user sentiment connected to a specific product or service. The use of efficient and effective sentiment analysis tools is required to solve such a complex problem with such a big volume of data. The sentiment analysis of videos is investigated in this study, with data available in three modalities: audio, video, and text. In today's world, modality fusion is a major problem. This study introduces a novel approach to speaker-independent fusion: utilizing deep learning to fuse in a hierarchical fashion. The work tried to obtain improvement over simple concatenation-based fusion.
Analisis Dan Simulasi Banjir Das Kenali Kecil Dengan Menggunakan Sig Dan Model Hidraulika Hec-Ras

Floods are the most common disasters in almost all places, including Indonesia and Jambi City in particular. Areas that are directly affected by the threat of flooding are in the Watershed. Kenali Kecil watershed is one of the sub- watersheds of Batanghari which is administratively located in Jambi City and Muaro Jambi Regency. The Kenali Kecil watershed is influenced by the rapid growth of Jambi City. Land conversion is not the only cause of flooding in the Kenali Kecil watershed. Floods also occur because the discharge/volume of water flowing in a river or drainage system exceeds its drainage capacity. This study analyzes the level of flood vulnerability based on SNI 8197:2015 and Head of BNPB Regulation No. 02 of 2012. The approach used in the SNI method is landscape analysis which emphasizes the process of forming natural systems on the earth's surface. Analysis of the level of flood vulnerability based on the Regulation of the Head of BNPB is based on the results of flood simulations using the HEC-RAS hydraulic model. The parameters used in this model are the manning’s coefficient, data geometry, discharge plan and terrain. The terrain used in this research is DEMNas. Discharge plan are obtained using the HEC-HMS application. In making the discharge plan, rainfall data for the last 10 years is needed, to get the CN and Impervious values, soil type maps and land use maps are needed. Based on the procedure of Indonesian National Standard (SNI) 8197:2015) the level of flood vulnerability in the Kenali Kecil watershed is in the medium level of 8.25 km2 (52.6%) and high level of 7.43 km2 (47.4%). Based on the HEC-RAS modeling for the 2-year return period (Q2), the flood area is 1.08 km2, the 5-year return period (Q5) is 1.2 km2 and the 10-year return period (Q10) is 1.3 km2. Based on the Regulation of the Head of BNPB No. 02 of 2012 the flood vulnerability level of the Kenali Kecil watershed is in the low level (&lt;0.76) Q2 = 0.33 km2, Q5 = 0.31 km2, Q10 = 0.32 km2, medium level (0.76 – 1 ,5) Q2 = 0.32 km2, Q5 = 0.31 km2, Q10 = 0.34 km2 and high level (&gt; 1.5) Q2 = 0.43 km2, Q5 = 0.58 km2, Q10 = 0.64 km2
Social and Cultural Background as the Potential for Aesthetical Education of Children in Conditions of Supplementary Education Facilities

The article is dedicated to research of processes of development of children’s supplementary education facilities as one of the factors of social and cultural activity in modern society conditions. The authors have reviewed definitions “social and cultural activity”, “supplementary education”, “modern supplementary education system”, “functions of social and cultural activity”, highlighted characteristics of aesthetical education of children through resources and methods applied in supplementary education and transitional tendencies to digitization in supplementary education. An analysis of strategic goals, tasks, national and Federal projects that challenge cultural establishments and supplementary education has been made. Tasks of supplementary education set by the government have been reviewed as to compliance to tasks indicative of activity of children’s organizations themselves. The current processes in social and cultural activity and in supplementary education facilities show their diversity that make them interest for researchers. The authors have surveyed parents of preschoolers and junior school children as well as parents of teenagers aged 15-16 all totaled 45 persons within the period from December 1st, 2021 to January 1st, 2022. The survey task was to research awareness of Russian school children of attendance, work and opportunities of the children’s social organizations. The received data have been consolidated and put to analysis. Problems that supplementary education is facing in its present stage of development have been discovered. Based on the research it has been summarized that aesthetical education in supplementary education facilities is necessary to be focused on application of modern methods and approaches, on new resources that would be of a greater demand among modern young people.
Towards User Interface Guidelines for Musical Grid Interfaces

Musical grid interfaces are becoming an industry standard for interfaces that allow interaction with music software, electronics, or instruments.However, there are no clearly defined design standards or guidelines, resulting in grid interfaces being a multitude of interfaces with competing design approaches, making these already abstract UIs even more challenging.In this paper, we compare the co-existing design approaches of UIs for grid interfaces used by commercial and non-commercial developers and designers, and present the results of three experiments that tested the benefits of co-existing design approaches to mitigate some of the inherent design challenges.
EBLIP Seeks Writing Assistants

Evidence Based Library and Information Practice (EBLIP) seeks volunteers to be Writing Assistants.Writing Assistants provide guidance to non-native English speakers who submit promising papers to EBLIP but who need help in terms of organization, grammar,
The Problem on Determining "How to Incorporate Knowledge into Information Mining Algorithms"

There is a massive amount of data on the Internet right now, but essentially little classification information. The main issue is figuring out how to incorporate knowledge into information mining algorithms. The authors examine information retrieval approaches and discuss their advantages and disadvantages. Although most Web documents are text oriented, there are plenty of them that contain multimedia elements, which are not easily accessible through common search methods. Web information is dynamic, semi-structured, and interwound with hyperlinks. Several advanced methods for Web information mining are analysed: 1) syntax analysis, 2) metadata-based searching using RDF, 3) knowledge annotation by use of conceptual graphs (CGs), 4) KPS: Keyword, Pattern, Sample search techniques, and 5) techniques of obtaining descriptions by fuzzification and back-propagation. The problem of choosing proper keywords is
INTEGRATED CIRC TECHNIQUE, AUTHENTIC MATERIALS, AND ONLINE LEARNING DURING COVID-19

This research aimed at finding out the integration of CIRC technique, authentic materials, and online learning during the Covid-19 pandemic, to enhance students writing ability, especially for procedure text. The objective of the research was junior high school class IX in Gowa South Sulawesi, which had 40 students. In this study, researchers used mix method namely explanatory research (quantitative and qualitative method). For quantitative analysis, researchers applied experimentally group by using pre and post-test. For qualitative analysis, the participants had to answers an open-ended questionnaire related to their perspective of the treatment session. The result of the quantitative data analysis showed that the percentage of students' results post-test was higher than pre-Test, which achieved 97.5 % in post-test. The result of the t-test value showed that the combination of CIRC technique, authentic materials, and online learning, affected positively students writing ability, and it was in line with students’ perception of the application of CIRC technique and authentic material. However, from the results of qualitative data, some students preferred to study in class and interact directly with teachers and friends, and some students showed a lack of motivation to cooperate.
Handwritten Digits Image Generation with help of Generative Adversarial Network: Machine Learning Approach

In recent years, research into Generative Adversarial Nets (GANs) has increased dramatically. GAN was first proposed in 2014 and has since used in various real-time applications,Includes computer vision and natural language processing for approximately accurate results. Image composition is the most popular study of the many applications of GAN,Studies in this area have already shown the great future of using GAN for image composition.This article shows how to classify image composition methods, reviews different models of text-to-image composition and image-to-image conversionand provides some metrics and future research on image composition using GAN. I will explain the direction of in this paper. In current years, frameworks using Generative Adversarial Networks (GAN) have been very successful in many areas many areas, especially in image generation, asthey can create very realistic and crisp images and train on large datasets. However, successful GAN training can be very difficult if you need high resolution images. Text-to-image compositing, image-to-image conversion, face manipulation, 3D image compositing, and deep master printing are five interesting areas that can be applied to image compositing based on the state-of-the-art GAN technology described in this article. It presents a comprehensive analysis of current GAN-based imaging models, including their strengths and weaknesses. At the same time, recent rediscovery of deep learning and widespread interest in generation methods in the scientific community have made it possible to generate realistic images by learning the data distribution from noise. If the input data contains information about the visual content of the image, the quality of the generated image will improve.
Database Security using Cryptography

Abstract: There has been an explosion in data since last two decades and this explosion of data is due to high rates of data conversion and better internet services worldwide [21]. All the conventional methods of data handling have been replaced by much more sophisticated means. One of the typical shifts of the emerging information society is that information is becoming a crucial if not the most vital source. Information contrasts profoundly from further resources; for example and it can be imitative without cost, it can be erased without leaving traces. [22] Protecting the new resource information is a major issue in the information economy [20]. One such means is a Database. It makes it easier for data related queries butit can be dangerous if this data is leaked or sent outside the organization. A high price is positioned on confidentiality when information concerning statesecrets, business plans, war strategy, medical recordsand financial transactions needs to be stored or transmitted. Since its inception, the Internet has enable [19]. A cyber crime emerging in recent years data breachis one of the most notorious and disastrous data crimes majorly caused due to unsecure database. To secure these databases we can apply the concepts of AES algorithm. It is an algorithm used in cryptographywhich changes normal text to unreadable or cypher text. Keywords: Cryptography, AES, cypher, digitzation, confidentiality
Application of Differential Evolution Algorithm in the Construction and Simulation of Interactive English Translation Teaching Mode

To improve the effect of English translation teaching, this paper combines the differential evolution algorithm to construct and simulate the interactive English translation teaching mode and analyzes the differential enumeration attack. Moreover, this paper studies the algorithm structure of the LowMC algorithm and evaluates the rationality of the LowMC algorithm round number setting by analyzing the actual attack effect of the key initial round number of a specific linear layer. Additionally, by studying whether the key initial round number can reach the theoretical value under the actual linear layer, the effect of differential evolution algorithm processing teaching information is evaluated. Through expert evaluation, it can be seen that the interactive English translation teaching model based on the differential evolution algorithm proposed in this paper has good effects and can improve the quality of English translation teaching.
An Empirical Study on Implicit Constraints in Smart Contract Static Analysis

Smart contracts are usually financial-related, which makes them attractive attack targets. Many static analysis tools have been developed to facilitate the contract audit process, but not all of them take account of two special features of smart contracts: (1) The external variables, like time, are constrained by real-world factors; (2) The internal variables persist between executions. Since these features import implicit constraints into contracts, they significantly affect the performance of static tools, such as causing errors in reachability analysis and resulting in false positives. In this paper, we conduct a systematic study on implicit constraints from three aspects. First, we summarize the implicit constraints in smart contracts. Second, we evaluate the impact of such constraints on the state-of-the-art static tools. Third, we propose a lightweight but effective mitigation method named ConSym to deal with such constraints and integrate it into OSIRIS. The evaluation result shows that ConSym can filter out 96% of false positives and reduce false negatives by two-thirds.
Mobile Robot Control Based on 3D Visual Servoing: A New Approach Combining Pose Estimation by Neural Network and Differential Flatness

This paper deals with 3D visual servoing applied to mobile robots in the presence of measurement disturbances, caused in particular by target occlusion. We propose a new approach based on the flatness concept. In 3D visual servoing, the task is performed out of image coordinate space and targets may leave the camera field of view during navigation (servoing). Forced to navigate blindly during one or more periods of time, the robot will use our new open-loop control algorithm inspired by the flatness concept. The 3D visual servoing method is performed using robot pose estimation. This estimation generally contains some errors. The exact position of the robot is therefore not guaranteed, and robust feedback control is necessary to reject these errors in the input. To solve this problem, we propose a new pose estimation method that uses neural networks. We reduce the complexity of the architecture of the neural networks used (the number of variables to estimate) by proving that the location and the orientation of the robot can be ensured by using a single point in the image coordinate space for mobile robots with two degrees of freedom. To show the efficiency of the proposed algorithm, we use the RVCTOOLS MATLAB toolbox.
An Ubiquitous Home Based Food ordering Application

Food ordering apps generally work as mediators between restaurants and customers. It has become easy for the customers to get any food they want from a restaurant to be delivered directly to the home. But there is no option of home cooked food in those food ordering apps. There are times when people staying far from their home feel like having home cooked meals daily and not preferring restaurants. Home chef app works as a bridge between the home chef and the customers hence serving the customers the authentic meals which gives them the feel of home. The app provides them with variety of meal plans from different home cooks from the locality. They can subscribe the meal plan according to their wish. The trial pack makes it easy for one to choose the chef according to his/her need. This way of subscribing the food makes the customer to eat the local homemade food along with the health taken care of. The online mode of payment makes the subscription of meal plan easy. After the successful payment the food will be delivered to the given address according the subscribed plan. Customer feedback will help in good customer chef relationship.
Role of Data Mining Technique: A Boon to Society

Abstract: Datamining is a method of finding interested patterns from huge volume of data. Datamining techniques helps to make business decisions. It analyses information from multiple sources like DataMart, databases. In this paper, we are focussing on datamining tasks and its variety of applications in different fields, which is boon to the society. Keywords: KDD, Decision Tree, OLAP servers, Cube API, ODBC, Frequent patterns
Optimization Of Determination Against K-Means Cluster Algorithm Using Elbow Creation

Clustering is a data mining method for grouping data that have similar or different characters in each section. One of the methods is using K-Means by measuring the distance between clusters using the shortest distance or Euclidean Distance. K-means entails weakness, which is the determination of clusters in k-means clustering, resulting in the different data grouping and affecting the results of the data cluster distribution. To overcome this issue, the elbow creation method is employed to determine the similarity level in the cluster by observing the comparison between Root Means Square and R Square to measure the homogeneity and heterogeneity of the cluster where this method is applied by considering the changes in the comparison between the RMSSTD (Root Means Square Standard Deviation) and RS (R Squared) values which have the intersection of the RMSSTD and RSquared values. The difference between RMSSTD cluster 1 and RMSSTD cluster 2 was 0.066 and RS cluster 1 and RS cluster 2 was -0.304. Based on those figures, the highest difference was found in cluster 2. All considered, tourist destinations in East Asia frequently visited or interested to visitors are grouped into cluster 2, comprising criteria 6, 7, 8, and 10, or in other words, resort destination, picnic area, beaches, and religious institutions
Implementation of Gain Ratio on KNN Method in Predicting Sales of Electronic Sparepart at Panasonic Service Center Lhokseumawe

K-Nearest Neighbor is a good classification technique, but judging by previous studies, the accuracy of the KNN performance obtained is still inferior to other methods. in the classification process, if some characteristics are not good it can cause errors in the new classifier. As for this study, the researcher uses the gain ratio method as a parameter to see the correlation between each attribute in the dataset, and the gain ratio serves as a weighting for each attribute so as to produce a dataset. the correct way of classifying data using the KNN method, this study is very suitable for predicting sales of spare parts at the Panasonic Service Center company, where the company experienced a decline in sales, this research is very useful for predicting sales for the following month. The results of this study produce very precise predictions of distance with an accuracy value of 13%, where the comparison of the highest accuracy value is found in the total attribute with an accuracy distance of 13%, while the lowest accuracy difference is obtained in the month and type of sales dataset with 0.08%. the overall accuracy of all datasets increases by 100% with K=3, and K=5 gets 80% accuracy. so this method can be used to make sales predictions to make it easier for the company.
Internet Threats and Mitigation Methods in Electronic Businesses Post Covid-19

With the advent of COVID-19 and the imposed lockdowns, many businesses were forced online.A number of these business owners had no prior knowledge of internet technology use and were therefore devoid of the knowledge of internet security threats.Many businesses still operate the ebusiness model even after the restrictions were lifted, due to the merits of the model.E-Business organizations were one of the main victims of internet fraud during the pandemic for various reasons.In this work, the most common threats and their mitigation measureshave been presented using the semisystematic literature review method.Knowledge and adherence to these mitigation measures, especially education of staff and customers will save electronic business owners from falling victim to internet fraud.