Reviewerly/exHarmony huggingface dataset:
Mobile Apps Business Design and Development for Integrated Waste Management

The conditions in Indonesia are specifically described in the research results of Jenna R Jambeck and friends [1] stated that Indonesia was in second place contributing plastic waste to the sea after China, followed by the Philippines, Vietnam and Sri Lanka. Waste Bank is local wisdom initiative from Indonesia for the waste management. Waste banks are established in a special environment for around 1,000 residents and are usually managed by people and targeted to people who want to increase their income. Bank customers bring all non-organic waste to banks that are treated as deposits. Transactions are recorded preferably in the bank book that the customer keeps or alternates in the list stored by the bank. Many banks also accept organic waste while the rest support composting at home. Waste banks sell materials stored to agents or ultimately to waste bank central developed by government and supplied to company for reuse or recycling. So, waste deposits are converted into money that can be withdrawn when needed after a contribution of around 10% to 15% is reduced for bank operational costs. Community empowerment through the concept of a waste bank still needs the support of infrastructure and information technology facilities and profitable partnerships. The empowerment program for the citizens were conducted through counseling, education, training with as well as dialogue with the citizens in the targeted community. The community waste bank will not have the potential to grow without the involvement and support from the stakeholders. It becomes important to develop model and implement the partnerships, networking and institutional cooperation mechanism between the community, waste bank management, institution, business and government. The integrated partnership on waste management with system information support can generate creativity and innovation as well as to improve the welfare of the community. This paper discuss about designing mobile apps business development for integrated waste management system. It’s a proposed design model for apps and business model for waste management in Indonesia and other developing country.
Pengembangan Sistem Informasi Manajemen

The Management Information System is a series of information subsystems that cover thewhole and have been arranged in an integrated manner that is able to move data so that itbecomes information through several ways to increase productivity similar to the model andnature of managers on the basis of predetermined criteria. The management informationsystem is defined as a pyramid building whose base layer is information then followed by anexplanation, status explanation, and so on. Management information systems rely heavily onelements that will produce an information system that suits their needs. imbalances that meetin an embodiment of these elements which will create a slightly incorrect information whichwill result in errors in every decision making in an organization or company. Therefore it isvery necessary to understand an understanding of the elements in a management informationsystem, especially operators that produce very accurate and precise information for a groupor company.
An innovative approach to students’professional training in the context of heuristic learning

The article deals with the didactic opportunities of heuristic education as an innovative condition for the students' professional training.The role of various types of heuristic activity in the formation of such an important quality of future teachers as tolerance as well as students' professional and creative skills in the process of their participation in the student theatre is analyzed.The results of a pedagogical experiment on the formation of students' tolerance and their professional and creative skills are presented in the article.
Data Visualization

In this chapter we will see more depth in terms of data visualization, where we will see the different ways of representing data visually, with the use of different commands, and create a range of different types of graphs. We will also see how to customize plots and use predefined plot themes.
On Secured Blockchain Technology For K-Nearest Neighbors Algorithm

This paper proposes a cloud-based manufacturing knowledge sharing system for injection mould redesign (IMR) in perspective on square chain development. In our proposed structure, private cloud is connected to spare the IMR becoming more acquainted with, and square chain offers measures and shows to completing the system similarly as making certain the wellbeing in a trustless space. k-Nearest colleagues is connected for convalescing the square chain-essentially based report becoming more acquainted with. The proposed system not solely can energize imbuement structure supplant, yet further give a component to data proprietors to share their own special favorable circumstances adequately.
Evolutionary Computing in Neuronal Modeling

The efficacy of genetic algorithms in the design of models that model specific and experimental aspectsof action potentials in a wide variety of organisms is proven. A specific example of a plant actionpotential is used to illustrate the use of genetic algorithms in the search for parameters of models. Theefficiency of the genetic algorithms as a search method is in the short generation span of theconvergence of the algorithm.
An Open Source Tesseract Based Optical Character Recognizer for Bengali Language

Optical Character Recognition (OCR) is the process of extracting text from an image. The main purpose of an OCR is to make editable documents from existing paper documents or image files. OCR primarily works in two phases; they are character and word detection. In case of more sophisticated approach, an OCR also works on sentence detection to preserve documents’ structures. In this paper, we would discuss the process of developing an OCR for Bengali language. Lots of efforts have been put on developing an OCR for Bengali. Though some OCRs have been developed, none of them is completely error free. For our thesis, we trained Tesseract OCR Engine to develop an OCR for Bengali language. Tesseract is currently the most accurate OCR engine. This engine was developed at HP labs and currently sponsored by Google. In Tesseract there are two option to training first one is Legacy Training and second is LSTM Training. We do both of them.
Gaussian Mixture Model and Lifting Wavelet Transformed Base Satellite Image Enhancement

From the last few decades, Satellite images are being used widely in various applications like monitoring of forest areas, weather forecasting, polar bears counting, etc. In those applications to get more details of images efficiently, satellite images should be enhanced up to the required level as the images captured by the satellites are covered very large areas and those are very low-resolution images due to the high altitudes of satellites from the earth. We proposed a method of an image enhancement which includes both resolution enhancement and contrast enhancement. In this method, Stationary Wavelet Transform (SWT) in combination with Lifting Wavelet Transform (LWT) is used for image decomposition into low-frequency sub band images and high-frequency sub band images to separate smooth regions and sharp edges to interpolate regions and edges separately to reduce blurring effect in edges and noise in smooth regions. To get smoother details and sharper edges, Gaussian Mixture Model (GMM) is used for interpolation in resolution enhancement process and SWT with the combination of Contrasts Limited Adaptive Histogram Equalization (CLAHE) for contrast enhancement process. SWT in combination with LWT improves the resolution effectively and also minimizes the execution time drastically than existing methods due to the shift invariance of SWT and reduced computations in LWT and GMM interpolation results from sharper edges and smoother details. SWT is used in combination with CLAHE to enhance the contrast and mitigate the noise effects than existing methods. The proposed method gives superior results and compared with existing techniques with PSNR, Noise Estimation, and visual results.
Feature Specific Optimal Random Forest Algorithm for Enhancing Classification Accuracy

creature an ensemble method, Random Forest create numerous DTs as base classifiers and invoke larger part voting to consolidate the results of the base trees. In this exploration work an endeavor is made to improve execution of Random Forest classifiers as far as correctness and time required for erudition and classification. we first present another variety of Optimal irregular Forest reliant on a direct classifier, by then build up a group classifier subject to the blend of a brisk neural Network (NN), vector-utilitarian association arrange and Optimal arbitrary Forests. Arbitrary Vector have a rich close structure game plan with incredibly short preparing time. The observational assessment and consequences of tests finished in this investigation work lead to reasonable learning and arrangement using RF.
Landslide Early Warning in Indonesia: A Gap Analysis

&amp;lt;p&amp;gt;For the last decade, rainfall-triggered landslides have been one of the major hazards in Indonesia. According to the National Agency for Disaster Management (BNPB) reports, from 2010 to 2020, a total of 5822 landslides occurred in Indonesia and caused 1812 casualties, 1627 injured, and 234 missing. More than 75% of those landslides occurred in Java, the most populous island in the region. Settlements alongside agricultural fields often are located in areas that are susceptible to landslides. As relocation would be costly, a landslide early warning system (LEWS) could provide the necessary information for communities susceptible to landslides to prepare for the upcoming hazard. The objective of this study is to map the issues with the existing landslide early warning system in Indonesia and our plan to improve landslide forecasting by tailoring available rainfall forecasts and monitoring.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The United Nations International Strategy for Disaster Reduction (UNISDR) has defined an end-to-end early warning system that essentially comprises knowledge risk, hazard forecasting, alerts dissemination, and community response. In the definition, the UNISDR also highlighted timely and meaningful warning information for appropriate preparedness and action in a sufficient time. Landslide prediction itself is challenging in terms of when and where precisely the landslides occur as different landslide types have different characteristics and trigger mechanisms. Moreover, when rainfall forecast data is used as input for a physically-based hydrological and landslide model, the uncertainty and accuracy of the rainfall will affect the forecast skill.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;National LEWS with a longer lead-time is operational, utilizing generic rainfall thresholds derived from 1-day and 3-day cumulative rainfall triggering landslides occurred in Indonesia (mostly in the Java Island) as warning signals. The rainfall thresholds were derived from NASA Tropical Rainfall Measuring Mission (TRMM) rainfall estimates with a spatial resolution of 0.25&amp;amp;#176;&amp;amp;#215;0.25&amp;amp;#176;. Different studies showed that the thresholds derived from that product are lower than those derived from raingauge measurements, potentially leading to more false alerts. These thresholds are applied for all catchments in Indonesia even though the region has different climate regimes and geomorphological characteristics, leading to insufficient accuracy for the local landslide prediction.&amp;amp;#160; As for the forecast, the current LEWS applies rainfall forecast with the same spatial resolution as TRMM, which is not suitable for (sub-)catchment-scale prediction.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;This study proposes an approach to tailor rainfall data from various high-resolution sources, like radar, NWP models, and satellite, where historical landslide data are to be used to derive dynamical rainfall thresholds at local scale.&amp;lt;/p&amp;gt;
Homomorphic Cryptosystems for Data Security in Cloud Storage

Cloud Computing enables users to use remote resources thus reduces the burden on local storage. However, the use of such services gives rise to new set of problems. The users have no control over the data which they have stored on those storages so to achieve data authentication with confidentiality is utmost important. As every user may not have that expertise so they can request for data verification task to Trusted Verifier (TV) which will be an authorized party to check the intactness of outsourced data. Since the data owner stores the data on the cloud in an encrypted format, it becomes difficult to check the integrity of the data without decrypting. But by using homomorphic encryption schemes the integrity checking can be made possible without original copy. In this paper, we have given implementation and performance details of two homomorphic encryption schemes, Rivest Shamir Adleman (RSA) and Paillier. The RSA is multiplicative homomorphic scheme where the Paillier is additive homomorphic scheme. Both the algorithms are partially homomorphic thus limited in their functions. Due to homomorphic property of these algorithms, original contents will not get revealed in the verification process. This framework will achieve authentication of data by maintaining confidentiality.
Aspect Based Sentiment Analysis for E-Commerce Websites with Visualization through Machine Learning Algorithm

E-commerce is evolving at a rapid pace that new doors have been opened for the people to express their emotions towards the products. The opinions of the customers plays an important role in the e-commerce sites. It is practically a tedious job to analyze the opinions of users and form a pros and cons for respective products. This paper develops a solution through machine learning algorithms by pre-processing the reviews based on features of mobile products. This mainly focus on aspect level of opinions which uses SentiWordNet, Natural Language Processing and aggregate scores for analyzing the text reviews. The experimental results provide the visual representation of products which provide better understanding of product reviews rather than reading through long textual reviews which includes strengths and weakness of the product using Naive Bayes algorithm. This results also helps the e-commerce vendors to overcome the weakness of the products and meet the customer expectations.
INHOUSE STYLE ON 5 SCIENTIFIC JOURNAL ARTICLES IN INDONESIAN LANGUAGE AND LITERATURE EDUCATION

Inhouse style is the style of language or guidelines that apply to a media. In writing or editing a text, the author must also be able to adjust the writing style that is applied in the publisher concerned. Every publisher or media has a different style of environment. There are those who obey the EYD and the Good and True Indonesian Language Rules, some do not. Publishers consider in terms of comfort of the reader, the category of readers, and so on. The cheating style is not only the choice of words, but also the style of language in the arrangement of words and sentences. Although sometimes, the shelling style of a publisher makes an EYD part or an Indonesian language rule not fulfilled, there are still things that must be considered. Selingkung style that is different from EYD / KBBI, usually consider in terms of pronunciation or words that have become a habit.
Conceptual Schematic Design of Evolving Bci Design Principles

At once of boosting disagreement and fast technological change, the ICRC requires each to understand the influence of brand new modern technologies on folks impacted through armed dispute and also to make altruistic answers that take care of the necessities of one of the most susceptible. Learning algorithms in lots of uses that's we take advantage of daily. Whenever a web online search engine like Google or Bing is made use of to browse the world wide web, some of the explanations that functions so properly is due to the fact that a learning formula, one applied by Google.com or even Microsoft, has actually learned exactly how to position website. Today, machine learning is a widespread condition that incorporates a lot of sorts of plans that you'll stumble upon in significant records analytics and records mining.
Factors on Learning Satisfaction with a Focus on E-learning in the Military

The Department of National Defense in South Korea is taking steps to develop smart learning to prepare for the information age, but as of yet there have not been any sufficient empirical analyses on learning satisfaction. The Department of National Defense in South Korea is taking steps to develop smart learning to prepare for the information age, but as of yet there have not been any sufficient empirical analyses on learning satisfaction. The findings of this study showed the following factors as positively affecting learning satisfaction with e-learning in the military: learning motivation, ease of the use environment, learning support level of the organization, content feasibility, and instructor-learner interaction. Similarly with the official education centers and universities, learning motivation was proven to be the most important factor in e-learning education in the military. Also, as factors that reflect the nature of the military, ease of the use environment and learning support level of the organization were identified as factors that affect learning satisfaction. This result suggests the importance of the infrastructure and setting for e-learning in the military. The factors of content feasibility and infrastructure-learner interaction were also shown to affect learning satisfaction. Suggesting further investment in the design and development of e-learning contents and an increased proactiveness of the instructors to improve learning satisfaction.
Face Recognition using Discrete Haar Wavelet Transforms

Wavelet transform is being applied as an important analyzing tool in signal and image processing because it provides better signal representations with less computation time because of property of multiresolution analysis. An analogue image is transformed into a discrete image in a space through a sampling process. The wavelet transforms and analysis of discrete image are performed using Haar wavelet, level-2. Through analyzing and comparing different patterns, one or more persons are identified in the face recognition process. It is accomplished by using correlation coefficient and Euclidean distance of scaling coefficients of wavelet transformed images. In the face recognition the typically facial features are extracted and compared to a database for finding the best match. Matching of features is performed between test image and stored database images.
Anonymization and Publication of Trajectories by Sensitive Halting points Generalization

The profuse use of wireless and GPS enriched mobile devices has left spatio-temporal trajectory traces in an enormous scale. The researchers and mobility management people are keen to extract and make use of the published mobility traces for their own developmental activities. The spatio-temporal traces publication is definitely a major privacy encroachment for the individuals/objects, especially for VVIPs. The publication of trajectory details urges us for a privacy preserved anonymization approach. The observation was the trajectory consists of halts and passes and anonymizing the sensitive halting points is adequate enough for the trajectory anonymization. This paper suggests a different approach, which derives the major halting points from the trajectories and anonymizes them by using the personalized generalization technique. The prototype referred to here safeguards the major sensitive halting points in an area zone, the size of which is specified by the user. This work uses Haversine measure for the spatial distance instead of Euclidean measure, since the former takes into account the spherical shape of the earth and gives an exact distance from sensitive to non-sensitive points. For the evaluation, the model mentioned here utilizes the real world dataset and the outcome proves that, the published trajectory has lesser information loss and greater privacy than the anonymity methods that exists now and it can be used safely for mobility related applications and developments.
Servitization Trend in Big Data to Personal Styling Service

Servitization is a customer service with integrated product-service offerings, called product-service systems. This study aims to analyze consumer awareness and user behavior of servitization and focus the personal styling service in fashion industry. We used the social network and text mining techniques to capture social network service communications, which is a great source of useful information close to customers. Frequency analysis, centrality analysis, clustering analysis, and network visualization were conducted to investigate consumer awareness and user behavior using big data in social media. “Shoes” and “clothes” were the most frequently apparent keywords with the notion of “servitization,” and the keywords “home” and “fashion” had the highest degree of centrality in the network. Four clusters were found on the notion of servitization: fundamentals, fashion, home, and job seeking. A significant transition toward servitization is ongoing in various industries, especially the fashion industry, according to the clustering analysis. To gain a better understanding of this transition, a commercially available personal styling service was investigated. Three major companies were selected by sales volume and reputation, and the names of these companies were used as search keywords to acquire related data on social media. The keywords “men’s fashion” and “subscription box” appeared frequently apart from common fashion-related hashtags. In betweenness centrality, “best quality” and “low price” were the most important keywords in the market. This study contributes to the investigation on the trend of servitization and provides insights to service providers on consumer awareness and user behavior toward this trend via social media.