Reviewerly/exHarmony huggingface dataset:
SISTEM INFORMASI LINGKUNGAN SEBAGAI PENGEMBANGAN SISTEM KEWASPADAAN DINI MALARIA (Kajian di Kabupaten Ciamis Provinsi Jawa Barat)

Nowadays, the detection system of outbreak uses Early Warning System (EWS), whereas the base of EWS is the malaria case founded If the outbreak information is late accepted by malaria program organizer in district/municipality level, it could cause the unoptimal malaria outbreak control. An Environmental Information System (EIS) would be developed to prevent it. In order to develop EIS, it need to be determined the research location to get EIS parameter. The research objective is, to research the relation between environmental factor (the tide of sea water, rainfall, salinity, and algae) with An. sundaicus larva density. An. sundaicus mosquito density, and malaria case to be utilized as parameter in compilation of EIS. The design of the research is analytic epidemiology study to evaluate the hypothesis of the possibility of causal relations's between risk factor and the disease. Format of the study is observational study by using a retrospective and prospective research plans. The analysis unit is the individual group that is bordered by geographically, between High Case Incidence village with Anopheles sundaicus vector. By using the SPSS version 10.0 software, data is processed to answer the hypothesis of the research and by using the programming language of Borland Delphi 7, the model of EIS can be compiled; and also Matlab software version 7.1 is used to analyze the approximation, to formulate, that will become a parameter in EIS and for the Data Base Management System, SQL Server 2000 software is used that has been conducted in Informatics Laboratory of the S2/S3 Study Program of Electrical Engineering, Faculty of Engineering, Gadjah Mada University. The tide of sea water factor, rainfall, salinity, algae, density of An. sundaicus larva, density of An. sundaicus mosquito, and malaria case, could be used as EIS parameter. A competent model of EIS in technical programming has been developed, that could be used easily, beneficially and optimally in the effort ofprevention of malaria outbreak. To conclude, environment factor, has a relation with An. sundaicus larva density, and An. sundaicus mosquito density. Environment factor such as rainfall, salinity, and algae, also An. sundaicus larva density, and An. sundaicus mosquito density gives the multiple regression impact to 51,9% of malaria case factor. That could be used as EIS parameter are rainfall, salinity, and algae, also An. sundaicus larva density, and An.sundaicus mosquito density, and malaria case. The utilization of environmental information system, is coordinated by health centre. Keyword: environmental information system, early warning system, malaria, outbreak. Anopheles sundaicus
Various Methods of Image Mosaicing

Image Mosaicing is that the method of mixing 2 or additional pictures of identical scene into one image and generate panorama of high-resolution image. In this paper, we've represented the essential strategies used to generate panorama image. Our aim is to supply different strategies and algorithms used to generate wide angle image. This paper is principally for those who want to try to learn and implement image mosaicing.
Ontological Nature of P. A. Florensky’s Theory of Cognition

The purpose of the article is to shed light on ontological nature of P. A. Florensky’s theory of cognition. Scientific novelty of the work lies in determining reasons why philosophical and dialectical type of cognition considered by P. A. Florensky is ontological in nature. In particular, the paper argues that P. A. Florensky distinguishes this type of cognition as authentic, firstly, because it corresponds to essence of reality, understood as a living integral organism, and, secondly, because it contributes to increasing manifestation of ideal meaning in things. As a result, it is shown that P. A. Florensky’s philosophical and dialectical cognition is ontological, since it spiritualises a cognoscible thing, transforms it towards ideal reality.
Analisis Usability Situs Web Vocabulary Control Nusantara Menggunakan Metode WEBUSE

Vocabulary Control Nusantara Website is a voluntary movement that focused work on developing the index language automation system web-based, which is everyone can contribute to the development of site content. From the beginning of the movement until now Vocabulary Control Nusantara Website still in the development stage and no assessment evaluates the level of usability of the website. Therefore, usability analysis is needed to measure the level usability of the Vocabulary Control Nusantara Website and also to predict the potential benefits which will be obtained later when this movement complete. This study does a usability analysis on the homepage and backend page of the Vocabulary Control Nusantara Website by using the WEBUSE method to measure how good the level usability website. The analysis results show on the homepage page get the level usability “Good”, although there are two categories on the backend page which gets the level usability “Moderate”. Besides, there are some unsolved problems that are recommended to further testing and implementation redesign websites.
Timesias: A machine learning pipeline for predicting outcomes from time-series clinical records

The prediction of outcomes is a critical part of the clinical surveillance for hospitalized patients. Here, we present Timesias, a machine learning pipeline which predicts outcomes from real-time sequential clinical data. The strategy implemented in Timesias is the first-place solution in the crowd-sourcing DII (discover, innovate, impact) National Data Science Challenge involving more than 100,000 patients, achieving 0.85 as evaluated by AUROC (area under receiver operator characteristic curve) in predicting the early onset of sepsis status. Timesias is freely available via PyPI and GitHub. For complete details on the use and execution of this protocol, please refer to Guan et al. (2021).
Designing Machine Learning Pipeline Toolkit for AutoML Surrogate Modeling Optimization

The pipeline optimization problem in machine learning requires simultaneous optimization of pipeline structures and parameter adaptation of their elements.Having an elegant way to express these structures can help lessen the complexity in the management and analysis of their performances together with the different choices of optimization strategies.With these issues in mind, we created the AutoMLPipeline (AMLP) toolkit which facilitates the creation and evaluation of complex machine learning pipeline structures using simple expressions.We use AMLP to find optimal pipeline signatures, datamine them, and use these datamined features to speed-up learning and prediction.We formulated a two-stage pipeline optimization with surrogate modeling in AMLP which outperforms other AutoML approaches with a 4-hour time budget in less than 5 minutes of AMLP computation time.
Lessons Learned from Applying Requirements and Design Techniques in the Development of a Machine Learning System for Predicting Lawsuits Against Power Companies

Machine Learning (ML) has shown great potential for automating several aspects of everyday life and business. Experiences reports on developing ML systems, however, focus mainly on how to install, configure and maintain an ML system, but do not focus on the requirements engineering process and the design of the user interface that will present the data to the user. In this paper, we report the lessons learned from applying different requirements and design methods in one of the stages of a large development project (18 months). Its goal was to develop and evaluate a Web based application embedding an ML model that would produce data on the probability of lawsuits based on features such as: number of complaints, electrical damage to appliances and power shutdowns. At all, the design team applied the following techniques: (a) Interviews and document analysis, to identify the major reasons for filling a lawsuit; (b) Personas, to define which type of clients could file a lawsuit; (c) Scenarios, to define which interaction (conversations) would be automatically triggered by a chatbot to try to solve client problems, avoiding a lawsuit; and (d) Prototype evaluation, to define the interaction and type of data that would be available to the lawyers through a Web application. Through the lessons learned within this paper and by providing details for its replication, we intend to encourage software companies to combine requirements and design approaches for cost-effective user centered design, especially in decision support intelligent systems.
Increasing security measures in ATM Transactions using NFC

Automated Teller Machine (ATM) is a helpful method to gather the financial necessities of the clients. Notwithstanding, the utilization of charge bank card or different kinds of bank cards during bank ATM exchanges has a few issues like inclined to bank ATM skimming, attractive segments of card getting harmed, assembling and carrying cost of ATM cards, longer an ideal opportunity to validate clients and so forth The target of this examination is to think about smart mobile phone in Near-Field Communication (NFC) Card Emulation approach as an option in contrast to ATM bank cards. In NFC the space between the particular gadgets should be little (regularly under 4 cm) which makes NFC perfect for building expenses and different exchanges including delicate/private information. In the proposed framework, to validate at the ATM booth, the client needs to swipe his/her advanced mobile phone before the NFC per user. An ATM card isn't needed for verification and the framework will in any case have a more grounded protection contrasted with the framework where the ATM card was utilized. Security examination and danger demonstrating appeared in this paper features the security strength of the framework during verification.
An Embedding Strategy Using Q-Ary Convolutional Codes for Large and Small Payloads

Matrix embedding (ME) code is a commonly used steganography technique, which uses linear block codes to improve embedding efficiency. However, its main disadvantage is the inability to perform maximum likelihood decoding due to the high complexity of decoding large ME codes. As such, it is difficult to improve the embedding efficiency. The proposed q-ary embedding code can provide excellent embedding efficiency and is suitable for various embedding rates (large and small payloads). This article discusses that by using perforation technology, a convolutional code with a high embedding rate can be easily converted into a convolutional code with a low embedding rate. By keeping the embedding rate of the (2, 1) convolutional code unchanged, convolutional codes with different embedding rates can be designed through puncturing.
Searchable Encryption Technique for Cloud Storage

Cloud computing and cloud services are getting popularity because it providing low cost solution for storages and high speed data computation. Now data are transferring local storage to cloud because of its feature of large storage on low price. But cloud some time untreatable because of lack data confidentiality against to third parties. cloud servers are using some cryptographic technology for protection data at the time of downloading. However it is difficult to perform some task on encrypted data like searching of data over cloud. To solve this issue Encrypted encryption technique are use. Single user setting searchable encryption is more efficient in compare to multi-user setting. Here we proposed attribute-based searchable encryption technique for multi-owner to multi-user search. This technique keep the data safe in the cloud next to the various third party attack on data. It allow user to execute search process on encrypted data only when they have appropriate authorization. Searching is perform on token basis , tokens are generatedd by user instead of owner of data. We conform with this technique that the token confidentiality and index confidentiality are better confined in our scheme. Any illegal user & cloud servers are not capable to get some info regards search token and ciphertexts. We user constant size ciphertexts for reduced the time complexity and bandwidth of our scheme.
SMOTE-Text: A Modified SMOTE for Turkish Text Classification

One of the most common problems faced by large enterprise companies is the loss of knowhow after employee’s job replacements and quits. Creating a well-organized, indexed, connected, user friendly and sustainable digital enterprise memory can solve this problem and creates a practical knowhow transfer to new recruited personnel. In this regard, one of the problems that generated is the correct classification of documents that will be stored in the digital library. The most general meaning of text classification also known as text categorization is the process of categorizing text into labeled groups. A document can be related to one or more subjects and choosing the correct labels and classification is sometimes a challenging process. Information repository shows various distributions according to the company’s business areas. For a good and successful machine learning based text classification requires balanced datasets related with the business and previous samples. Due to the lack of documents from minor business creates imbalanced learning dataset. To overcome this problem synthetic data can be created with some methods but those methods are suitable for numerical inputs not proper for text classification. This article presents a modified version of Synthetic Minority Oversampling Technique SMOTE algorithm for text classification by integrating the Turkish dictionary for oversampling for text processing and classification.
Optimal Action Strategy approach for Desert Crossing Based on Dynamic Programming

It is a novel but challenging task that simulated desert crossing strategy for the game players under the specified conditions. This study is aimed to develop an optimal action strategy approach for desert crossing based on dynamic programming. According to the game rules, a multi-stage decision optimization model was first established to maximize the remaining funds of players within given game time. Then, a simulation-based dynamic programming algorithm was designed to solve the optimization model, and the optimal action strategy was obtained by backtracking crossing routes. Finally, two experimental case studies with different initial conditions were used to validate the model. In comparison with the benchmark exhaustive search algorithm, the proposed approach has higher performance and efficiency. The case studies confirm that the method can obtain the optimal action strategy under different game maps and initial resources.
A Psychometric Analysis and Revision of the Mathematics Teaching Efficacy Beliefs Instrument Using the Rasch Model : Focusing on Personal Teaching Efficacy

The purpose of the study was to examine the psychometric properties of the personal teaching efficacy of the Mathematics Teaching Efficacy Beliefs Instrument and revise the scale for the use of Korean elementary school teachers. Data were collected from 299 elementary teachers. A Rasch analysis was used to evaluate unidimensionality and appropriateness of category use and item difficulty levels. Moreover, person separation and reliability as well as item separation and reliability were examined using the revised scale. Results suggested that the original personal teaching efficacy scale (13 items with five categories) had several problems in its psychometric properties. Thus, we revised the scale into eight items with four categories. The follow-up analysis results showed the revised scale provided sufficient psychometric properties for measuring Korean elementary school teachers’ self-efficacy beliefs for teaching mathematics. Limitations and implications of the study were also discussed.
Augmented Reality (AR) Press Machine as the application of the latest learning media technology in the XXI Century

Abstract The objectives of this study are: (1) creating an augmented reality (AR) application in the form of a press machine; (2) testing the attractiveness of the technology developed; and (3) testing the effectiveness of AR technology in the form of press machines. The method used is research and development (R&amp;D). The final stage of product development is to carry out quasi-experiments. The phase is focused on all vocational students at Malang State University. The findings in this study include: (1) AR-shaped press machine that was developed proved to have a high level of design attractiveness and material; (2) AR shaped press machine that was developed proved effective in increasing student’s basic understanding of the competence in understanding the function of press machine components; and (3) all results in this study are expected to be the main reference in the development of AR technology for learning.
Is there a "software engineering ethics"? Comparing commercial and research software engineering

While ethical principles like fairness and honesty may be broad cultural or even universal virtues, many inputs into a professional software engineer's ethical code will be situational, depending on the nature of the engineer's employing institution and the line of business in which that organisation participates. We compare published codes of ethics for employees at Silicon Valley technology companies and at UK universities, to identify the commonalities and differences of the ethical values that guide engineering practice in each category of employer. This comparison represents the beginning of a context-dependent methodology for software engineering, in which practices are recommended based on the distinct properties of the problem domain and the solutions expected therein.
Model Pruning Techniques for Boosting the Inference Efficiency on Embedded Systems

Deep learning is one kind of machine learning schemes that leverages the multi-layer neural network to extract the features from the input data so as to make accurate estimation on new data. Along with the rapid growth of deep neural networks, the model is becoming more and more accuracy, but at the same time the parameter size and computation intensity also become a huge burden for inference, especially for embedded devices like cellphones robotics and autonomous vehicles. In order to solve this contradiction, experts propose distinguished pruning technologies to lighten the volume of the model and alleviate the storage imposition. To summarize the technologies, we compare them in different aspects clearly. We firstly describe the differences of state-of-the-art pruning schemes, and then give the direct comparison in terms of the accuracy and parameter size. Finally, we discuss the reasons of different performance results in order to suggest the software or hardware designers the best option when facing their specific use cases.
Visual Analysis of Goal-Leading Phases in Soccer

This work focuses on the use of a specific type of visualization to analyze soccer matches and highlight individual players’ goal contributions. An analytic approach in team sports is nowadays considered crucial by both practitioners and other interested parties such as fans or betters. In soccer, the analysis of sequences of passes and shoots can help the analysts understanding some aspects of the performance of players and teams. We show how, through a compact representation of n-ary temporal relationship, users can get a comprehensive view of the evolution of the passes leading to a goal in several matches. The dataset considered in this work contains data from the first 26 weeks of the season 2019-2020 of the Italian major soccer league.
Research on landscape design of community pension under the background of aging

As a country with a large population in the world, China is currently aging. This paper starts from the basic needs of the elderly's care environment, and takes the elderly's psychological needs, physiological needs and behavioral needs as the starting point, and explores the ecological design of community landscape under the background of aging to meet the many needs of today's aging population.
Private Genetic Genealogy Search

Genetic genealogy search is a powerful tool for identifying individuals within a wider population by using their genetic information in combination with a genealogical network. The current practice relies on searching within a pre-constructed genetic database, and as such exposes those in the database to substantial privacy risks. Motivated by these privacy concerns, we propose a framework of genealogy search that takes into account the amount of privacy exposure. Instead of collecting a large amount of genetic data beforehand, we advocate for a new search paradigm whereby genetic data are accessed sequentially. Our results show that carefully designed sequential search procedures can significantly outperform existing static approaches in terms of the trade-off between cost and privacy exposure. We further characterize the optimal trade-off and propose a family of search strategies that provably achieve it over path- and grid-like genealogy networks. Finally, we validate our findings via numerical experiments on both real and synthetic genealogical networks and discuss the policy implications of our results.
Comparative study of presumptive and confirmatory tests for detection of blood on serial dilutions and washed stains

Background and aims: Detection of blood from blood stains is the first crucial step for forensic analysis, such as DNA profiling.After committing the crime, the criminal tries to destroy evidence such as blood stains by washing their clothes or other circumstances found at the crime scene make the blood or blood stains diluted due to washing by water or detergent.This study aimed to identify the most sensitive presumptive test among phenolphthalein, tetramethylbenzidine (TMB), benzidine, leuco-malachite green (LMG), and luminol for the washed and serially diluted blood and bloodstains and confirmatory test of blood among Takayama, Teichmann, and Wagenaar.Materials and methods: In this study, serially diluted blood, stains of the serially diluted blood, and blood-stained clothes were prepared and subjected to different kinds of washings.Blood was detected using reagents of phenolphthalein, TMB, benzidine, LMG, and luminol with variable protocols reported in various literatures.The samples were further tested for the confirmatory tests of blood using Takayama, Teichmann, and Wagenaar tests.Results: It is observed that in presumptive testing of serially diluted bloodstains, luminol shows positive results in all (1:10 to 1:100,00,000) followed by TMB (1:10000).TMB in acetate buffer solution works better for liquid blood; however, solution of TMB in glacial acetic acid works better for stains.LMG solution with zinc has higher sensitivity as compared to a solution without zinc.Conclusion: Luminol is the most sensitive presumptive test for detecting blood on washed and diluted bloodstains, and sensitivity decreases with an increase in wash cycles.Among confirmatory tests, the Takayama test is more promising than Teichmann and Wagenaar test.