Reviewerly/exHarmony huggingface dataset:
Decision Support System To Determine The Best Tax Payer Nominee At Regional Government Using Saw &amp; Ahp

Tax, as generally known, are important aspect for Indonesia country sustainability. Taxpayer compliance is a conditionwhere the taxpayer has completed all of their tax obligations and get their tax rights. These compliance are identifiedwhen they send back SPT and their compliance of paying tax debts. Decision support system is a part of computerizedinformation system. AHP-SAW is one kind of a method which developed by combining weight and comparisonbetween criteria to determine the best alternative. Using the method, this research will help the tax office to choosewhich hotel and restaurant are eligible to get the best criteria in tax compliance. Based on the test result, for hotel,accuracy obtained is 78.6% on average, where Hotel Wijaya 1 always get the first rank. For restaurant, the accuracyobtained is 84.7%, where RM Ramio always get the first rank. Business entity criteria has big impact on rankingprocess where in a 100% accuracy test, this criteria got bigger value than other criteria.
COVID-19 Vaccination and Data Protection Issues: A European Comparative Study With Focuses on France, Germany, Belgium, and Switzerland

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL Copy DOI
Increasing Irrigation Efficiency through Maintenance of Irrigation Network Based on Dynamic Simulation

Given the increasing demand for water, it is necessary to make an effort to anticipate water scarcity through increasing efficiency in an irrigation area. Increasing efficiency requires an increase in the contribution of farmers to finance the repair of irrigation canals. The purpose of this study is to formulate a financing scheme for maintenance of irrigation networks by the state and farmer participation (contribution). Research was conducted at the Cihea Irrigation Area (Cianjur Regency). The method used is system dynamics modeling by observing the parameters studied, including; asset damage, productivity, farmer contributions, public works budget and irrigation efficiency. The results of the analysis with dynamic simulations show that the best scenario to reduce damage to Cihea Irrigation assets is scenario 2 because it reduces the damage by 10.29% and increases the irrigation maintenance index by 0.05 within 10 years. Thus, it is necessary suggest to the government and farmers to increase the contribution and budget for the improvement of the Cihea Irrigation. Keywords: Asset Damage, Efficiency, Farmer's Contribution, Government Budget, Maintenance
Development and Implementation of Search Engine Optimization Algorithm using Angular Framework

The paper deals with the development of search engine optimization algorithm and its integration into Internet browsers. In particular, the paper presents an effective search engine optimization algorithm and the algorithm is implemented using a client-side programming angular framework. The research algorithm and its implementation make the search process efficient and flexible for the user, which is reflected in the fact that frequently searched phrases will be automatically suggested.
Mediation Model of Digital Technology Factors Affecting Health Care Service Performance

Healthcare technologies have become a crucial component of healthcare providers' daily operations. Hence, healthcare innovation technologies are being promoted worldwide. Healthcare service technologies are constantly improving necessitates ongoing research to show how these technologies affect healthcare services. Hence, current study investigating the state of innovative digital healthcare service practises in the UAE. It examining the effect of innovative technology on healthcare service performance in the UAE and modelling mediating role of organisational learning capacity in the relationship between innovative technology and healthcare service performance. A structural equation model was developed in SmartPLS software using the data collected of the questionnaire. The model showed that the factors system development, digital services, process integration, and IT base innovations have strong relationship effect to the health care performance. Also, the organisational learning capacity has strong mediation effect on the health services relationship. This research has contributed to current state of literature regarding digital service innovations related to health service performance in the UAE. The results emphasized a critical need for practitioners for promoting developments in digital services impacted the performance of health services.
IMPLEMENTASI APLIKASI ANGKET PENILAIAN TINGKAT KEPUASAN LAYANAN PADA AMIK MAHAPUTRA BERBASIS ANDROID

Improving the quality of service is something that must be prioritized for the achievement and success of AMIK Mahaputra Riau in carrying out the teaching and learning process. However, often limited resources become one of the inhibiting factors in achieving service satisfaction. The development of information technology is one of the alternative solutions that can be utilized in an effort to improve services to stakeholders. AMIK Mahaputra Riau is currently still using manual questionnaires in assessing service satisfaction, often the implementation requires quite a lot of time and effort so that it is less effective and efficient in getting optimal results. Therefore it is necessary to develop an assessment questionnaire application so that it can facilitate the recording, processing and reporting of data. The weighted average method is an alternative solution in an effort to accumulate questionnaire data so that it is expected to obtain optimal results. Applying the average order method in the Android-based satisfaction questionnaire application is the right solution in answering the problem of measuring the level of service satisfaction at AMIK Mahaputra Riau. This was answered in system testing with Blackbox which gave the desired results. So that it can be concluded that the application of the android-based service satisfaction questionnaire application system at AMIK Mahaputra Riau is able to increase efficiency and effectiveness in the process of implementing the satisfaction questionnaire.
MONOCULAR DEPTH ESTIMATION OF GOOGLE EARTH IMAGES USING CONVOLUTIONAL NEURAL NETWORKS

Abstract. Depth estimation from images is an important task using scene understanding and reconstruction. Recently, encoder-decoder type fully convolutional architectures have gained great success in the area of depth estimation. Depth extraction from aerial and satellite images is one of the important topics in photogrammetry and remote sensing. This is usually done using image pairs, or more than two images. Solving this problem using a single image is still a challenging problem and has not been completely solved. Several convolutional neural networks have been proposed to extract depth from a single image, which act as encoders and decoders. In this article, we use one of these networks, which has performed well for depth estimation, in order to extract height from aerial and satellite images. Our main goal is to investigate the performance of Google Earth satellite data in order to produce a digital elevation model. At first, we extracted the digital model of the target area using ISPRS benchmark data, then we did the same thing using Google Earth satellite images. The paper presents a convolutional neural network for computing a high-resolution depth map given a single RGB Google Earth image. The results show the proper performance of Google Earth satellite images for height extraction. We achieved values of 2.07 m and 0.36 m for the RMS and REL metrics, respectively, which are very comparable and acceptable to the values of 2.04 m and 0.39 m obtained from the ISPRS benchmark images.
The Creation of Chinese Educational Resources for Sixth Grade Students

The majority of the Chinese teaching resources for sixth graders are textbooks that originate in China. These textbooks are written at a level that is too advanced for sixth graders. The purpose of this project is to generate teaching materials in Chinese for students in the sixth grade. The research is conducted using a pretest and posttest method, the sample consists of students in the sixth grade, and the research instruments consist of Chinese teaching materials, Chinese exercises, academic achievement exams, and a learning satisfaction questionnaire. The findings revealed that the average score on the pre-school achievement exam for the 44 kids who participated in the research was 45.34 percent, but the post test score was 82.39 percent. The standard deviation of the scores on the pre-test was 3.08 percent, whereas on the post-test it was 1.62 percent. This paper indicated that students had significant differences in their pre-test and post-school accomplishment at the level of 0.05, and postschool achievement scores were greater than pre-test achievement scores. In addition, students were highly happy with the Chinese language teaching materials.
Ciliwung river normalization analysisusing HEC-RAS application (TB. Simatupang Bridge to Bidara Cina)

&lt;p&gt;Ciliwung River area which starts from TB. Simatupang Bridge to Bidara Cina is one of the areas that experienced severe flooding.This is caused by changes or conversion of land functions which were originally a water catchment area into settlements. Buildings that stand along the river body makes the current cross section of the Ciliwung River unable to function optimally in accommodating flood discharges. In addition, there is no public awareness in protecting the environment, it can be seen from the large piles of garbage on the riverside of the Ciliwung River.One of the efforts made by the government in flood control is river normalization, but in practice the normalization of the Ciliwung River can be said to be not running optimally. The purpose of this research is : the Author want to know how big the capacity of Ciliwung River existing cross section (starting from TB Simatupang Bridge to Bidara Cina) using Hec-Ras software application to modeling the river’s cross section existing and so does recording and mapping ofpotentialflood locations&lt;em&gt;.&lt;/em&gt;&lt;em&gt; &lt;/em&gt;Based on the hydrology calculation, known that flood discharge plan Q&lt;sub&gt;25&lt;/sub&gt;is 404.3m&lt;sup&gt;3&lt;/sup&gt;/s, while the hydraulic Q is only 79.03 m3/s, the Q total is 483,38 m&lt;sup&gt;3&lt;/sup&gt;/s. The results of modeling using the &lt;em&gt;Hec-Ras&lt;/em&gt; river cross section existingcannot accommodate the planned flood discharge so that river normalization efforts are needed. Recording and mapping flood locations are useful to get the effectivity of River’s normalization according to flood controlling at Ciliwung River (specific at TB Simatupang Bridge to Bidara Cina).&lt;/p&gt;
Systematical Analysis and Pathological Classification of Breast Cancer from Mammographic Images with Using Specific Machine Learning Methods

For years, breast cancer has been a serious problem and malignant tumor case primarily causes death of women all around the world. In this paper, a computer based breast tumor analysis and pathological case classification system has been achieved and some novelties are included to the image processing methods, especially in segmentation and base frequency distribution acquisition of the processed image and classification part. First, the possible noises and artifacts are eliminated by using common filtering. Second, the filtered images are segmented with integrating gray level Image Processing methods. Then, these images (ROIs) are converted to the base frequency distribution images with using Fast Fourier Transform (FFT) and Lab&amp;HSV color spaces. The most important key for these images is frequency distribution can be obtained with specific color tones and totally 100 images (50 benign-50 malignant) are accumulated to fed the two different Machine Learning models in literature such as Probabilistic Neural Network as Learning Vector Quantization (LVQ) and Support Vector Regression (SVR) for classification of Benign and Malignant cases without the need for additional medical data. Then the performance of the proposed system is analyzed with 30 different test images (15 benign-15 malignant) according to the metrics like accuracy, sensitivity, specificity, precision, F-score and area under the ROC curve (AUC score). The experimental results on the open access mammogram image set show that discriminating between Benign and Malignant cases can be achieved with an important success rate as 91.38% with LVQ and %.92 with SVR.
Introducing fastpos: A Fast R Implementation to Find the Critical Point of Stability for a Correlation

The R package fastpos provides a fast algorithm to estimate the required sample size for a Pearson correlation to *stabilize* [@schonbrodt2013]. The stability approach is an innovative alternative to other means of sample size planning, such as power analysis. Although the approach is young, it has already attracted much interest in the research community. Still, to date, there exists no easy way to use the stability approach because there is no analytical solution and a simulation approach is computationally expensive with a quadratic time complexity. The presented package overcomes this limitation by speeding up the calculation of correlations and achieving linear time complexity. For typical parameters, the theoretical speedup is around a factor of 250, which was empirically confirmed in a comparison with the original implementation `corEvol`. This speedup allows practitioners to use the stability approach to plan for sample size and theoreticians to further explore the method.
THE THEORY OF SEALING PROPHECY IN CONTEMPORARY SPEECH SCIENCE

The Islamic nation agreed to collect its communities and dissolve them, that its prophet Muhammad Salamah Allah upon him and a machine, The ring of the prophets, and that its sharia is the conclusion of the canons, and its book ring and newspapers He is the last divine Ambassador.He was committed to the door of the letter and prophecy.And the message of heaven to Earth concluded with him, that her prophet's religion God's eternal religion, and that his book, God's immortal book, God ended every piece of legislation, complementing his religion and his book with the heavenly laws that are the message of heaven to Earth.And the prophets with all the sub-differences were one message campaign and following one school, This school was progressively presented according to the requirements of the capacities of the human society to the extent that humanity reached so that the school offered its full university, The prophecy reached the end, by which the school was presented and fully reached Mohammed bin Abdullah and the last heavenly book is The Quran, as the Holy Quran said (And when the prophecies were renewed in the past, the prophets were Yatton respectively, and if not all of them had the law and the law and the predominance was to implement the existing sharia and this ended after the seal of the prophets The Holy Quran is a miracle of the seal of the immortal prophets.Former prophets Kabrahim, Moses and Issa were their books and their helplessness in something other than their heavenly books.Turning the land stick into a snake, the miracle of the prophet's ring is a book that was a book simultaneously and the proof of his message was a miracle of conclusion unlike the other helpless, In contemporary times, many theories have been raised regarding the seals of Prophet Muhammad Salwatullah on what is meant by the conclusion, its causes and the dimensions resulting therefrom.Several theories have been put forward by the Islamic intellectual
Задачи логики смысла

Short, middle and long-term objectives for the logic of sense are outlined. The short-term objective is, firstly, to sketch the logic-and-meaning map of the four big cultures of hu­mankind (European, Arab-Muslim, South Asian and Far Eastern) producing the first de­scription of the logics of sense manifold. This description will outline that variant of (1) power of judgment, (2) basic (indefinable) categories of the theoretical (philosophi­cal included) discourse and (3) basic logical regulative principles that underlies that spe­cific big culture and defines its “morphology” (Spengler) and all the stages of its epis­temic chain (the most important of them being perception, speech and thought). Sec­ondly, we need to sketch the logic-and-meaning map for the individual consciousness which is basically open to all possible kinds of the logic of sense, elaborating on the line of psychological studies developed by V.K. Solondaev. Thirdly, it is especially promising to discover the neural network parallels for the logic-and-meaning regularities of human consciousness activity and to map them. The three maps superposition is likely to suggest new interesting conclusions. The middle term objective is to develop the cognitive history of philosophy as an antipode to the analytic history of philosophy. The cognitive history of philosophy will study the development of philosophy in the big cultures and their sub­cultures as defined by the basic toolkit provided by the concrete variant of the logic of sense (that is, the variant of the power of judgment and of the set of basic categories and logical principles). The cognitive history of philosophy approaches the philosophical tra­ditions of every big culture as, firstly, independent and irreducible to the philosophical discourse in any other big culture, and, secondly, as embedded in the system of that big culture and organically belonging to it. The long term objective is to make logic of sense and the cognitive history of philosophy converge to arrive at the cognitive phi­losophy which will discover the freedom of sense positing by virtue of mastering its regularities in full. The ‘cognitive philosophy’ is another name for the logic of sense in its completeness.
RSS, Atom, JSON Feed

As I discussed in a recent post, RSS is an essential building block for the upcoming Rogue Scholar Scholarly Blog Archive. RSS makes it easy to import blog posts (both metadata and content) automatically and is supported by all blogging platforms. This kind of automation is critical to keep the costs of running the Rogue Scholar low, allowing it to scale to cover a substantial number of science blog posts, and hopefully becoming an important Open Science resource.But there are also challenges...
Effective Weighted k-Nearest Neighbors for Dynamic Data Streams

Many real-world applications involve classification from evolving data streams. However, learning in such environment requires algorithms able to learn and predict from potentially unbounded data that are constantly changing. For this to happen, stream algorithms should restrict the storage to a part of – and/or synopsis information from – the stream using efficient and accurate manners and strategies, such as window models and summarization techniques (e.g., sampling, sketching, dimensionality reduction). In this work, we focus on the k-Nearest Neighbors (kNN) where most of the existing approaches for data streams consider that instances have the same weight from the start to the finish of the processing task.In a streaming data scenario, it is often the case that the most recent elements from the data stream are the more relevant ones. Taking into account that the most recent instances are more relevant, we propose a novel kNN approach that stores instances in a sliding window and weighs them according to their arrival time (i.e position on the window) using an adjusted weight function. The empirical results on comprehensive real and synthetic datasets indicate the effectiveness and efficiency of our proposed approach in comparison with state-of-the-art algorithms.
The Rise of Creative Roboticists

The entertainment industry has co-opted industrial robots for filming special effects sequences. Now, lessons learned here are filtering back into industry.
Building a Better Reality

Augmented reality is a relatively new technology, but the role it has played in meeting the UK’s Ventilator Challenge has proved its value.
Could Blockchain Beat the Pirates?

Chris Johnson, managing director at specialist bearing supplier SMB Bearings, investigates three benefits of blockchain to increase traceability in the bearing supply chain.
<b>AR FINDS</b> ‘KILLER APPS’

The pandemic has accelerated the adoption of Augemented Reality, but so has the availability of a multitude of applications.
Evolutionary Algorithm to Auto-tuning Hyperbolic Tangent Sliding-Mode Controllers

In recent years, control engineers has started to explore new control, optimization and tune paradigms. And they have found that Evolutionary Algorithms (EA) are good alternatives for traditional methods. Thanks to the power to explore high search-spaces with multicombinational problems and a lot of potential solutions. For this reason, in this work an Evolitive Algorithm is planned as a heuristic auto tunning algorithm for Sliding-Mode Controllers. Using an approach by Hyperbolic Tangents. In order to obtain easily implementable control laws with a desirable performance to linear and non-linear systems.
A IMPORTÂNCIA DA INOVAÇÃO TECNOLÓGICA PARA A TRANSFORMAÇÃO DIGITAL E O PLENO EXERCÍCIO DA CIDADANIA

In an increasingly digital world and connected in information technology, bringing a high-speed internet for all is a matter of full citizenship in the face of the benefits inherent in connectivity for all, especially now when the pandemic has made clear the need for home office work and online classes.High-speed and quality Internet in public schools, hospitals and public clinics, throughout the public security sector and in the judiciary guarantees the full exercise of citizenship because it gives citi-REVISTA ESMAT
Pre-Provisioned Security Solution

MICROCHIP'S TRUST PLATFORM LOOKS TO SIMPLIFY HARDWARE-BASED IOT SECURITY.
Empowering Soc Design Teams

ARM UNVEILS FLEXIBLE ACCESS GIVING CHIP DESIGNERS THE FREEDOM TO EXPERIMENT AND TEST BEFORE THEY INVEST.
A Comprehensive Study on Monument Recognition Techniques and its Integration with Explainable AI

The wide diversity in monument structures are crucial identifiers for the recognition of monuments and is a difficult task in the image classification area. The importance of the monument recognition system may be attributed to the fact that it both serves as a symbol of past great accomplishments in the arts and sciences and serves as the foundation for future socioeconomic development in the form of tourism for the surrounding area. Existing technologies used for monument recognition include Deep Learning algorithms like VGGNET, ResNet etc. Satellite image processing for remote sensing is the latest trend and its processing is done using machine Leaning and deep learning models such as Convolutional Neural Networks (CNN), it's variations and other deep learning architectures like Inceptors, MobileNet, ResNet, AlexNet etc. These techniques can be altered to detect monuments from high resolution satellite images and Explainable AI framework can be applied to the developed model to interpret the characteristics of monuments based on which classification is made.
Healthcare Blockchain Quantum Computing Threats and Opportunities

Highlights of this panel discussion include:&#x0D; &#x0D; The Imminent Quantum Computing threat&#x0D; NIST Post-Quantum Solutions&#x0D; How Quantum Technologies revolutionize Blockchain Technology and Healthcare&#x0D;