Reviewerly/exHarmony huggingface dataset:
On the ubiquity of the Bayesian paradigm in statistical machine learning and data science

This paper seeks to provide a thorough account of the ubiquitous nature of the Bayesian paradigm in modern statistics, data science and artificial intelligence.Once maligned, on the one hand by those who philosophically hated the very idea of subjective probability used in prior specification, and on the other hand because of the intractability of the computations needed for Bayesian estimation and inference, the Bayesian school of thought now permeates and pervades virtually all areas of science, applied science, engineering, social science and even liberal arts, often in unsuspected ways.Thanks in part to the availability of powerful computing resources, but also to the literally unavoidable inherent presence of the quintessential building blocks of the Bayesian paradigm in all walks of life, the Bayesian way of handling statistical learning, estimation and inference is not only mainstream but also becoming the most central approach to learning from the data.This paper explores some of the most relevant elements to help to the reader appreciate the pervading power and presence of the Bayesian paradigm in statistics, artificial intelligence and data science, with an emphasis on how the Gospel according to Reverend Thomas Bayes has turned out to be the truly good news, and in some cases the amazing saving grace, for all who seek to learn statistically from the data.
High dynamic range and real-time 3D measurement based on a multi-view system

Fringe projection profilometry is a mature 3D measurement technique, however it is still difficult to measure high dynamic range objects in real-time. In this paper, we present a method of using digital micro-mirror devices to dynamic range enhancement of fringe projection profilometry. After applying this method, we can obtain two fringe images with different exposures in one projection period. These two fringes will be combined to solve the high dynamic range problem. Furthermore, we also build a multi-view system to realize real-time measuring stably because the multi-view system can retrieve the absolute phase without projecting additional fringe patterns. Experiments demonstrate that the proposed method can realize real-time three-dimensional measurement at 28 frames per second and the dynamic range of fringe projection profilometry system is increased by 2 times.
Bilingual Dictionary for Sanskrit—Gujarati MT Implementation

Working with cross-linguistic environments where lexico-semantic features are vital, the use of digitized bilingual dictionary cannot be overlooked. Here, Sanskrit-Gujarati bilingual dictionary design, contents and its applicability is discussed. The Sanskrit-Gujarati lemmas are correspondingly mapped so as to facilitate use-cases like machine translation, cross-lingual information retrieval, stemming, lemmatization, and other related task. The dictionary design and implementation is through Comma Separated Verbose (CSV) format and Relational Database Management System (RDBMS), but also convertible to formatted tag-based form for better portability. It is usual to have bilingual dictionary for scarce resourced languages prepared manually as opposed to automated and aligned bilingual corpora method for several Natural Language Processing (NLP) related task.
Tracking Control for Quad-Rotor Using Velocity Field and Obstacle Avoidance Based on Hydrodynamics

In this work, the problem of navigation control of a quad-rotor, which includes path planning (to a desired trajectory with obstacle avoidance) and tracking control, is addressed. Path planning is achieved by means of the velocity field technique, since this method generates smooth trajectories that are suitable for this kind of vehicles. We propose a recursive method for the composition of the total velocity reference. In order to achieve a good tracking of the generated references, a saturated controller is used, namely, nested saturation. It is demonstrated that the velocity reference can be tracked with a reduction in the order of the controller, from four to three saturators, which simplifies the implementation. Numerical results show that a correct tracking could be guaranteed.
Analisa Algoritma Apriori Pada Pola Peminjaman Buku di Perpustakaan ITB Ahmad Dahlan

The library is a source of information and a place of learning. Each book lending information is stored by the library so as to produce large data lending books. Big data if not utilized will create problems in the future. In this study, researchers will utilize a priori algorithms and Tanagra software to group library book borrowing data at Ahmad Dahlan ITB based on trends that occur together in library visit activities. In the process of borrowing books, of course the raw data will be processed by dividing it into different pieces of data. Among the lending data tables processed are general lending tables, 2-itemset candidate tables, lending tabular tables, support value tables, confidence value tables. From the results of this study it can be seen what books are often borrowed together with a minimum support of 5% and 10% confidence one of which is Taxation and Taxation Accounting with a minimum support of 7.30% confidence 62.79%. And can be used as a reference for ITB Ahmad Dahlan in the procurement and placement of library book layout.
Pengujian Black Box pada Sistem Aplikasi Informasi Data Kinerja Menggunakan Teknik Equivalence Partitions

Software that contains defects (errors) can cause harm. Losses caused can affect all stakeholders. Losses can take the form of financial, time, and others. So before the software is implemented it needs to be tested. Testing on an application aims to check whether a program is running properly or not. In testing this software will use Blackbox Testing. Black Box Testing Method consists of several techniques, including Equivalence Partitions, Boundary Value Analysis, Sample Testing, and so on. Among the many testing techniques, in this study the testing technique was chosen using Equivalence Partitions. Equivalence Partitions technique is a test based on data input on each form in the performance data information application system, each menu input will be tested and grouped according to function whether it is valid or invalid. Testing is done on 4 forms that will be filled with data form added jobdesk, form added work targets, form edit work targets, form approve work targets, and employee performance while in the company. The test results show that there are still many shortcomings when validating data to be entered, so that it can cause data stored in the database to be incompatible with the expected data. The results of this test can be used as input to improve the application of performance data for the future.
Efektivitas Aplikasi Mobile Learning Role Play Games (RPG) Maker MV untuk Meningkatkan Kemampuan Berpikir Kritis

Student learning activities that are less conducive, passive in asking questions and answering questions from problems raised by teachers, difficult to express ideas or ideas of problem solving and the learning process provided, and have not been oriented to develop students' critical thinking skills.The purpose of this study is to determine the feasibility, find out the increase in students' critical thinking skills, and to find out students' responses to the application of RPG maker MV based mobile learning applications in the learning ecosystem. The research method used is Quasi-Experimental, the design used in this study is Quasi-Experimental Design with Randomized Control-Group Pretest-Postest. The data obtained in this study consisted of qualitative data, namely the results of observations of student activities during learning and student questionnaire responses to the application of mobile learning applications based on RPG maker MV, and quantitative data namely the results of students' critical thinking abilities. The results showed (1) the implementation of the RPG maker MV based mobile learning application has moderate criteria, (2) the application of the RPG maker MV based mobile learning application can improve students 'critical thinking skills, (3) students' responses to the use of RPG maker based learning mobile applications MV in ecosystem learning has very good criteria.
Intimate partner violence: A novel warning system in which the victims' environment alerts to the danger

Intimate Partner Violence (IPV) has become a problem of a great magnitude as it is a leading cause of death for women according to the World Health Organization. This paper presents a novel Early Warning System (EWS) for locating and protecting potential victims of IPV in which the victims' environment plays a central role. Specifically, based on Markov random fields, our EWS measures the danger through the perception that the victims' surroundings have. This new standpoint is of particular relevance since most of the IPV victims do not have a clear perception of the approaching danger.The EWS has been designed without geographical constrains to be appropriate for use in every country of the world (universal EWS). Importantly, it may be rewritten into computational terms thereby providing a real tool for police investigations. Connections with text mining and sentiment analysis may provide additional devices based on this model.
VCC-DASH: A Video Content Complexity-Aware DASH Bitrate Adaptation Strategy

Traditional DASH (dynamic adaptation streaming over HTTP(i.e., HyperText Transfer Protocol)) bitrate strategy cannot differentiate segments with different complexities of video content, resulting in the user’s QoE (quality of experience) of segments with high content complexity as worse than that with low content complexity. In case of this, this paper firstly studies video coding and puts forward the definition of video content complexity. Then the effects of content complexity on user’s QoE is analyzed and the QoE utility function of the segment is formulated based on its MOS (mean opinion score, related to the content complexity and bitrate) and bitrate switching between consecutive segments. Last, in order to maximize user’s QoE, this paper proposes VCC-DASH (video content complexity-aware DASH bitrate adaptation strategy) under the constraints of the network bandwidth and the buffer occupancy. In simulations, we compare VCC-DASH with the classical bitrate adaptation strategy proposed by Liu et al. (LIU’s strategy, for short). The simulation results show that the two strategies have similar performances in bitrate switching numbers, playback interruption times, and buffer lengths. In addition, it is more important for simulation results to reveal that VCC-DASH’s average bitrate is much higher than that of LIU’s strategy, which means that VCC-DASH can make fuller use of the network bandwidth than LIU’s strategy does. Moreover, the MOS distribution of the VCC-DASH is more concentrated on the better scores “4~5”, which profit from its content complexity-aware adaptation to allocate more bandwidth resources to high-complexity segments.
Interpretable Complex-Valued Neural Networks for Privacy Protection

Previous studies have found that an adversary attacker can often infer unintended input information from intermediate-layer features. We study the possibility of preventing such adversarial inference, yet without too much accuracy degradation. We propose a generic method to revise the neural network to boost the challenge of inferring input attributes from features, while maintaining highly accurate outputs. In particular, the method transforms real-valued features into complex-valued ones, in which the input is hidden in a randomized phase of the transformed features. The knowledge of the phase acts like a key, with which any party can easily recover the output from the processing result, but without which the party can neither recover the output nor distinguish the original input. Preliminary experiments on various datasets and network structures have shown that our method significantly diminishes the adversary's ability in inferring about the input while largely preserves the resulting accuracy.
Sistem Informasi Pengolahan Data Kependudukan Pada Kantor Desa Sampean Berbasis Android

The population data is the data have to be in record in any office the villages around. With the citizens data , the village office can do monitoring inhabitant of which is found in the neighborhood. So far, the village office sampean kecamatan sungai kanan kabupaten labuhan batu selatan, north sumatra still use application desktop in doing processing the population data that is use application microsoft excel .In such a manner as there are still several problems and the obstacles, especially time and energy issued when their distribution data population in parties in need by the village office sampean. The purpose of he did this research is to design and construct information system the population data processing based android. With the information systems that in designed by the writer, is expected to help parties the village office sampean in doing processing the population data and do distribution the population data easily And rapidly through a smartphone android. Information system built by using application kodular and a database airtable
Fake News Detection by Image Montage Recognition

Fake news have been a problem for multiple years now and in addition to this “fake images” that accompany them are becoming increasingly a problem too. The aim of such fake images is to back up the fake message itself and make it appear authentic. For this purpose, more and more images such as photo-montages are used, which have been spliced from several images. This can be used to defame people by putting them in unfavorable situations or the other way around as propaganda by making them appear more important. In addition, montages may have been altered with noise and other manipulations to make an automatic recognition more difficult. In order to take action against such montages and still detect them automated, a concept based on feature detection is developed. Furthermore, an indexing of the features is carried out by means of a nearest neighbor algorithm in order to be able to quickly compare a high number of images. Afterwards, images suspected to be a montage are reviewed by a verifier. This concept is implemented and evaluated with two feature detectors. Even montages that have been manipulated with different methods are identified as such in an average of 100 milliseconds with a probability of mostly over 90%.
DEIXIS IN THE CLEVER SERVANT STORY

Pragmatics is a study of contextual meaning. Finding out the context and meaning of a conversation can be learned through deixis. This research analyzes types of deixis such as personal, time and place deixis. This research discusing about recount text entitled "The Clever Servant" as the instrument of this study. This research applied a descriptive qualitative method. The steps to analyze data are searching the story, reading the story, finding the data based on three kinds of deixis above. In this research, there was 27 deixis found in the text. The most common type of deixis is person deixis with 19 words. Whereas place deixis has 5 words and time deixis has 3 words. In this study, the researcher find out that personal deixis is the dominant type in the text. Keywords: Deixis, Pragmatics, The Clever Servant
IMPLEMENTASI CUSTOMER RELATIONSHIP MANAGEMENT (CRM) PADA KLINIK VALERIE BEAUTY

Valerie Beauty Clinic is a beauty care services company. The problem that arises is that even though the customer is still recorded in the recipe book, Valerie Beauty Clinic still has difficulty in providing information, products, schedule changes, changes in schedule services, events, or the latest things to customers. This problem occurs because all customers remain systemically unregulated. Another problem that arises is that all beauty products have not been recorded in a computerized database, this is what causes difficulties in conducting product data searches. Furthermore, customers also cannot do clients or suggestions and also good dissatisfaction because of the unavailability of media. If this is allowed to continue, customers can just go to another salon. The purpose of creating a website at the Valerie Beauty Clinic is to provide satisfying services to customers through a CRM (Customer Relationship Management) strategy by looking at existing problems. The methodology that will be used is conducting interviews, observations and literatures. With the existence of a website-based system with the implementation of CRM, it can facilitate customers and clinics in providing information, products, changes in schedule services, events, or the latest things to customers, computerize all products and provide clients with complaints or suggestions online. Your data is stored in accordance with our privacy statement.
Random number generation using magnetic domain images of magneto-optical materials

Random numbers were generated from magnetic domain patterns of a magneto-optical (MO) material. A hundred thousand chaotic magnetic domain images were photographed by a transparent polarization microscope. Post data processing (binarization, frequency adjustment, exclusive-OR, and offset data reduction) was used to obtain a random number from the images. The generated random numbers passed the statistical test (NIST SP-800-22). This result could contribute to realizing a relatively simple and fast random number generator using MO materials.
MODEL RAD DALAM PERANCANGAN FRONT END APLIKASI PAYMENT POINT ONLINE BANK (PPOB) BERBASIS ANDROID

The conventional purchase of credit by sending sms to the agent server is often has problem. The error was caused by different format of SMS for each server. This error has an impact on the high cost of using SMS. Another problem when the customer wants to check the electricity bill, the website provided by PLN is less attractive or have to come directly to the PLN payment counter. With these problems, an Android-based application was developed to provide convenience in purchasing credit without worrying about writing format errors and checking until payment of various types of bills becomes more efficient. Bill payments become more practical in one unit, so there is no need to go to different payment counters each month and not get stuck in a long queue that wash time. Development model of this PPOB application is RAD which consists of business modeling, data modeling, process modeling, application development and testing.
An Image Super-resolution Reconstruction Method by Using of Deep Learning

In order to better apply clothing style design in clothing industries, this paper presents an image super-resolution reconstruction method based on deep learning. In this proposed method, we add a sub-pixel convolutional layer and a replacement concatenated convolution kernel, which makes a more efficient super-resolution. Therefore, a convolutional neural network consisting of a suitable depth is designed to ensure the quality of the image reconstruction, and cascaded small convolution kernels is applied to improve the running speed. The experimental results show that compared with the Efficent Sub-Pixel Convolutional Neural Network (ESPCN) algorithm, the reconstruction quality of the high-resolution image reconstructed PSNR by the algorithm is improved by 2.57dB and the reconstruction speed by 68 milliseconds.
Health Insurance Anomaly Detection Based on Dynamic Heterogeneous Information Network

With the development of health insurance, the consequent problem of health insurance fraud has become increasingly serious. Outlier detection is a common method for health insurance anomaly detection. Researchers use some prior knowledge to assume patterns and indicators of interest. However, fraud pattern is concealed and changeable. The method of mining anomalies from fixed patterns is difficult to meet the current needs. In order to overcome this limitation, this paper combines the rich expression ability of heterogeneous information networks to model the complex relationships between entities, and establish a health insurance business representation model. The paper explores all possible business patterns, interrelated business portfolio patterns and related indicators in the field of health insurance. Considering the dynamic nature of a network, anomaly mining is carried out from both horizontal and vertical perspectives. Among them, the horizontal comparison adopts a fixed time period. The vertical comparison dynamically adjusts the time period according to the frequency of occurrence of the health insurance pattern instance, and then performs indicator calculation and outlier detection. Finally, the experimental results on the real data set show that our approach can narrow the scope of professional review and find more records of possible fraud than traditional methods.
3D Face Model Super-Resolution Based on Radial Curve Estimation

Consumer depth cameras bring about cheap and fast acquisition of 3D models. However, the precision and resolution of these consumer depth cameras cannot satisfy the requirements of some 3D face applications. In this paper, we present a super-resolution method for reconstructing a high resolution 3D face model from a low resolution 3D face model acquired from a consumer depth camera. We used a group of radial curves to represent a 3D face. For a given low resolution 3D face model, we first extracted radial curves on it, and then estimated their corresponding high resolution ones by radial curve matching, for which Dynamic Time Warping (DTW) was used. Finally, a reference high resolution 3D face model was deformed to generate a high resolution face model by using the radial curves as the constraining feature. We evaluated our method both qualitatively and quantitatively, and the experimental results validated our method.
Ant colony algorithm for text classification in multicore-multithread environment

This paper presents about Ant Colony Algorithm (ACO) for Text Classification in Multicore-Multithread Environment in Artificial Intelligent domain. We had develop a software which assimilate concurrency concept to multiple artificial ants. Pheromone in ACO is the main concept used to solve the text classification problem. In regards to its role, pheromone value is changed depending on the solution finding that has been discovered at the pseudo random heuristic attempt in selecting path from text words. However, ACO can take up longer time to process larger training document. Based on the cooperative concept of ants living in colony, the ACO part is examined to work in multicore-multithread environment as to cater additional execution time benefit. In running multicore-multithread environment, the modification aims to make artificial ants actively communicate between multiple physical cores of processor. The execution time reduction is expected to show an improvement without compromising the original classification accuracy by the investment of trading on more processing power. The single and multicore-multithreaded version of ACO was compared statistically by conduction relevant test. It was found that the result shows a positive time reduction improvement.