Reviewerly/exHarmony huggingface dataset:
Fast AIS Data Decoding Algorithm for Multi-Core CPU

According to the provisions of the SOLAS convention, more than 600,000 ships in the world have installed automatic identification systems, which can produce more than 3 billion lines of AIS message data every day.The large amount of AIS message data provides many applications.At the same time, the design of efficient decoding of AIS messages has become a new problem.The former AIS message decoding methods mostly use online real-time decoding and decode the messages line by line according to the order of messages.These methods are slow and inefficient when decoding large amounts of AIS messages, and they cannot use multi-core CPU computing power to the extreme.In this paper, the decoding process is decomposed into several steps such as data reading, single-line message filtering, multi-line message filtering, single-line message binary transcoding, multi-line message binary transcoding, binary code decoding, and preservation results.Because multi-line message filtering and multi-line message binary transcoding are difficult to perform in parallel, these two steps are performed in serial, while the other steps are run in parallel.For binary code decoding, which consumes the largest computing resources in the process, the data is blocked first, and then decoding tasks are created and run in parallel.This method makes full use of the parallel computing capability of multi-core CPU and achieves high speed in the running test.
Author Correction: Solar superstorm of AD 774 recorded subannually by Arctic tree rings

The authors became aware of a mistake in the data displayed in Fig. 1 and Supplementary Table 2 of the original version of the Article. Specifically, the 14 C production values were printed out in the code before the conversion between the omnidirectional fluence and the flux. As a consequence, the values of the 14 C production in Fig. 1 and Supplementary Table 2 were too high by a factor of 4× π = 12.566.. As a result of this, a number of changes have been made to both the PDF and the HTML versions of the Article. A full list of these changes is available online.
DEVELOPING THE VERBAL-LINGUISTIC INTELLIGENCE OF ELEMENTARY SCHOOL STUDENTS INTHE SCOPE OF FAMILY, SCHOOL AND COMMUNITY

The gold generation of 2045 is expected to bring Indonesia to reach its golden period in 2045. Therefore, this generation needs to be complemented with human and social capital. The social capital would be pervaded if the generation has linguistic skills. Such skill would be auspicious when it is equipped by verbal-linguistic intelligence. Thus, the development of linguistic intelligence is needed for elementary school students as part of the golden generation of 2045. Development of verbal-linguistic intelligence can be carried out in the family, school and community scopes.
New Constructions of Asymptotically Optimal Codebooks via Cyclotomic Classes of Order 8

Asymptotically optimal codebooks are a family of codebooks that can approach an optimal codebook meeting the Welch bound when the lengths of codewords are large enough. They can be constructed easily and are a good alternative for optimal codebooks in many applications. In this paper, we construct a new class of asymptotically optimal codebooks by using the product of some special finite fields and almost difference sets, which are composed of cyclotomic classes of order eight.
Directional phase-shift circular arrays targets for out-of-focus camera calibration

We design a directional phase-shift circular arrays targets to calibrate camera system under the assumption that targets are in a defocus condition. In contrast to conventional camera calibration method, we can achieve accurate camera calibration with severely defocused images by using the proposed directional phase-shift circular arrays targets. In this paper, three directional phase-shift circular arrays targets are used to calibrate the measurement system. We set up a mathematical model to detect the feature points accurately even though the targets images are seriously blurred. In the experiments, the targets are displayed in a LCD monitor, camera system can capture the three targets images at the same position to extract the feature points. Gaussian filters are utilized to blur the targets images to simulate the fuzzy images. And we obtain targets images with different defocus degree by adjusting the depth range of the actual camera system. We have done a series comparative tests with checkerboard. We evaluate the performance of the proposed method on simulated and real data. Finally, the measurements of displacement and morphology are implemented. Experimental results indicate that the directional phase-shift circular arrays targets can be used to achieve accurate camera calibration parameters.
WORKING WITH A LINGUISTIC CORPUS USING R: AN INTRODUCTORY NOTE WITH INDONESIAN NEGATING CONSTRUCTION

This paper demonstrates the use of R for a unified data science in corpus linguistics via a series of corpus-based analyses on Indonesian Negating Construction. The data is based on c17-million word-tokens of an online-news corpus, a part of the Indonesian Leipzig Corpora. We identified that tidak is the most frequent form in our corpus. Next, we found that tak has significantly higher type frequency for negated-predicates with [ter-X-kan] schema compared to tidak; this finding provides a quantitative nuance against a description in an Indonesian reference grammar, stating that (i) in present-day Indonesian tidak is also common to negate ter- related predicates, while (ii) the compulsoriness of tak to negate ter- predicates is a past usage. Lastly, we refine our second finding by applying Distinctive Collexeme Analysis to determine that tak strongly attracts specific verbs predominantly in the [ter-X-kan] schema compared to tidak; this finding offers a deeper characterisation for tidak and tak.
GMSimViz: Automated 3D Visualization of Ground Motion Simulation with Generic Mapping Tools (GMT)

GMSimViz is an automation tool that produces an animated 3D visualization of geological faults, ground motion and other earthquake related data.Typically ground motion simulations are computed by a High Performance Computing (HPC) facility, and its verification involves various data visualization methods.A 3D animation of the ground motion is an excellent media to understand the nature of an earthquake, and to communicate with the general public.However, its production has been largely left to time-consuming manual interaction with a 3D visualization software package, such as Paraview as no existing solution provides a fully-automated workflow.
About one approach to implementing semantic search

Traditional search mechanisms are based on the keyword search, which does not consider the semantic links between different concepts.This leads to the loss of relevant documents due to inaccurate query formulation or using contextually close words and concepts in the query.To solve the problems of formulating user queries and interdisciplinarity of concepts, it is suggested to use semantic search.The proposed method for implementing semantic search is applicable to large scopes of text data and is based on using a genetic algorithm.Unlike standard methods for information search, the suggested method allows us to consider the semantics of interrelationships between concepts and to handle interdisciplinary concepts correctly.By the aid of semantic tagging, documents contain concepts that are not present in the user's initial query but are semantically close to the requested concepts.Semantic tagging is performed for each document separately, which provides parallel tagging in several subject areas.By the time of the document ontological profile formation is completed, all semantic distances between pairs of distinguished concepts are calculated.Concepts are considered contextually close if their semantic proximity value is above a certain threshold value that is specified in the search parameters.Building a document ontological profile is a multicriteria task, since it depends on a lot of characteristics, so genetic algorithms can be used to solve it effectively.The developed genetic algorithm is intended for more accurate distribution of weight coefficients and estimation of semantic proximity of concepts.
Sistem Perancangan Web Penjualan Material Bangunan Pada PT Bangun Tiara Teknik

Web-based information systems technology is one of the media information that is efficient and effective in the dissemination of information that can be accessed by anyone, anytime, and anywhere. Currently, many companies are already making use of web-based information systems technology to help his efforts in promoting his company, to introduce its product, getting consumers more, making transactions faster and provide satisfying service for consumers. PT. Bangun Tiara Teknik is a company engaged in the field of building materials. Sales system that exists today of PT. Bangun Tiara Teknik is still done manually, where starting from the process of supply of goods, the ordering of merchandise, the deals, the creation of shipping documents, to reporting, so it takes a lot of time and in create a document and are still often goes wrong in terms of record keeping and input data by the sales section. The results of the design of this web-based information system is the best solution to solve the problem. Error logging orders can be minimized and reporting can be done appropriately. Therefore, the authors are interested in making the design of information system of sales with web-based at PT Bangun Tiara Teknik. With web-based computerized system allows the addition of a number of consumers to purchase the desired product, consumer satisfaction against the speed and accuracy of orders as well as reporting.
Analysis on the Innovation of Small Business Management Theory based on Cloud Model

Since the reform and opening-up, with the rapid development of economic construction and the continuous advancement of science and technology, a number of large, medium and small enterprises have emerged in China, which have further promoted social and economic growth. If enterprises want to develop and cannot do without scientific management, China's research on business management theory begins in modern times. During this period, it has experienced numerous innovations and changes in enterprise management. Some enterprises have tried to create according to their actual conditions and new management model, and achieved brilliant achievements. This paper mainly reviews the perspectives and methods of Chinese enterprise management innovation theory research, hoping to help the development of Chinese enterprises.
SISTEM INFORMASI GEOGRAFIS PEMETAAN LOKASI BENCANA ALAM DI SUMATERA UTARA BERBASIS WEB

Abstract - Developments in information technology, especially information systems have brought convenience that promises a work efficiency. For example geographic information system is a tool with a computer system that is used to map conditions and events that occur on the face of the earth is a system that is helpful in providing and presenting information needed by users. The development especially in the aspect of environmental needs in order to overcome or reduce the impact of disasters in the Sumatran region, and by improving the performance of the BPBD, it is necessary to have a GIS-based information system that can show BPBD disaster points that already exist in North Sumatra. With the existence of map information, especially in the web system, it is expected to provide fast and accurate information, especially knowing the exact location of the disaster. thus facilitating the work of officers in providing disaster information at the head office. Keywords - Geographic Information Systems, Mapping, Web.
Cerita Si Kuncung: Membaca Relasi Kuasa dalam Majalah Anak-anak Indonesia

Si Kuncung is the first kid's magazine that officially accepted as a national kid's magazine by the Indonesian government in the era of President Soeharto. Aside from being a media for education and culture, the government also helped Si Kuncung's publications, especially in marketing and financing. The relationship between the publishers and the government expanded the deployment of Kuncungand strengthened its position in the national children's reading materials. However, on the other hand, Si Kuncung who dissolved in the leadership of power also faded along with the collapse of the New Order era.
Security analysis of a cloud authentication protocol using applied pi calculus

Nowadays cloud computing is the most promising model within information technology. One of the most important issues is to achieve secure user authentication. Vulnerability of an authentication protocol results in successful attacks against confidentiality and integrity of user data stored and processed in the cloud. In our suggested protocol a person uses a static password and a one-time password for identity verification. Shared control among the cloud servers is provided by applying a Merkle-tree for storing one-time passwords distributed. A security analysis is carried out in case of outsider adversaries. We show that our authentication protocol fulfils typical security requirements of a key exchange protocol, i.e., authentication of the participants, key secrecy, key freshness and confirmation that both parties know the new key in the Dolev-Yao model.
Experimental Evaluation of a Method for Simulation based Learning for a Multi-Agent System Acting in a Physical Environment

A method for simulation based reinforcement learning (RL) for a multi-agent system acting in a physical environment is introduced, which is based on Multi-Agent Actor-Critic (MAAC) reinforcement learning.In the proposed method, avatar agents learn in a simulated model of the physical environment and the learned experience is then used by agents in the actual physical environment.The proposed concept is verified using a laboratory benchmark setup in which multiple agents, acting within the same environment, are required to coordinate their movement actions to prevent collisions.Three state-of-the-art algorithms for multi-agent reinforcement learning (MARL) are evaluated, with respect to their applicability for a predefined benchmark scenario.Based on simulations it is shown that the MAAC method is most applicable for implementation as it provides effective distributed learning and suits well to the concept of learning in simulated environments.Our experimental results, which compare simulated learning and task execution in a simulated environment with that of task execution in a physical environment demonstrate the feasibility of the proposed concept.
A new feature-based self-embedding image watermarking scheme

The performance of digital watermarking algorithm is mainly manifested in invisibility and robustness. At present, many algorithms improve these two aspects by sacrificing embedding capacity for the reason that if watermark embedding amount is small, the watermark has little influence on the visuality of the cover image, and its robustness is also higher. Therefore, how to improve the anti-attack performance of the algorithm without reducing the amount of embedding has become a major research direction. This paper proposed a new robust watermarking scheme based on feature extraction techniques. Firstly, the SIFT (scale invariant feature transform) algorithm is used to extract the stable feature points from cover image to form embedding region. Then watermark is composed of the cover's texture features obtained by LBP (local binary pattern) extracting method. Finally, embedding region is transformed by singular value decomposition (SVD) and the watermark is embedded into its singular value vector. The simulation results showed that the watermark embedding capacity of this algorithm is relatively high, and it has good resistance to common image processing and geometric transformation.
Scalarity and alternatives of Japanese mora (letter)-based minimizers

This paper investigates interpretations of the Japanese mora- (letter-) based minimizer “X.Y.Z”-no “X”-no ji-mo ‘even the letter “X” of “X.Y.Z”.’ I argue that this mora/letter-based minimizer has two types, a literal type and a non-literal type, and each type has different semantic characteristics regarding scale structure and computation of alternatives. In the literal type, X corresponds to the first mora of a target “X.Y.Z” and is construed as a minimum on the number scale of moras (among higher scalar alternatives). On the other hand, in the non-literal type it refers to the degree of a main predicate about the target “X.Y.Z” where X is construed as a minimum on the scale of the main predicate. That is, in the non-literal type, scale does not have to do with the number of moras, but with the degree of a predicate. I propose on the basis of the findings that in addition to a local minimizer whose alternatives are lexically activated (Chierchia 2013), there is a global minimizer in natural language, whose alternatives are activated by information contained in the main predicate.
Return Instruction Identiﬁcation in Binary Code with Machine Learning

Binary code analysis is the main method for malware analysis.In this paper, the analysis is started by identifying return instructions to disassemble binary code.The return instruction identification problem is converted into a binary classification problem: is a byte in binary code the first byte of a return instruction?The 32 bytes around a byte in binary code are considered the feature of the byte.A multilayer perceptron is employed to build the classification model.Then, the model is trained with 1,383 binaries from Windows XP SP3.The evaluation results on several open sources show that our approach is feasible and has high accuracy.
Penentuan Rencana Strategis Penjualan Fashion Melalui Penerapan Data Mining Untuk Pengelompokan Market Share Penjualan Fashion

Changes in consumer thinking patterns have a huge impact on several companies engaged in e commerce. Every company engaged in e commerce has several ways to attract consumers to be interested in a product created by the company, one way is to classify consumer desires. The group examined in this paper is to group fashion interests from several desires. Diverse grouping through the application of data mining with clustering methods that determine the number of clusters then allocate data into clusters after that calculate the average of the data that is in each cluster after that allocate each data to the closest average, and if still there is data that moves clusters or changes in average values then returns to calculate the average. The results of this paper can classify the desires of consumers from the desires that consumers want. This research can classify the types of fashion, and can increase sales profits through these types of desires, then improve marketing or to restore goods. Key Word: Fashion, Data Mining, clustering
A novel approach for image enhancement with binocular cameras

Binocular cameras have gained increasing attention because they can capture high-resolution images at a lower cost than monocular cameras. However, many existing binocular camera technologies typically require accurate depth estimation. To address this problem, this paper presents a new image enhancement method based on monochromecolored cameras. Our method replaces depth estimation with dense matching of feature points, thereby effectively reducing the computational complexity. After image matching, matrix completion is used to recover the color information of the monochrome image. Consequently, our method produces a high-quality image under the low-light condition. We built real image database for the experiments, and the results reveal that our method exhibits superior performance over existing methods.
Rancang Bangun Dashboard dan Visualisasi Data Kickstarter dengan Pendekatan Business Intelligence

Kickstarter is one of the most famous worldwide crowdfunding platforms.Pebble smart watch slash wearable technology is one example of successful story on Kickstarter.With current trend on how successful a project can be delivered until its product launch, Kickstarter must analyze its data to asses which projects that is successful and how its revenue progress.With business intelligence approach, Kickstarter could make performance evaluation from three aspects, such as Strategic, Management, and Operational.This will detect which project is failed to reach their goal and how project grow each region.Based on our approach, there are four types of insights, namely descriptive, diagnostic, predictive, and prescriptive insights.This insight could be used as a reference for companies reaching their goals.Although there are some of the biggest and most-pledged projects done in 2015, Kickstarter hit their worst year because they found that many projects could not reach their target.However, respectively in 2016 and 2017 Kickstarter had their percentage of success projects increase slowly although there are many competitors, such as new crowdfunding platform.
Abstract P158: Depression After Cardiac Transplantation From 2012 to 2018 in a Reference Hospital in Recife: A Transversal Study

Introduction: Cardiac transplantation represents a treatment opportunity for cardiovascular diseases that are refractory to traditional methods. For the procedure’s success, the individual needs to be collaborative and remain surrounded by restrictions and intensive care even after its performance. Thus, the emotional burden that surrounds the process contributes to depression after the surgery. The impact of depression on one’s quality of life has been subject of research all over the world, but its value is not completely clarified after a heart transplantation. Objective: To estimate the occurrence of symptoms of depression in 50 patients who underwent cardiac transplantation at the Institute of Integral Medicine Professor Fernando Figueira between 2012 and 2018. Hypothesis: Depression was a frenquent event after cardiac transplatation in the sample of this study. Methods: A cross-sectional observational study using questionnaires adapted, translated and validated in Brazil, the Medical Outcomes Study 36- Item Short-Form Health Survey (SF-36) for quality of life assessment and the Beck II Depression Inventory (BDI-II), for evaluation of depression symptoms. The collection was performed at the Cardiac Transplant Outpatient Clinic of the referred hospital, through individual interviews. The data collected was entered in the program Microsoft Excel version 2010 and the Statistical Package for the Social Sciences - SPSS 13.0 Software for Windows was used. All tests were applied with 95% confidence. This study is based on Resolution 466/2012 of the National Health Council. This research was approved in the Ethics Committee of the Institute of Integral Medicine Professor Fernando Figueira with CAAE n°66851517.7.0000.5201. Results: The sample consisted of 50 patients, 76% male (38 of 50), mean age of 47.76 years and 48% (24 of 50) had low education level. Data obtained by the application of BDI-II (n = 50) presented a mean of 13.36, median of 13.00, standard deviation of 12.76. Of the sample, 70% (35 of 50) were considered to have symptoms of depression, reaching scores with more than 9 points, the difference of genres being of little statistical significance. Among the variables related to the symptoms of depression, only the need for anxiolytic after transplantation was statistically relevant. In the comparison of the SF-36 with the 35 symptomatic patients for depression, of their eight scales only limitation by physical aspects and emotional aspects were not statistically relevant. Conclusion: The symptoms of depression could be verified in the sample with a significant impact on quality of life, when associated with functional capacity, pain, general health, vitality, social aspects and mental health. Patients who underwent heart transplantation should receive multidisciplinary care in order to minimize their vulnerabilities.