Reviewerly/exHarmony huggingface dataset:
Research on the Supervision Method of Big Data Technology in the Systemic Risk of Internet Finance in China

In order to standardize the supervision process of systemic risk of Internet finance in China, this paper puts forward a novel supervision method of systemic risk of Internet finance in China based on big data technology. This method is based on big data technology, combines computer technology and Internet of things technology, can real-time monitor the systematic data of China's Internet finance, and quickly feedback the information to the relevant staff. The results show that this method can effectively improve the standardization of China's Internet financial systemic risk supervision and reduce the harm caused by China's Internet financial systemic risk.
Smart Features for Dynamic Vision Sensors

This paper presents a semi-supervised procedure for training a fully convolutional neural network for interest point detection and description. Contrary to previously trained networks utilized for the same purpose, our network was tailored to work with event-based imagery from a downward facing camera aboard a fixed-wing unmanned aerial vehicle. Event-based cameras are a novel type of visual sensor that operate under a unique paradigm, providing asynchronous data on the log-level changes in light intensity for individual pixels. This hardware-level approach to change detection allows these cameras to achieve ultra-wide dynamic range and high temporal resolution. The final system produces state-of-the-art repeatability and homography estimation results on an aerial event-based image dataset when compared to traditional interest point detector and descriptor algorithms.
EXPPO: EXecution Performance Profiling and Optimization for CPS Co-simulation-as-a-Service

A co-simulation may comprise several heterogeneous federates with diverse spatial and temporal execution characteristics. In an iterative time-stepped simulation, a federation exhibits the Bulk Synchronous Parallel (BSP) computation paradigm in which all federates perform local operations and synchronize with their peers before proceeding to the next round of computation. In this context, the lowest performing (i.e., slowest) federate dictates the progression of the federation logical time. One challenge in co-simulation is performance profiling for individual federates and entire federations. The computational resource assignment to the federates can have a large impact on federation performance. Furthermore, a federation may comprise federates located on different physical machines as is the case for cloud and edge computing environments. As such, distributed profiling and resource assignment to the federation is a major challenge for operationalizing the co-simulation execution at scale. This paper presents the Execution Performance Profiling and Optimization (EXPPO) methodology, which addresses these challenges by using execution performance profiling at each simulation execution step and for every federate in a federation. EXPPO uses profiling to learn performance models for each federate, and uses these models in its federation resource recommendation tool to solve an optimization problem that improves the execution performance of the co-simulation. Using an experimental testbed, the efficacy of EXPPO is validated to show the benefits of performance profiling and resource assignment in improving the execution runtimes of co-simulations while also minimizing the execution cost.
Using automatic constructed thesauri instead of dictionaries in the verbal phraseological units validation task

Automatic validation of compositionality vs non-compositionality is a very challenging problem in NLP. A very small number of papers in literature report results in this particular problem. Recently, some new approaches have arised with respect to this particular linguistic task. One of these approaches that have called our attention is based on what authors call “lexical domain”. In this paper, we analyze the use of Pointwise Mutual Information for constructing thesauri on the fly, which can be further employed instead of dictionaries for determining whether or not a given phraseological unit is compositional or not. The experimental results carried out in this paper show that this dissimilarity measure (PMI), can effectively be used when determining compositionality of a given verbal phraseological unit. Moreover, we show that the use of thesauri improves the results obtained in comparison with those experiments employing dictionaries, highlighting the use of self-constructed lexical resources which are, in fact, taking advantage of the same vocabulary of the target dataset.
CONSTRUCTIVISM LEARNING IN WRITING OF LITERARY WORKS

Constructivism is a function as a method in learning both science and socio-cultural sciences, including literary learning. The purpose of this research was to find out the Increasing of student's performance in writing literary works and to know the effectiveness of constructivist methods in the teaching of writing literary works. This study was experimental method. There were 30 samples in this study, and the assessment was through tests and non-tests. The post-test showed a higher difference than the pre-test, that was 18%. So the constructivism method can be used in the teaching of writing literary works and able to improve student writing competence. The method of constructivism helps students to organize creative ideas in writing literary works. Students can develop ideas, characterizations, good storylines and the ability to raise current phenomena in writing stories.
Coiflet Based Deblurring of Insulator Images for Remote Monitoring

Remote monitoring of electrical equipment in the existing power system network has become indispensable for ensuring the reliability and efficiency of entire power network. This paper presents a robust wavelet domain based image processing technique for deblurring aerial images of suspension type insulators to be employed in the power transmission network. The proposed technique modifies the wavelet transform coefficients of blurred aerial images. The resultant deblurred images, though, have small artifacts near edges but they do not cause any loss of significant information. The key contribution of this paper is validation of proposed algorithm on Xilinx ZedBoard to test the robustness of proposed technique for real-time applications.
Deep Reinforcement Learning for Auto-optimization of I/O Accelerator Parameters

Reinforcement Learning (RL) has made several advances in the machine learning domain especially Deep Reinforcement Learning. AlphaGo developed by DeepMind is a good example of how the deep neural network can train an agent to play and outperform professional Go players. Auto optimizing parameter is a relatively challenging research area. To automatically tune the parameters of the system, we formalize the problem into the setting of reinforcement learning model, where the aim is to train an agent whose goal is to find the optimum parameters by observing the state of the system and taking actions to maximize a cumulative reward. In this work, we solve this problem with the matrix version of Q-learning and the neural network version of Q-learning. We developed a new heuristic of Q-learning algorithm, called Dynamic Action Space (DAS), to further improve the robustness of the algorithm in finding the optimum state. The DAS approach significantly improved the convergence and stability of the algorithm. Then we tested the approach on three deep neural network variants, namely Deep Q-Networks (DQN), Double Deep Q-Networks (DDQN) and Dueling Networks. We show that the heuristic DAS model helps the Deep RL networks to converge better than the baseline Q-Learning model.
A Novel Feature Matching Ranked Search Mechanism Over Encrypted Cloud Data

Encrypted search technology has been studied extensively in recent years. With more and more information being stored in cloud, creating indexes with independent keywords has resulted in enormous storage cost and low search accuracy, which has become an urgent problem to be solved. Thus, in this paper, we propose a new feature matching ranked search mechanism (FMRSM) for encrypted cloud data. This mechanism uses feature score algorithm (FSA) to create indexes, which allows multi-keywords which are extracted from a document as a feature to be mapped to one dimension of the index. Thus, the storage cost of indexes can be reduced and the efficiency of encryption can be improved. Moreover, FMRSM uses a matching score algorithm (MSA) in generating trapdoor process. With the help of FSA, the matching score algorithm can rank the search results according to the type of match and the number of matching keywords, and therefore it is able to return results with higher ranking accuracy. Comprehensive analysis prove that our mechanism is more feasible and effective.
Principles of Digital Watermarking

This chapter introduces the benefits of watermark over cryptography and stenography. It provides the digital ownership on a file, but the noise is also attached with the file. Even if somebody copies the file and claims ownership, watermark still provides security. Watermarking is a robust and secured technique compared to other techniques. Implementation cost of this technique is optimized. This chapter also elucidates the attacks on watermarks and solutions to handle these attacks. Authors suggest watermarking will remain unchanged even if the file is compressed.
An information model‐based interface design method: A case study of cross‐channel platform interfaces

Abstract Interface design involves large amounts of information and many complex processes. However, existing interface design methods have not addressed the potential to allocate information volume reasonably and effectively. In addition, current usability testing methods do not customize the weights of usability criteria for different displays. This study addresses the problem of too much information in the early stages of interface design and introduces the use of weighted usability criteria for developing different types of the user interface (UI) displays. An information model that can reasonably distribute information to varied interfaces to improve usability is presented. Using the analytic hierarchy process to weight usability criteria according to UI type, the proposed method generates convincing and objective usability test results. It handles the overall processing and effectively distributes information within a reasonable range, allowing designers to improve UI usability levels. Our findings compare the performance of an original interface and an improved interface, resulting in significant differences for both websites and mobile phone apps. This study provides a systematic interface design method enabling developers to use a core set of directions for developing more engaging interfaces and customizing usability criteria according to display type, resulting in more sophisticated and rewarding UI designs.
Morphological contour decomposition and reconstruction by using asymmetric SEs

Abstract We had proposed an algorithm based on mathematical morphology to decompose and reconstruct an image by using two contours [4]. These contours are defined as the edge and the second edge (i.e., the edge of the image which has been removed an edge once) of the original image. Since these contours have informations of boundary and internal direction of image, the original image can be reconstructed exactly from them. However, there was a restriction in this algorithm that the structuring element (SE) used for making contours must be symmetric. In this paper, we will show an expansion of the algorithm to be able to use asymmetric SEs under a certain condition and also show some applications of this method.
Darkness visible; blindness and borders/memories and movies

The author considers a trio of films of recent vintage in which the primary narrator is sight impaired and consider the role memory and recollection play in the telling of their accounts. Each film – Notes on Blindness, Blue, and The Diving Bell and the Butterfly – are biographical and depicted in documentary or hybrid/stylised documentary format. Common threads and themes unite the seemingly disparate characters and these focus on water and waiting. How a ‘sightless’ scene is recreated for film is at the heart of this article.
Solving Job Shop Scheduling with Parallel Population-Based Optimization and Apache Spark

The paper proposes an architectureJedrzejowicz, Piotr for the population-based optimization in which Apache Spark is used as a platform enabling parallelization of the process of search for the best solution. The suggested architecture,Wierzbowska, Izabela based on the A-Team concept, is used to solve the Job Shop Scheduling Problem (JSP) instances. Computational experiment is carried out to compare the results from solving a benchmark set of the problem instances obtained using the proposed approach with other, recently reported, results.
Secure third‐party data clustering using <scp>SecureCL</scp>, Φ‐data and multi‐user order preserving encryption

Abstract Secure collaborative data clustering using SecureCL is presented. SecureCL is founded on the concept of Φ‐data implemented using Super Secure Chain Distance Matrices and encrypted using Multi‐User Order Preserving Encryption. The advantage offered, unlike comparable systems, is that SecureCL does not require any user participation once the Φ‐data proxy has been encrypted; it does not require recourse to Secure Multi‐Party Computation protocols or ‘secret sharing’ mechanisms. The utility of SecureCL is illustrated using Nearest Neighbour Clustering and Density‐Based Spatial Clustering of Applications with Noise, although it can be applied to any data clustering algorithm that involves distance comparison. The reported experiments demonstrate that SecureCL can produce securely cluster configurations comparable to those produced using standard, non‐encrypted, approaches without entailing any significant computational overhead, thus indicating its suitability in the context of Data Mining as a Service.
Predicting Round-Trip Time Distributions in IoT Systems using Histogram Estimators

In this paper we describe and evaluate an approach for predicting conditional RTT probability distributions in an IoT system. From the distributions we derive conditional mean and quantiles, for example, which are essential for performance management and service assurance. The distribution is represented by a histogram, which requires a discretized target space, trained using supervised learning of a random forest classifier.We evaluate the approach using data traces obtained from experimentation in a realistic IoT testbed. The results show high model performance in prediction of quantiles and aggregated distributions, and the trends for conditional mean are captured.For the operator, the approach enables low-overhead and tractable IoT performance assessment, especially compared to traditional approaches using for example active measurements.
A Code Profiling Model for StART

Abstract Test case selection in software testing is one of the process that support to quality in finding bug. Decreasing number of bug may increase quality of software. Many strategies have been proposed by researcher for software testing. Specially to avoid exhausted testing which all the testers take into account which may increase time and performance. One of the strategy is StART. The code profiling is a part of StART, which is a selection test cases strategy using code profiling. The strategy is based on the adaptive random testing and support with code profiling in the strategy. The aim of this paper is to show the code profiling model. The selection of domain area to test is based on the highest probability in the code profiling result. The probability of in the code profiling is calculated and the highest value to be chosen as the first area to test. The value to be chosen as a domain area for the first to be tested in SUT. This model used AspectJ as case study to show the model can be implemented for a new programming paradigm. Tetris selected as case study to show the model flow. From the case study of Tetris, the model shows the area to be tested first is in the package Gui, for aspect menu and advice after the probability value shows the highest result. For future study, this model need to test their efficiency of their strategy.
Secure Communications in Unmanned Aerial System Swarms

Drones or Unmanned Aerial Systems (UAS) are being used widely for various applications in the civilian, academic, industrial, and military settings, mainly due to their low cost, versatility, and ease of use. This is only expected to increase with a wider regulatory acceptance of their operations in the National Airspace System (NAS) in the near future. While their wide availability is a significant advantage, they also carry vulnerabilities to cyber-attacks, potentially compromising their missions and safety. In this paper, we explore a method of securing UAS communications to address such a vulnerability. Our approach is to apply techniques based on Ciphertext policy Attribute-Based Encryption (CP-ABE) cryptosystem. In this effort, UAS are distinguished between each other based on their configuration and payload. For instance, distinguishing attributes that were considered included membership in a particular team (Blue/Red team), a serial identifier within that team (Unit 1, etc.), and the presence or absence of a particular payload (camera or microphone). Tests were conducted by issuing a voice command to a central computer, which converted the commands into text and subsequently sent to all the drones in the setup. The response of the appropriate drone to the command that were intended to it was successfully demonstrated. Additionally, the cost of the encryption was also measured in terms of CPU execution time and memory usage. Performance analysis of encryption and decryption indicated that it mainly depends on the complexity of the access policy and the size of the data being encrypted or decrypted.
Effect of Change in Tilt Angle on the Performance of Photovoltaic Systems

Photovoltaic (PV) system is increasingly required in industries, commercial and domestic buildings. The performance of PV is a problem that needs attention. Many factors contribute to the performance of PV systems.  This study presents the effect of change in tilt angle on the performance of PV systems. The system’s location is Port Harcourt. An average yearly load of 2170kWh/day was estimated for the system. Various angles were used for the position of the PV panel on the working plane. It was observed that as the tilt angle increases, the lower the yearly irradiation on global collection planes. Also as the overall system losses reduces, the performance ratio reduced as well. The reduction in the overall system and improvement of the system’s ‘performance ratio was as a result of increase in tilt angle. The ranges of tilt angle selected are: 10 o , 15 o , 20 o , 25 o , 30 o , 35 o , 40 o and 45 o . The success of this project was achieved using PVSYST tool. It is recommended that the system can be used at a location with similar solar data with study location, Port Harcourt Nigeria.
ANALISIS KEBUTUHAN AIR IRIGASI DENGAN SOFTWARE CROPWAT 8.0 DI DAERAH IRIGASI BELIMAU SAMARINDA

Muhammad Ali Wardana, 2019, ANALYSIS OF IRRIGATION WATER REQUIREMENTS WITH CROPWAT 8.0 SOFTWARE IN VELVET IRRIGATION AREAS, Thesis, Civil Engineering Study Program, Faculty of Engineering, University August 17, 1945. Water is a natural resource that is very important for the survival of all living things. Water is also very necessary for industrial activities, fisheries, agriculture, and other businesses. In the use of water, there is often no caution in its use and utilization, so that efforts are needed to maintain a balance between the availability and demand of water through development, preservation, repair and protection. In the use of water, especially once again in terms of agriculture, in order to meet food needs and regional development. In meeting water needs, especially for water and rice fields, it is necessary to build irrigation systems and weir buildings. The need for water in the fields is then called the need for irrigation water. Irrigation is an effort to supply, regulate and dispose of irrigation water to support agriculture whose types include surface irrigation, swamp irrigation, underground water irrigation, pump irrigation and pond irrigation. The purpose of irrigation is to utilize available irrigation water correctly, efficiently and effectively so that agricultural productivity can increase as expected. In terms of calculations, the calculation of irrigation water needs is manually guided by Irrigation Planning Standards Planning Criteria for Irrigation Networks KP-01 2010, while Cropwat 8.0 is guided by FAO because CROPWAT is software developed by FAO. With the Cropwat 8.0 software calculation method, the results of the CWR Rice feature show that the maximum effective rainfall results in December are 47.8 mm/dec (47,800 liters/second/Ha). The maximum irrigation water demand occurred in October of 186.4 mm/dec (186,400 liters/second /Ha). For Palawija CWR, the maximum effective rainfall is 46.2 mm/dec (46,200 liters/second/Ha) in December. Whereas the maximum irrigation water requirement occurs in December of 19.1 mm/dec (19,100 liters /second/Ha).
Changes in the Stereotype of Italians in Polish Students of Italian Philology

This study aimed to examine if a stereotype of a target culture constructed in a home culture can change as a result of education and the target language learning as claimed by Lippmann (Public opinion. Harcourt Brace and Co., New York, 1922/1965). Participants included 67 students of Italian Philology, in the first and third year of undergraduate and second year of graduate studies of a university in Poland. Results indicated that the stereotype of Italians changed over the course of degree. The first year undergraduates reasoned mainly with the stereotype and the graduates fell for the more objective, reality-grounded knowledge. We discuss these results in terms of the classic view that stereotypes are fixed, exaggerated, oversimplified and resistant to change representations of groups of people.
Features of Competence-oriented Task Use at Mathematics Lessons

This article discusses features of competence-oriented tasks used in mathematics lessons. Result of education is not only knowledge of speciﬁc disciplines, but also ability to apply them in everyday life, for use in the future training. And this largely depends not on the knowledge, skills and practices acquired, but on some additional qualities, competencies and more relevant to understanding the modern goals of education. Introduction of these concepts into teaching practice in school has required a change in the content and methods of education, speciﬁcation of activity types that school students have to master at the end of an educational process and in the study of individual subjects. Success of today’s student in the future largely depends on his/her ability to acquire and develop skills, practices and competencies that can be used in any life situation. Therefore, it is necessary to educate children in readiness for change, developing of qualities such as mobility, constructiveness and ability to learn.