Reviewerly/exHarmony huggingface dataset:
Performance Analysis on Features of Headlines and Media Organizations about Terrorist Attacks: based on a Combinatory Algorithm

This paper aims to study the relationship between the geographical distribution of terrorist attacks and features of headlines and media organizations reporting terrorist attacks.Data are derived from the Global Terrorism Database (GTD) and are established into terrorist attacks news corpus along One Belt One Road.This paper adopted a combinatory algorithm with the edit distance algorithm and the longest common subsequence algorithm to calculate the similarity headlines of media organizations across the world.Also, this paper further explores the relationship between the geographical distribution of terrorist attacks and that of global media organizations with cooccurrence analysis and social network analysis.The results show that the mainstream media organizations always imitate or copy news reports of media organizations with regional natures where terrorist attacks often happened.In regards to the geographical distribution of terrorist attacks, the results show that there is a positive correlation between the geographical distribution frequencies of terrorist attacks and that of media organizations in areas prone to suffering from terrorist attacks.The proposed combinatory algorithm for features of media coverage about terrorist attacks along One Belt One Road could provide a very significant performance increase in the terrorist events studies.The findings of this research could help relevant institutions early warn and guard against hazards of terrorist attacks.
An Adaptive Multi-sensor Data Consistency Algorithm Based on Node Credibility

By using the principle of sensor data consistency and combining the kalman filter algorithm with the bayesian algorithm, the accuracy of the algorithm is significantly improved under the condition of large data volume and complex system. An adaptive multi-sensor data consistency algorithm based on node credibility proposes the internal correlation between the sensor credibility and the data values it provides, and the final data fusion results are obtained by fusion of the optimized data through the sensor credibility. The advantages of this algorithm include: (1) the data is optimized by kalman filter, which reduces the influence of the data provided by the sensor with low reliability on the fusion result; (2) bayesian algorithm is adopted to calculate the correct probability of data values and the reliability of the sensor, which overcomes the inherent uncertainty of the sensor and improves the accuracy of data fusion. The results show that compared with the traditional data consistency algorithm, this algorithm can further improve the accuracy of fusion results and reduce the position error.
Underwater Optical Image Coding for Marine Health Monitoring Based on DCT

Introduction: Optical imaging in the underwater environment to monitor marine objects is now a hot topic of research which can be used for environmental healthcare systems through the underwater ecosystem. Among different areas of research, image coding techniques are widely applied to compress data for reliable communications. One of the challenges faced during the underwater communications is having a low bit rate in acoustic links, particularly while doing imaging in deep waters (in this condition, light needed for imaging is provided by a power supply). Materials and Methods: Two Dimensional-Discrete Cosine Transform (2D-DCT) is the main technique that we want to use for image compression, to test two different patch sizes in 2D-DCT to study the patch size effect on the quality of compression, execution time and preservation ability of high-frequency information in edges. Results: The results clearly show that a larger patch size can always be better in terms of computational complexity, quality of coded images and also edge preservation when we use DCT for the compression process. Discussion and Conclusion: b-image block in image compression (in terms of similarity and complexity), however, the use of an edge preservation factor is a new finding for our research. On the other hand, using the largest patch size is not a general approach for all image processing applications, because some studies have shown that smaller patch may be more effective for some other applications.
Could DCT Reveal Photorealistic Images?

With the development of computer graphics rendering software, it has become extremely difficult to distinguish whether an image is computer generated or a natural one. Therefore, it is really important to device robust methods for correctly classifying these two categories of images. In this work, a new approach to face the above problem is developed that is based upon the discrete cosine transform (DCT) of an image, in the YCbCr color space. The statistical features extracted, have been tested in suitable databases and the remarkable results indicate that the proposed model has a great potential to be used in digital images forensics.
Isotopic-geochemical characteristics of quartz and pyrite in the Upper Carboniferous rocks of South Verkhoyanye, Northeast Russia: an insight into the genesis of veinlet-disseminated mineralization

Abstract Discussed are characteristics of veinlet-disseminated mineralization in the northern part of South Verkhoyanye, in the sections located far away from the known gold deposits. The mineralization is represented mainly by quartz and pyrite enclosed in the Upper Carboniferous terrigenous rocks. Mineralogical-geochemical studies of mineralization are made, and isotopic compositions of oxygen in quartz and sulfur in pyrite are determined. The main trace elements in pyrite are Co, Ni, and Sb, with rare As, Cu, and Zn. Quartz contains significant amounts of Sr, W, and Co. The REE content in quartz is an order of magnitude higher than that seen in chondrites. Pyrite is light in sulfur isotopic composition (δ 34 S = -2.7… – -7.1%o). Quartz contains isotopically heavy oxygen (δ 18 O=18.2-19.1%o). The data obtained indicate that the veinlet-disseminated mineralization hosted by the Upper Carboniferous rocks in the northern South Verkhoyanye was developed as a result of metamorphogenic-plutonogenic processes.
Distinguishing Road Surface Conditions for Wheelchair Users

Japan plans to host the Tokyo Olympic Games and the Paralympic Games in 2020. To do so, Japan's government and Tokyo metropolitan government are working on welfare environment improvements around stadiums and public facilities. In addition, the rapid aging of the population resulting from the decline in the birthrate is increasing the number of wheelchair users. Nevertheless, many difficulties are associated with going outdoors in a wheelchair. Being able to discern road surfaces that are suitable for wheelchairs can provide support information for users who visit an area for the first time. The development of assistive technologies considered herein can provide optimal route information to a destination and road surface information that requires attention. This study measures the acceleration rate and angular rate of the wheelchairs during outdoor use and discerns changes in the road conditions. We produced a prototype sensor board for measuring vibration location information during running. This sensor board is mounted along with an acceleration sensor, gyro sensor, and GPS module. It can collect location information and sensor data to evaluate road conditions. The experiment evaluates measurement results obtained when the wheelchair moves on the asphalt roads and an interlocking concrete block road surface. Results of frequency analysis of acceleration sensor data enable an observer to distinguish the asphalt road surface and the interlocking concrete block road surfaces.
Paraphrase generation and evaluation: a view from the trenches

In this paper we evaluate the current state of the art in natural language paraphrase generation using deep learning methods. The focus is put on the entire modeling pipeline from data gathering up to model evaluation. Specifically, we list the publicly available datasets suitable for this task, assess their quality and discuss procedures connected with data preparation and model training. Finally, we discuss problems related to the currently used evaluation approaches.
Index Based Multiple Image Cryptosystem Using DNA Sequence

This study aims to provide an efficient multiple image Encryption (MIE) algorithm based on DNA and Image indices. In this study, various encryption techniques were analyzed and a transcending algorithm was constructed to provide better results. A two-stage encryption technique using Logistic map and DNA sequence was used for encryption. Firstly, four images of equal dimensioned and fused into one plain image. In the first phase of the encryption process the new plain image is then scrambled using Logistic map. The shuffling of the image is applied twice once on the columns and then on the rows generating a scrambled image. The permuted matrix is then encrypted using different rules of DNA which are obtained from a patterned logic from the previous pixel values. The idea is carried out and implemented using different methods and algorithms and this process of encryption has been analyzed using various parameters like the correlation, Number of pixels change rate (NPCR) and Unified average change intensity (UACI) and have been tabulated for better understanding of the respective methods.
The Geological Survey of NSW’s approach to the MinEx Cooperative Research Centre’s National Drilling Initiative.

SummaryThe Geological Survey of New South Wales (GSNSW) is undertaking a ten-year project to increase knowledge of basement and cover geology, mineral systems and hydrogeology in five under-explored regions in NSW. The project is part of the MinEx Cooperative Research Centre’s (MinEx CRC) National Drilling Initiative (NDI). GSNSW will acquire new regional geophysics, hydrogeochemical samples, biogeochemical samples and geological field observations, and analyse legacy data and samples before drilling. All data and mapping will be made available to the public.
Problems of creating an online scientific journal with multimedia content

This article discusses the format of an electronic scientific journal and scientific publication focused on online presentation of the results of scientific research, discusses the creation of online tools of an electronic scientific journal containing multimedia elements.The article describes the problems associated with the need to include multimedia data and presents a working prototype of multimedia scientific journal.
Research on an Algorithm of Service Composition Path Generation and Selection in Service–oriented Manufacturing System

Abstract Service composition, which can realize the added value of service, is the core to implement service-oriented manufacturing system. This paper mainly studies the method of service composition path generation and selection drove by the user’s service request. First, the abstract service aggregation algorithm is designed. The partial ordering relation of abstract service is discovered base on the composable correlation among services which can realize aggregation of service. Then complete graph of service composition path is constructed by employing Hasse diagram. Based on the complete graph, an algorithm is designed to select the optimal service composition path.
A Synchronization-Avoiding Distance-1 Grundy Coloring Algorithm for Power-Law Graphs

In this paper, we propose a distributed, unordered, label-correcting distance-1 Grundy (vertex) coloring algorithm, namely, Distributed Control (DC) coloring algorithm. Our algorithm eliminates the need for vertex-centric barriers and global synchronization for color refinement, relying only on atomic operations and local termination detection to update vertex color. DC proceeds optimistically, correcting the colors asynchronously as the algorithm progresses and depends on local ordering of tasks to minimize the execution of sub-optimal work. We implement our DC coloring algorithm and the well-known Jones-Plassmann algorithm and compare their performance with 4 different types of standard RMAT graphs and real-world graphs. We show that the elimination of waiting time of global and vertex-centric barriers and investing this time for local ordering leads to improved scaling for graphs with prominent power-law characteristics and densely interconnected local subgraphs.
Comparative Analysis of Efficient Image Segmentation Technique for Text Recognition and Human Skin Recognition

Abstract Computer Vision and Pattern Recognition is one of the most interesting research subject on computer science, especially in case of reading or recognition of objects in real-time from the camera device. Object detection has wide range of segments, in this study we will try to find where the better methodologies for detecting a text and human skin. This study aims to develop a computer vision technology that will be used to help people with disabilities, especially illiterate (tuna aksara) and deaf (penyandang tuli) to recognize and learn the letters of the alphabet (A-Z). Based on our research, it is found that the best method and technique used for text recognition is Convolutional Neural Network with achievement accuracy reaches 93%, the next best achievement obtained OCR method, which reached 98% on the reading plate number. And also OCR method are 88% with stable image reading and good lighting conditions as well as the standard font type of a book. Mean while, best method and technique to detect human skin is by using Skin Color Segmentation: CIELab color space with accuracy of 96.87%. While the algorithm for classification using Convolutional Neural Network (CNN), the accuracy rate of 98%.
An Approach to the Applicability Evaluation of Moving Target Tracking Algorithm

Objective and effective algorithm performance evaluation results are an important basis for the selection of tracking algorithms. Problems in the existing performance evaluation of moving target tracking algorithms include an enlarge number of trials, and in particular, failure to consider the influence of algorithm performance on the multifactor combination scenario. This study proposes a method based on the orthogonal test to evaluate algorithms. First, the factors and levels of the tracking algorithm are analyzed, and an orthogonal test dataset is constructed by using an orthogonal table. Second, the experiments of the performance evaluation are arranged with the dataset and the results are analyzed via range analysis. Finally, evaluation results show that the strong–weak sequence of factors affect the performance of the algorithm and the combination of levels form the factors that can achieve enhanced algorithm performance. Experimental results show that the proposed method can evaluate algorithms comprehensively, objectively, and effectively with decreased test and data volume.
Reversible Data Hiding in Encrypted Images using Block Selection and Adjacent Pixel Correlation

This paper represents a reversible data hiding scheme for encrypted images. Block permutation is used to encrypt the cover image through encryption key. Then, the data to be hidden is embedded into the cover image by converting the pixels of it into binary. Data recovery and direct decryption and cover image recovery are conducted by the recipient using the same encryption key and data-hiding key used earlier which uses the property of spatial correlation of the image pixels. Improved algorithm is used in this paper which embedded `n' secret bits per block. Test results and correlation are done to outline the viability of the proposed scheme.
Fast Direct Detection of Accelerating Radar Targets

This paper describes a group theoretic method for the detection of accelerating targets in both active and passive radar applications. The method directly produces a two dimensional range-Doppler rate map by utilizing multiple time and frequency shifts of the slow time data to structure the problem as one of detection of a multi-channel unknown rank-one component in noise. Our technique provides considerable computation saving when compared to the optimal method of computing and searching the three dimensional range-Doppler-Doppler rate map.
Learning Low-Rank Images for Robust All-Day Feature Matching.

Image-based localization plays an important role in today's autonomous driving technologies. However, in large scale outdoor environments, challenging conditions, e.g., lighting changes or different weather, heavily affect image appearance and quality. As a key component of feature-based visual localization, image feature detection and matching deteriorate severely and cause worse localization performance. In this paper, we propose a novel method for robust image feature matching under drastically changing outdoor environments. In contrast to existing approaches which try to learn robust feature descriptors, we train a deep network that outputs the low-rank representations of the images where the undesired variations on the images are removed, and perform feature extraction and matching on the learned low-rank space. We demonstrate that our learned low-rank images largely improve the performance of image feature matching under varying conditions over a long period of time.
Automated update of geological domains using blast-hole assays and minimum covariance determinant

Mining operations demand accurate 3D geological models for resource estimation and production. The industry-wide accepted method for constructing such domains is to use exploration-based wireframes, limiting the accuracy of the domains by the sparsity of the exploration holes. Update of the domains using blast-hole data is highly desirable to increase the accuracy of the models and enable better decision making for downstream mining processes. We discuss some of the practical and theoretical problems of using existing boundaries created using exploration drill-hole data. We also propose using the blast-hole data to adjust ore to waste boundaries. The proposed methodology is evaluated on a dataset from an iron ore deposit located in the Brockman Iron Formation of the Hamersley Province, Western Australia, demonstrating important changes in multiple boundaries in this real-world mining dataset.
Survey in Finding the Best Algorithm for Data Analysis of Privacy Preservation in Healthcare

Security for the patient's information can be achieved by using different encryption algorithms. This paper reviews several encryption methods to gain knowledge about the possible attacks during managing and transmitting the sensitive data. The algorithms are compared to analyze and develop an appropriate encryption algorithm that provides security and integrity to the medical health records, thus the patient's information remain confidential.
Single Image Reflection Removal Based on Deep Residual Learning

We present a deep residual learning approach to address the single image reflection removal problem. Specifically, residual learning exploits the mapping between the observed image and its comparatively simple reflection information, which is then removed to obtain a clear background. Different from other methods that roughly eliminating the reflections and producing the images with remanent sticking, a novel generative adversarial framework is proposed, where the generator is embedded with the deep residual learning, significantly boosting the performance without impairing the intactness of the background by adversarial training. Moreover, a multi-part balanced loss is introduced with comprehensive consideration on the measure of feature similarity as well as the discriminating ability of GAN. It produces the result of high quality by learning the reflection and the background feature simultaneously. Experiments show that the proposed method achieves a state-of-the-art performance.
Defining the Contours of Combined Stressed, Anomaly Elastic and Anomaly Densed Hierarchical Inclusions Located into a Block Layered Medium by Wave’s Data of Active Acoustic and Electromagnetic Monitoring

A new approach to the interpretation of wave fields has been developed to determine the contours or surfaces of composite local hierarchical objects. An iterative process has been developed to solve a theoretical inverse problem for the case of determining the configurations of 2D hierarchical inclusions of the l-th, m-th, and s-th ranks located one above the other in different layers of the N-layer medium and various physical and mechanical properties for active acoustic monitoring with sources of longitudinal and transversal waves. When interpreting the results of monitoring, it is necessary to use data from such observation systems that can be configured to study the hierarchical structure of the environment. Such systems include acoustic (in the dynamic version) and electromagnetic monitoring systems. The hierarchical structure of the geological environment is clearly visible when analyzing rock samples taken from ore mines. On the other hand, the more complex the environment, the each wave field introduces its information about its internal structure, therefore, the interpretation of the seismic and electromagnetic fields must be conducted separately, without mixing these databases. This result is contained in the explicit form of the equations of the theoretical inverse problem for a 2D electromagnetic field (E and H polarization), as well as for the propagation of a linearly polarized elastic wave when excited by an N-layer conducting or elastic medium with a hierarchical conducting or elastic inclusion located in the ν-th layer. In the present work, the inverse problem for a complicated hierarchical model of inclusions is considered. It can be used when conducting monitoring seismic and acoustic borehole studies to monitor the fluid return of oil fields, to analyze the dynamic state of a mountain range of deep-seated deposits which are under various mechanical effects.
Telecommunications Field Operations Supported by Augmented Reality – a Systematic Review

The main objective of this study has been to perform an extensive systematic review of publications related to augmented reality and how this technology can aid field operations for the telecommunications industry. The expected result is to validate the feasibility of a new proposed framework, which consists of an augmented reality application that makes use of mobile device sensors, such as GPS and compass, a database and computer vision, to provide relevant information to the user, who is in this case a technician working for a large telecommunications operator. The application will aid the technician's tasks, since it provides some network equipment information, such as name, location and occupation rate.
Physico-chemical Properties and Mineralogical Identification of Soils from Mélange in Beluran-Sandakan, Sabah, Malaysia

Abstract The study area located in the main road of Beluran - Sandakan, Sabah, Malaysia which mostly consists of melange. Melange material consists of mixed rocks with different sizes and originated from old rock formation. These materials commonly embedded in shale matrix and highly sheared. A total of twelve soil samples were collected along the main road in order to analyse the physico-chemical properties and mineral identification. The result of analysis shows the moisture content was in the range from 7.0% to 23.38% with the plasticity indexes were in the range from 6.32% to 34.18%. The plotted in plasticity chart shows that the soil can be classified as intermediate plasticity to high plasticity. The texture of soil best classified as clayey sand, silt with sandy clay, sand with silty clay and clay soil. The mineral content of the soil mainly contains of quartz, kaolinite and illite. Other minerals also were observed such as maghemite, hematite, chlorite and calcite. The various minerals composition shows many types of parent rocks. Whereas the high clay minerals will affect the stability of soil slope due to high moisture-adsorption minerals and high plasticity index.