Reviewerly/exHarmony huggingface dataset:
Application of an Inverse Distance Weighted Anisotropic Method for Rock Quality Designation distribution in Eastern Kahang deposit, Central Iran

Estimation of Rock Quality Designation (RQD) distribution with low value of error is crucial for mining excavation based on geomechanical data. This paper proposes an application of an Inverse Distance Weighted Anisotropic Method (IDWAM) based on combined variograms to construct RQD block model in KahangCopper-Molybdenum (Cu-Mo) porphyry deposit, Central Iran, using subsurface data.To do this, an appropriate voxel size was calculated and then RQD variography was carried in horizontal and vertical directions.In addition, Deere and Miller rock classification was used to classify RQD block model for a final open pit interpretation.Finally, correlation between results for RQD estimated derived via the IDWAM and raw data was carried out using jackknife method.The results obtained by the combination of IDWAM and experimental variogram showed that the excellent RQD zones are located in the central and North Western parts of this area.
Video dehazing based on CNN

The appearance of outdoor images is easily affected by natural phenomena such as fog and dust, which reduces contrast and color distortion. Video dehazing has a wide range of real-time applications, but the challenges mainly come from large amount of computation and bad real-time performance. In this paper, we propose a video dehazing system which is an end-to-end network based on CNN (Convolutional Neural Network). The dehazing algorithm learns the scene transmission and the global atmospheric light simultaneously, which simplifies the dehaze process and improves the real-time performance. Finally, we process videos through combining the end-to-end dehaze network and bicubic interpolation algorithm, and obtain satisfactory results. The experiment results demonstrate that the proposed method performs favorably against the state-of-the-art methods on both quantitative and qualitative evaluation.
Recognition of the objects contours in CT and MRI images

Biomechanical modeling is used for preoperative planning of surgical treatment and allows you to choose the most rational option from the mechanical point of view. At the same time, the basic data for building models of the biological objects under study are the data of computed tomography (CT) and magnetic resonance imaging (MRI). To optimize and partially automate the process of constructing models of biological objects in Delphi, a software was developed that allows determining the outlines of areas corresponding to the object under examination on CT and MRI slices, to build a flat closed curve corresponding to the contour of a specific vessel lumen, to save data about the constructed curve to a file whose format corresponds to the format storage of curves in the software package Solid Works. The method of recursive two-dimensional frontal growth allows cutting off (due to the choice of the starting point) all “extra” shear vessels, which along with the section of interest can fall on the processed section. If the boundary of the object is determined, the algorithm does not imply further checks of the remaining pixels to reduce the number of operations and optimize the use of computer resources. In this case, the sensitivity of the method (the numerical value for the similarity criterion of pixels) can be changed manually by the user. Within the framework of the study, the frontal growth method is programmatically implemented. The created application allows you to create three-dimensional solid-state models of sections of the vascular bed on the basis of data from medical diagnostic equipment in a semi-automatic mode. This approach can significantly reduce the execution time of numerical modeling of hemodynamics of blood vessels.
An Identity Privacy Preserving IoT Data Protection Scheme for Cloud Based Analytics

Efficient protection of huge amount of IoT produced data is key for wide scale data analytic services. The most efficient way is to use pure symmetric encryption as that allows both fast decryption at the analytic engine side as well as energy efficient encryption at the IoT side. However, symmetric encryption can only be performed if there is a way to directly map an encrypted object to the correct key. Typically, such mapping require a unique IoT identity, which constitute a privacy problem. In this paper, we present an IoT identity protection scheme for symmetric IoT data encryption. We give basic security definitions for this problem setting, present a new construction and give security proofs of security level achieved with the construction. Performance figures for a proof of concept implementation are also given. The new scheme gives a fair trade-off between identity privacy and complexity.
Novel Hardware Design of Correlation Function and Its Application on Binary Matrix Factorization Based Features

Machine learning is being used in a wide variety of applications in our daily lives, such as image processing, speech processing, text analysis, stock market, etc. Most of these applications contain a lot of features so that features’ extraction is an important step in the process because of the huge size of raw data. Binary Matrix Factorization is a common method for extracting non-traditional features from the data to be processed. It is a powerful data mining tool. Correlation is one of the ways to check the similarity of data. In this paper, we have proposed a novel hardware design of correlation using Binary Matrix Factorization in order to increase the frequency of operation of this step in machine learning. The goal is to use it as an independent processing unit in portable embedded systems. The target device used for synthesis is xa6slx100-2-fgg484 in Xilinx and simulations were performed in ISim. Propagation delay and hardware utilization analysis has been shown to compare its efficacy with software implementation.
A Method for Realizing Covert Communication at Router Driving Layer

The existing information hiding methods mainly focus on the analysis of the header field of the network protocol and the researches of VoIP. Well, the location of embedded covert data is easy to detect, its capacity is limited and the condition of covert communication is limited. In this paper, we propose a method which builds a covert channel between two routers for transmitting large-capacity information at the driver layer. The router is divided into sender and receiver, both of which mount our own driver and user application, intercept UDP packets generated during the user’s voice or video call with instant message software. We analyze the UDP characteristics and construct UDP meta-model, and then split the secret information into the payload part of the meta-model with CRC check. The forged UDP is sent out with the common UDP traffic. The receiver router intercepts and identifies the forged UDP packets by CRC check and utilizes the obtained forged UDP to restore the original information. Moreover, we exploited WeChat and QQ voice call to conduct numerous simulations of covert communication, and successfully transmitted the secret information transparently from a network-restricted area to a more relaxed area of network supervision, verifying the concealment of the method.
MapReduce Processing with 5G networks

MapReduce processing, which was originally designed to be executed on a cluster of high-performance servers, is also useful for processing data generated at the edge of a network. To support edge computing, we previously developed an approach to enable processing in embedded computers connected through wired or wireless local area networks in a peer-to-peer manner. Here, we extend our approach to give it with the ability to work 5G networks, which connects nodes at the edge to base stations but not directly nodes. This paper describes the extension and its performance. The extension has several contributions in common with other embedded computing systems for 5G networks.
Practical Evaluation Methodology of Higher-Order Maskings at Different Operating Frequencies

FPGA is widely used in the cryptographic devices, such as security co-processor and crypto engine, due to its high speed and customizability. Side-channel analysis is the state-of-the-art method which could recover the secret information in the FPGA through measuring and analysing the power consumption or the electromagnetic radiation. Therefore, side-channel analysis may lead to a potential threat of the security of FPGA. We find that an excessively high operating frequency could cause a pretty serious security vulnerability in the FPGA implementation of a cryptographic algorithm with side-channel countermeasures. And then, how to evaluate the security of the implementation at different operating frequencies is an important question in the practical application. After investigating the physical reason of the information leakage of the FPGA, we propose a generic evaluation methodology derived from CPA and MIA that can be utilized to analyze the security of FPGA implementation of a cryptographic algorithm with side-channel countermeasures at different operating frequencies. By this methodology, the evaluator only needs to collect the measurements when the FPGA operates at an arbitrary frequency rather than collecting the measurement of all possible frequencies exhaustively. Finally, several experiments in an FPGA with AES cryptographic algorithm protected with a masking countermeasure are conducted to illustrate the feasibility of this methodology.
Using Equivalent Class to Solve Interval Discrete Logarithm Problem

The interval discrete logarithm problem (IDLP) is to find a solution n such that $${{g}^{n}}=h$$ in a finite cyclic group $$G\,=\,{<}g{>}$$ , where $$h\in G$$ and n belongs to a given interval. In this paper, we assume that computing the inverse of an element is easier than the multiplication of two elements in a group, and define an equivalent class to be the pair consisting of element and its inverse. So, a kangaroo jump can be performed between equivalent classes through pre-computation on these classes. To accelerate solving IDLP, we first introduce the concept of jumping distance and expanding factor to decide whether to perform the class operation or not. When the value of the expanding factor is greater than a given value, the class operation will be performed, such that each decision on jumps is locally optimal. The improved method takes an average of $$(1+o(1))\sqrt{N}$$ times of class operation, where N is the size of a given interval.
Analysis and Research of Simulated Annealing Algorithm and Parameters

Simulated annealing algorithm (SA) has the performance of jumping out of local extremum and good global convergence. This algorithm can solve many multidimensional problems well. Based on the basic principle, process and characteristics of the simulated annealing algorithm, this paper analyzed and discussed the influencing factors of the algorithm, and emphatically analyzed the selection principles of the simulation annealing algorithm's Metropolis criteria and cooling schedule parameters. In this paper, the annealing process of the object is simulated to solve the problem, that is, the value of the parameter is adjusted, and the appropriate parameter value is finally selected. It is of great significance to the selection of the parameter of the simulated annealing algorithm in solving the multi-dimensional problem.
Iwinac 2017: Assistive intelligence for the elderly

Expert SystemsVolume 37, Issue 2 e12535 EDITORIAL Iwinac 2017: Assistive intelligence for the elderly Mariano Rincón-Zamorano, Mariano Rincón-Zamorano orcid.org/0000-0002-0138-4662 Department of Artificial Intelligence, Universidad Nacional de Educación a Distancia (UNED), Madrid, SpainSearch for more papers by this authorRafael Martínez-Tomás, Rafael Martínez-Tomás orcid.org/0000-0003-4706-7168 Department of Artificial Intelligence, Universidad Nacional de Educación a Distancia (UNED), Madrid, SpainSearch for more papers by this authorJosé Manuel Ferrández, José Manuel Ferrández Department of Electronic and Computer Technology, Universidad Politécnica de Cartagena, Cartagena, SpainSearch for more papers by this author Mariano Rincón-Zamorano, Mariano Rincón-Zamorano orcid.org/0000-0002-0138-4662 Department of Artificial Intelligence, Universidad Nacional de Educación a Distancia (UNED), Madrid, SpainSearch for more papers by this authorRafael Martínez-Tomás, Rafael Martínez-Tomás orcid.org/0000-0003-4706-7168 Department of Artificial Intelligence, Universidad Nacional de Educación a Distancia (UNED), Madrid, SpainSearch for more papers by this authorJosé Manuel Ferrández, José Manuel Ferrández Department of Electronic and Computer Technology, Universidad Politécnica de Cartagena, Cartagena, SpainSearch for more papers by this author First published: 29 February 2020 https://doi.org/10.1111/exsy.12535Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume37, Issue2April 2020e12535 RelatedInformation
Thermal Imagery Based Instance Segmentation for Energy Audit Applications in Buildings

Energy audit in buildings is an essential task for optimal energy management and operations. This paper focuses on a machine learning pipeline to quantify heat loss using 60,000 thermal images in buildings. The images are captured from a small Unmanned Aerial System (sUAS) over the last two years to form a large thermal data repository. Intense efforts are made to annotate multiple sections of the buildings (e.g. windows, doors, ground, facade, trees, and sky). Data augmentation processes are then applied to generate a large comprehensive training data set. Object detection and instance segmentation models such as Mask R-CNN, Fast R-CNN, and Faster R-CNN were trained, and tested. The preliminary results indicate that Mask R-CNN has a larger mean average precision (mAP) of (83%) over R-CNN (51%), Fast R-CNN (62%), and Faster R-CNN (62 %) for a threshold of 50%. The surface temperature values from these thermal images (pixel-by-pixel) were then used in the standard heat transfer coefficient (U-value in BTU/hr/Sq.ft./F) calculations.
AALADIN: Ambient Assisted Living Assistive Device for Internet

Accidents during elderly are one of the greatest geriatric syndromes due to the frequency with which they appear between patients. There are incidents that mark a milestone for acute and chronic deterioration in the health during old age. Among the instruments explored over time by the medical area in order to know the factors that lead to falls in elderly people, the Tinetti test is the most complete and validated measurement instrument. Tinetti is an observational scale that allows the evaluation by means of two sub-scales (i) the march (9 items) and (ii) the balance (13 items) in static position and when the patient is moving. Generally, this test is performed by specialized medical personnel (doctors or physiotherapists) and the acquisition of data used in each one of the items in this test is recorded manually. This paper presents the design and construction of an Assistive Technology Device, which supports medical personnel during the application of the balance sub-scale in the Tinetti test. This solution will consist of a carpet equipped with sensors that allows to know the position of the patient through heat maps and the body weight that is distributed in each area during the performance of the Tinetti test. In addition, it will allow the acquisition of data in a digital form, and since it is an object of the Internet of Things, it will allow the monitoring of the information coming from the test locally and remotely, as well as registering the information and making it available on the cloud.
Form and Contents of Award

Article 31 is typically associated with the formalities of arbitral awards. Given that this is the first time in the Model Law that significant – as opposed to mere passing – reference is made to the award, it is necessary to examine the legal nature of awards. The travaux to the 1986 version of the Model Law does not demonstrate significant differences from the current version, save for the fact that paragraph 4 (on delivery of the award to the parties) was not included in the first draft. This was added a little later and is identical to its current wording.
The Technological Imagination

This final chapter is concerned with two kinds of “what-if” questions. The first of these focus on the speculative questions which have realisable answers, so an example would be: what if we could interact with our TV (or any other home technology) by simply speaking to it or gesturing at it? These first kinds of questions have received our attention in Chaps. 3 , 4 and 5 . Some are at the speculative end of HCI, but others are pretty much mainstream. Although these technologies rely on imagination and make-believe, the literature, of course, offers little or no mention of their contribution in the operation of the associated technologies. The second kinds of speculative questions reject the very idea of technological solutions and these are the design fictions. Design fictions have numerous but more-or-less complementary definitions: for some they are design research tools; for others they are intended to be provocative prototypes which bridge the modern world and the make-believe world described in science fiction; for others, they are “never to be commercial” thought experiments. All-in-all, they are speculative, that is, they are products of our imaginations. Indeed, more than anywhere else in HCI, we find frequent reference to the imaginary and the fictional. They occupy the extreme end of the technological imagination which I cannot help but imagine is the left side, the sinister end of the spectrum.
Quantum Key Sharing Protocol Using GHZ Like States in Multiparty Scheme

Key sharing is the most important aspect in any cryptographic algorithm whether it is classical or quantum cryptography. Quantum key distribution (QKD) is the procedure by which secret keys required for cryptographic protocols can be shared or distributed. Thus, they remain private among the communicating parties only. Recent works show that quantum keys can be created by using Greenberger–Horne–Zeilinger (GHZ) states. Here, we have shown that a quantum key sharing protocol can be realized using GHZ like states too. Three parties can create a quantum key in the form of random strings. By the law of quantum mechanics, our realization in this work is totally secure under different kinds of attacks.
DNN-based Hyperspectral Image Denoising with Spatio-spectral Pre-training

We propose a method for DNN-based hyperspectral image denoising. In recent years, many methods have been proposed for applying deep learning to the problems of restoring grayscale and color images, and their performance has exceeded that of conventional methods. For these deep learning methods to succeed, great contributions are made to large data sets that are sufficient for demonstrating the performance of learning systems. However, for hyperspectral images, it is often difficult to obtain such a large data set. In this paper, we study a denoising network that uses a separable CNN combining point-wise and depthwise convolution to tackle the problem of hyperspectral image restoration. To address the data shortage problem, we propose a pre-training method that trains two types of convolutional layers in the separable network by using two-dimensional images and one-dimensional spectral information. In this way, it is possible to perform training effectively even in cases where only a small number of hyperspectral images are available. As a result, we show that it is possible to achieve better denoising performance than conventional model-based state-of-the-art methods.
On multiplicative independence of rational function iterates

Abstract We give lower bounds for the degree of multiplicative combinations of iterates of rational functions (with certain exceptions) over a general field, establishing the multiplicative independence of said iterates. This leads to a generalisation of Gao’s method for constructing elements in the finite field $${\mathbb {F}}_{q^n}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>F</mml:mi><mml:msup><mml:mi>q</mml:mi><mml:mi>n</mml:mi></mml:msup></mml:msub></mml:math> whose orders are larger than any polynomial in n when n becomes large. Additionally, we discuss the finiteness of polynomials which translate a given finite set of polynomials to become multiplicatively dependent.
Robust, Evidence-Based Data Fusion

This paper presents a strategy for determining system state estimates from unreliable and noisy system inputs. The concepts of sensor error orthogonality, meta-sensors, output equivalence, and adaptive state estimation are discussed. Although the proposed data fusion strategy is applicable to a large range of both 2-D and 3-D applications that consume unreliable inputs to support real-time control, an autonomous ground vehicle is used as a motivating example.
Automatic Generation of Pictorial Maps from Photos on Social Media to Represent Regional Features

In recent years, with the spread of smartphones and SNSs, billions of photos have been posted on SNSs. Photographs from different locations show different charms of each region. This paper introduces a system for automatic generation of pictorial maps using geotagged photographs posted on Flickr. The proposed system can extract the most representative photograph of each region automatically and can generate pictorial maps with the extracted photographs. Generated pictorial maps can be used to help people to discover the unique charms and cultures of a region in an easy-to-understand manner and the proposed system can also be applied to various web services such as geographic search engines, travel apps and so on.