Reviewerly/exHarmony huggingface dataset:
Composite Sorbent Filter Material on the Basis of Man-Caused and Minerals

It is about problems in purification of industrial wastewater and utilization of solid wastes as raw materials resources which are needed a scientific way of studying. The way of generation composite granular sorbent filter material on the basis of man-caused and minerals, using which is allowed to increase ecological safety food industry enterprise because of using waste conversion technique, as well modern methods of sorption purification , is offered and described here. A detailed chemical composition, which consists of tobacco dust and natural component as bentonitic clay, using for getting granular sorbent filter material, is studied. They studied real industrial wastewater to make researches for the detection residual impurity in the filtrate using composite granular sorbent filter material.
The mixture problem in flake analysis: Allocating flake samples to segments of reduction using CLSR methods

Flake assemblages often are mixtures from knapping episodes that vary by reduction mode or stage. Stahle and Dunn (1982) developed a constrained least-squares regression (CLSR) method to allocate hypothetically mixed chert assemblages to successive biface-reduction stages, a partial solution to the mixing problem. ConReg is a recently developed alternative, validated against Stahle and Dunn's and our own experimental controls from replication of obsidian biface preforms. Using both controls, we apply ConReg to the “unmixing” of flake assemblages from North American Great Basin obsidian quarries. Controls produce different solutions; their separate comparison to independent analytical results of stage composition favor ConReg used with our controls. What appeared to be relatively similar early “stage” assemblages are resolved to finer proportional allocation across wider ranges of the reduction continuum, in the process showing considerable variation between samples that otherwise might escape detection. The mixture problem is a challenge to all approaches to flake analysis, not just mass analysis, but one that ConReg can help us surmount.
Driver Assistance in Fog Environment Based on Convolutional Neural Networks (CNN)

Driver Assistance Systems (ADAS) are designed to assist the driver and improve road safety. For this, various sensors are generally embedded in vehicles to alert the driver in case of danger present on the road. Unfortunately, the performance of such systems degrades in the presence of adverse weather conditions. In addition, eliminating the fog of a single image captured by a camera is a very difficult and ill-posed phenomenon in Advanced Driver Assistance Systems (ADAS). Recent developments in the field of deep learning have allowed researchers to build relevant models using various tools available. We propose in this paper a new architecture based on fast R-CNN for the detection of objects in fogged images, and a convolutional neuron network (CNN) is designed on the basis of a reformulated model of atmospheric diffusion for fog elimination to restore the sharp image.
Event Extraction Using Transportation of Temporal Optical Flow Fields

In this paper, we develop a method to transform a sequence of images to a sequence of events. Optical flow, which is the vector fields of pointwise motion computed from monocular image sequences, describes pointwise motion in an environment. The method extracts the global smoothness and continuity of motion fields and detects collapses of the smoothness of the motion fields in long-time image sequences using transportation of the temporal optical flow field.
Data-Driven Analysis of Tiny Touchscreen Performance with MicroJam

The widespread adoption of mobile devices, such as smartphones and tablets, has made touchscreens a common interface for musical performance. New mobile musical instruments have been designed that embrace collaborative creation and that explore the affordances of mobile devices, as well as their constraints. While these have been investigated from design and user experience perspectives, there is little examination of the performers' musical outputs. In this work, we introduce a constrained touchscreen performance app, MicroJam, designed to enable collaboration between performers, and engage in a novel data-driven analysis of more than 1600 performances using the app. MicroJam constrains performances to five seconds, and emphasises frequent and casual music making through a social media-inspired interface. Performers collaborate by replying to performances, adding new musical layers that are played back at the same time. Our analysis shows that users tend to focus on the centre and diagonals of the touchscreen area, and tend to swirl or swipe rather than tap. We also observe that while long swipes dominate the visual appearance of performances, the majority of interactions are short with limited expressive possibilities. Our findings are summarised into a set of design recommendations for MicroJam and other touchscreen apps for social musical interaction.
A Dynamic Interoperability Model for an Emergent Middleware Framework

Standard middleware platforms are unable to cope with extreme heterogeneity and dynamicity of distributed systems. With new trends in mobile/pervasive applications, distributed systems are required to connect to one another at run time, implying that heterogeneities arising in systems need to be resolved on the fly. This ability of a system to interact with a different system is known as interoperability. More advanced solutions, which exceed the state-of-the-art in middleware, are required to handle interoperability on the fly. This paper investigates the challenges of enabling dynamic interoperability for the domain of vehicular ad-hoc networks (VANETs). The paper uses semantic web technologies to help devise an emergent middleware to enable different VANETs to interact with each other at runtime. An ontology-based framework coupled with an experimental evaluation of the framework is presented. The need for linguistic techniques in assisting ontologies is also emphasized in the framework.
Simulation model framework design for complex communication network of satellite navigation system based on SMP2.0

Summary The complex communication network of satellite navigation system (SNS‐CCN) possesses the characteristics such as large scale, complicated architecture, and integrated satellite earth. Composite modeling and simulation take significant roles in solving large‐scale system simulation issues, as far as one concerned, the solution has not been proposed in the field of SNS‐CCN yet. According to the simulation of information flow for SNS‐CCN, this paper proposes a composite framework of simulation model based on SMP2.0 while applied with combination modeling methods, and then proposes a development and integration method for component structure and simulation service structure, which can support the composite modeling and make appropriate simulation service extensions according to the request. Then, we develop an information flow verification simulation system for SNS‐CCN with the proposed development and integration method of simulation model.
Solutions for library collection digitization: The experience of the Far Eastern Federal University Scientific Library

The experience of the E-library Department of the Far Eastern Federal University Scientific Library in digitizing the library collections is examined. The technological problems are discussed. The choice of TIFF graphic format for scanning and the PDF – for storing user copies is substantiated. Free license program IrfanView, a graph editor with a scanning embedded function which speeds up and smoothens the process, is suggested as an alternative scanner software. To ease and speed up the labor-intensive process of graphic images editing to supplement standard software, the author suggests to use FastStone Image Viewer, a free license program. The FastStone Image Viewer offers the useful function of edited graphic images batch processing, in particular conversion to PDF with simultaneous document compression which saves the digital depository storage volume. The suggested alternative programs, online resources, and methods to eliminate scanning defects, as described by the author, would significantly lighten the work of digitization specialist.
A Comparative Analysis of Breadth First Search Approach in Mining Frequent Itemsets

The ensuing paper contrasts the algorithms using breadth first search technique of mining frequent itemset. The Apriori algorithm is a well-known algorithm which adopts breadth first search approach to mine frequent itemsets. The process of finding the frequent itemsets is simple for smaller database and complex for larger databases. Candidate itemset generation is a major disadvantage for Apriori algorithm. In this research paper, the proposed BFS-LP-Growth algorithm is compared with another breadth first search algorithm Apriori. The proposed BFS-LP-Growth algorithm overcomes the limitation of Apriori algorithm by processing the database twice and also avoids the exploration of candidate itemset. The structure of LP-Growth algorithm makes the proposed BFS-LP-Growth algorithm more advantageous. The breadth first search enhances the performance of the proposed BFS-LP-Growth algorithm by creating subheader table which avoids the necessity of conditional pattern base and conditional LP-tree. Standard databases used for comparison are Chess and Mushroom. Based on the results, we find that the proposed BFS-LP-Growth algorithm is more worthwhile than the Apriori algorithms as execution time is low and the need for candidate patterns is diminished.
Wavelets for Differential Equations and Numerical Operator Calculus

Differential equations are commonplace in engineering, and lots of research have been carried out in developing methods, both efficient and precise, for their numerical solution.Nowadays the numerical practitioner can rely on a wide range of tools for solving differential equations: finite difference methods, finite element methods, meshless, and so on.Wavelets, since their appearance in the early 1990s, have attracted attention for their multiresolution nature that allows them to act as a "mathematical zoom," a characteristic that promises to describe efficiently the functions involved in the differential equation, especially in the presence of singularities.The objective of this chapter is to introduce the main concepts of wavelets and differential equation, allowing the reader to apply wavelets to the solution of differential equations and in numerical operator calculus.
Structure of Professional and Business Communication of Graduates Majoring in Innovation

Verbal activity is always directed, i.e. the subject of communication determines its scope. This pattern conditions both choice and arrangement of the teaching material, i.e. its content and structure, as well as development of verbal skills, its motivation (e.g., cognitive interest), and acts primarily in the field of the content of training material and organization of the pedagogical process and, accordingly, methods, goals and means of instruction. The article attempts to establish, firstly, the subject of professional and business activities of graduates majoring in Innovation and to describe it; secondly, based on the characteristics found, to outline the scope of professional activity; thirdly, to establish the subject of professional and business communication of graduates in the specialty given and, consequently, to determine the scope of professional and business communication. In addition, the authors consider the situational structure of professional and business communication. Hence, the approaches suggested can be used as a basis to develop methods for training such skills as speaking and writing, and allow revealing the content of communicative competence of graduates majoring in Innovation.
Philosophical Problems of Multi-Agent Systems Modeling

Multi-agent systems (MAS) is a technology based on distributed computing, designed to emulate the complex emergent behavior of multiple agents on the basis of various feedback mechanisms. Philosophical interest therein is caused, firstly, by the cognitive properties of individual agents and of the system as a whole; secondly, with the possible modeling of complex social behavior and, possibly, by the perspective of a progress in social understanding. The main problem is the extent to which multi-agent models correspond to the simulated reality. Since they are computing systems, it is necessary to consider the general theory of computations and their ontological status; to determine how the computational processes form rule-like systems consisting of multiple cognitively enabled agents; to make plausible assumptions about the regularities of the evolution of such systems under natural and artificial conditions. Particular attention is paid to the hypothesis of the limited rationality of agents or, what is the same, to their cognitive limitations, which demands the application of epistemic logic formalism to MAS functioning. The obtained results give additional arguments in favor of the well-known philosophical thesis: the higher cognitive capabilities are determined and explained by the complex social organization of their bearers.
BUNDER’S PARADOX

Abstract Systems of illative logic are logical calculi formulated in the untyped λ -calculus supplemented with certain logical constants. 1 In this short paper, I consider a paradox that arises in illative logic. I note two prima facie attractive ways of resolving the paradox. The first is well known to be consistent, and I briefly outline a now standard construction used by Scott and Aczel that establishes this. The second, however, has been thought to be inconsistent. I show that this isn’t so, by providing a nonempty class of models that establishes its consistency. I then provide an illative logic which is sound and complete for this class of models. I close by briefly noting some attractive features of the second resolution of this paradox.
Employing 3D Printing to Fabricate Augmented Reality Headsets for Middle School STEM Education

This chapter examines the theories, strategies, and techniques for employing 3D printing technologies to fabricate education-appropriate augmented reality (AR) headsets and provides a concrete example of an AR headset that the authors developed. The chapter begins by discussing theories and historically relevant events that provide a context for the chapter's narrative about use of 3D printers to support AR in education. Next, the chapter presents the strategies that were employed while developing and 3D fabricating a custom-designed AR headset that was intended for supporting middle school students learning science and mathematics content knowledge. Afterward, the chapter provides directions and resources for the reader describing how to build the presented AR headset design themselves by using a 3D printer and affordable electronic components, as well as information about how to join the Maker community and participate in the designing and producing of similar projects. Lastly, the chapter delivers a summarization of all findings discussed.
Sequent Calculi for Normal Update Logics

Normal update logic is the temporalization of normal conditional logic. Sequent calculi for the least normal update logic $$\mathbf {UCK}$$ by Andreas Herzig (1998) and some of its extensions are developed. The subformula property of these sequent calculi is shown by Takano’s semantic method. Consequently we prove the finite model property and decidability of these sequent calculi.
Improvement of geometric calibration algorithm with collinear constraints

With digital cameras coming into wide-spread use and the intelligence in application system increasingly growing, 3D reconstruction has become an essential part of the vision system. For the sake of achieving it, geometric camera calibration in the context of three-dimensional machine vision must be performed firstly to determine a set of parameters that describe the mapping between 3-D reference coordinates and 2-D image coordinates. In the typical classic method with high calculation accuracy and strong robustness, however, little attention has been paid to initial values of distortion coefficients, and model constraints that make results global optimal. In this paper, we present an improved algorithm based on the traditional calibration method. First, determine exact homography matrices by RANSAC algorithm to reject more error points, solve the initial values of distortion with distortion model, and then constrain the image coordinates of feature points in line by straight lines. Finally, the whole optimized parameters, the suppression of re-projection errors, and the calibration parameters with higher precision are obtained. It becomes a prerequisite for the realization of image fusion and the wide application of computer vision in the field of 3D reconstruction.
Parallelization of the DIANA Algorithm in OpenMP

Global data production has been increasing by approximately 40% per year since the beginning of the last decade. These large datasets, also called Big Data, are posing great challenges in many areas and in particular in the Machine Learning (ML) field. Although ML algorithms are able to extract useful information from these large data repositories, they are computationally expensive such as AGNES and DIANA, which have O(n) and O(2n) complexity, respectively. Therefore, the big challenge is to process large amounts of data in a realistic time frame. In this context, this paper proposes the parallelization of the DIANA OpenMP algorithm. Initial tests with a database with 5000 elements presented a speed up of 5,2521. It is believed that, according to Gustafson’s law, for a larger database the results will also be larger.
A Novel Parameter-Light Subspace Clustering Technique Based on Single Linkage Method

Subspace clustering is a challenging high-dimensional data mining task. There have been several approaches proposed in the literature to identify clusters in subspaces, however their performance and quality is highly affected by input parameters. A little research is done so far on identifying proper parameter values automatically. Other observed drawbacks are requirement of multiple database scans resulting into increased demand for computing resources and generation of many redundant clusters. Here, we propose a parameter light subspace clustering method for numerical data hereafter referred to as CLUSLINK. The algorithm is based on single linkage clustering method and works in bottom up, greedy fashion. The only input user has to provide is how coarse or fine the resulting clusters should be, and if not given, the algorithm operates with default values. The empirical results obtained over synthetic and real benchmark datasets show significant improvement in terms of accuracy and execution time.
A VLSI Architecture for the PRESENT Block Cipher with FPGA and ASIC Implementations

The infrastructure of internet-of-things (IoT) and cyber-physical systems (CPS) is based on the security of communicated data. Here, lightweight cryptography plays a vital role in IoT/CPS resource-constrained environments. In this paper, we propose an architecture for the PRESENT lightweight block cipher and its VLSI implementations in an FPGA and ASIC. The input-output ports of the architecture are registered and datapath is based on 8-bit. It requires 49 clock cycles for processing of 64-bit plaintext with 80-bit user key. The FPGA implementation of the proposed architecture is done in Xilinx Virtex-5 device in comparison to an existing design improved performance has been obtained. Further, an ASIC implementation of the architecture is done in SCL 180 nm technology where gate equivalent (GE) of the design is 1608 GEs and area of chip is 1.55 mm2. At 100 MHz operating frequency, total power consumption of the chip is 0.228 mW. A throughput of 130.612 Mbps, energy 112.15 nJ, energy/bit 14.018 nJ/bit, and 0.813 efficiency is obtained.
Hiding in Plain Sight - Symmetric Key Chaotic Image Encryption by Sequential Pixel Shuffling

Security of personal information is affirmation of the right to privacy. With increasing data requirements of consumers and the bulk of archival information thereby created needs storage space and here cloud storage comes to the rescue, which however is prone to cyber attacks and needs better data security protocols as time changes. In this paper, we propose a novel symmetric-key image encryption scheme by shuffling the pixels which renders the information unintelligible. We show how our technique provides an additional layer of security on top of the regular encryption techniques. We analyze our algorithm by performing statistical and difference attack tests. We also discuss the brute force attack and its viability. The results validate effectiveness of our encryption scheme.
Classification Methods in Colon Disease Information System

This paper presents the process of building a new logistic regression model, which aims to support the decision-making process in medical database. The developed logistic regression model, J48 classifier and Random Tree algorithm define the probability of the disease and indicates the statistically significant changes that affect the onset of the disease. In our work, we attempted to build a classifier that would classify patients undergoing ulcerative colitis and other conditions within the lower gastrointestinal tract. The value of probability can be treated as one of the feature in decision process of patient’s future treatment.
Nonhomogeneous Risk Rank Analysis Method for Security Network System

Security measures for a computer network system can be enhanced with better understanding the vulnerabilities and their behavior over the time.It is observed that the effects of vulnerabilities vary with the time over their life cycle.In the present study, we have presented a new methodology to assess the magnitude of the risk of a vulnerability as a "Risk Rank".To derive this new methodology well known Markovian approach with a transition probability matrix is used including relevant risk factors for discovered and recorded vulnerabilities.However, in addition to observing the risk factor for each vulnerability individually we have introduced the concept of ranking vulnerabilities at a particular time taking a similar approach to Google Page Rank Algorithm.New methodology is exemplified using a simple model of computer network with three recorded vulnerabilities with their CVSS scores.
Allowance for the Earth’s Surface Topography in Processing the Magnetic Field Measurements

The questions concerning the allowance for the Earth’s surface topography in the measurements of the magnetic field in mountainous regions are considered. The new method is suggested for estimating the influence of the sharply contrasting relief composed of the strongly magnetized rocks on the results of the field observations. The method uses the decomposition of the magnetic field and elevation data in the empirical modes with subsequent application of the method of group allowance for arguments. The results of reducing the airborne magnetic survey carried out n the northwestern part of the Siberian platform above the copper-nickel ore deposit are presented.
A Certificate-Less Key Exchange Protocol for IoT

Diffie-Hellman key exchange is a popular cryptographic algorithm that allows Internet protocols to agree on a shared key and negotiate a secure connection. It is used in many protocols including SSH, IPsec, SMTPS, and protocols that rely on TLS. In the Internet of Things (IoT), we cannot rely on the PKI architecture to secure communications due to the growing number of connected things. We are proposing to decentralize the encryption keys management while maintaining the property of authentication and secrecy. We use the ability of each node to build a private channel to create a shared key, safe from the eye of an attacker. Our solution provides a solution to build a certificate-less trusted ecosystem for IoT.