Reviewerly/exHarmony huggingface dataset:
Topology-Based 3D Reconstruction of Mid-Level Primitives in Man-Made Environments

In this paper a novel reconstruction method is presented that uses the topological relationship of detected image features to create a highly abstract but semantically rich 3D model of the reconstructed scenes. In the first step, a combined image-based reconstruction of points and lines is performed based on the current state of art structure from motion methods. Subsequently, connected planar three-dimensional structures are reconstructed by a novel method that uses the topological relationships between the detected image features. The reconstructed 3D models enable a simple extraction of geometric shapes, such as rectangles, in the scene.
Online course: GDPR essentials

This course summarises the key contents of the General Data Protection Regulation and explains what the key changes are and what needs to be done in response to them.
PICTURE ETUDE “SUFI AND BUDDHA” BY T. SHAHIDI IN THE CONTEXT OF “NEW SACREDNESS” TRENDS IN COMPOSER’S CREATIVE WORK

The article considers the picture etude “Sufi and Buddha” by the Tajik composer Tolib Shahidi in the aspect of the “new sacredness” trend in contemporary composer’s creativity. The work embodies the modern artist’s view on the problem of similarities and differences between the two religious conceptions. As a result of the analysis, the universal and specific parameters characterizing Sufi and Buddha are revealed. Commonness is represented by the musical arsenal designed to convey meditativeness. At the same time, each representative of the religious teaching has its own intonation sphere.
A Digital Tool to Understand the Pictorial Procedures of 17$$^\mathrm{th}$$ Century Realism

To unveil the mystery of the exquisitely rendered materials in Dutch 17th century paintings, we need to understand the pictorial procedures of this period. We focused on the Dutch master Jan de Heem, known for his highly convincing still-lifes. We reconstructed his systematic multi-layered approach to paint grapes, based on pigment distribution maps, layers stratigraphy, and a 17th century textual source. We digitised the layers reconstruction to access the temporal information of the painting procedure. We combined the layers via optical mixing into a digital tool that can be used to answer “what if” art historical questions about the painting composition, by editing the order, weight and colour of the layers.
Interactive Print Media Using Augmented Reality

Augmented Reality is one of the revolutionary technologies gaining fast pace in enhancing user interaction. Education is evolving rapidly and needs to keep accomplishing its goal of providing knowledge seamlessly. The use of mere images in print media like textbooks limits learner’s understandability. A much more interactive approach is required to boost the overall learning experience. The existing systems are quite capable of delivering useful content such as 3D models, by using special markers for tracking done in images. This limits their potential as it is not feasible to create markers for every image and is time-consuming. This research work focusses on developing an Android application using Marker-less AR. The proposed system encompasses image recognition using a mobile camera, rendering relevant YouTube videos pertaining to the image, and their superimposition in AR. The aim of this system is to enhance the productivity of education to enliven images with interactive videos.
Detection of Pedestrians Based on the Fusion of Human Characteristics and Kernel Density Estimation

The kernel density estimate does not need to have the characteristic distribution hypothesis to the background, it also does not require the estimation parameter, and it can deal with the moving target detection under the complex background, but the kernel function bandwidth choice uniformly puzzles the algorithm application. To solve this problem, this paper proposes a fusion method of human body characteristics and kernel density estimation for pedestrian detection. Firstly, the kernel function bandwidth is chosen by the prior information of moving target, then the foreground (moving target) is extracted based on kernel density estimation, finally, using human features to detect video pedestrians. The experimental results show that the calculation of kernel density estimation is reduced by comparing introduction of prior information with traditional methods, and the pedestrian and no pedestrian can be detected accurately by the interference of light variation and noise.
Convolutional Photomosaic Generation via Multi-scale Perceptual Losses

Photographic mosaics (or simply photomosaics) are images comprised of smaller, equally-sized image tiles such that when viewed from a distance, the tiled images of the mosaic collectively resemble a perceptually plausible image. In this paper, we consider the challenge of automatically generating a photomosaic from an input image. Although computer-generated photomosaicking has existed for quite some time, none have considered simultaneously exploiting colour/grayscale intensity and the structure of the input across scales, as well as image semantics. We propose a convolutional network for generating photomosaics guided by a multi-scale perceptual loss to capture colour, structure, and semantics across multiple scales. We demonstrate the effectiveness of our multi-scale perceptual loss by experimenting with producing extremely high resolution photomosaics and through the inclusion of ablation experiments that compare with a single-scale variant of the perceptual loss. We show that, overall, our approach produces visually pleasing results, providing a substantial improvement over common baselines.
A model for soil moisture dynamics estimation based on artificial neural network

Research on soil moisture estimation models can effectively improve the growth environment of crops. In this paper, the author studied the artificial neural network and variation pattern of soil moisture. Then, application of the model for water diversion estimation was explored based on artificial neural network. On this basis, an optimization algorithm was presented to simulate water diversion. Furthermore, a model for remote sensing of soil moisture dynamics was applied to artificial neural network. It has been proven that the research can optimize the application of the proposed model, laying a solid foundation for future study.
What Kind of Research Do We Want?

From January 1, 2012 - December 31, 2016, David Salisbury and Andrew Schwarz served as Editors-in-Chief of The DATA BASE for Advances in Information Systems. In this reflection, the former editors-in-chief share how their relationship with this publication as well as their own partnership emerged over time. Salisbury and Schwarz share some of their major accomplishments while serving in this role as they sought to develop and promote this publication during their tenure.
Convexity, Majorization and Time Optimal Control of Coupled Spin Dynamics

In this chapter, we study some control problems that derive from time optimal control of coupled spin dynamics in NMR spectroscopy and quantum information and computation. Time optimal control helps to minimize relaxation losses. In a two qubit system, the ability to synthesize, local unitaries, much more rapidly than evolution of couplings, gives a natural time scale separation in these problems. The generators of unitary evolution, g , are decomposed into fast generators k (local Hamiltonians) and slow generators p (couplings) as a Cartan decomposition g = p ⊕ k . Using this decomposition, we exploit some convexity ideas to completely characterize the reachable set and time optimal control for these problems. The main contribution of the chapter is, we carry out a global analysis of time optimality.
Development of the Competence Evaluation Coordinated the Learning Materials and Teaching Methods

The objectives of this research were to develop the competence evaluation for the global engineer resource development coordinated the learning materials and teaching methods. We could determine that the generic skill concerning the global engineer development consisted of three axes: the critical thinking and the collaborative thinking, the creative thinking. We built the assessment rubric and problem-posing manual for evaluating generic skill. This research based on an international test involving five countries including Japan, estimated these results:We could understand that the characteristics of competence depended on engineering education in each country. As the grade rose, total of competences tended to rise. In every grade, the score of critical thinking became high, and the collaborative thinking score became low. This meant that the learning materials and teaching methods of engineer development agreed with growing of the critical thinking.
A Digital Decision Support System for Efficient Policing in Urban Security in a Community Policing Context

The community era of policing emphasizes the crime control function through a decentralized organization design. The diversification and evolution of crime made evident the value of citizen contribution towards its combating. The introduction of the directives of General Data Protection Regulation (GDPR) and Data Protection for Police and Criminal Justice Authorities (PCJA) call for privacy and security by design software implementations that preserve ownership to the data source and use by other bodies only under certain circumstances. This chapter presents aspects concerning the implementation of, web and mobile, terminals as part of a greater architecture, for citizens and Police authorities, capable of fulfilling data privacy and security needs. Two separate access control layers have been developed: one for defining architectural policies and the other for controlling runtime operations for matching use preferences. Within the perspective of end user devices, data availability and system performance are discussed targeting: improved early warning and identification of public safety and security risks, enhanced crime reporting by allowing citizens and community to report incidents and perceived offences/crime more efficiently and effectively, enabling more proficient timely intervention.
A Comparison of Two Cache Augmented SQL Architectures

Cloud service providers augment a SQL database management system with a cache to enhance system performance for workloads that exhibit a high read to write ratio. These in-memory caches provide a simple programming interface such as get, put, and delete. Using their software architecture, different caching frameworks can be categorized into Client-Server (CS) and Shared Address Space (SAS) systems. Example CS caches are memcached and Redis. Example SAS caches are Java Cache standard and its Google Guava implementation, Terracotta BigMemory and KOSAR. How do CS and SAS architectures compare with one another and what are their tradeoffs? This study quantifies an answer using BG, a benchmark for interactive social networking actions. In general, obtained results show SAS provides a higher performance with write policies playing an important role.
A GPU-based parallel WFST decoder on nnet3

One performance-intensive part of automatic speech recognition is the weighted finite-state transducer (WFST) decoding. To solve the problem, we expand parallel Graphics Processing Units (GPU) computing to the decoding period. We describe extension work based on Kaldi toolkit for speech recognition research. Our work can support weighted finite-state transducer decoding on Kaldi neural nets with CUDA toolkit. Our paper also expands an efficient parallel Viterbi beam decoding algorithm to decrease the speech recognition Real Time Factor (RTF) value. Together with our optimization algorithm, we have reached 2.3x speed up on the AISHELL corpus decoding. We also implement nnet3 decoder that improves real-time speed up with no word error rate raise.
Optimization of SURF Algorithm for Image Matching of Parts

SURF algorithm, which is featured with high speed and good robustness, is a common algorithm for feature points detection. But this algorithm has such drawbacks as the separating capacity of its feature points descriptor is low and principal direction of feature points is not accurate, which can easily cause less image matching pairs and high mismatching ratio. Therefore, an improved SURF algorithm is proposed to increase matching pairs effectively and raise accuracy of matching. For the algorithm, two new-type feature sets are added, and 128-dimensional feature descriptor is established. The method of combining Euclidean distance with cosine similarity match is adopted to match feature points. Then RANSAC method is used to lower mismatching ratio, thus achieving robots’ parts-matching in the indoor environment. The experiment result shows that under the conditions of images rotating, zooming, blurring, lighting and view change, the improved algorithm has better robustness. Besides, its matching ratio and accuracy are higher than standard SURF algorithm.
A Novel Symmetric Searchable Encryption Scheme for String Identification in Cloud Computing

In this paper, we first provide an efficient and easy-to-implement symmetric searchable encryption scheme (SSE) for string search, Unlike previous schemes, we use hash chaining instead of chain of encryption operations for index generation, which makes it suitable for lightweight applications. Here it’s first to propose probabilistic trapdoors in SSE for string search. We provide concrete proof of non-adaptive security of our scheme against honest-but-curious server based on the definitions . Here also introduce a new notion of search pattern privacy, which gives a measure of security against the leakage from trapdoor. i have shown that our scheme is secure under search pattern in distinguishability definition. i show why SSE scheme for string search cannot attain adaptive in distinguishability criteria as mentioned and  also propose modifications of our scheme so that the scheme can be used
A New DNA-Combining Chaos Scheme for Fast and Secure Image Encryption

This paper aims to introduce a new secured image encryption scheme base on Peace Wise Linear Chaotic Map (PWLCM) and DeoxyriboNucleic Acid (DNA) encoding. The first step is to increase the entropy of the original image by applying a dynamical XOR operation through all the pixels of the image. To satisfy security requirement inherent to an encryption algorithm, PWLCM random sequences are combined with DNA encoding rules, picked randomly among 8 rules available, in order to generate a DNA OTP-key used for encryption. The last step is to replace every pixel of the image with a randomly chosen index that corresponds to one index of occurrence of its DNA equivalent in the OTP-key following an S-BOX strategy. Experimental results show that this encryption algorithm is fast and efficient compared to existing solutions, but also secure to various types of attacks such as statistical attacks, differential attack or brute-force attacks.
Security Requirements for Cloud Environments: The Public Cloud Case

A company planning to implement a public cloud solution should be aware of the risks associated with cloud computing. This is due to the rapidly evolving threats to cloud security that are emerging at an increasing rate in recent years, also to multi-tenant and open nature of the public cloud. Cloud computing is a powerful technology in IT environment and to take advantage of all the benefits of cloud computing, it is necessary to have security and privacy requirements for the implementation and use of the cloud. A risk analysis must be done initially with a cloud provider in order to identify the existing vulnerabilities and to implement the measures to counter those threats. This paper explores the key issues surrounding cloud security, and passes on valuable guidance about not only information security and broadly risk. Also, it will help providers to make informed security decisions about their diverse cloud set-ups and better understand how to reap all the benefits of cloud without compromising their organizations’ security. As well, it discusses the security requirements, and various risks related to the public cloud.
Detection of Unseen Low-Contrast Signals Using Classic and Novel Model Observers

Automatic task-based image quality assessment has been of importance in various clinical and research applications. In this paper, we propose a neural network model observer, a novel concept which has recently been investigated. It is trained and tested on simulated images with different contrast levels, with the aim of trying to distinguish images based on their quality/contrast. Our model shows promising properties that its output is sensitive to image contrast, and generalizes well to unseen low-contrast signals. We also compare the results of the proposed approach with those of a channelized hotelling observer (CHO), on the same simulated dataset.
Framework Architecture for Querying Distributed RDF Data

Today, the Web knows a rapid increase in data level that makes their processing and storage limited in traditional technologies. That is why future technology tries to exploit the notion of semantics and ontology by adapting them to big data technology to allow a fundamental change in the access to voluminous information in the web. That Intended to have a complete and relevant response to the user request. Our research work focuses on the semantic web. Focus exactly on the semantic search on many data expressed by RDF (Resource Description Framework) in distributed system. The semantic language proposed by W3C (World Wide Web Consortium) provides the formalism necessary for the representation of data for the Semantic Web. However, only a knowledge representation format is insufficient and we need powerful response mechanisms to manage effectively global and distributed queries across a set of stand-alone and heterogeneous RDF resources marked by the dynamic and scalable nature of their content.
A Dialogue of Social Philosophy with W. Whewell’s Logic of Science

In the 21 st century, there is a turn of thinking toward its reorientation first of all to the human as an author of thought and not to the nature, existing independently of us and of the process of scientific knowledge obtaining. It is possible to see the difference of these two types of thinking (classical and non-classical) in the context of dialogue between W. Whewell’s philosophy and the scientific investigations after the scientific revolution in the beginning of the 20 th century. In the philosophy of 21 st century, man is a social being and this is the basis of social philosophy (social epistemology). The artificial world around us is created by a human, it has its foundation in the laws of thinking but not the laws of nature. The foundations of both systems are quite different. In what way can we achieve mutual understanding between them? From both sides some aspects can be put forward, for instance, the concept of a mediator (carrier) of a thought. This concept is studied actively by W. Whewell and by philosophers of our time, and this leads in both cases to some unexpected interpretation of the basic question of philosophy: the border between thing and thought is becoming less noticeable. We can come to the same result, going by different ways. Whewell finds common qualities for some group of things. Social philosophers are interested in what makes things different. Not one of these idealizations corresponds completely to the reality. Always something is not taken into consideration. A thinker chooses out of real world some of its characteristics that become a basis of a thought system, which explains everything but in its own way. The paper demonstrates the way of possible creation of a new type of thinking.
3D Path Planning for Quadrotor Using Gazebo Simulator

This research explores the 3D path planning for quadrotor, which is an unmannedaerial vehicle (UAV) with four rotors. The quadrotor is simulated using robot operating system(ROS) and Gazebo software, and is equipped with camera, GPS sensor, and inertialmeasurement unit (IMU) sensor to do the mapping of its environment. The packages used inROS are Hector Quadrotor package, joystick package, Octomap package, and MoveIt package.These packages were modified so that it could be integrated with each other and fulfill theobjective of this research. For the 3D path planning, a method called rapidly-exploring randomtree (RRT) is explored and implemented. Several experiments regarding the behavior of thequadrotor, the mapping, and the path planning were conducted to find out the performance andlimitations of the simulation. This simulation is set up so that it can be used to validate a newdesign of quadrotor before it is tested with a physical prototype.
Fog/Cloud Service Scalability, Composition, Security, Privacy, and SLA Management

Cloud computing has started a new era in the field of computing, which allows the access of remote data or services at anytime and anywhere. In today's competitive environment, the service dynamism, elasticity, and choices offered by this highly scalable technology are too attractive for enterprises to ignore. The scalability feature of cloud computing allows one to expand and contract the resources. The owner's data stored at the remote location, but he is usually afraid of sharing confidential data with cloud service provider. If the service provider is not the trusted one, there may be a chance of leakage of confidential data to external third party. Security and privacy of data require high consideration, which is resolved by storing the data in encrypted form. Data owner requires that the service provider should be trustworthy to store its confidential data without any exposure. One of the outstanding solutions for maintaining trust between different communicating parties could be the service level agreement between them.
Reinventing Clinical Decision Support

The diagnosis of disease can become so complex that the human brain is incapable for processing all the possibilities. The latest clinical decision support software can help meet this challenge, using massive informational databases, machine learning, neural networks, and systems biology.
Machine Imagination: A Step Toward the Construction of Artistic World Through Storytelling

Development of conscious machines requires the implementation of artifacts that might enable an agent to formulate, represent, and regulate its actions and behaviors in a diverse environment. Regulation involves the rehearsal of all context-based possibilities considering emotional state and goals before execution of motor actions. It also means that an agent should be able to manipulate information that is not directly perceived through sensory stimuli. In order to incorporate these abilities, an agent is required to be constructed with cognitive memories, sensory system, sensory integration, emotion, drives, motivations, and action regulatory system. This study proposes a sub-architecture for QuBIC (cognitive architecture) to generate imaginations in QuBIC agents. The proposed architecture was implemented along with required computational constructs discussed in the paper. Furthermore, the paper presents the empirical analysis showing the potential of the proposed solution to construct imaginations in an agent. Experimental results illustrate how the aforementioned cognitive states participated in the process of machine imagination.