Reviewerly/exHarmony huggingface dataset:
Semantic Web Search Engines : A Comparative Survey

Search engines play important role in the success of the Web. Search engine helps the users to find the relevant information on the internet. Due to many problems in traditional search engines has led to the development of semantic web. Semantic web technologies are playing a crucial role in enhancing traditional search, as it work to create machines readable data and focus on metadata. However, it will not replace traditional search engines. In the environment of semantic web, search engine should be more useful and efficient for searching the relevant web information. It is a way to increase the accuracy of information retrieval system. This is possible because semantic web uses software agents; these agents collect the information, perform relevant transactions and interact with physical devices. This paper includes the survey on the prevalent Semantic Search Engines based on their advantages, working and disadvantages and presents a comparative study based on techniques, type of results, crawling, and indexing.
Real-Time Action Recognition Using Multi-level Action Descriptor and DNN

This work presents a novel approach to the problem of real-time human action recognition in intelligent video surveillance. For more efficient and precise labeling of an action, this work proposes a multilevel action descriptor, which delivers complete information of human actions. The action descriptor consists of three levels: posture, locomotion, and gesture level; each of which corresponds to a different group of subactions describing a single human action, for example, smoking while walking. The proposed action recognition method is able to localize and recognize simultaneously the actions of multiple individuals using appearance-based temporal features with multiple convolutional neural networks (CNN). Although appearance cues have been successfully exploited for visual recognition problems, appearance, motion history, and their combined cues with multi-CNNs have not yet been explored. Additionally, the first systematic estimation of several hyperparameters for shape and motion history cues is investigated. The proposed approach achieves a mean average precision (mAP) of 73.2% in the frame-based evaluation over the newly collected large-scale ICVL video dataset. The action recognition model can run at around 25 frames per second, which is suitable for real-time surveillance applications.
Non-local Haze Propagation with an Iso-Depth Prior

The primary challenge for removing haze from a single image is lack of decomposition cues between the original light transport and airlight scattering in a scene. Many dehazing algorithms start from an assumption on natural image statistics to estimate airlight from sparse cues. The sparsely estimated airlight cues need to be propagated according to the local density of airlight in the form of a transmission map, which allows us to obtain a haze-free image by subtracting airlight from the hazy input. Traditional airlight-propagation methods rely on ordinary regularization on a grid random field, which often results in isolated haze artifacts when they fail in estimating local density of airlight properly. In this work, we propose a non-local regularization method for dehazing by combining Markov random fields (MRFs) with nearest-neighbor fields (NNFs) extracted from the hazy input using the PatchMatch algorithm. Our method starts from the insightful observation that the extracted NNFs can associate pixels at the similar depth. Since regional haze in the atmosphere is correlated with its depth, we can allow propagation across the iso-depth pixels with the MRF-based regularization problem with the NNFs. Our results validate how our method can restore a wide range of hazy images of natural landscape clearly without suffering from haze isolation artifacts. Also, our regularization method is directly applicable to various dehazing methods.
Weakened Random Oracle Models with Target Prefix

Weakened random oracle models (WROMs) are variants of the random oracle model (ROM). The WROMs have the random oracle and the additional oracle which breaks some property of a hash function. Analyzing the security of cryptographic schemes in WROMs, we can specify the property of a hash function on which the security of cryptographic schemes depends. Liskov (SAC 2006) proposed WROMs and later Numayama et al. (PKC 2008) formalized them as CT-ROM, SPT-ROM, and FPT-ROM. In each model, there is the additional oracle to break collision resistance, second preimage resistance, preimage resistance respectively. Tan and Wong (ACISP 2012) proposed the generalized FPT-ROM (GFPT-ROM) which intended to capture the chosen prefix collision attack suggested by Stevens et al. (EUROCRYPT 2007). In this paper, in order to analyze the security of cryptographic schemes more precisely, we formalize GFPT-ROM and propose additional three WROMs which capture the chosen prefix collision attack and its variants. In particular, we focus on signature schemes such as RSA-FDH, its variants, and DSA, in order to understand essential roles of WROMs in their security proofs.
Lightweight R-LWE based Privacy Preservation Scheme for Smart Grid Network

Privacy preservation is one of the important research challenges in IoT applications. In one such IoT application; smart grid network, billing information and energy profiling information of the customer may be collected, aggregated, and forwarded to control centre for further analytics. Based on the research findings, traditional public key cryptography is not secured against quantum attacks. Our study is motivated by the recent developments in the lattice-cryptography schemes. This paper presents a lightweight R-LWE lattice-cryptography-based scheme to sign and encrypt message traffic in smart grid. Security analysis suggests that proposed scheme preserves the privacy of customer. Performance analysis shows that proposed scheme cause less communication overhead as compared to traditional public key cryptography yet maintain parallel with NTRU-based scheme and outperforms both formats of public key cryptography in regards to computation overhead.
Do the online information searching strategies affect individual innovativeness in nursing students?

Aim: The study was conducted to determine the effect of online information searching strategies on individual innovativeness in students taking the course of information techniques in nursing.Material and Methods:The study was conducted as a descriptive and correlational study. The population of the study consisted of 548 students whoattended nursing faculty andtookthe course of information techniques in the nursing. In the study, the whole of the population was tried to be reached without using sample selection and the study was completed with 453 students. The data were collected by using Personal Information Form prepared by the researchers, Online Information Searching Strategies Inventory, and Individual Innovativeness Scale. Descriptive statistics, independent samples t-test, One way ANOVA, post-hoc tests, Correlation analysis, and the Cronbach’s Alpha reliability analysis test were used to assess the data. Results: It was found that OISSI and subscale mean scores of the nursing students were moderate. IIS mean scores of the students were 59.76±11.38 and they were early majority according to the scale evaluation. While a positive moderate correlation was determined between the OISSI subscale levels andindividual innovativeness levels of the students in the study, a positive strong correlation was found between the online information searching strategies andindividual innovativeness (p
Building Conversational Interfaces

Dr Martin J Wheatman explores how meaning is conveyed through language, how to measure understanding, and what an appreciation of semiotics might mean for teaching computers to understand language.
Image Retargeting Using Dynamic Load Balancing-Based Parallel Architecture

Nowadays, enormously expanding use of mobile gadgets for capturing images is getting overwhelming response. This fact results in a tremendously increasing usage of digital images. To maintain the quality of vastly pervading digital images on variable sized display contraptions becomes a pensive task for a Web administrator. We are providing a three-leveled image retargeting approach on a parallel architecture with ranking-based dynamic load balancing (RBDLB). Image retargeting is both computational and memory intensive task. Static load balancing cannot offer equity to image retargeting errand as incoming image jobs are required to be processed at dynamic time. The motive of thought process of this undertaking is to provide a good response time and efficient resource utilization in a task of image retargeting without compromising quality of image.
Government data, commercial cloud: Will public access suffer?

New data handling models may affect use for research
Mixed Reality Could Improve Science, Technology, Engineering, and Mathematics Learning

Cyberpsychology, Behavior, and Social NetworkingVol. 22, No. 2 CyberSightingsMixed Reality Could Improve Science, Technology, Engineering, and Mathematics LearningCompiled by: Andrea GaggioliCompiled by: Andrea GaggioliAddress correspondence to: Dr. Andrea Gaggioli, Department of Psychology, Catholic University of Milan, Largo Gemelli 1-20123 Milan, Italy E-mail Address: andrea.gaggioli@unicatt.itDepartment of Psychology, Catholic University of Milan, Milan, Italy.Applied Technology for Neuro-Psychology Lab, Istituto Auxologico Italiano, Milan, Italy.Search for more papers by this authorPublished Online:19 Feb 2019https://doi.org/10.1089/cyber.2018.29141.csiAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"Mixed Reality Could Improve Science, Technology, Engineering, and Mathematics Learning." Cyberpsychology, Behavior, and Social Networking, 22(2), pp. 166–167FiguresReferencesRelatedDetailsCited byCreativity in Digital Reality / Creatividad en la realidad digital1 November 2019 | Estudios de Psicología, Vol. 40, No. 3 Volume 22Issue 2Feb 2019 InformationCopyright 2019, Mary Ann Liebert, Inc., publishersTo cite this article:Compiled by: Andrea Gaggioli.Mixed Reality Could Improve Science, Technology, Engineering, and Mathematics Learning.Cyberpsychology, Behavior, and Social Networking.Feb 2019.166-167.http://doi.org/10.1089/cyber.2018.29141.csiPublished in Volume: 22 Issue 2: February 19, 2019PDF download
Modelling Action in Verbal Command Context with Fuzzy Subsets and Semantic Networks

This study deals with the interpretation of verbal commands for action. After an experimental study of human interpretation of instructions for drawing geometrical figures, we have devised a model whose computerized version is called SIROCO. This model represents an attempt to simulate differents mechanisms implied in interpretation of verbal commands. These mechanisms exploiting contextual informations allow clarifying and completing propositions expressed in natural language. In the model, first, the constraints expressed in present command, in environnement (already present figures), and in background communication, are represented with fuzzy subsets and circumstantial semantic networks (well suited for flexible and dynamical representations). Subsequently, an optimization procedure integrating all this constraints allows finding a relevant response to the command. Finally a simulation which consists in translating instructor’s verbal commands in a defined minimal language and making it interpreted by the system shows quite good results for the model.
Context-Awareness in Internet of Things - Enabled Monitoring Services

Remote monitoring services are required to meet the very high demands on availability and efficiency of industrial systems. The fast evolution of technologies associated with the deeper penetration of Internet of Things in industry creates considerable challenges for such services. These are related to the whole data lifecycle, encompassing data acquisition, real-time data processing, transmission, storage, analysis, and higher added value service provision to users, with adequate data management and governance needed to be in place. The sheer complexity of such activities the need to ground such processing on sound domain knowledge emphasises the need for context information management. The aim of this paper is to survey and analyse recent literature that addresses Internet of Things context information management, mapping how context-aware computing addresses key challenges and supports delivering appropriate monitoring solutions.
Relativistic properties and invariants of the Du Fort–Frankel scheme for the one-dimensional Schrödinger equation

Abstract The Du Fort–Frankel scheme for the one-dimensional Schrodinger equation is shown to be equivalent, under a time-dependent unitary transformation, to the Ablowitz–Kruskal–Ladik scheme for the Klein–Gordon equation. The Schrodinger equation describes a non-relativistic quantum particle, while the Klein–Gordon equation describes a relativistic particle. The conditional convergence of the Du Fort–Frankel scheme to solutions of the Schrodinger equation arises because solutions of the Klein–Gordon equation only approximate solutions of the Schrodinger equation in the non-relativistic limit. The time-dependent unitary transformation is the discrete analog of the transformation that arises from seeking a non-relativistic limit using the interaction picture of quantum mechanics to decompose the Klein–Gordon Hamiltonian into the relativistic rest energy and a remainder. The Ablowitz–Kruskal–Ladik scheme is in turn decomposed into a quantum lattice gas automaton for the one-dimensional Dirac equation, which is also the one-dimensional discrete time quantum walk. This relativistic interpretation clarifies the origin of the known discrete invariant of the Du Fort–Frankel scheme as expressing conservation of probability for the 2-component wavefunction in the one-dimensional Dirac equation under discrete unitary evolution. It also leads to a second invariant, the matrix element of the evolution operator, whose imaginary part gives a discrete approximation to the expectation of the non-relativistic Schrodinger Hamiltonian.
INSTalytics: Cluster Filesystem Co-design for Big-data Analytics.

We present the design, implementation, and evaluation of INSTalytics, a co-designed stack of a cluster file system and the compute layer, for efficient big-data analytics in large-scale data centers. INSTalytics amplifies the well-known benefits of data partitioning in analytics systems; instead of traditional partitioning on one dimension, INSTalytics enables data to be simultaneously partitioned on four different dimensions at the same storage cost, enabling a larger fraction of queries to benefit from partition filtering and joins without network shuffle. To achieve this, INSTalytics uses compute-awareness to customize the three-way replication that the cluster file system employs for availability. A new heterogeneous replication layout enables INSTalytics to preserve the same recovery cost and availability as traditional replication. INSTalytics also uses compute-awareness to expose a new sliced-read API that improves performance of joins by enabling multiple compute nodes to read slices of a data block efficiently via co-ordinated request scheduling and selective caching at the storage nodes. We have built a prototype implementation of INSTalytics in a production analytics stack, and we show that recovery performance and availability is similar to physical replication, while providing significant improvements in query performance, suggesting a new approach to designing cloud-scale big-data analytics systems.
A Discrete Bisector Function Based on Annulus

In this paper we are proposing a new way to compute a discrete bisector function, which is an important tool for analyzing and filtering Euclidean skeletons. From a continuous point of view, a point that belongs to the medial axis is the center of a maximal ball that hits the background in more than one point. The maximal angle between those points is expected to be high for most of the object points and corresponds to the bisector angle. This logic is not really applicable in the discrete space since in some configurations we miss some background points leading sometimes to small bisector angles. In this work we use annuli to find the background points in order to compute the bisector angle. The main advantage of this approach is the possibility to change the thickness and therefore to be more flexible while computing the bisector angle.
Towards Malicious Security of Private Coin Honest Verifier Zero Knowledge for NP via Witness Encryption

We develop a new method for transforming private coin HVZK protocols into witness indistinguishable, and zero knowledge protocols, via witness encryption. This causes at most one additional round. Previously, the general way of transforming a private coin HVZK protocol into zero knowledge is to employ a standard commitment technique, which causes two more rounds. Following this method, we present two-round witness indistinguishable proofs for specific languages, such as OR-DDH, OR-QR, OR-LWE, based on the associated lossy encryption and witness encryption. We apply this witness encryption idea to the HVZK protocol in [Jawurek et al. CCS13] and present a three-round zero knowledge protocol with super-polynomial simulation (or zero knowledge in $$\mathcal {F}_{OT}$$ -hybrid model) for NP, assuming the existence of Yao’s garble circuit and two-message oblivious transfer protocol (or ideal oblivious transfer). In addition, our three-round zero knowledge protocol works for generic languages, avoiding expensive Karp reductions.
Developing Reversible Data Hiding with Interpolation and Local Dispersion

Recent Interpolation-based Reversible Data Hiding (IRDH) schemes demonstrated significantly higher embedding capacity, however, their embedded image quality is not much impressive, particularly for higher size payload. This paper presents an improved IRDH scheme with local dispersion for better quality embedded image. For high embedding capacity, correlation based embedding is utilized in all embeddable bits only in the interpolated pixels. The error between an embedded pixel and its original version is then reduced using the local (i.e., block-wise) standard deviation to further improve the embedded image quality. Since the standard deviation is computed from the original pixels and their respective interpolated pixels in a block, the improved embedding process remains reversible to losslessly extract the embedded data. All the original pixels are also kept intact for perfect recovery of the original image. A significant improvement in embedded image quality is thus recorded in comparison to the state-of-the-art IRDH schemes.
Indian e-journals in library and information science: A study based on coverage in UGC approved list of journals

In the recently released UGC list of approved journals, 11 out of 40 Indian LIS journals were found having e-ISSNs. While searching the ISSN database for e-ISSNs of the remaining journals, 7 more were found having e-ISSNs. However, four of these seven journals could not be considered for the present study as they had wrong country of origin, the journal is not an exclusive LIS journal, etc. Finally, fourteen LIS online Indian journals with e-ISSNs have been studied. The study finds that a detailed check list needs to be developed to assess the journals and concludes that there is a need for improving the quality of journals and making them comparable with the global standards.
*Thing: Improve Anything to Anything Collaboration

This is a work in the context of Collaborative Working Environment (CWE). In particular, in that of collaboration and productivity software tools. CWEs have seen the adoption of application software to addresses business problems as team communication and workload management. Instant messaging solutions, mobile devices and the virtual assistant paradigm have also come into the picture. Software tools in this context lack nonetheless real collaborative features. The problem that we address in this work is therefore that of a truly collaborating team collaboration and productivity software environment. Our approach leverages recent trends, like that of instant chats, virtual assistants and the Internet of Things, focuses on team members utterances and on a customizable and configurable bot framework to automate routine tasks, provide content over structure information management, and enable workflow management to improve productivity. The result is a prototypical software product which: enables the collaboration of both humans and Internet enabled things alike, provides easy context driven collaboration (i.e. entities graphs), allows the systematic processing of messages exchanged in a concurrent multi-user environment to fulfill team actions, provides a middle layer bot framework that handles the dialog flow for these actions and the interaction with any external systems. All of which distinguishes it from current software solutions. Given the features and the architecture of our original software components, we can confidently state that their adoption would enable software developers to create more effective collaboration and productivity working environment software tools.
ExSS

Smart systems that apply complex reasoning to make decisions and plan behavior are often difficult for users to understand. While research to make systems more explainable and therefore more intelligible and transparent is gaining pace, there are numerous issues and problems regarding these systems that demand further attention. The ExSS 2019 workshop is a follow-on from the very successful ExSS 2018 workshop previously held at IUI, to bring academia and industry together to address these issues. This workshop includes a keynote, paper panels, poster session, and group activities, with the goal of developing concrete approaches to handling challenges related to the design and development of explainable smart systems.
Applications of higher-order phase shifting algorithms for multiple-wavelength metrology

Multiple-wavelength interferometric techniques have been successfully used for large step-height and large deformation measurements. Also it could resolve the step height between smooth and rough surfaces which is not possible with single wavelength interferometry. Temporal phase shifting algorithm, which requires a phase shifter such as PZT, has been widely used for accurate phase evolution in interferometry. The phase shifter needs to be calibrated at every wavelength if multiple wavelengths are used for measurement, it is a time consuming process. If phase shifter is not calibrated accurately, it can introduce phase shift errors. In this work, we will discuss various phase shifting algorithms, and their tolerance for phase shift error. And the applications of higher-order phased shifting algorithms will be presented. The study is useful for multiple-wavelength and white light interferometry where more than one wavelength is used for optical phase measurements.
Application of Process Approach to Knowledge Management in Education Institutions: Competence Centres

In recent years, Russia has carried out reforms in the vocational education system. In order to improve the reforms efficiency leading engineering universities of the country are organising Competence centres. In technical universities this tendency is actually to provide training for teachers, professors, experts in hi-tech industries. The article considers the main functions of competence centers as structures aimed at active search, transfer and accumulation of new knowledge and unique experience, based on the students and employers needs. It is suggested to apply process approach for university centres design, while in the framework of this approach it is possible to optimize the acquisition, storage, and knowledge management process.