Reviewerly/exHarmony huggingface dataset:
Enhanced dynamic team access control for collaborative Internet of Things using context

Summary The development of the Internet of Things (IoT) aims to overcome security issues especially in critical areas that require integrity, confidentiality and a high level of privacy of the data. Among security challenges, the access control model should be well defined and adapted to the characteristics and security requirements of IoT applications. The work presented here proposes big enforcement of security for dynamic team access control using context information in order to provide granular and secure authorizations with different access control levels related to collaborative IoT. The enhanced dynamic team access control (EDTMAC) model introduces a formal theoretical model which relies on the top of the role‐based access control model. The use of different context information with a global context information security policy and security rules raised the model strength against unauthorized access and avoided security breaches such as the leak of information by providing the least privileges for the users. The result of EDTMAC analysis shows that the model is well adapted to IoT dynamic nature and collaborative IoT activities for teams. Moreover, the model is flexible and scalable, user‐driven, reliable, and secure against unauthorized access requests. The developed model supports the well‐known least‐privilege principle and separation of duties for the team members. In addition, it allows easy management of the teams, provides fine‐grained access control authorizations and supports delegation.
The service task of automotive troubleshooting process in collaborative environment using knowledge support approach

The automotive troubleshooting unfolds from the system phase to the multiple-domain phase. It is necessary that different field members, for example, system and domain engineers, cooperate tightly toward an integrated product service process. Therefore, the purpose of this research is to generate a knowledge management platform for the overall automotive troubleshooting service. Besides, general ontologies, automotive troubleshooting service ontology (ATSO), is also created as a helpful tool for the communication of heterogeneous systems. This proposed approach of automotive collaborative troubleshooting is explained with the corresponding meta-model. The main contribution of this research is to assure the traceability in both system and domain phases by structuring knowledge. Eventually, an application is illustrated in enhancing re-usability in the region of automotive braking system in collaborative environment.
An efficient statistical adaptive order-switching methodology for kalman filters

Variants and improvements of the extended Kalman filter (EKF) always encounter a dilemma between the estimation accuracy delivered and the computational burden associated. Targeting to improve this shortcoming, achieving estimations with high accuracy and computational efficiency, this paper investigates a new adaptive high order extended Kalman filter (AHEKF) based on the design of a special order-switching strategy within one single filter run. At each filter step, an innovation-based function, accounting for the filter consistency, is put forward and estimated to determine the necessity of an order-switching operation. We think that the methodology could be of general applicability in procedures where a switching order approximation is possible, and in our work, simulations and performance evaluations are illustrated with a particular celestial mechanics problem dealing with orbit determination.
DIGITAL REPOSITORY FOR RESEARCH AND EDUCATION INFORMATION SYSTEMS

The article is devoted to the overview of the most popular digital repository support systems and their information model. The choice of DSpace for the data warehouse of the scientific and educational information system is justified.
Firing pin impressions: a valuable feature for determining the orientation of the weapon at the time of shooting

Sometimes the firearm forensic examiner is required to provide information useful to discriminate between suicide, homicide or accident, or between contradictory reconstructions of the events (like attempted murder versus accidental discharge). In such situations, knowledge of the position and orientation of the firearm at the time of firing can be of fundamental help for the reconstruction of events. To achieve these goals, the analysis of the firing impressions is very important. In this study, the cartridge cases shot with three different revolvers aiming at three different spatial orientations (vertical upwards, horizontal or vertical downwards) were studied. The depth and morphology of the firing pin impression was characterised by optical microscopy and quantified by a surface topography analysis. The orientation of the firearm significantly modified the morphology and depth of the firing pin impression: ammunition fired upwards had the deepest firing pin impression, those fired downwards had the shallowest. Such behaviour was attributed to the different geometry of the firing pin-primer cup interaction and to the different pressure exerted by the primer as the orientation of the weapon changes. Therefore, this work has shown that a suitable protocol of morphological and topographical analysis can be set up to understand if a shot by a revolver was fired holding the weapon upwards, downwards or horizontally.
A first look at forensic analysis of sailfishos

SailfishOS is a Linux kernel-based embedded device operation system, mostly deployed on cell phones. Currently, there is no sufficient research in this space, and at the same time, this operating system is gaining popularity, so it is likely for investigators to encounter it in the field. This paper focuses on mapping the digital artifacts pertinent to an investigation, which can be found on the filesystem of a phone running SailfishOS 3.2. Currently, there is no other known publicly available research and no commercially available solutions for the acquisition and analysis of this platform. This is a major gap, as the adoption of this OS is accelerating in emerging markets on low-cost devices. This paper presents many of the major forensics points of interest, such as call and text, log, phonebook, web browser artifacts as well as hardware-specific features.
Extended Target Marginal Distribution Poisson Multi-Bernoulli Mixture Filter

The existence of clutter, unknown measurement sources, unknown number of targets, and undetected probability are problems for multi-extended target tracking, to address these problems; this paper proposes a gamma-Gaussian-inverse Wishart (GGIW) implementation of a marginal distribution Poisson multi-Bernoulli mixture (MD-PMBM) filter. Unlike existing multiple extended target tracking filters, the GGIW-MD-PMBM filter computes the marginal distribution (MD) and the existence probability of each target, which can shorten the computing time while maintaining good tracking results. The simulation results confirm the validity and reliability of the GGIW-MD-PMBM filter.
A Bichannel Transformer with Context Encoding for Document-Driven Conversation Generation in Social Media

Along with the development of social media on the internet, dialogue systems are becoming more and more intelligent to meet users’ needs for communication, emotion, and social intercourse. Previous studies usually use sequence-to-sequence learning with recurrent neural networks for response generation. However, recurrent-based learning models heavily suffer from the problem of long-distance dependencies in sequences. Moreover, some models neglect crucial information in the dialogue contexts, which leads to uninformative and inflexible responses. To address these issues, we present a bichannel transformer with context encoding (BCTCE) for document-driven conversation. This conversational generator consists of a context encoder, an utterance encoder, and a decoder with attention mechanism. The encoders aim to learn the distributed representation of input texts. The multihop attention mechanism is used in BCTCE to capture the interaction between documents and dialogues. We evaluate the proposed BCTCE by both automatic evaluation and human judgment. The experimental results on the dataset CMU_DoG indicate that the proposed model yields significant improvements over the state-of-the-art baselines on most of the evaluation metrics, and the generated responses of BCTCE are more informative and more relevant to dialogues than baselines.
GUI2WiRe

High-fidelity Graphical User Interface (GUI) prototyping is a well-established and suitable method for enabling fruitful discussions, clarification and refinement of requirements formulated by customers. GUI prototypes can help to reduce misunderstandings between customers and developers, which may occur due to the ambiguity comprised in informal Natural Language (NL). However, a disadvantage of employing high-fidelity GUI prototypes is their time-consuming and expensive development. Common GUI prototyping tools are based on combining individual GUI components or manually crafted templates. In this work, we present GUI2WiRe, a tool that enables users to retrieve GUI prototypes from a semiautomatically created large-scale GUI repository for mobile applications matching user requirements specified in Natural Language (NLR). We extract multiple text segments from the GUI hierarchy data and employ various Information Retrieval (IR) models and Automatic Query Expansion (AQE) techniques to achieve ad-hoc GUI retrieval from NLR. Retrieved GUI prototypes mined from applications can be inserted in the graphical editor of GUI2WiRe to rapidly create wireframes. GUI components are extracted automatically from the GUI screenshots and basic editing functionality is provided to the user. Finally, a preview of the application is created from the wireframe to allow interactive exploration of the current design. We evaluated the applied IR and AQE approaches for their effectiveness in terms of GUI retrieval relevance on a manually annotated collection of NLR and discuss our planned user studies. Video presentation of GUI2WiRe: https://youtu.be/2nN-Xr2Hk7I
Adaptive sampling for active learning with genetic programming

Active learning is a machine learning paradigm allowing to decide which inputs to use for training. It is introduced to Genetic Programming (GP) essentially thanks to the dynamic data sampling, used to address some known issues such as the computational cost, the over-fitting problem and the imbalanced databases. The traditional dynamic sampling for GP gives to the algorithm a new sample periodically, often each generation, without considering the state of the evolution. In so doing, individuals do not have enough time to extract the hidden knowledge. An alternative approach is to use some information about the learning state to adapt the periodicity of the training data change. In this work, we propose an adaptive sampling strategy for classification tasks based on the state of solved fitness cases throughout learning. It is a flexible approach that could be applied with any dynamic sampling. We implemented some sampling algorithms extended with dynamic and adaptive controlling re-sampling frequency. We experimented them to solve the KDD intrusion detection and the Adult incomes prediction problems with GP. The experimental study demonstrates how the sampling frequency control preserves the power of dynamic sampling with possible improvements in learning time and quality. We also demonstrate that adaptive sampling can be an alternative to multi-level sampling. This work opens many new relevant extension paths.
Feature location enhancement based on source code augmentation with synonyms of terms

Summary In software maintenance the developers may add new feature to program, improve existing function, and remove bugs. In this case the developer should identify the location in the source code that corresponds to a specific functionality; this is known as feature location. This presents a new approach for enhancing the process of feature location using Information Retrieval (IR) and Natural Language Processing. The approach presented augments the source code with additional semantic information that was extracted and derived from the synonyms of source code terms. This approach works in a pipeline structure, starting by augmenting the source code corpus with synonyms of the original terms and ending by inferring the source code with a particular user query. More specifically, the WordNet platform is used for extracting the synonyms of terms. Moreover, the approach uses an advanced IR technique, namely the Latent Semantic Indexing, for searching and inferring the source code. The used approach was tested and evaluated on two open source systems, namely the Qt and Hippodraw. Four experiments were conducted on each system using 21 features and the results showed that enriching the source code with synonyms of terms clearly and significantly improved the process of feature location efficiently. The experimental results showed that the approach presented obtained higher levels of Recall and Precision. For that reason, it has been shown to improve the state‐of‐the‐art techniques for feature location process.
Comparing immersiveness and perceptibility of spherical and curved displays

Curved displays are believed to create a feeling of immersiveness similar to virtual reality. However systematic studies are needed to demonstrate that this is, in fact, true and under what conditions. In an experimental study 24 participants compared five different displays (concave, convex, hemisphere, sphere and a flat display) in terms of their immersiveness and perceptibility, and they also rated their overall preferences. Both immersiveness and perceptibility affected overall preference ratings. Participants gave higher preference ratings to the convex and concave displays, which were rated high in immersiveness and perceptibility, but gave lower preference ratings to the hemisphere/spherical display which had high ratings on immersiveness but low ratings on perceptibility. The study results imply that curved displays do indeed create a feeling of immersiveness. Concave and convex displays were rated highly favorably and should receive more attention for applications where visual experience and a feeling of immersiveness is particularly important.
Computing Eigenvalues of Diagonalizable Matrices on a Quantum Computer

Computing eigenvalues of matrices is ubiquitous in numerical linear algebra problems. Currently, fast quantum algorithms for estimating eigenvalues of Hermitian and unitary matrices are known. However, the general case is far from fully understood in the quantum case. Based on a quantum algorithm for solving linear ordinary differential equations, we show how to estimate the eigenvalues of diagonalizable matrices that only have real eigenvalues. The output is a superposition of the eigenpairs, and the overall complexity is polylog in the dimension for sparse matrices. Under an assumption, we extend the algorithm to diagonalizable matrices with complex eigenvalues.
Development of an audio watermarking with decentralization of the watermarks

In this paper, a digital watermarking technique for ensuring security to an audio signal is presented. The proposed technique is developed by using discrete wavelet transform (DWT) and singular value decomposition (SVD). The proposed technique is executed by incorporating multi-level DWT along with the use of multiple images with different sizes as watermarks. The proposed technique is developed by keeping in mind the distribution of watermark signals’ energy throughout the entire host signal i.e. the watermarks are decentralized over the entire region of the host signal. The proposed technique is robust as experimentally the proposed technique offers PSNR (Peak Signal to Noise Ratio) of 196.8105 dB and normalized cross-correlation (NCC) over 0.9.
In situ geochemistry of dyke−marble interfaces obtained by portable X-ray fluorescence (pXRF) spectroscopy: Implications for sources of ore-forming materials in the Baiyinnuo'er Zn–Pb deposit, inner Mongolia, China

In situ analysis performed by portable X-ray fluorescence (pXRF) spectroscopy was used to measure two different contact interfaces of dyke and marble in the Baiyinnuo'er Zn–Pb deposit located in Inner Mongolia, China. The limit of detection (LOD) standardisation method was used to assess pXRF readings through dividing readings into low, medium and high concentrations, and readings were screened according to the concentration range distribution. Spatial trend analysis and enrichment factor calculation were used for data processing. In both profiles of quartz porphyry−marble (Q−M) and granodiorite−marble (G−M), high values of Ca and Mg, and Si, Al and K, respectively, could be used to distinguish the distribution of marble and dykes. However, there were significant differences in the distributions of ore-forming elements between the two profiles. No ore-forming elements were enriched near the contact interface of the Q−M profile, but all ore-forming elements, such as Zn, Pb, Cu and Fe, were significantly enriched in the skarns located between granodiorite and marble. Therefore, the intrusion of granodiorite resulted in the enrichment of ore-forming elements, and provided metals for mineralisation. Based on the results of the calculated enrichment factor for the G−M profile, the enrichment degree of selected elements in descending order was Pb, Zn > Ca > Fe > Al, Si > K in skarns relative to granodiorite, and Pb, Fe > Si, Al > Zn > K > Ca in skarns relative to marble. Zn and Pb were enriched in skarns relative to granodiorite but partially depleted relative to marble, indicating the high background Zn and Pb in marble; therefore, marble could provide at least part of the Zn and Pb. As a consequence, the intrusion of granodiorite resulted in skarnisation and mineralisation, and introduced ore-forming elements including Zn, Pb, Cu and Fe, but marble also provided at least part of the Zn and Pb, and the deposit was considered to be a skarn Zn–Pb deposit. In situ geochemical analysis at the outcrop scale is a useful approach for research into geological processes including skarnisation and mineralisation, as well as determining the source of ore-forming materials.
ACSiamRPN: Adaptive Context Sampling for Visual Object Tracking

In visual object tracking fields, the Siamese network tracker, based on the region proposal network (SiamRPN), has achieved promising tracking effects, both in speed and accuracy. However, it did not consider the relationship and differences between the long-range context information of various objects. In this paper, we add a global context block (GC block), which is lightweight and can effectively model long-range dependency, to the Siamese network part of SiamRPN so that the object tracker can better understand the tracking scene. At the same time, we propose a novel convolution module, called a cropping-inside selective kernel block (CiSK block), based on selective kernel convolution (SK convolution, a module proposed in selective kernel networks) and use it in the region proposal network (RPN) part of SiamRPN, which can adaptively adjust the size of the receptive field for different types of objects. We make two improvements to SK convolution in the CiSK block. The first improvement is that in the fusion step of SK convolution, we use both global average pooling (GAP) and global maximum pooling (GMP) to enhance global information embedding. The second improvement is that after the selection step of SK convolution, we crop out the outermost pixels of features to reduce the impact of padding operations. The experiment results show that on the OTB100 benchmark, we achieved an accuracy of 0.857 and a success rate of 0.643. On the VOT2016 and VOT2019 benchmarks, we achieved expected average overlap (EAO) scores of 0.394 and 0.240, respectively.
Interacting T-S fuzzy semantic model estimation for maneuvering target tracking

This paper proposes an interacting Takagi–Sugeno(T-S) fuzzy semantic model estimator (ITS-FSM) for maneuvering target tracking, and constructs a framework for a generic interacting T-S fuzzy semantic model to incorporate semantic information concerning the target. To adaptively calculate the transition probability matrix of the models, a probabilistic switching model based on semantic fuzzy sets is derived by using the degree of intersection between fuzzy sets, which enables switching from one semantic fuzzy set to another. We also propose an efficient kernel maximum entropy fuzzy clustering method to identify the premise parameters of the model. This enables the proposed algorithm to recursively estimate the premise parameters in case of a limited number of samples. Moreover, a modified extended forgetting factor recursive least squares (MEFRLS) estimator is used to identify the parameters of the T-S fuzzy semantic model. The results of experiments on three simulation datasets show that the proposed ITS-FSM algorithm is efficient, and is excellent at handling non-Gaussian noise.
Face Illumination Transfer and Swapping via Dense Landmark and Semantic Parsing

The image-based virtual illumination technology directly changes the illumination effect of objects on the image. It does not require complex light propagation simulation calculations, it is an image-based rendering technology. The image mainly relies on the imaging of the visual sensor, and uses the virtual illumination technology of the image to illuminate the image obtained by the visual sensor. This is a new cross-cutting direction in computer vision, virtual reality and other fields. Face Illumination Swapping via Dense Landmark and Semantic Parsing is a major branch. Keeping the geometrical features of the target images and relighting the entire image instead of the face area are problems to be solved in the research. This paper based on the three-dimensional model to analyze the illumination information of the face images and re-render the illumination of the target face, and finally achieves the illumination swap between the two face images. We designed and implemented a 3DDFA-based face image illumination transfer method. First, 3DDFA is used to reconstruct the target face image. Estimate the surface normal and albedo. Then align and fill the surface normal and face parsing to illuminate the face image for light rendering and illumination transfer of the face images. Finally, the illumination analysis and re-rendering of face images based on 3DDFA are expanded to achieve the swap of illumination between face images. Experimental results show that this method can generate good effects of face image illumination transmission and swap while keeping the geometric features of the target images.