Reviewerly/exHarmony huggingface dataset:
A Novel Watermarking Mechanism for Deep Learning Models based on Chaotic Boundaries

With the development of deep learning models, how to protect model owners intellectual property rights has become a realistic problem. Black-box watermarking technology provides an idea which allows model owners to validate a suspect model through trigger sets. Usually, the trigger set is formed by adding Gaussian noise to the data set or manually marking the data set. In this paper, we propose a novel watermarking mechanism for deep learning models. Firstly, CGAN is used to generate the data at classification boundaries. Secondly, Chaos automatic annotation generates chaotic values through iterations is used to label these extra data in boundaries, so as to distinguish the watermarked model and non-watermarked model. Compared with former trigger sets, the labeling of our trigger set is automatic, and due to the excellent characteristics of chaos, the chaotic value of the trigger set is difficult to predict in a long term. The chaotic sequence is sensitive to the initial value. Therefore, the initial value and the rule for selecting the chaotic value form our key space. Even if the trigger set is leaked, as long as the key is not leaked, the attacker cannot get our chaotic value. In addition, experiments and simulations show that the mechanism is effective, secure and robust. It can resist fine-tuning attacks, compression attacks, fraudulent ownership claim attacks and overwriting attacks.
The Amalgamation of Blockchain and IoT: A Survey

Blockchain, the form of Distributed Ledger Technology, is getting momentum. Data in the blockchain is in the form of transactions. Blockchains are transparent, immutable and auditable distributed ledgers with peer to peer connection, cryptography and consensus algorithm. All the parties involved have the same copy of data (transparency), data cannot be modified or deleted (immutability) and a full history of transactions is available (auditable). Based on history, future transactions are validated by all the parties (consensus). Internet of Things means connecting lightweight devices to share information among themselves and to enable some functionalities based on the shared information. This exchange of information among multiple devices must be secure as it contains sensitive and safety-critical data. Because of the scale and distributed nature of IoT, security and privacy are major concerns. Traditional security solutions are not suitable for IoT devices as they have limited resources in terms of memory and processing power. Blockchain can bridge the gap. The information exchange among these devices can be stored on the blockchain to increase transparency among the devices. This paper provides a review of literature in the area of IoT and blockchain.
A shape and texture features fusion to retrieve similar Trademark Image Material

Abstract Trademark images or materials such as symbols, text, logos, image, design or phrase are used to unique representation of any organization. Retrieval of trademark material images are important to protect the new trademark image that is to be registered. Therefore, retrieval of similar trademark images is required. In this paper, an approach is presented to extract more similar trademark images so that a unique trademark image can be registered. In this paper, Zernike moment of the query image and dataset images are computed, then most similar images from the dataset are retrieved at the first layer refinement. In the second layer, texture features are extracted of query image and refined dataset images to retrieve most appropriate similar images. Zernike moments is applied to extract global shape features and Scale Invariant Feature Transform (SIFT) and Speeded-Up Robust Feature (SURF) are applied to extract texture features on the basis of a few key-points of the trademark images. A weighted average of both the key-points feature vectors is computed for retrieving the rank1, rank5, rank10, rank15 and rank20 most similar images using Euclidean distance. Experiments have been performed on a proposed dataset to perform the analysis and found that proposed work perform better and improves the accuracy.
INFORMATION AND LIBRARY RESOURCES ON ISSUES OF PEDAGOGY AND EDUCATION (ON THE MATERIALS OF LIBRARY SITES OF UNIVERSITIES OF GERMANY)

The Results of the information review of the materials of the Websites of the Libraries of German Universities are presented. A sample of eleven libraries was formed, the selection criteria for which were the following indicators: The Universality of the acquisition of the fund; the presence in the structure of information resources of collections of rare, handwritten and old printed publications; participation in the network of library institutions located on campuses (libraries), library funds are completed with documents of a narrow-specialized direction. The practical problems of creating Information and library resources on education and pedagogy are highlighted; the defining components of the content and composition of the sites of these libraries are described. The Directions of formation of resources of the researched segment of libraries of universities with single - circuit and double – circuit structure are revealed and generalized. In universities of the first type, libraries perform the functions of the central and peripheral library structure, as a rule, information and library resources on pedagogy and education are exported from OPAC (Online public access Catalog) and KVK (Karlsruher Virtuelle Katalog). In universities with a two-circuit structure of libraries, the site presents resources for educational and pedagogical purposes, in library departments, resources of specialized direction are reflected. The qualitative characteristics of the portals of educational and pedagogical issues, placed on the basis of the DBIS information System, are given. features of the formed information resources on the basis of various information sources, according to needs of users, minimizing information overload by optional («superfluous») information flows are revealed. The directions of content formation, prospects of development of the portal «Pädagogik» are covered.
Visualization of Pterygomaxillary Fissure Structure and Shape in CT Image via Non-Linear Perspective Projection

The neurologist analyses the brain images to diagnose disease via structure and shape of the part in scanned Medical images such as CT, MRI, and PET. The Medical image segmentation performs less in the regions where no or little contrast, artifacts over the different boundary regions. The manual process of segmentation shows poor boundary differentiation due to discernibility in shape and location, intra and inter observer reliability. In this paper, we propose dyadic CAT optimization (DCO) algorithm to segment the regions in the brain from CT and MRI image via Non-linear perspective Foreground and Back Ground projection. The DCO algorithm removes the artifacts in the boundary regions and provide the exact structure and shape of the brain regions. The DCO algorithm shows the region boundary for pterygomaxillary fissure, occipital lobe, vaginal process zygomatic arch, maxilla and piriform aperture in brain image with high visibility in the regions of inadequately visible boundary and distinguishes the deformable shape. The DCO algorithm applies on 50 images and eight images with complex bone and muscle mass structure for performance evaluation. The DCO algorithm shows the increased Structural similarity index (SSIM) with 90% accuracy.
OTT Video over Mobile Networks: Operators Cost and Challenges

Increase of video streaming services popularity led it to become the main contributor to LTE network load. Loaded mobile network by 3rd party applications brings cost for Mobile Network Operators to build new base stations or add additional carriers. This paper presents a short description of OTT video delivery methods, used transport protocols and typical video codecs. Also measurements of video streaming over mobile networks. Equivalent bitrate requirements for video stream measured in different LTE RF signal quality areas. It allows to evaluate LTE network capacity requirements in terms of physical resource blocks utilization.
PENGOLAHAN MATERIAL KAIN GONI SEBAGAI EMBELLISHMENT PADA PRODUK FESYEN

ABSTRACTEmbellishment is widely used in Fashion product applications with a variety of materials and techniques to make it look more attractive. Embellishment in the form of beads, sequins, amulets made of gemstones, wood, plastic, fish scales, leather and processed fabrics that are already in modular or sheet form. One of these processed fabrics is burlap, which is a woven material made of natural fibers in the form of hemp fibers and rosella fibers. In general, burlap materialis widely used in handicraft products such as tablecloths, bags, shoes, wallets, dolls and others. Although there have been many uses of burlap, its use is still limited to handicraft products with low functional and aesthetic values. Along with the development of the fiber usage industry, now the use of materials has been used as an Embellishment in the product, but the application of burlap Embellishment has not experienced many updates in the form of the resulting visual appearance. However, this is a potential development of burlap Embellishment in Fashion products.Based on the explanation above, the authors innovate to develop the burlap material as an embellishment with a more varied form and still pay attention to the character of burlap processing with surface design techniques on bag products.Keywords: Material, Burlap, Embellishment, Surface Design Technique, Fashion Product
An Investigation of Problem Instance Difficulty for Case-Based Reasoning and Heuristic Search

For managing the ever increasing variability of hardware/software interfaces (HSIs), e.g., in automotive systems, there is a need for the reuse of already existing HSIs. This reuse should be automated, and we (meta-)modeled the HSI domain for design space exploration. These models together with additionally defined transformation rules that lead from a model of one specific HSI to another one facilitate automatic adaptations of HSI instances in these models and, hence, both case-based reasoning (CBR) and (heuristic) search. Using these approaches for solving concrete problem instances, estimating their difficulty really matters, but there is not much theory available.This work compares different approaches to estimating problem instance difficulty (similarity metrics, heuristic functions). It also shows that even measuring problem instance difficulty depends on the ground truth available and used. In order to avoid finding only domain-specific insights, we also employed sliding-tile puzzles for our experiments. The experimental results in both domains show how different approaches statistically correlate. Overall, this paper investigates problem instance difficulty for CBR and heuristic search. This investigation led to the insight that admissible functions guiding heuristic search may also be used for retrieving cases for CBR.
The Effect of FDI on the Convergence of Economic Growth Through the Prospective of Institutional Quality in GCC Countries

In the current study, we attempt to develop a model on how institutional quality aids economic growth convergence and FDI inflow in GCC countries using panel dataset spanning 1996 to 2016. We estimate growth convergence by deviating GDP growth rate of individual economy from its group average, emanating equation approximate ADF equation which was used for testing convergence in each economy. We found evidence of economic growth convergence in Saudi Arabia, Kuwait, UAE and Oman, while the economy of Kuwait and Qatar did not converge to the group average. The result of system GMM estimation shows that there is positive and significant relationship between FDI and economic growth in GCC economies, meanwhile, controlling for institutional quality produce mixed result because FDI negatively and significantly relates to FDI. We also found that FDI least contribute to the convergence of economic growth in GCC countries, while institutional quality produces positive and significant impact in converging growth in GCC economy. We therefore, recommend strengthening institutions as well as relaxing stringent rules that may hinder the activities of MNCs.
Digital Smartphone Tracking for COVID-19: Public Health and Civil Liberties in Tension

This Viewpoint compares manual and digital strategies for coronavirus disease 2019 (COVID-19) contact tracing, describes how countries in Asia and Europe have used smartphone tracking, and discusses privacy and discrimination concerns and strategies for balancing public health and civil liberties in the US.
Analyzing Ocular Parameters for Web Browsing and Graph Visualization

This paper proposes a set of techniques to investigate eye gaze and fixation patterns while users interact with electronic user interfaces. In particular, two case studies are presented—one on analyzing eye gaze while interacting with deceptive materials in web pages and another on analyzing graphs in standard computer monitor and virtual reality displays. We analyzed spatial and temporal distributions of eye gaze fixations and sequence of eye gaze movements. We used this information to propose new design guidelines to avoid deceptive materials in web and user-friendly representation of data in 2D graphs. In 2D graph study, we identified that area graph has the lowest number of clusters for user's gaze fixations and lowest average response time. The results of 2D graph study were implemented in virtual and mixed reality environment. Along with this, it was observed that the duration while interacting with deceptive materials in web pages is independent of the number of fixations. Furthermore, web-based data visualization tool for analyzing eye tracking data from single and multiple users was developed.
Supporting Architectural Decision-Making with Data Retrieved from Online Communities

The focal question of this paper is how to support architecture decision-making by utilising data stored in internet services such as Git Hub, Stack Overflow or Wiki Data. Our proposition is to query such internet services in order to identify alternative architectural solutions to a given architectural problem, and to estimate their properties. This would provide assistance to the decision-making architect. The above idea resulted in the implementation of an Architecture Decision Support System (ADSS) prototype. This enabled the validation of the proposed approach in terms of technical feasibility, as well as its usefulness, for software engineers during practical experimental use.
Mathematical theory of analysis and synthesis of control systems based on the general principle of isomorphism

Abstract A new paradigm in the theory of control systems is presented, in which all the basic concepts and properties of systems are formalized on the basis of a single principle - the general principle of isomorphism. The principle made it possible to formulate and prove the realization theorem, on the basis of which the basic concepts (model, abstract system, simple, complex, large system) have been mathematically strictly defined and the fundamental properties of systems and criteria for their provision have been formalized: in a new way, up to isomorphic models of a rather general form, the concepts and criteria of observability, controllability, checkability, identifiability of systems have been defined, and new formalized methods of analysis and synthesis of regulators, observers and integrated information-control systems have been developed, the examples of applications of the theory have been given.
WITHDRAWN: Experimental study on mechanical properties of E-glass fiber reinforced with epoxy composite and compare its properties with hybrid composite

This article has been withdrawn at the request of the author(s). The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal
Multi-Criteria Evaluation of Publication Impacts: Deep Learning in Autonomous Vehicles

Deep learning is the state-of-the-art approach that has been extensively used in the recent years to variety of real-world problems in the literature. The autonomous vehicles are among the applications where their integration with deep learning techniques has potential to disruptively change our daily lives. In this work, we have proposed a multi-criteria framework to evaluate the relative impacts of both publications and authors for deep learning in autonomous vehicles. For the framework, we have considered several criteria extracted from the metadata of the publications and the authors. The conflicts among the criteria are also justified through Pearson correlation. For the experiments, two comprehensive datasets for the publication and the author impacts have been constructed. The resulting pareto-fronts of the datasets after ranking are presented. Moreover, top 30 most impactful publications and authors in the literature are identified. We hope that our findings will be useful for researchers to accelerate the further technological advancements.
Small Unmanned Aerial Vehicle Flight Planning in Urban Environments

This work proposes a fast algorithm for generating obstacle-free and wind-efficient flight paths at a constant above-ground-level altitude in urban environments because a fast flight path planning algorithm is an essential function or service needed for enabling small unmanned aerial vehicle (sUAV) to operate in urban environments within Class G airspace. The proposed method first converts the 3D path planning problem to a 2D problem by constructing an obstacle map at a given above-ground-level altitude. A quad-tree decomposition is then used to build a search space in terms of obstacle occupancy and wind difference. The wind cost of traveling through each cell is defined based on energy consumption under various wind conditions. A repulsive potential is also adopted to make sure that the flight plans stay away from obstacles. The Theta* search algorithm, a variant of A* algorithm, is applied to mitigate the path angle change constraints introduced by grid-based graphs. With the Theta* and postsmoothing techniques, an obstacle-free, wind efficient, and constant above-ground-level flight plan can be quickly generated for sUAV operations in urban environments while meeting the lateral path angle constraints. The results showed that the path planning algorithm is efficient and can be finished within several seconds. With a proper choice of wind coefficient, the proposed path planning algorithm outperforms the multiple-shooting trajectory optimization method even in an obstacle-free environment. With the flexibility of incorporating other geo-related costs and computation efficiency, the proposed algorithm shows the potential for real-time flight path planning in complex urban environments.
A Structural Saliency-Based Approach for Automatic Intrahepatic Vascular Separation From Contrast-Enhanced Multi-Phase MR Images

Intrahepatic vascular separation on contrast-enhanced Magnetic Resonance (MR) images is indispensable for the hepatic tumor surgery. This paper presents an unsupervised frame-work based on structural saliency for automatically separating portal vein (PV) and hepatic vein (HV) from contrast-enhanced multi-phase MR images. In our work, we propose a new multi-scale filter based on statistics and shape information in the region of interest, called SSIROI, with which the vascular connectivity and saliency in the 3D hepatic region can be guaranteed. Experiments are conducted on clinical contrast-enhanced MR images, and the results show that our method achieves effective separation of intrahepatic vasculature by extracting the PV and HV from multi-phase images, and our proposed SSIROI filter outperforms state-of-the-art methods.
The study results of environmental design engineers’ professional activity psychological readiness

The article presents the results of theoretical and empirical research of the design engineers’ (civil engineering) professional activity psychological readiness problem, which was carried out in the general and special abilities’ theory context, the need to take into account general and individual typological mental development. The subject of study was intellectual readiness for work, as a system of mental activity qualities - generalization, awareness, independence, resilience, which are necessary for solving work tasks, and individual style of work - its formation (certainty), compliance with the reference method of work tasks and executive, in connection with the labor activity efficiency - quality and time costs. It was found that these pgsychological readiness components are interrelated, and the oranizing factor in their unity (as well as specific elements and indicators of manifestation) is the generalization of mental activity, which provides the subject's ability to determine and use the optimal way to solve work problems. The conclusion about the need for professionals to develop psychological readiness to work in such a structure is based on the results of empirical research.
Inferring Hierarchical Mixture Structures: A Bayesian Nonparametric Approach

We present a Bayesian Nonparametric model for Hierarchical Clustering (HC). Such a model has two main components. The first component is the random walk process from parent to child in the hierarchy and we apply nested Chinese Restaurant Process (nCRP). Then, the second part is the diffusion process from parent to child where we employ Hierarchical Dirichlet Process Mixture Model (HDPMM). This is different from the common choice which is Gaussian-to-Gaussian. We demonstrate the properties of the model and propose a Markov Chain Monte Carlo procedure with elegantly analytical updating steps for inferring the model variables. Experiments on the real-world datasets show that our method obtains reasonable hierarchies and remarkable empirical results according to some well known metrics.
Countering Adversarial Inference Evasion Attacks Towards ML-Based Smart Lock in Cyber-Physical System Context

Machine Learning (ML) has been taking significant evolutionary steps and provided sophisticated means in developing novel and smart, up-to-date applications. However, the development has also brought new types of hazards into the daylight that can have even destructive consequences required to be addressed. Evasion attacks are among the most utilized attacks that can be generated in adversarial settings during the system operation. In assumption, ML environment is benign, but in reality, perpetrators may exploit vulnerabilities to conduct these gradient-free or gradient-based malicious adversarial inference attacks towards cyber-physical systems (CPS), such as smart buildings. Evasion attacks provide a utility for perpetrators to modify, for example, a testing dataset of a victim ML-model. In this article, we conduct a literature review concerning evasion attacks and countermeasures and discuss how these attacks can be utilized in order to deceive the, i.e., CPS smart lock system’s ML-classifier to gain access to the smart building.