Reviewerly/exHarmony huggingface dataset:
Overlap-Free Drawing of Generalized Pythagoras Trees for Hierarchy Visualization

Generalized Pythagoras trees were developed for visualizing hierarchical data, producing organic, fractal-like representations. However, the drawback of the original layout algorithm is visual overlap of tree branches. To avoid such overlap, we introduce an adapted drawing algorithm using ellipses instead of circles to recursively place tree nodes representing the subhierarchies. Our technique is demonstrated by resolving overlap in diverse real-world and generated datasets, while comparing the results to the original approach.
BlockSwap: Fisher-guided Block Substitution for Network Compression on a Budget

The desire to map neural networks to varying-capacity devices has led to the development of a wealth of compression techniques, many of which involve replacing standard convolutional blocks in a large network with cheap alternative blocks. However, not all blocks are created equally; for a required compute budget there may exist a potent combination of many different cheap blocks, though exhaustively searching for such a combination is prohibitively expensive. In this work, we develop BlockSwap: a fast algorithm for choosing networks with interleaved block types by passing a single minibatch of training data through randomly initialised networks and gauging their Fisher potential. These networks can then be used as students and distilled with the original large network as a teacher. We demonstrate the effectiveness of the chosen networks across CIFAR-10 and ImageNet for classification, and COCO for detection, and provide a comprehensive ablation study of our approach. BlockSwap quickly explores possible block configurations using a simple architecture ranking system, yielding highly competitive networks in orders of magnitude less time than most architecture search techniques (e.g. 8 minutes on a single CPU for CIFAR-10).
The secret life of PETs

Purpose The purpose of this paper is to explore to what extent the legal environment influences a user’s choice to employ privacy-enhancing technologies (PETs). Drawing upon existing theoretical frames specific to arbitrariness and uncertainty, this research examines whether interest in PETs is influenced by the legal environment of a country. Design/methodology/approach Using data from Google Trends, the International Property Rights Index, Freedom House and the Organization for Economic Cooperation and Development, the research analyzes interest in Tor, VPN technology and pretty good privacy (PGP) in 153 countries between 2012 and 2016. Findings Findings suggest both countries with both higher and lower arbitrariness and uncertainty of law are associated with an increased interest in Tor and PGP. However, interest in VPN technology does not appear influenced by the legal environment and, instead, is influenced by freedom within the press. Research limitations/implications The dual use nature of Tor and PGP is influenced by law enforcement and judiciary effectiveness and transparency and arbitrariness contributing to the public’s interest in decentralized technological protections. Practical implications Law enforcement should continue to police via the technologies rather than shutting them down to protect the identities of those needing to use these technologies for legitimate purposes. Only by embracing the technologies, as opposed to seeing them as hurdles to be banned, may law enforcement agencies remain vigilant to the threats posted by nefarious actors. Originality/value In this study, the authors introduce a more robust measure of interest in PETs, and do so with a larger, more substantive sample. By situating this interest within the context of policing, the authors can document the dual use nature of the technology, which can be useful in guiding future research, specifically in the area of policy development and officer training.
THE MARKET FOR CRYPTOCURRENCY: HOW WILL IT EVOLVE?

This study examines the concept of cryptocurrency and gives a brief history and overview of its characteristics. In an increasingly electronic society, cryptocurrency could be the next step in the evolution of finance in the same way that the internet was a step in the evolution of communication. In the coming years, countries may even announce the release of national cryptocurrencies, although certain conditions must be met for these efforts to be successful. Although the market is still in the early stages, as it begins to mature, cryptocurrency may become more prominent, until it becomes the new status quo.
Genetic–Frog-leaping Algorithm for Text Document Clustering

In recent years, the volume of information in digital form has increased tremendously owing to the increased popularity of the World Wide Web. As a result, the use of techniques for extracting useful information from large collections of data, and particularly documents, has become more necessary and challenging. Text clustering is such a technique; it consists in dividing a set of text documents into clusters (groups), so that documents within the same cluster are closely related, whereas documents in different clusters are as different as possible. Clustering depends on measuring the content (i.e., words) of a document in terms of relevance. Nevertheless, as documents usually contain a large number of words, some of them may be irrelevant to the topic under consideration or redundant. This can confuse and complicate the clustering process and make it less accurate. Accordingly, feature selection methods have been employed to reduce data dimensionality by selecting the most relevant features. In this study, we developed a text document clustering optimization model using a novel genetic frog-leaping algorithm that efficiently clusters text documents based on selected features. The proposed approach is based on two metaheuristic algorithms: a genetic algorithm (GA) and a shuffled frog-leaping algorithm (SFLA). The GA performs feature selection, and the SFLA performs clustering. To evaluate its effectiveness, the proposed approach was tested on a well-known text document dataset: the “20Newsgroup” dataset from the University of California Irvine Machine Learning Repository. Overall, after multiple experiments were compared and analyzed, it was demonstrated that using the proposed algorithm on the 20Newsgroup dataset greatly facilitated text document clustering, compared with classical K-means clustering. Nevertheless, this improvement requires longer computational time.
Analysis review on spatial and transform domain technique in digital steganography

This paper presents several techniques used in digital steganography in term of spatial and transform domain. Additionally, it analyses the performance and the metric evaluation of the techniques used in digital steganography based on spatial and transform domain. This paper aims to identify the main mediums of digital steganography, which are image-based, video-based and audio-based, in order to recognize the various techniques used with them. As a result, the primary technique used in the digital medium was LSB technique in the spatial domain, while in the transform domain, the main technique used was differentiated between DTC and DWT. Meanwhile, the common domain utilized in digital steganography was the spatial domain due to its simplicity and high embedding capacity. The future efforts for this paper will be considering the feature based in text steganography.
Building Energy Management System Modelling via State Fuzzy Cognitive Maps and Learning Algorithms

The last decades the decrease of the energy consumed by the building sector has become a crucial subject. This is the reason why the modelling and control of Building Energy Management Systems (BEMS) has become a very important scientifc feld. In such a system where the human factor and the uncertainties caused by its presence play a very important role the need for intelligent, cognitive modelling methodologies becomes obvious. The State Fuzzy Cognitive Maps Methodology combined with Nonlinear Hebbian Learning techniques are used to model the behaviour of a BEMS and improve its response.
State Transformation Extended Kalman Filter for SINS based Integrated Navigation System

This paper first gives further explanations of the State Transformation Extended Kalman Filter (ST-EKF) from the perspective of common frame velocity error definition. Then develops the loosely-coupled integrated navigation models for Strapdown Inertial Navigation System (SINS)/Global Navigation Positioning System (GNSS) integration, which includes the system error models and measurement models. In the framework of EKF, the propagation of the state and covariance should be executed as fast as possible in order to capture the dynamic change of specific force. For example, the propagation rate is the same as the SINS calculation rate. However, in the framework of ST-EKF, the propagation and measurement updating processes can be implemented simultaneously, which reduces the computation cost greatly. Land vehicle experiment by using a Micro-Electro-Mechanical-Systems (MEMS)-Inertial Measurement Unit (IMU) was conducted to validate the performance of the ST-EKF. Results showed that ST-EKF integrated navigation system had higher positioning when GPS signals were loss from multiple locations. Meanwhile, ST-EKF had higher yaw and velocity maintaining accuracy than EKF when under quasi-static parking situations.
Polarized-state-based coding strategy and phase image estimation method for robust 3D measurement

Polarized structured light is a novel method to measure shiny surface. However, the SNR of the captured image was affected by the additional polarizing filter. And the blurred influence of camera defocus was also strengthened. The accuracy of fringe edges detection was reduced. In this paper, a polarized-state-based structured light coding strategy and a phase image estimation method are proposed to improve the measurement robustness. To preserve the coding message in the complex environment, a special polarized-state-based coding strategy is adopted. To reduce the error which induced by additional polarizing filter and extracting the information from the saturated areas as much as possible, a phase image estimation method based on Stokes parameter is proposed. Compared with the traditional polarization-based structured light system, the experimental setup of proposed method is configured without any additional hardware. The experiment shows that the interference of camera defocus is remarkably reduced and the robustness of fringe edges detection is improved.
Revisiting Lightweight Encryption for IoT Applications: Error Performance and Throughput in Wireless Fading Channels With and Without Coding

Employing heavy conventional encryption algorithms in communications suffers from added overhead and processing time delay; and in wireless communications, in particular, suffers from severe performance deterioration (avalanche effect) due to fading. Consequently, a tremendous reduction in data throughput and increase in complexity and time delay may occur especially when information traverse resource-limited devices as in Internet-of-Things (IoT) applications. To overcome these drawbacks, efficient lightweight encryption algorithms have been recently proposed in literature. One of those, that is of particular interest, requires using conventional encryption only for the first block of data in a given frame being transmitted. All the information in the remaining blocks is transmitted securely without the need for using heavy conventional encryption. Unlike the conventional encryption algorithms, this particular algorithm achieves lower overhead/complexity and higher data throughput. Assuming the additive white Gaussian noise (AWGN) channel, the performance of the lightweight encryption algorithm under study had been evaluated in literature in terms of throughput under the assumption that the first block, that undergoes conventional encryption, is free of error, which is practically unfeasible. In this paper, we consider the AWGN channel with Rayleigh fading and assume that the signal experiences a certain channel bit error probability and investigate the performance of the lightweight encryption algorithm under study in terms of bit error probability and throughput. We derive analytical expressions for these performance metrics considering modulated signals with and without coding. In addition, we propose an extension to the lightweight encryption algorithm under study by further enhancing its security level without significantly affecting the overhead size and processing time. Via numerical results we show the superiority of the lightweight encryption algorithm under study over the conventional encryption algorithms (like the AES) and the lightweight encryption algorithms proposed in literature in terms of error and throughput performance.
The hunt for computerized support in information security policy management

Purpose The purpose of this paper is to survey existing information security policy (ISP) management research to scrutinise the extent to which manual and computerised support has been suggested, and the way in which the suggested support has been brought about. Design/methodology/approach The results are based on a literature review of ISP management research published between 1990 and 2017. Findings Existing research has focused mostly on manual support for managing ISPs. Very few papers have considered computerised support. The entire complexity of the ISP management process has received little attention. Existing research has not focused much on the interaction between the different ISP management phases. Few research methods have been used extensively and intervention-oriented research is rare. Research limitations/implications Future research should to a larger extent address the interaction between the ISP management phases, apply more intervention research to develop computerised support for ISP management, investigate to what extent computerised support can enhance integration of ISP management phases and reduce the complexity of such a management process. Practical implications The limited focus on computerised support for ISP management affects the kind of advice and artefacts the research community can offer to practitioners. Originality/value Today, there are no literature reviews on to what extent computerised support the ISP management process. Findings on how the complexity of ISP management has been addressed and the research methods used extend beyond the existing knowledge base, allowing for a critical discussion of existing research and future research needs.
Domain Adaptive Multibranch Networks

We tackle unsupervised domain adaptation by accounting for the fact that different domains may need to be processed differently to arrive to a common feature representation effective for recognition. To this end, we introduce a deep learning framework where each domain undergoes a different sequence of operations, allowing some, possibly more complex, domains to go through more computations than others.This contrasts with state-of-the-art domain adaptation techniques that force all domains to be processed with the same series of operations, even when using multi-stream architectures whose parameters are not shared.As evidenced by our experiments, the greater flexibility of our method translates to higher accuracy. Furthermore, it allows us to handle any number of domains simultaneously.
Attack on LAC Key Exchange in Misuse Situation

LAC is a Ring Learning With Error based cryptosystem that has been proposed to the NIST call for post-quantum standardization and passed the first round of the submission process. The particularity of LAC is to use an error-correction code ensuring a high security level with small key sizes and small ciphertext sizes. LAC team proposes a CPA secure cryptosystem, LAC.CPA, and a CCA secure one, LAC.CCA, obtained by applying the Fujisaki-Okamoto transformation on LAC.CPA. In this paper, we study the security of LAC Key Exchange (KE) mechanism, using LAC.CPA, in a misuse context: when the same secret key is reused for several key exchanges and an active adversary has access to a mismatch oracle. This oracle indicates information on the possible mismatch at the end of the KE protocol. In this context, we show that an attacker needs at most 8 queries to the oracle to retrieve one coefficient of a static secret key. This result has been experimentally confirmed using the reference and optimized implementations of LAC. Since our attack can break the CPA version in a misuse context, the Authenticated KE protocol, based on the CCA version, is not impacted. However, this research provides a tight estimation of LAC resilience against this type of attacks.
Blockchain: Moving Beyond Bitcoin into a Digitalized World

Little over a decade has passed since Blockchain gave birth to its prodigy Bitcoin, but Bitcoin despite all the hype (which was referred to as “big bang” by many) failed to become a simple (stable) global crypto-currency for everyday life to enable users worldwide to purchase products/services online, transfer money and conduct business with both individuals and entities within seconds without going through access related issues and financial burden of high transactional costs. Blockchain’s close link to Bitcoin has been rather negative on the revolutionary technology to live its true potential, but now it is time for blockchain to move beyond Bitcoin. Blockchain distributed ledger technology (DLT) can be used in many areas that are traditionally under government control. In fact, numerous tools and applications we are so accustomed to using or seeing around could be decentralized via blockchain to create a paperless digitalized world; as a side goal, this could possibly help reduce global warming as well. Internet, marketing (advertisement), asset management, traffic control, utilities (electric, gas, and water) and social security (retirement benefits) can all be decentralized through blockchain to provide more efficient and unrestricted access to personal and public records. Blockchain possesses immense opportunities and has the capacity to take unimaginable forms in the future, but only if regulators, law makers, central banks and other branches of governments allow it to happen.
Simulated and Real-World Evolution of Predator Robots

This paper addresses the problem of designing behavioural strategies for a group of robots with a specific task, capturing another robot. Our proposed approach is to employ a smart prey with a pre-programmed strategy based on a novel Gaussian model of danger zones and use an evolutionary algorithm (EA) to optimize the predators’ behavior. The EA is applied in two stages: first in simulation, then in hardware on the real robots. The best evolved robot controllers are then further inspected and compared by their robustness, i.e., performance under different conditions. The results show that our approach is successful, combining simulations, real-world evolution, and robustness analysis it is possible to develop good solutions for the predator-prey problem.
A Semantic Agile Approach for Reconfigurable Distributed Applications in Pervasive Environments

Nowadays, future mobile applications must have the ability to use distributed smart connected objects on various smart cities domains. Most existing mobile applications have mostly neglected to consider the user's current needs and their preferences that continuously quickly evolve. The authors have developed a novel framework to generate dynamically distributed application as service chains of components and optimize connected objects life cycle. The framework combines a generic context-aware ontology situation model, middleware and IoT for managing user's composite situations at the design and the run-time levels. The first level consists of modeling applications, profiles and usage contexts through a model-driven methodology considering the specified user's constraints. The second level consists of context monitoring mechanisms, situation reasoning and deploying adapted services using Kai-smart platform for meeting user's needs and its current contexts. The proposed framework is validated through several use cases in different smart domains.
Super-resolution magnetic resonance imaging reconstruction using deep attention networks

We propose a deep-learning-based method to reconstruct super-resolution images from routinely captured MRI images. We propose to integrate a deeply supervised attention model into a generative adversarial network (GAN)-based framework to improve MRI image resolution. Deep attention GANs are introduced to enable end-to-end encoding-and-decoding learning. Next, an attention model is used to retrieve the most relevant information from the encoder. The residual network is used to learn the difference between low- and high-resolution images. This technique was validated with 20 patients. We performed a leave-one-out cross-validation method to evaluate the proposed algorithm and further tested it with a down-sampling rate 1/3 and 1/6. Our reconstructed high-resolution MRI images from down-sampling images were compared with the original image to evaluate the performance quantitatively. The reconstructed super-resolution images were compared to a high-resolution reference scan using and the mean absolute error (MAE) and peak signal-to-noise ratio (PSNR) of image intensity profiles. The MAE and PSNR between reconstructed and original images for 1/3 down sampling rate were 3.86±1.53 and 41.95 ± 5.06dB, and 9.45 ± 1.73, 35.05 ± 3.64dB for 1/6 respectively, which demonstrates the accuracy of the proposed method.
Renal biopsy under augmented reality guidance

Kidney biopsies are currently performed using preoperative imaging to identify the lesion of interest and intraoperative imaging used to guide the biopsy needle to the tissue of interest. Often, these are not the same modalities forcing the physician to perform a mental cross-modality fusion of the preoperative and intraoperative scans. This limits the accuracy and reproducibility of the biopsy procedure. In this study, we developed an augmented reality system to display holographic representations of lesions superimposed on a phantom. This system allows the integration of preoperative CT scans with intraoperative ultrasound scans to better determine the lesion’s real-time location. An automated deformable registration algorithm was used to increase the accuracy of the holographic lesion locations, and a magnetic tracking system was developed to provide guidance for the biopsy procedure. Our method achieved a targeting accuracy of 2.9 &plusmn; 1.5 mm in a renal phantom study.