Reviewerly/exHarmony huggingface dataset:
Spatial Focal Loss for Pedestrian Detection in Fisheye Imagery

Objects in the periphery of fisheye images can become extremely distorted. This distortion can cause false positives and missed detections for automated object detection systems. This is problematic, not only for systems which have been trained on perspective images, but also for those that have been explicitly trained on fisheye data. In this paper we propose a new cost function for training object detectors on fisheye images. We model fisheye image distortion as an imbalanced domain problem and develop a domain association loss function to approach it with deep learning. We define separate domains based on the level of distortion within the image plane and propose a new objective function, inspired by the recently introduced focal loss for object detection, which we call a spatial focal loss. Our proposed loss incorporates a domain-modulating term which re-weights samples from different domains to encourage the learning of domain-invariant features. We implement spatial focal loss function in the YOLOv2 architecture and evaluate it on the task of pedestrian detection in a fisheye dataset captured by a 360 camera system mounted on a moving vehicle and labeled with over 11,000 pedestrian instances. Our experiments demonstrate that spatial focal loss can improve model performance in the highly distorted image periphery versus existing loss functions, including focal loss, without sacrificing performance in the less distorted image center, with no adaptations to network architectures required. By analyzing the locations of missed detections, we show further evidence that our loss function can improve the learning of domain-invariant features.
Hooking up mildly or wildly

Abstract This article explores a specific linguistic intervention ("mild to wild”) that occurs in online communication on gay internet hook up sites. It argues that despite supposed knowledge as to what “mild to wild” means, we must look at this linguistic intervention within specific socio-cultural contexts. Without context, the actual uses and meanings of “mild to wild” might be misunderstood while our knowledge of sexual communities of practice risks falling squarely into stereotypes. For this community of practice, “mild to wild” creates a linguistic opportunity for men interested in having sex with other men to be able to define their desires and further explicate how their sexual interaction will take place while also negotiating expectations and assumptions of male-male sex within increasingly homonormative strictures. Data was gathered from over four years of ethnographic research and is presented from a cultural and anthropological linguistics perspective. The phrase “mild to wild” is used by these men in order to: (1) contest supposed concrete categorizations of sexuality and desire; (2) to create highly contextual intimacies and organizations of desire through online-linguistic interaction; and (3) to alleviate detrimental social effects attached to specific unsafe and variant sex practices. The author argues that this community of practice is an example of how new socialities develop within homonormativities designed to control queer sex and desire.
Cognitive and biologically cryptographic protocols for data security

This article presents new methods of cognitive computational paragigms dedicated to data security solutions. Especially, these paragidms will be presented based on new, combined classes of threshold schemes – names linguistic-biometric threshold schemes. Linguistic, biometric and combined classes of protocols applied cognitive techniques for data analysis, so new classes of cryptographic threshold schemes also based on cognitive techniques. Cognitive and bilogically cryptographic protocols can be applied for data/secret security. It’s possible by used cryptographic techniques based on threshold protocols. These protocols provide secret protection by splitting and distributing shadows between protocol participants. Participants of the protocol receive shadows of a shared secret and ensure their total security by managing them. The authors of this paper have solved the problem of combining existing linguistic and biometric protocols of data protection. The proposed innovative combination of secret protection protocols give new possibilities of application for linguistic-biometric threshold schemes. One of possible application of such protocols is Cloud application, so in this paper will be also describe this possible application. The fundamental methods of data and service protection, dedicated to processes of its security will be describe by cryptographic algorithms, particularly data sharing protocols. This paper will discuss a detailed description of proposed algorithms and their characteristic features.
Novel Trace-Based Construction of the Parallel-In-Serial-Out Multiplication for Elliptic Curve Digital Signature Algorithm Like Binary Extension Fields

The Gaussian normal bases (GNBs) recommended by the National Institute of Standards and Technology (NIST) for the five binary extension fields of the Elliptic Curve Digital Signature Algorithm (ECDSA), are self-dual. Multiplication, is a complex, and critical, field operation for the hardware-oriented implementations of field inversion - an important operation in the elliptic curve based algorithms - in the GNB representation. This paper, introduces a novel construction for the bit-serial parallel-in-serial-out (BS-PISO) multiplication over the "NIST-like" fields, based on the Trace mapping. The new formulations, are presented for the first time in literature as far as we know, and provide a new and simple understanding of the Trace-based mathematical model behind such a BS-PISO multiplication. In addition, derivation of existing formulations for the PISO GNB field multiplication, based on the new Trace-based construction, is presented. A digit-serial most-significant-digit first PISO field multiplication architecture is constructed, based on the new Trace-based BS-PISO formulations, and the corresponding theoretical space and time complexities are derived and compared to other counterparts. Moreover, post synthesis space and time readings are reported, based on Application specific integrated circuit (ASIC) realizations, using the NANGate 45nm open cell libraries.
The Design of UDOO Boards: Contributing to the Appropriation of Digital Technology

The domain of Human-Computer Interaction does not concern just the design of technology that is easy to use, useful, and fancy – it has to do with our role in shaping our environment, our ecological niche that today involves the whole earth. A key concept in the interaction between humans and computing resources is that of appropriation originally proposed by Aleksei Nikolaevich Leontiev. In the present paper we will first review the concept of appropriation and will present bricolage as a key activity for fostering appropriation. Then we will present the Makers Movement as a socio-cultural movement relevant for the process of appropriation of digital technology. Finally, we will describe our approach and vision in the design of the UDOO, a single board computer, and of a specific developing environment, UAPPI, for enabling the appropriation through meaningful activities of digital technologies.
SSIM and ML based QoE enhancement approach in SDN context

Today, video streaming rose above all other traffic types over the internet. While providing this service with a high quality is the most challenging task, researchers are trying to solve the challenge by giving a more efficient network where congestion, broadband limitations and unsatisfied users are limited. In new multimedia based networks, new challenges move from technology-oriented services to user-oriented services which prove the importance of QoE. Service providers' growth depends nowadays not only on QoS parameters but also on clients' feeling and expectation. That is why; service providers must measure received QoE and this becomes a challenge regarding the evaluation of users' feeling. For users, qualitative perception differs from one user to another and service providers affront difficulties to transform the qualitative values into the quantitative one. The QoE evaluation needs more sophisticated methods to describe the real expectation of users. New multimedia applications provide at any user locations media who are sharing video, and communicating together in virtual network. These applications require providing the best possible QoE to consumers. When it comes to us, we present in this paper a machine learning approach combined with adaptive coding in order to provide a better QoE for video streaming services. This solution will be established using SDN architecture. We can justify this choice because we need a centralized architecture, where the totality of the network is known, to predict its status. So, we will implement a machine learning algorithm in the controller: this algorithm, called ML-based SSIM, will calculate approximately the quality needed for a video to be streamed. Finally, the quality found by the ML-based SSIM Algorithm will be combined with the network situation to choose the right coding. First part of the paper deals with an introduction of QoE requirement, metrics and protocols used especially in streaming services, then we give a complete study around Machine learning algorithms and other fields used in literature to enhance QoE. We define in this paper, at first, QoS and QoE, then the serving environment such as mobile cloud computing and software Defined Network (SDN). Then, we give both objective and subjective metrics, expose mathematical approaches used in modeling, predicting and evaluating QoE. Second, we expose the SSIM approach and explain how our proposed one is based on. The last part of the paper deals with experiments: we describe SDN environment deployment, describe scenarios and finally simulate on SDN emulator some topologies to demonstrate the impact of SDN components helping QoE measurement. At the end, we give the results and values. We highlight the future of our proposition.
Swagger-based jQuery Ajax Validation

JavaScript is a vital programming language for web applications and it is becoming more important as it is being adopted for developing mobile and desktop applications. Many JavaScript applications are making use of Ajax requests to communicate with remote servers to fulfill its intended purpose. The use of Ajax requests in JavaScript results in two main issues, traditional type checking in other programming languages is not available in JavaScript and JavaScript application does not know what APIs the remote server serves. In this paper, we will introduce a novel tool called Ajax Validator to solve some of the consequences of the mentioned issues. We will use Swagger to validate Ajax requests against their specifications in terms of Local Ajax HTTP Method and Body consistency, Local Ajax HTTP Method and Remote HTTP Method consistency, and Local and Remote HTTP Headers consistency. To evaluate our tool, we obtained 666 swagger specifications for different API providers using the GURU project and nine JavaScript applications from GitHub. From the nine JavaScript Applications, our results showed that eight applications were locally consistent, and one was not. Five applications were remotely consistent, one was not and three of them were not applicable to the validator checking, due to syntax errors or non-matching paths in the Swagger specification. Regarding the header validation, one application was missing two headers in one of its Ajax requests that were specified in the Swagger specification. Also, the same Ajax request specified three headers that were not expected by the Swagger specification. Allowing IDEs to have such Ajax requests checking capabilities in static time will help in reducing the testing costs as long as reducing the runtime errors that a developer could face and fix.
A Conversation with Actuators

An exciting, expanding palette of hybrid materials is emerging that can be programmed to actuate by a range of external and internal stimuli. However, there exists a dichotomy between the physicality of the actuators and the intangible computational signal that is used to program them. For material practitioners, this lack of physical cues limits their ability to engage in a "conversation with materials" (CwM). This paper presents a creative workstation for supporting this epistemological style by bringing a stronger physicality to the computational signal and balance the conversation between physical and digital actors. The station utilizes a streaming architecture to distribute control across multiple devices and leverage the rich spatial cognition that a physical space affords. Through a formal user study, we characterize the actuation design practice supported by the CwM workstation and discuss opportunities for tangible interfaces to hybrid materials.
A Wavelet-Based Blind Digital Image Watermarking using Dynamic LSB Replacement (DLSBR) and Symmetric Key Cryptography

With advancement of technology and ease of access of digital information and its creation and transference, protection of copyrights for information security is of the prime concern. Digital watermarking gives copyright protection of digital images by impregnating additional information in the original cover image. Thus, watermarking prevents illegal copying by providing a method of enacting the ownership of a redistributed copy. In this paper, we have proposed a wavelet-based dynamic LSB replacement method, which serves the purpose by providing excellent robustness and imperceptibility. Moreover, the watermark is encrypted by a symmetric key cryptographic algorithm to make it secure from further eavesdropping.
Exploring Craft in the Context of Digital Fabrication

In this work in progress, we start to unpack the act of making in a digital fabrication process. In particular, one kind of digital fabrication - 3D printing - that is typically considered to be highly automated but in this case is not. In this process, a tension exists between our skills, the properties of a novel material and the capabilities of a novel machine. As design researchers, we navigated through the design space that emerged in this tension and explored how to 3D print in wood. In unpacking this tension between machine, material and designer, we pay attention to how the embodied nature of this process was essential for its development. We start to explore how we might explain the embodied act of making in the context of digital fabrication through the lense of ambiguity and resistance, notions previously used to unravel craftsmanship.
Approximate training of one-class support vector machines using expected margin

One-class support vector machine (OCSVM) has demonstrated superior performance in one-class classification problems. However, its training is impractical for large-scale datasets owing to high computational complexity with respect to the number of training instances. In this study, we propose an approximate training method based on the concept of expected margin to obtain a model identical to full training with reduced computational burden. The proposed method selects prospective support vectors using multiple OCSVM models trained on small bootstrap samples of an original dataset. The final OCSVM model is trained using only the selected instances. The proposed method is not only simple and straightforward but also considerably effective in improving the training efficiency of OCSVM. Preliminary experiments are conducted on large-scale benchmark datasets to examine the effectiveness of the proposed method in terms of approximation performance and computational efficiency.
Multimodal image registration of pre- and intra-interventional data for surgical planning of transarterial chemoembolisation

Multimodal registration improves surgical planning and the performance of interventional procedures such as transarterial chemoembolizations (TACE), since it allows to combine complementary information provided by pre- and intrainterventional data about tumor localization and access. However, no registration methods specifically developed for the multimodal registration of abdominal scans exist and as a result only general-purpose methods are available for this application. In this paper, we evaluate and optimize the performance of three standard registration methods which rely on different similarity metrics, namely Advanced Mattes Mutual Information (AMMI), Advanced Normalized Correlation (ANC) and Normalized Mutual Information (NMI), for the registration of preinterventional T1- and T2-weighted MRI to preinterventional CT as well as intrainterventional Cone Beam CT (CBCT) to preinterventional CT of the liver. Moreover, different variants of the registration algorithms, based on the introduction of masks and different resolution levels in multistage registrations, are investigated. To evaluate the performance of each registration method, the capture range was estimated based on the calculation of the mean target registration error.
Boundary Recovery of Depth Map for Synthesis View Optimization in 3D Video

Depth map generally includes structural errors and blurs near boundaries due to the limitation of depth acquisition technique. These distortions severely degrade the quality of synthesis views in 3D video systems. In this paper, we propose a method to accurately recover the boundaries of the depth map with the guidance of its associated texture image. First, we detect the structural error regions of the depth map by considering its structural consistency with the texture image. Then, we incorporate the information of the detected structural error regions into the weight term of the general weighted median filter for depth map recovery. Experiments are conducted on a set of depth maps. The results show that the boundaries of the depth maps with the proposed method are more accurate and clear than that of the other methods. Consequently, it well improves the subjective quality of the synthesis views.
Detection of sea surface obstacle based on super-pixel probabilistic graphical model and sea-sky-line

With the development of marine resources, the USV (Unmanned Surface Vehicle) was widely used as a platform for autonomous navigation in the marine environment. In order to ensure the safe navigation of USV, this paper proposed a sea surface obstacle detection method based on probability graphical model and sea-sky-line. Our method utilized the SLIC algorithm to segment the sea surface image for image pre-processing. Then, we proposed the superpixel-based probability graphical model to segment the image, and the sea surface image would be divided into three main semantic regions and an obstacle region. Finally, we proposed a sea-sky-line detection algorithm. Based on this, obstacles within the sea-sky-line would be detected. The accuracy of this method has reached 82.1%, and the recall rate has reached 92.0%. The method can effectively avoid the interference of sea surface reflection and objects such as clouds in the sky, and has a good effect on the detection of obstacles.
On Cryptographic Properties of Some Lightweight Algorithms and its Application to the Construction of S-Boxes

We consider some approaches to the construction of lightweight block ciphers and introduce the definitions for "index of strong nonlinearity" and "index of perfection". For PRESENT, MIDORI, SKINNY, CLEFIA, LILLIPUT mixing and nonlinear properties were evaluated. We obtain the exact values of the exponents for mixing matrices of round functions and the upper bounds for indexes of perfection and strong nonlinearity. It was determined by the experiment that each coordinate function of output block is nonlinear during 500 rounds. We propose the algorithmic realization of 16×16 S-box based on the modified additive generator with lightweight cipher SPECK as a modification which does not demand memory for storage huge substitution tables. The best value of the differential characteristic of such S-box is 18/2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">16</sup> , the minimal nonlinearity degree of coordinate functions is equal to 15 and the minimal linear characteristic is 788/2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">15</sup> .
Privacy-Preserving Data Collection Scheme on Smartwatch Platform

In recent years, smartwatches, which are the most representative wearable device exploiting Internet of things technologies, have been developed and used. With growing use of smartwatches in the healthcare field, there have been considerable efforts to use diverse smartwatch sensor data such as heart rates and body temperatures with the aim of improving healthcare services. However, because the data collected from smartwatches usually contain sensitive user information, individual users are reluctant to provide their data to healthcare service providers because of privacy concerns. Thus, to support such healthcare service provider needs, a method capable of collecting individuals' sensitive data from smartwatches, while preserving privacy, is presented. Preliminary experimental results demonstrate that the proposed approach is well suited to the collection of smartwatch users' sensitive data for the purpose of inferring population statistics while preserving privacy.
Exploring experiences of librarians in Zimbabwean state universities with the consortium model of subscribing to electronic journals

The study explores the experiences of librarians in three state universities in Zimbabwe with the consortium model of subscribing to electronic journals. The study employed a qualitative approach. Interviews were held with nine professional librarians from each of the participating institutions. Findings showed that state universities in Zimbabwe have benefitted from consortium subscribed electronic journals; however, librarians were concerned about their coverage and relevancy. Librarians felt disempowered as they have lost the independence to select resources suitable for their own institutions. The lack of archival rights is detrimental to post-termination access to previously subscribed resources. Institutions face challenges with technological infrastructure that allows them to convey consortium resources to their users. The study provides important insight into the practice of consortium from a developing country context. The findings will alert consortia managers and member institutions to the key shortfalls of consortia arrangements. The study’s recommendations hopefully triggers corrective actions aimed at improving the practice of consortia to the benefit of end users.
New Construction of Blind Signatures From Braid Groups

A new construction of a blind signature scheme based on braid groups is proposed. In the random oracle model, the proposed scheme is provably unforgeable against chosen message attacks, assuming that the one-more matching conjugate problem in braid groups is intractable. Furthermore, in the infinite group model, the scheme is proved to be perfectly blind. Our construction represents a technique to lift a braid group to its conjugate subgroups for particular applications. The proposed scheme is very fast in signing but relatively slow in verifying and is thus suitable for scenarios that require signing as soon as possible but permit a slight delay in verifying. In addition, our proposal is invulnerable to known quantum attacks and therefore would be a good alternative to RSA-based and DLP-based blind signatures in the post-quantum era.