Reviewerly/exHarmony huggingface dataset:
Exploiting Emerging Sensing Technologies Toward Structure in Data for Enhancing Perception in Human-Centric Applications

Structure in data can be leveraged to enhance learning. In many perception tasks, the embedded signals arising from physical processes of interest naturally have structure of high semantic relevance. However, traditional forms of remote sensing (e.g., vision) preserve such structure only in limited ways. This paper examines how embedded, form-fitting sensing, referred to as physically integrated (PI) sensing, can preserve such structure in richer ways. While the analysis is agnostic to the particular technology for PI sensing, for which a range of options is emerging, especially driven by the Internet of Things, a particular emerging technology called large-area electronics (LAE) is considered. Using synthetic data from 3-D modeling and rendering of human-activity scenes, LAE-based PI sensing and vision-based remote sensing are emulated and perception systems are formed, showing: 1) enhanced data-efficiency of learning models based on PI sensing; 2) potential for selective deployment of PI sensors in new perception tasks, thanks to robust ranking of their value in such tasks; 3) enhanced data-efficiency of learning models based on vision sensing, by integrating PI sensing; and 4) efficient mapping of PI-sensing features across perception tasks to enhance transferability of learning.
Hybrid 4D cardiovascular modeling based on patient-specific clinical images for real-time PCI surgery simulation

In this paper, we proposed a hybrid 4D cardiovascular modeling method based on the clinical CTA and MRI to simulate the motion of the heart, as well as the patient-specific vessel structure attached to the heart model, in order to support the personalized Percutaneous Coronary Intervention (PCI) simulation which is used to train surgeons of skills and to help planning surgery. To obtain patient-specific vessel structure, a coarse segmentation with the centerlines extraction subsequently is applied to the computed tomography (CT) scans and the vessels along the centerlines is modeled using a lofted 2D segmentation method. The vessels are then combined with a template heart model to construct a cardiovascular system. For the cardiac motion, we estimate the ventricles motion from 4D Magnetic Resonance Imaging (MRI) sequences to drive the whole heart motion. And the position-based method coupling with a mass-spring model constructed with elastic spheres is used to simulate the cardiac motion cycle stably in the interactive PCI simulator. With our method, a personalized highly realistic beating motion of a whole heart is able to be created and applied to our patient-specific PCI surgery simulation system.
A touchless interaction interface for observing medical imaging

Using volume rendering to generate 3D models is associated with the problem of missing features on areas of interest, which are possibly concealed by other information. This article presents a novel focus-and-context medical imaging observation system using gesture-based technique to build a touchless interactive environment. The system offers two types of medical imaging observation tool, namely, 3D section cutting tool and 3-axes cross-section synchronization tool, enabling users to quickly and easily observe tissue sections. Feature classification was achieved using region growing and size-based transfer approaches. Combined with view penetration function (cylinder and cone view penetration functions), the system allows for direct observation of hidden features. The analytical experimental results verified that the proposed system is easy to operate in a touchless environment and creates positive user experience regarding observation and interaction.
Approximate Homomorphic Encryption over the Conjugate-Invariant Ring

The Ring Learning with Errors (RLWE) problem over a cyclotomic ring has been the most widely used hardness assumption for the construction of practical homomorphic encryption schemes. However, this restricted choice of a base ring may cause a waste in terms of plaintext space usage. For example, an approximate homomorphic encryption scheme of Cheon et al. (ASIACRYPT 2017) is able to store a complex number in each of the plaintext slots since its canonical embedding of a cyclotomic field has a complex image. The imaginary part of a plaintext is not underutilized at all when the computation is performed over the real numbers, which is required in most of the real-world applications such as machine learning. In this paper, we are proposing a new homomorphic encryption scheme which supports arithmetic over the real numbers. Our scheme is based on RLWE over a subring of a cyclotomic ring called conjugate-invariant ring. We show that this problem is no easier than a standard lattice problem over ideal lattices by the reduction of Peikert et al. (STOC 2017). Our scheme allows real numbers to be packed in a ciphertext without any waste of a plaintext space and consequently we can encrypt twice as many plaintext slots as the previous scheme while maintaining the same security level, storage, and computational costs.
Robust Depth Estimation Using Auto-Exposure Bracketing

As the computing power of hand-held devices grows, there has been increasing interest in the capture of depth information, to enable a variety of photographic applications. However, under low-light conditions, most devices still suffer from low imaging quality and inaccurate depth acquisition. To address the problem, we present a robust depth estimation method from a short burst shot with varied intensity (i.e., Auto-exposure bracketing) and/or strong noise (i.e., High ISO). Our key idea synergistically combines deep convolutional neural networks with geometric understanding of the scene. We introduce a geometric transformation between optical flow and depth tailored for burst images, enabling our learning-based multi-view stereo matching to be performed effectively. We then describe our depth estimation pipeline that incorporates this geometric transformation into our residual-flow network. It allows our framework to produce an accurate depth map even with a bracketed image sequence. We demonstrate that our method outperforms state-of-the-art methods for various datasets captured by a smartphone and a DSLR camera. Moreover, we show that the estimated depth is applicable for image quality enhancement and photographic editing.
Obfuscatable Anonymous Authentication Scheme for Mobile Crowd Sensing

Mobile crowd sensing (MCS) is a rapidly developing technique for information collection from the users of mobile devices. This technique deals with participants' personal information such as their identities and locations, thus raising significant security and privacy concerns. Accordingly, anonymous authentication schemes have been widely considered for preserving participants' privacy in MCS. However, mobile devices are easy to lose and vulnerable to device capture attacks, which enables an attacker to extract the private authentication key of a mobile application and to further invade the user's privacy by linking sensed data with the user's identity. To address this issue, we have devised a special anonymous authentication scheme where the authentication request algorithm can be obfuscated into an unintelligible form and thus the authentication key is not explicitly used. This scheme not only achieves authenticity and unlinkability for participants, but also resists impersonation, replay, denial-of-service, man-in-the-middle, collusion, and insider attacks. The scheme's obfuscation algorithm is the first obfuscator for anonymous authentication, and it satisfies the average-case secure virtual black-box property. The scheme also supports batch verification of authentication requests for improving efficiency. Performance evaluations on a workstation and smart phones have indicated that our scheme works efficiently on various devices.
Learning Style Compatibility for Furniture

When judging style, a key question that often arises is whether or not a pair of objects are compatible with each other. In this paper we investigate how Siamese networks can be used efficiently for assessing the style compatibility between images of furniture items. We show that the middle layers of pretrained CNNs can capture essential information about furniture style, which allows for efficient applications of such networks for this task. We also use a joint image-text embedding method that allows for the querying of stylistically compatible furniture items, along with additional attribute constraints based on text. To evaluate our methods, we collect and present a large scale dataset of images of furniture of different style categories accompanied by text attributes.
An empirical comparative evaluation of gestUI to include gesture-based interaction in user interfaces

empirical evaluationCurrently there are tools that support the customisation of users' gestures.In general, the inclusion of new gestures implies writing new lines of code that strongly depend on the target platform where the system is run.In order to avoid this platform dependency, gestUI was proposed as a model-driven method that permits (i) the definition of custom touch-based gestures, and (ii) the inclusion of the gesture-based interaction in existing user interfaces on desktop computing platforms.The objective of this work is to compare gestUI (a MDD method to deal with gestures) versus a code-centric method to include gesturebased interaction in user interfaces.In order to perform the comparison, we analyse usability through effectiveness, efficiency and satisfaction.Satisfaction can be measured using the subjects' perceived ease of use, perceived usefulness and intention to use.The experiment was carried out by 21 subjects, who are computer science M.Sc.and Ph.D. students.We use a crossover design, where each subject applied both methods to perform the experiment.Subjects performed tasks related to custom gesture definition and modification of the source code of the user interface to include gesture-based interaction.The data was collected using questionnaires and analysed using non-parametric statistical tests.The results show that gestUI is more efficient and effective.Moreover, results conclude that gestUI is perceived as easier to use than the code-centric method.According to these results, gestUI is a promising method to define custom gestures and to include gesture-based interaction in existing user interfaces of desktop-computing software systems.
Information Processing Capability of Soft Continuum Arms

Soft Continuum arms, such as trunk and tentacle robots, can be considered as the “dual” of traditional rigid-bodied robots in terms of manipulability, degrees of freedom, and compliance. Introduced two decades ago, continuum arms have not yet realized their full potential, and largely remain as laboratory curiosities. The reasons for this lag rest upon their inherent physical features such as high compliance which contribute to their complex control problems that no research has yet managed to surmount. Recently, reservoir computing has been suggested as a way to employ the body dynamics as a computational resource toward implementing compliant body control. In this paper, as a first step, we investigate the information processing capability of soft continuum arms. We apply input signals of varying amplitude and bandwidth to a soft continuum arm and generate the dynamic response for a large number of trials. These data is aggregated and used to train the readout weights to implement a reservoir computing scheme. Results demonstrate that the information processing capability varies across input signal bandwidth and amplitude. These preliminary results demonstrate that soft continuum arms have optimal bandwidth and amplitude where one can implement reservoir computing.
Free Public Wi-Fi Security in a Smart City Context—An End User Perspective

With participatory action and engagement of end users (urban dwellers) playing an important role in the success of smart city initiatives, and the smart city model as a whole [1], free, public Wi-Fi hotspots are a viable option that may be employed to advance this endeavor. As end users become more reliant on the availability of these hotspots for various aspects of their everyday life, however, security becomes a prominent concern as hotspots may not only attract the attention of the end user, but also that of the abuser (cybercriminals). With various stakeholders typically involved in the delivery of smart city Wi-Fi initiatives, the question of who should be held responsible in the event of a cybercrime incurring losses to an end user while making use of the free Wi-Fi becomes of particular interest. As a result, in this chapter, various security aspects relating to smart city Wi-Fi offerings are discussed, striving to provide initial remedial recommendations from both the perspectives of the end user as well as the smart city. Further insight is also provided through a comparative analysis of the approaches taken to deliver free, public Wi-Fi in the cities of Barcelona (Spain), and Geneva (Switzerland).
Empirical studies to investigate the usability of text- and image-based CAPTCHAs

This article reports the findings of two empirical studies investigating the usability of image-based and text-based CAPTCHAs that authenticate users accessing the web. The first investigated four image-based CAPTCHAs, Asirra, ESP-PIX, SQ-PIX and IMAGINATION, with twenty participants interacting with five of each type on a desktop computer. The participants then completed the computer system usability questionnaire (CSUQ), the NASA Task Load Index (NASA-TLX), and a final post-test subjective questionnaire ranking the CAPTCHAs based on preference. The results found statistically significant differences among the CAPTCHAs for all dependent variables except task completion time, with participants preferring Asirra and ESP-PIX. The second compared the usability of these two with the two most commonly used text-based CAPTCHAs, ReCAPTCHA and Google's CAPTCHA. After receiving training on Asirra and ESP-PIX, twenty-four participants completed 10 trials with each type on a desktop computer, subsequently completing the CSUQ and the NASA-TLX followed by a retrospective think-aloud session. The results of this second study indicated that Google's CAPTCHA and ReCAPTCHA took the least amount of time to complete. The workload associated with Asirra and ReCAPTCHA was lower than that for ESP-PIX and Google's CAPTCHA. Perceived overall usability tended to be highest for Asirra and ReCAPTCHA. Participant comments indicated that Google's CAPTCHA was too visually distorted and ESP-PIX had commonalities between the images that weren't immediately obvious, factors perhaps contributing to their lower perceived usability scores. Overall, ReCAPTCHA is recommended for use on a desktop computer because of its high perceived usability, low completion time, and low workload.
Entanglement, nonclassical properties, and geometric phase in circuit quantum electrodynamics with relativistic motion

In this work, we study qualitatively the nonclassical properties, nonlocal correlation, and geometric phase in a superconducting qubit system connected to a transmission line resonator (TLR) within a circuit quantum electrodynamics setup, where the modulation of the coupling strength can imitate the harmonic motion of the superconducting system at relativistic speeds. We analyze the effects of the relativistic motion on these quantum quantifiers under the influence of the physical parameters implicated in the whole quantum system state. Furthermore, the relationship between the different quantifiers is explored. Our results may open new perspectives to understand and explore the relativistic phenomena on the comportment of the quantum quantifiers for new applications in superconducting quantum technologies.
A Test Vector Generation Method Based on Symbol Error Probabilities for Low-Complexity Chase Soft-Decision Reed–Solomon Decoding

This work presents a Low-Complexity Chase (LCC) Decoder for Reed-Solomon (RS) codes, which uses a novel method for the selection of test vectors that is based on the analysis of the symbol error probabilities derived from simulations.Our results show that the same performance as the classical LCC is achieved with a lower number of test vectors.For example, the amount of test vectors is reduced by half and by 1/16 for the RS(255,239) and RS(255,129) codes, respectively.We provide evidence that the proposed method is suitable for RS codes with different rates and Galois Fields.In order to demonstrate that the proposed method results in a reduction of the complexity of the decoder, we also present a hardware architecture for an RS(255,239) decoder that uses 16 test vectors.This decoder achieves a coding gain of 0.56 dB at FER=10 -6 compared to hard-decision decoding, which is higher than that of an η=5 LCC.The implementation results in ASIC show that a throughput of 3.6 Gbps can be reached in a 90 nm process and 29.1 KXORs are required.The implementation results in Virtex-7 FPGA devices show that the decoder reaches 2.5 Gbps and requires 5085 LUTs.
Landscape evolution and geochemical dispersion of the DeGrussa Cu-Au deposit, Western Australia

Sedimentary systems associated with ore deposits may act as mechanical dispersion agents of pathfinder elements at local and regional scales. The DeGrussa Cu-Au Volcanogenic Massive Sulfide (VMS) deposit (12.4 Mt @ 4.7% Cu and 1.8 g/t Au) was discovered in a deeply weathered landscape in Western Australia. The DeGrussa deposit is geochemically characterized as being enriched in Cu, Zn, Au and Ag, as well as significant enrichments in In, Mo, Se, Te, Bi, As, Cd and Co, and depletions in Nb, Hf, Th, REE, Cr, Ni, V, Sc and Ba. The Cenozoic palaeochannel sedimentary package that overlies the DeGrussa deposit displays elevated Cu, Zn, Au, and Ag concentrations, as well as significant enrichments in Cr, Ni, V, Sc, In, Mo, Se, Te, Bi, As, Cd and Co, and a remarkable depletion in REE. The palaeochannel sedimentary package shows similarities in its chemical signature to the DeGrussa deposit and associated basement rocks. However, due to the complexity of the landscape evolution and weathering impacts, there is uncertainty regarding the source(s) of this anomalous signature. It may represent (1) the geochemical signature of the immediately underlying basement rocks and/or the DeGrussa deposit; (2) concentration related to the weathering intensity experienced by the sediments, (3) concentration related to the cannibalistic nature of the sedimentary system, resulting in the reworking of previous deposits, or (4) a combination of the above. The Cenozoic channel clay deposits display strikingly depleted values of total REE (TREE) content, which has been interpreted to indicate that the palaeochannel clay units were mostly derived from weathering of proximal dolerite, with no mixing with other weathering products. This, in combination with high Mo, In and Se, and elevated Cu, Zn, Au, and Ag concentrations, may represent the relics of the DeGrussa footprint. Chromium Ni, V, and Sc are interpreted as being sourced mainly from the mafic basement units. Despite the geochemical signatures reported, this study has discovered that the metal geochemical footprint observed in the palaeochannel sedimentary package represents the footprint of the DeGrussa deposit. Hence the geochemistry of the transported cover can be used as an efficient tool for mineral exploration in specific landscape contexts, since the cover can preserve key elemental vectors of the mineral deposit and the geochemical signature of the basement rocks.
Formally and practically verifying flow properties in industrial systems

Industrial systems are nowadays regularly the target of cyberattacks, the most famous being Stuxnet.At the same time such systems are increasingly interconnected with other systems and insecure media such as Internet.In contrast to other IT systems, industrial systems often do not only require classical properties like data confidentiality or authentication of the communication, but have special needs due to their interaction with physical world.For example, the reordering or deletion of some commands sent to a machine can cause the system to enter an unsafe state with potentially catastrophic effects.To prevent such attacks, the integrity of the message flow is necessary.We provide a formal definition of Flow Integrity.We apply our definitions to two wellknown industrial protocols: OPC-UA and MODBUS.Using TAMARIN, a cryptographic protocol verification tool, we confirm that most of the secure modes of these protocols ensure Flow Integrity given a resilient network.However, we also identify weaknesses in a supposedly secure version of MODBUS, as well as subtleties in the handling of sequence numbers in OPC-UA.We also practically examine an OPC-UA stack named python-opcua, where some of the subtleties are not handled correctly.
Feature comparison and analysis for new challenging research fields of image quality assessment

Nowadays, objective image quality assessment (IQA) issue becomes increasingly important for both the practical application and scientific research in digital image processing systems. In this paper, we conduct feature comparison and analysis on new challenging research fields including contrast-distorted, screen content, multiply-distorted, tone-mapped, Depth Image Based Rendering (DIBR) and authentically distorted IQA. We describe the performance criteria, design rationale, and benchmark databases for validating IQA metrics in accordance with human perceptions. Then we provide some important conclusions of feature selection in terms of different IQA problems. In this work, our goal is dominantly towards judging the robustness of mainstream features used in the IQA field, which can help current and emerging researchers for better and faster grasping the speciality of each of novel IQA directions reported.
Solar and Climatic High Performance Factors for the Placement of Solar Power Plants in Argentina Andes Sites—Comparison With African and Asian Sites

The installation of solar power plants is currently having a notable expansion. The results presented show that the Argentinean Andes range, from the central to northern latitudes, is an excellent region for the placement of these plants, due to the sum of different positive factors: very high mean annual solar irradiation, low ambient temperature and relative humidity, low precipitable water content, normal wind speeds, and extremely low aerosol content of the atmosphere. The proposed regions are nearby San Antonio de los Cobres and El Leoncito and are compared with two important locations where large solar power plants have been (or will be) built: a site in Africa (Ouarzazate, Morocco) and one in Asia (Dubai, Arab Emirates). We present the results of the possible production of electricity, supplying a total of about 21,000 GWh, which is 15.6% of the 2015 Argentinean electric consumption and, consequently, could reduce the emission of greenhouse gases in a total mass of 11.2 × 106 tons of CO2eq. The installation of this type of renewable power plant will contribute significantly to the Argentinean population due to frequent (mainly summer) cutoff of electric power supply and, in particular, to isolated (low income) populations leaving in the Argentinean Andes range.