Reviewerly/exHarmony huggingface dataset:
Salvage of Supervision in Weakly Supervised Object Detection

Weakly supervised object detection (WSOD) has recently attracted much attention. However, the lack of bounding-box supervision makes its accuracy much lower than fully supervised object detection (FSOD), and currently modern FSOD techniques cannot be applied to WSOD. To bridge the performance and technical gaps between WSOD and FSOD, this paper proposes a new framework, Salvage of Supervision (SoS), with the key idea being to harness every potentially useful supervisory signal in WSOD: the weak image-level labels, the pseudo-labels, and the power of semi-supervised object detection. This paper proposes new approaches to utilize these weak and noisy signals effectively, and shows that each type of supervisory signal brings in notable improvements, outperforms existing WSOD methods (which mainly use only the weak labels) by large margins. The proposed SoS- WSOD method also has the ability to freely use modern FSOD techniques. SoS-WSOD achieves 64.4 mAP <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">50</inf> on VOC2007, 61.9 mAP <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">50</inf> on VOC2012 and 16.6 mAP <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">50:</inf> <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">95</inf> on MS-COCO, and also has fast inference speed. Ablations and visualization further verify the effectiveness of SoS.
Multiple-participant measurement-device-independent quantum secret sharing protocol based on entanglement swapping

Abstract Quantum secret sharing (QSS) is a multi-party quantum communication mode, which allows the dealer to split a key into several parts and send each part of a key to a participant. The participants can obtain the key only by cooperation. Entanglement swapping is a promising method to construct the entanglement channel. In the paper, we propose a multiple-participant measurement-device-independent QSS protocol based on entanglement swapping. All the measurement tasks are handed over to an untrusted measurement party, so that our protocol can resist all possible attacks from imperfect measurement devices. Our protocol requires the linear-optical Bell state analysis, which is easy to operate. Our protocol has application potential in the future quantum communication field.
GPS-Free Collaborative Elliptical Circumnavigation Control for Multiple Non-Holonomic Vehicles

This paper investigates a novel GPS-free collaborative elliptical circumnavigation control for multiple non-holonomic vehicles, where two realistic issues — achieving a higher efficiency observation and saving the energy expenditures during cooperation are involved. By defining a novel coordinated error relative to neighboring arc length, under the premise of accessible global position, a cooperative elliptical enclosing control strategy is derived for multiple vehicles connected by a digraph to enable formation behaviors with a uniform forward speed. To surmount the reliance on global position data in hostile surroundings where GPS is being attacked or disrupted, by resorting to a distance-based relative position observer, a new GPS-free cooperative elliptical circling controller is formulated to force all vehicles to collaboratively evolve along the prescribed ellipse. The special innovation includes two aspects, one is that by specifying the adjacent arc length instead of separation angles appearing in existing vehicle coordination, energy consumption can be reduced by approximately 7.6% during cooperative periodic enclosing process, another is that the dependency on global position can be removed by resorting to a relative position estimator utilizing distance-only data. It is inferred from Lyapunov stability that all signals are demonstrated to be convergent. Eventually, both simulation and experimental results substantiate the utility of suggested avenue.
The slow-paced digital evolution of pathology: lights and shadows from a multifaceted board

The digital revolution in pathology represents an invaluable resource fto optimise costs, reduce the risk of error and improve patient care, even though it is still adopted in a minority of laboratories. Barriers include concerns about initial costs, lack of confidence in using whole slide images for primary diagnosis, and lack of guidance on transition. To address these challenges and develop a programme to facilitate the introduction of digital pathology (DP) in Italian pathology departments, a panel discussion was set up to identify the key points to be considered.On 21 July 2022, an initial conference call was held on Zoom to identify the main issues to be discussed during the face-to-face meeting. The final summit was divided into four different sessions: (I) the definition of DP, (II) practical applications of DP, (III) the use of AI in DP, (IV) DP and education.Essential requirements for the implementation of DP are a fully tracked and automated workflow, selection of the appropriate scanner based on the specific needs of each department, and a strong commitment combined with coordinated teamwork (pathologists, technicians, biologists, IT service and industries). This could reduce human error, leading to the application of AI tools for diagnosis, prognosis and prediction. Open challenges are the lack of specific regulations for virtual slide storage and the optimal storage solution for large volumes of slides.Teamwork is key to DP transition, including close collaboration with industry. This will ease the transition and help bridge the gap that currently exists between many labs and full digitisation. The ultimate goal is to improve patient care.
Geometric and holonomic quantum computation

Geometric and holonomic quantum computation utilizes intrinsic geometric properties of quantum-mechanical state spaces to realize quantum logic gates. Since both geometric phases and quantum holonomies are global quantities depending only on the evolution paths of quantum systems, quantum gates based on them possess built-in resilience to certain kinds of errors. This review provides an introduction to the topic as well as gives an overview of the theoretical and experimental progress for constructing geometric and holonomic quantum gates and how to combine them with other error-resistant techniques.
A Race-Track Trapped-Ion Quantum Processor

We describe and benchmark a new quantum charge-coupled device (QCCD) trapped-ion quantum computer based on a linear trap with periodic boundary conditions, which resembles a race track. The new system successfully incorporates several technologies crucial to future scalability—including electrode broadcasting, multilayer rf routing, and magneto-optical trap (MOT) loading—while maintaining, and in some cases exceeding, the gate fidelities of previous QCCD systems. The system is initially operated with 32 qubits, but future upgrades will allow for more. We benchmark the performance of primitive operations, including an average state preparation and measurement error of 1.6(1)×10−3, an average single-qubit gate infidelity of 2.5(3)×10−5, and an average two-qubit gate infidelity of 1.84(5)×10−3. The system-level performance of the quantum processor is assessed with mirror benchmarking, linear cross-entropy benchmarking, a quantum volume measurement of QV=216, and the creation of 32-qubit entanglement in a GHZ state. We also tested application benchmarks, including Hamiltonian simulation, QAOA, error correction on a repetition code, and dynamics simulations using qubit reuse. We also discuss future upgrades to the new system aimed at adding more qubits and capabilities.17 MoreReceived 17 May 2023Revised 15 August 2023Accepted 28 September 2023DOI:https://doi.org/10.1103/PhysRevX.13.041052Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasQuantum algorithmsQuantum benchmarkingQuantum computationQuantum gatesQuantum information processingQuantum Information, Science & Technology
Finding Optimal Solutions to Sokoban Using Instance Dependent Pattern Databases

Pattern databases have been successfully applied to several problems. Their use assumes that the goal state is known, and once the pattern database is built, commonly it can be used by all instances. However, in Sokoban, before solving the puzzle, the goal position of each stone is unknown. Moreover, each Sokoban instance has its own state space search. In this paper we apply pattern databases to Sokoban. The proposed approach uses an instance decomposition, that allows multiple possible goal states to be abstracted into a single state. Thus, an instance dependent pattern database is employed. Experiments with the standard set of instances show that the proposed approach overcomes the current best lower bounds in initial states for several instances. Furthermore, three of these new best lower bounds match exactly with the optimal solution length. Finally, we run experiments of 5 million explored states for each instance. Nine instances were solved with optimality guarantees, while only four instances were solved under the same conditions by previous methods.
Perception, usage and barriers towards the utilisation of the Telecentre among rural women in Tanzania

Purpose This paper aims to assess the usage pattern of telecentres, how rural women frame telecentres and barriers that limit use of telecentres. Further, the study examined the effects of demographic characteristics and location on telecentre usage. Design/methodology/approach The study used a sequential mixed research design in three rural districts surrounding telecentres: Kongwa, Sengerema and Kilosa districts. The study population comprised rural women who were users and non-users of telecentres. The study conducted six focus group discussions (FGDs) with 37 users and six FGDs with 36 non-users in the first phase of the study in 2014; questionnaires were administered to 90 users and 90 non-users in the second phase of the study in 2015. Findings The primary use of telecentres among users was to access internet (71.4 per cent, n = 60), followed by information and communication technology (ICT) training courses (63.1 per cent, n = 53) and secretarial purposes (63.1 per cent, n = 53). Rural women used internet for educational purposes, followed by news, information on health issues, job opportunities, social and entertainment issues. Rural women currently using internet were more likely to be better educated ( ß = 1.926, p = 0.001) and have higher incomes ( ß = 5.318, p = 0.021) at both bivariate and multivariate analysis. Users indicated that they faced the following barriers towards using telecentre: short duration of ICT training, frequent power outages, low speed of internet and few computers at the telecentres. Non-users were not using telecentres because of lack of ICT skills and language barriers. Originality/value This study provides empirical evidence to telecentres, libraries and other rural ICT initiatives to design rural ICT services that are gender-sensitive and demand-driven.
Shall deep learning be the mandatory future of document analysis problems?

As the use of deep methods become widespread in the scientific community, causing major changes in systems architecture and position in terms of knowledge acquisition, we report here our insights about how document analysis systems are built. Where does the expertise really lie? In the features, in the decision making step, in the system design, in the data illustrating the problem to be solved? The examination of the practices of researchers in this field, and their evolution, allows us to conclude that the tools that are used, and related issues, have become more and more complex over time. Nevertheless, human skill is needed to activate these tools and to imagine new ones.
Long term behavior of a random Hopfield neural lattice model

A Hopfield neural lattice model is developed as the infinite dimensional extension of the classical finite dimensional Hopfield model. In addition, random external inputs are considered to incorporate environmental noise. The resulting random lattice dynamical system is first formulated as a random ordinary differential equation on the space of square summable bi-infinite sequences. Then the existence and uniqueness of solutions, as well as long term dynamics of solutions are investigated.
A jointly learned deep embedding for person re-identification

Person re-identification (ReID) is an importance study issue in the modern video surveillance area. However, it is very challenging due to the large variations of intra-class and the small variations of inter-class. To solve the problem, most deep ReID methods usually learn a feature embedding based on verification or identification. However, both learning approaches are complementary and neither of them can well address this issue. Motivated by this, we propose a deep joint learning framework based on verification-identification to achieve a discriminative deep feature embedding. Specifically, for verification, a triplet network is adopted and an improved triplet loss is proposed by adding a novel penalty item in the framework. For identification, an identity classifier with the softmax loss is attached to the top of the triplet network at the same time. Thus, driven by the improved triplet loss and the softmax loss simultaneously, a more discriminative and compact feature embedding will be learned for ReID. Extensive experiments over several popular benchmarks achieve state-of-the-art results which well demonstrate the effectiveness of the proposed method for ReID.
Quantum hacking on a free-space quantum key distribution system without measuring quantum signals

We hack a practical free-space quantum key distribution (QKD) system using active wavelength control attacks without measuring quantum signals. This method is a hacking method that uses a wavelength change according to Alice’s laser diodes’ internal temperature change caused by Eve’s external laser source, unlike the existing hack, which simply analyzes the initial characteristic difference between transmitter signal laser diodes. In this paper, beyond a feasibility test, the proposed QKD hacking method is verified with the complete QKD system. Furthermore, we also suggest a new quantum hacking scheme in which the quantum signal does not need to be measured during the hacking process. Hence, Eve does not require complex hardware such as single-photon detectors and sources. Using the proposed quantum hacking method, we confirm that Eve can acquire not only a complete quantum key but also basis information without revealing her presence.
Quality measures for speaker verification with short utterances

The performances of the automatic speaker verification (ASV) systems degrade due to the reduction in the amount of speech used for enrollment and verification. Combining multiple systems based on different features and classifiers considerably reduces speaker verification error rate with short utterances. This work attempts to incorporate supplementary information during the system combination process. We use quality of the estimated model parameters as supplementary information. We introduce a class of novel quality measures formulated using the zero-order sufficient statistics used during the i-vector extraction process. We have used the proposed quality measures as side information for combining ASV systems based on Gaussian mixture model–universal background model (GMM–UBM) and i-vector. The proposed methods demonstrate considerable improvement in speaker recognition performance on NIST SRE corpora, especially in short duration conditions. We have also observed improvement over existing systems based on different duration-based quality measures.
Analysis of Doddington zoo classification for user dependent template update: Application to keystroke dynamics recognition

Biometric authentication systems are increasingly considered in different access control applications. Regarding that users have completely different interactions with these authentication systems, several techniques have been developed in the literature to model distinctive users categories. Doddington zoo is a biometric menagerie that defines and labels user groups with animal species to reflect their behavior with the biometric systems. This menagerie was developed for different biometric modalities including keystroke dynamics. The present study proposes a user dependent adaptive strategy based on the Doddington zoo, for the recognition of the user’s keystroke dynamics. The novelty of the proposed approach lies in applying an adaptive strategy specific to the characteristics of each user of the Doddington zoo menagerie aiming to solve the intra-class variation problems. The obtained results demonstrate competitive performances on significant keystroke dynamics datasets WEBGREYC and CMU.
NoRML: No-Reward Meta Learning

Efficiently adapting to new environments and changes in dynamics is critical for agents to successfully operate in the real world. Reinforcement learning (RL) based approaches typically rely on external reward feedback for adaptation. However, in many scenarios this reward signal might not be readily available for the target task, or the difference between the environments can be implicit and only observable from the dynamics. To this end, we introduce a method that allows for self-adaptation of learned policies: No-Reward Meta Learning (NoRML). NoRML extends Model Agnostic Meta Learning (MAML) for RL and uses observable dynamics of the environment instead of an explicit reward function in MAML's finetune step. Our method has a more expressive update step than MAML, while maintaining MAML's gradient based foundation. Additionally, in order to allow more targeted exploration, we implement an extension to MAML that effectively disconnects the meta-policy parameters from the fine-tuned policies' parameters. We first study our method on a number of synthetic control problems and then validate our method on common benchmark environments, showing that NoRML outperforms MAML when the dynamics change between tasks.
Improving eye-tracking calibration accuracy using symbolic regression

Eye tracking systems have recently experienced a diversity of novel calibration procedures, including smooth pursuit and vestibulo-ocular reflex based calibrations. These approaches allowed collecting more data compared to the standard 9-point calibration. However, the computation of the mapping function which provides planar gaze positions from pupil features given as input is mostly based on polynomial regressions, and little work has investigated alternative approaches. This paper fills this gap by providing a new calibration computation method based on symbolic regression. Instead of making prior assumptions on the polynomial transfer function between input and output records, symbolic regression seeks an optimal model among different types of functions and their combinations. This approach offers an interesting perspective in terms of flexibility and accuracy. Therefore, we designed two experiments in which we collected ground truth data to compare vestibulo-ocular and smooth pursuit calibrations based on symbolic regression, both using a marker or a finger as a target, resulting in four different calibrations. As a result, we improved calibration accuracy by more than 30%, with reasonable extra computation time.
Social Education: Opportunities and Challenges in Cyber-Physical-Social Space

We are making good progresses in our impact and reputation over the last year. According to the latest data released by Scopus on February 11, 2019, our CiteScore hits its historical high to 3.94, and TCSS ranks 8th out of the 226 journals (top 3.54%) in the field of social sciences. This is a solid improvement compared with the corresponding data in 2017 (CiteScore: 2.36, Rank: 17/226, top 8%). Thanks and congratulations to our authors, reviewers, and members of our editorial board. The current issue includes 17 regular papers and a brief discussion on social education.
Robust transfer integrated locally kernel embedding for click-through rate prediction

With the rapid development of online advertising, the click-through rate (CTR) prediction plays an important role in improving the benefits of advertising and user experience. CTR is the most commonly used evaluation indicator of the effects of online advertising. At present, the keys including feature extraction and user click behavior modeling have been taken into consideration by many researchers to design methods for CTR prediction. However, the characteristics of high-dimensional data sparseness and imbalance in advertising data are not fully considered, which results in the insufficient utilization of advertising information. To alleviate the problems of data sparsity and imbalance, this paper proposes a robust integrated locally kernel embedding (RILKE) model to solve data sparseness and incorporate unsupervised transfer learning into RILKE to form an improved model, named robust transfer integrated locally kernel embedding (RTILKE). Through theoretical analysis and empirical experiments, RTILKE can efficiently solve the data-imbalance problem of CTR prediction in online advertising, which effectively improves the prediction performance of advertising responses.
Designing Monitoring Systems for Continuous Certification of Cloud Services: Deriving Meta-requirements and Design Guidelines

Continuous service certification (CSC) involves the consistently gathering and assessing certification-relevant information about cloud service operations to validate whether they continue to adhere to certification criteria. Previous research has proposed test-based CSC methodologies that directly assess the components of cloud service infrastructures. However, test-based certification requires that certification authorities can access the cloud infrastructure, which various issues may limit. To address these challenges, cloud service providers need to conduct monitoring-based CSC; that is, monitor their cloud service infrastructure to gather certification-relevant data by themselves and then provide these data to certification authorities. Nevertheless, we need to better understand how to design monitoring systems to enable cloud service providers to perform such monitoring. By taking a design science perspective, we derive universal meta-requirements and design guidelines for CSC monitoring systems based on findings from five expert focus group interviews with 33 cloud experts and 10 one-to-one interviews with cloud customers. With this study, we expand the current knowledge base regarding CSC and monitoring-based CSC. Our derived design guidelines contribute to the development of CSC monitoring systems and enable monitoring-based CSC that overcomes issues of prior test-based approaches.
Blockchain Technology and Cryptocurrenices

A blockchain can be referred to as a collection of records or open record that gets shared amongst participating parties. Every transaction that gets incorporated is first verified by all the participants of that transaction. Once the data gets recorded by the blockchain, can never be rewritten or changed. Thus the blockchain can be termed as a record book of all the transactions held. Cryptocurrencies, the decentralized bitcoin or say ethereum which can be termed as peertopeer computerized cash also uses the blockchain technology. This paper includes history of bitcoin, a few literary reviews, working of the blockchain and its application.