Reviewerly/exHarmony huggingface dataset:
SoK: How private is Bitcoin? Classification and Evaluation of Bitcoin Privacy Techniques

Blockchain is a disruptive technology that promises a multitude of benefits, such as transparency, traceability, and immutability. However, this unique bundle of key characteristics has proved to be a double-edged sword that can put users’ privacy at risk. Unlike in traditional systems, Bitcoin transactions are publicly and permanently recorded, and anyone can access the full history of the records. Despite using pseudonymous identities, an adversary can undermine users’ financial privacy and reveal their actual identities by using advanced heuristics and techniques to identify possible links between transactions, senders, receivers, and consumed services (e.g., online purchases). Hence, a multitude of approaches has been proposed to reduce financial transparency and enhance users’ anonymity. These techniques range from mixing services to off-chain transactions that address different privacy issues. In this paper, we particularly focus on comparing and evaluating privacy techniques in the Bitcoin blockchain (which can be applied in (Unspent Transaction Output (UTXO) based blockchains), present their limitations, and highlight new challenges.
Mining with Rarity for Web Intelligence

Mining with rarity makes sense to take advantage of data mining for Web intelligence. In some scenarios, the rare patterns are meaningful in data intelligent systems. Interesting pattern discovery plays an important role in real-world applications. In this field, a great deal of work has been done. In general, a high-utility pattern may include frequent items and also rare items. Rare pattern discovery emerges gradually and helps policy-makers making related marketing strategies. However, the existing Apriori-like methods for discovering high-utility rare itemsets (HURIs) are not efficient. In this paper, we address the problem of mining with rarity and propose an efficient algorithm, named HURI-Miner, which uses the data structure called revised utility-list to find HURIs from a transaction database. Furthermore, we utilize several powerful pruning strategies to prune the search space and save the computational complexity. In the process of rare pattern mining, the HURIs are directly generated without the generate-and-test method. Finally, a series of experimental results show that this proposed method has superior effectiveness and efficiency.
MarkovGNN: Graph Neural Networks on Markov Diffusion

Most real-world networks contain well-defined community structures where nodes are densely connected internally within communities. To learn from these networks, we develop MarkovGNN that captures the formation and evolution of communities directly in different convolutional layers. Unlike most Graph Neural Networks (GNNs) that consider a static graph at every layer, MarkovGNN generates different stochastic matrices using a Markov process and then uses these community-capturing matrices in different layers. MarkovGNN is a general approach that could be used with most existing GNNs. We experimentally show that MarkovGNN outperforms other GNNs for clustering, node classification, and visualization tasks. The source code of MarkovGNN is publicly available at https://github.com/HipGraph/MarkovGNN.
PARIS and ELSA

Providing low latency to end-users while maximizing server utilization and system throughput is crucial for cloud ML servers. NVIDIA's recently announced Ampere GPU architecture provides features to "reconfigure" one large, monolithic GPU into multiple smaller "GPU partitions". Such feature provides cloud ML service providers the ability to utilize the reconfigurable GPU not only for large-batch training but also for small-batch inference with the potential to achieve high resource utilization. We study this emerging GPU architecture with reconfigurability to develop a high-performance multi-GPU ML inference server, presenting a sophisticated partitioning algorithm for reconfigurable GPUs combined with an elastic scheduling algorithm tailored for our heterogeneously partitioned GPU server.
Optimizing quantum circuit placement via machine learning

Quantum circuit placement (QCP) is the process of mapping the synthesized logical quantum programs on physical quantum machines, which introduces additional SWAP gates and affects the performance of quantum circuits. Nevertheless, determining the minimal number of SWAP gates has been demonstrated to be an NP-complete problem. Various heuristic approaches have been proposed to address QCP, but they suffer from suboptimality due to the lack of exploration. Although exact approaches can achieve higher optimality, they are not scalable for large quantum circuits due to the massive design space and expensive runtime. By formulating QCP as a bilevel optimization problem, this paper proposes a novel machine learning (ML)-based framework to tackle this challenge. To address the lower-level combinatorial optimization problem, we adopt a policy-based deep reinforcement learning (DRL) algorithm with knowledge transfer to enable the generalization ability of our framework. An evolutionary algorithm is then deployed to solve the upper-level discrete search problem, which optimizes the initial mapping with a lower SWAP cost. The proposed ML-based approach provides a new paradigm to overcome the drawbacks in both traditional heuristic and exact approaches while enabling the exploration of optimality-runtime trade-off. Compared with the leading heuristic approaches, our ML-based method significantly reduces the SWAP cost by up to 100%. In comparison with the leading exact search, our proposed algorithm achieves the same level of optimality while reducing the runtime cost by up to 40 times.
Achieving Sustainability: From Innovation to Valorisation and Continuous Improvement

The Software Process Improvement methodology plans and implements improvement activities to achieve specific goals, for example, increase development speed, achieve higher product quality, and reduce costs. The approach paves way for the implementation of SPI innovations in software organisations. Innovation is the successful implementation of novel and appropriate ideas within an organisation. Innovation is underpinned by the concepts of creativity and invention. Often organisations, projects and individuals fail to gain adequate value let alone added value from their innovations. The term valorisation encompasses all activities that maximise the achievements of a project and innovation. The emphasis is on optimising the value of the project and innovation for diverse stakeholders (society, community, institutions, and individuals) and boosting its impact. In this paper, the authors report on the understandings and collective experience gained over several years in industry as well as academia culminating in the design and implementation of the European Union VALO Project which dissemination and exploitation. VALO outputs include the elements of the training and on-line examination for possible certification to become Valorisation experts. The insights gained from the VALO project, enabled the development of a valorisation strategy which is used, alongside quality strategies to enable the development of a Quality and Valorisation of Projects Framework. The genericity of the framework provides the potential foundations for successful projects of high quality and maximises the valorisation of project and innovation results. Software development projects (and projects in general) fail regularly. These quality failures manifest themselves in late deliveries, over-budget, not satisfying the users' requirements and more importantly in poor reliability. Quality attributes are system qualities (such as availability, modifiability, performance and security), business qualities, (such as time to market, cost and benefit, product lifetime and target market), and architectural qualities (such as conceptual integrity, correctness and completeness). Whenever any of these qualities are compromised a system can be considered a total or partial failure. Moreover, after a project's completion there is often evidence that it fails to deliver sustained value to stakeholders. In this paper we examine the challenges and benefits of sustainability viewed from a STEEPLED multidimensional analysis.
Design Process of a Ceramic Modeling Application for Virtual Reality Art Therapy

In the last years, teletherapy has provided the possibility of improving the accessibility to the therapy itself, by means of digital platforms. Of all the technologies that make up e-health, Virtual Reality is the one that creates the sense of presence, using immersive, interactive and collaborative virtual environments. From this perspective, this paper presents the preliminary study for a Virtual Reality (VR) Art Therapy application. It concerns one module of a project called Ermes, aimed at providing psychological support for remote practice for hospitalized patients, by means of Mindfulness and Art therapy practice. This perspective research starts with the aim of experimenting with a new system of interaction in Virtual Reality for the practice of Art Therapy. In particular, the medium that we want to adopt for the practice is the modeling of ceramics with traditional techniques. In this paper, we introduce the methodology and the design of this VR Art Therapy application, by explaining the gamification choices we made, in terms of mechanics, dynamics (visual responses), and aesthetics. The output is the definition of an optimal experience for the implementation of the Art Therapy scenario.
Near-optimal circuit mapping with reduced search paths on IBM quantum architectures

Due to technological constraints in the quantum devices, two-qubit gates can be executed only if their qubits are physically connected (neighbours). If all the qubits of the two-qubit gates in a circuit cannot be kept adjacent to each other, then a remapping has to be performed. We insert swap gates between two adjacent qubits to update the mapping of qubits, increasing the number of basic operations. Generally, the mapping problem was addressed in terms of two sub-problems in the related works, the global ordering by initial mapping and the re-ordering of qubits (local ordering). We propose a technique where these two sub-problems are combined together; the need of local ordering is greatly reduced. We divide the circuit into blocks such that every block contains maximum gates and all the interacting qubits within the blocks are connected. Swap operations are performed between two consecutive blocks, and a series of swap operations form a path. The shortest route between two successive blocks is acquired using a breadth first search strategy. The main objective is to provide a near-optimal solution in reduced time. Experiments were conducted using the latest versions of the 5-qubit IBM Q devices, and the effects of qubit connectivities on the circuit cost was also investigated.
Enhancing the ISO 25010 for Evaluating the Quality in Clouds and Cloud Services

Enterprises have to find their way to ensure systematic quality management in decentralized cloud setups and services. However, there is no standard approach for the evaluation and selection or development of the right cloud setup – private, public or hybrid – and cloud-based services. This work presents the approach of the Volkswagen Group IT to handle this topic by offering a self-service with a set of indicators for the evaluation of cloud setups and services. The work describes also the way to the development and identification of this set of indicators and the challenge of building a useful solution and offering this self-service within the Group IT.
Search Filter Ranking with Language-Aware Label Embeddings

A search on the major eCommerce platforms returns up to thousands of relevant products making it impossible for an average customer to audit all the results. Browsing the list of relevant items can be simplified using search filters for specific requirements (e.g., shoes of the wrong size). The complete list of available filters is often overwhelming and hard to visualize. Thus, successful user interfaces desire to display only the ones relevant to customer queries.
Designing STEM Learning Activity Based on Virtual Reality

As teaching materials continue to develop and improve, learners have gradually shifted from abstract learning methods such as learning formulas and understanding images to hands-on learning. Learners apply the acquired knowledge and skills to practical STEM hands-on experiential courses to verify the formulas and knowledge they have acquired. Hands-on learning effectively helps learners transform abstract knowledge into conceptual skills and practical abilities and apply these in practical fields. In a traditional STEM hands-on learning experiment environment, learners verify knowledge through experiments. However, in the experimental fields set up at many schools and laboratories, there is often a lack of experimental equipment. Also, in experiments such as fire drills and medical experiments, learners may not be permitted to perform actual operations and practices in laboratories due to safety factors. Learners lack a safe and secure learning environment where they can study anytime, anywhere. Therefore, we design and develop a virtual reality system which we apply to embedded electronic circuit learning activities, creating for learners a virtual environment for immersive learning. The effectiveness of the system is verified through a pilot study using the technology acceptance model (TAM) to measure learner acceptance. The results of this study and the analysis of the TAM data show that the system was well-accepted by participants.
Thinking beyond <i>If You Build It, They Will Come</i>: Increasing Submissions to Campus Institutional Repositories

Institutional repositories have not lived up to their potential. Faculty consider preparing and submitting works to repositories onerous, they worry about making works freely available, and they fail to see benefits of submitting works to repositories. Nevertheless, opportunities to increase repository submissions exist, and IRs offer campuses a way to promote dissemination of research and scholarship while meeting user needs. This article identifies hurdles to getting faculty to submit works and highlights how librarians can leverage campus resources and address faculty priorities to increase submissions. Insights gathered via assessments of repository workflows, library processes, and communications with librarians at several U.S. universities are presented to support the conclusion that, to increase submissions, repository staff should leverage information channels, increase benefits associated with submitting works to the repository, and reduce costs associated with the submission process. By grounding the study's approach in rational choice logic, the findings represent a broadly-applicable framework.
The Nexus among Good E-Governance Practice, Decentralization, and Public Administration for Sustainable Local Development

The formulation and implementation of development-oriented public policies, particularly in a post-conflict state like Iraq, requires empirical investigation. Consequently, this study investigates the effect of effective e-governance practices and decentralization on public administration in the Erbil district of Iraq. The purpose of this study is to determine the role of decentralization as a mediator between good e-governance practices and public administration in relation to the sustainable local development of the Erbil city. The sample of 409 employees of the Erbil municipality who participated in the survey was analyzed using Partial Least Square Structural Equation Modeling (PLS-SEM) with the assistance of WarPLS 7.0. The results of the study revealed a significant correlation between e-governance practices and decentralization and public administration. In addition, it was discovered that decentralization has a significant effect on public administration. The finding of a significant negative relationship between e-governance and decentralization suggests that e-governance has a negative impact on decentralization in Erbil. The implications of the study are discussed, and the study suggests that devolving power and authority to subunits in Iraq would enhance public administration and promote sustainable local development.
Improved YOLOv4-tiny network for pedestrian detection

In the intelligent driving system, it is very important to identify pedestrians accurately and efficiently. However, when pedestrians are in a long distance, they are small in the field of vision and difficult to detect. This paper presents a pedestrian detection method based on YOLOv4-tiny network. According to the characteristics of pedestrians and the multi-level detection principle, we improved the anchor box and structure of YOLOv4-tiny network. The improved model was tested by using the collected multi-segment driving image data and the result shows that the performance of the model for pedestrian detection is significantly improved, especially for small pedestrians. In three of the test scenarios, the accuracy of pedestrian detection is improved from 54.5%, 68.2% and 67.8% to 86.7%, 90.4% and 91.3%, respectively. In addition, this method can also be used to detect other types of targets (such as vehicles) and has a certain versatility.
A Boosted Wavelet Improvement Thresholding Algorithm Based on Birgé- Massart Strategy for Pipeline Leakage Signal Noise Reduction Processing

This paper investigates the negative pressure waves generated when the pipeline leaks based on the negative pressure wave localization method, adopts a boosted wavelet transform method that does not depend on the Fourier transform, selects the noise reduction threshold based on the Birgé-Massart strategy, introduces a soft and hard threshold compromise noise reduction algorithm to process the noise-containing signals, and finally uses the negative pressure waves collected from field experiments to test and apply the above algorithm, and compares the effect and error analysis with the traditional soft threshold method and hard threshold method. The results show that the denoising effect and the root mean square error after signal processing of the algorithm established in this paper are better than the traditional algorithms, and have good application value in pipeline leakage signal noise reduction.
Handwriting Analysis for Personality Trait Features Identification using CNN

Handwriting analysis is an approach to get information through the handwriting. It extremely useful information, for instance in personality traits identification. The information came from the feature extracted from the handwriting. This feature can be size, slantness, pressure, and so forth. In this research, handwriting analysis is through the AND dataset that provide handwriting dataset along with feature label while most public dataset has nothing with it. By using the Coonvolutional Neural Networks (CNN) potentiality in capturing and recognizing global features, there are 15 models had built in this research in accordance with each feature and divided into three group by its number of types. After built a simple CNN architecture by only conduct two convolution layer, overall result show fair enough performance where the highest rate of accuracy is 80.88%. Furthermore, there are three best features had recognized, which is "entry stroke ‘A’", "size", and "slantness", where the last two is naturally global features. However, the fact that handwriting image data cannot be oversampled which can lead to the bias result, than the imbalance data becomes a problem in this research that reduced the model performance.
A Non-Optimization-Based Dynamic Path Planning for Autonomous Obstacle Avoidance

This article presents a non-optimization-based framework for path planning and tracking for evasive maneuvers in autonomous cars. The framework exploits a two-layer approach where a path planner generates a reference trajectory that is then tracked by a path-tracking controller. A nested curvature preview controller (CPC) implements path tracking. In this article, we show how to describe the closed-loop performance of the controller. The quantification of the closed-loop performance in the frequency domain guides the generation of the evasive path. In this way, the algorithm generates a path that avoids the obstacle (if possible) accounting for both static and dynamic constraints. The proposed framework, thus, provides a non-optimization-based way to integrate the characteristics of the path tracker in the path-planner algorithm, thus avoiding the need to define cost functions and use the third-party optimizers. This article validates the proposed evasive maneuver strategy in simulation and on an instrumented vehicle. First, we test the trajectory tracker, showing that it tracks aggressive trajectories (with a lateral acceleration close to 1 g) with an error smaller than 30 cm. Subsequently, we integrate the curvature preview with the path generator and show the joint generation-tracking performance in two different scenarios.
A Flexible and High-Performance Lattice-Based Post-Quantum Crypto Secure Coprocessor

Progress of quantum computing technology seriously threaten the industrial information security based on traditional public-key cryptosystem. Thus, the cryptosystem with anti-quantum attack characteristics is gradually becoming a significant research in the security field. In this article, a flexible and high-performance secure coprocessor is designed for security in industrial processes, which can execute the post-quantum cryptographic algorithm Saber efficiently. Custom instruction set and arithmetic accelerators are proposed to effectively optimize the flexibility of system architecture, and improve the performance of calculation. The hardware implementation results show that the maximum operating frequency of the coprocessor can reach 345 MHz. Compared with related state-of-the-art works, it achieves the highest operating frequency on the same Xilinx UltraScale+ FPGA platform, performing the encryption and decryption operations within 13.5 and 15.4 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> s, respectively. Meanwhile, this article achieves 1.7/3.1/5.9× area-time product improvements in look-up table flip-flop block memory storage with good flexibility.