Reviewerly/exHarmony huggingface dataset:
Moderate deviation analysis of majorisation-based resource interconversion

We consider the problem of interconverting a finite amount of resources within all theories whose single-shot transformation rules are based on a majorisation relation, e.g. the resource theories of entanglement and coherence (for pure state transformations), as well as thermodynamics (for energy-incoherent transformations). When only finite resources are available we expect to see a non-trivial trade-off between the rate r <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> at which n copies of a resource state ρ can be transformed into nr <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> copies of another resource state σ, and the error level ε <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> of the interconversion process, as a function of n. In this work we derive the optimal trade-off in the so-called moderate deviation regime, where the rate of interconversion r <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> approaches its optimum in the asymptotic limit of unbounded resources (n → ∞), while the error ε <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> vanishes in the same limit. We find that the moderate deviation analysis exhibits a resonance behaviour which implies that certain pairs of resource states can be interconverted at the asymptotically optimal rate with negligible error, even in the finite n regime.
Augmented Reality in Lower Secondary Science Teaching: Teachers and Students as Producers

This paper presents research looking into the use of Augmented Reality (AR) in lower secondary science. The first part of the findings is based on empirical data from the 3-year project ARsci. A design-based research approach was applied with three rounds of testing AR-animation models at schools in Denmark, Norway, and Spain. Data sources were interviews, questionnaires, video, and classroom observations. Findings pointed to positive possibilities for supporting students’ modeling competencies, however dependent on the teachers’ thorough use of scaffolding. Students referred positively to perceived learning outcomes and highlighted a sense of presence in the scientific phenomena. The findings from the ARsci project, where students were working with micro-processes like photosynthesis and combustion, are with the support of a focused state-of-the-art review (the second part of the findings) discussed with perspectives about using AR in the context of Ocean Literacy and macro-processes in science.
Hexagonal Grid Numbering

A fundamental requirement for scientific treatment of board games is a simple and practical numbering of the map locations. With square grids, an obvious solution is coordinates along two orthogonal axes. Hexagonal grids, however, have three axes, and only one of them can be aligned with an edge of a square board. Various systems have been proposed for numbering hexagonal grids, and several remain in use. Computational tools that support games with hexagonal grids will presumably need to convert, or operate directly on, the grid coordinates. While it would be possible to write separate software for each of the different coordinate systems, a more general approach is to define a formal description of the coordinate system, which is then supplied as data, and have a single piece of software that can handle all possible hexagonal grid coordinates. Such a system is proposed here, after an exhaustive survey of the various existing coordinate systems, and a comprehensive investigation of the logical possibilities for defining a coordinate system on a hexagonal grid. The formal expression that defines any specific coordinate system consists of around ten characters in the standard 7-b ASCII alphabet, for maximum computational interoperability.
Manipulation of Multi‐Level Quantum Systems via Unsharp Measurements and Feedback Operations

Abstract The recently proposed quantum control method called self‐fulfilling prophesy is investigated in multi‐level cases, based on a sequence of measurement‐feedback operations. The feedback operation is elaborately designed with respect to the eigenstates of the density matrix of the target state and its post‐measurement state. This design procedure is suitable for the generation of any predefined coherent superpositions of multiple quantum states and elicitation of desired quantum dynamics. For the sake of clearness, arbitrarily prescribed superposition states in three‐ and four‐level systems are prepared, and quantum dynamics achieved as desired. The simulation results indicate that the scheme tolerates modest imprecisions of feedback operation and is robust against sudden perturbations. Thus, the scheme enables new insight on quantum manipulations in a variety of multi‐level systems to be achieved.
Logic foundations of manipulation as game mechanics

Several subfields in symbolic AI can be useful in game agents: dynamic epistemic logic, epistemic planning, belief revision and natural language processing. Furthermore, there is a sizeable number of papers exploring their interactions, but very few practical implementations. We present WemblAI, a toolbox that aims at collecting algorithms from these fields using a common framework. WemblAI is still largely a work in progress.
Motion Control of Wheeled Mobile Robot Based on Data Driven

Aiming at the kinematics model of wheeled mobile robot, a data-driven T-S fuzzy predictive control method is proposed.. This method uses system identification to obtain the T-S fuzzy model of the car, i. e. the linear representation of the car's non-linear system. At the same time, the predictive control method can also be applied to the control when the system is constrained by input and output. The simulation results verify the effectiveness of the proposed generalized prediction method of T-S fuzzy model.
A Sequential Investigation Model for Solving Time Critical Digital Forensic Cases Involving a Single Investigator

The number of evidences found in a digital crime scene has burgeoned significantly over the past few years. In addition, the demand for delivering accurate results within a given time deadline has increased. The major challenges coinciding with these aforementioned objectives are to investigate the right set of evidences and to allocate appropriate times for their investigation. In this paper, we present a mixed integer linear programming (MILP) model to analyze the problem of allocating optimal investigation times for evidences involving a single investigator. The objective is to maximize the overall effectiveness of a forensic investigation procedure. We particularly focus on the time critical digital forensic cases, in which results have to be finalized in a court of law within a specified time deadline. While the general problem is NP-hard, two special cases are illustrated to be optimally solvable in polynomially computational effort. Two heuristic algorithms are proposed to solve the general problem. Results of extensive computational experiments to empirically evaluate their effectiveness in finding an optimal or near-optimal solution are reported. Finally, this paper concludes with a summary of findings and some fruitful directions for future research.
A New Approach for Image Dehazing Using Koschmieder’s Model

Images captured in open air environments are normally destroyed due to the existence of awful climate conditions. The impact of murkiness is extensively spread; the anticipated transmission ought to be uniformly changed over the spot. This paper proposed the Koschmieder’s Model to clear such corrupted pictures from dehazing. To safeguard more points of interest and right the shading twisting, an answer in light of Koschmieder’s Model is presented. The proposed method provides parallel or significantly higher quality with bring down multifaceted nature by connecting with the best in class single picture dehazing techniques. With a specific end goal to confirm the high perceivability remaking and productivity of the proposed method, comparable investigations are conveyed toward the end.
Triple-Joint Modeling for Question Generation Using Cross-Task Autoencoder

Question Generation (QG) aims to generate a question based on the context. Given the intrinsic connections between QG and QA (Question Answering), we focus on training a joint model for both QG and QA, and take one step further to integrate one more context self-encoding (CSE) task into the joint model, as a junction auxiliary task to better integrate QG and QA. In particular, our model employs a cross-task autoencoder to incorporate QG, QA and CSE into a joint learning process, which could better utilize the correlation between the contexts of different tasks in learning representations and provide more task-specific information. Experimental results show the effectiveness of our triple-task training model for QG, and the importance of learning interaction among QA and CSE for QG.
Document-Based Question Answering Improves Query-Focused Multi-document Summarization

Due to the lack of large scale datasets, it remains difficult to train neural Query-focused Multi-Document Summarization (QMDS) models. Several large size datasets on the Document-based Question Answering (DQA) have been released and numerous neural network models achieve good performance. These two tasks above are similar in that they all select sentences from a document to answer a given query/question. We therefore propose a novel adaptation method to improve QMDS by using the relatively large datasets from DQA. Specifically, we first design a neural network model to model both tasks. The model, which consists of a sentence encoder, a query filter and a document encoder, can model the sentence salience and query relevance well. Then we train this model on both the QMDS and DQA datasets with several different strategies. Experimental results on three benchmark DUC datasets demonstrate that our approach outperforms a variety of baselines by a wide margin and achieves comparable results with state-of-the-art methods.
Development of an Integrated Laboratory Information Management System in the United Arab Emirates

This paper presents an integrated Laboratory Information Management System (LIMS), which was developed and implemented for a gas manufacturing and distribution company operating in Abu Dhabi in the United Arab Emirates. Specifically, LIMS was developed for all the analytical areas available in the ADGAS laboratory, including the marketable products (LNG, propane, butane, paraffinic naphtha sulfur, and crude oil), lube oil, water, raw materials, gases, and other products/services. Ever since it was launched in January 2008, routine testing schedules are generated every morning automatically, and the data files generated by the major instruments are automatically transferred. Complicated downstream calculations are also performed automatically. The sample life cycle goes through steps such as entry of variables, calculations, data control, and validation of results.
Identifying Latent Semantics in Action Games for Player Modeling

Machine learning approaches to player modeling traditionally employ a high-level game-knowledge-based feature for representing game sessions, and often player behavioral features as well. The present work makes use of generic low-level features and latent semantic analysis for unsupervised player modeling, but mostly for revealing underlying hidden information regarding game semantics that is not easily detectable beforehand.
A Centralized Digital Currency System with Rich Functions

The developments of cryptocurrencies push central banks of many countries to consider their own digital fiat currencies. As banks are usually taken as a trusted third party, it is unnecessary to rebuild a blockchain system to rebuild trust. However, cryptocurrencies provide many interesting features except the basic financial functions. It is naturally to absorb the interesting parts of cryptocurrencies to the centralized bank system. We here extract a stateful authentication mechanism from the practice of Ethereum and show how to run puzzle and payment channel templates in a centralized system, based on which we may build a fiat currency lighting network to support direct exchanges of users.
Cross-lingual Neural Vector Conceptualization

Recently, Neural Vector Conceptualization (NVC) was proposed as a means to interpret samples from a word vector space. For NVC, a neural model activates higher order concepts it recognizes in a word vector instance. To this end, the model first needs to be trained with a sufficiently large instance-to-concept ground truth, which only exists for a few languages. In this work, we tackle this lack of resources with word vector space alignment techniques: We train the NVC model on a high resource language and test it with vectors from an aligned word vector space of another language, without retraining or fine-tuning. A quantitative and qualitative analysis shows that the NVC model indeed activates meaningful concepts for unseen vectors from the aligned vector space. NVC thus becomes available for low resource languages for which no appropriate concept ground truth exists.
Performance, Art, and Cyber-Interoceptive Systems (PACIS)

This paper1 provides a survey of the research-creation activities of the collaboration, Performance, Art, and Cyber-Interoceptive Systems (PACIS). PACIS has been exploring how technology can help us create deeper connections with the world around us, each other, and ourselves by combining bioinformatic sensing technology with physiological awareness techniques found in The Batdorf Technique (TBT). Primary outputs of this research involve the development of new and novel interfaces that integrate complex physiological data in performance and computational art contexts. The focus of this endeavour is on the sharing of knowledge and exchange of ideas across disciplines, the traineeship of students and emerging scholars in the technological as well as somatic techniques and the creation of workshops, articles and performances.
Author identification with feature transformation method

Abstract Over the last few decades, there has been tremendous growth in online communication through different types of media. Communication via the Internet is anonymous, which causes a critical issue regarding identity tracing. Authorship identification can apply to tasks such as identifying an anonymous author, detecting plagiarism, or finding a ghostwriter. Previous research has outlined the various methods and their improvements for the identification of anonymous authors based on stylometry. However, changes in the writing style of an author over a long period has not been addressed. In this article, we propose a methodology for author identification where the writing style of an author changes. The proposed methodology consists of two phases: the first will show the change in writing style of the author and in another phase the change is mitigated by a new feature normalization technique. A novel Transform Feature to Current Time function is proposed for normalization, where features are shifted to current time and made available for further classification. A machine-learning algorithm is used to identify an author candidate. The experiments of the proposed methodology conducted on a set of text samples by several authors were collected over a different time period and the results show an improvement in performance.
Challenging judicial impartiality

Abstract Impartiality is one of the core values underlying the administration of justice. A complaint about a judge’s supposed lack of impartiality may be filed on the grounds of the judge’s verbal behavior. In this article I will analyze complaints that concern the judge’s use of rhetorical questions during court hearings. I will explore what role these complaints may play in the strategic maneuvering of a party who seeks the judge’s disqualification.
Second-Order Characterizations via Partial Smoothing

Smooth entropies are a tool for quantifying resource trade-offs in information theory and cryptography. However, in typical multi-partite problems some of the sub-systems are often left unchanged and this is not reflected by the standard smoothing of information measures over a ball of close states. We propose to smooth instead only over a ball of close states which also have some of the reduced states on the relevant sub-systems fixed. This partial smoothing of information measures naturally allows to give more refined characterizations of various information-theoretic problems in the one-shot setting. As a consequence, we can derive asymptotic second-order characterizations for tasks such as privacy amplification against classical side information or classical state splitting. For quantum problems like state merging the general resource trade-off is tightly characterized by partially smoothed information measures as well.
Performance Evaluation and Scheme Selection of Person Re-Identification Algorithms in Video Surveillance

With the increasing number of camera networks deployed in public places, intelligent video processing has become a key technology for video surveillance. In order to alleviate the workload of the tracers in the artificial tracking video, person re-identification (re-id) can match a large number of pedestrian images to obtain the location of same person at different time in surveillance. This article focuses on the comparison of different classic distance metric learning methods so as to select optimum person re-identification scheme with excellent performance. The authors compare four algorithms matching Local Maximal Occurrence (LOMO) feature representation on three common databases and obtains a criterion to choose algorithms for different datasets. The selection of re-identification algorithms can simplify the video investigation process according to the size and number of person images. In the end, they propose an improved metric learning based on one of algorithms and get improved results. The re-id is useful and efficient in works such as the criminal investigators etc.
Missing and Modified Data in Nonparametric Estimation: With R Examples.

Missing and modified data are common complications in statistical analysis. In this book, missing data are considered as those elements in the data matrix that are unavailable, while modified data ...
One More Accuracy k-Anonymity Framework for LBS

To achieve privacy protection in the k-anonymity algorithm, replacing the starting positions of k users with the center of the cloaked area results in the route from the starting position to the center of the cloaked area probably nonlinear, which will bring out the inconvenience for the user. This paper proposes a new anonymous server framework, on which we add the function of electronic map and navigation compared to the original one based on the framework of k-anonymity for LBS. In addition to the original tasks including computing the center of cloaked area <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi>O</mml:mi></mml:math> and the actual query result <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mrow><mml:msub><mml:mrow><mml:mi>r</mml:mi></mml:mrow><mml:mrow><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> corresponding to the query <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mrow><mml:msub><mml:mrow><mml:mi>q</mml:mi></mml:mrow><mml:mrow><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math>, the anonymous server with the new architecture will plan the actual path <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M4"><mml:mrow><mml:msub><mml:mrow><mml:mi>l</mml:mi></mml:mrow><mml:mrow><mml:msub><mml:mrow><mml:mi>o</mml:mi></mml:mrow><mml:mrow><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>−</mml:mo><mml:mi>O</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> from the starting query location <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M5"><mml:mrow><mml:msub><mml:mrow><mml:mi>o</mml:mi></mml:mrow><mml:mrow><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> to the center of the cloaked area <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M6"><mml:mi>O</mml:mi></mml:math> and return the new result collection of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M7"><mml:mrow><mml:mfenced open="{" close="}" separators="|"><mml:mrow><mml:msub><mml:mrow><mml:mi>r</mml:mi></mml:mrow><mml:mrow><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mrow><mml:mi>r</mml:mi></mml:mrow><mml:mrow><mml:mi>O</mml:mi><mml:mo>−</mml:mo><mml:mi>s</mml:mi><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mfenced></mml:mrow></mml:math> for the user <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M8"><mml:mrow><mml:msub><mml:mrow><mml:mi>u</mml:mi></mml:mrow><mml:mrow><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math>. Moreover, this paper improves the algorithm of computing the route <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M9"><mml:mrow><mml:msub><mml:mrow><mml:mi>r</mml:mi></mml:mrow><mml:mrow><mml:mi>O</mml:mi><mml:mo>−</mml:mo><mml:mi>s</mml:mi><mml:mi>i</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> to make it more in line with the actual situation of road network operation. Finally, we prove the importance of the approach by the experiment demonstration.
Towards a Pile Quality Prediction for Screw Displacement Piles Using Bayesian Networks

For screw displacement piles, there is quite some machine data being gathered during the installation, such as torque, pull down and velocity. However, there is no systematic way to process these data and knowledge from the engineer and machinist, neither during nor after the installation stage. Aiming to optimize the installation process, a research project was set up jointly with the Dutch industry. The main focus has been to deliver a proof-of-concept of a Bayesian Network that provides an assessment of the installation of each installed pile. The approach had to make use of analysing measurement data during installation, including expert knowledge and interpretation, and other usually unexploited process parameters. In the end, we believe that including these in a decision support system may bring us closer to a robotized installation of piles.
New Business Applications for the Blockchain

Until recently, blockchain technology was primarily of interest to financial institutions. The ability of blockchain to authenticate digital information and create smart contracts is leveraging the usefulness of technology on a world-changing scale. The new breed of programmable blockchain platforms, such as Ethereum, which provides decentralized computational power, is making the technology applicable to a wide range of cases and industries.