Reviewerly/exHarmony huggingface dataset:
Physical Implementability of Linear Maps and Its Application in Error Mitigation

Completely positive and trace-preserving maps characterize physically implementable quantum operations. On the other hand, general linear maps, such as positive but not completely positive maps, which can not be physically implemented, are fundamental ingredients in quantum information, both in theoretical and practical perspectives. This raises the question of how well one can simulate or approximate the action of a general linear map by physically implementable operations. In this work, we introduce a systematic framework to resolve this task using the quasiprobability decomposition technique. We decompose a target linear map into a linear combination of physically implementable operations and introduce the physical implementability measure as the least amount of negative portion that the quasiprobability must pertain, which directly quantifies the cost of simulating a given map using physically implementable quantum operations. We show this measure is efficiently computable by semidefinite programs and prove several properties of this measure, such as faithfulness, additivity, and unitary invariance. We derive lower and upper bounds in terms of the Choi operator's trace norm and obtain analytic expressions for several linear maps of practical interests. Furthermore, we endow this measure with an operational meaning within the quantum error mitigation scenario: it establishes the lower bound of the sampling cost achievable via the quasiprobability decomposition technique. In particular, for parallel quantum noises, we show that global error mitigation has no advantage over local error mitigation.
Learning Temporal Quantum Tomography

Quantifying and verifying the control level in preparing a quantum state are central challenges in building quantum devices. The quantum state is characterized from experimental measurements, using a procedure known as tomography, which requires a vast number of resources. However, tomography for a quantum device with temporal processing, which is fundamentally different from standard tomography, has not been formulated. We develop a practical and approximate tomography method using a recurrent machine learning framework for this intriguing situation. The method is based on repeated quantum interactions between a system called quantum reservoir with a stream of quantum states. Measurement data from the reservoir are connected to a linear readout to train a recurrent relation between quantum channels applied to the input stream. We demonstrate our algorithms for representative quantum learning tasks, followed by the proposal of a quantum memory capacity to evaluate the temporal processing ability of near-term quantum devices.
Dynamics of Transmon Ionization

Qubit measurement and control in circuit QED rely on microwave drives, with higher drive amplitudes ideally leading to faster processes. However, degradation in qubit coherence time and readout fidelity has been observed even under moderate drive amplitudes corresponding to few photons populating the measurement resonator. Here, we numerically explore the dynamics of a driven transmon-resonator system under strong and nearly resonant measurement drives, and find clear signatures of transmon ionization where the qubit escapes out of its cosine potential. Using a semiclassical model, we interpret this ionization as resulting from resonances occurring at specific resonator photon populations. We find that the photon populations at which these spurious transitions occur are strongly parameter dependent and that they can occur at low resonator photon population, something which may explain the experimentally observed degradation in measurement fidelity.
Exploring Eye Gaze Visualization Techniques for Identifying Distracted Students in Educational VR

Virtual Reality (VR) headsets with embedded eye trackers are appearing as consumer devices (e.g. HTC Vive Eye, FOVE). These devices could be used in VR-based education (e.g., a virtual lab, a virtual field trip) in which a live teacher guides a group of students. The eye tracking could enable better insights into students’ activities and behavior patterns. For real-time insight, a teacher’s VR environment can display student eye gaze. These visualizations would help identify students who are confused/distracted, and the teacher could better guide them to focus on important objects. We present six gaze visualization techniques for a VR-embedded teacher’s view, and we present a user study to compare these techniques. The results suggest that a short particle trail representing eye trajectory is promising. In contrast, 3D heatmaps (an adaptation of traditional 2D heatmaps) for visualizing gaze over a short time span are problematic.
Single-photon scattering in a giant-molecule waveguide-QED system

We study the coherent single-photon scattering in a one-dimensional waveguide coupled to a giant artificial molecule consisting of two coupled giant atoms. Since each giant atom couples to the waveguide via two coupling points, the couplings of the molecule with the waveguide have three different coupling configurations: the separated-, braided-, and nested-coupling cases. We obtain the exact expressions of the single-photon transmission and reflection amplitudes with the real-space approach. It is found that the behavior of the scattering spectra depends on the phase shift between two neighboring coupling points, the coupling configuration, and the coupling between the two giant atoms. Concretely, we study the photon scattering in both the Markovian and non-Markovian regimes, in which the photon propagating time between two neighboring coupling points is neglected and considered, respectively. Under the Markovian limit, the asymmetric Fano line shapes in different coupling configurations of the giant-molecule waveguide-QED system can be obtained by choosing proper phase shift, and the transmission window can be adjusted by the coupling strength between the two giant atoms in these three coupling configurations. In particular, multiple reflection peaks and dips in these configurations are revived in the non-Markovian regime. This paper will pave the way for the study of controllable single-photon devices based on the giant-molecule waveguide-QED systems.
Text2Human

Generating high-quality and diverse human images is an important yet challenging task in vision and graphics. However, existing generative models often fall short under the high diversity of clothing shapes and textures. Furthermore, the generation process is even desired to be intuitively controllable for layman users. In this work, we present a text-driven controllable framework, Text2Human, for a high-quality and diverse human generation. We synthesize full-body human images starting from a given human pose with two dedicated steps. 1) With some texts describing the shapes of clothes, the given human pose is first translated to a human parsing map. 2) The final human image is then generated by providing the system with more attributes about the textures of clothes. Specifically, to model the diversity of clothing textures, we build a hierarchical texture-aware codebook that stores multi-scale neural representations for each type of texture. The codebook at the coarse level includes the structural representations of textures, while the codebook at the fine level focuses on the details of textures. To make use of the learned hierarchical codebook to synthesize desired images, a diffusion-based transformer sampler with mixture of experts is firstly employed to sample indices from the coarsest level of the codebook, which then is used to predict the indices of the codebook at finer levels. The predicted indices at different levels are translated to human images by the decoder learned accompanied with hierarchical codebooks. The use of mixture-of-experts allows for the generated image conditioned on the fine-grained text input. The prediction for finer level indices refines the quality of clothing textures. Extensive quantitative and qualitative evaluations demonstrate that our proposed Text2Human framework can generate more diverse and realistic human images compared to state-of-the-art methods. Our project page is https://yumingj.github.io/projects/Text2Human.html. Code and pretrained models are available at https://github.com/yumingj/Text2Human.
KuaiRec

The progress of recommender systems is hampered mainly by evaluation as it requires real-time interactions between humans and systems, which is too laborious and expensive. This issue is usually approached by utilizing the interaction history to conduct offline evaluation. However, existing datasets of user-item interactions are partially observed, leaving it unclear how and to what extent the missing interactions will influence the evaluation. To answer this question, we collect a fully-observed dataset from Kuaishou's online environment, where almost all 1,411 users have been exposed to all 3,327 items. To the best of our knowledge, this is the first real-world fully-observed data with millions of user-item interactions.
Inference from Ignorance: The Recognition Heuristic

While a hindrance to statistical and computational models of inference, missing knowledge can be exploited by organisms in their natural environments. The recognition heuristic utilizes missing knowledge to make accurate inferences about the real world. A consequence of applying this heuristic is a counterintuitive less-is-more effect where less knowledge is better than more for inferential accuracy. Theoretical arguments and experimental evidence supporting the less-is-more effect are given.
Performance Evaluation Of The Biological Unit Process For Fecal Sludge Supernate Treatment (Case Study: Iplt Madurejo Sleman Regency, Special Region Of Yogyakarta)

IPLT Madurejo is located in Sub-village Tinjon, Madurejo Village, Prambanan District, Sleman Regency, DIY. This IPLT was built in 2017 with a capacity design of 25 m3 /day. The existing condition shows that IPLT effluent from 2021-2022 has not met the quality standards of Minister of Environment and Forestry Regulation No. 68 of 2016. Therefore it is necessary to evaluate the technical processes so that the effluent meets quality standards. The method in this evaluation is carried out through evaluating existing conditions with design criteria and recommendations, both in terms of operational and process aspects of each stabilization pond unit, namely evaluating technical criteria, evaluating capacity, evaluating efficient removal of treatment, evaluating IPLT operations and planning on alternative unit designs. The average influent discharge of IPLT Madurejo from 2021-2022 is 29 m3 /day, of which the planning design capacity is 25 m3 /day. Therefore, IPLT Madurejo has an overload capacity of 4 m3 /day. The alternatives are to add similar pools with the same volume as well as adding Holding Tanks, Grease Traps, and disinfectant pools can be used as recommendations to increase the performance of IPLT and have a high probability of successful operation.
Effectiveness of Using Online Academic Information System (Siakad) at Uncen's Faculty of Social and Political Sciences

Information and communication technology today is growing rapidly in all fields. The conceptualization of technology implies that every administration and management activity is technology and definitely requires technology. The position of the technology is even more important when the innovation successfully combines technology and information. There have been many users who use information and communication technology in their daily lives, who have experienced an escalation of transformation that was so powerful that it was impossible to imagine before, information technology has penetrated so deeply into the smallest domains of human life, including in the application of academic information systems. (SIAKAD) in improving the quality of academic services at FISIP-UNCEN. The application of SIAKAD in seven (7) Study Programs has unique characteristics because it provides the data needed by users, namely lecturers and students. Comprehensive SIAKAD should be successful in its application and accepted by its users. One of the determining factors for success in implementing a system is when the system is acceptable to users. SIAKAD that can be accepted by users (students and lecturers) can improve the quality of academic services which in turn has implications for quality improvement. The purpose of this research is to find out how effective the use of the Online Academic Information System (SIAKAD) is. and factors that become obstacles to the use of the SIAKAD application in seven (7) Study Programs in the FISIP-UNCEN environment. The methodology used in conducting this research is to use more qualitative data methods&#x0D;
Accomodation Theory in Language Teaching and for Students With Special Needs

This research aims to find out the forms of accommodation that can be used for students with special needs and students in general in language or non-language classes. This research method is qualitative, namely taking references from these or from forms of accommodation made by researchers while teaching English. The results of the study show that teachers, with all their efforts, have made efforts to provide accommodation in the teaching and learning process so that students can be treated according to their needs, so that they can be independent and develop their potential. They are enthusiastic in the teaching and learning process because the learning is more interesting and varied, and they appreciate diversity. However, it cannot be denied that the majority of these accommodations usually apply to specific educational institutions and the creativity of teachers to always learn to improve their teaching and learning process, which takes a lot of time to find suitable methods and ignore the potential negative effects of accommodations on students.
Obfuscating Verifiable Random Functions for Proof-of-Stake Blockchains

Blockchain systems, such as Bitcoin and Ethereum, enable new applications, such as cryptocurrencies and smart contracts, using decentralized consensus without trusted authorities. Since the most widely used technique, proof-of-work, suffers from the costs of high latency and huge energy consumption, a number of blockchain systems based on proof-of-stake techniques have been proposed in recent years, many of which use verifiable random functions as fundamental building blocks, such as Ouroboros, Algorand, and Dfinity, etc. The secret key of a verifiable random function scheme, similar to that of a digital signature scheme, is critical to the security of a verifiable random function and the entire blockchain system built on it. To protect the secret keys of verifiable random functions and maintain the efficiency of the proof-of-stake protocol, we extend the objective of cryptographic program obfuscation to verifiable random functions and propose a novel obfuscatable verifiable random function scheme. In particular, we propose an obfuscator that can transform the implementation of the scheme's random string generation algorithm and the given secret key into an unintelligible form. Obfuscated implementations of the random string generation algorithm are deployed on peers of a blockchain for supporting normal routines of the proof-of-stake protocol. Even if a hacker has controlled a peer's host, the owner's secret key will not be compromised because the key has been hardwired into the obfuscated implementation in an “encrypted manner”. We formally prove the correctness and the security of the proposed verifiable random function and obfuscator. Since the proposed scheme supports the general semantics of verifiable random functions, it can be used as a building block for all blockchain systems that adopt proof-of-stake protocols based on Verifiable Random Functions (VRFs). The extensive experimental result indicated that the scheme performs well on various platforms, such as cloud servers, workstations, PCs, smartphones, and embedded devices.
Towards Video Anomaly Detection in the Real World: A Binarization Embedded Weakly-Supervised Network

In this letter, we pioneer to propose a binarization embedded weakly-supervised video anomaly detection (BE-WSVAD) method by constructing a binarized GCN-based anomaly detection module. Compared to the existing weakly-supervised video anomaly detection (WS-VAD) methods, BE-WSVAD focuses on the detection efficiency, which is ignored by the existing literature yet vital in real applications. Specifically, to improve the detection performance of the binary anomaly detection module, we propose a binary network augmentation strategy in the training process. Due to the weakly supervision mechanism, the videos employed in the training process are usually lengthy, in which the lengthy-input dependencies tend to be exploited to improve the detection performance with extra memory consumption. Then, we propose the short-input inference modes, which can largely reduce the desired length of the input video. Experimental results demonstrate the superiority of our BE-WSVAD in terms of the memory and computational consumptions while giving comparable accuracies.
Data preprocessing and tokenization techniquesfortechnical Ukrainian texts

The field of Natural Language Processing (NLP) has witnessed significant advancements fueled by machine learning, deep learning, and artificial intelligence, expanding its applicability and enhancing human-computer interactions. However, NLP systems grapple with issues related to incomplete and error-laden data, potentially leading to biased model outputs. Specialized technical domains pose additional challenges, demanding domain-specific fine-tuning and custom lexicons. Moreover, many languages lack comprehensive NLP support, hindering accessibility.In this context, we explore novel NLP data preprocessing and tokenization techniques tailored for technical Ukrainian texts. We address a dataset comprising automotive repair labor entity names, known for errors and domain-specific terms, often in a blend of Ukrainian and Russian. Our goal is to classify these entities accurately, requiring comprehensive data cleaning, preprocessing and tokenization.Our approach modifies classical NLP preprocessing, incorporating language detection, specific Cyrillic character recognition, compounded word disassembly, and abbreviation handling. Text line normalization standardizes characters, punctuation, and abbreviations, improving consistency. Stopwords are curatedto enhance classification relevance. Translation of Russian to Ukrainian leverages detailed classifiers, resulting in a correspondence dictionary.Tokenization addresses concatenated tokens, spellingerrors, common prefixes in compound words and abbreviations.Lemmatization, crucial in languages like Ukrainian and Russian, builds dictionaries mapping word forms to lemmas, with a focus on noun cases. The results yield a robust token dictionary suitable for various NLP tasks, enhancing the accuracy and reliability of applications, particularly in technical Ukrainian contexts. This research contributes to the evolving landscape of NLP data preprocessing and tokenization, offering valuable insights for handling domain-specific languages.
HotGestures: Complementing Command Selection and Use with Delimiter-Free Gesture-Based Shortcuts in Virtual Reality

Conventional desktop applications provide users with hotkeys as shortcuts for triggering different functionality. In this paper we consider what constitutes an effective parallel to hotkeys in a 3D interaction space where the input modality is no longer limited to the use of a keyboard. We propose HotGestures: a gesture-based interaction system for rapid tool selection and usage. Hand gestures are frequently used during human communication to convey information and provide natural associations with meaning. HotGestures provide shortcuts for users to seamlessly activate and use virtual tools by performing hand gestures. This approach naturally complements conventional menu interactions. We evaluate the potential of HotGestures in a set of two user studies and observe that our gesture-based technique provides fast and effective shortcuts for tool selection and usage. Participants found HotGestures to be distinctive, fast, and easy to use while also complementing conventional menu-based interaction.
Phase-diagram investigation of frustrated 1D and 2D Ising models in OEO-based Ising machine

Ising machines have emerged as promising solvers for combinatorial optimization problems in recent years. In practice, these problems are often mapped into a frustrated Ising model due to randomness or competing interactions, which reduces the success ratio for finding the optimal solution. In this study, we simulate one-dimensional and two-dimensional frustrated Ising models in an Ising machine based on the optoelectronic oscillator. Our experiment aims to show the relationship between the Fourier mode of the coupling matrix and the spin distribution under frustration. The results prove the validity of the theoretical predictions and provide insights into the behavior of Ising machines in the presence of frustration. We believe it would help to develop a better strategy to improve the performance of Ising machines.
GrAI-pho-logy: Integration of Graphology With Artificial Intelligence

Graphology is the study of handwriting and it is used to analyse personality traits and characteristics. It is based on the idea that a person's handwriting has certain physical characteristics that are thought to reflect various aspects of their personality. It has traditionally been a field conducted by human experts who interpret various aspects of handwriting such as stroke patterns, letter formations, and spacing. While graphology relies on subjective interpretation, the introduction of artificial intelligence (AI) has the potential to enhance and automate certain aspects of graphological analysis. In the present work, the intention is to provide an overview in the integration of the concept of graphology with AI and the method is casted as grAIphology (grAI-pho-logy). The word grAIphology is coined by the authors of the present paper.
Textbooks as Value-laden: A Critical Discourse Analysis of Moral Values Representation in Primary School EFL Textbooks

The inculcation of moral values in English textbooks, particularly in primary schools, has been a global concern in recent decades due to English’s growing importance as a global lingua franca and the impact it carries. Hence, the present study aimed to: (1) elucidate the realisation of moral values discursively represented in three primary school English textbooks entitled English Chest 1, 2 and 3, and (2) determine the extent of the textbooks’ contents in teaching the moral values. Fairclough’s (1995, 2013) framework of Critical Discourse Analysis (CDA) integrated with Kress &amp; Van Leeuwen’s (2006) Visual Grammar Theory (VGT) was applied to elucidate the depiction of moral values in the textbooks. Additionally, Isaacs’ (2001) framework of Developmental Moral Values and Smetana’s (2006) Social Domain Theory were also adopted to look at how the contents of the textbooks teach moral values. The results show that (1) modesty (8,99%), curiosity (8,44%), perseverance (7,08%), and friendship (6,53%) are the most frequently occurring values in the three EFL textbooks. (2) The discursive realisation has revealed that certain fundamental moral values such as audacity, sociability, industriousness, respect for others, and responsibility are taught through the depictions of verbal-visual images in both school and familial contexts. Importantly, the three EFL textbooks have fairly adhered to the Indonesian moral (character) education goals and stipulation. They also provide implications on both primary school students and English teachers’ pedagogical, linguistic, and moral development so as to raise EFL textbook designers’ awareness to develop more morally-laden content.