Reviewerly/exHarmony huggingface dataset:
On the application of projection threading method in the teaching of probability theory

The probability density function of the sum of random variables and marginal density function are important and difficult concepts in the course of probability theory. The key to calculate them is to determine the range of interested variables and integral variables. Combined with graphics, the range of those variables can be determined quickly by using projection threading method. The proposed method is intuitive and easy to master.
Programmable photonic system for quantum simulation in arbitrary topologies

Synthetic dimensions have generated great interest for studying many types of topological, quantum, and many-body physics, and they offer a flexible platform for simulation of interesting physical systems, especially in high dimensions. In this Letter, we describe a programmable photonic device capable of emulating the dynamics of a broad class of Hamiltonians in lattices with arbitrary topologies and dimensions. We derive a correspondence between the physics of the device and the Hamiltonians of interest, and we simulate the physics of the device to observe a wide variety of physical phenomena, including chiral states in a Hall ladder, effective gauge potentials, and oscillations in high-dimensional lattices. Our proposed device opens new possibilities for studying topological and many-body physics in near-term experimental platforms.
SPACE: Speech-driven Portrait Animation with Controllable Expression

Animating portraits using speech has received growing attention in recent years, with various creative and practical use cases. An ideal generated video should have good lip sync with the audio, natural facial expressions and head motions, and high frame quality. In this work, we present SPACE, which uses speech and a single image to generate high-resolution, and expressive videos with realistic head pose, without requiring a driving video. It uses a multi-stage approach, combining the controllability of facial landmarks with the high-quality synthesis power of a pretrained face generator. SPACE also allows for the control of emotions and their intensities. Our method outperforms prior methods in objective metrics for image quality and facial motions and is strongly preferred by users in pair-wise comparisons. The project website is available at https://deepimagination.cc/SPACE/
Research and Applications Analysis of Knowledge Base Question Answering

Knowledge Base Question Answering (KBQA) has become one of recent trends in Natural Language Processing (NLP). It helps solve question answering tasks in many fields, such as commerce, medical treatment, etc. This article represents research of KBQA from theory to practice. The concept of knowledge graph in a new way are defined, the steps for building a basic knowledge graph are listed. The category of knowledge base is generalized. This article analyzes the category of knowledge based on systems and introduces the definition and working principle of KBQA. This article also introduces two main approaches used in KBQA, Information Retrieval-based (IR-based) methods and Semantic Parsing-based (SP-based) methods, including summarizing pipeline frameworks of these two approaches and the comparison between them. Two successful applications of KBQA, Meituan and AliMe, including researching on the schema of knowledge graph and pipeline frameworks are discussed in this article. Moreover, this article analyzes the applicable scenes of the two applications and analyzes the main challenges of KBQA.
T-SEA: Transfer-based Self-Ensemble Attack on Object Detection

Compared to query-based black-box attacks, transfer-based black-box attacks do not require any information of the attacked models, which ensures their secrecy. However, most existing transfer-based approaches rely on ensembling multiple models to boost the attack transferability, which is time- and resource-intensive, not to mention the difficulty of obtaining diverse models on the same task. To address this limitation, in this work, we focus on the single-model transfer-based black-box attack on object detection, utilizing only one model to achieve a high-transferability adversarial attack on multiple black-box detectors. Specifically, we first make observations on the patch optimization process of the existing method and propose an enhanced attack framework by slightly adjusting its training strategies. Then, we analogize patch optimization with regular model optimization, proposing a series of self-ensemble approaches on the input data, the attacked model, and the adversarial patch to efficiently make use of the limited information and prevent the patch from overfitting. The experimental results show that the proposed framework can be applied with multiple classical base attack methods (e.g., PGD and MIM) to greatly improve the black-box transferability of the well-optimized patch on multiple mainstream detectors, meanwhile boosting white-box performance. Our code is available at https://github.com/VDIGPKU/T-SEA.
Education information management system based on Cloud Computing Technology

To overcome the shortcomings in the stage of education and teaching management in college and effectively transform the education mode, in this paper, cloud computing as well as big data technology are combined with college education and teaching management to promote the education and teaching managementinformationization. Therefore, on the basis of learning useful experience in the past, this paper realizes the effective docking of cloud computing, big data technology and university education and teaching management informatization from multiple dimensions, and then clarifies the requirements for the informatization of college education and teaching management.Moreover, these problems existing in the informatization link are explored in the context of the actual situation. Thereby, on this basis, the steady progress of informatization work can be promoted from the level of attention and technical equipment upgrading.
Exact Quantum Algorithms for Quantum Phase Recognition: Renormalization Group and Error Correction

We explore the relationship between renormalization group (RG) flow and error correction by constructing quantum algorithms that exactly recognize 1D symmetry-protected topological (SPT) phases protected by finite internal Abelian symmetries. For each SPT phase, our algorithm runs a quantum circuit which emulates RG flow: an arbitrary input ground state wavefunction in the phase is mapped to a unique minimally-entangled reference state, thereby allowing for efficient phase identification. This construction is enabled by viewing a generic input state in the phase as a collection of coherent `errors' applied to the reference state, and engineering a quantum circuit to efficiently detect and correct such errors. Importantly, the error correction threshold is proven to coincide exactly with the phase boundary. We discuss the implications of our results in the context of condensed matter physics, machine learning, and near-term quantum algorithms.
Pengaruh Kompetensi Sumberdaya Manusia terhadap Kualitas Laporan Keuangan Daerah Pemerintah Provinsi Jambi melalui Pemanfaatan Teknologi Informasi sebagai Variabel Intervening

This study aimed to determine the effect of human resource competence on the quality of regional financial reports at the Jambi Provincial Government through the utilization of information technology. The populations in this study were officials at the Regional Apparatus Organization within the Jambi Provincial Government which functions as accounting entities involved in regional financial management and reporting. The sample in this study was selected by using the judgment sampling method, namely officials authorized in the management and reporting of regional finances from 19 OPD in the Jambi Provincial Government. Data analysis in this study used the Partial Least Square (PLS) approach with the help of Smart PLS 3.0 software. The results of this study indicated that HR competencies had a direct influence on the utilization of information technology and the quality of regional financial reports. The results of this study also indicated that the competence of human resources had an indirect influence on the quality of regional financial reports at the Regional Government Organization of Jambi Province through the utilization of information technology.
Fast Coalgebraic Bisimilarity Minimization

Coalgebraic bisimilarity minimization generalizes classical automaton minimization to a large class of automata whose transition structure is specified by a functor, subsuming strong, weighted, and probabilistic bisimilarity. This offers the enticing possibility of turning bisimilarity minimization into an off-the-shelf technology, without having to develop a new algorithm for each new type of automaton. Unfortunately, there is no existing algorithm that is fully general, efficient, and able to handle large systems. We present a generic algorithm that minimizes coalgebras over an arbitrary functor in the category of sets as long as the action on morphisms is sufficiently computable. The functor makes at most $\mathcal{O}(m \log n)$ calls to the functor-specific action, where $n$ is the number of states and $m$ is the number of transitions in the coalgebra. While more specialized algorithms can be asymptotically faster than our algorithm (usually by a factor of $\mathcal{O}(\frac{m}{n})$), our algorithm is especially well suited to efficient implementation, and our tool Boa often uses much less time and memory on existing benchmarks, and can handle larger automata, despite being more generic.
Quantum Computing by Quantum Walk on Quantum Slide

Continuous-time quantum walk is one of the alternative approaches to quantum computation, where a universal set of quantum gates can be achieved by scattering a quantum walker on some specially-designed structures embedded in a sparse graph [Childs, Phys. Rev. Lett. 2009]. Recent advances in femtosecond laser-inscribed optical waveguides represent a promising physical platform for realizing this quantum-walk model of quantum computation. However, the major challenge is the problem of preparing a plane-wave initial state. Previously, the idea of quantum slide has been proposed and experimentally realized for demonstrating the working principle of NAND tree [Wang et al. Phy. Rev. Lett. 2020]. Here we show how quantum slide can be further applied to realize universal quantum computation, bypassing the plane-wave requirement. Specifically, we apply an external field to the perfect-state-transfer chain, which can generate a moving Gaussian wave packet with an arbitrary momentum. When the phase is properly tuned, the universal gate set in Childs' proposal can be realized in our scheme. Furthermore, we show that the gate fidelities increase with the length of the slide, and can reach unity asymptotically.
Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality

Stochastic restoration algorithms allow to explore the space of solutions that correspond to the degraded input. In this paper we reveal additional fundamental advantages of stochastic methods over deterministic ones, which further motivate their use. First, we prove that any restoration algorithm that attains perfect perceptual quality and whose outputs are consistent with the input must be a posterior sampler, and is thus required to be stochastic. Second, we illustrate that while deterministic restoration algorithms may attain high perceptual quality, this can be achieved only by filling up the space of all possible source images using an extremely sensitive mapping, which makes them highly vulnerable to adversarial attacks. Indeed, we show that enforcing deterministic models to be robust to such attacks profoundly hinders their perceptual quality, while robustifying stochastic models hardly influences their perceptual quality, and improves their output variability. These findings provide a motivation to foster progress in stochastic restoration methods, paving the way to better recovery algorithms.
Designing Immersive Art Installation Highlighting Culture using Spatial Augmented Reality: Case Study in Kuching, Malaysia

People have recently discussed Augmented Reality (AR) in art. In the present society, technological advancement has expanded the understanding and creation of art. Augmented Reality is not just limited to interacting using digital devices by the creators or viewers. It is also used as a non-interactive such as with the application of Spatial Augmented Reality. However, more research needs to be conducted on the potential and integration of Spatial Augmented Reality's role in art to promote culture. Based on previous observational studies and surveys among local youth, we proposed a design for art installation employing SAR. The aim was to present to local youth an immersive art as a case study that highlights local artistic motifs to seek its potential as a strategy to create an immersive art experience while promoting local culture. As a result, the study's findings are divided into two categories. First was the process of integrating SAR with an art installation that focused on local aesthetics. Second, the understanding of how SAR-based impact on spectators' experience.
Related Formalisms and Applications

Abstract In this chapter, we discuss connections of approval-based committee voting with a number of other applications and formalisms.
Pemberdayaan Pembangkit Listrik Mikro Tenaga Surya dan Sosialisasi Resiko Pencurian Arus PLN di Desa Blang Pulo

At this time, electricity has become a primary need for the community, the existence of the State Electricity Company (PLN) is very supportive of all community activities. The high use of electricity can cause negative effects for users, where the higher the use of electricity, the greater the costs incurred. This is what triggers the emergence of things that are not wanted in society. One of them is the emergence of a desire to steal electric current. In general, people do not know what the risks are due to stealing the electric current. In addition, there are other ways to reduce excessive use of electricity, one of which is by assembling a solar micro-power plant, of which not many people know about the use of assembling the power plant. Based on this, service is carried out with the aim of providing explanations and adding knowledge to the community in the safe use of electrical energy; provide explanations and increase knowledge for the public about the risk of theft of electrical energy; increase community participation in using and protecting the environment by using alternative energy; foster a strong bond between the Blang Pulo gampong which is the closest village to the Malikussaleh University Bukit Indah campus and the Malikussaleh University academic community, especially the electric energy-saving extension team. The counseling activity on the risk of theft of PLN flows in the village of Blang Pulo is carried out in the following activity methods: Program introduction, assembly and delivery of various forms of energy, especially solar energy; The submission of a frugal living attitude according to Islamic law is accompanied by showing several verses of the Koran and hadith and conveying the risks due to stealing electric current. The expected results of this service are through the micro-solar electricity empowerment program and energy-saving counseling, It is hoped that the awareness, sensitivity and participation of lecturers and the community of Blang Pulo will grow and develop in the safe and efficient use of electrical energy so that there is an adequate supply of electricity and there will be no longer rotating blackouts caused by the limited supply of electricity from the PLN, and explain the consequences if electrical energy is stolen for personal or group use in order to be able to use electrical energy for free.
All-optical generation of deterministic squeezed Schrödinger-cat states

Quantum states are important resources and their preparations are essential prerequisites to all quantum technologies. However, they are extremely fragile due to the inevitable dissipations. Here, an all-optical generation of a deterministic squeezed Schr$\ddot{\mathrm{o}}$dinger-cat state based on dissipation is proposed. Our system is based on the Fredkin-type interaction between three optical modes, one of which is subject to coherent two-photon driving and the rest are coherent driving. We show that an effective degenerate three-wave mixing process can be engineered in our system, which can cause the simultaneous loss of two photons, resulting in the generation of a deterministic squeezed Schr$\ddot{\mathrm{o}}$dinger-cat state. More importantly, by controlling the driving fields in our system, the two-photon loss can be adjustable, which can accelerate the generation of squeezed Schr$\ddot{\mathrm{o}}$dinger-cat states. Besides, we exploit the squeezed Schr$\ddot{\mathrm{o}}$dinger-cat states to estimate the phase in the optical interferometer, and show that the quantum Fisher information about the phase can reach the Heisenberg limit in the limit of a large photon number. Meanwhile, it can have an order of magnitude factor improvement over the Heisenberg limit in the low-photon-number regime, which is very valuable for fragile systems that cannot withstand large photon fluxes. This work proposes an all-optical scheme to deterministically prepare the squeezed Schr$\ddot{\mathrm{o}}$dinger-cat state with high speed and can also be generalized to other physical platforms.
Towards Practical Privacy-Preserving Solution for Outsourced Neural Network Inference

When neural network model and data are outsourced to cloud server for inference, it is desired to preserve the confidentiality of model and data as the involved parties (i.e., cloud server, model providing client and data providing client) may not trust mutually. Solutions were proposed based on multi-party computation, trusted execution environment (TEE) and leveled or fully homomorphic encryption (LHE/FHE), but their limitations hamper practical application. We propose a new framework based on synergistic integration of LHE and TEE, which enables collaboration among mutually-untrusted three parties, while minimizing the involvement of (relatively) resource-constrained TEE and allowing the full utilization of the untrusted but more resource-rich part of server. We also propose a generic and efficient LHE-based inference scheme as an important performance-determining component of the framework. We implemented/evaluated the proposed system on a moderate platform and show that, our proposed scheme is more applicable/scalable to various settings, and has better performance, compared to the state-of-the-art LHE-based solutions.
Meningkatkan Motivasi Belajar Melalui Kegiatan Kolase pada Anak Kelompok B TK Pertiwi II Pringsurat Temanggung Semester II Tahun Pelajaran 2017/2018

In general, classroom action research aims to increase learning motivation through collage activities for children in Group B of TK Pertiwi II Pringsurat Temanggung in the second semester of the 2017/2018 academic year. Specifically, it aims to: (1) find out the application of collage activities can increase children's learning motivation (2) To determine the magnitude of the increase in children's learning motivation after collage activities are carried out. The research was carried out in two cycles, where each cycle consists of stages planning, implementation, observation, and reflection. Cycle I consisted of two meetings, as well as Cycle II. The subjects in this study were children in Group B, with a total of 16 children. The object of this research is to increase children's learning motivation through collage activities. In this study, the data collection methods used were observation, documentation and interviews. The results showed that during the implementation of collage activities with various materials at TK Pertiwi II Pringsurat, the researchers motivated all children, especially children who were not confident. After the action was taken, in Cycle I, the child started to want to do the given task. In Cycle II the children have shown an increase in their learning motivation. From the results of the research described above, collage activities can increase children's learning motivation. The children also seemed happy in doing collage activities both in Cycle I and Cycle II. The advantages of the activities carried out are very varied, including collage activities using various basic fields and using varied and diverse materials. Through fun learning activities, children's learning motivation can develop optimally.
IDENTIFICATION OF FACE MASK USING CONVOLUTIONAL NEURAL NETWORK-BASED EFFICIENTNET MODEL

The highly contagious coronavirus wreaked havoc around the globe. There has been a rapid spread of the virus throughout the world. According to the World Health Organization (WHO), wearing a facemask will help keep the virus from infecting others. Consequently, many governments have adopted the solution of wearing facemasks. In this paper, we use a convolutional neural network (CNN), and a scaling method, namely, EfficientNet with Adam optimizer, for detecting face masks in real-time. A dataset including 10,000 colored images was collected from a public data platform, Kaggle, for training, and testing of the model. Image augmentation is also investigated on the dataset to improve the training, and testing accuracy. Then the binary classifier model is used to detect masks after detecting faces using single shot detection (SSD). From the experimental results, the EfficientNet model outperforms the existing CNN-based methods in terms of accuracy, efficiency, and the validation accuracy of EfficientNet models is above 99 percent. This efficient and highly accurate model can be used to detect facemask anywhere in a real time video surveillance system.
Analisis Implementasi Metode Home Visit di Masa Pandemi Covid-19 dalam Mengatasi Masalah Belajar Siswa pada Mata Pelajaran Matematika Materi Pecahan Kelas IV SDN Batursari 6 Mranggen Demak

This study was to find out the reasons for choosing the home visit method, how the process of implementing the home visit method was, how the response of parents and students to the implementation of the home visit method to overcome student learning problems in the mathematics subject matter of fractions in class IV SDN Batursari 6 Mranggen Demak. This type of research is qualitative research. The research population is class IV SDN Batursari 6 Mranggen Demak. The research subjects were all students of class IVB at SDN Batursari 6 Mranggen Demak for the academic year 2021/2022. The data in this study were obtained through teacher and principal interview instruments, observation sheets, parent and student questionnaires, and documentation. The implementation of home visits can be an effort to overcome student learning difficulties because teachers can know firsthand the condition of the learning environment and the development of each student.
Artificial Intelligence in the Delivery of Healthcare Service Using Chatbot

Artificial Intelligence and its application in healthcare delivery has led to the development of chatbot. Artificial Intelligence is concerned with development of machines that simulates intelligence of human expert in a domain to perform complex task associated with human. The need for urgent healthcare delivery is essential to all humans. Artificial Intelligence provides the platform to meet this need and resolve the associated challenges through the use of chatbot in healthcare delivery. Chatbot leverages branches of Artificial Intelligence such as Natural Language Processing and Machine Learning and features like word segmentation and tokenization to provide appropriate response to patients requiring immediate healthcare service. This paper aim to review the process of chatbot in healthcare delivery. Keywords: Artificial Intelligence, Delivery, Healthcare Service, Chatbot, Natural Language Processing