Reviewerly/exHarmony huggingface dataset:
A Scalable Virtualized Server Cluster Providing Sensor Data Storage and Web Services

With the rapid development of the Internet of Things (IoT) technology, diversified applications deploy extensive sensors to monitor objects, such as PM2.5 air quality monitoring. The sensors transmit data to the server periodically and continuously. However, a single server cannot provide efficient services for the ever-growing IoT devices and the data they generate. This study bases on the concept of symmetry of architecture and quantities in system design and explores the load balancing issue to improve performance. This study uses the Linux Virtual Server (LVS) and virtualization technology to deploy a virtual machine (VM) cluster. It consists of a front-end server, also a load balancer, to dispatch requests, and several back-end servers to provide services. These receive data from sensors and provide Web services for browsing real-time sensor data. The Hadoop Distributed File System (HDFS) and HBase are used to store the massive amount of received sensor data. Because load-balancing is critical for resource utilization, this study also proposes a new load distribution algorithm for VM-based server clusters that simultaneously provide multiple services, such as sensor services and Web service. It considers the aggregate load of all back-end servers on the same physical server that provides multiple services. It also considers the difference between physical machines and VMs. Algorithms such as those for LVS, which do not consider these factors, can cause load imbalance between physical servers. The experimental results demonstrate that the proposed system is fault tolerant, highly scalable, and offers high availability and high performance.
Comparing and Analyzing Cohesive Devices of SMT and NMT from Chinese to English: A Diachronic Approach

This work presents a detailed comparison and analysis of the usage of cohesive devices by three Machine Translation systems from Chinese to English, in both SMT and NMT situations.By both a general analysis of sentence length as well as cohesive devices and detailed analysis of a sentence translation in SMT and NMT with human translation as a reference, it is shown that, compared with SMT, NMT system is better at handling cohesive ties such as additive, adverbs and pronouns; however, both SMT and NMT underperform at dealing with demonstratives and lexical cohesion.This suggests an evidence of improved translation quality and the necessity of pre-editing and post-editing cohesive devices in MT translations.
Consumer Technology Versus 5G

At its inception in the 19th-century, the talking telegraph (AKA the telephone) was an amazing feat of engineering using analog technology. One could speak into a micro-phone in one city and be heard in another city. Accom-plishing this required a very large investment in technol-ogy. The customers were consumers of the service.
A Generic Visualization Approach Supporting Task-Based Evaluation of Usability and User Experience

Analyzing evaluation results of usability and user experience studies has its limitations when it comes to personalized user interfaces, highly complex and connected systems, or internationally used services involving millions of users. To support the analysis of the evaluation results of usability and user experience, a task-based evaluation approach is proposed. This approach uses multiple visualization views to support the analysis of evaluation results. The visualization offers different temporal views ranging from individual to more cumulative data views in order to combine results from evaluations and task models. The applicability of this approach is presented on a simple but demonstrative case study from television and entertainment.
Describing squeezed-light experiments without squeezed-light states

Coherent states are normally used to describe the state of a laser field in experiments that generate and detect squeezed states of light. Nevertheless, since the laser field absolute phase is unknown, its quantum state can be described by a statistical mixture of coherent states with random phases, which is equivalent to a statistical mixture of Fock states. Here we describe single-mode squeezed vacuum experiments using this mixed quantum state for the laser field. Representing the laser state in the Fock basis, we predict the usual experimental results without using the squeezing concept in the analysis and concluding that no squeezed state is generated in the experiments. We provide a general physical explanation for the noise reduction in the experiments in terms of a better definition of the relative phase between the signal and local oscillator fields. This explanation is valid in any description of the laser field (in terms of coherent or Fock states), thus providing a deeper understanding of the phenomenon.
Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs

While Generative Adversarial Networks (GANs) show increasing performance and the level of realism is becoming indistinguishable from natural images, this also comes with high demands on data and computation. We show that state-of-the-art GAN models -- such as they are being publicly released by researchers and industry -- can be used for a range of applications beyond unconditional image generation. We achieve this by an iterative scheme that also allows gaining control over the image generation process despite the highly non-linear latent spaces of the latest GAN models. We demonstrate that this opens up the possibility to re-use state-of-the-art, difficult to train, pre-trained GANs with a high level of control even if only black-box access is granted. Our work also raises concerns and awareness that the use cases of a published GAN model may well reach beyond the creators' intention, which needs to be taken into account before a full public release. Code is available at https://github.com/a514514772/hijackgan.
Case Study: Reflection of COVID-19 on Teaching Physics for Undergraduate Students

The case study presented in this report provides information on the challenges of teaching physics for undergraduate students.We discuss the physics teaching method before and during the spread of COVID-19.Within the text, we explored the following topics: ( 1) Education before COVID-19; (2) The study problems in physics; (3) The face to face teaching methods; (4) Why is physics necessary for life?(5) Physics is associated with human thought; (6) Effective physics teaching skills; (7) Evaluation and assignments; (8) Characteristics of physics teaching skills; (9) Teaching physics and digital technology; (10) Challenges of the physics quality teaching during COVID-19.
Free-Viewpoint Facial Re-Enactment from a Casual Capture

We propose a system for free-viewpoint facial re-enactment from a casual video capture of a target subject. Our system can render and re-enact the subject consistently in all the captured views. Furthermore, our system also enables interactive free-viewpoint facial re-enactment of the target from novel views. The re-enactment of the target subject is driven by an expression sequence of a source subject, which is captured using a custom app running on an iPhone X. Our system handles large pose variations in the target subject while keeping the re-enactment consistent. We demonstrate the efficacy of our system by showing various applications.
No Crash, No Exploit: Automated Verification of Embedded Kernels

The kernel is the most safety- and security-critical component of many computer systems, as the most severe bugs lead to complete system crash or exploit. It is thus desirable to guarantee that a kernel is free from these bugs using formal methods, but the high cost and expertise required to do so are deterrent to wide applicability. We propose a method that can verify both absence of runtime errors (i.e. crashes) and absence of privilege escalation (i.e. exploits) in embedded kernels from their binary executables. The method can verify the kernel runtime independently from the application, at the expense of only a few lines of simple annotations. When given a specific application, the method can verify simple kernels without any human intervention. We demonstrate our method on two different use cases: we use our tool to help the development of a new embedded real-time kernel, and we verify an existing industrial real-time kernel executable with no modification. Results show that the method is fast, simple to use, and can prevent real errors and security vulnerabilities.
Evaluation on the Security of Commercial Cloud Container Services

With the increasing adoption of the container mechanism in the industrial community, cloud vendors begin to provide cloud container services. Unfortunately, it lacks a concrete method to evaluate the security of cloud containers, whose security heavily depends on the security policies enforced by the cloud providers. In this paper, we first derive a metric checklist that identifies the critical factors associated with the security of cloud container services against the two most severe threats, i.e., the privilege escalation and container escaping attacks. Specifically, we identify the metrics which directly reflect the working conditions of the attacker. We also extract the metrics essential to achieve privilege escalation and container escaping attacks by investigating the feasible methods for breaking the security measures, including KASLR, SMEP and SMAP, etc. Since memory corruption vulnerabilities are frequently adopted in the privilege escalation attacks, we collect a dataset of the publicly released memory corruption vulnerabilities to assist the evaluation. Then, we develop a tool to collect the metric data listed in the checklist from inside the cloud containers and perform security inspection on five in-service commercial cloud container services. The results show that some containers are enforced with weak protection mechanisms (e.g., with the Seccomp mechanism being disabled), and the KASLR could be bypassed on all five cloud containers. However, even after obtaining ROOT privilege in a container, attackers still can hardly escape from the container on the public cloud platforms, since the necessary files for crafting or compiling a loadable kernel module for the host OS are inaccessible to the container. Finally, we provide some suggestions to improve the security of the cloud container services.
Detection Power of Separability Criteria Based on a Correlation Tensor: A Case Study

Detection power of separability criteria based on a correlation tensor is tested within a family of generalized isotropic state in $d_1 \otimes d_2$. For $d_1 \neq d_2$ all these criteria are weaker than positive partial transposition (PPT) criterion. Interestingly, our analysis supports the recent conjecture that a criterion based on symmetrically informationaly complete positive operator-valued measure (SIC-POVMs) is stronger than realignment criterion.
A New Mixed Clustering-based Method to Analyze the Gait of Children with Cerebral Palsy

Cerebral palsy is a group of persistent central movement and postural developmental disorders, and restricted activity syndromes. This syndrome is caused by non-progressive brain damage to the developing fetus or infants. Cer... | Find, read and cite all the research you need on Tech Science Press
Differentially Private k-Means Clustering with Convergence Guarantee

Iterative clustering algorithms help us to learn the insights behind the data. Unfortunately, this may allow adversaries to infer the privacy of individuals with some background knowledge. In the worst case, the adversaries know the centroids of an arbitrary iteration and the information of n-1 out of n items. To protect individual privacy against such an inference attack, preserving differential privacy (DP) for the iterative clustering algorithms has been extensively studied in the interactive settings. However, existing interactive differentially private clustering algorithms suffer from a non-convergence problem, i.e., these algorithms may not terminate without a predefined number of iterations. This problem severely impacts the clustering quality and the efficiency of a differentially private algorithm. To resolve this problem, in this paper, we propose a novel differentially private clustering framework in the interactive settings which controls the orientation of the movement of the centroids over the iterations to ensure the convergence by injecting DP noise in a selected area. We prove that, in the expected case, algorithm under our framework converges in at most twice the iterations of Lloyd's algorithm. We perform experimental evaluations on real-world datasets to show that our algorithm outperforms the state-of-the-art of the interactive differentially private clustering algorithms with guaranteed convergence and better clustering quality to meet the same DP requirement.
Foreign Language Pre-Service Teachers’ Attitudes Towards Integrated Technology

The COVID-19 pandemic worldwide evidenced the need to revise and strengthen the current perspective of the role of technology in non-technology-based classes. The current situation requires the revision of practices and basic knowledge of computer literacy and use. Traditionally, technology in the process of language learning has been considered anecdotical. As a result, many teachers do not have the necessary skills to implement proper technology-supported classes. Being that the case at Universidad de Alcalá (Spain), we looked at the students’ needs in integrating a number of different applications in the classroom in order to provide them with additional technological skills. Twenty-two pre-service teachers enrolled in the College of Education prepared a whole package of applications for computer and mobile phones by working cooperatively. This paper looks at their attitudes towards technology learning and implementation. A Likert-scale questionnaire was developed to assess their attitudes. Results indicated that students do not evidence as much interest as expected despite their limited ability to implement the package.
Teacher’s professional image: reimagining the future

In this research, the authors aim to determine the teachers’ professional image in the present-day context. The issues of teachers’ new role, new image and professional conditions are analyzed with regard to the reforms and commercialization of higher education as the most common trends. The paper examines the data of the survey which was conducted on the basis of written questionnaire designed to investigate the university teachers’ readiness to work in the new conditions, their readiness to innovation, the factors constraining innovation in the sphere of higher education in the context of its commercialization. The research carries value to education policymakers and university authorities. They can use these findings to reflect on regulations that would ensure favorable academic environment and increase the brand image of their staff.
Real-Time High-Resolution Background Matting

We introduce a real-time, high-resolution background replacement technique which operates at 30fps in 4K resolution, and 60fps for HD on a modern GPU. Our technique is based on background matting, where an additional frame of the background is captured and used in recovering the alpha matte and the foreground layer. The main challenge is to compute a high-quality alpha matte, preserving strand-level hair details, while processing high-resolution images in real-time. To achieve this goal, we employ two neural networks; a base network computes a low-resolution result which is refined by a second network operating at high-resolution on selective patches. We introduce two largescale video and image matting datasets: VideoMatte240K and PhotoMatte13K/85. Our approach yields higher quality results compared to the previous state-of-the-art in background matting, while simultaneously yielding a dramatic boost in both speed and resolution.
Jointly-Learned State-Action Embedding for Efficient Reinforcement Learning

While reinforcement learning has achieved considerable successes in recent years, state-of-the-art models are often still limited by the size of state and action spaces. Model-free reinforcement learning approaches use some form of state representations and the latest work has explored embedding techniques for actions, both with the aim of achieving better generalization and applicability. However, these approaches consider only states or actions, ignoring the interaction between them when generating embedded representations. In this work, we establish the theoretical foundations for the validity of training a reinforcement learning agent using embedded states and actions. We then propose a new approach for jointly learning embeddings for states and actions that combines aspects of model-free and model-based reinforcement learning, which can be applied in both discrete and continuous domains. Specifically, we use a model of the environment to obtain embeddings for states and actions and present a generic architecture that leverages these to learn a policy. In this way, the embedded representations obtained via our approach enable better generalization over both states and actions by capturing similarities in the embedding spaces. Evaluations of our approach on several gaming, robotic control, and recommender systems show it significantly outperforms state-of-the-art models in both discrete/continuous domains with large state/action spaces, thus confirming its efficacy.
Relaxed Peephole Optimization: A Novel Compiler Optimization for Quantum Circuits

In this paper, we propose a novel quantum compiler optimization, named relaxed peephole optimization (RPO) for quantum computers. RPO leverages the single-qubit state information that can be determined statically by the compiler. We define that a qubit is in a basis state when, at a given point in time, its state is either in the X-, Y-, or Z-basis. When basis qubits are used as inputs to quantum gates, there exist opportunities for strength reduction, which replaces quantum operations with equivalent but less expensive ones. Compared to the existing peephole optimization for quantum programs, the difference is that our proposed optimization does not require an identical unitary matrix, thereby named `relaxed' peephole optimization. We also extend our approach to optimize the quantum gates when some input qubits are in known pure states. Both optimizations, namely the Quantum Basis-state Optimization (QBO) and the Quantum Pure-state Optimization (QPO), are implemented in the IBM's Qiskit transpiler. Our experimental results show that our proposed optimization pass is fast and effective. The circuits optimized with our compiler optimizations obtain up to 18.0% (11.7% on average) fewer CNOT gates and up to 8.2% (7.1% on average) lower transpilation time than that of the most aggressive optimization level in the Qiskit compiler. When running on real quantum computers, the success rates of 3-qubit quantum phase estimation algorithm improve by 2.30X due to the reduced gate counts.
EMPLOYMENT OF GRADUATES OF SECONDARY VOCATIONAL EDUCATION IN INFORMATION TECHNOLOGIES AND INFORMATION SECURITY: CAREER PREFERENCES AND JOB SEARCH

The article presents the study results of job search tactics and career preferences of graduates in the field of information technology and information security (hereinafter referred to as IT specialties) who graduated from educational institutions of secondary vocational education (hereinafter referred to as SVE) in 2016–2019. The main method to collect data was a formalized quantitative survey of 1,500 graduates, including those living in regional centers (cities with a population of over one million) in 17 constituent entities of the Russian Federation, by means of a structured online questionnaire. The respondents took part in the study by filling out the questionnaire online, by telephone and in person filling out a printed copy of the questionnaire. To improve the quality of the data and to form a holistic view of the peculiarities of recruiting graduates of secondary vocational education in IT specialties, the questionnaire survey was supplemented by 15 profound interviews on a structured guide with representatives of professional educational organizations who deal with the employment of graduates. The study results may help determine the main employment practices and career guidelines for young IT specialists (channels and duration of job search, demand for professional competencies, salary expectations, etc.), identify the main reasons why young specialists refuse to work by profession, develop conceptual schemes, and key directions for their employment.
Interactivity in digital teaching of a foreign language (on the example of Don State Technical University)

The article discusses the issues of methods of teaching a foreign language using digital technologies, taking into account their development in the Rostov region on the basis of the Don State Technical University. Attention is focused on the creation of information and educational environment at the university and the features of such an important didactic property of digital learning as interactivity. The types of interactivity, their differentiation, functioning, and interaction in the educational process are considered in detail. The authors observe such directions of digital education as blended learning, distance learning, and mass public on-line courses. To create a digital medium, the university organized a digital portal SKIF. The authors describe this portal and its opportunities for distance teaching. The advantages of digital education in comparison with traditional ones are noted, and the problems of transition from reproductive to creative-problematic type of teaching a foreign language are considered. The authors also note usage of gamification and augmented reality in the digital educational process.
Assessment of cancer embryonic antigen (CEA) biomarker in women with breast cancer disease

Breast cancer (BC) is the second close frequent most cancers among women, afterwards pores and skin cancer. It is near typically determined of ladies used fifty five in conformity with 64 The aim concerning the current education is in accordance with consider plasminogen activator inhibitor-1 biomarker, additionally measured the rapport among this biomarker or some parameters include: distressed diagnosis, youth, stage, par yet physique substance index between girls ith mamma most cancers disease. Method: The longevity existing study blanketed fifty five patients over AL-Najaf longevity ladies diagnosed along breast cancer. The samples have been stability pulled beside the sufferers when presence in conformity with AL-forat Al- Awsat center among AL-Najaf metropolis because of stability checking then treating in the course of the length prolonged from1/12/2018 to2/3/2019. The healthy team namely power was once drawn up of thirty -five (35) show up as like healthy were accrued beyond laboratory over pathological analyzes within AL-Najaf AL-Ashraf of one-of-a-kind times. The a long time over healthful crew had been matched along affected person ages.( 5 ml) about venous blood had been stretched out of breast most cancers sufferers then healthy team at 9-1A.M beyond ante cubital venipuncture the use of a disposable tine then plastic syringes. Results: The effects indicated a widespread expand (P<0.05) in PAI-1 degree of female along breast most cancers ailment into comparing along government group. The results over this learning toughness revealed a extensive make bigger (P<permanency 0,05) among PAI-1 stage within lobular carcinoma within evaluating together with ductal carcinoma. The (50-59y) revealed a noticeably appreciably (P<0.05) within PAI-1 stage compared with( 40-49y) and (60-69y). A sizeable make bigger between the levels concerning PAI-1 (P<0.05) among tribune 4 ( ΙⅤ) or value 3 between ladies with breast most cancers disease, whilst The statistical analysis confirmed longevity no substantial differences among the levels over Plasminogen activator inhibitor -1 between ladies together with breast cancer disorder (P>0.05) according after their BMI.