Reviewerly/exHarmony huggingface dataset:
The whole from the parts: Markovian stabilizing dynamics and ground-state cooling under locality constraints

We focus on two classes of pure states for a finite-dimensional multipartite quantum system: those that can be identified as unique ground states (UGS) of a locally-constrained Hamiltonian, and those that can be obtained as unique, asymptotically stable equilibria of a Markov quantum dynamics under the same quasi-locality constraints (QLS). While there is an equivalence between (strict) subsets of two classes, namely, states that are UGS of frustration-free Hamiltonians and unique equilibria of purely dissipative dynamics, two paradigmatic entangled states, GHZ and W, offer counterexamples to either implication in the general setting. The intuition that every UGS state can be obtained as the exact steady state of a Markovian cooling process is salvaged only if suitable non-local resources are added. We show that stochastic stabilization of the target UGS state can be achieved if we perform continuous measurement of the global Hamiltonian, while controlling the dynamics with a switching, filtering-based quantum feedback strategy.
Practical Data Sharing at Untrusted Stores

The most effective way to protect data in remote stores is to adopt cryptographic schemes, so that all of the delegated data are ciphertext. In order to share these encrypted data with others, the Proxy Re-Encryption ( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$PRE$</tex> ) technique is proposed. It allows a proxy to convert a ciphertext encrypted under one key into an encryption of the same message under another key, while placing as little trust and reveal to the proxy as necessary to allow it to perform its translations. <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$PRE$</tex> turns out to be the most suitable scheme for remote data sharing and becomes popular with the spread of cloud computing. However, in reality, it is difficult for users to manage their secret keys by themselves and not to authorize others by generating the re-encryption keys. In this proposal, we introduce a distributed key management system ( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$DKMS$</tex> ) to manage user keys and handle data sharing requests. The <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$DKMS$</tex> is an honest authority that does not provides any encryption or re-encryption services, thus it is of zero-knowledge to the data. Moreover, the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$DKMS$</tex> will not store the intact secret keys, which will only appear in runtime environment and be destroyed after lifecycle.
DIY (Do-It-Yourself) Electronics, Coin-Operated Relic Boxes and Techno-Animist Shrines

Abstract The author uses creative practice and DIY electronics as the vehicle for a practice-led inquiry into the similarities between techno-animism and material agency. Combining technology with aspects of magic and religion, techno-animism is an emerging concept in postmodern anthropology used to discuss the sentient agency of objects and materials within the context of modern technological societies. This combination of seemingly disparate fields of knowledge is the basis of a postdisciplinary research into creative practices, attitudes and ethos using a series of artifacts that visualize the ideas of techno-animism, made by the author over a period of 30 years.
Track-to-Track fusion with cross-covariances from radar and IR/EO sensor

The Track-to-track fusion (T2TF) problem for estimates from radar and infrared/electro-optical (IR/EO) sensor is studied in this work. For such a problem, the heterogeneous estimates from local trackers (LT) are in different state spaces with various dimensions and are related by a nonlinear relationship with no inverse transformation. For the homogeneous T2TF problem, where the common state model is shared by both LTs in the same state space, the cross-covariance between the local estimation errors, which has been known for some time, needs to be considered in the T2TF. However, such a cross-covariance for heterogeneous T2TF was not available in previous works. In the present work, the derivation of the cross-covariance for heterogeneous LTs of different dimension states is provided, yielding a recursion, by taking into account the relationship between the local state model process noises. A linear minimum mean square (LMMSE) estimator is used for the T2TF. With the cross-covariance involved, the fusion will generate the covariance of the fused estimation error which makes the system consistent as shown in the simulation through Monte-Carlo runs.
Nagement of Social Development of Organization in Russia

The aim of the study is to analyze the mechanism for managing the social development of Russian organizations. The article discusses the historical aspects of social processes, priority areas of the concept of the formation of a new social policy, the goals of modern social programs. A visual mechanism for managing social development is given, recommendations are formulated to ensure its eff ective operation. The domestic methodology for calculating social indicators based on compiling social passports in the context of humanization of labor and social infrastructure is considered. The typical organizational structures of the personnel management system of Western and Russian organizations are analyzed, distinguishing characteristics are noted. In practice, the traditional tool for implementing the mechanism of managing social development is a set of social benefi ts, in connection with which the article provides an analysis of the components of the social package. The characteristic of social, moral, creative incentives, options for intangible incentives in modern Russian companies, methods and specifi c measures of intangible incentives are given.
On-Demand Teleradiology Using Smartphone Photographs as Proxies for DICOM Images

Teleradiology is the transmission of radiographic images from one location to another for interpretation. Teleradiology service providers help to fill the need for sub-specialty expert consultants, vacation leaves, and overflow gaps in the onsite radiology facilities. Teleradiology has become a large and growing industry [1] . The integration standard called the Integrating of Healthcare Enterprise (IHE) [2] have been developed to address communication issues between medical imaging sites. However, the IHE standard allows different vendors to implement the standard in different ways [3] which significantly limits the ability to transmit and receive images between organizations in practice.
Non-Euclidean Kalman Filters for Nonlinear Measurements

Target tracking in the presence of nonlinear measurements has long been recognized as a challenge. When measurements are in polar coordinates this sometimes manifests itself as the &#x2018;contact lens&#x2019; distribution, especially in radar applications. The authors propose a new filtering paradigm - the Non-Euclidean Kalman Filter (NEUKF) - to efficiently represent these nonlinear distributions using isomorphic coordinate transforms, which requires only modest computation beyond the popular Unscented Kalman Filter. They propose a family of parabolic isomorphisms well suited for representing the contact lens distribution. The NEUKF using one of the parabolic transforms is compared to a number of other prominent filters in both single and multiple sensor scenarios. The NEUKF demonstrates either the best-in-class or competitive precision and accuracy across all four scenarios, and is the only filter to maintain near perfect covariance consistency at all times.
Limiting distribution of periodic position measurements of a quantum harmonic oscillator

We consider a particle in harmonic oscillator potential, whose position is periodically measured with an instrument of finite precision. We show that the distribution of the measured positions tends to a limiting distribution when the number of measurements tends to infinity. We derive the expression for the limiting position distribution and validate it with numerical simulation.
The Development of an Artificial Intelligence Assistant for Participatory Design in the Engineering Design Educational Environment

Participatory design (PD) is a method that focuses on the nature of collaboration, enabling users to participate actively in the design process and assess the feasibility of the design and give feedback. The characteristics make it suitable for application in the field of education, to train students to explore the user's needs for products and participate in the solution of the problem. However, applying PD in the educational environment is not easy because it is difficult to find product users to participate in the teaching process throughout the school. Therefore, the purpose of this study is to design, construct, and develop a smart voice assistant. It can act like a product user to have a smooth conversation with students. The intelligent voice assistant will give feedback to students. This study has analyzed the dialogue between users and designers by the past PD research and found out the intention in the process of dialogue based on the engineering design process. And based on these intentions, the experience in the use of products, product requirements, unmet, and other information was collected into the database. The developed intelligent voice assistant can partially replace the real user in the PD. An experiment will be conducted to confirm the effectiveness of the developed intelligent voice assistant.
Developing a Method of Composing Key Components of a Video Image Based on the Integration of their Code Structures

Developed a method for the reconstruction of sections of video images, based on information about its significant coordinate- brightness and uneven linearly scaling components by integrating segment overheads obtained for a row of the array of non-uniform lengths of coherence areas.
A Multiple Hypothesis Approach to Extended Target Tracking

Extended target tracking is a challenging task which has recently been the subject of intense research. Indeed, with the increase of the resolution of modern sensors such as LIDAR or large bandwidth radar, targets reflect multiple measurements and cannot be tracked as a single point. This is a very acute problem in the automotive context, where the targets to be tracked are other vehicles or trucks, and estimating jointly their shape and position is critical to achieve higher level functionalities. In this paper, we propose a PMHT approach to track extended targets modeled as rectangles. Implicit measurement models are used to solve the problem of the unknown origin of the measurement on the surface of the object. As the PMHT does not offer a mechanism to model existence probability, we use a Hidden Markov Model (HMM) to decide on the presence of every target. Also, as laser scanner does not offer a classification for static and dynamic objects, we created a freespace based classification used for track initialization. Finally, we demonstrate the effectiveness of our approach with real data from laser scanner and radar.
A Short-Time Prediction of Sun Radiation Intensity

This paper deals with short-time sun intensity prediction. The power of the solar panel correlates closely with the amount of electromagnetic radiation in the visible light and near-infrared radiation band. We measure the radiation of a visible and infrared wave, in short intervals using SparkFun spectral sensors. Data are preprocessed to clusters and prepared for prediction by the artificial neural networks. The experiment uses two variations of time clusters one-hour and quarter-hour. The networks were trained by different algorithms to compare the results. Further, it analyzes measured data and makes a short-time prediction of solar irradiance. This work aims to predict the amount of power delivered by the solar panel.
Hadoop Performance Acceleration by Effective Data and Job Placement

In order to accelerate Hadoop performance, it is important to efficiently handle the data and job placement. More specifically, we focus on to accelerate the performance of heterogeneous distributed cluster as Hadoop default has limited performance outcome for data-intensive jobs. To improve the Hadoop performance, it is important to consider the heterogeneity of nodes, reduce job latency, and improve the data locality of blocks. In this research, we use block rearrangement policy which can rearrange the data blocks considering node’s processing capability or heterogeneity of node for data placement and effectively use node labeling and scheduling schemes for job placement to meet the goal. The experimental result shows that the proposed model accelerates the Hadoop performance by achieving high data locality and less job completion time compared to default configuration and policy.
Analysis: Various Load Balancing Competencies for Data Centres

Use of Information Technology is increasing daily, thus there's a requirement of storage and calculating tools such as jog. Substantial quantities of information adapting within the Web and have been produced has to necessitate the quantities of tools. Several organizations are profoundly requiring virtualization systems such as cloud-computing etc., to exhibit their own infrastructure capacities also to advertise their own funding. Amounts of end users can access internet software in any time period virtually. It will become an endeavor for your own internet app to react and deal with these consumer requests. As a result of media traffic that is significant it ends in procedure accident or operation lag. There must be a considered described way to supports users and to defeat those bottlenecks. Balancing is also to be considered while using the proper method of distributing computing tools and workloads. This method ensures utmost at as well as throughput response period. This paper introduces a questionnaire on various load balancing approaches.
Network Authentication Based on Blockchain Technology without Tokens

With the development of information technologies, not only the economy is digitalised, but also other spheres of human activity. Cryptography plays a massive role in ensuring the security of this process. With its help, such tasks as ensuring confidentiality, integrity control, authentication, securing the impossibility of renouncing authorship are solved. Network authentication is especially relevant nowadays because it determines access to the services of many people. This raises the issue of user data security, including personal data.In this paper, an algorithm for network-based authentication technology of the distributed registry is proposed. The features of application, advantages, disadvantages, the possibility of introduction into existing systems are considered.
The Collaborative Identification of Design Flaws in Software Systems

Discovering defects in software source code is crucial to ensuring extendable and available computer systems, and a fundamental feature of their development and maintenance. Detecting such defects at an early stage of development can bring significant economic benefits, so efforts have been made to automate their detection and correction. The objective of this research study is to devise a way to improve the detection of such errors by using a cooperative approach, using metrics-based error detection. With the cooperation of 20 professional software developers, disciplined experiments were carried out, with preliminary results confirming their effectiveness in revealing design flaws. In addition, procedures were also produced in support of a cooperative approach to the problem, and the results can form the basis of further research and help individual software developers in their efforts to detect source code errors.
Webometric Analysis Agriculture University Websites for Maharashtra State

The article examines the website of Agriculture University of Maharashtra State. The study is to do the webometric analysis of Agriculture university of Maharashtra state. This study during January 2019 to March 2019. It was found that 5 (4 Agriculture +1 Animal & Fishery Sciences University) Agriculture University in Maharashtra. Further the data were analyzed to find out the evaluate the efficiency of these websites of University by university website, Global Rank, website audience, and Marketing Channels. Based on the parameters determined by similarweb.
Autonomous Portuguese L3 learning through an adaptive platform

Despite increasing need for on-demand, autonomous language learning, difficult technical issues render this approach insufficient without a human in the loop (e.g., blended learning). In this chapter, we discuss how recent advances in human language technology (HLT), cognitive science, and second language acquisition (SLA) combined can address seemingly intractable problems (e.g., intelligent feedback on error). We introduce an HLT-enabled adaptive language learning platform and examine the results from a pilot study in which English native speakers highly proficient in Spanish as a second language used the platform to learn Portuguese as a third language. Such “conversion” training from Spanish to Portuguese provides an ideal testbed for these innovative HLT and SLA ideas.
Design of Transaction System for Remote Sensing Cloud Service based on Blockchain

With the development of RS (Remote Sensing) technology and RS application, RS industry is faced with opportunities and challenges in expanding the application fields. There is a high maintenance costs, time-consuming, low transaction processing efficiency, user privacy leaks and so on in the traditional centralized RSCS (Remote Sensing Cloud Services) trading mode. Meanwhile, it can't adapt to high-frequency and real-time trading scenario. In order to realize efficient, fair and transparent trade and protect the privacy of users, this paper proposed transaction system mode for RSCS based on blockchain. The user may call or produce the same task multiple times in the traditional transaction process. In this case, the system allocates and recycles resources frequently. It has caused unnecessary overhead and wasted the time of user. Therefore, we proposed AS (Algorithm Service) transaction mode combine smart contract. We can achieve decentralized P2P trade among through smart contract. The AS can reduce user's repetitive work, improve the efficiency of transaction processing, and improve user experience.
Impact of Correlation-based Feature Selection on Photovoltaic Power Prediction

This paper empirically presents the impact of the correlation-based feature selection on the accuracy of the photovoltaic (PV) power prediction, and then selects the weather variables that maximize prediction accuracy. To this end, the experiments are conducted using the weather dataset consisting of eighteen weather variables (i.e., features). For experiments, we first calculate a correlation coefficient of each weather variable by analyzing the correlation between PV power and each weather variable. Then, we create the subsets of weather variables considering the absolute value of correlation coefficient and generate the multiple prediction models using the created subsets. Finally, the accuracy of the generated prediction models is compared with each other to find the most accurate prediction model. The experiment results provide a reference guideline for selecting the weather variables that maximize the accuracy of PV power prediction.
EntiTies

We describe an open source web application called EntiTies for annotating the entities throughout a text and the ties between them. Example uses of this tool include extracting character networks from novels or entity networks from legal documents. EntiTies' interface allows users to annotate a text from scratch, to process it automatically, or to process it automatically and then correct it. Forking allows multiple annotations to exist for the same text. EntiTies enables texts and annotations to be easily shared with others or kept private.
Implementing Alternative Communication using a Limited Number of Simple Sign Language Gestures

The article discusses one of the approaches to the implementation of alternative communication using non-verbal communication means. It is proposed to use human finger configurations as input controls. A model of a human hand is proposed for the implementation of the dactyl alphabet of sign language for the deaf. The possibilities of existing hand tracking devices have been investigated. An application has been developed to identify a set of finger configurations that are reliably recognized by front stereo cameras. A limited number of simple sign language gestures are defined that are convenient to show and easy to remember for people. A software module for text entry messages with a limited number of simple finger configurations has been developed. The main advantage of this approach is its ease of use and accessibility for people with temporary communication disabilities. Further research is focused on the use of dynamic gestures as controls.
Experimental Study on Lightning Warning by Atmospheric Electric Field

The atmospheric electric field intensity threshold method is generally used for lightning warning at present. However, this method has the problem of high false alarm rate. The lightning warning effect can be effectively improved by combining the electric field change rate threshold of 5 minutes and electric field threshold. The lightning warning effect can be effectively improved by combining the 5 minutes electric field change rate threshold with electric field threshold. The threshold value of electric field and the threshold value of electric field change rate in Wenjiang can be obtained by using the statistical method to approach the actual first and last moments of lightning weather, and a lightning warning model based on atmospheric electric field is established. The lightning warning model is verified with the lightning monitoring data from 2014 to 2017. The results show that: 1) The success rate of lightning warning is 74.2%, the false alarm rate is 12.9% and the missing alarm rate is 9.7%. 2) The start warning for the lightning weather process was 2.2 minutes ahead, and the end of the lightning weather process was 4.4 minutes behind. The warning time series basically covers the lightning weather process, and meets the need of short local warning for the lightning weather process.
Software Safety Requirement Analysis Based on Improved AHP and Grey Clustering Model

Aiming at the existing software safety requirements analysis, there are many subjective qualitative analysis with less objective quantitative analysis. First, the weapon equipment software safety requirement index system is constructed in this paper. Secondly, an analysis method based on improved Analytic Hierarchy Process (AHP) and grey clustering model are proposed. The model can solve the problem that the AHP index weight is not objective and the grey clustering model has similar clustering coefficients. Finally, the safety requirement analysis of a certain weapon equipment software system is taken as an example to evaluate the results. The results show that the method can effectively improve the accuracy and scientificity of the assessment.