Reviewerly/exHarmony huggingface dataset:
Convergence Rates for the Quantum Central Limit Theorem

Various quantum analogues of the central limit theorem, which is one of the cornerstones of probability theory, are known in the literature. One such analogue, due to Cushen and Hudson, is of particular relevance for quantum optics. It implies that the state in any single output arm of an n-splitter, which is fed with n copies of a centred state ρ with finite second moments, converges to the Gaussian state with the same first and second moments as ρ . Here we exploit the phase space formalism to carry out a refined analysis of the rate of convergence in this quantum central limit theorem. For instance, we prove that the convergence takes place at a rate On-1/2 in the Hilbert-Schmidt norm whenever the third moments of ρ are finite. Trace norm or relative entropy bounds can be obtained by leveraging the energy boundedness of the state. Via analytical and numerical examples we show that our results are tight in many respects. An extension of our proof techniques to the non-i.i.d. setting is used to analyse a new model of a lossy optical fibre, where a given m-mode state enters a cascade of n beam splitters of equal transmissivities λ1/n fed with an arbitrary (but fixed) environment state. Assuming that the latter has finite third moments, and ignoring unitaries, we show that the effective channel converges in diamond norm to a simple thermal attenuator, with a rate O(n-12(m+1)) . This allows us to establish bounds on the classical and quantum capacities of the cascade channel. Along the way, we derive several results that may be of independent interest. For example, we prove that any quantum characteristic function χρ is uniformly bounded by some ηρ<1 outside of any neighbourhood of the origin; also, ηρ can be made to depend only on the energy of the state ρ .
Augmenting Tactile 3D Data Navigation With Pressure Sensing

Abstract We present a pressure‐augmented tactile 3D data navigation technique, specifically designed for small devices, motivated by the need to support the interactive visualization beyond traditional workstations. While touch input has been studied extensively on large screens, current techniques do not scale to small and portable devices. We use phone‐based pressure sensing with a binary mapping to separate interaction degrees of freedom (DOF) and thus allow users to easily select different manipulation schemes (e. g., users first perform only rotation and then with a simple pressure input to switch to translation). We compare our technique to traditional 3D‐RST (rotation, scaling, translation) using a docking task in a controlled experiment. The results show that our technique increases the accuracy of interaction, with limited impact on speed. We discuss the implications for 3D interaction design and verify that our results extend to older devices with pseudo pressure and are valid in realistic phone usage scenarios.
Diagnostics of Leadership Qualities of Specialists of "Man–Man" Type of Professions in Military and Civil Higher Education Institutions: Psychological and Pedagogical Approach

The article deals with the actual practical aspects of the problem of leadership qualities of future specialists of "man-man" type in military and civilian institutions of higher education.The aim of the research is to present the results of empirical research on the comparative diagnosis of the formation of leadership qualities of future specialists in the social sphere (psychologists, social employees) and cadets (military lawyers, psychologists).According to the results of scientific works, it has been determined that leadership qualities are a set of qualities that reflect the attitude to other people and society as a whole, allow oneself to influence other people, contribute to the creation of a positive atmosphere in the group, the team, is displayed in a stable, active, responsible behavior in order to achieve one's own and collective goals.Leadership qualities include commitment, determination, confidence, responsibility, activity, efficiency, success, influence, endurance.Diagnostics of formation of leadership qualities has been carried out by means of survey and a psychodiagnostic technique of the leadership abilities diagnostics by E. Zharikov, E. Krushelnytsky.The diagnostic results showed the predominance of students and cadets of the average level of leadership qualities formation.
Video compression to support the expansion of whole-slide imaging into cytology

Digital screening and diagnosis from cytology slides can be aided by capturing multiple focal planes. However, using conventional methods, the large file sizes of high-resolution whole-slide images increase linearly with the number of focal planes acquired, leading to significant data storage and bandwidth requirements for the efficient storage and transfer of cytology virtual slides. We investigated whether a sequence of focal planes contained sufficient redundancy to efficiently compress virtual slides across focal planes by applying a commonly available video compression standard, high-efficiency video coding (HEVC). By developing an adaptive algorithm that applied compression to achieve a target image quality, we found that the compression ratio of HEVC exceeded that obtained using JPEG and JPEG2000 compression while maintaining a comparable level of image quality. These results suggest an alternative method for the efficient storage and transfer of whole-slide images that contain multiple focal planes, expanding the utility of this rapidly evolving imaging technology into cytology.
Physics on the Go: A Mobile Computer-Based Physics Laboratory for Learning Forces and Motion

“Forces and Motion” is a topic that requires students to relate contents to re-al life applications but most of them have difficulties in connecting physics concepts to its corresponding representations and the connections of the rep-resentations to the real world. This contributes to poor conceptual under-standing among the students. Conventional teaching approaches also create poor interest among the students in studying Physics. Some school laborato-ries are not equipped sufficiently and some apparatus are broken or out dat-ed. Therefore, a Mobile Science Laboratory (MSL) is applied in the research to provide an alternative to better functioning laboratory which also uses Microcomputer-Based Laboratory (MBL) in providing up-to-date apparatus in data acquisition. This research investigates the impact of Mobile Com-puter-based Physics Laboratory (MCPL) which is a combination of the use of MSL and MBL in teaching and learning “Forces and Motion” called PotGo (Physics on the Go) using semi-structured interview. The data was analysed using thematic analysis. The result shows that MCPL improves the students’ understanding in Forces and Motion because the students can see and expe-rience the concepts in real life and getting the data in real time. MCPL is in-teresting for students because they can conduct Physics experiments using computers and technology, it is fun and the students can explore the Physics concepts with little time for setting up the experiments. Therefore, the use of PoTGo in MCPL affects students’ learning in “Forces and Motion” and interest towards Physics.
A Gridmap-Path Reshaping Algorithm for Path Planning

Path planning is a vital function of robotic systems. Different from existing roadmap algorithms which first determine the free space and then determine the collision-free path, researchers recently proposed several convex relaxation based smoothing algorithms which first select an initial path to link the starting configuration and the goal configuration and then reshape this path to meet other requirements (e.g., collision-free conditions) by using convex relaxation. However, convex relaxation based smoothing algorithms often fail to give a satisfactory path, since the initial paths are selected improperly. Moreover, the curvature constraints were not considered in many existing convex relaxation based smoothing algorithms. In this paper, we show that we can first grid the whole configuration space to pick a candidate path and reshape the shortest path to meet our goal. This new algorithm inherits the merit of roadmap algorithms and a convex feasible set algorithm. We further discuss how to meet the curvature constraints by using both the Beamlet algorithm to select a better initial path and an iterative optimization algorithm to adjust the curvature of a path. Theoretical analysis and numerical testing results show that our algorithm can almost surely find a feasible path and require a short computation time.
Automatic Quality Estimation for Natural Language Generation: Ranting (Jointly Rating and Ranking)

We present a recurrent neural network based system for automatic quality estimation of natural language generation (NLG) outputs, which jointly learns to assign numerical ratings to individual outputs and to provide pairwise rankings of two different outputs.The latter is trained using pairwise hinge loss over scores from two copies of the rating network.We use learning to rank and synthetic data to improve the quality of ratings assigned by our system: we synthesise training pairs of distorted system outputs and train the system to rank the less distorted one higher.This leads to a 12% increase in correlation with human ratings over the previous benchmark.We also establish the state of the art on the dataset of relative rankings from the E2E NLG Challenge (Dušek et al., 2019), where synthetic data lead to a 4% accuracy increase over the base model. Synthetic Training Data GenerationWe use RatPred's code to generate synthetic rating instances from both NLG outputs and humanauthored texts by distorting the text and lowering its score (i.e., randomly removing or adding words; cf.Dušek et al. (2017) and Figure 3 for details).We also create synthetic training pairs by using the same NLG output/human-authored text under two different levels of distortion (e.g., one vs.two artificially introduced errors).The system is then trained to rank higher the version of the text with fewer errors (see Figure 3 for an example).This novel approach can be used to generate synthetic training data for both ranking and rating tasks-in a rating task, the generated ranking instances are simply mixed among the original training instances for rating, and the model uses both kinds for training.Note that synthetic data are never used for validation or testing in any of our setups.
The Right to Benefit from Science and Its Implications for Genomic Data Sharing

Abstract The right to benefit from science and its applications is one of the least studied, discussed and applied human rights. In the current time of globalization, characterized by the rapid advancement of science and its technological applications, as well as by increased flows of scientific data, there is a growing need to fully awaken the right of everyone to enjoy the benefits of science. This would enable science to better serve the humanitarian purposes of the law as well as foster scientific and technological development through data sharing. This article contributes to the awakening of the right by exploring it doctrinally with the aim of ascertaining its normative content by reference to the preparatory works of Article 15 of the International Covenant on Economic, Social and Cultural Rights and, especially, the subsequent state practice in its application. Based on the evidence, it will be argued that, today, the right to benefit from science has two aspects – first, the right to access scientific knowledge and information and, second, the right to benefit from scientific applications. It will be shown that the first aspect of the right is increasingly reflected in the practice of states and international organizations and has important implications for the regulation and sharing of big genomic data.
Evaluation of Home-Based Rehabilitation Sensing Systems with Respect to Standardised Clinical Tests

With increased demand for tele-rehabilitation, many autonomous home-based rehabilitation systems have appeared recently. Many of these systems, however, suffer from lack of patient acceptance and engagement or fail to provide satisfactory accuracy; both are needed for appropriate diagnostics. This paper first provides a detailed discussion of current sensor-based home-based rehabilitation systems with respect to four recently established criteria for wide acceptance and long engagement. A methodological procedure is then proposed for the evaluation of accuracy of portable sensing home-based rehabilitation systems, in line with medically-approved tests and recommendations. For experiments, we deploy an in-house low-cost sensing system meeting the four criteria of acceptance to demonstrate the effectiveness of the proposed evaluation methodology. We observe that the deployed sensor system has limitations in sensing fast movement. Indicators of enhanced motivation and engagement are recorded through the questionnaire responses with more than 83 % of the respondents supporting the system’s motivation and engagement enhancement. The evaluation results demonstrate that the deployed system is fit for purpose with statistically significant ( ϱ c &gt; 0.99 , R 2 &gt; 0.94 , I C C &gt; 0.96 ) and unbiased correlation to the golden standard.
Spatio-Temporal Attention Network for Video Instance Segmentation

In this paper, we propose a method named spatio-temporal attention network for video instance segmentation. The spatio-temporal attention network can estimate the global correlation map between the successive frames and transfers it to the attention map. Added with the attention information, the new features may enhance the response of the instance for pre-defined categories. Therefore, the detection, segmentation and tracking accuracy will be greatly improved. Experimental result shows that combined with MaskTrack R-CNN, it may improve the video instance segmentation accuracy from 0.293 to 0.400@Youtube VIS test dataset with a single model. Our method took the 6th place in the video instance segmentation track of the 2nd Large-scale Video Object Segmentation Challenge.
Detection and Inpainting of Specular Reflection in Colposcopic Images with Exemplar-based Method

Cervical cancer is the most common genital malignant tumor which seriously threats to women's health, especially in poor areas. As one of the screening methods for cervical lesions, colposcopy plays an important role in the early stage of cervical lesions. However, due to the physiological mucus in the human body, the specular reflection region (SR region) is often shown in a high-definition image obtained by doctors through a colposcopy. The expression of the highlight area in the colposcopic image has a certain similarity with the abnormal metaplasia epithelium (AW area, i.e. the lesion area), which leads to a series of problems in the medical image processing in the later stage, such as the segmentation of the lesion area, misdiagnosis by doctors, etc. Therefore, this paper proposed the exemplar-based inpainting method combining with the improved threshold method to detect the SR regions. In the experiment, 150 sets of data (50 pieces for different degrees of cervical lesions) were inpainted by this paper and the other two existing inpainting methods, and the results were compared with subjective and objective quality. The experiment showed that the exemplar-based method has better effect in removing the specular reflection in cervical images.
PENGUJIAN USABILITY WEBSITE TIME EXCELINDO MENGGUNAKAN SYSTEM USABILITY SCALE (SUS) (sTUDI KASUS: WEBSITE TIME EXCELINDO)

Usability testing of Time Excelindo website using System Usability Scale (SUS) is an action research with purpose to measure usability scale of Time Excelindo website.Based on the results of the test conducted will be analyzed further to produce website improvement recomendations to improve website usability.The test will be conducted using SUS questionaire that consists of 10 statements and Likert scale for the answer.There is two stages testing, firstly with the use of SUS questionaire to measure website usability.The results then being analyzed to produce improvement recomendations.Secondly using SUS questionaire that have been tampered with by adding recomendations into questionaire statements.Conclusions obtained from this research is the fact that Time Excelindo website already have acceptable usability.But by implementing improvement recomendations, will further improve website usability.
Bangla Sign Language Conversation Interpreter Using Image Processing

This project about sign language conversation interpreter system. It is made for speak disable people. Here a man who don’t know the sign language can make conversation with a speak disable people. In this project we used efficient methods to convert sign language into text. We used our own dataset and collected dataset of Bangla Sign Languages using hand gestures. Inputs will be taken by webcam and recognized by neural network system. System will show text output by using gestures. We have created a CNN which is similar model of the MNIST classifying model. It can use both Tensorflow and Keras. This model was trained using Keras by video streaming. In a video stream sign language, interpreter can turn it fast into text. We used histogram back projection method to recognize people’s hand as object. For better result we calculated the grey level of hands.
Separability discrimination and decomposition of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>m</mml:mi></mml:math> -partite quantum mixed states

We propose an $E$-truncated $K$-moment and semidefinite relaxations (ETKM-SDR) method to check whether an $m$-partite quantum mixed state is separable and give a decomposition for it if it is. We first convert the separability discrimination problem of mixed states to the positive Hermitian decomposition problem of Hermitian tensors. Then, employing the $E$-truncated $K$-moment method, we obtain an optimization model for discriminating separability. Moreover, by applying the semidefinite relaxation method, we get a hierarchy of semidefinite relaxation optimization models and propose an algorithm for detecting the separability of mixed states. The algorithm can also be used for symmetric and nonsymmetric decomposition of separable mixed states. By numerical examples, we find that not all symmetric separable states have symmetric decompositions.
Path Planning for Autonomous Underwater Vehicle in Presence of Moving Obstacle Based on Three Inputs Fuzzy Logic

This paper concentrated on the path planning for autonomous underwater vehicle (AUV) to avoid collisions with the moving obstacles. Considering the influence of moving speed of the obstacles on control effect, a 3-inputs fuzzy controller is designed, in which the change of the distance between the AUV and the obstacle is taken as one of the inputs. Simulation results show that the controller can avoid the slow moving obstacles in the same direction in front of the AUV, and also successfully avoid the obstacles moving towards the AUV. And it also shows that when the obstacle moves faster, the 3-inputs controller is obviously more effective than the commonly used 2-inputs controller.
Automatic Classification of Benign and Malignant Breast Tumors in Ultrasound Image with Texture and Morphological Features

Breast cancer has become one of the malignant tumors with the highest morbidity and mortality among women in the world, which seriously threatens women's health. Because the cause of breast cancer is unknown, early detection, early diagnosis and early treatment are the key to improve the cure rate of breast cancer. Computer aided diagnosis (CAD) system is a valuable assistant method for automatic detection and classification of breast cancer. In this paper, the morphological and texture features of ultrasonic images of breast tumors are extracted to train SVM classifier, so as to realize automatic classification of tumors. Of the 1061 newly collected breast ultrasound images, 589 were malignant and 472 were benign. Finally, features combined with texture and morphological get the best performance and the overall accuracy reaches 87.32%. The results show that this method has a good generalization ability and can be used as an assistant method for the classification of benign and malignant breast cancer.
Learning structured communication for multi-agent reinforcement learning

This work explores the large-scale multi-agent communication mechanism for multi-agent reinforcement learning (MARL). We summarize the general topology categories for communication structures, which are often manually specified in MARL literature. A novel framework termed Learning Structured Communication (LSC) is proposed by learning a flexible and efficient communication topology (hierarchical structure). It contains two modules: structured communication module and communication-based policy module. The structured communication module learns to form a hierarchical structure by maximizing the cumulative reward of the agents under the current communication-based policy. The communication-based policy module adopts hierarchical graph neural networks to generate messages, propagate information based on the learned communication structure, and select actions. In contrast to existing communication mechanisms, our method has a learnable and hierarchical communication structure. Experiments on large-scale battle scenarios show that the proposed LSC has high communication efficiency and global cooperation capability.
E-Books Preference Compared to Print Books Based on Student Perceptions: A Case of University of Fort Hare Students

&lt;p class="0abstract"&gt;Technology advent has been transforming students’ perceptions and preferences mostly on how they acquire information and learn. The way students perceive e-books and print books significantly influences the format they prefer to use for academic purposes. Recently, the accessibility of e-books on assorted mobile gadgets is substituting the conventional print based resources which are regarded costly in production, sharing and also heavy. Differing views on the format (e-book or print) that students prefer for academic purposes to improve their educational experience exist of which most studies have been done in developed countries. Therefore, a research that reveals students’ perceptions and preferences towards the two book formats in the nation of South Africa can afford a better understanding and conclusion on an African student. This study aimed to determine students’ preference on using e-books and print books in meeting academic information needs based on perceptions. The study adopted a cross-sectional research design and a questionnaire as a research instrument which was administered to students at the University of Fort Hare. Findings revealed that students preferred using both (e-books and print books) for their academic needs. Moreover, they perceived e-books to be as good as print books, easy and friendly to use and capable of providing sufficient information to meet educational needs.&lt;/p&gt;&lt;p class="0keywords"&gt; &lt;/p&gt;