Reviewerly/exHarmony huggingface dataset:
SESAME: Software defined Enclaves to Secure Inference Accelerators with Multi-tenant Execution

Hardware-enclaves that target complex CPU designs compromise both security and performance. Programs have little control over micro-architecture, which leads to side-channel leaks, and then have to be transformed to have worst-case control- and data-flow behaviors and thus incur considerable slowdown. We propose to address these security and performance problems by bringing enclaves into the realm of accelerator-rich architectures. The key idea is to construct software-defined enclaves (SDEs) where the protections and slowdown are tied to an application-defined threat model and tuned by a compiler for the accelerator's specific domain. This vertically integrated approach requires new hardware data-structures to partition, clear, and shape the utilization of hardware resources; and a compiler that instantiates and schedules these data-structures to create multi-tenant enclaves on accelerators. We demonstrate our ideas with a comprehensive prototype -- Sesame -- that includes modifications to compiler, ISA, and microarchitecture to a decoupled access execute (DAE) accelerator framework for deep learning models. Our security evaluation shows that classifiers that could distinguish different layers in VGG, ResNet, and AlexNet, fail to do so when run using Sesame. Our synthesizable hardware prototype (on a Xilinx Pynq board) demonstrates how the compiler and micro-architecture enables threat-model-specific trade-offs in code size increase ranging from 3-7 $\%$ and run-time performance overhead for specific defenses ranging from 3.96$\%$ to 34.87$\%$ (across confidential inputs and models and single vs. multi-tenant systems).
Particle Swarm Optimization for Solving Medical Image Reconstruction Ill-conditioned Problems

Abstract Particle swarm algorithm applies to the field of computer neural networks a lot. In this paper, the medical image is used as an example to realize the modeling process based on the particle swarm algorithm. For the modeling and simulation analysis of medical images, the geometric model accuracy and physical model accuracy need to be solved. The mobile cube (MC) algorithm is used for surface reconstruction. At the same time, the quadratic error measurement (QEM) method is used to reduce and smooth the triangular patch. The Delaunay method is used to deduce the volume mesh model based on the surface mesh. and finally, the corresponding physical model is selected according to the target organization to use the finite element (FEM) method for analysis, and uses OpenGL to display the cloud chart of the equivalent stress. The analysis results show that the function and metabolism of human tissues and organs can be more accurately understood through the reconstruction of SPECT medical images.
Generating Recursive Sequence in Image Encryption using a New Method based on the Genetic Algorithm

Objective: To present a new method for generating a recursive sequence in image encryption using the genetic algorithm. Methods: In order to accomplish these goals in this study, the coefficients of the recurrence relation are calculated by the genetic algorithm taking into account a generic form for the recurrence relation and the definition of a proper fitness function, so that the resulting sequence has the optimal efficiency for image encryption. Findings: With the implementation of the algorithm, the results obtained from values UACI, NPCR, MAE, the fitness function, and Correlation, it is seen that the proposed method in this paper is more effective than old methods. Application: In order to achieve these results, at each stage of the implementation of the genetic algorithm, using a chromosome gene, a 2D time sequence is generated, and this sequence is used to scramble the image. Keywords: Chromosome Gene, Genetic Algorithm, Image Encryption, Recursive Sequence, 2D Time Sequence
Reconfiguração da formação de professores em tempos excecionais - COVID19

In extraordinary and exceptional times - COVID19 - teachers are invited to teach in entirely new learning and teaching environments with totally digital outlines, using resources that challenge their professional teaching practice at all intervention educational stages. A new challenge emerges - to implement a structured educational action based on something new - resulting from the impossibility of mobilizing the devices and mental structures of classroom teaching. Since March 16, 2020, Portuguese educational institutions were forced to replace face-to-face activities for distance activities, interrupting all regular classes, as well as internships. In this text, we will describe how, at the current and unique international educational context, a Portuguese higher education institution proceeded to reconfigure Initiation to Professional Practice activities in a teacher training course.
Chinese Learner Feature Classification Based on IFE Attribute Weighted kNN Algorithm

With the continuous improvement of China's comprehensive national strength and international influence, the “Chinese fever” has swept the world. Against this background, the “Chinese Bridge” world competition came into being. Taking the data of the Chinese world middle school students in the “Chinese Bridge” for example in the last five years, by analyzing the contestants' answers and making them a representative object for Chinese learners in this area, in this paper, the classification method of Chinese learners based on the improved K-Neighbor Algorithm has been put forward, combined to the theory of internal factor evaluation matrix, to achieve the accurate classification of “Chinese bridge” learners. Our works will provide a support for the “Chinese Bridge” world Chinese learners to carry out personalized precision recommendations.
A Study on the Establishment and Operation of National Education Committee: the Delphi Survey

이 연구는 가칭 국가교육위원회의 설치를 중심으로 하는 중앙교육행정체제 개편에 대해 전문가의 의견을 모아 개편의 필요성과 방향을 확인함과 함께 주요 쟁점에 대한 최적의 대안을 모색하고자 수행되었다. 이를 위하여 관련 연구 수행자 등을 중심으로 30명의 패널을 구성한 후 3차례의 델파이 조사를 실시하였다. 그 결과는 다음과 같다. 첫째, 교육부와 별도의 국가교육위원회 설치를 중심으로 하는 현행 중앙교육행정체제의 개편이 필요함에 합의가 이루어졌으며, 그 이유는 정책의 일관성·안정성 확보, 행정 중심의 과도한 관료주의 극복, 교육의 자주성·정치적 중립성 확보, 대학의 자율성 보장, 교육갈등 관리 기제 필요, 행정의 비민주성 제거로 의견이 모아졌다. 둘째, 국가교육위원회의는 법률상 독립 기구의 법적 지위를 갖도록 하되, 교육부는 현재와 같이 행정각부의 하나로 유지하는 방안에 가장 많은 전문가의 의견이 모였다. 셋째, 국가교육위원회의 주요 기능과 관련하여 종합적·장기적 국가 교육계획 수립, 주요 교육 관계 법률의 제안, 교육분야 갈등 조정, 주요 교육정책의 수립 및 조정, 주요 교육정책의 모니터링 및 평가는 합의가 이루어졌으며, 교육재정 및 교육예산 심의의 경우 합의되지는 못하였지만 많은 전문가의 지지를 받았다. 넷째, 국가교육위원회의 구성은 교육 전문성과 사회적 대표성을 함께 고려하는 절충식의 관점에서 이루어져야 한다는 것과 위원 수는 15인으로 함에 의견이 모아졌다. 다섯째, 하위 분과위원회로 유·초·중등교육위원회, 고등교육위원회, 평생·직업교육위원회를 설치하는 데 합의를 이루었다. 끝으로 국가교육위원회 설치와 관련된 우려도 확인할 수 있었는바, 신중하고 정교한 설계와 함께 특히, 교육행정권한의 지방 및 대학으로의 이양 지연 그리고, 입법부와 사법부의 교육에 대한 기능 축소가 나타나지 않도록 하여야 함을 제안하였다.The purpose of this study is to identify the needs and directions of launching the National Education Commission, as well as seek optimal solutions to key issues. For this purpose, a Delphi survey was conducted on 30 experts. The results of this study are as follows:First of all, it has been confirmed that there is a consensus on the need to set up the National Education Commission, separately from Ministry of Education, and the reasons are securing consistency and stability in policies, overcoming administrative-centered bureaucracy, securing independence and political neutrality in education, ensuring autonomy of universities, the need to manage educational conflicts, and eliminating non-democracies in administration. Second, experts agreed that the National Education Commission should be granted legal status as an independent body by law, while the Ministry of Education is maintain its current status. Third, with regard to the main functions of the National Education Commission, the consensus was reached on the establishment of comprehensive and long-term national education plans, proposals for major education-related laws, coordination of conflicts in the education sector, establishment and coordination of major education policies, and monitoring and evaluation of major education policies. Fourth, the formation of the National Education Commission should be made from a compromise perspective that takes into account both education expertise and social representation. Fifth, an agreement was reached on the establishment of the kindergarten, Elementary and Secondary Education Committee, Higher Education Committee, and Lifelong and Vocational Education Committee as sub-committees. Finally, it proposed that the installation of the National Education Commission should be carefully designed so that problems such as the delay of the transfer of educational administrative authority to local and university, and the reduction of functions of the legislature and judiciary for education would not arise.
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Evaluation of the Quality of Service Muasalat Oman Company

Public transportation is one of the significant contributor towards the economic growth and development of a country as it facilitates the movement of people, labour, products and services and raw materials among others. With the increasing competition and options in the public transportation sector, the customers have become highly demands and expect to be served better by the companies. There are many factors affecting the customer perception and the customer satisfaction level considering the public transportation including the quality of the buses, timing and punctuality of the business. The aim of this research is to examine the degree of service quality and customer satisfaction in the transport service industry in Oman, a case on Mwasalat Bus Way Company. The data was collected via the questionnaire distributed among the medium among the travelers. The data collected has been transformed into numerical format for ease of analysis using the SPSS software 23. The researcher has relied on the software for conducting the reliability test, frequency distribution test, cross tabulation and correlation analysis for assessing the potential relationship between different variables of the study. The research finding has indicated that through Urban transportation sector in Oman is focused on offering high quality service to the customers, there is need for the sector to offer additional benefits to reflect their adoption of market trends as in the free Wi-Fi access while travelling, electronic devices charging points and the latest means of payments like over the phone among others.
South Indian Recipe Recommendation from Ingredient Image

Applications involving ingredient recognition are very limited and most do not work in less ideal conditions like the ones faced in a typical kitchen.The main reason for this is the dataset that the existing models are based on.These datasets do not account for real-world factors like noise, blur, etc. in the input image since they are trained on images obtained from controlled and nearly idealistic environments.For these reasons, a new dataset was created, consisting of real-world images which represent the scenarios users are most likely to face during daily use.A simple and robust system was developed that aims to address this issue.A multi-label classification model was built to identify multiple ingredients present in a single image.A personalized recommendation system that recommends a list of South Indian recipes to users based on the ingredients identified was also developed.
Internal variability of surface solar radiation and associated PV production

&amp;lt;p&amp;gt;Results on the statistical properties of internal variability of annual mean surface solar radiation (SSR) and associated decadal scale trends are presented, following in part Folini et al. 2017 (doi:10.1002/2016JD025869). Estimates are based on 43 pre-industrial control (piControl) experiments of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Trends are shown to depend strongly on geographical region and on whether they are quantified in absolute units or relative to the long term mean SSR. Providing one map for absolute and one map for relative trends is sufficient, as approximate analytical relations are shown to hold between trends of different length and likelihood and the standard deviation of the underlying SSR time series. Comparison with present-day observations and inter-model spread suggest an average uncertainty of these estimates of about 30%. &amp;amp;#160;Intermodel spread suggests that regional uncertainties can be up to about three times larger or smaller. Using the model by Crook et al. 2011 (doi:10.1039/C1EE01495A) to translate SSR into PV production, associated internal variability of photo voltaic (PV) energy production is inferred. Results suggest that it is plausible for PV production to change by several per cent over a decade just because of internal variability.&amp;lt;/p&amp;gt;
Social Adaptive Module for Weakly-supervised Group Activity Recognition

This paper presents a new task named weakly-supervised group activity recognition (GAR) which differs from conventional GAR tasks in that only video-level labels are available, yet the important persons within each frame are not provided even in the training data. This eases us to collect and annotate a large-scale NBA dataset and thus raise new challenges to GAR. To mine useful information from weak supervision, we present a key insight that key instances are likely to be related to each other, and thus design a social adaptive module (SAM) to reason about key persons and frames from noisy data. Experiments show significant improvement on the NBA dataset as well as the popular volleyball dataset. In particular, our model trained on video-level annotation achieves comparable accuracy to prior algorithms which required strong labels.
Multi-robot Cooperative Object Transportation using Decentralized Deep Reinforcement Learning

Object transportation could be a challenging problem for a single robot due to the oversize and/or overweight issues. A multi-robot system can take the advantage of increased driving power and more flexible configuration to solve such a problem. However, increased number of individuals also changed the dynamics of the system which makes control of a multi-robot system more complicated. Even worse, if the whole system is sitting on a centralized decision making unit, the data flow could be easily overloaded due to the upscaling of the system. In this research, we propose a decentralized control scheme on a multi-robot system with each individual equipped with a deep Q-network (DQN) controller to perform an oversized object transportation task. DQN is a deep reinforcement learning algorithm thus does not require the knowledge of system dynamics, instead, it enables the robots to learn appropriate control strategies through trial-and-error style interactions within the task environment. Since analogous controllers are distributed on the individuals, the computational bottleneck is avoided systematically. We demonstrate such a system in a scenario of carrying an oversized rod through a doorway by a two-robot team. The presented multi-robot system learns abstract features of the task and cooperative behaviors are observed. The decentralized DQN-style controller is showing strong robustness against uncertainties. In addition, We propose a universal metric to assess the cooperation quantitatively.
Geodetic inversion of complex fault geometries for strong earthquakes

&amp;lt;p&amp;gt;The fault geometry closely controls earthquake rupture process. Previous seismic inversion of the fault geometry is to derive the multiple-point moment tensor solutions. Because of the trade-off between the moment tensor and rupture velocity, the inversion has high instabilities. In contrast, geodetic inversion has less unknowns, since there is no need to solve for rupture velocity. But from the elastic dislocation theory, the relations between the surface deformation and sub-fault parameters (i.e. strike, dip and rake) are nonlinear. In this study, we develop a linear technique to invert geodetic data for sub-fault moment tensors. From the sub-fault moment tensor solutions, the strike, dip, rake, and their spatial variations can be estimated, which provide valuable information for assessing the complexities in fault geometry. We applied this technique to several significant earthquakes, i.e., the 2008 Mw7.9 Wenchuan earthquake, the 2015 Mw7.8 Gorkha earthquake, and the 2017 Mw6.5 Jiuzhaigou earthquake. The results of the 2008 Wenchuan earthquake suggest that the strike, dip and rake are all variable from southwest to northeast, which are well consistent with the aftershock distributions and mechanisms. The dip variations of the 2015 Gorkha earthquake suggest the earthquake has ruptured a listric fault (dep decreases with depth). Particularly, a dip anomaly appears in the northeast corner of the rupture area, indicating a geometric barrier accounting for the slip gap between the mainshock and largest Mw7.3 aftershock. For the 2017 Jiuzhaigou earthquake, two right-stepping and left-lateral strike-slip segments were distinguished. Accordingly, a compressional step-over was identified between the two segments.&amp;lt;/p&amp;gt;
La difesa della morale come giustificazione di limitazioni al rispetto della vita privata, nella giurisprudenza della Corte europea dei diritti umani

The Author describes how the European Convention authorizes limits to rights and liberties, in particular by mentioning the protection of morals in article 8, the logic and problems of the margin of national appreciation and of the European consensus, with at the end the awkward recognition by the Court of the conclusive role of the majorities in the countries.
Randomized Algorithms for Some Sequence Clustering Problems

We consider two problems of clustering a finite sequence of points in Euclidean space. In the first problem, we need to find a cluster minimizing intracluster sum of squared distances from cluster elements to its centroid. In the second problem, we need to partition a sequence into two clusters minimizing cardinality-weighted intracluster sums of squared distances from clusters elements to their centers; the center of the first cluster is its centroid, while the center of the second one is the origin. Moreover, in the first problem, the difference between any two subsequent indices of cluster elements is bounded above and below by some constants. In the second problem, the same constraint is imposed on the cluster with unknown centroid. We present randomized algorithms for both problems and find the conditions under which these algorithms are polynomial and asymptotically exact.
A Novel Approach for Stutter Speech Recognition and Correction

Stuttering also called as Stammering is a speech disorder where a person suffering from this disorder repeats or prolongs words, syllables or phrases. He/ She may also stop during speech and make no sound for certain syllables. Current speech recognition systems such as Google Assistant, Apple's Siri etc have very efficient Speech recognition system for normal speech, but they fail to recognise when the person stutters. This paper proposes a system to detect as well as remove stutter from speech by using Speech-to-text Conversion method. This system is implemented in five stages namely, Amplitude thresholding and filtering, Silence ejection, speech to text conversion, repetition removal and text to speech (TTS) conversion.
El telèfon mòbil: Dimensió i recurs educatiu. Treballar amb imatges en el context de les arts visuals.

This text is part of the doctoral thesis ICT in the university teacher education. The mobile phone in the Teaching of Artistic Expression at the Faculty of Pedagogy at the Universitat de València (2017a). It offers a many-faceted view of the mobile phone – its dimension, evolution, social and historical function – and explores the opportunities that this device brings in an educational and artistic context through Mobile Learning. From the perspective of the Visual Arts, our interest lies in working through images and offering alternative work proposals. The theory related to Mobile Learning is presented, underlining the benefits that mobile and ubiquitous learning can represent today. The teaching opportunities that we must promote in the classrooms of the 21st century are assessed in terms of their relevance and appropriateness in the social and technological reality that surrounds us.
Measuring Progress and Performance in Global Engineering

MeasurementEngineering and feedbackFeedback are increasingly being incorporated into global engineeringEngineering and developmentDevelopment financing and programming. Within this ecosystem, there is room to incorporate near-time measurement of program, productProduct, and service performance, and feed these measures back to responsible parties in a way that enables iterative testing and improvement. This chapter presents a history of feedbackFeedback approaches, and reviews case studies in using instrumentationInstrumentation to support improved global developmentDevelopment program deployments.
Generation of Ripple Images by Smoothing Filters Using Different Regions

We propose a non-photorealistic rendering method for generating ripple images from gray-scale photographic images. Ripple images represent photographic images with wavy lines in a certain direction. Our method is executed by an iterative process with two smoothing filers using different regions in the window. Our method has two features. The first feature is that ripple patterns can be automatically generated according to the density and contour of photographic images. The second feature is that the interval and direction of ripple patterns can be changed by changing the values of the parameters of our method. In order to verify the effectiveness of our method, we conducted experiments using various photographic images. Experimental results show that our method can realize the two features.
Appearance-Preserving 3D Convolution for Video-based Person Re-identification

Due to the imperfect person detection results and posture changes, temporal appearance misalignment is unavoidable in video-based person re-identification (ReID). In this case, 3D convolution may destroy the appearance representation of person video clips, thus it is harmful to ReID. To address this problem, we propose AppearancePreserving 3D Convolution (AP3D), which is composed of two components: an Appearance-Preserving Module (APM) and a 3D convolution kernel. With APM aligning the adjacent feature maps in pixel level, the following 3D convolution can model temporal information on the premise of maintaining the appearance representation quality. It is easy to combine AP3D with existing 3D ConvNets by simply replacing the original 3D convolution kernels with AP3Ds. Extensive experiments demonstrate the effectiveness of AP3D for video-based ReID and the results on three widely used datasets surpass the state-of-the-arts. Code is available at: https://github.com/guxinqian/AP3D.