Reviewerly/exHarmony huggingface dataset:
Exploring a Unified Sequence-To-Sequence Transformer for Medical Product Safety Monitoring in Social Media

Adverse Events (AE) are harmful events resulting from the use of medical products. Although social media may be crucial for early AE detection, the sheer scale of this data makes it logistically intractable to analyze using human agents, with NLP representing the only low-cost and scalable alternative. In this paper, we frame AE Detection and Extraction as a sequence-to-sequence problem using the T5 model architecture and achieve strong performance improvements over competitive baselines on several English benchmarks (F1 = 0.71, 12.7% relative improvement for AE Detection; Strict F1 = 0.713, 12.4% relative improvement for AE Extraction). Motivated by the strong commonalities between AE-related tasks, the class imbalance in AE benchmarks and the linguistic and structural variety typical of social media posts, we propose a new strategy for multi-task training that accounts, at the same time, for task and dataset characteristics. Our multi-task approach increases model robustness, leading to further performance gains. Finally, our framework shows some language transfer capabilities, obtaining higher performance than Multilingual BERT in zero-shot learning on French data.
Analysis of Employment Status and Countermeasures of Biology Graduates in Local Normal Universities Based on Big Data Technology—Take the Graduates of Guangxi Normal University From 20l6 to 2020 as an Example

The data of annual reports on the employment quality f local normal universities from 2016 to 2020 were captured from the network with the help of information technology. The data related to basic situation and employment destination of biology graduates in Guangxi Normal University were analyzed and collected by data analytic technology such as Data Mining Algorithms, Data Quality Master Data Management and Predictive Analytic Capabilities. In view of the problems of single employment structure, insufficient employment skills, vague employment planning and low achievement of Innovation and Entrepreneurship, measures such as the employment policy interpretation, the talent training programs adjustment, the employment guidance services system improvement and teaching mode innovation are needed in the purpose of promoting employment, providing useful reference to the further progress of teaching reform and optimizing talent training modes and methods for graduates of biology.
Food Budget of Inmates and Their Body Mass Index

This study aimed to evaluate the food budget allowance of inmates in Dapitan and Dipolog City jail and determine the inmates body mass index as one of the indicators in assessing the nutrition of person whether he/she is malnourished or not. The study employed a mix of quantitative and qualitative approaches in carrying out the results of the study. Quantitative method was used to describe the inmate’s profile as to age, gender, number of years in jail, types of food served and body mass index. While qualitative method was used to determine the budget allocation of inmates and medical records of inmates. An information sheet was created and distributed to the inmates who were the primary respondents in order to gather quantitative data. In addition, unstructured interview was also conducted to the warden during site visit. Random sampling method was used. Descriptive statistics were used in presenting, analyzing and interpreting the data of the study. Most of the inmates incarcerated are within the age ranging from 42-51 years old, while most of the inmates are incarcerated for a period ranging from 2 to 4 years. There are very few inmates with medical history like ulcer, diabetes, mayoma and high blood. Beef or pork tinola with sayote and rice is the commonly meals serve to the inmates. Majority of the inmates are within normal weight. Monitoring of those inmates with medical history to prevent from any possible complications.
A Digital Twin of Intensive Aquabiotechnological Production Based on a Closed Ecosystem Modeling &amp; Simulation

Currently, intensive fish farming using closed water circulation technology is becoming one of the breakthrough technologies in the aquaculture production. Digital transformation for such production is necessary for the effective management of ultra-high-density aquaculture farms. This transformation is based on the digital twin of aqua-biotechnological farms. The authors performed digital modeling & simulation of the biotechnological component of intensive aqua farm. The main equations of the model are presented in the article. Models of lungfish and trout ecosystems are considered. The models were tested as part of the digital twin for the real aqua farm. The qualitative coincidence of the results of modeling & simulation with the behavior of the ecosystem is obtained. The model has not yet achieved sufficient accuracy for commercial use. The reasons for the insufficient accuracy of the simulation are discussed. Some variants of the simulation model’s development for simple closed aquatic ecosystems with a large biological load are considered. It is concluded that it is necessary to integrate a digital twin based on a simulation model of a biosystem with the technology of the Industrial Internet of Things to achieve the necessary accuracy of describing a complex engineering and biotechnological system.
LibGuides: Course Clearances For Instructors: Permissions

Navigate copyright requirements related to the use of resources in online and campus classrooms
Realistic PointGoal Navigation via Auxiliary Losses and Information Bottleneck

We propose a novel architecture and training paradigm for training realistic PointGoal Navigation -- navigating to a target coordinate in an unseen environment under actuation and sensor noise without access to ground-truth localization. Specifically, we find that the primary challenge under this setting is learning localization -- when stripped of idealized localization, agents fail to stop precisely at the goal despite reliably making progress towards it. To address this we introduce a set of auxiliary losses to help the agent learn localization. Further, we explore the idea of treating the precise location of the agent as privileged information -- it is unavailable during test time, however, it is available during training time in simulation. We grant the agent restricted access to ground-truth localization readings during training via an information bottleneck. Under this setting, the agent incurs a penalty for using this privileged information, encouraging the agent to only leverage this information when it is crucial to learning. This enables the agent to first learn navigation and then learn localization instead of conflating these two objectives in training. We evaluate our proposed method both in a semi-idealized (noiseless simulation without Compass+GPS) and realistic (addition of noisy simulation) settings. Specifically, our method outperforms existing baselines on the semi-idealized setting by 18\%/21\% SPL/Success and by 15\%/20\% SPL in the realistic setting. Our improved Success and SPL metrics indicate our agent's improved ability to accurately self-localize while maintaining a strong navigation policy. Our implementation can be found at https://github.com/NicoGrande/habitat-pointnav-via-ib.
The problem of student dropout in modern higher education

Analyzed is contingent of potential candidates for dropping out of university because of academic failure has never been the object of special methodical consideration. The technology of overcoming low academic performance of this category of students through the formation of professional-educational subjective position of students has been developed. It is based on the collective personification of the learning process, self-study of students, thematic cluster training.
Image Deraining Convolutional Neural Network ForAutonomous Driving

Perception plays an important role in reliable decision-making for autonomous vehicles. Over the last ten years, huge advances have been made in the field of perception. However, perception in extreme weather conditions is still a difficult problem, especially in rainy weather conditions. In order to improve the detection effect of road targets in rainy environments, we analyze the physical characteristics of the rain layer and propose a deraining convolutional neural network structure. Based on this network structure, we design an ablation experiment and experiment results show that our method can effectively improve the accuracy of object detection in rainy conditions.
Balance Training for Anchor-Free Face Detection

Large-scale variations on face detection make the performance of the model hard to improve. In this paper, we propose a novel balance training method for anchor-free face detection. Firstly, we propose a data augmentation called crop-mosaic to provide scale continuous, balance and controllable Gtboxes. Secondly, we design a density balance scale assignment strategy to divide the scale matching range for different scale faces. Thirdly, we introduce a scale normalization loss for comparing training performance with each levels. The proposed methods are implemented on Caffe. Extensive experiments on popular benchmarks WIDER FACE demonstrate that the performance of model training based on Mobilenet-v1 is close to the state-of-the-art face detectors.
The NiuTrans Machine Translation Systems for WMT21

This paper describes NiuTrans neural machine translation systems of the WMT 2021 news translation tasks. We made submissions to 9 language directions, including English$\leftrightarrow$$\{$Chinese, Japanese, Russian, Icelandic$\}$ and English$\rightarrow$Hausa tasks. Our primary systems are built on several effective variants of Transformer, e.g., Transformer-DLCL, ODE-Transformer. We also utilize back-translation, knowledge distillation, post-ensemble, and iterative fine-tuning techniques to enhance the model performance further.
A novel Shape Feature Extraction Technique for Content-Based Image Retrieval (CBIR) Systems

Content-Based Image Retrieval is regularly developing examination topic into the subject in regards to pc innovative and farsighted because of the reality its appropriateness inside different utility areas. This article gives form essentially based structure descriptor for CBIR frameworks. The essential advances concerned are image preprocessing, point division, shape trademark extraction or closeness estimation. The development 3 stages are normal in view of on line (question image) and disconnected (dataset image) handling. The picture preprocessing base performs photograph resizing, zero cushioning, gaps expulsion, at that point labyrinth evacuation. The perspective comparable division calculation is back incongruity with concentrate target confine pixels. The component extraction footsie performs rise to scale standardization (EDN) and even place standardization (EAN). The components present by utilizing EDN are utilized so notice file point since the sum region list focuses calculation. In EAN the form focuses are gotten through getting the triangle inside two abutting purposes of shape or centroid. The proposed work performs EAN by utilizing applying region about the fragment procedure as a substitute of the region on the triangle technique, at that point that does not lose shape measurements at someone cost. It is more noteworthy right as per standardize the form focuses in light of the fact that understanding measure. Closeness among inquiry picture yet dataset pictures are looked at the use of Euclidean separation. The general execution concerning proposed work is contrasted and territory about the triangle standardization technique for MPEG-7 CE Shape-1 Part-B dataset. From the empiric outcomes, we finish that standardization based concerning place about the area is additional precise.
Development of the fundamentals of educational activity among primary school students in the Russian language classes

This article provides an example of arranging functional educational activity in the Russian language classes within the framework of general primary education; describes the stage-by-stage structure of one of the object topics in the Russian language course, considering all components of educational activity from outlining the academic pursuit to monitoring and assessing performance; lists the techniques and examples of the tasks used in the development of control materials based on the formation of metadisciplinary competencies among primary school students; gives partial description to the monitoring and assessment toolset based on inclusion into the educational process. The article characterizes assessment as a means of ensuring the quality of modern education, which implies engagement of both pedagogues and students into assessing the performance. The system of the criterion-based comprehensive assessment, formation of the skills of reflection, introspection, self-control, self-and mutual assessment help the students to develop the effective techniques of managing their educational activity, promote self-awareness, readiness to openly express and defend their position, independent actions, responsibility for their results. The systematic, targeted formation of assessment skills allow the primary school students are to detect the difficulties they face, analyze their causes, plan and implement corrective measures to overcome them.
Use of the Google Drive Platform By University Students

This paper presents the level of post-use of the Google Drive platform in academic and personal activities in university students. A descriptive research was carried out on students who attended the TICs between the semesters March–August 2013 and April–August 2016 at the School of Public Health of the Politecnica Superior School of Chimborazo, through the application of an online questionnaire. With 87 valid responses, 62.1% use the platform in personal activities, 88.5% use files and folders, the most used tool is 62.1%, while 65.5% Synchronized your smart phone with Google Drive. Students who participated in the study continue to use Google Drive in their academic and personal activities.&#x0D; Keyword: collaborative work, cloud computing, mobile devices, Google Drive.&#x0D; RESUMEN&#x0D; Este trabajo presenta el nivel de pos-utilización de la plataforma Google Drive en actividades académicas y personales en estudiantes universitarios. Se desarrolló una investigación de tipo descriptivo en estudiantes que cursaron las cátedras TICs entre los semestres Marzo–Agosto 2013 y Abril–Agosto 2016 en la Facultad de Salud Pública de la Escuela Superior Politécnica de Chimborazo, mediante la aplicación de un cuestionario en linea. Con 87 respuestas válidas, el 62,1% utiliza la plataforma en actividades personales, el 88,5% utiliza para compartir archivos y carpetas, la herramienta más utilizada es el formulario con el 62,1%, mientras que el 65,5% tiene sincronizado su celular inteligente con Google Drive. Los estudiantes que participaron en el estudio continuan utilizando Google Drive en sus actividades académicas y personales.&#x0D; Palabras claves: trabajo colaborativo, computación en la nube, dispositivos móviles, Google Drive.
Comparison of Serial and Parallel Computation on Predicting Missing Data with EM Algorithm

One way to deal with the presence of missing value or incomplete data is to impute the data using EM Algorithm. The need for large and fast data processing is necessary to implement parallel computing on EM algorithm serial program. In the parallel program architecture of EM Algorithm in this study, the controller is only related to the EM module whereas the EM module itself uses matrix and vector modules intensively. Parallelization is done by using OpenMP in EM modules which results in faster compute time on parallel programs than serial programs. Parallel computing with a thread of 4 (four) increases speed up, reduces compute time, and reduces efficiency when compared to parallel computing by the number of threads 2 (two).
The Humble Creative Machine

In this paper, we present a fresh perspective at co- creativity - using human development as a blueprint, we argue that fostering human creativity is a natural evolu- tion of creative machines. We introduce the notion of a “humble” creative machine - one that is less concerned with demonstrating its own independence, and instead uses its (potentially advanced) creative abilities to cul- tivate human creativity. We present characteristics of Humble Creative Machines and offer examples of ex- isting (almost) humble machines.
Sketch Photosynthesis and Classification using K Nearest Neighbor Classifier

Sketch-photosynthesis approach is sketching the face of the photograph. Sketch-photosynthesis makes use of a strategy of equivalent composite comic strip with photograph. The capabilities are separated and combined to teach the system. In this paper caricature photosynthesis using K-means and Knearest neighbor classifier is used to sketch the photograph. The K-means algorithm in data mining starts from the primary organization of randomly decided on centroids. It is practiced as the starting point for every cluster because it plays iterative calculations to optimize the positions of the centroids.
Criptoactivos negociables y fichas de servicio (tokens no monetarios) en la propuesta de reglamento europeo de mercados distribuidos o blockchain

espanolEl nuevo regimen de la Propuesta europea de Reglamento sobre mercados de criptoactivos (Reglamento MiCA), disciplina los tokens o fichas de inversion semejantes a valores negociables en mercados estructurados conforme a la tecnologia de registro distribuido (TRD) y en particular de la cadena de bloques (blockchain), al tiempo que deja margen para la negociacion de algunos criptoactivos en mercados organizados y supervisados del modo clasico, conforme al regimen MiFID 2 y MiFIR, creando una dualidad regulatoria. Por otra parte, la Propuesta tambien regula otros tokens o fichas como las de servicio, cuyo analisis presenta extraordinario interes desde la optica tanto de la regulacion publica financiera como del Derecho privado; analisis que esboza el presente trabajo, junto con un apunte sobre la prestacion de servicios de inversion en criptoactivos y una presentacion general de la teleologia y politica regulatoria de la digitalizacion financiera en Europea, desde la doble perspectiva de la industria DLT y de la politica legislativa de ABE y la AEMV. EnglishThe new EU Proposal for a Regulation on crypto-asset markets (MiCA Regulation) sets a legal regime for investment tokens similar to market instruments tradable on DLT platforms and infrastructures, particularly in accordance with blockchain technology, at once leaving a regulatory space for crypto-asset trading in traditionally stock exchanges ruled and supervised according to MIFIR and MIFID II current regime, thus creating a dual cryptoasset regulation. Apart from this, the Proposal also sets rules for other cryptos like utility tokens herein analysed considering their outstandingly interesting questions posed by their private-law and public financial regulation. Such analysis is such sketched out within this article, together with a note on the provision of related cryto-asset investment services and a general presentation of the teleology and regulatory policy of the European financial digitisation, from the double viewpoint of DLT industry and EBA / ESMA.
Compositional Cyber-Physical Systems Theory

This dissertation builds a compositional cyber-physical systems theory to develop concrete semantics relating the above diverse views necessary for safety and security assurance. In this sense, composition can take two forms. The first is composing larger models from smaller ones within each individual formalism of requirements, behaviors, and architectures which can be thought of as horizontal composition -- a problem which is largely solved. The second and main contribution of this theory is vertical composition, meaning relating or otherwise providing verified composition across requirement, behavioral, and architecture models and their associated algebras. In this dissertation, we show that one possible solution to vertical composition is to use tools from category theory. Category theory is a natural candidate for making both horizontal and vertical composition formally explicit because it can relate, compare, and/or unify different algebras.
ANALISIS PEMANFAATAN PLATFORM E-LEARNING MENGGUNAKAN FRAMEWORK COBIT 5 PADA DOMAIN DSS

This study aims to determine the level of capability of using E-Learning at Universal University. In this study, the measurement of capability level uses the COBIT 5 framework which is devoted to the DSS05 (Manage Security Services) process. The data from this study were obtained from observations and interviews. The results show that the capability level in the DSS05 (Manage Security Services) process reached level 1 with a rating level of Largely achieved (57.8%). After knowing the level of capability at the E-Learning level,recommendations for improvement are made based on the acquisition of each value. The recommendations for improvement are the creation of SOPs related to E-Learning security at Universal University, the establishment of information technology asset inventory management, and the procurement of intrusion detection tools.
Method for Recommending Custody to Minors based on Parental Responsibility using a Neutrosophic Cognitive Map

Children and adolescents under custody are a phenomenon that occurs daily in the country. Many homes are disorganized because parents abandon their children and leave them in the hands of guardians, who do not take good care of children and adolescents, usually being victims, having consequences in their behavior due to lack of the proper protection of their children parents. These children and adolescents are sometimes victims of violent situations, that is, the rights of children and adolescents are violated. It is necessary to analyze the use of neutrosophic cognitive maps on this problem to determine and characterize the variable factors that affect the custody of minors and the development of childhood and adolescence. So that, with the ranking of the incidence factors, decision-making by the government would be facilitated by defining strategies to mitigate the negative effects coming from custody not conceived under the parents' responsibility and the protection of the rights of childhood and adolescence.
Museums Tour Enhancement WithAugmented Reality: A Proposed Enhancement Designs of Exhibits to ImproveInformal Learning

Augmented Reality (AR) is one of the fastest growing fields in computing and it has penetrated into many other areas such as medical, engineering, and education. In this paper, we will investigate and propose a design to develop an interactive museum experience with AR to make it engaging for museum visitors and improve their retention towards museum exhibits. The implementation of AR may also yield unexpected benefits, such as providing users new perspective with non-linear interactivity, as well as encouraging them to experiment with technology and increase their curiosity. Benefits such as these may have the potential to better enhance the chances for learning and analytical activities to take place.