Reviewerly/exHarmony huggingface dataset:
ImTeNet: Image-Text Classification Network for Abnormality Detection and Automatic Reporting on Musculoskeletal Radiographs

Deep learning techniques have been increasingly applied to provide more accurate results in the classification of medical images and in the classification and generation of report texts. The main objective of this paper is to investigate the influence of fusing several features of heterogeneous modalities to improve musculoskeletal abnormality detection in comparison with the individual results of image and text classification. In this work, we propose a novel image-text classification framework, named ImTeNet, to learn relevant features from image and text information for binary classification of musculoskeletal radiography. Initially, we use a caption generator model to artificially create textual data for a dataset lacking text information. Then, we apply the ImTeNet, a multi-modal information model that consists of two distinct networks, DenseNet-169 and BERT, to perform image and text classification tasks respectively, and a fusion module that receives a concatenation of feature vectors extracted from both. To evaluate our proposed approach, we used the Musculoskeletal Radiographs (MURA) dataset and compare the results obtained with image and text classification scheme individually.
On the Worst-Case Side-Channel Security of ECC Point Randomization in Embedded Devices.

Point randomization is an important countermeasure to protect Elliptic Curve Cryptography (ECC) implementations against side-channel attacks. In this paper, we revisit its worst-case security in front of advanced side-channel adversaries taking advantage of analytical techniques in order to exploit all the leakage samples of an implementation. Our main contributions in this respect are the following: first, we show that due to the nature of the attacks against the point randomization (which can be viewed as Simple Power Analyses), the gain of using analytical techniques over simpler divide-and-conquer attacks is limited. Second, we take advantage of this observation to evaluate the theoretical noise levels necessary for the point randomization to provide strong security guarantees and compare different elliptic curve coordinates systems. Then, we turn this simulated analysis into actual experiments and show that reasonable security levels can be achieved by implementations even on low-cost (e.g. 8-bit) embedded devices. Finally, we are able to bound the security on 32-bit devices against worst-case adversaries.
Proportional Fuzzy Control of the Height of a Lubricant Mixture

Different components mix to get the required viscosities and lubrication qualities in the manufacturing processes of lubricating oils. This paper shows a proportional fuzzy controlled model for control of the height of this mixture, inside a stirred tank with heating, through the flow of two components: the base and the additive, depending on the variation in the opening of the valves and their corresponding inputs and outputs in the system. Three alternatives are studied: the variation in the number of rules used and the called negative errors, the variation in the flow range, and the change in the membership function. It also shows the importance of defining the limits of linguistic labels and determining the appropriate stabilization time, which ultimately determines a dynamic behavior of slow response; thus, the greater the system’s input flow, the stabilization time will be shorter.
College Libraries: Self-Quarantine Activities: Self-Care & Personal Development

Here are a few activities and resources to student, faculty and staff to cope while self-quarantining
CERED baseline models

Relationship extraction models for the Czech language. Models are trained on CERED (dataset created by distant supervision on Czech Wikipedia and Wikidata) and recognize a subset of Wikidata relations (listed in CEREDx.LABELS). We supply a demo.py that performs inference on user-defined input and requirements.txt file for pip. Adapt the demo code to use the model.Both the dataset and the models are presented in Relationship Extraction thesis.
Seismic sensors for global seismic monitoring and earthquake research in Armenia

In the field geophysical instruments, various seismic sensors (an accelerometer, a velocimeter) and auxiliary equipment in the form of recorders (loggers) have been designed, which provide wireless information transfer to the data collecting and processing center. On the basis of these, instrumental earthquake observation systems have been developed to ensure the integrated security of critical facilities. These systems can be transformed to control global seismic monitoring of the territories, dams, also facilities of critical importance such as nuclear power plants, bridges, tunnels and technological pipelines for chemical and oil-processing plants. The report presents the technical characteristics of the above mentioned instruments and the possibilities of their wide application in different countries. Additionally, monitoring of seismicity of Armenian regions is implemented for the earthquake research.
ANDROID-BASED LEARNING GUIDANCE INFORMATION SYSTEM ON MADIUN SMARTIES LEARNING GUIDANCE

At Smarties Tutoring in Madiun District, currently in the management of study guidance which includes data collection announcements, schedules, details, tutors and students still use handwritten media. This requires a long time in the process of inputing data on admission, schedules, details, tutors, and students as well as notification of the information to all tutors. Currently needed management and access of information that is easy and fast for Smarties Tutoring. To overcome the above problems, it is necessary to design and build an android-based application using the ionic framework. The system development method used is using the Waterfall method, while the stages include requirements analysis, design / design, coding, testing, implementation, and maintenance. With an android-based tutoring information system using the ionic framework can simplify admin management in the management of tutoring including recording announcement data, schedule data collection, data collection details, tutoring data collection, and student data collection, as well as facilitating tutors and students to access data provided by the admin that can be accessed online at SMARTIES tutoring. With research, an android application called the SMARTIES Tutoring application was formed. Keywords : Tutoring, Ionic Framework, Android.
Acme-modeling in the Teaching Profession: Models of Productivity and Professionalism

The relevance of the study is determined by the fact that in the context of transformation of the education system, it is especially important for the teacher to know and understand the process of modeling educational activities with an acme-focus on the final result in the student. This presupposes that the teacher has developed professional competencies and competencies in the field of educational systems modeling and personal and professional acme-development of the student. The purpose of the study is to analyse the concept and process of acme-modeling in the teacher’s professional activity and determine its main elements as a method of developing the teacher’s productive competencies in the professional activity. The hypothesis of the study is that knowledge and implementation of the acme-modeling technology in the teacher’s professional activity contributes to the development of his/her highly productive professional competencies and the achievement of results among students as the main indicator of his/her high level of professionalism. We used the following methods: theoretical, logical, scientific and practical analysis; systematization and interpretation of research results. In accordance with the laws of the acmeological theory of fundamental education, the theory of functional systems and the acme-synergetic and socio-synergetic concept of the development of social systems, we made an attempt to identify different types of models of productive professional competencies of a teacher and to identify their characteristics, taking into account a single quality criterion for education in the system of professional education at different levels. Based on the results of the study we 1) theoretically substantiated and determined the features of acmemodeling as a method of developing teacher productivity in professional and educational activities, 2) identified and gave characteristics of invariant idealized models in the activities of a teacher, 3) clarified functional elements of the educational system activity and highlighted the interrelated structural elements for all invariant idealized models of productivity.
The Female Financial Inclusion and the Sustainable Development in MENA Countries

Abstract In this paper we try to examine the effect of Microfinance on the sustainable development in a group of Middle East and North Africa countries (MENA). Can we consider that Microcredits are performing instrument for the sustainable development in MENA countries? To answer this question we chose a period from 1990 to 2018 and a sample of 10 MEN countries was selected. We have approximated sustainable development supported by the endogenous variable corresponds to the net adjustment of sustainable development (GS). Exogenous variables are: Active female borrowers (AFB), Labor Force female (LFF), the female to male labor force ratio, Gender parity index (GPI), GINI Index (GINI) and the GDP deflator. In the empirical analysis, we examined the linear fit of this long-term relationship within an error correction (ECM) model. We founded that 67% of sustainable development imbalance will be corrected by micro-financial institutions as the speed of adjustment brings this imbalance back to a stable state in the long term. Subsequently, we adopted the GMM method to determine the dynamics of sustainable development. Our results showed that participation rate of men in the labor force has a negligible and not significant influence on sustainable development and this can refer to their limit. JEL classification: O16; O57; C38; C33.
Using a digital relief model for searching for primary sources of gold in metamorphic complexes of the Evota region (Aldan-Stanovoy shield, North-Asian craton)

Placers of precious metals and other mineral resources are associated with the uplifted basement of the North-Asian craton and metamorphic terrains near its borders. The complex geological structure of these territories does not allow to make obvious conclusions about the sources of the placers. One of the areas of the southern outcrop of the craton basement, the Evota gold-bearing region of the Aldan-Stanovoy shield was studied. Analysis of the morphology of native gold selected from creeks of the region and eluvium from one of the primary deposits show that grains with similar morphological features occur. Probably, not far from the points of sampling, primary sources are located. Possible erosion and sediment removal should occur in positive forms of relief. Therefore, an attempt to determine the location of primary sources by modeling positive forms of relief, where erosion occurs and removal could be manifested, was made. The methodology for modeling these forms using modern geoinformation systems was considered as an attempt to analyze the obtained results. Digitized relief maps (topographic base) of the area and sample points with discovered gold were a basis for the calculations. Further steps were: building a surface of relief as a regular network of highs, calculating directions and slope angle of the surface, building a map of removal vectors, constructing a path with a maximum slope upward from the point with gold particles discover. Lines of positive forms of relief confined to gold discover points were constructed as a result. Field works for identifying signs of gold content in these lines and point sampling of rock debris were carried out. Microprobe analyses of rock debris were performed. Minerals of gold and silver were discovered in the debris. The obtained data shows that this method of analysis can be useful for deciphering ore-bearing structures and searching for primary sources.
Navigating Challenges of Virtual Science Instruction During and Beyond COVID-19

This paper provides narrative experiences of mentor teachers involved with the planning, preparation, implementation, and reflection of a virtual mathematics and science summer camp in the summer of 2020.  In the wake of the COVID-19 pandemic, the annual Advancing Mathematics and Science Excellence summer camp was forced to pivot to a completely on-line format. The staff set to lead the weeklong camp were faced with the task of converting this traditionally in-person, hands-on experience into a format that would educate a group of middle school students from their own homes without sacrificing engagement or educational quality. Primary concerns discussed by mentor teachers in early planning stages included accessibility, Zoom meeting etiquette, selecting activities that used only household items, and student safety during the activities. Through weeks of collaborative planning, activity and lesson preparation, technology troubleshooting, and practice run-throughs, the team was able to implement a successfully engaging camp for sixty students. Informal feedback from students and focus groups with mentor teachers and undergraduate interns revealed the efficiency of particular strategies, technologies, and activities that were implemented during the week. The team found that attendance was lower than expected; while there were 138 students registered for the camp, only 60 students actually attended the scheduled meetings.  Setting clear norms and expectations for the students during the sessions in general and clear objectives for each activity specifically were found to be essential.  Strategic use of the breakout room function in Zoom to facilitate small group discussion and the private chat function to maintain communication with students who were not able to use audio/video technology was very effective. Finally, the team found that it was absolutely necessary to emphasize flexibility and understanding in all aspects of the camp. This information can be used to refine practices for future or similar virtual science camps and, with appropriate modifications and considerations, may be able to inform best practices in science classrooms in the event K-12 schooling will occur either partially or completely through remote learning in upcoming school years .
Building Teams Apps Using Solution Accelerators

This chapter covers Building Teams Apps using Solution Accelerators, building Teams apps using power apps, power automate integration with teams, App templates, and team mobile platform extensibility. Today, using a low-code approach to building applications instead of writing code in an IDE like Visual Studio, you can actually draw your app like a picture and we take care of generating the code that you need on the back end to make your application actually work. The best part is built apps without writing code and easily adding them as tabs or integrate apps in Teams.
Evaluation of the Reliability, Utility, and Quality of the Information in Testicular Cancer Self-exam Videos Shared on YouTube

Objective: The aim of this study was to assess the testicular cancer self-examination (TSE) videos on YouTube. Material and Methods: This study was conducted to evaluate the content, reliability and quality of internet videos related to TSE. The search engine of YouTube® was queried for the keyword 'TSE' in April 01, 2019. Videos were scaled according to the time since upload day, running time, number of comments and number of like/dislike. All videos were also categorized according to source into 3 groups: Health information websites/TV programs; independent users; university channels/medical professionals. DISCERN questionnaire score (DISCERN) Journal of the American Medical Association benchmark criteria (JAMAS), Global Quality Scores (GQS), TSE-Comprehensiveness (TSE-C) and Video Power Index (VPI) were used. Results: Total of 68 videos were included and 32 of videos were excluded due to being unrelated or repeated. When VPI values were examined according to the video source, there was no statistically significant difference (p>0.05). According to the video source, there was a statistically significant difference in terms of DISCERN scores (p=0.049) and TSE-C scores (p=0.019). DISCERN scores of the videos whose source is university channels/medical professionals are higher than the DISCERN scores of the videos whose source is independent users (p=0.042). There was a statistically significant difference in terms of JAMAS scores (p=0.009). Conclusion: It is concluded that the information of TSE videos on YouTube is a weak source when evaluated in terms of reliability, benefit and quality.
Correct-by-Design Synthesis of Neural Network Controllers

The use of artificial neural networks is becoming ever more ubiquitous as the computational power available to use grows. The widespread implementation of neural networks as controllers in the field of systems and control is however being hindered by the lack of verifiability of these controllers. One type of controller that does not lack verifiability is the correct-by-design controller. The main drawback of correct-by-design controllers is that they inherently produce large data structures in order to store their control rules. In this work, a novel methodology to synthesize correct-by-design neural network controllers is presented in order to alleviate these issues. This methodology combines reinforcement learning techniques and abstraction based correct-by-design control verification techniques in order to synthesize neural network controllers that are correct-by-design. The procedure does so by alternating between a controller training routine and a controller verification routine in a system abstraction framework. This framework ensures that numerical training and verification results in a controller with formal guarantees applicable to real systems. Using the proposed methodology, neural network controllers are synthesized and verified in order to prove that the methodology works. In addition to this, the resulting correct-by-design neural network controllers are compared to conventional correct-by-design controllers in order to judge their performance and data requirements. This comparison also includes alternative structures used to store these different controllers. Based on this comparison, a conclusion is drawn regarding when to use which type of controller. The proposed methodology is implemented into a correct-by-design neural network synthesis framework called COSYNNC. This framework is intended as a basis for further research into correct-by-design neural network control and is publicly available.
Student Attendance System using QR Codes (Case Study: Institut Teknologi Telkom Surabaya)

Student attendance system is needed to measure student participation in a classroom, especially in Institut Teknologi Telkom Surabaya. Several at- tendance systems have been proposed based on manual presence. This is a high- ly important problem. The administration requires careful follow-up, taking care of it and not being lenient. The previous systems are inefficient in term of processing time and low in accuracy. This paper aims to propose student at- tendance system using QR code based on mobile application. To ensure the stu- dent attends in the classroom, QR code contained the time information was generated and displayed at lecturer presentation. The student only needed to scan the displayed QR code using his/her android or IOS smartphone. The code was then sent to the server for attendance process. The proposed work was de- signed and implemented using Android Studio, Objective C, and UML (Unified Modelling Language). The experimental result shows that the proposed attend- ance system only needed 0.000030s to recognize a QR Codes in the server.
CAN WE TRUST OUR COLLEAGUES? REVISITING THE INTRACOMMUNITY TRUST BETWEEN THE HIGHER SCHOOL TEACHERS

In the context of the higher education transformation there are risks that the academic community can get deformed. One of such risks is the reducing of intracommunity trust. The authors consider it as a necessary condition for the reproduction and development of the academic community and overcoming its fragmentation. The purpose of the article is to examine the quality of trust-based relationships between the university teachers. The empirical basis of the article is the data of the sociological study «Trust as a fundamental problem of Russian higher education», conducted in 2019-2020 in Higher Education Institutions in Yekaterinburg. The results are the following: 1. It examines the connection between trust and the phenomenon of fragmentation within the academic community. It as well shows the risks of deformations in university communities. 2. It defines the key characteristics of intracommunity trust among scientific and pedagogical personnel both at the level of value orientations and in behavioral terms. 3. It determines the functions of intracommunity trust.
On informed using of citedness-based indicators. Review of books of V. S. Lazarev

The paper reviews two recent monographs by Vladimir S. Lazarev, a well-known expert in scientific information, scientometrics, and bibliometrics as its application area – “Nobel Class Citedness Level and the Notions that Designate Characteristics and Properties of Cited Scientific Documents”; “Citedness as the Means of Representation of Value and Quality of Scientific Documents, Performance of Scientists and the Nobel Level of Research”. We selected the monographs of 2018 and current year for review since they both represented the complete nature of the author’s perception of termbase in applied bibliometrics: to a great extent, those books summarized multi-year author’s research of citedness nature and various properties of scientific documents that they may express. In addition to original and meticulous specifying of citedness features as the main phenomenon in bibliometrics, books provide a survey of international perception models regarding citedness, which is especially valuable in the absence of similar extended studies. Books may be interesting to scientimetricians; however, their studying may also help experts in research policy to improve the current system of research evaluation among scientists, research teams, and research organizations.
A Simulation of the Response of a Sounding Temperature Sensor Based on the Combination of a Genetic Algorithm and Computational Fluid Dynamics

The present study aims at improving the accuracy of weather forecast by providing useful information on the behavior and response of a sounding temperature sensor. A hybrid approach relying on Computational Fluid Dynamics an... | Find, read and cite all the research you need on Tech Science Press
Robust Handwritten Digit Classification Using Tensors Decomposition

Various handwritten digits recognition methods have been developed and their good performances have been reported. Nonetheless, recognizing digits types and patterns remains a challenging task. Recognition performance is highly affected by image corruption, perspective and illumination variation. On the other hand, vectors and matrices are sometimes not suitable or enough to describe the intrinsic nature of data from various fields of data processing. In this paper, we propose a handwritten digit classification method based on robust higher-order tensors. The proposed approach handles invariance to occlusions, misalignment and illumination variation. Evaluation of the MNIST and USPS handwritten numeral databases is performed to assess the performance and effectiveness of the proposed method. Substantial results are achieved in terms of recognition accuracy, image alignment, numerical stability and computational speed.