Reviewerly/exHarmony huggingface dataset:
Codes over $ \frak m $-adic completion rings

&lt;p style='text-indent:20px;'&gt;The theory of linear codes over finite rings has been generalized to linear codes over infinite rings in two special cases; the ring of &lt;inline-formula&gt;&lt;tex-math id="M2"&gt;\begin{document}$ p $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt;-adic integers and formal power series ring. These rings are examples of complete discrete valuation rings (CDVRs). In this paper, we generalize the theory of linear codes over the above two rings to linear codes over complete local principal ideal rings. In particular, we obtain the structure of linear and constacyclic codes over CDVRs. For this generalization, first we study linear codes over &lt;inline-formula&gt;&lt;tex-math id="M3"&gt;\begin{document}$ \hat{R}_{ \frak m} $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt;, where &lt;inline-formula&gt;&lt;tex-math id="M4"&gt;\begin{document}$ R $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt; is a commutative Noetherian ring, &lt;inline-formula&gt;&lt;tex-math id="M5"&gt;\begin{document}$ \frak m = \langle \gamma\rangle $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt; is a maximal ideal of &lt;inline-formula&gt;&lt;tex-math id="M6"&gt;\begin{document}$ R $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt;, and &lt;inline-formula&gt;&lt;tex-math id="M7"&gt;\begin{document}$ \hat{R}_{ \frak m} $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt; denotes the &lt;inline-formula&gt;&lt;tex-math id="M8"&gt;\begin{document}$ \frak m $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt;-adic completion of &lt;inline-formula&gt;&lt;tex-math id="M9"&gt;\begin{document}$ R $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt;. We call these codes, &lt;inline-formula&gt;&lt;tex-math id="M10"&gt;\begin{document}$ \frak m $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt;-adic codes. Using the structure of &lt;inline-formula&gt;&lt;tex-math id="M11"&gt;\begin{document}$ \frak m $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt;-adic codes, we present the structure of linear and constacyclic codes over complete local principal ideal rings.&lt;/p&gt;
Guidelines for Evaluation of Visual Narrative Technology Based on Image Objects

Computer Vision research, which extracts and utilizes the information of images, has been in progress for a long time, and recently, researches that automatically describe the contents of images have attracted great interest. Scene graph, which have been widely used in vector-based graphic editing applications or modern computer games, can be very useful for describing or retrieving images. This is because the scene graph has a function to sequentially describe the contents of the image using the objects, in the image, and relations and attributes of the objects. This paper briefly introduces Visual Narrative technology that can describe the contents of an image in sequence by using image objects linked to scene graph, and explain about the standardized experimental images and evaluation criteria and procedures for evaluating the performance of the technology.
A Simple Platform for Reinforcement Learning of Simulated Flight Behaviors

We present work-in-progress on a novel, open-source software platform supporting Deep Reinforcement Learning (DRL) of flight behaviors for Miniature Aerial Vehicles (MAVs). By using a physically realistic model of flight dynamics and a simple simulator for high-frequency visual events, our platform avoids some of the shortcomings associated with traditional MAV simulators. Implemented as an OpenAI Gym environment, our simulator makes it easy to investigate the use of DRL for acquiring common behaviors like hovering and predation. We present preliminary experimental results on two such tasks, and discuss our current research directions. Our code, available as a public github repository, enables replication of our results on ordinary computer hardware.
Python for healthcare analytics made simple

Machine learning (ML) is found to be an element of healthcare industries for the past two decades after it was initially implemented for monitoring the antibiotic doses for patients who suffer from various infections. Nowadays, the volume of electronic healthcare records (EHR) gets increased, and thus, it leads to the huge massive of genetic sequential data which in turn directs the healthcare&apos;s importance in ML. A brief discussion about the common data sources in healthcare would be explained in detail. From various inferences, it is found that Python is a go-to language for developers, and it is extensively used in several fields. This chapter gives a brief description of the characteristics of data and the significance of the data quality in healthcare. Data has to be extracted from various sources for better analysis. Hence, the chapter puts forth an overview of challenges that must be resolved, and various types of extraction tools would be discussed. To describe the perceptions that are obtained through the analysis of the large data sets, data visualization is immensely used. In this world of healthcare, data analytics is huge, and it could include an extensive variety of organizations and other uses cases such as emergency rooms (ER), intensive care units, hospitals, and medical equipment manufacturers. The function of data visualization in the data science process flow could be discussed in detail in addition to the several techniques used to denote the complex data. It also covers advanced visualization techniques that emphasize grid, wordcloud, heatmap, and geospatial. Data analytics is a buzzword that refers to the diversified types of analysis. Perception is required since more information is required by the users for an extensive analysis. Certain techniques for the management of the data and analysis need more efforts and continuous attention particularly for data aggregation, data capture, real-time data streaming, analytics, and other visualization solutions, so that the integration could be done further for the improved utilization of electronic medical record (EMR) with the healthcare. Finally, this chapter briefs about the challenges that could be identified with the vast amount of data composed as EMR.
Applicability of MDA (Model Driven Architecture) for IoT

IoT (Internet of Things) is broadly utilized in practically every circle of our life. Area of uses of IoT may include: Smart home, Agriculture, Healthcare, Transportation, Manufacturing, Smart Cities and so on It's utilization is in countless territories yet it is as yet confronting numerous difficulties. Regardless of many purposed arrangements, bottlenecks actually exits. MDD (Model Driven Designing) has offered answers for some zones. It is generally being utilized because of its engaged deliberation. Reflection clears path for better answers for the issue. In view of MDD, MDA (Model driven Architecture) is appropriate for some application areas. This paper is an endeavor to examine the MDA based answers for IoT based frameworks. MDA has a splendid history. This examination assists with checking its legitimacy for IoT and zone of materialness.
Servant - "researchers" of Kazan University

On the jubilee days of our university, it is appropriate and fair to remember them too especially in our Soviet era, and when we and they - professors and technical staff, former servants - are equal members of the same trade union. Each of the universities can note a number of such "ministers" who are eligible for the title of "researchers". It is clear that these are scientific workers of a technical order, trainees, but still scientific workers with the identification of consciousness, a kind of creativity and technical ingenuity. It is necessary to recognize their significant role in the studies of students, in the training of scientific "personnel" of the past and present; it must be admitted that their role in the implementation of "active teaching methods" in the past was very significant. I would like to recall three such figures of ministers "scientific workers" of Kazan University during these jubilee days of Kazan University.
Experimental Analysis of in-Air Trajectories at Long Distances in Online Handwriting.

In this paper, we analyze in-air movements in online handwriting databases when the distance from the tip of the pen to the paper surface is higher than 1 cm. In this case, the computer can only know the time spent in air because the distance is too high to track the x and y coordinates of the movement. While this kind of movement is usually discarded, some investigation must be done in order to decide if computational algorithms can take advantage of this information in some scenarios. In this paper, we establish a criterion to differentiate useful in-air long distance strokes from user pauses.
Contemplative mental training increases serum BDNF levels with differing success depending on practice type and training sequence

In the inverse heat transfer problem, the reasonable allocation and placement of temperature measurement points is the key to the successful retrieve of thermal condition. For the inverse problems of heat transfer process with irregular heat transfer domain, the reasonable selection scheme of representative measurement points in temperature observable space is studied in this paper, and a selection mechanism of representative temperature measurement points based on fuzzy clustering technology is established. Firstly, based on dynamic response coefficients of heat transfer system, the characteristic vectors of temperature observable points to thermal boundary conditions of heat transfer system is constructed, and then the fuzzy partition of temperature observable domain is conducted by the fuzzy c-means (FCM) clustering of temperature characteristic vector. Furthermore, the categories of observable points are clearly defined by the defuzzification according to the principle of maximum membership degree. The spatial location of representative measurement points can be determined according to the shortest distance principle between the clustering center and the temperature observable points. Based on the obtained representative measurement points and the model predictive estimation algorithm, the estimation of the distributed thermal boundary conditions in heat transfer process with irregular heat transfer domain is realized. The validity of the above optimal placement scheme is verified by numerical simulation experiments, and comparison with the uniform measurement point allocation scheme is also conducted. The results show that the estimation results based on clustering of observable points are significantly better than those based on the uniform measurement point allocation scheme. In addition, under the same estimation accuracy, the established allocation scheme of the measurement points in this paper significantly reduces the dependence of the estimation results on the number of measurement points.
A dimensionality reduction method of power load data based on the combination of VMD-OMP-Kmeans

Abstract With the power data becoming more and more complex, it is of great significance to reduce the dimension and reconstruct the power data for the subsequent processing and application of power big data. This paper presents an algorithm based on variational mode decomposition (VMD) decomposition and orthogonal matching pursuit (OMP) reconstruction to reduce the dimension of power load data. Firstly, VMD method is used to decompose and filter the power load data; Secondly, K-means clustering algorithm is used to synthesize the decomposed data mode into a cluster center data set. Then, the data set is used as a dictionary; Thirdly, an OMP algorithm is proposed to select the elements to be reconstructed in the dictionary. And the corresponding data weights are given to reconstruct the load data with high-precision. As a result, the dimensionality of massive load data is reduced automatically. Finally, this paper builds a flexible load data dimensionality reduction model based on VMD method to verify the proposed method.
The impact of COVID-19 on Higher Education: Rethinking internationalization behind the iceberg: COVID-19 and Higher Education

The Corona virus (Covid-19) epidemic, which was first indicated in Wuhan, China and rapidly became a pandemic, led numerous deaths around the world until today. The global Covid-19 pandemic affected higher education institutions, as it affected all areas of life. The pandemic caught the nations off-guard. The effects of the pandemic on internationalization in higher education institutions were among the important issues emphasized in this process. Due to the pandemic, higher education institutions were closed in most nations. While certain countries attempted to solve the problem through distance education, certain others failed to manage the crisis due to the socio-economic and technological infrastructure problems. That’s way, as the impact of the pandemic on the economy was felt both in developed and developing countries, it also led to an increase in prevailing inequalities in several fields. Ironically, the invisible part of iceberg of internationalization in higher education became even more significant. Because the inequalities in the opportunities provided for international students became more pronounced. The possibility of an increase in the decline in number of international students made it necessary to rethink internationalization in higher education in the near future. Thus, this study aimed to investigate the impact of Covid-19 on higher education with a critical approach and to present sustainable internationalization recommendations for higher education institutions.
Optimization Method of Target Detection and Tracking System for Mobile Robot

The existing target detection and tracking methods, as an underlying design of service robot, are highly dependent on the computing ability, which will limit the transplantation to the robot platform. To solve the problem, this paper proposes a detection and tracking system suitable for mobile robot. For the target detection, an optimization method for feature extraction is proposed, by reducing the dimensionality of feature vectors to improve detection speed. For the target tracking, a multi-scale optimization method is proposed, which can accurately obtain all the characteristics of the upper body of the target. The last section is the experiment of the integrated system, which will resist the interference and robustly dynamically tracking the target.
Sistem Pakar Mendiagnosa Penyakit Difteri Pada Anak dengan Menggunakan Metode Certainty Factor

Diphtheria is now common among the general public, especially children who are very susceptible to various diseases. Diphtheria disease can cause death to anyone if it is not immediately treated medically. The spread of diphtheria is caused by corynebacterium bacteria through the air or physical contact by the sufferer. There are several early symptoms that can be recognized such as fever accompanied by chills, nasal congestion or a runny nose, but these symptoms are almost the same as the symptoms of tonsillitis, which also has the same symptoms as diphtheria. Apart from the symptoms caused by diphtheria there are also several factors that affect the disease such as; lack of maintenance of environmental cleanliness, wrong food intake, lack of nutritious food and so on. This is what causes the medical team to have difficulty diagnosing diphtheria in children. Therefore, the authors use an expert system by applying the certainty factor method to diagnose diphtheria. Through the application of this method is expected to be able to provide diagnosis of diphtheria and provide definite information about the possibility of a patient being diagnosed with diphtheria according to experts
Trend Analysis for Annual Rainfall Data in Dili, Timor-Leste using Mann Kendall Method

Rainfall is a key element of the hydrological cycle, therefore detecting trends of rainfall data can be used as information for understanding climate change. The trend of rainfall data in Dili needs to be made to identify changes in the hydrological climate system. The purpose of this study was to determine the rainfall trend in Dili using the Mann-Kendall test. The longest and most complete daily rain data is from stations installed at Dili Airport. Available data is from 1953 - 2017. The rainfall trend obtained can serve to detect possible changes in rainfall in Dili for the coming years. The linear trend shows that the rainfall in Dili tends to decrease every year. According to the Mann-Kendall test, The Aeroporto Dili annual rainfall trends are statistically insignificant.  This shows that there is a variation in the daily rainfall in one year, which can be different from other years due to fluctuations in weather and seasons. Although the reduction in rainfall every year is not very significant, it has implications for climate change that affects to water availability. Therefore, the information on trends in annual rainfall data can be used as a reference in dealing with impacts of climate change and water resources available in Dili.
Complexity analysis of a sampling-based interior point method for convex optimization

We develop a short-step interior point method to optimize a linear function over a convex body assuming that one only knows a membership oracle for this body. The approach is based on Abernethy and Hazan's sketch of a universal interior point method using the so-called entropic barrier [arXiv 1507.02528v2, 2015]. It is well-known that the gradient and Hessian of the entropic barrier can be approximated by sampling from Boltzmann-Gibbs distributions, and the entropic barrier was shown to be self-concordant by Bubeck and Eldan [arXiv 1412.1587v3, 2015]. The analysis of our algorithm uses properties of the entropic barrier, mixing times for hit-and-run random walks by Lovasz and Vempala [Foundations of Computer Science, 2006], approximation quality guarantees for the mean and covariance of a log-concave distribution, and results from De Klerk, Glineur and Taylor on inexact Newton-type methods [arXiv 1709.0519, 2017].
Про застосування методу аналізу ієрархій для автоматизованого оцінювання студентських робіт

The problem of applying multicriteria optimization on the basis of the analytical hierarchy process (AHP) for a specific subject domain is regarded in the paper. Namely, the situation when some students’ study projects should be compared and assessed with the aid of automated algorithm-based tools for grading especially if these projects are nearly of the same quality level is considered. It is well-known that using the classical graduation scale of pairwise comparisons preferences, suggested by T.Saati and commonly used in AHP, may lead to not very good results. The reason for this is that the difference between the automatically evaluated grades of the projects may become unacceptably large even though all of the projects are good enough and deserve good grades. On the other hand, a competitive and comparative approach to grading study projects should be preserved.In order to mitigate this problem, many authors proposed to apply alternative scales of pair comparisons, which are sometimes referred to as transitive ones. Constructing such scales should imply introducing some parameter that determines how many times the next graduation in the scale of preferences in pair comparisons matrices is bigger than the previous one. Typically this parameter is a rational value between 1 and 2 whereas 2 is the least graduation of preferences in the standard Saati scale. The main issue is how to find out appropriate values of this parameter in order to meet the requirements of the certain task.For exploring this question, some numerical experiments have been carried out and are reported in this paper. According to the typical algorithm of estimations, some projects executed by students have been compared pairwise by each criterion separately. Then the chosen criteria have been compared pairwise as well, and the linear convolution method has been applied for getting final grades. The reported experiments show that for the task of automated grading of students’ study projects alternative transitive scales described above can provide more adequate results than using the standard Saati scale, and the best choice of the parameter for this specific task is about 1.1.All experiments have been carried out with the help of the author software toolkits developed for the purposes of exploring AHP and of applying it for various practical tasks. Some screenshots illustrating the main points of reported experiments are supplied.Manuscript received 20.05.2020
Analysis on Establishing the Direction for Improving GAP Certification Standards Using Analytic Hierarchy Process

As the number of agricultural products produced or imported increases, the issue regarding the quality of the safety of agricultural products arises. The government is implementing various certification systems to ensure safety in the production process in order to increase the reliability of consumers'' food safety. Unlike other certification systems that focus on the safety issue in the production side, the GAP certification system manages the agricultural environment and hazards at all stages from the production of agricultural products to the distribution process. Despite the necessity and importance of the system, the GAP certification system is experiencing difficulties in terms of activation. This study examines the ways to establish a direction for improving GAP certification standards using the Analytic Hierarchy Process(AHP). As a result of the analysis, the promotion of consumption of GAP agricultural products is recognized as the most important improvement direction, and the detailed strategies with high priority are strengthening the safety management at the production stage and strengthening the safety management of the harvest. Therefore, when improving GAP certification standards, it is necessary to focus on strengthening production-level safety management in consideration of the consumption promotion aspect of consumers in the short term. However, in the medium and long term, the pursuit of GAP internationalization should also be considered. The results of this analysis are expected to be used as preliminary data to establish a plan to activate the GAP certification system.
Futuristic Technologies and Weapon Systems of the 21st Century

Technology is the application of scientific knowledge for practical purposes that involves development, processing, and management. Technology is dynamic and keeps on improving at a high speed. Currently, we are in the Information Age and a variety of advanced technologies are being used in our day-to-day life. For instance, in communications technology, today the phone can prepare a PowerPoint presentation, construction material are being fabricated on 3D computers, blood can be tested without samples, a guitar can be played using an application and learning can be done by Artificial Intelligence2—exemplifying the advancement under the use of technology.
Pest and Disease Identification with Incomplete Data

The problem of similarity of the symptoms causes a high degree of ambiguity in identifying pests and diseases, another problem in identifying pests and diseases is the incomplete symptoms (missing data) are told by the farmers because the symptoms conveyed have similarities with pests and other diseases making it difficult to identify. The objective of this study is to identify pests and diseases based on incomplete data. The similarity method with Jaccard Similarity (JS), Cosine Similarity (CS), and Dice Similarity (DS) is used to solve the problem of incomplete data. The purpose of the three methods is to find the best accuracy to solve the problem of incomplete data of symptoms to identify the pests and diseases of rice plants. The result of the experiment shows DS obtained the highest performance of accuracy compared to JS and CS.
Guides: Subject Guide: Management and Marketing: Archives and Special Collections

A guide to getting the most out of the Library and Collections resources for Management and Marketing