scholarly journals LeafLive-DB: Classification and Data Storage of Botanical Studies

Data ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 29
Author(s):  
Jorge Rodolfo Beingolea ◽  
Diego Ramos-Pires ◽  
Jorge Rendulich ◽  
Milagros Zegarra ◽  
Juan Borja-Murillo ◽  
...  

The development of studies, projects, and technologies that contribute to the understanding and preservation of plant biodiversity is becoming highly necessary, as well as tools and software platforms that enable the storage and classification of information resulting from studies on biodiversity. This work presents LeafLive-DB, a software platform that helps map and characterize species from the Brazilian plant biodiversity, offering the possibility of worldwide distribution. Developed by Brazilian and Peruvians researchers, this platform, which is available in its first version, features some functions for consulting and registering plant species and their taxonomy, among other information, through intuitive interfaces and an environment that promotes collaboration and data and research sharing. The platform innovates in data processing, functionality, and development architecture. It has ten thousand registers, and it should start to be distributed in partnership with schools and higher education institutions.

2021 ◽  
Vol 11 (3) ◽  
pp. 92
Author(s):  
Mehdi Berriri ◽  
Sofiane Djema ◽  
Gaëtan Rey ◽  
Christel Dartigues-Pallez

Today, many students are moving towards higher education courses that do not suit them and end up failing. The purpose of this study is to help provide counselors with better knowledge so that they can offer future students courses corresponding to their profile. The second objective is to allow the teaching staff to propose training courses adapted to students by anticipating their possible difficulties. This is possible thanks to a machine learning algorithm called Random Forest, allowing for the classification of the students depending on their results. We had to process data, generate models using our algorithm, and cross the results obtained to have a better final prediction. We tested our method on different use cases, from two classes to five classes. These sets of classes represent the different intervals with an average ranging from 0 to 20. Thus, an accuracy of 75% was achieved with a set of five classes and up to 85% for sets of two and three classes.


Biomimetics ◽  
2021 ◽  
Vol 6 (2) ◽  
pp. 32
Author(s):  
Tomasz Blachowicz ◽  
Jacek Grzybowski ◽  
Pawel Steblinski ◽  
Andrea Ehrmann

Computers nowadays have different components for data storage and data processing, making data transfer between these units a bottleneck for computing speed. Therefore, so-called cognitive (or neuromorphic) computing approaches try combining both these tasks, as is done in the human brain, to make computing faster and less energy-consuming. One possible method to prepare new hardware solutions for neuromorphic computing is given by nanofiber networks as they can be prepared by diverse methods, from lithography to electrospinning. Here, we show results of micromagnetic simulations of three coupled semicircle fibers in which domain walls are excited by rotating magnetic fields (inputs), leading to different output signals that can be used for stochastic data processing, mimicking biological synaptic activity and thus being suitable as artificial synapses in artificial neural networks.


2020 ◽  
Author(s):  
K. Thirumalesh ◽  
Salgeri Puttaswamy Raju ◽  
Hiriyur Mallaiah Somashekarappa ◽  
Kumaraswamy Swaroop

2021 ◽  
pp. 1-10
Author(s):  
Chao Dong ◽  
Yan Guo

The wide application of artificial intelligence technology in various fields has accelerated the pace of people exploring the hidden information behind large amounts of data. People hope to use data mining methods to conduct effective research on higher education management, and decision tree classification algorithm as a data analysis method in data mining technology, high-precision classification accuracy, intuitive decision results, and high generalization ability make it become a more ideal method of higher education management. Aiming at the sensitivity of data processing and decision tree classification to noisy data, this paper proposes corresponding improvements, and proposes a variable precision rough set attribute selection standard based on scale function, which considers both the weighted approximation accuracy and attribute value of the attribute. The number improves the anti-interference ability of noise data, reduces the bias in attribute selection, and improves the classification accuracy. At the same time, the suppression factor threshold, support and confidence are introduced in the tree pre-pruning process, which simplifies the tree structure. The comparative experiments on standard data sets show that the improved algorithm proposed in this paper is better than other decision tree algorithms and can effectively realize the differentiated classification of higher education management.


Author(s):  
Stepanenko

The purpose of the study is to study the organization and procedure for conducting an audit of operating expenses of the enterprise. Materials and methods. The study used research methods such as monographs and synthesis (when analyzing existing publications), analysis, induction and deduction, comparisons and key components. Research results. The essence of the audit is to provide practical assistance to the management and economic services of the enterprise in the management and management of its finances, as well as the establishment of financial and management accounting, providing various consultations. Audit can be divided into the following stages: organizational, pilot, final. Operating expenses are a major component of an enterprise's costs. These are the costs associated with the main activity of the enterprise (production of products, services, performance of work). According to P (C) BO 16 “Expenses” to operating expenses include administrative expenses, sales expenses, other operating expenses. Expenditure audit entities may include: accounting policies, cost accounting transactions, records in primary documents, accounting records and reporting, information on accounting misconduct, and abuses that have been documented in audit acts, audits, auditors' reports. The audit of costs should begin with the verification of the statement of financial results to confirm the accuracy of its performance, the study of the organization of production (if the enterprise is engaged in production) and technological processes, the study of cost estimates, planned calculations and other conditions. When reviewing the accumulation and write-off of administrative expenses, sales costs and other operating expenses, the auditor should check the correctness of the classification of expenses to administrative, sales and other operating expenses. The following techniques are used to collect audit evidence: document verification, confirmation, counting, surveys, analytical procedures. Through the procedures of observation, questioning and confirmation, they obtain the supporting information contained in the accounting records. The calculation procedure consists in checking the arithmetic accuracy of the primary documents and accounting records or in performing the calculations independently (inventory). Analytical procedures involve the analysis of the most important indicators and ratios, including a summary study of deviations and relationships that conflict with other information relevant to the case or deviate from the expected indicators. During the cost audit, the auditor checks the appropriateness of the formulas used in the calculations, the correctness of the calculation procedures (the amount of tests depends on the materiality of the estimated values). Conclusions. Operating expense audit is an integral part of an enterprise's overall audit. Improving organizational aspects of cost audit is associated with deepening the practice of analytical procedures at all stages of the audit. For organization of internal audit of expenses at the enterprise it is necessary to carry out regular control of correctness of their formation.


2021 ◽  

The Social Media Handbook provides guidance on long-term developments in the ever-changing social media sector and explains fundamental interrelationships in this field. It describes a strategy model for the development of one’s own solutions, summarises the theories, methods and models of leading authors and shows their practical application, while also highlighting current developments and dealing with the topic of data processing in social media. An examination of the platform economy with its economic functions facilitates the classification of business models in social media. The book also shows how platforms and their algorithms can influence our actions and shape our opinions. With contributions by Prof. Karin Bjerregaard Schlüter, Andrea Braun, Franziska Geue, Tobias Knopf, Markus Korbien, Prof. Dr. Daniel Michelis, Stefan Pfaff, Thanh H. Pham, Tom Reichstein, Prof. Dr. Anna Riedel, Michael Sarbacher, Prof. Dr. Dr. Thomas Schildhauer, Prof. Dr. Hendrik Send, Dr. Stefan Stumpp, Prof. Dr. Sebastian Volkmann, Jan-Benedikt Weber, Julia Weißhaupt, Norman Wiebach und Prof. Dr. Christian Wissing.


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