scholarly journals Teaching in Higher Education: Students’ Deep Learning of Brewing by Labwork

2019 ◽  
Vol 1 (1) ◽  
pp. 198-205
Author(s):  
Mariana-Liliana Păcală ◽  
Anca Sorina Șipoş ◽  
Lucica Brudiu ◽  
Lidia Favier
Keyword(s):  
Deep Learning ◽  
Laboratory Work ◽  
Integrative Approach ◽  
Research Activity ◽  
Laboratory Activity ◽  
Food Engineering ◽  
Beer Industry ◽  
Teaching Learning ◽  
Teaching In Higher Education ◽  
And Control

AbstractThe amount of theoretical and practical information to be given to students from engineering food specialty is increasingly greater. Within this perspective, it is important to use teaching-learning methods which to develop students’ cognitive ability through the efficient by of them of knowledge acquired at fundamental and specialized disciplines. The article aims to present in an integrated graphical manner the laboratory entitled “Determination of alcoholic concentration of beer by distillation” within the discipline of “Technology and control in the malt and beer industry” that is taught to students in the field of Food Engineering. The integrative approach to the laboratory theme is based on the generation of a graphical organization of the laboratory work content, thus enabling an efficient guidance of the teaching-learning process. On the same structure of the graphical organization of laboratory work are processed and interpreted experimental results, resulting in students’ deep learning of brewing by laboratory work. In conclusion, the use of integrated graphical manner in the teaching of laboratory work allowed students to achieve much better results in the assessment of laboratory activity, to find an improvement in self-organizing and self-evolving and to be more confident about the scientific research activity.

scholarly journals ENSINAR NA DOCÊNCIA UNIVERSITÁRIA: indícios da integração ensino e pesquisa

2014 ◽  
Vol 21 (3) ◽  
pp. 68
Author(s):  
Isabel Maria Sabino de Farias ◽  
Silvina Pimentel Silva
Keyword(s):  
Higher Education ◽  
Teaching Practice ◽  
Pedagogical Practices ◽  
Educación Superior ◽  
Research Activity ◽  
University Professors ◽  
Educacion Superior ◽  
Teaching Learning ◽  
Teaching In Higher Education ◽  
De Medicina

Docentes universitários que pesquisam possuem um modo diferenciado de ensinar? A interrogação permeia as análises deste artigo, que discute a integração ensino e pesquisa com base em estudo empírico com professores que mantêm vínculo com a atividade de pesquisa no exercício da docência na Educação Superior. Argumenta sobre a natureza epistêmica do ensinar e sua interface com a pesquisa, compreendida como indissociável da aprendizagem. Descreve a prática de ensino de cinco professores da Medicina, Biologia, Educação Física, Enfermagem e Física, evidenciando elementos que ancoram suas decisões. Identificou uma racionalidade prática no modo de ensinar dos professores pesquisados, desdobrada, por diferentes caminhos, na preocupação com o aluno.Palavras-chave: Ensino Superior. Práticas pedagógicas. Aprendizagem da docência. Pesquisa. Formação docente.  TEACHING IN UNIVERSITY: evidence of the integration between teaching and researchAbstract: University professors who research have a different way of teaching? The question permeates the analyzes in this article, which discusses the integration of teaching and research based on empirical study with professors who maintain ties with the research activity in the practice of teaching in Higher Education. Argues about the epistemic nature of teaching and its interface with the research, understood as inseparable from learning. Describes the teaching practice of five professors of Medicine, Biology, Physical Education, Nursing and Physics, highlighting elements that anchor their decisions. The research Identified a practical rationality in the way that the professors surveyed teaches, outspread in different ways in the concern with the student.Keywords: Higher education. Pedagogical practices. Teaching learning. Research. Teacher training.  ENSEÑAR EN LA CARRERA UNIVERSITARIA: evidencia de la integración de la enseñanza y la investigaciónResumen: ¿Maestros universitarios que pesquisan tienen un modo diferente de enseñanza? La interrogación impregna los análisis en este artículo, que trata de la integración entre enseñanza y la investigación basada en el estudio empírico con los maestros que mantienen vínculos con la actividad de investigación en la práctica de la enseñanza en la Educación Superior. Discute la naturaleza epistémica de la enseñanza y su interrelación con la investigación, comprendida como inseparable de la aprendizaje. Describe la práctica de la enseñanza de cinco profesores de Medicina, Biología, Educación Física, Enfermería y Física, destacando los elementos que anclan sus decisiones. Identificada una racionalidad práctica en la manera de enseñanza de los maestros encuestados, desplegada de distintas maneras, en la preocupación con el estudiante.Palabras clave: Educación Superior. Prácticas pedagógicas. Enseñanza-aprendizaje. Investigación. Formación de maestros.

scholarly journals Real-Time Detection of Dictionary DGA Network Traffic Using Deep Learning

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Kate Highnam ◽  
Domenic Puzio ◽  
Song Luo ◽  
Nicholas R. Jennings
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Real Time ◽  
Network Traffic ◽  
Short Term Memory ◽  
Domain Names ◽  
Control Networks ◽  
Detection Techniques ◽  
Lstm Network ◽  
And Control

AbstractBotnets and malware continue to avoid detection by static rule engines when using domain generation algorithms (DGAs) for callouts to unique, dynamically generated web addresses. Common DGA detection techniques fail to reliably detect DGA variants that combine random dictionary words to create domain names that closely mirror legitimate domains. To combat this, we created a novel hybrid neural network, Bilbo the “bagging” model, that analyses domains and scores the likelihood they are generated by such algorithms and therefore are potentially malicious. Bilbo is the first parallel usage of a convolutional neural network (CNN) and a long short-term memory (LSTM) network for DGA detection. Our unique architecture is found to be the most consistent in performance in terms of AUC, $$F_1$$ F 1 score, and accuracy when generalising across different dictionary DGA classification tasks compared to current state-of-the-art deep learning architectures. We validate using reverse-engineered dictionary DGA domains and detail our real-time implementation strategy for scoring real-world network logs within a large enterprise. In 4 h of actual network traffic, the model discovered at least five potential command-and-control networks that commercial vendor tools did not flag.

scholarly journals Flying Free: A Research Overview of Deep Learning in Drone Navigation Autonomy

Drones ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 52
Author(s):  
Thomas Lee ◽  
Susan Mckeever ◽  
Jane Courtney
Keyword(s):  
Deep Learning ◽  
Research Work ◽  
Learning Approaches ◽  
Clear Definition ◽  
Top Down ◽  
Research Activity ◽  
Comprehensive Overview ◽  
The Past ◽  
Computer Vision Applications ◽  
Definition Of

With the rise of Deep Learning approaches in computer vision applications, significant strides have been made towards vehicular autonomy. Research activity in autonomous drone navigation has increased rapidly in the past five years, and drones are moving fast towards the ultimate goal of near-complete autonomy. However, while much work in the area focuses on specific tasks in drone navigation, the contribution to the overall goal of autonomy is often not assessed, and a comprehensive overview is needed. In this work, a taxonomy of drone navigation autonomy is established by mapping the definitions of vehicular autonomy levels, as defined by the Society of Automotive Engineers, to specific drone tasks in order to create a clear definition of autonomy when applied to drones. A top–down examination of research work in the area is conducted, focusing on drone navigation tasks, in order to understand the extent of research activity in each area. Autonomy levels are cross-checked against the drone navigation tasks addressed in each work to provide a framework for understanding the trajectory of current research. This work serves as a guide to research in drone autonomy with a particular focus on Deep Learning-based solutions, indicating key works and areas of opportunity for development of this area in the future.

scholarly journals The Integrated Project for the Redevelopment of a Historic Building

2020 ◽  
pp. 261-282
Author(s):  
Liala Baiardi ◽  
Emerson A. M. Ferreira
Keyword(s):  
New Technologies ◽  
Research Activity ◽  
Existing Building ◽  
Digital Revolution ◽  
Management Processes ◽  
Building Process ◽  
Market Needs ◽  
Effective Development ◽  
And Control ◽  
Building Project

In a scenario influenced by innovation and new technologies such as the internet of things (IoT) that have projected us towards industry 4.0, the digital revolution has involved the construction sector and the entire building process. This research activity aims to deepen the tools at the base of the design and management processes to an effective development and respect for the environment. The text will illustrate the example of redevelopment of an existing building in response to new market needs and in line with the circular economy vision. The redevelopment foresees the integrated development of the architectural building project and the management of the building during his entire life cycle. The innovation authors intend to achieve aims to combine building automation with the quality of life through management techniques that exploit the best use of space and control of the eco-system of the building and the services provided.

scholarly journals CONTEMPORARY TECHNOLOGY SUPPORT FOR EDUCATION

2017 ◽  
Vol 5 ◽  
pp. 802-806 ◽  
Author(s):  
Teodor Savov ◽  
Valentina Terzieva ◽  
Katia Todorova ◽  
Petia Kademova-Katzarova
Keyword(s):  
Information And Communication Technologies ◽  
Technology Implementation ◽  
Online Survey ◽  
Human Life ◽  
Instructional Process ◽  
Innovative Learning ◽  
Information And Communication ◽  
Teaching Learning ◽  
Almost All ◽  
And Control

The information and communication technologies (ICT) have penetrated into almost all areas of human life. They have a dual impact on education – increase learning efficiency and train students actively to use innovations. We assess this impact by examining teachers’ experience with innovative tools in Bulgarian schools. In an anonymous online survey, we investigate their opinions on the issues related to technology integration in contemporary classrooms. The research shows that educators appreciate the benefits of technology implementation in the teaching-learning process, but they need a single structured system encompassing all technological resources and tools. This work proposes a conception for a smart classroom – an innovative learning environment that can establish and control suitable conditions for education as well as to impact the instructional process directly.

scholarly journals Efficient Deep Learning Models for DGA Domain Detection

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Juhong Namgung ◽  
Siwoon Son ◽  
Yang-Sae Moon
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Ensemble Model ◽  
Learning Models ◽  
Short Term ◽  
Domain Names ◽  
Additional Information ◽  
Domain Sequence ◽  
Long Short Term Memory ◽  
And Control

In recent years, cyberattacks using command and control (C&C) servers have significantly increased. To hide their C&C servers, attackers often use a domain generation algorithm (DGA), which automatically generates domain names for the C&C servers. Accordingly, extensive research on DGA domain detection has been conducted. However, existing methods cannot accurately detect continuously generated DGA domains and can easily be evaded by an attacker. Recently, long short-term memory- (LSTM-) based deep learning models have been introduced to detect DGA domains in real time using only domain names without feature extraction or additional information. In this paper, we propose an efficient DGA domain detection method based on bidirectional LSTM (BiLSTM), which learns bidirectional information as opposed to unidirectional information learned by LSTM. We further maximize the detection performance with a convolutional neural network (CNN) + BiLSTM ensemble model using Attention mechanism, which allows the model to learn both local and global information in a domain sequence. Experimental results show that existing CNN and LSTM models achieved F1-scores of 0.9384 and 0.9597, respectively, while the proposed BiLSTM and ensemble models achieved higher F1-scores of 0.9618 and 0.9666, respectively. In addition, the ensemble model achieved the best performance for most DGA domain classes, enabling more accurate DGA domain detection than existing models.

scholarly journals Hybrid Rule-Based Solution for Phishing URL Detection Using Convolutional Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-24
Author(s):  
Youness Mourtaji ◽  
Mohammed Bouhorma ◽  
Daniyal Alghazzawi ◽  
Ghadah Aldabbagh ◽  
Abdullah Alghamdi
Keyword(s):  
Deep Learning ◽  
High Efficiency ◽  
Personal Information ◽  
Support Vector ◽  
Learning Models ◽  
Rule Based ◽  
Common Purpose ◽  
Behavioral Method ◽  
And Control ◽  
Similarity Method

The phenomenon of phishing has now been a common threat, since many individuals and webpages have been observed to be attacked by phishers. The common purpose of phishing activities is to obtain user’s personal information for illegitimate usage. Considering the growing intensity of the issue, this study is aimed at developing a new hybrid rule-based solution by incorporating six different algorithm models that may efficiently detect and control the phishing issue. The study incorporates 37 features extracted from six different methods including the black listed method, lexical and host method, content method, identity method, identity similarity method, visual similarity method, and behavioral method. Furthermore, comparative analysis was undertaken between different machine learning and deep learning models which includes CART (decision trees), SVM (support vector machines), or KNN ( K -nearest neighbors) and deep learning models such as MLP (multilayer perceptron) and CNN (convolutional neural networks). Findings of the study indicated that the method was effective in analysing the URL stress through different viewpoints, leading towards the validity of the model. However, the highest accuracy level was obtained for deep learning with the given values of 97.945 for the CNN model and 93.216 for the MLP model, respectively. The study therefore concludes that the new hybrid solution must be implemented at a practical level to reduce phishing activities, due to its high efficiency and accuracy.

scholarly journals A comparative study on perceptions of medical students from the different curriculum on team-based learning

2021 ◽  
Vol 0 ◽  
pp. 1-6
Author(s):  
Vijayalakshmi S. Bhojaraja ◽  
B. K. Manjunatha Goud ◽  
Joan Kumar ◽  
Anand Srinivasan ◽  
Jeevan K. Shetty
Keyword(s):  
Deep Learning ◽  
Medical Students ◽  
Integrated Curriculum ◽  
Positive Impact ◽  
Learning Experience ◽  
Traditional Curriculum ◽  
Cross Sectional ◽  
Problem Solving Skills ◽  
Team Based Learning ◽  
Teaching Learning

Objectives: Our medical school followed the traditional curriculum earlier, and due to a large amount of content embedded in each discipline, which had less scope for active and deep learning. To overcome this, we adopted an integrated curriculum and introduced a few active teaching/learning (T/L) methodologies, which promote deep learning and problem-solving skills. One such T/L methodology we introduced was team-based learning (TBL). Before implementing this active T/L methodology in the integrated curriculum, we evaluated the effectiveness of TBL in medical students from the traditional curriculum and aimed to determine students’ perceptions. Furthermore, we aimed to explore the perception of TBL in students who underwent integrated curriculum to evaluate the difference in their perception compared to the traditional curriculum. Materials and Methods: This cross-sectional study was conducted in RAK Medical and Health Sciences University on the 1st year medical students from the traditional and integrated curriculum. Institutional ethical committee clearance and informed consent were obtained before starting the study. A pre-validated 5-item survey questionnaire comprising questions related to the content, process, and teamwork was used to obtain perceptions of students’ on TBL. Results: The students positively perceived the teaching-learning experience using TBL and understood the concepts better. Even the students with integrated curriculum had the same positive impact on their learning attitudes. The majority of students in both cohorts agreed that discussion among their teams helped them to learn better. Around two-thirds (66%) of students from the traditional curriculum and one-third (39%) of students from integrated curriculum wanted TBLs as T/L methodology over didactic lectures. Conclusion: TBL helped to learn better and understand the subject and promoted self and peer engagement, which facilitated their learning by clarifying the doubts with peers. Due to this positive TBL experience, most students from both curriculums recommended its use as a T/L method over lecture. Hence, TBL sessions in medical schools can be used as an effective T/L method to facilitate meaningful learning.

scholarly journals PENGARUH METODE PRAKTIKUM BERBANTUAN FLASH TERHADAP HASIL BELAJAR SISWA PADA MATERI HIDROKARBON DI KELAS XI IPA SMA MUHAMMADIYAH PONTIANAK

2016 ◽  
Vol 4 (2) ◽  
Author(s):  
Salmauwati Salmauwati ◽  
Muhamad Agus Wibowo ◽  
Dedeh Kurniasih
Keyword(s):  
Learning Outcomes ◽  
Practical Method ◽  
Control Group ◽  
Control Groups ◽  
Lecture Method ◽  
Post Test ◽  
Quasi Experimental ◽  
Teaching Learning ◽  
And Control ◽  
Positive Effect

ABSTRACTThis study was initiated by the students’ low learning outcomes on Chemistry subject and the teachers’ preference in using lecture method in teaching learning process.This study aimed at 1) finding out the differences of students’ learning outcomes between the use of flash media-assisted practical method and lecture method on hydrocarbon class at grade XI MIA of SMA Muhammadiyah I Pontianak. Using quasi experimental design and Control Group Posttes Design, this study employed the students of grade XI MIA 2 as the samples of experiment group, andthe students of grade XI MIA 2 as the samples of control group. The data collection techniques used were measurement and observation. While the instruments employed were observation sheet and essay. TheU-Mann Whitneytest revealed that the post test score of 0,0140< 0,05 Ho was rejected, while the Ha one was accepted. It means that there was correlation of students’ learning outcomes between the experiment and the control groups. In addition, the effect size result was 1,086 > 0,8 and considered high which indicated the positive effect of flash media-assisted practical method in enhancing students’ learning achievement.Keywords: flash, learning outcomes, hydrocarbon, practical method

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