Journal of
Systemics, Cybernetics and Informatics
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ABSTRACTS


   





Construction of a Music Database for Earphone Hearing Loss Prevention and Music Therapy - Discussions on the Relationship Between Beethoven's Music and His Deafness -
Hirotoshi Hishida, Yoshihiro Komatsu, Keiko Hishida, Dai Yamamoto, Yasuhiro Hishida
(Pages: 1-8)

A music database is indispensable for both basic research on earphone hearing loss prevention and music therapy. In this study, Beethoven’s 32 piano sonatas and 16 string quartets are added to into the classical music genre of the database. And then, the relationship between his progress in hearing loss and the pitch distribution used in these works is discussed. Several elements are considered for the information that needs to be included in the music database: WAVE data and the corresponding spectrum obtained by FT analysis, musical score, and optional MIDI data, and the corresponding pitch distribution. The present study shows the following results. Both Beethoven’s piano sonatas and string quartets have frequency characteristics close to the natural 1/f spectrum, which is comfortable and not dangerous to the ears. On the other hand, there are minor differences in the same classical music. For example, a string quartet can be effective in inducing sleep, and a piano sonata can be ear-friendly.




The 4.0 Competences as Facilitators in the Realization, Management and Sustainability of Erasmus+ Projects in the Times of COVID-19 Pandemic
Pawel Poszytek, Jadwiga Fila, Mateusz Jezowski
(Pages: 9-12)

This article discusses the research on the role of 4.0 competences in the implementation of projects under Erasmus+ Programme – the European Union initiative for education, training youth and sport (2014-2020). It also puts the competences 4.0 in the perspective of labour market expectations in times of the fourth industrial revolution.




A STEM Literacy Program for Students in Secondary-Tertiary Transition to Reduce the Gender Gap: a Focus on the Students' Perception
Francesca Alessio, Chiara de Fabritiis, Agnese Ilaria Telloni
(Pages: 13-21)

This study concerns the design and implementation of a STEM literacy program for 11th to 13th-grade high achieving students, mainly females. The program, funded by the Italian Ministry of Equal Opportunities, aims at reducing the gender gap in the STEM disciplines and at orienting students towards university studies. We carried out a qualitative analysis of the students’ perception in terms of (1) a-priori expectations about the STEM literacy program and (2) a-posteriori thoughts and reflections about the attended course. Our analysis shows that students aspiring to participate had strong motivations with respect to the program; moreover, most students who participated in the program displayed satisfaction and an increase of awareness about their learning. We put a specific focus on the mathematical sessions of the curriculum, involving students as designers of educational resources. Some differences between male and female students arose for what concerns the perception of the program and the awareness of the impact of the STEM literacy program on their own learning.




Toward an Integrative Professional and Personal Competency-Based Learning Model for Inclusive Workforce Development
Amy J. Arnold, Jared Keyel, Alkan Soysal, Michael Kretser, Shahabedin Sagheb, Thanassis Rikakis
(Pages: 22-29)

Recent workforce disruptions highlight the need for just-in-time competency acquisition. Developing cyber-human tools that incorporate both human guidance and artificial intelligence may shorten learning and provide better career-upskilling pathways. Deconstructing degree programs to provide adaptive pathways of multi-modal micro-experiences offers greater flexibility. To implement such learning programming, the Calhoun Discovery Program (CDP) at Virginia Tech and its industry and non-profit partners are developing an adaptive education model based on Integrative Professional and Personal Competencies (IPPCs) for Industry 4.0. We argue that implementing whole-person-development-focused curricula that uses heterogeneous analytics and adaptive pathways can increase learners’ mobility within current and future economies. With our partners, we have developed real-world applied problem solving experiences to prepare transdisciplinary learners to work collaboratively on Industry 4.0 applications promoting sustainable and equitable development. This paper defines IPPCs and elaborates how they are integrated in the CDP through Problem-based Learning Experiences (PBLE), research and just-in-time modules. We note program outcomes over the first two years or operations and the generalizable takeaways of IPPC-based learning. Next, we describe computer-assisted tools we will develop to help us standardize and scale this learning model and summarize what the learning cycle looks like in our model. We conclude by sketching prospects for scaling this approach to K-12, industry and other settings.




Spotlight on Information Security Integration in the German Health Sector
Margit Scholl
(Pages: 30-39)

Based on extensive research of the literature on the cur-rent status of the health sector in Germany, the four spot-light areas of CRITIS, the pandemic situation, pandemic planning, and communication and learning are discussed in more detail in connection with information security. They may be used to create an integrative research map for holistic approaches in future research projects. With this in mind, the aim of this paper is to summarize key aspects of the spotlight areas based on a sound under-standing of the literature. The focus here is on general lessons learned from previous awareness-raising projects in information security.




Interdisciplinarity as a Key Competence on Industry 4.0 Labor Market
Paweł Poszytek
(Pages: 40-42)

The discussions on the concept of competencies 4.0 in the context of 4th industrial revolution, or industry 4.0, have been being growing recently and extensive analyses and researches have been being carried out by experts within various scientific disciplines such as management, economy, psychology, education, human resource, informatics and systemics. Due to the relevance of industry 4.0 concept in relation to current socio-economic challenges worldwide, the growing interest on the part of researchers and the proliferation of the above-mentioned terms in literature has formed a complicated network of patterns and relations constituting a scientific landscape of the discussions in questions. Accordingly, the aim of this article is to explain the contextual terminology of these discussions, namely: industry 4.0 and competencies 4.0 and discuss the nature of interdisciplinarity as one of the key factors defining future skills in the context of the new labor market needs.




A Meta-Analysis of Evolution of Deep Learning Research in Medical Image Analysis
David Zeng, Cherie Noteboom, Kruttika Sutrave, Rajesh Godasu
(Pages: 43-50)

With a text mining and bibliometrics approach, we review the literature on the evolution of deep learning in medical image literature from 2012 – 2020 to understand the current state of the research and to identify the major research themes in image analysis to answer our research questions: RQ1: What are the learning modes that are evident in the literature? RQ2: What are the emerging learning modes in the literature? RQ3: What are the major themes in medical imaging literature? The analysis of 8704 resulting from a data collection process from peer-reviewed databases, our analysis discovered the six major themes of image segmentation studies, studies with image classification, evaluation procedures such as sensitivity and specificity, optical coherence tomography studies, MRI imaging studies, and Chest imaging studies. Additionally, we assessed the number of articles published each year, the frequent keywords, the author networks, the trending topics, and connections to other topics. We discovered that segmenting and classifying the images are the most common tasks. Transfer learning is the most researched area and cancer is the highly targeted disease and Covid-19 is the most recent research trend.




The Tool Path Tolerance Setting with Respect to Accuracy During 3axis Milling
Marek Sadilek, Robert Cep, Lenka Cepova, Lukas Kusnir, Patrik Sniehotta
(Pages: 51-56)

Article describes CNC milling center programing during 3 axis finish milling. Article is focused on setting the tolerance of toolpaths during finish milling in CAM systems. Finding of suitable toolpaths during finish milling is very time consuming and can be expensive.

Target is to recommend specific settings of tolerance in CAM system with the respect to achieved accuracy, machining time, surface roughness and quantity of NC blocks. The aim is also to compare the practical results of machining with predicted simulation.

The methodology evaluating this problem is based on the following steps: experimental sample design for 3axis milling, accuracy prediction of machined samples, production of samples using CNC milling center, analysis of accuracy and surface roughness with respect to shape of workpiece.

The result is the variance of shape accuracy deviations from the specified CAD model of the workpiece, focused on individual areas of its shape. The research results show milled surface errors depending on the toolpath tolerances. It is not preferred to set very low tolerance in the CAM system with respect to increasing machining time.




Multidisciplinary Threat Recognition in Homeland Protection Systems
Mario La Manna
(Pages: 57-60)

The use of a multisensor system, composed of a set of heterogeneous sensors and other devices has already been demonstrated to improve sensibly the recognition capability, through the exploitation of its spatial/capability diversity, given by the presence of multiple devices and coordinated processes which perform threat detection/recognition. In this paper, we evaluate the performance of a multidisciplinary system, which uses a combination of a multisensory classification algorithm and a multidisciplinary fusion rule. This fusion rule combines the decisions coming from different channels with the reasoning process of a machine learning/human in the loop agent. The multidisciplinary fusion rule takes into account the different channel decisions, taken by different sensors and/or devices, and the intelligence provided by the machine learning/ human in the loop channel. The purpose of this channel is to highlight the channels which, inside the machine learning process and through the interaction with the human in the loop agent, show better performance in terms of recognition capabilities in the specific scenario. The performance evaluation of the multidisciplinary threat recognition system is carried out by considering different case studies. The evaluation demonstrates that a multidisciplinary system can classify different threats, by using a set of methods and algorithms, with a high probability of correct classification.




Numerical Solution of the Partial Differential Equation Bilaplacian Type by the Finite Element Method for the Simulation of Accelerometer-Type MEMS
José David Alanís Urquieta, Blanca Bermúdez Juárez, Paulo Daniel Vazquez Mora, Armando Hernández Flores
(Pages: 61-67)

In this paper, the numerical solution of the Partial Differential Equation Bilaplacian type by the finite element method is presented in order to simulate the accelerometer-type MEMS behavior. The above mentioned solution is used to emulate the behavior of the deformation of an Accelerometer-type MEMS. The technique is the physically based modelling as a methodology of simulation with visualization that was used to solve the current problem. The first step is to solve the partial differential equation, which represents the structure, by the finite element method. This numerical method was instrumented in Octave, taking into account the primitive functions that it contains, and taking advantage of the powerful language, and free software resource. For this problem, the software built, it has results suitable for these types of problems and has well rates of error. Once these types of results have been obtained, the next step will be the rendering and interpretation of the results in a graphical way. In spite of the complexity and size in memory used by the numerical method, this procedure results be a good alternative for this case and maybe in other similar cases. In future works will be looking for parallelize some numerical methods.




Optimal Analysis for Enhancement of Thermo Mechatronic Processes
J. Alan Calderón Ch., John Lozano, Julio Tafur, Benjamín Barriga, Juan Carlos Lengua, Gonzalo Solano, Darío Huanca
(Pages: 68-75)

Thermodynamic processes are part of the road of a thermodynamic system, while it has an initial and final state of the thermal trajectory. Nevertheless, there are many intricate variables while the process goes from a transient to a steady state, in many contexts it causes imbalances in the final system, such as given losses in internal efficiencies of subsystems from the main system, furthermore the total losses in the system efficiency. Hence, in this work is proposed a procedure to optimize a general thermodynamic process which was evaluated in different applications that are part of primary manufacturing tasks like there are in Perú, even they can produce pollution or disturbances in nature conditions when it is not an optimal procedure to develop the thermodynamic process. This proposal procedure is based in mathematical modelling by correlation in theoretical analysis of the thermal system with analysis of experimental data through adaptive/predictive techniques, moreover, it was evaluated and suggested applications of new technologies as sensors/actuators based in nanostructures due to faster and robust characteristics as comparisons with traditional sensors/actuators. Finally, the results achieved were interpreted by standards norms that help to keep based comparisons to interchange with international community.