Search results for: Leonardo Simon

Authors: Abdul Halim Abdul Razik, Ali Elkamel, Leonardo Simon

Abstract:

Wheat straw is one of the alternative feedstocks that may be utilized for bioethanol production especially when sustainability criteria are the major concerns. To increase market competitiveness, optimal supply chain plays an important role since wheat straw is a seasonal agricultural residue. In designing the supply chain optimization model, economic profitability of the thermochemical and biochemical conversion routes options were considered. It was found that torrefied pelletization with gasification route to be the most profitable option to produce bioethanol from the lignocellulosic source of wheat straw.

Keywords: bio-ethanol, optimization, supply chain, wheat straw

Procedia PDF Downloads 698

Authors: Leonardo C. Pacheco-Londoño, Nataly J. Galan-Freyle, Lisandro Pacheco-Lugo, Antonio Acosta, Elkin Navarro, Gustavo Aroca-Martínez, Karin Rondón-Payares, Samuel P. Hernández-Rivera

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In our Life Science Research Center of the University Simon Bolivar (LSRC), one of the focuses is the diagnosis and prognosis of different diseases; we have been implementing the use of gold nanoparticles (Au-NPs) for various biomedical applications. In this case, Au-NPs were used for Surface-Enhanced Raman Spectroscopy (SERS) in different diseases' diagnostics, such as Lupus Nephritis (LN), hypertension (H), preeclampsia (PC), and others. This methodology is proposed for the diagnosis of each disease. First, good signals of the different metabolites by SERS were obtained through a mixture of urine samples and Au-NPs. Second, PLS-DA models based on SERS spectra to discriminate each disease were able to differentiate between sick and healthy patients with different diseases. Finally, the sensibility and specificity for the different models were determined in the order of 0.9. On the other hand, a second methodology was developed using machine learning models from all data of the different diseases, and, as a result, a discriminant spectral map of the diseases was generated. These studies were possible thanks to joint research between two university research centers and two health sector entities, and the patient samples were treated with ethical rigor and their consent.

Keywords: SERS, Raman, PLS-DA, diseases

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Authors: Craig A. Kaplan

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If AGI proves to be a “winner-take-all” scenario where the first company or country to develop AGI dominates, then the first AGI must also be the safest. The safest, and fastest, path to Artificial General Intelligence (AGI) may be to harness the collective intelligence of multiple AI and human agents in an AGI network. This approach has roots in seminal ideas from four of the scientists who founded the field of Artificial Intelligence: Allen Newell, Marvin Minsky, Claude Shannon, and Herbert Simon. Extrapolating key insights from these founders of AI, and combining them with the work of modern researchers, results in a fast and safe path to AGI. The seminal ideas discussed are: 1) Society of Mind (Minsky), 2) Information Theory (Shannon), 3) Problem Solving Theory (Newell & Simon), and 4) Bounded Rationality (Simon). Society of Mind describes a collective intelligence approach that can be used with AI and human agents to create an AGI network. Information theory helps address the critical issue of how an AGI system will increase its intelligence over time. Problem Solving Theory provides a universal framework that AI and human agents can use to communicate efficiently, effectively, and safely. Bounded Rationality helps us better understand not only the capabilities of SuperIntelligent AGI but also how humans can remain relevant in a world where the intelligence of AGI vastly exceeds that of its human creators. Each key idea can be combined with recent work in the fields of Artificial Intelligence, Machine Learning, and Large Language Models to accelerate the development of a working, safe, AGI system.

Keywords: AI Agents, Collective Intelligence, Minsky, Newell, Shannon, Simon, AGI, AGI Safety

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Authors: Leonardo C. Pacheco-Londoño, Nataly J Galan-Freyle, Lisandro Pacheco-Lugo, Antonio Acosta-Hoyos, Elkin Navarro, Gustavo Aroca-Martinez, Karin Rondón-Payares, Alberto C. Espinosa-Garavito, Samuel P. Hernández-Rivera

Abstract:

At the Life Science Research Center at Simon Bolivar University, a primary focus is the diagnosis of various diseases, and the use of gold nanoparticles (Au-NPs) in diverse biomedical applications is continually expanding. In the present study, Au-NPs were employed as substrates for Surface-Enhanced Raman Spectroscopy (SERS) aimed at diagnosing kidney diseases arising from Lupus Nephritis (LN), preeclampsia (PC), and Hypertension (H). Discrimination models were developed for distinguishing patients with and without kidney diseases based on the SERS signals from urine samples by partial least squares-discriminant analysis (PLS-DA). A comparative study of the Raman signals across the three conditions was conducted, leading to the identification of potential metabolite signals. Model performance was assessed through cross-validation and external validation, determining parameters like sensitivity and specificity. Additionally, a secondary analysis was performed using machine learning (ML) models, wherein different ML algorithms were evaluated for their efficiency. Models’ validation was carried out using cross-validation and external validation, and other parameters were determined, such as sensitivity and specificity; the models showed average values of 0.9 for both parameters. Additionally, it is not possible to highlight this collaborative effort involved two university research centers and two healthcare institutions, ensuring ethical treatment and informed consent of patient samples.

Keywords: SERS, Raman, PLS-DA, kidney diseases

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Authors: Fonteyne Lot

Abstract:

SIMON (Study capacities and Interest Monitor is a freely accessible online self-assessment tool that allows secondary education pupils to evaluate their interests and capacities in order to choose a post-secondary major that maximally suits their potential. The tool consists of two broad domains that correspond with two general questions pupils ask: 'What study fields interest me?' and 'Am I capable to succeed in this field of study?'. The first question is addressed by a RIASEC-type interest inventory that links personal interests to post-secondary majors. Pupils are provided with a personal profile and an overview of majors with their degree of congruence. The output is dynamic: respondents can manipulate their score and they can compare their results to the profile of all fields of study. That way they are stimulated to explore the broad range of majors. To answer whether pupils are capable of succeeding in a preferred major, a battery of tests is provided. This battery comprises a range of factors that are predictive of academic success. Traditional predictors such as (educational) background and cognitive variables (mathematical and verbal skills) are included. Moreover, non-cognitive predictors of academic success (such as 'motivation', 'test anxiety', 'academic self-efficacy' and 'study skills') are assessed. These non-cognitive factors are generally not included in admission decisions although research shows they are incrementally predictive of success and are less discriminating. These tests inform pupils on potential causes of success and failure. More important, pupils receive their personal chances of success per major. These differential probabilities are validated through the underlying research on academic success of students. For example, the research has shown that we can identify 22 % of the failing students in psychology and educational sciences. In this group, our prediction is 95% accurate. SIMON leads more students to a suitable major which in turn alleviates student success and retention. Apart from these benefits, the instrument grants insight into risk factors of academic failure. It also supports and fosters the development of evidence-based remedial interventions and therefore gives way to a more efficient use of means.

Keywords: academic success, online self-assessment, student retention, vocational choice

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Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

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The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

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Authors: Umukoro Omonigho Simon, Ashaolu David ‘Diya, Aroyewun-Olaleye Temitope Folashade

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The VELMA Action to Reduce Cybercrime (ARC) is an initiative, the first of its kind in Nigeria, designed to identify, rehabilitate and empower repentant cybercrime offenders popularly known as ‘yahoo boys’ in Nigerian parlance. Velma ARC provides social inclusion boot camps with the goal of rehabilitating cybercriminals via psychotherapeutic interventions, improving their IT skills, and empowering them to make constructive contributions to society. This report highlights the psychological interventions provided for participants of the maiden edition of the Velma ARC boot camp and presents the outcomes of these interventions. The boot camp was set up in a hotel premises which was booked solely for the 1 month event. The participants were selected and invited via the Velma online recruitment portal based on an objective double-blind selection process from a pool of potential participants who signified interest via the registration portal. The participants were first taken through psychological profiling (personality, symptomology and psychopathology) before the individual and group sessions began. They were profiled using the Minnesota Multiphasic Personality Inventory -2- Restructured Form (MMPI-2-RF), the latest version of its series. Individual psychotherapy sessions were conducted for all participants based on what was interpreted on their profiles. Focus group discussion was held later to discuss a movie titled ‘catch me if you can’ directed by Steven Spielberg, featuring Leonardo De Caprio and Tom Hanks. The movie was based on the true life story of Frank Abagnale, who was a notorious scammer and con artist in his youthful years. Emergent themes from the movie were discussed as psycho-educative parameters for the participants. The overall evaluation of outcomes from the VELMA ARC rehabilitation boot camp stemmed from a disaggregated assessment of observed changes which are summarized in the final report of the clinical psychologist and was detailed enough to infer genuine repentance and positive change in attitude towards cybercrime among the participants. Follow up services were incorporated to validate initial observations. This gives credence to the potency of the psycho-educative intervention provided during the Velma ARC boot camp. It was recommended that support and collaborations from the government and other agencies/individuals would assist the VELMA foundation in expanding the scope and quality of the Velma ARC initiative as an additional requirement for cybercrime offenders following incarceration.

Keywords: Velma-ARC, cybercrime offenders, rehabilitation, Nigeria

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Authors: Komal Saeed

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Introduction: Rhinoplasty is considered one of the challenging aesthetic procedures. Psychosocial concerns motivate the urge for aesthetic procedures especially rhinoplasty. Males who fall in this category are designated as single, immature, male, over expectant and narcissistic (SIMON) in literature. As of yet, there is no term that depicts females showing similar characteristics. The purpose of this study is to evaluate the incidence of body dysmorphic disorder (BDD) in females seeking rhinoplasty and to introduce a term for such individuals. Materials and Methods: A prospective, questionnaire based, qualitative study was conducted in the Department Of Plastic Surgery between March 2018 and March 2020. 110 female candidates seeking aesthetic rhinoplasty were included in the study. BDD was evaluated using the Dysmorphic Concerns Questionnaire, DCQ. Data were analyzed using SPSS version 25 software and correlation between the groups was evaluated. Results: Out of 110 female subjects, 77.3% (n=85) were single, 16.4% (n=18) were married and 6.4% (n=7) were divorced. BDD was found in 41.8% (n=46) of the candidates, majority being single (n=41, 89.1%) and having educational status above diploma (n=39, 84.8%). There was a statistically higher percentage of young adults between 24 and 28 years (n=33, 71.7%) having BDD (p= 0.0001). Conclusion: Considering the high frequency of BDD among females seeking rhinoplasty, a standardized term ‘SIFON’ is introduced to describe such individuals who are S; single, I; immature, F; female, O; over expectant, N; narcissistic as apposed to SIMON in males. These individuals perceive aesthetic procedures as a solution to their body dissatisfaction. Therefore, preoperative counseling seems necessary to avoid unsatisfactory outcomes secondary to mental health.

Keywords: aesthetic rhinoplasty, body dismorphic disorder, single, immature, obsessive

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Authors: Jenny K. Ubaque, Edward P. Guillen, Juan S. Solórzano, Leonardo J. Ramírez

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The health care must be a right for people around the world, but in order to guarantee the access to all, it is necessary to overcome geographical barriers. Telemedicine take advantage of Information Communication Technologies to deploy health care services around the world. To achieve those goals, it is necessary to use existing last mile solution to create access for home users, which is why is necessary to establish the channel characteristics for those kinds of services. This paper presents an analysis of network performance of last mile solution for the use of IPTV broadcasting with the application of streaming for telemedicine apps.

Keywords: telemedicine, IPTV, GPON, ADSL2+, coaxial, jumbogram

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Authors: Yuli Paola Cifuentes Sanabria, Lina Paola Beltrán Beltrán, Leonardo Juan Ramírez López

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The availability to deploy mobile applications for healthcare is increasing daily thru different mobile app stores. But within these capabilities the number of hacking attacks has also increased, in particular into medical mobile applications. The security vulnerabilities in medical mobile apps can be triggered by errors in code, incorrect logic, poor design, among other parameters. This is usually used by malicious attackers to steal or modify the users’ information. The aim of this research is to analyze the vulnerabilities detected in mobile medical apps according to risk factor standards defined by OWASP in 2014.

Keywords: mHealth apps, OWASP, protocols, security vulnerabilities, risk factors

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Authors: Ciolomic Ioana Andreea, Farcas Teodora, Tiron-Tudor Adriana

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Investments in research and innovation are widely acknowledged as being crucial drivers for economic growth, for job-creation and to secure social and economic welfare. The aim of this article is to disseminate the results of a Leonardo da Vinci Innovation Transfer project, AdapTykes Adaptation of trainings based up on the Finnish Workplace Development Programme. This project aims to analyses the adaptability of the Finnish model to the economic and political environment of the two emergent countries Romania and Hungary, in order to develop workplace innovation. The focus of this paper is to present the adaptability of the Finnish model to the Romanian context.

Keywords: innovation, human resources, education, tools

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Authors: M. E. Joret, F. Germeys, P. Van de Craen

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Background: Previous studies have shown that ‘full’ bilingualism seems to enhance the executive functions in children, young adults and elderly people. Executive functions refer to a complex cognitive system responsible for self-controlled and planned behavior and seem to predict academic achievement. The present study aimed at investigating whether similar effects could be found in children learning their second language at school in immersion education programs. Methods: In this study, 44 children involved in immersion education for 4 to 5 years were compared to 48 children in traditional schools. All children were between 9 and 11 years old. To assess executive functions, the Simon task was used, a neuropsychological measure assessing executive functions with reaction times and accuracy on congruent and incongruent trials. To control for background measures, all children underwent the Raven’s coloured progressive matrices, to measure non-verbal intelligence and the Echelle de Vocabulaire en Images Peabody (EVIP), assessing verbal intelligence. In addition, a questionnaire was given to the parents to control for other confounding variables, such as socio-economic status (SES), home language, developmental disorders, etc. Results: There were no differences between groups concerning non-verbal intelligence and verbal intelligence. Furthermore, the immersion learners showed overall faster reaction times on both congruent and incongruent trials compared to the traditional learners, but only after 5 years of training, not before. Conclusion: These results show that the cognitive benefits found in ‘full’ bilinguals also appear in children involved in immersion education, but only after a sufficient exposure to the second language. Our results suggest that the amount of second language training needs to be sufficient before these cognitive effects may emerge.

Keywords: bilingualism, executive functions, immersion education, Simon task

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Authors: K. Sekulová, M. Šimon

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This article focuses on upper-extremity musculoskeletal disorders risk assessment model at workplace. In this model are used risk factors that are responsible for musculoskeletal system damage. Based on statistic calculations the model is able to define what risk of MSD threatens workers who are under risk factors. The model is also able to say how MSD risk would decrease if these risk factors are eliminated.

Keywords: ergonomics, musculoskeletal disorders, occupational diseases, risk factors

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Authors: Sarah Ullrich, Juliane Rolle, Christian Beste, Nicole Wolff

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Inhibition and cognitive flexibility are essential parts of executive functions in our daily lives, as they enable the avoidance of unwanted responses or selectively switch between mental processes to generate appropriate behavior. There is growing interest in improving inhibition and response selection through brief mindfulness-based meditations. Arguably, open-monitoring meditation (OMM) improves inhibitory and flexibility performance by optimizing cognitive control and information processing. Yet, the underlying neurophysiological processes have been poorly studied. Using the Simon-Go/Nogo paradigm, the present work examined the effect of a single 15-minute smartphone app-based OMM on inhibitory performance and response selection in meditation novices. We used both behavioral and neurophysiological measures (event-related potentials, ERPs) to investigate which subprocesses of response selection and inhibition are altered after OMM. The study was conducted in a randomized crossover design with N = 32 healthy adults. We thereby investigated Go and Nogo trials in the paradigm. The results show that as little as 15 minutes of OMM can improve response selection and inhibition at behavioral and neurophysiological levels. More specifically, OMM reduces the rate of false alarms, especially during Nogo trials regardless of congruency. It appears that OMM optimizes conflict processing and response inhibition compared to no meditation, also reflected in the ERP N2 and P3 time windows. The results may be explained by the meta control model, which argues in terms of a specific processing mode with increased flexibility and inclusive decision-making under OMM. Importantly, however, the effects of OMM were only evident when there was the prior experience with the task. It is likely that OMM provides more cognitive resources, as the amplitudes of these EKPs decreased. OMM novices seem to induce finer adjustments during conflict processing after familiarization with the task.

Keywords: EEG, inhibition, meditation, Simon Nogo

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Authors: Souad Slimani, Sylvain Gravier, Simon Schmidt

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Recently, several vertex identifying notions were introduced (identifying coloring, lid-coloring,...); these notions were inspired by identifying codes. All of them, as well as original identifying code, is based on separating two vertices according to some conditions on their closed neighborhood. Therefore, twins can not be identified. So most of known results focus on twin-free graph. Here, we show how twins can modify optimal value of vertex-identifying parameters for identifying coloring and locally identifying coloring.

Keywords: identifying coloring, locally identifying coloring, twins, separating

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Authors: K. Sekulová, M. Šimon

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The article demonstrates on a case study how it is possible to identify MSD risk. It is based on a dissertation risk identification model of occupational diseases formation in relation to the work activity that determines what risk can endanger workers who are exposed to the specific risk factors. It is evaluated based on statistical calculations. These risk factors are main cause of upper-extremities musculoskeletal disorders.

Keywords: case study, upper-extremity musculoskeletal disorders, ergonomics, risk identification

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Authors: Simon Oga Egboja

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In Africa, particularly in Nigeria, unemployment is a serious issue of concern to every citizen. Hence, this paper focuses on the employment situation and trends in Nigeria. It also investigated the causes why unemployment persists in the country. Prominent among them is the population explosion and rapid expansion of education opportunities all over the country without a corresponding increase in industrial establishment. The paper also discusses the way of reducing the rate of unemployment by encouraging graduates of tertiary institutions in Nigeria to read professional courses and also to indulge in the habit of establishing small-scale enterprises so that after them school they can be self-employed rather than relying solely on government for employment.

Keywords: causes, population, remedy, unemployment

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Authors: Gisele C. A. Martins, Leonardo A. Marcolin, Laurenn B. de Macedo, Francisco A. Rocco Lahr, Carlito Calil Jr

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The use and development of wood composite materials increased in the past few years. However, in Brazil there are some restrictions on these products regarding their use since it could be considered a potential risk in a fire situation. Thus, becomes evident the need for research aiming to fit these in safety standards. This study aims to evaluate the efficiency of two new fire retardant products produced by a Brazilian industry. Tests were performed on plywood panels of Pinus spp previously immersed, varying the products concentrations and compared with untreated samples. The test used to evaluate the flame spread in a panel was the modified Schlyter test. The product in question was proved efficient, before and after shutting off the burner. Comparing panels with the panels without treatment, there was a decrease of 400% of the height of the flame spread on the treated ones.

Keywords: fire retardant, flame spread, plywood, wood-based material

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Authors: Leal Leonardo, Pires Carlos Augusto de Moraes, Casiraghi Magela

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In this work were realized the modeling and simulation of the catalytic reformer process, of ample form, considering all the equipment that influence the operation performance. Considered it a semi-regenerative reformer, with four reactors in series intercalated with four furnaces, two heat exchanges, one product separator and one recycle compressor. A simplified reactional system was considered, involving only ten chemical compounds related through five reactions. The considered process was the applied to aromatics production (benzene, toluene, and xylene). The models developed to diverse equipment were interconnecting in a simulator that consists of a computer program elaborate in FORTRAN 77. The simulation of the global model representative of reformer unity achieved results that are compatibles with the literature ones. It was then possible to study the effects of operational variables in the products concentration and in the performance of the unity equipment.

Keywords: catalytic reforming, modeling, simulation, petrochemical engineering

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Authors: Leonardo Ko

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In an era marked by rapid technological innovation, the classical instrument industry nonetheless has not seen significant change. Is this a matter of stubborn traditionalism, or do old, conventional instruments really sound better? Because of the widespread use of 3-D printing, it seems feasible to produce modern, 3-D printed instruments that adhere to the basic conventions of standard construction. This study aimed to design and create a practical, effective 3-D printed acoustic violin. A cost-benefit analysis of materials and design is presented in addition to a report on sound tests in which a pool of professional musicians compared the traditional violin to its synthetic counterpart with regard to acoustic properties. With a low-cost yet functional instrument, musicians of all levels would be able to afford instruments with much greater ease; the present study thus hopes to contribute to efforts to increase the accessibility of classical music education.

Keywords: acoustic musical instrument, classical musical education, low-cost, 3-D printing

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Authors: Suzana Leitão Russo, Mayara Laysa de Oliveira Silva, José Augusto Andrade Filho, Vitor Hugo Simon

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Currently, seismic methods and prospecting methods are commonly applied in the oil industry and, according to the information reported every day; oil is a source of non-renewable energy. It is easier to understand why the ownership of areas of oil extraction is coveted by many nations. It is necessary to think about ways that will enable the maximization of oil production. The technique of spectral analysis can be used to analyze the behavior of the variables already defined in oil well the profile. The main objective is to verify the series dependence of variables, and to model the variables using the frequency domain to observe the model residuals.

Keywords: oil, well, spectral analysis, oil extraction

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Authors: Cheila Cristina Leonardo Oliveira Gaioli, Fernanda Ludmilla Rossi Rocha, Sandra Cristina Pillon

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Resilience is a psychological process that facilitates the maintenance of health, developed in response to numerous existing stressors in daily life. Furthermore, resilience can be described as the ability which allows an individual or group to hold up well before unfavorable situations. This study aimed to identify nursing workers’ resilience at a psychiatric hospital in Brazil. This is an exploratory research with quantitative data approach. The sample consisted of 56 workers, using the Resilience Scale. Of the 56 subjects, 45 (80.4%) were women; 22 (39.2%) were 20- to 40-years-old and 30 (53.6%) were 41- to 60-years-old; 11 (19.6%) were nurses and 45 (80.4%) were technicians or nursing assistants. The results also showed that 50% of subjects showed a high resilience degree and 42.9% an average resilience degree. Thus, it was found that workers seek to develop protective factors in coping with a work environment that does not value the individual subjectivity and does not allow professional development, discouraging workers.

Keywords: health promotion, nursing, occupational health, resilience

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Authors: Leonardo Dias Cruz

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The advent of web 2.0 has enabled users to engage in translocal and transtemporal interactions in which meanings can be constantly (re)constructed. The fluidity of such interactions in the time-space spectrum makes it evident that D/discourses are always in movement and that here-and-now discursive practices are always linked to macro Discourses in social structures. Considering these assumptions, this study aims at exploring the social construction of masculinities in light of feminist D/discourses in online interactions. The data used are a series of comments from readers of articles posted in a website for (projected) male audiences. In order to approach the movable and fluid nature of such interactions, I examine the data through the lens of processes of entextualization, social positioning and indexical cues. The analysis explores the interactions as social arenas in which struggles for the control over entextualization processes are clearly noticeable. Moreover, two main stances are perceived: one that legitimates male’s participation in Feminism and one that rejects such participation.

Keywords: entextualization, feminism, masculinities, positionings

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Authors: Frank Alexis, Jenny Antonia Rodriguez Leon, Cristobal Leonardo Dominguez Borbor, Mery Rosario Ramirez Munoz

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The shrimp industry has increased in the last years to the point of becoming one of the most dynamic industries. However, the appearance of diseases that significantly affect the production of shrimps has been an obstacle for the shrimp industry. We hypothesized that natural fibers from biodiversity can stimulate the immune system to prevent shrimp diseases like vibriosis. In this project, we extracted the fibers from vegetal sources in Ecuador and characterized them using common techniques like XRD, SEM, and then we tested the effect of fibers as immunostimulants for shrimps in-vitro and in-vivo using small aquarium and large pools. Our results demonstrate that vegetal fibers can significantly increase the survival of shrimps. Moreover, the production of shrimps in a large pool was significantly increased. Lastly, the test of color and taste successfully surpass the control group of shrimps not treated with fiber food supplements.

Keywords: fibers, immunostimulant, shrimp, vibriosis

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The increasing use of deep learning applications in production is becoming a competitive advantage. Predictive quality enables the assurance of product quality by using data-driven forecasts via machine learning models as a basis for decisions on test results. The use of real Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the leakage of directional valves.

Keywords: artificial neural networks, classification, hydraulics, predictive quality, deep learning

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Authors: Leonardo Herrera, Shield B. Lin, Stephen J. Montgomery-Smith, Ziraguen O. Williams

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A one-directional dynamic model of a Stewart Platform was developed to assist NASA in analyzing the dynamic response in spacecraft docking operations. A simplified mechanical drawing was created, capturing the physical structure's main features. A simplified schematic diagram was developed into a lumped mass model from the mechanical drawing. Three differential equations were derived according to the schematic diagram. A Simulink diagram was created using MATLAB to represent the three equations. System parameters, including spring constants and masses, are derived in detail from the physical system. The model can be used for further analysis via computer simulation in predicting dynamic response in its main docking direction, i.e., up-and-down motion.

Keywords: stewart platform, docking operation, spacecraft, spring constant

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Due to increasing cost pressure in global markets, artificial intelligence is becoming a technology that is decisive for competition. Predictive quality enables machinery and plant manufacturers to ensure product quality by using data-driven forecasts via machine learning models as a decision-making basis for test results. The use of cross-process Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: predictive quality, hydraulics, machine learning, classification, supervised learning

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Authors: Leonardo Juan Ramírez López, Javier Oswaldo Rodriguez Velasquez

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We have designed a Holter that measures the heart´s activity for over 24 hours, implemented a prediction methodology, and generate alarms as well as indicators to patients and treating physicians. Various diagnostic advances have been developed in clinical cardiology thanks to Holter implementation; however, their interpretation has largely been conditioned to clinical analysis and measurements adjusted to diverse population characteristics, thus turning it into a subjective examination. This, however, requires vast population studies to be validated that, in turn, have not achieved the ultimate goal: mortality prediction. Given this context, our Insight Research Group developed a mathematical methodology that assesses cardiac dynamics through entropy and probability, creating a numerical and geometrical attractor which allows quantifying the normalcy of chronic and acute disease as well as the evolution between such states, and our Tigum Research Group developed a holter device with 12 channels and advanced computer software. This has been shown in different contexts with 100% sensitivity and specificity results.

Keywords: attractor , cardiac, entropy, holter, mathematical , prediction

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Authors: Leonardo Alfredo Mendoza, Cristian Munoz, Marco Aurelio Pacheco, Manoela Kohler, Evelyn Batista, Rodrigo Moura

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Natural Language Processing (NLP) techniques are increasingly more powerful to be able to interpret the feelings and reactions of a person to a product or service. Sentiment analysis has become a fundamental tool for this interpretation but has few applications in languages other than English. This paper presents a classification of sentiment analysis in Portuguese with a base of comments from social networks in Portuguese. A word embedding's representation was used with a 50-Dimension GloVe pre-trained model, generated through a corpus completely in Portuguese. To generate this classification, the bidirectional long short-term memory and bidirectional Gated Recurrent Unit (GRU) models are used, reaching results of 99.1%.

Keywords: natural processing language, sentiment analysis, bidirectional long short-term memory, BI-LSTM, gated recurrent unit, GRU

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

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