Search results for: node classification

Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: Alexander Zotov, Ilkin Osmanov, Emil Sakharov, Oleg Shelest, Aleksander Troitskiy, Robert Khabazov

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Objective: Thoracoscopic surgical ablation of atrial fibrillation (AF) includes two technologies in performing of operation. 1st strategy used is the AtriCure device (bipolar, nonirrigated, non clamping), 2nd strategy is- the Medtronic device (bipolar, irrigated, clamping). The study presents a comparative analysis of clinical outcomes of two strategies in thoracoscopic ablation of AF using AtriCure vs. Medtronic devices. Methods: In 2 center study, 123 patients underwent thoracoscopic ablation of AF for the period from 2016 to 2020. Patients were divided into two groups. The first group is represented by patients who applied the AtriCure device (N=63), and the second group is - the Medtronic device (N=60), respectively. Patients were comparable in age, gender, and initial severity of the condition. Among the patients, in group 1 were 65% males with a median age of 57 years, while in group 2 – 75% and 60 years, respectively. Group 1 included patients with paroxysmal form -14,3%, persistent form - 68,3%, long-standing persistent form – 17,5%, group 2 – 13,3%, 13,3% and 73,3% respectively. Median ejection fraction and indexed left atrial volume amounted in group 1 – 63% and 40,6 ml/m2, in group 2 - 56% and 40,5 ml/m2. In addition, group 1 consisted of 39,7% patients with chronic heart failure (NYHA Class II) and 4,8% with chronic heart failure (NYHA Class III), when in group 2 – 45% and 6,7%, respectively. Follow-up consisted of laboratory tests, chest Х-ray, ECG, 24-hour Holter monitor, and cardiopulmonary exercise test. Duration of freedom from AF, distant mortality rate, and prevalence of cerebrovascular events were compared between the two groups. Results: Exit block was achieved in all patients. According to the Clavien-Dindo classification of surgical complications fraction of adverse events was 14,3% and 16,7% (1st group and 2nd group, respectively). Mean follow-up period in the 1st group was 50,4 (31,8; 64,8) months, in 2nd group - 30,5 (14,1; 37,5) months (P=0,0001). In group 1 - total freedom of AF was in 73,3% of patients, among which 25% had additional antiarrhythmic drugs (AADs) therapy or catheter ablation (CA), in group 2 – 90% and 18,3%, respectively (for total freedom of AF P<0,02). At follow-up, the distant mortality rate in the 1st group was – 4,8%, and in the 2nd – no fatal events. Prevalence of cerebrovascular events was higher in the 1st group than in the 2nd (6,7% vs. 1,7% respectively). Conclusions: Despite the relatively shorter follow-up of the 2nd group in the study, applying the strategy using the Medtronic device showed quite encouraging results. Further research is needed to evaluate the effectiveness of this strategy in the long-term period.

Keywords: atrial fibrillation, clamping, ablation, thoracoscopic surgery

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Authors: Liane J. Ioannou, Jonathan Serpell, Cino Bendinelli, David Walters, Jenny Gough, Dean Lisewski, Win Meyer-Rochow, Julie Miller, Duncan Topliss, Bill Fleming, Stephen Farrell, Andrew Kiu, James Kollias, Mark Sywak, Adam Aniss, Linda Fenton, Danielle Ghusn, Simon Harper, Aleksandra Popadich, Kate Stringer, David Watters, Susannah Ahern

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BACKGROUND: There are significant variations in the management, treatment and outcomes of thyroid cancer, particularly in the role of: diagnostic investigation and pre-treatment scanning; optimal extent of surgery (total or hemi-thyroidectomy); use of active surveillance for small low-risk cancers; central lymph node dissections (therapeutic or prophylactic); outcomes following surgery (e.g. recurrent laryngeal nerve palsy, hypocalcaemia, hypoparathyroidism); post-surgical hormone, calcium and vitamin D therapy; and provision and dosage of radioactive iodine treatment. A proven strategy to reduce variations in the outcome and to improve survival is to measure and compare it using high-quality clinical registry data. Clinical registries provide the most effective means of collecting high-quality data and are a tool for quality improvement. Where they have been introduced at a state or national level, registries have become one of the most clinically valued tools for quality improvement. To benchmark clinical care, clinical quality registries require systematic measurement at predefined intervals and the capacity to report back information to participating clinical units. OBJECTIVE: The aim of this study was to develop a core set clinical indicators that enable measurement and reporting of quality of care for patients with thyroid cancer. We hypothesise that measuring clinical quality indicators, developed to identify differences in quality of care across sites, will reduce variation and improve patient outcomes and survival, thereby lessening costs and healthcare burden to the Australian community. METHOD: Preparatory work and scoping was conducted to identify existing high quality, clinical guidelines and best practice for thyroid cancer both nationally and internationally, as well as relevant literature. A bi-national panel was invited to participate in a modified Delphi process. Panelists were asked to rate each proposed indicator on a Likert scale of 1–9 in a three-round iterative process. RESULTS: A total of 236 potential quality indicators were identified. One hundred and ninety-two indicators were removed to reflect the data capture by the Australian and New Zealand Thyroid Cancer Registry (ANZTCR) (from diagnosis to 90-days post-surgery). The remaining 44 indicators were presented to the panelists for voting. A further 21 indicators were later added by the panelists bringing the total potential quality indicators to 65. Of these, 21 were considered the most important and feasible indicators to measure quality of care in thyroid cancer, of which 12 were recommended for inclusion in the final set. The consensus indicator set spans the spectrum of care, including: preoperative; surgery; surgical complications; staging and post-surgical treatment planning; and post-surgical treatment. CONCLUSIONS: This study provides a core set of quality indicators to measure quality of care in thyroid cancer. This indicator set can be applied as a tool for internal quality improvement, comparative quality reporting, public reporting and research. Inclusion of these quality indicators into monitoring databases such as clinical quality registries will enable opportunities for benchmarking and feedback on best practice care to clinicians involved in the management of thyroid cancer.

Keywords: clinical registry, Delphi survey, quality indicators, quality of care

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Authors: Anna Rudzińska, Katarzyna Szklener, Pola Juchaniuk, Anna Rodzajweska, Katarzyna Machulska-Ciuraj, Monika Rychlik- Grabowska, Michał łOziński, Agnieszka Kolak-Bruks, SłAwomir Mańdziuk

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Introduction: Immune checkpoint inhibition (ICI) belongs to the modern forms of anti-cancer treatment. Due to the constant development and continuous research in the field of ICI, many aspects of the treatment are yet to be discovered. One of the less researched aspects of ICI treatment is the influence of the adverse effects on the treatment success rate. It is suspected that adverse events in the course of the ICI treatment indicate a better response rate and correlate with longer progression-free- survival. Methodology: The research was conducted with the usage of the documentation of the Department of Clinical Oncology and Chemotherapy. Data of the patients with a lung cancer diagnosis who were treated between 2019-2022 and received ICI treatment were analyzed. Results: Out of over 133 patients whose data was analyzed, the vast majority were diagnosed with non-small cell lung cancer. The majority of the patients did not experience adverse effects. Most adverse effects reported were classified as grade 1 or grade 2 according to CTCAE classification. Most adverse effects involved skin, thyroid and liver toxicity. Statistical significance was found for the adverse effect incidence and overall survival (OS) and progression-free survival (PFS) (p=0,0263) and for the time of toxicity onset and OS and PFS (p<0,001). The number of toxicity sites was statistically significant for prolonged PFS (p=0.0315). The highest OS was noted in the group presenting grade 1 and grade 2 adverse effects. Conclusions: Obtained results confirm the existence of the prolonged OS and PFS in the adverse-effects-charged patients, mostly in the group presenting mild to intermediate (Grade 1 and Grade 2) adverse effects and late toxicity onset. Simultaneously our results suggest a correlation between treatment response rate and the toxicity grade of the adverse effects and the time of the toxicity onset. Similar results were obtained in several similar research conducted - with the proven tendency of better survival in mild and moderate toxicity; meanwhile, other studies in the area suggested an advantage in patients with any toxicity regardless of the grade. The contradictory results strongly suggest the need for further research on this topic, with a focus on additional factors influencing the course of the treatment.

Keywords: adverse effects, immunotherapy, lung cancer, PD-1/PD-L1 inhibitors

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Authors: Dumont Maxime, Correia Carlos, Sauvage Jean-François, Schwartz Noah, Gray Morgan

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Context: The concept of the segmented telescope is unavoidable to build extremely large telescopes (ELT) in the quest for spatial resolution, but it also allows one to fit a large telescope within a reduced volume of space (JWST) or into an even smaller volume (Standard Cubesat). Cubesats have tight constraints on the computational burden available and the small payload volume allowed. At the same time, they undergo thermal gradients leading to large and evolving optical aberrations. The pupil segmentation comes nevertheless with an obvious difficulty: to co-phase the different segments. The CubeSat constraints prevent the use of a dedicated wavefront sensor (WFS), making the focal-plane images acquired by the science detector the most practical alternative. Yet, one of the challenges for the wavefront sensing is the non-linearity between the image intensity and the phase aberrations. Plus, for Earth observation, the object is unknown and unrepeatable. Recently, several studies have suggested Neural Networks (NN) for wavefront sensing; especially convolutional NN, which are well known for being non-linear and image-friendly problem solvers. Aims: We study in this paper the prospect of using NN to measure the phasing aberrations of a segmented pupil from the focal-plane image directly without a dedicated wavefront sensing. Methods: In our application, we take the case of a deployable telescope fitting in a CubeSat for Earth observations which triples the aperture size (compared to the 10cm CubeSat standard) and therefore triples the angular resolution capacity. In order to reach the diffraction-limited regime in the visible wavelength, typically, a wavefront error below lambda/50 is required. The telescope focal-plane detector, used for imaging, will be used as a wavefront-sensor. In this work, we study a point source, i.e. the Point Spread Function [PSF] of the optical system as an input of a VGG-net neural network, an architecture designed for image regression/classification. Results: This approach shows some promising results (about 2nm RMS, which is sub lambda/50 of residual WFE with 40-100nm RMS of input WFE) using a relatively fast computational time less than 30 ms which translates a small computation burder. These results allow one further study for higher aberrations and noise.

Keywords: wavefront sensing, deep learning, deployable telescope, space telescope

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Authors: Lou-Hon Sun, Yu-Ming Chiu, Chen-Wei Tao, Chia-Yun Tsai

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It is common practice for many companies to ask employees to provide heart-touching service for customers and to emphasize the attitude of 'customer first'. However, services may not necessarily gain praise, and may actually be considered excessive, if customers do not appreciate such behaviors. In reality, many restaurant businesses try to provide as much service as possible without taking into account whether over-provision may lead to negative customer reception. A survey of 894 people in Britain revealed that 49 percent of respondents consider over-attentive waiters the most annoying aspect of dining out. It can be seen that merely aiming to exceed customers’ expectations without actually addressing their needs, only further distances and dissociates the standard of services from the goals of customer satisfaction itself. Over-service is defined, as 'service provided that exceeds customer expectations, or simply that customers deemed redundant, resulting in negative perception'. It was found that customers’ reactions and complaints concerning over-service are not as intense as those against service failures caused by the inability to meet expectations; consequently, it is more difficult for managers to become aware of the existence of over-service. Thus the ability to manage over-service behaviors is a significant topic for consideration. The Kano model classifies customer preferences into five categories: attractive quality attribute, one-dimensional quality attribute, must-be quality attribute, indifferent quality attribute and reverse quality attributes. The model is still very popular for researchers to explore the quality aspects and customer satisfaction. Nevertheless, several studies indicated that Kano’s model could not fully capture the nature of service quality. The concept of over-service can be used to restructure the model and provide a better understanding of the service quality construct. In this research, the structure of Kano's two-dimensional questionnaire will be used to classify the factors into different dimensions. The same questions will be used in the second questionnaire for identifying the over-service experienced of the respondents. The finding of these two questionnaires will be used to analyze the relevance between service quality classification and over-service behaviors. The subjects of this research are customers of fine dining chain restaurants. Three hundred questionnaires will be issued based on the stratified random sampling method. Items for measurement will be derived from DINESERV scale. The tangible dimension of the questionnaire will be eliminated due to this research is focused on the employee behaviors. Quality attributes of the Kano model are often regarded as an instrument for improving customer satisfaction. The concept of over-service can be used to restructure the model and provide a better understanding of service quality construct. The extension of the Kano model will not only develop a better understanding of customer needs and expectations but also enhance the management of service quality.

Keywords: consumer satisfaction, DINESERV, kano model, over-service

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Authors: Pavana Basavakumar, Devadas Bhat

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Diabetes is a disease which often goes undiagnosed until its secondary effects are noticed. Early detection of the disease is necessary to avoid serious consequences which could lead to the death of the patient. Conventional invasive tests for screening of diabetes are mostly painful, time consuming and expensive. There’s also a risk of infection involved, therefore it is very essential to develop non-invasive methods to screen and estimate the level of blood glucose. Extensive research is going on with this perspective, involving various techniques that explore optical, electrical, chemical and thermal properties of the human body that directly or indirectly depend on the blood glucose concentration. Thus, non-invasive blood glucose monitoring has grown into a vast field of research. In this project, an attempt was made to device a prototype for screening of diabetes by measuring electrical impedance of the skin and building a model to predict a patient’s condition based on the measured impedance. The prototype developed, passes a negligible amount of constant current (0.5mA) across a subject’s index finger through tetra polar silver electrodes and measures output voltage across a wide range of frequencies (10 KHz – 4 MHz). The measured voltage is proportional to the impedance of the skin. The impedance was acquired in real-time for further analysis. Study was conducted on over 75 subjects with permission from the institutional ethics committee, along with impedance, subject’s blood glucose values were also noted, using conventional method. Nonlinear regression analysis was performed on the features extracted from the impedance data to obtain a model that predicts blood glucose values for a given set of features. When the predicted data was depicted on Clarke’s Error Grid, only 58% of the values predicted were clinically acceptable. Since the objective of the project was to screen diabetes and not actual estimation of blood glucose, the data was classified into three classes ‘NORMAL FASTING’,’NORMAL POSTPRANDIAL’ and ‘HIGH’ using linear Support Vector Machine (SVM). Classification accuracy obtained was 91.4%. The developed prototype was economical, fast and pain free. Thus, it can be used for mass screening of diabetes.

Keywords: Clarke’s error grid, electrical impedance of skin, linear SVM, nonlinear regression, non-invasive blood glucose monitoring, screening device for diabetes

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Authors: Gulnara Galeeva, Yulia Kasperskaya

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The study deals with the relevant problem related to the formation of the efficient investment portfolio of an enterprise. The structure of the investment portfolio is connected to the degree of influence of intangible assets on the enterprise’s income. This determines the importance of research on the content of intangible assets. However, intangible assets studies do not take into consideration how the enterprise state can affect the content and the importance of intangible assets for the enterprise`s income. This affects accurateness of the calculations. In order to study this problem, the research was divided into several stages. In the first stage, intangible assets were classified based on their synergies as the underlying intangibles and the additional intangibles. In the second stage, this classification was applied. It showed that the lifecycle model and the theory of abrupt development of the enterprise, that are taken into account while designing investment projects, constitute limit cases of a more general theory of bifurcations. The research identified that the qualitative content of intangible assets significant depends on how close the enterprise is to being in crisis. In the third stage, the author developed and applied the Wide Pairwise Comparison Matrix method. This allowed to establish that using the ratio of the standard deviation to the mean value of the elements of the vector of priority of intangible assets makes it possible to estimate the probability of a full-blown crisis of the enterprise. The author has identified a criterion, which allows making fundamental decisions on investment feasibility. The study also developed an additional rapid method of assessing the enterprise overall status based on using the questionnaire survey with its Director. The questionnaire consists only of two questions. The research specifically focused on the fundamental role of stochastic resonance in the emergence of bifurcation (crisis) in the economic development of the enterprise. The synergetic approach made it possible to describe the mechanism of the crisis start in details and also to identify a range of universal ways of overcoming the crisis. It was outlined that the structure of intangible assets transforms into a more organized state with the strengthened synchronization of all processes as a result of the impact of the sporadic (white) noise. Obtained results offer managers and business owners a simple and an affordable method of investment portfolio optimization, which takes into account how close the enterprise is to a state of a full-blown crisis.

Keywords: analytic hierarchy process, bifurcation, investment portfolio, intangible assets, wide matrix

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Authors: Jayeola A. O., Ayodele O. S., Olususi J. I.

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From field studies, six (6) lithological units were identified to be common around the study area, which includes quartzites, granites, granite gneiss, porphyritic granites, amphibolite and pegmatites. Petrographical analysis was done to establish the major mineral assemblages and accessory minerals present in selected rock samples, which represents the major rock types in the area. For the purpose of this study, twenty (20) pulverized rock samples were taken to the laboratory for geochemical analysis with their results used in the classification, as well as suggest the geochemical attributes of the rocks. Results from petrographical studies of the rocks under both plane and cross polarized lights revealed the major minerals identified under thin sections to include quartz, feldspar, biotite, hornblende, plagioclase and muscovite with opaque other accessory minerals, which include actinolite, spinel and myrmekite. Geochemical results obtained and interpreted using various geochemical plots or discrimination plots all classified the rocks in the area as belonging to both the peralkaline metaluminous and peraluminous types. Results for the major oxides ratios produced for Na₂O/K₂O, Al₂O₃/Na₂O + CaO + K₂O and Na₂O + CaO + K₂O/Al₂O₃ show the excess of alumina, Al₂O₃ over the alkaline Na₂O +CaO +K₂O thus suggesting peraluminous rocks. While the excess of the alkali over the alumina suggests the peralkaline metaluminous rock type. The results of correlation coefficient show a perfect strong positive correlation, which shows that they are of same geogenic sources, while negative correlation coefficient values indicate a perfect weak negative correlation, suggesting that they are of heterogeneous geogenic sources. From factor analysis, five component groups were identified as Group 1 consists of Ag-Cr-Ni elemental associations suggesting Ag, Cr, and Ni mineralization, predicting the possibility of sulphide mineralization. in the study area. Group ll and lll consist of As-Ni-Hg-Fe-Sn-Co-Pb-Hg element association, which are pathfinder elements to the mineralization of gold. Group 1V and V consist of Cd-Cu-Ag-Co-Zn, which concentrations are significant to elemental associations and mineralization. In conclusion, from the potassium radiometric anomaly map produced, the eastern section (northeastern and southeastern) is observed to be the hot spot and mineralization zone for the study area.

Keywords: petrography, Ila Orangun, petrochemistry, pegmatites, peraluminous

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Authors: Castillo-Acevedo J, Mena-Rivero R, Silva-Poot H

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In Mexico, as largely of the developing countries, the rural housing is a study object, since the diversity of constructive idiosyncrasies for locality, involves various factors that make it vulnerable; an important aspect of study is the progressive deterioration that is seen in the rural housing. Various social programs, contribute financial resources in the field of housing to provide support for families living in rural areas, however, they do not provide a coordination with the self-construction that is usually the way in which is built in these areas. The present study, exposes the physical situation and an economic assessment that presents the rural self-constructed housing in three rural communities in the south of the state of Quintana Roo, Mexico, which were built with funding from federal social programs. The information compilation was carried out in a period of seven months in which there was used the intentional sampling of typical cases, where the object study was the housing constructed with supports of the program “Rural Housing” between the year 2009 and 2014. Instruments were used as the interview, ballot papers of observation, ballot papers of technical verification and various measuring equipment laboratory for the classification of pathologies; for the determination of some pathologies constructive Mexican standards were applied how NMX-C-192-ONNCCE, NMX-C-111-ONNCCE, NMX-C-404-ONNCCE and finally used the software of Opus CMS ® with the help of tables of the National Consumer Price Index (CPI) for update of costs and wages according to the line of being applied in Mexico, were used for an economic valuation. The results show 11 different constructive pathologies and exposes greater presence with the 22.50% to the segregation of the concrete; the economic assessment shows that 80% of self-constructed housing, exceed the cost of construction it would have compared to a similar dwelling built by a construction company; It is also exposed to the 46.10% of the universe of study represent economic losses in materials to the social activities by houses not built. The system of self-construction used by the social programs, affect to some extent the program objectives applied in underserved areas, as implicit and additional costs affect the economic capacity of beneficiaries who invest time and effort in an activity that are not specialists, which this research provides foundations for sustainable alternatives or possibly eliminate the practice of self-construction of implemented social programs in marginalized rural communities in the south of state of Quintana Roo, Mexico.

Keywords: economic valuation, pathologies constructive, rural housing, social programs

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Authors: Bechir Hbibi, Lamine Mili

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Understanding the condition of comatose patients can be difficult, but it is crucial to their optimal treatment. Consequently, numerous scoring systems have been developed around the world to categorize patient states based on physiological assessments. Although validated and widely adopted by medical communities, these scores still present numerous limitations and obstacles. Even with the addition of additional tests and extensions, these scoring systems have not been able to overcome certain limitations, and it appears unlikely that they will be able to do so in the future. On the other hand, physiological tests are not the only way to extract ideas about comatose patients. EEG signal analysis has helped extensively to understand the human brain and human consciousness and has been used by researchers in the classification of different levels of disease. The use of EEG in the ICU has become an urgent matter in several cases and has been recommended by medical organizations. In this field, the EEG is used to investigate epilepsy, dementia, brain injuries, and many other neurological disorders. It has recently also been used to detect pain activity in some regions of the brain, for the detection of stress levels, and to evaluate sleep quality. In our recent findings, our aim was to use multifractal analysis, a very successful method of handling multifractal signals and feature extraction, to establish a state of awareness scale for comatose patients based on their electrical brain activity. The results show that this score could be instantaneous and could overcome many limitations with which the physiological scales stock. On the contrary, multifractal analysis stands out as a highly effective tool for characterizing non-stationary and self-similar signals. It demonstrates strong performance in extracting the properties of fractal and multifractal data, including signals and images. As such, we leverage this method, along with other features derived from EEG signal recordings from comatose patients, to develop a scale. This scale aims to accurately depict the vigilance state of patients in intensive care units and to address many of the limitations inherent in physiological scales such as the Glasgow Coma Scale (GCS) and the FOUR score. The results of applying version V0 of this approach to 30 patients with known GCS showed that the EEG-based score similarly describes the states of vigilance but distinguishes between the states of 8 sedated patients where the GCS could not be applied. Therefore, our approach could show promising results with patients with disabilities, injected with painkillers, and other categories where physiological scores could not be applied.

Keywords: coma, vigilance state, EEG, multifractal analysis, feature extraction

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Authors: Nadia E. Christiana, Azzahra A. N. Ginting, Ardhito Nurcahya, Havisa P. Novira

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One of the quickest ways to do a short trip in urban areas is by walking, either individually, in couple or groups. Walkability nowadays becomes one of the parameters to measure the quality of an urban neighborhood. As a Central Business District and public transport transit hub, Dukuh Atas area becomes one of the highest numbers of commuters that pass by the area and interchange between transportation modes daily. Thus, as a public transport hub, a lot of investment should be focused to speed up the development of the area that would support urban transit activity between transportation modes, one of them is revitalizing pedestrian walkways. The purpose of this research is to formulate the visual design concept of 'Walkable City' based on the results of the observation and a series of rankings. To achieve this objective, it is necessary to accomplish several stages of the research that consists of (1) Identifying the system of pedestrian paths in Dukuh Atas area using descriptive qualitative method (2) Analyzing the sidewalk walkability rate according to the perception and the walkability satisfaction rate using the characteristics of pedestrians and non-pedestrians in Dukuh Atas area by using Global Walkability Index analysis and Multicriteria Satisfaction Analysis (3) Analyzing the factors that determine the integration of pedestrian walkways in Dukuh Atas area using descriptive qualitative method. The results achieved in this study is that the walkability level of Dukuh Atas corridor area is 44.45 where the value is included in the classification of 25-49, which is a bit of facility that can be reached by foot. Furthermore, based on the questionnaire, satisfaction rate of pedestrian walkway in Dukuh Atas area reached a number of 64%. It is concluded that commuters have not been fully satisfied with the condition of the sidewalk. Besides, the factors that influence the integration in Dukuh Atas area have been reasonable as it is supported by the utilization of land and modes such as KRL, Busway, and MRT. From the results of all analyzes conducted, the visual design and the application of the concept of walkable city along the pathway pedestrian corridor of Dukuh Atas area are formulated. Achievement of the results of this study amounted to 80% which needs to be done further review of the results of the analysis. The work of this research is expected to be a recommendation or input for the government in the development of pedestrian paths in maximizing the use of public transportation modes.

Keywords: design, global walkability index, mass rapid transit, walkable city

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Authors: Amandeep Kaur, Ns Atri, Munruchi Kaur

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Mushrooms have shaped our environment in ways that we are only beginning to understand. The weather patterns, topography, flora and fauna of Punjab state in India create favorable growing conditions for thousands of species of mushrooms, but the complete region was unexplored when it comes to coprophilous mushrooms growing on herbivorous dung. Coprophilous mushrooms are the most specialized fungi ecologically, which germinate and grow directly on different types of animal dung or on manured soil. In the present work, the diversity of coprophilous mushrooms' of Family Psathyrellaceae of the order Agaricales is explored, their relationship to the human world is sketched out, and their supreme significance to life on this planet is revealed. During the investigation, different dung localities from 16 districts of Punjab state have been explored for the collection of material. The macroscopic features of the collected mushrooms were documented on the Field key. The hand cut sections of the various parts of carpophore, such as pileus, gills, stipe and the basidiospores details, were studied microscopically under different magnification. Various authentic publications were consulted for the identification of the investigated taxa. The classification, authentic names and synonyms of the investigated taxa are as per the latest version of Dictionary of Fungi and the MycoBank. The present work deals with the taxonomy of 81 collections belonging to 39 species spread over 05 coprophilous genera, namely Psathyrella, Panaeolus, Parasola, Coprinopsis, and Coprinellus of family Psathyrellaceae. In the text, the investigated taxa have been arranged as they appear in the key to the genera and species investigated. In this work, have been thoroughly examined for their macroscopic, microscopic, ecological, and chemical reaction details. The authors dig deeper to give indication of their ecology and the dung type where they can be obtained. Each taxon is accompanied by a detailed listing of its prominent features and an illustration with habitat photographs and line drawings of morphological and anatomical features. Taxa are organized as per their status in the keys, which allow easy recognition. All the taxa are compared with similar taxa. The study has shown that dung is an important substrate which serves as a favorable niche for the growth of a variety of mushrooms. This paper shows an insight what short-lived coprophilous mushrooms can teach us about sustaining life on earth!

Keywords: abundance, basidiomycota, biodiversity, seasonal availability, systematics

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Authors: Nicholas S. Norbert Jr., John E. Bischoff, Christopher J. Willy

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Knowledge Management (KM) is globally recognized as a crucial element in securing competitive advantage through building and maintaining organizational memory, codifying and protecting intellectual capital and business intelligence, and providing mechanisms for collaboration and innovation. KM frameworks and approaches have been developed and defined identifying critical success factors for conducting KM within numerous industries ranging from scientific to business, and for ranges of organization scales from small groups to large enterprises. However, engineering and technical teams operating within restricted environments are subject to unique barriers and KM challenges which cannot be directly treated using the approaches and tools prescribed for other industries. This research identifies barriers in conducting KM within Hardware Development Engineering (HDE) teams and statistically compares significance to barriers upholding the four KM pillars of organization, technology, leadership, and learning for HDE teams. HDE teams suffer from restrictions in knowledge sharing (KS) due to classification of information (national security risks), customer proprietary restrictions (non-disclosure agreement execution for designs), types of knowledge, complexity of knowledge to be shared, and knowledge seeker expertise. As KM evolved leveraging information technology (IT) and web-based tools and approaches from Web 1.0 to Enterprise 2.0, KM may also seek to leverage emergent tools and analytics including expert locators and hybrid recommender systems to enable KS across barriers of the technical teams. The research will test hypothesis statistically evaluating if KM barriers for HDE teams affect the general set of expected benefits of a KM System identified through previous research. If correlations may be identified, then generalizations of success factors and approaches may also be garnered for HDE teams. Expert elicitation will be conducted using a questionnaire hosted on the internet and delivered to a panel of experts including engineering managers, principal and lead engineers, senior systems engineers, and knowledge management experts. The feedback to the questionnaire will be processed using analysis of variance (ANOVA) to identify and rank statistically significant barriers of HDE teams within the four KM pillars. Subsequently, KM approaches will be recommended for upholding the KM pillars within restricted environments of HDE teams.

Keywords: engineering management, knowledge barriers, knowledge management, knowledge sharing

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Forensic DNA analysis has received much attention over the last three decades, due to its incredible usefulness in human identification. The statistical interpretation of DNA evidence is recognised as one of the most mature fields in forensic science. Peak heights in an Electropherogram (EPG) are approximately proportional to the amount of template DNA in the original sample being tested. A stutter is a minor peak in an EPG, which is not masking as an allele of a potential contributor, and considered as an artefact that is presumed to be arisen due to miscopying or slippage during the PCR. Stutter peaks are mostly analysed in terms of stutter ratio that is calculated relative to the corresponding parent allele height. Analysis of mixture profiles has always been problematic in evidence interpretation, especially with the presence of PCR artefacts like stutters. Unlike binary and semi-continuous models; continuous models assign a probability (as a continuous weight) for each possible genotype combination, and significantly enhances the use of continuous peak height information resulting in more efficient reliable interpretations. Therefore, the presence of a sound methodology to distinguish between stutters and real alleles is essential for the accuracy of the interpretation. Sensibly, any such method has to be able to focus on modelling stutter peaks. Bayesian nonparametric methods provide increased flexibility in applied statistical modelling. Mixture models are frequently employed as fundamental data analysis tools in clustering and classification of data and assume unidentified heterogeneous sources for data. In model-based clustering, each unknown source is reflected by a cluster, and the clusters are modelled using parametric models. Specifying the number of components in finite mixture models, however, is practically difficult even though the calculations are relatively simple. Infinite mixture models, in contrast, do not require the user to specify the number of components. Instead, a Dirichlet process, which is an infinite-dimensional generalization of the Dirichlet distribution, is used to deal with the problem of a number of components. Chinese restaurant process (CRP), Stick-breaking process and Pólya urn scheme are frequently used as Dirichlet priors in Bayesian mixture models. In this study, we illustrate an infinite mixture of simple linear regression models for modelling stutter ratio and introduce some modifications to overcome weaknesses associated with CRP.

Keywords: Chinese restaurant process, Dirichlet prior, infinite mixture model, PCR stutter

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Authors: Natalia Sypion-Dutkowska

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Abstract — The main research objective of the paper is to discover the relationship between the age groups of residents and crime in particular districts of a large city. The basic analytical tool is specific crime rates, calculated not in relation to the total population, but for age groups in a different social situation - property, housing, work, and representing different generations with different behavior patterns. They are the communities from which criminals and victims of crimes come. The analysis of literature and national police reports gives rise to hypotheses about the ability of a given age group to generate crime as a source of offenders and as a group of victims. These specific indicators are spatially differentiated, which makes it possible to detect socio-demographic determinants of spatial patterns of urban crime. A multi-feature classification of districts was also carried out, in which specific crime rates are the diagnostic features. In this way, areas with a similar structure of socio-demographic determinants of spatial patterns on urban crime were designated. The case study is the city of Szczecin in Poland. It has about 400,000 inhabitants and its area is about 300 sq km. Szczecin is located in the immediate vicinity of Germany and is the economic, academic and cultural capital of the region. It also has a seaport and an airport. Moreover, according to ESPON 2007, Szczecin is the Transnational and National Functional Urban Area. Szczecin is divided into 37 districts - auxiliary administrative units of the municipal government. The population of each of them in 2015-17 was divided into 8 age groups: babes (0-2 yrs.), children (3-11 yrs.), teens (12-17 yrs.), younger adults (18-30 yrs.), middle-age adults (31-45 yrs.), older adults (46-65 yrs.), early older (66-80) and late older (from 81 yrs.). The crimes reported in 2015-17 in each of the districts were divided into 10 groups: fights and beatings, other theft, car theft, robbery offenses, burglary into an apartment, break-in into a commercial facility, car break-in, break-in into other facilities, drug offenses, property damage. In total, 80 specific crime rates have been calculated for each of the districts. The analysis was carried out on an intra-city scale, this is a novel approach as this type of analysis is usually carried out at the national or regional level. Another innovative research approach is the use of specific crime rates in relation to age groups instead of standard crime rates. Acknowledgments: This research was funded by the National Science Centre, Poland, registration number 2019/35/D/HS4/02942.

Keywords: age groups, determinants of crime, spatial crime pattern, urban crime

Procedia PDF Downloads 171

Authors: Yarra Sulina, Nunna Tagore Sai Priya, Ankhi Banerjee

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With the rapid growth in tourist arrivals, there has been a huge demand for the growth of infrastructure in the destinations. With the increasing preference of tourists to stay near attractions, there has been a considerable change in the land use around tourist sites. However, with the inclusion of certain regulations and guidelines provided by the authorities based on the nature of tourism activity and geographical constraints, the pattern of growth of built form is different for various tourist sites. Therefore, this study explores the patterns of growth of built-up for a decade from 2009 to 2019 through two-dimensional and three-dimensional analysis. Land use maps are created through supervised classification of satellite images obtained from LANDSAT 4-5 and LANDSAT 8 for 2009 and 2019, respectively. The overall expansion of the built-up area in the region is analyzed in relation to the distance from the city's geographical center and the tourism-related growth regions are identified which are influenced by the proximity of tourist attractions. The primary tourist sites of various destinations with different geographical characteristics and tourism activities, that have undergone a significant increase in built-up area and are occupied with tourism-related infrastructure are selected for further study. Proximity analysis of the tourism-related growth sites is carried out to delineate the influence zone of the tourist site in a destination. Further, a temporal analysis of volumetric growth of built form is carried out to understand the morphology of the tourist precincts over time. The Digital Surface Model (DSM) and Digital Terrain Model (DTM) are used to extract the building footprints along with building height. Factors such as building height, and building density are evaluated to understand the patterns of three-dimensional growth of the built area in the region. The study also explores the underlying reasons for such changes in built form around various tourist sites and predicts the impact of such growth patterns in the region. The building height and building density around tourist site creates a huge impact on the appeal of the destination. The surroundings that are incompatible with the theme of the tourist site have a negative impact on the attractiveness of the destination that leads to negative feedback by the tourists, which is not a sustainable form of development. Therefore, proper spatial measures are necessary in terms of area and volume of the built environment for a healthy and sustainable environment around the tourist sites in the destination.

Keywords: sustainable tourism, growth patterns, land-use changes, 3-dimensional analysis of built-up area

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Authors: Orkide Donma, Mustafa M. Donma

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Obesity is associated with increased fat mass as well as fat percentage. Minerals are the elements, which are of vital importance. In this study, the relationships between body as well as bone mineral profile and the percentage as well as mass values of fat, fat-free portion, protein, skeletal muscle were evaluated in adult men with normal body mass index (N-BMI), and those classified according to different stages of obesity. A total of 103 adult men classified into five groups participated in this study. Ages were within 19-79 years range. Groups were N-BMI (Group 1), overweight (OW) (Group 2), first level of obesity (FLO) (Group 3), second level of obesity (SLO) (Group 4) and third level of obesity (TLO) (Group 5). Anthropometric measurements were performed. BMI values were calculated. Obesity degree, total body fat mass, fat percentage, basal metabolic rate (BMR), visceral adiposity, body mineral mass, body mineral percentage, bone mineral mass, bone mineral percentage, fat-free mass, fat-free percentage, protein mass, protein percentage, skeletal muscle mass and skeletal muscle percentage were determined by TANITA body composition monitor using bioelectrical impedance analysis technology. Statistical package (SPSS) for Windows Version 16.0 was used for statistical evaluations. The values below 0.05 were accepted as statistically significant. All the groups were matched based upon age (p > 0.05). BMI values were calculated as 22.6 ± 1.7 kg/m², 27.1 ± 1.4 kg/m², 32.0 ± 1.2 kg/m², 37.2 ± 1.8 kg/m², and 47.1 ± 6.1 kg/m² for groups 1, 2, 3, 4, and 5, respectively. Visceral adiposity and BMR values were also within an increasing trend. Percentage values of mineral, protein, fat-free portion and skeletal muscle masses were decreasing going from normal to TLO. Upon evaluation of the percentages of protein, fat-free portion and skeletal muscle, statistically significant differences were noted between NW and OW as well as OW and FLO (p < 0.05). However, such differences were not observed for body and bone mineral percentages. Correlation existed between visceral adiposity and BMI was stronger than that detected between visceral adiposity and obesity degree. Correlation between visceral adiposity and BMR was significant at the 0.05 level. Visceral adiposity was not correlated with body mineral mass but correlated with bone mineral mass whereas significant negative correlations were observed with percentages of these parameters (p < 0.001). BMR was not correlated with body mineral percentage whereas a negative correlation was found between BMR and bone mineral percentage (p < 0.01). It is interesting to note that mineral percentages of both body as well as bone are highly affected by the visceral adiposity. Bone mineral percentage was also associated with BMR. From these findings, it is plausible to state that minerals are highly associated with the critical stages of obesity as prominent parameters.

Keywords: bone, men, minerals, obesity

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Authors: Areti Angeliki Veroniki, Sofia Tsokani, Evangelos Paraskevaidis, Dimitris Mavridis

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The plethora of diagnostic test accuracy (DTA) studies has led to the increased use of systematic reviews and meta-analysis of DTA studies. Clinicians and healthcare professionals often consult DTA meta-analyses to make informed decisions regarding the optimum test to choose and use for a given setting. For example, the human papilloma virus (HPV) DNA, mRNA, and cytology can be used for the cervical intraepithelial neoplasia grade 2+ (CIN2+) diagnosis. But which test is the most accurate? Studies directly comparing test accuracy are not always available, and comparisons between multiple tests create a network of DTA studies that can be synthesized through a network meta-analysis of diagnostic tests (DTA-NMA). The aim is to summarize the DTA-NMA methods for at least three index tests presented in the methodological literature. We illustrate the application of the methods using a real data set for the comparative accuracy of HPV DNA, HPV mRNA, and cytology tests for cervical cancer. A search was conducted in PubMed, Web of Science, and Scopus from inception until the end of July 2019 to identify full-text research articles that describe a DTA-NMA method for three or more index tests. Since the joint classification of the results from one index against the results of another index test amongst those with the target condition and amongst those without the target condition are rarely reported in DTA studies, only methods requiring the 2x2 tables of the results of each index test against the reference standard were included. Studies of any design published in English were eligible for inclusion. Relevant unpublished material was also included. Ten relevant studies were finally included to evaluate their methodology. DTA-NMA methods that have been presented in the literature together with their advantages and disadvantages are described. In addition, using 37 studies for cervical cancer obtained from a published Cochrane review as a case study, an application of the identified DTA-NMA methods to determine the most promising test (in terms of sensitivity and specificity) for use as the best screening test to detect CIN2+ is presented. As a conclusion, different approaches for the comparative DTA meta-analysis of multiple tests may conclude to different results and hence may influence decision-making. Acknowledgment: This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Extension of Network Meta-Analysis for the Comparison of Diagnostic Tests ” (MIS 5047640).

Keywords: colposcopy, diagnostic test, HPV, network meta-analysis

Procedia PDF Downloads 139

Authors: Natalia Rudeli, Elisabeth Viles, Adrian Santilli

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Delays in the construction industry are a global phenomenon. Many construction projects experience extensive delays exceeding the initially estimated completion time. The main purpose of this study is to identify construction projects typical behaviors in order to develop a prognosis and management tool. Being able to know a construction projects schedule tendency will enable evidence-based decision-making to allow resolutions to be made before delays occur. This study presents an innovative approach that uses Cluster Analysis Method to support predictions during Earned Value Analyses. A clustering analysis was used to predict future scheduling, Earned Value Management (EVM), and Earned Schedule (ES) principal Indexes behaviors in construction projects. The analysis was made using a database with 90 different construction projects. It was validated with additional data extracted from literature and with another 15 contrasting projects. For all projects, planned and executed schedules were collected and the EVM and ES principal indexes were calculated. A complete linkage classification method was used. In this way, the cluster analysis made considers that the distance (or similarity) between two clusters must be measured by its most disparate elements, i.e. that the distance is given by the maximum span among its components. Finally, through the use of EVM and ES Indexes and Tukey and Fisher Pairwise Comparisons, the statistical dissimilarity was verified and four clusters were obtained. It can be said that construction projects show an average delay of 35% of its planned completion time. Furthermore, four typical behaviors were found and for each of the obtained clusters, the interim milestones and the necessary rhythms of construction were identified. In general, detected typical behaviors are: (1) Projects that perform a 5% of work advance in the first two tenths and maintain a constant rhythm until completion (greater than 10% for each remaining tenth), being able to finish on the initially estimated time. (2) Projects that start with an adequate construction rate but suffer minor delays culminating with a total delay of almost 27% of the planned time. (3) Projects which start with a performance below the planned rate and end up with an average delay of 64%, and (4) projects that begin with a poor performance, suffer great delays and end up with an average delay of a 120% of the planned completion time. The obtained clusters compose a tool to identify the behavior of new construction projects by comparing their current work performance to the validated database, thus allowing the correction of initial estimations towards more accurate completion schedules.

Keywords: cluster analysis, construction management, earned value, schedule

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Authors: Nina Ponikvar, Katja Zajc Kejžar

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While the positive impacts of heritage on a broad societal spectrum have long been recognized and measured, the economic effects of the heritage sector are often less visible and frequently underestimated. At macro level, economic effects are usually studied based on one of the two mainstream approach, i.e. either the multiplier approach or the value chain approach. Consequently, there is limited comparability of the empirical results due to the use of different methodological approach in the literature. Furthermore, it is also not clear on which criteria the used approach was selected. Our aim is to bring the attention to the difference in the scope of effects that are encompassed by the two most frequent methodological approaches to valuation of economic effects of cultural heritage on macroeconomic level, i.e. the multiplier approach and the value chain approach. We show that while the multiplier approach provides a systematic, theory-based view of economic impacts but requires more data and analysis, the value chain approach has less solid theoretical foundations and depends on the availability of appropriate data to identify the contribution of cultural heritage to other sectors. We conclude that the multiplier approach underestimates the economic impact of cultural heritage, mainly due to the narrow definition of cultural heritage in the statistical classification and the inability to identify part of the contribution of cultural heritage that is hidden in other sectors. Yet it is not possible to clearly determine whether the value chain method overestimates or underestimates the actual economic impact of cultural heritage since there is a risk that the direct effects are overestimated and double counted, but not all indirect and induced effects are considered. Accordingly, these two approaches are not substitutes but rather complementary. Consequently, a direct comparison of the estimated impacts is not possible and should not be done due to the different scope. To illustrate the difference of the impact assessment of the cultural heritage, we apply both approaches to the case of Slovenia in the 2015-2022 period and measure the economic impact of cultural heritage sector in terms of turnover, gross value added and employment. The empirical results clearly show that the estimation of the economic impact of a sector using the multiplier approach is more conservative, while the estimates based on value added capture a much broader range of impacts. According to the multiplier approach, each euro in cultural heritage sector generates an additional 0.14 euros in indirect effects and an additional 0.44 euros in induced effects. Based on the value-added approach, the indirect economic effect of the “narrow” heritage sectors is amplified by the impact of cultural heritage activities on other sectors. Accordingly, every euro of sales and every euro of gross value added in the cultural heritage sector generates approximately 6 euros of sales and 4 to 5 euros of value added in other sectors. In addition, each employee in the cultural heritage sector is linked to 4 to 5 jobs in other sectors.

Keywords: economic value of cultural heritage, multiplier approach, value chain approach, indirect effects, slovenia

Procedia PDF Downloads 75

Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Adham Al Yaari, Montaha Al Yaari, Ayman Al Yaari, Aayah Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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Introduction: Like many dialects, the Arabic dialect of Yemen (ADY) exhibited utterance phonemic distinction- vowel deletion, lengthening, and insertion- that were investigated using speakers from different dialectal backgrounds, with particular focus on the difference typically developing and achieving speakers and those suffering linguistic problems make. Phonological variations were found to be inevitable, suggesting further investigation of consonants to see to what extent they are prone to such phonemic changes. This study investigates the patterns of consonant substitution in ADY by examining if there is a clear-cut line between normal and pathological consonants to decide which of these consonants is substituted more. Methods: A total of hundred and twenty nine Yemeni male participants (age= 6-13) were enrolled in this study. Participants were preassigned into two groups (Articulation disorders (AD) group= 42 and typically developing and achieving group (TD) = 70), each of which consists of five sub-groups in decided sociolinguistic classification. In a 45 minute-session, 180 pictures of commonly used verbs (4 pics/m.) were presented to participants who were asked to impulsively describe these verbs before their production was psychoneurolinguistically and statistically analyzed. Results: There was a pattern of consonant substitution in some dialects that participants from both groups have in common: Voiceless consonants (/t/, /ṣ/,/s/, /ḥ, /k/, /ʃ/, /f//, and /k/) in northern and eastern dialects; voiced consonants (/q/, /gh/, /Ʒ/, /g/,/ḍ/, /b/, and /d/) in southern, eastern, western and central dialects; and voiceless and voiced consonants(/t/, /f/, /Ø/, /ṣ/, /s/, /q/, /gh/, /Ʒ/, /g/,/ḍ/, and /b/) in southern dialect. Voiceless consonants (/t/, /ṣ/,/s/, /ḥ, /k/, /ʃ/, /f//, /Ø/and /k/) found to be substituted more by ADY speakers of both AD and TD groups followed by voiced consonants (/q/, /gh/, /Ʒ/, /g/,/ḍ/,/d/ /b/, and /ð/), nasals (/m/, /n/), mute (/h/), semi-vowels (/w/ and /j/) and laterals (/l/ and /r/). Unexpectedly, a short vowel (/æ/) and two long vowels (/u: and /a:/) were found to substitute consonants in ADY both by AD and TD participants. Conclusions: AD and TD participants of ADY substitute consonants in their dialectal speech. Consonant substitution processes cover not only consonants but extend to include monophthongs. The finding that speakers of ADY substitute consonants in multisyllabic words is probably due to the fact that the sociolinguistic factor plays a pivotal role in the problematic substitution of consonants in ADY speakers. Larger longitudinal studies are necessary to further investigate the effect of sociolinguistic background on phonological variations, notably sound change in the speech of Yemeni TD speakers compared to those with linguistic impairments.

Keywords: consonant substitution, Arabic dialect of Yemen, phonetics, phonology, syllables, articulation disorders

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Authors: Bryan Clark B. Hernandez, Eugene C. Herrera, Kazuo Nadaoka

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Mangrove forests thriving in intertidal zones in tropical and subtropical regions of the world offer a range of ecosystem services including carbon storage and sequestration. They can regulate the detrimental effects of climate change due to carbon releases two to four times greater than that of mature tropical rainforests. Moreover, they are effective natural defenses against storm surges and tsunamis. However, their proliferation depends significantly on the prevailing hydroperiod at the coast. In the Philippines, these coastal ecosystems have been severely threatened with a 50% decline in areal extent observed from 1918 to 2010. The highest decline occurred in 1950 - 1972 when national policies encouraged the development of fisheries and aquaculture. With the intensive land use conversion upstream, changes in the freshwater-saltwater envelope at the coast may considerably impact mangrove growth conditions. This study investigates a developing urban watershed in Kalibo, Aklan province with a 220-hectare mangrove forest replanted for over 30 years from coastal mudflats. Since then, the mangrove forest was sustainably conserved and declared as protected areas. Hybrid land cover classification technique was used to classify Landsat images for years, 1990, 2010, and 2017. Digital elevation model utilized was Interferometric Synthetic Aperture Radar (IFSAR) with a 5-meter resolution to delineate the watersheds. Using numerical modelling techniques, the hydrologic and hydraulic analysis of the influence of land cover change to flow and sediment dynamics was simulated. While significant land cover change occurred upland, thereby increasing runoff and sediment loads, the mangrove forests abundance adjacent to the coasts for the urban watershed, was somehow sustained. However, significant alteration of the coastline was observed in Kalibo through the years, probably due to the massive land-use conversion upstream and significant replanting of mangroves downstream. Understanding the hydrologic-hydraulic response of these watersheds to change land cover is essential to helping local government and stakeholders facilitate better management of these mangrove ecosystems.

Keywords: coastal mangroves, hydrologic model, land cover change, Philippines

Procedia PDF Downloads 122

Authors: Dimitrios Tzilopoulos, Panagiotis Symeonidis, Michael Loufakis, Dimosthenis Ioannidis, Dimitrios Tzovaras

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The domestic film industry in Greece has traditionally relied heavily on state support. While film productions are crucial for the country's economy, it has not fully capitalized on attracting and promoting foreign productions. The lack of motivation, organized state support for attraction and licensing, and the absence of location scouting have hindered its potential. Although recent legislative changes have addressed the first two of these issues, the development of a comprehensive location database and a search engine that would effectively support location scouting at the pre-production location scouting is still in its early stages. In addition to the expected benefits of the film, television, marketing, and multimedia industries, a location-scouting service platform has the potential to yield significant financial gains locally and nationally. By promoting featured places like cultural and archaeological sites, natural monuments, and attraction points for visitors, it plays a vital role in both cultural promotion and facilitating tourism development. This study introduces LOCATION3, an internet platform revolutionizing film production location management. It interconnects location providers, film crews, and multimedia stakeholders, offering a comprehensive environment for seamless collaboration. The platform's central geodatabase (PostgreSQL) stores each location’s attributes, while web technologies like HTML, JavaScript, CSS, React.js, and Redux power the user-friendly interface. Advanced functionalities, utilizing deep learning models, developed in Python, are integrated via Node.js. Visual data presentation is achieved using the JS Leaflet library, delivering an interactive map experience. LOCATION3 sets a new standard, offering a range of essential features to enhance the management of film production locations. Firstly, it empowers users to effortlessly upload audiovisual material enriched with geospatial and temporal data, such as location coordinates, photographs, videos, 360-degree panoramas, and 3D location models. With the help of cutting-edge deep learning algorithms, the application automatically tags these materials, while users can also manually tag them. Moreover, the application allows users to record locations directly through its user-friendly mobile application. Users can then embark on seamless location searches, employing spatial or descriptive criteria. This intelligent search functionality considers a combination of relevant tags, dominant colors, architectural characteristics, emotional associations, and unique location traits. One of the application's standout features is the ability to explore locations by their visual similarity to other materials, facilitated by a reverse image search. Also, the interactive map serves as both a dynamic display for locations and a versatile filter, adapting to the user's preferences and effortlessly enhancing location searches. To further streamline the process, the application facilitates the creation of location lightboxes, enabling users to efficiently organize and share their content via email. Going above and beyond location management, the platform also provides invaluable liaison, matchmaking, and online marketplace services. This powerful functionality bridges the gap between visual and three-dimensional geospatial material providers, local agencies, film companies, production companies, etc. so that those interested in a specific location can access additional material beyond what is stored on the platform, as well as access production services supporting the functioning and completion of productions in a location (equipment provision, transportation, catering, accommodation, etc.).

Keywords: deep learning models, film industry, geospatial data management, location scouting

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Authors: Orkide Donma, Mustafa M. Donma

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Obesity may lead to growing serious health problems throughout the world. Vitamin D appears to play a role in cardiovascular and metabolic health. Vitamin D deficiency may add to derangements in human metabolic systems, particularly those of children. Childhood obesity is associated with an increased risk of chronic and sophisticated diseases. The aim of this study is to investigate associations as well as possible differences related to parameters affected by obesity and their relations with vitamin D status in obese (OB) and morbid obese (MO) children. This study included a total of 78 children. Of them, 41 and 37 were OB and MO, respectively. WHO BMI-for age percentiles were used for the classification of obesity. The values above 99 percentile were defined as MO. Those between 95 and 99 percentiles were included into OB group. Anthropometric measurements were recorded. Basal metabolic rates (BMRs) were measured. Vitamin D status is determined by the measurement of 25-hydroxy cholecalciferol [25- hydroxyvitamin D3, 25(OH)D] using high-performance liquid chromatography. Vitamin D status was evaluated as deficient, insufficient and sufficient. Values < 20.0 ng/ml, values between 20-30 ng/ml and values > 30.0 ng/ml were defined as vitamin D deficient, insufficient and sufficient, respectively. Optimal 25(OH)D level was defined as ≥ 30 ng/ml. SPSSx statistical package program was used for the evaluation of the data. The statistical significance degree was accepted as p < 0.05. Mean ages did not differ between the groups. Significantly increased body mass index (BMI), waist circumference (C) and neck C as well as significantly decreased fasting blood glucose (FBG) and vitamin D values were observed in MO group (p < 0.05). In OB group, 37.5% of the children were vitamin D deficient, and in MO group the corresponding value was 53.6%. No difference between the groups in terms of lipid profile, systolic blood pressure (SBP), diastolic blood pressure (DBP) and insulin values was noted. There was a severe statistical significance between FBG values of the groups (p < 0.001). Important correlations between BMI, waist C, hip C, neck C and both SBP as well as DBP were found in OB group. In MO group, correlations only with SBP were obtained. In a similar manner, in OB group, correlations were detected between SBP-BMR and DBP-BMR. However, in MO children, BMR correlated only with SBP. The associations of vitamin D with anthropometric indices as well as some lipid parameters were defined. In OB group BMI, waist C, hip C and triglycerides (TRG) were negatively correlated with vitamin D concentrations whereas none of them were detected in MO group. Vitamin D deficiency may contribute to the complications associated with childhood obesity. Loss of correlations between obesity indices-DBP, vitamin D-TRG, as well as relatively lower FBG values, observed in MO group point out that the emergence of MetS components starts during obesity state just before the transition to morbid obesity. Aside from its deficiency state, associations of vitamin D with anthropometric measurements, blood pressures and TRG should also be evaluated before the development of morbid obesity.

Keywords: children, morbid obesity, obesity, vitamin D

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Authors: Mona G. Alharbi

Abstract:

A new family of methionine-sulfoxide reductase (Msr) was recently discovered and was named free methionine sulfoxide reductase (fRMsr). This family includes enzymes with a reductase activity toward the free R isomer of a methionine sulfoxide substrate. The fRMsrs have a GAF domain topology, a domain, which was previously identified as having in some cases a cyclic nucleotide phosphodiesterase activity. The classification of fRMsrs as GAF domains revealed a new function can be added to the GAF domain family. Interestingly the four members identified in the fRMsr family share the GAF domain structure and the presence of three conserved cysteines in the active site with free R methionine sulfoxide substrate specificity. This thesis presents the crystal structures of reduced, free Met-SO substrate-bound and MES-bound forms of a new fRMsr from Burkholderia pseudomallei (BPSL2418). BPSL2418 was cloned, overexpressed and purified to enable protein crystallization. The crystallization trials for reduced, Met-SO-bound and MES-bound forms of BPSL2418 were prepared and reasonable crystals of each form were produced. The crystal structures of BPSL2418MES, BPSL2418Met-SO and BPSL2418Reduced were solved at 1.18, 1.4 and 2.0Å, respectively by molecular replacement. The BPSL2418MES crystal belongs to space group P 21 21 21 while BPSL2418Met-SO and BPSL2418Reduced crystals belong to space group P 1 21 1. All three forms share the GAF domain structure of six antiparallel β-strands and four α-helices with connecting loops. The antiparallel β-strands (β1, β2, β5 and β6) are located in the center of the BPSL2418 structure flanked on one side by a three α-helices (α1, α2 and α4) and on the other side by a (loop1, β3, loop2, α3, β4 loop4) unit where loop4 forms a capping flap and covers the active site. The structural comparison of the three forms of BPSL2418 indicates that the catalytically important cysteine is CYS109, where the resolving cysteine is CYS75, which forms a disulfide bond with CYS109. They also suggest that the third conserved cysteine in the active site, CYS85, which is located in α3, is a non-essential cysteine for the catalytic function but it may play a role in the binding of the substrate. The structural comparison of the three forms reveals that conformational changes appear in the active site particularly involving loop4 and CYS109 during catalysis. The 3D structure of BPSL2418 shows strong structure similarity to fRMsrs enzymes, which further suggests that BPSL2418 acts as a free Met-R-SO reductase and shares the catalytic mechanism of fRMsr family.

Keywords: Burkholderia pseudomallei, GAF domain protein, methionine sulfoxide reductase, protein crystallization

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Authors: Huinan Zhang, Wenjie Jiang

Abstract:

Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: Maris Eugênia Dela Rosa, Ana Luiza Menegatti Pavan, Marcela De Oliveira, Diana Rodrigues De Pina, Luis Carlos Vulcano

Abstract:

In medical veterinary as well as in human medicine, radiological study is essential for a safe diagnosis in clinical practice. Thus, the quality of radiographic image is crucial. In last year’s there has been an increasing substitution of image acquisition screen-film systems for computed radiology equipment (CR) without technical charts adequacy. Furthermore, to carry out a radiographic examination in veterinary patient is required human assistance for restraint this, which can compromise image quality by generating dose increasing to the animal, for Occupationally Exposed and also the increased cost to the institution. The image optimization procedure and construction of radiographic techniques are performed with the use of homogeneous phantoms. In this study, we sought to develop a homogeneous phantom of canine chest to be applied to the optimization of these images for the CR system. In carrying out the simulator was created a database with retrospectives chest images of computed tomography (CT) of the Veterinary Hospital of the Faculty of Veterinary Medicine and Animal Science - UNESP (FMVZ / Botucatu). Images were divided into four groups according to the animal weight employing classification by sizes proposed by Hoskins & Goldston. The thickness of biological tissues were quantified in a 80 animals, separated in groups of 20 animals according to their weights: (S) Small - equal to or less than 9.0 kg, (M) Medium - between 9.0 and 23.0 kg, (L) Large – between 23.1 and 40.0kg and (G) Giant – over 40.1 kg. Mean weight for group (S) was 6.5±2.0 kg, (M) 15.0±5.0 kg, (L) 32.0±5.5 kg and (G) 50.0 ±12.0 kg. An algorithm was developed in Matlab in order to classify and quantify biological tissues present in CT images and convert them in simulator materials. To classify tissues presents, the membership functions were created from the retrospective CT scans according to the type of tissue (adipose, muscle, bone trabecular or cortical and lung tissue). After conversion of the biologic tissue thickness in equivalent material thicknesses (acrylic simulating soft tissues, bone tissues simulated by aluminum and air to the lung) were obtained four different homogeneous phantoms, with (S) 5 cm of acrylic, 0,14 cm of aluminum and 1,8 cm of air; (M) 8,7 cm of acrylic, 0,2 cm of aluminum and 2,4 cm of air; (L) 10,6 cm of acrylic, 0,27 cm of aluminum and 3,1 cm of air and (G) 14,8 cm of acrylic, 0,33 cm of aluminum and 3,8 cm of air. The developed canine homogeneous phantom is a practical tool, which will be employed in future, works to optimize veterinary X-ray procedures.

Keywords: radiation protection, phantom, veterinary radiology, computed radiography

Procedia PDF Downloads 417