Search results for: CBI methods

Authors: Ya-Mei Chang

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This research is intended to apply spatio-temporal point process methods to the dengue fever data in Tainan. The spatio-temporal intensity function of the dataset is assumed to be separable. The kernel estimation is a widely used approach to estimate intensity functions. The intensity function is very helpful to study the relation of the spatio-temporal point process and some covariates. The covariate effects might be nonlinear. An nonparametric smoothing estimator is used to detect the nonlinearity of the covariate effects. A fitted parametric model could describe the influence of the covariates to the dengue fever. The correlation between the data points is detected by the K-function. The result of this research could provide useful information to help the government or the stakeholders making decisions.

Keywords: dengue fever, spatial point process, kernel estimation, covariate effect

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Authors: Aswathy Rajagopal

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Many research agendas addressed interesting questions concerning the extent and character of water transport and many others looked at various phenomenon of urban waterfront development. The paper explore to highlight the importance of Inland Water Transportation(IWT) and the need for further development of IWT regulatory framework and for synergy between the inland navigation institutions both at policy and expert levels by taking the Backwater system of Kerala, India as the demonstration site. The author seeks to highlight the hurdles faced in integrating water transportation, the interchange between water and land and the waterfront development. The aim of the research is to look at the tools and methods that can be applied for waterfront regeneration and end with suggestions for policies and design considerations to guide the physical development along the proposed Kottayam –Chenganassery arterial waterway.

Keywords: waterways, inland water transportation (IWT), urban policy, waterfront development, Kerala backwaters

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Authors: Mehdi Ameur, Ahmed Essakdi, Tamou Nasser

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The purpose of this paper is the analysis and modeling of the photovoltaic system with MPPT techniques. This system is developed by combining the models of established solar module and DC-DC converter with the algorithms of perturb and observe (P&O), incremental conductance (INC) and fuzzy logic controller(FLC). The system is simulated under different climate conditions and MPPT algorithms to determine the influence of these conditions on characteristic power-voltage of PV system. According to the comparisons of the simulation results, the photovoltaic system can extract the maximum power with precision and rapidity using the MPPT algorithms discussed in this paper.

Keywords: photovoltaic array, maximum power point tracking, MPPT, perturb and observe, P&O, incremental conductance, INC, hill climbing, HC, fuzzy logic controller, FLC

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Authors: O. Anan, D. Böhning, A. Maruotti

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The purpose of the study is to estimate the elusive target population size under a truncated count model that accounts for heterogeneity. The purposed estimator is based on the generalized Poisson distribution (GPD), which extends the Poisson distribution by adding a dispersion parameter. Thus, it becomes an useful model for capture-recapture data where concurrent events are not homogeneous. In addition, it can account for over-dispersion and under-dispersion. The ratios of neighboring frequency counts are used as a tool for investigating the validity of whether generalized Poisson or Poisson distribution. Since capture-recapture approaches do not provide the zero counts, the estimated parameters can be achieved by modifying the EM-algorithm technique for the zero-truncated generalized Poisson distribution. The properties and the comparative performance of proposed estimator were investigated through simulation studies. Furthermore, some empirical examples are represented insights on the behavior of the estimators.

Keywords: capture, recapture methods, ratio plot, heterogeneous population, zero-truncated count

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Authors: JoãO Paulo Estevam De Souza, Rob Dekkers

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Particularly for the space sector the inclusion of sustainability in product development poses considerable challenges for practitioners. Outcomes of action research at two companies in this sector demonstrate how this contemporary theme could be included in methods for product and process development; this was supported by wider focus groups involving more companies. The working together with practitioners brought to the fore that holistic product life-cycle thinking needs further development, especially when firms are suppliers to original equipment manufacturers. Furthermore, the findings indicate that the social aspect of the triple-bottom-line causes remains elusive for companies; to this purpose, some pathways based on the action research and focus groups are proposed.

Keywords: aerospace, action research, product development, product life-cycle, sustainability, triple bottom-line

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Authors: Shiyin He, Zheng Huang

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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

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Authors: V. Moser-Siegmeth, M. C. Gambal, M. Jelovcak, B. Prytek, I. Swietalsky, D. Würzl, C. Fida, V. Mühlegger

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Adaptability is the capacity to adjust without great difficulty to changing circumstances. Within our project, we aimed to detect whether older people living within a long-term care hospital lose the ability to adapt. Theoretical concepts are contradictory in their statements. There is also lack of evidence in the literature how the adaptability of older people changes over the time. Following research questions were generated: Are older residents of a long-term care facility able to adapt to changes within their daily routine? How long does it take for older people to adapt? The study was designed as a convergent parallel mixed method intervention study, carried out within a four-month period and took place within seven wards of a long-term care hospital. As a planned intervention, a change of meal-times was established. The inhabitants were surveyed with qualitative interviews and quantitative questionnaires and diaries before, during and after the intervention. In addition, a survey of the nursing staff was carried out in order to detect changes of the people they care for and how long it took them to adapt. Quantitative data was analysed with SPSS, qualitative data with a summarizing content analysis. The average age of the involved residents was 82 years, the average length of stay 45 months. The adaptation to new situations does not cause problems for older residents. 47% of the residents state that their everyday life has not changed by changing the meal times. 24% indicate ‘neither nor’ and only 18% respond that their daily life has changed considerably due to the changeover. The diaries of the residents, which were conducted over the entire period of investigation showed no changes with regard to increased or reduced activity. With regard to sleep quality, assessed with the Pittsburgh sleep quality index, there is little change in sleep behaviour compared to the two survey periods (pre-phase to follow-up phase) in the cross-table. The subjective sleep quality of the residents is not affected. The nursing staff points out that, with good information in advance, changes are not a problem. The ability to adapt to changes does not deteriorate with age or by moving into a long-term care facility. It only takes a few days to get used to new situations. This can be confirmed by the nursing staff. Although there are different determinants like the health status that might make an adjustment to new situations more difficult. In connection with the limitations, the small sample size of the quantitative data collection must be emphasized. Furthermore, the extent to which the quantitative and qualitative sample represents the total population, since only residents without cognitive impairments of selected units participated. The majority of the residents has cognitive impairments. It is important to discuss whether and how well the diary method is suitable for older people to examine their daily structure.

Keywords: adaptability, intervention study, mixed methods, nursing home residents

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Authors: Nadarajah I. Ramesh

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Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.

Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model

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Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

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An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

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Authors: R. Frikha, H. Kamoun

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Background:Chronicmyeloidleukemia (CML), a hematologicaldisease, ischaracterized by t (9; 22) and relatedoncogene BCR-ABL formation. Although Tyrosine kinase inhibitors (TKIs) have revolutionized the treatment of CML, resistanceoccurs and possibly médiates by mutation in severalgenesindependently of the bcr-abl1 kinase mechanism. it has been reportedthat JAK2V617F/BCR-ABL double positivitymaybe a potential marker of resistance in CML. Aims: This studywasinvestigated the JAK2V617F mutation in TKI-resistant CML patients. Methods: A retrospectivestudywasconducted in the Hospital University of Sfax, south of Tunisia, including all CML TKI-resistant patients. A Sanger sequencingwasperformedusing a high-fidelity DNA polymerase. Results:Nineresistant CP-CML patients wereenrolled in thisstudy. The JAK2V617F mutation wasdetectedin 3 patients with TKI resistance. Conclusion:Despite the limit of ourstudy, ourfinding highlights the high frequency of JAK2V617F/BCR-ABL double positivity as an important marker of resistance. So; the combination of JAK and TKI inhibitorsmightbe effective and potentiallybeguided by molecular monitoring of minimal residual disease1.

Keywords: chronic myeloid leukemia, tyrosine kinase inhibitors, resistance, JAK2V617F, BCR-ABL

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Authors: Mark Christian Inductivo Siwa, Jesrelle Ormoc Bontuyan

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This study was conducted in selected tertiary schools in selected universities in Asian countries such as Philippines, Thailand, and China, which are the top performing countries in Southeast Asian Games or SEA Games and Asian School Games (ASG), also known as the Youth SEA Games and Asian Games. The respondents of the study are sports administrators/directors and coaches in selected Southeast Asian countries such as Philippines, Thailand, and in Asia which is China. This study has generated a progressive sports operational model of Sports Leadership and Management in Selected Universities in Asia. This study utilized mixed-method research. It is a methodology for conducting research that involves collecting, analyzing and integrating quantitative (e.g., experiments, surveys) and qualitative (e.g., focus groups, interviews) research. This approach to research is used to provide integration for a better understanding of the research problem than either of each alone. This study particularly employed the explanatory sequential design of mixed methods, which involved two phases: the quantitative phase, which involves the collection and analysis of quantitative data, followed by the qualitative phase, which involves the collection and analysis of qualitative data. This study will prioritize the quantitative data and the findings will be followed up during the interpretation phase in the qualitative data of the study. The qualitative data help explain or build upon initial quantitative results. In phase I, the researcher began with the collection and analysis of the quantitative data. His investigation gave greater emphasis on the quantitative methods, particularly employed surveys with the coaches and sports directors of the three selected universities in Asia. In Phase II, the researcher subsequently collected and analyzed the qualitative data obtained through an interview with the sports directors to follow from or connect to the results of the quantitative phase. This study followed the data analysis spiral so that the researcher could follow – up or explain the quantitative results. The researcher engaged in the process of moving in analytic circles. Based on the school's mission and vision, the sports leadership and management consistently followed the key factors to take into account when leading the organization and managing the process in sports leadership and management when formulating objectives/goals, budget, equipment care and maintenance, facilities, training matrix, and consideration. Also, sports management demonstrates the need for development in terms of the upkeep and care of equipment as well as athlete funding. The development of goals or sports management goals, sports facilities and equipment, as well as improvements in demonstrating training and consideration, and incentives, should also include a maintenance plan. The study concluded with a progressive sports operational model that was created based on the result of the study.

Keywords: sports leadership and management, formulating objectives, budget, equipment care and maintenance, training, consideration, incentives, progressive sports operational model

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Authors: Subha D. Puthankattil, Paul K. Joseph

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Analyzing brain signals of the patients suffering from the state of depression may lead to interesting observations in the signal parameters that is quite different from a normal control. The present study adopts two different methods: Time frequency domain and nonlinear method for the analysis of EEG signals acquired from depression patients and age and sex matched normal controls. The time frequency domain analysis is realized using wavelet entropy and approximate entropy is employed for the nonlinear method of analysis. The ability of the signal processing technique and the nonlinear method in differentiating the physiological aspects of the brain state are revealed using Wavelet entropy and Approximate entropy.

Keywords: EEG, depression, wavelet entropy, approximate entropy, relative wavelet energy, multiresolution decomposition

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Authors: Rita Rani, Ramesh Kumar

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The intend of the current study is to date an old grand Peepal tree that is still alive. The tree is situated in Kalibard village, Sector 9, Chandigarh (India). Due to its huge structure, it has got the status of ‘Heritage tree.’ Optically Stimulated Luminescence of sediments beneath the roots is used to determine the age of the tree. Optical dating is preferred over conventional dating methods due to more precession. The methodology includes OSL of quartz grain using SAR protocol for accumulated dose measurement. The age determination of an alive tree using sedimentary quartz is in close agreement with the approximated age provided by the related agency. This is the first attempt at using optically stimulated luminescence in the age determination of alive trees in this region. The study concludes that the Luminescence dating of alive trees is the nondestructive and more precise method.

Keywords: luminescence, dose rate, optical dating, sediments

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Authors: Rady A., Elsheshai A., Eltawel M.

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Introduction and Aim of work: Literature suggest that antipsychotic medications may decrease cortisol level, an effect that seems to be more present with second generation antipsychotic. Our study aims at assessing effect of long term use of antipsychotics on cortisol level Subjects and Methods: 30 chronic schizophrenic patients on antipsychotics compared to 20 drug naive schizophrenic patients as regards serum cortisol level Results: Cortisol level was significantly lower in chronic schizophrenic patients receiving antipsychotics compared to drug naive patients (P=0.002 <0.05) Conclusion: Antipsychotic medications seem to have the potential to decrease cortisol level in blood. Among hypothesis proposed in literature is the good control of pseudo stress due to psychotic features.

Keywords: schizophrenia, antipsychotic, cortisol, HPA

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Authors: Marie-Elise Beydon, Daniel Sacristan, Isabel Ruppen

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MB02 (Alymsys®) is a candidate biosimilar to bevacizumab, which was developed against the reference product (RP) Avastin® sourced from both the European Union (EU) and United States (US). MB02 has been extensively characterized comparatively to Avastin® at a physicochemical and biological level using sensitive orthogonal state-of-the-art analytical methods. MB02 has been demonstrated similar to the RP with regard to its primary and higher-order structure, post- and co-translational profiles such as glycosylation, charge, and size variants. Specific focus has been put on the characterization of Fab-related activities, such as binding to VEGF A 165, which directly reflect the bevacizumab mechanism of action. Fc-related functionality was also investigated, including binding to FcRn, which is indicative of antibodies' half-life. The data generated during the analytical similarity assessment demonstrate the high analytical similarity of MB02 to its RP.

Keywords: analytical similarity, bevacizumab, biosimilar, MB02

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Authors: Joanna Gerszon, Aleksandra Rodacka

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In the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, protein and peptide aggregation processes play a vital role in contributing to the formation of intracellular and extracellular protein deposits. One of the major components of these deposits is the oxidatively modified glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Therefore, the purpose of this research was to answer the question whether piceatannol, a stilbene derivative, counteracts and/or slows down oxidative stress-induced GAPDH aggregation. The study also aimed to determine if this natural occurring compound prevents unfavorable nuclear translocation of GAPDH in hippocampal cells. The isothermal titration calorimetry (ITC) analysis indicated that one molecule of GAPDH can bind up to 8 molecules of piceatannol (7.3 ± 0.9). As a consequence of piceatannol binding to the enzyme, the loss of activity was observed. Parallel with GAPDH inactivation the changes in zeta potential, and loss of free thiol groups were noted. Nevertheless, the ligand-protein binding does not influence the secondary structure of the GAPDH. Precise molecular docking analysis of the interactions inside the active center allowed to presume that these effects are due to piceatannol ability to assemble a covalent binding with nucleophilic cysteine residue (Cys149) which is directly involved in the catalytic reaction. Molecular docking also showed that simultaneously 11 molecules of ligand can be bound to dehydrogenase. Taking into consideration obtained data, the influence of piceatannol on level of GAPDH aggregation induced by excessive oxidative stress was examined. The applied methods (thioflavin-T binding-dependent fluorescence as well as microscopy methods - transmission electron microscopy, Congo Red staining) revealed that piceatannol significantly diminishes level of GAPDH aggregation. Finally, studies involving cellular model (Western blot analyses of nuclear and cytosolic fractions and confocal microscopy) indicated that piceatannol-GAPDH binding prevents GAPDH from nuclear translocation induced by excessive oxidative stress in hippocampal cells. In consequence, it counteracts cell apoptosis. These studies demonstrate that by binding with GAPDH, piceatannol blocks cysteine residue and counteracts its oxidative modifications, that induce oligomerization and GAPDH aggregation as well as it prevents hippocampal cells from apoptosis by retaining GAPDH in the cytoplasm. All these findings provide a new insight into the role of piceatannol interaction with GAPDH and present a potential therapeutic strategy for some neurological disorders related to GAPDH aggregation. This work was supported by the by National Science Centre, Poland (grant number 2017/25/N/NZ1/02849).

Keywords: glyceraldehyde-3-phosphate dehydrogenase, neurodegenerative disease, neuroprotection, piceatannol, protein aggregation

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Authors: Eugenia Jilinguirian

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In the healthcare industry, data mining is essential since it transforms the field by collecting useful data from large datasets. Data mining is the process of applying advanced analytical methods to large patient records and medical histories in order to identify patterns, correlations, and trends. Healthcare professionals can improve diagnosis accuracy, uncover hidden linkages, and predict disease outcomes by carefully examining these statistics. Additionally, data mining supports personalized medicine by personalizing treatment according to the unique attributes of each patient. This proactive strategy helps allocate resources more efficiently, enhances patient care, and streamlines operations. However, to effectively apply data mining, however, and ensure the use of private healthcare information, issues like data privacy and security must be carefully considered. Data mining continues to be vital for searching for more effective, efficient, and individualized healthcare solutions as technology evolves.

Keywords: data mining, healthcare, big data, individualised healthcare, healthcare solutions, database

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Authors: Ali Cheraghian, Farshid Hajati, Soheila Gheisari, Yongsheng Gao

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In this paper, we present a novel 2.5D face recognition method based on Gabor Discrete Cosine Transform (GDCT). In the proposed method, the Gabor filter is applied to extract feature vectors from the texture and the depth information. Then, Discrete Cosine Transform (DCT) is used for dimensionality and redundancy reduction to improve computational efficiency. The system is combined texture and depth information in the decision level, which presents higher performance compared to methods, which use texture and depth information, separately. The proposed algorithm is examined on publically available Bosphorus database including models with pose variation. The experimental results show that the proposed method has a higher performance compared to the benchmark.

Keywords: Gabor filter, discrete cosine transform, 2.5d face recognition, pose

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Authors: Annika Bastian, Paula Restrepo Cadavid, Raphael Grau, Albert Albers

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Designing a method that assists culturally diverse and distributed teams in better understanding each other's perspectives and, therefore, improving their creative output and collaboration is the goal of this contribution. To do so, the research on cultural theories and different creativity methods that engage communication have been analyzed. Thereafter, a method has been designed combining interactive elements that engage creativity with the content of what lies behind cultural differences. The method uses Hofstede’s Cultural Dimensions as a theoretical basis, and De Bono’s six thinking hats as a practical basis to reach its goal and, therefore, successfully support multicultural distributed development teams in solving problems creatively.

Keywords: creative problem-solving, creativity method, distributed product development, method design, supporting culturally diverse teams

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Authors: Saiping An

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The spells in Chinese Buddhism are often regarded by current scholarship as syllables with mystical power, as a ritual and practice of oral chanting, or as texts engraved on cultural relics. This study hopes to point out that the spell as a kind of behavior and material also provokes the believers to interpret its soteriology with various Buddhist doctrines and philosophies. It will analyze Mahāvairocana Tantra which is the main classic of the tradition regarded by the academic circles as 'Esoteric Buddhism', two annotations of these scriptures composed in the Tang and Liao Dynasty respectively, as well as some works of monks and lay Buddhists in the late Ming and early Qing dynasties. It aims to illustrate that spells in Chinese Buddhism are not simply magical voices and the words engraved on the cultural relics; they have also enriched the doctrines and thoughts of Chinese Buddhism. Their nature and soteriological methods are far more abundant than current academic circles have revealed.

Keywords: spell, Chinese Buddhism, philosophy, Buddhist doctrines

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Authors: Nilson Barbieri, Bruno Matos Martins, Gabriel de Sant'Anna Vitor Barbieri

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In more complex systems, such as automotive gearbox, a rigorous treatment of the data is necessary because there are several moving parts (gears, bearings, shafts, etc.), and in this way, there are several possible sources of errors and also noise. The basic objective of this work is the detection of damage in automotive gearbox. The detection methods used are the wavelet method, the bispectrum; advanced filtering techniques (selective filtering) of vibrational signals and mathematical morphology. Gearbox vibration tests were performed (gearboxes in good condition and with defects) of a production line of a large vehicle assembler. The vibration signals are obtained using five accelerometers in different positions of the sample. The results obtained using the kurtosis, bispectrum, wavelet and mathematical morphology showed that it is possible to identify the existence of defects in automotive gearboxes.

Keywords: automotive gearbox, mathematical morphology, wavelet, bispectrum

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Authors: Mary Deyo, Zmara Harrison

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This study reports the outcomes of an 8-week experiential learning program for 6 adults with Intellectual and Developmental Disabilities (IDD) at a day habilitation program. The intervention foci for this program include executive function, language learning in the domains of expressive, receptive, and pragmatic language, and quality of life. The interprofessional collaboration aimed at supporting adults with IDD to reach person-centered, functional goals across skill domains is critical. This study is a significant addition to the speech-language pathology literature in that it examines a therapy method that potentially meets this need while targeting domains within the speech-language pathology scope of practice. Communication therapy was provided during highly valued and meaningful hands-on learning experiences, referred to as the Garden Club, which incorporated all aspects of planting and caring for a garden as well as related journaling, sensory, cooking, art, and technology-based activities. Direct care staff and an undergraduate research assistant were trained by SLP to be impactful language guides during their interactions with participants in the Garden Club. SLP also provided direct therapy and modeling during Garden Club. Research methods used in this study included a mixed methods analysis of a literature review, a quasi-experimental implementation of communication therapy in the context of experiential learning activities, Quality of Life participant surveys, quantitative pre- post- data collection and linear mixed model analysis, qualitative data collection with qualitative content analysis and coding for themes. Outcomes indicated overall positive changes in expressive vocabulary, following multi-step directions, sequencing, problem-solving, planning, skills for building and maintaining meaningful social relationships, and participant perception of the Garden Project’s impact on their own quality of life. Implementation of this project also highlighted supports and barriers that must be taken into consideration when planning similar projects. Overall findings support the use of experiential learning projects in day habilitation programs for adults with IDD, as well as additional research to deepen understanding of best practices, supports, and barriers for implementation of experiential learning with this population. This research provides an important contribution to research in the fields of speech-language pathology and other professions serving adults with IDD by describing an interprofessional experiential learning program with positive outcomes for executive function, language learning, and quality of life.

Keywords: experiential learning, adults, intellectual and developmental disabilities, expressive language, receptive language, pragmatic language, executive function, communication therapy, day habilitation, interprofessionalism, quality of life

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Authors: Mohammad Ghavami, Reza S. Dilmaghani

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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: adaptive methods, LSE, MSE, prediction of financial Markets

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Authors: Abubakar Ahmed, Zainab Mohammed, Hadiza D. Nuhu, Hamisu Ibrahim

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Introduction: The plant Tacazzea apiculata Oliv (Periplocaceae) is widely distributed in tropical West Africa. It is claimed to have multiple uses in traditional medicine among which are its use to treat hemorrhoids, inflammations and cancers. Methods: Ethno-botanical survey through interview and using show-and-tell method of data collection were conducted among Hausa and Fulani tribes of northern Nigeria with the view to document useful information on the numerous claims by the local people on the plant. Results: The results revealed that the plant T. apiculata has relative popularity among the herbalist (38.2 %), nomads (14.8 %) and fishermen (16.0%). The most important uses of the plant in traditional medicine are inflammation (Fedelity level: 25.7 %) and Haemorrhoids (Fedelity level: 17.1 %) Conclusion: These results suggest the relevance of T. apiculata in traditional medicine and as a good candidate for drug Development.

Keywords: ethno-botany, periplocaceae, Tacazzea apiculata, traditional medicine

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Authors: Viktória Sugár, Zoltán Laczó, András Horkai, Gyula Kiss, Attila Talamon

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The majority of the building stock of Budapest inner districts was built around the turn of the 19^th and 20^th century. Although the structural stability of the buildings is not questioned, as the load bearing structures are in sufficient state, the secondary structures are aged, resulting unsatisfactory energetic state. The renovation of these historical buildings requires special methodology and technology: their ornamented facades and custom-made fenestration cannot be insulated or exchanged with conventional solutions without damaging the heritage values. The present paper aims to introduce and systematize the possible technological solutions for heritage respecting energy retrofit in case of a historical residential building stock. Through case study, the possible energy saving potential is also calculated using multiple renovation scenarios.

Keywords: energy efficiency, heritage, historical building, renovation

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Authors: B. H. Aitchanov, Sh. K. Aitchanova, O. A. Baimuratov

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This paper is focused on dynamic pulse-frequency modulation (DPFM) control systems. Currently, the control law based on DPFM control signals is widely used in direct digital control subsystems introduced in the automated control systems of technological processes. Statistical analysis of automatic control systems is reduced to its construction of functional relationships between the statistical characteristics of the errors processes and input processes. Structural and dynamic Volterra models of digital pulse-frequency control systems can be used to develop methods for generating the dependencies, differing accuracy, requiring the amount of information about the statistical characteristics of input processes and computing labor intensity of their use.

Keywords: digital dynamic pulse-frequency control systems, dynamic pulse-frequency modulation, control object, discrete filter, impulse device, microcontroller

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Authors: Hengameh Hosseini

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Design of large healthcare facilities – such as hospitals, multi-service line clinics, and nursing facilities - that can accommodate patients with wide-ranging disabilities is a challenging endeavor and one that is poorly understood among healthcare facility managers, administrators, and executives. An even less-understood extension of this problem is the implications of weakly or insufficiently accommodative design of facilities for healthcare workers in physically-intensive jobs who may also suffer from a range of disabilities and who are therefore at increased risk of workplace accident and injury. Combine this reality with the vast range of facility types, ages, and designs, and the problem of universal accommodation becomes even more daunting and complex. In this study, we focus on the implication of facility design for healthcare workers suffering with low vision who also have physically active jobs. The points of difficulty are myriad and could span health service infrastructure, the equipment used in health facilities, and transport to and from appointments and other services can all pose a barrier to health care if they are inaccessible, less accessible, or even simply less comfortable for people with various disabilities. We conduct a series of surveys and interviews with employees and administrators of 7 facilities of a range of sizes and ownership models in the Northeastern United States and combine that corpus with in-facility observations and data collection to identify five major points of failure common to all the facilities that we concluded could pose safety threats to employees with vision impairments, ranging from very minor to severe. We determine that lack of design empathy is a major commonality among facility management and ownership. We subsequently propose three methods for remedying this lack of empathy-informed design, to remedy the dangers posed to employees: the use of an existing open-sourced Augmented Reality application to simulate the low-vision experience for designers and managers; the use of a machine learning model we develop to automatically infer facility shortcomings from large datasets of recorded patient and employee reviews and feedback; and the use of a computer vision model fine tuned on images of each facility to infer and predict facility features, locations, and workflows, that could again pose meaningful dangers to visually impaired employees of each facility. After conducting a series of real-world comparative experiments with each of these approaches, we conclude that each of these are viable solutions under particular sets of conditions, and finally characterize the range of facility types, workforce composition profiles, and work conditions under which each of these methods would be most apt and successful.

Keywords: artificial intelligence, healthcare workers, facility design, disability, visually impaired, workplace safety

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Authors: Le Hieu Giang, Truong Nguyen Luan Vu, Le Linh

Abstract:

In this paper, the analytical tuning rules of IMC-PID controller are presented for the multivariable Smith predictor that involved the ideal decoupling. Accordingly, the decoupler is first introduced into the multivariable Smith predictor control system by a well-known approach of ideal decoupling, which is compactly extended for general nxn multivariable processes and the multivariable Smith predictor controller is then obtained in terms of the multiple single-loop Smith predictor controllers. The tuning rules of PID controller in series with filter are found by using Maclaurin approximation. Many multivariable industrial processes are employed to demonstrate the simplicity and effectiveness of the presented method. The simulation results show the superior performances of presented method in compared with the other methods.

Keywords: ideal decoupler, IMC-PID controller, multivariable smith predictor, Padé approximation

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Authors: R. Devicharan

Abstract:

In a short span 3D Printing is expected to play a vital role in our life. The possibility of creativity and speed in manufacturing through various 3D printing processes is infinite. This study is performed on the FDM (Fused Deposition Modelling) method of 3D printing, which is one of the pre-dominant methods of 3D printing technologies. This study focuses on physical properties of the objects produced by 3D printing which determine the applications of the 3D printed objects. This paper specifically aims at the study of the tensile strength and the folding endurance of the 3D printed objects through the FDM (Fused Deposition Modelling) method using the ABS (Acronitirile Butadiene Styrene) and PLA (Poly Lactic Acid) plastic materials. The study is performed on a controlled environment and the specific machine settings. Appropriate tables, graphs are plotted and research analysis techniques will be utilized to analyse, verify and validate the experiment results.

Keywords: FDM process, 3D printing, ABS for 3D printing, PLA for 3D printing, rapid prototyping

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Authors: Vinod Kumar, Arun Kumar, Surjit Angra

Abstract:

This paper addresses the junction stress analysis of orthogonally intersecting thin walled cylindrical shell and thin walled cylindrical nozzle subjected to external loading on nozzle. Junction stresses have been calculated theoretically by welding research council (WRC) bulletins 107 and 297 for different nozzle loads. WRC bulletins 107 and 297 have been used by design engineers for calculating nozzle-vessel junction stresses since their publication. They give simple empirical relations and easy in application. Also 3D FEA in which material is elastic has been done in ANSYS software with 8 node solid element model and results of FEA have been compared with WRC results. Stress intensities obtained by WRC 297 are generally slightly higher than obtained by WRC 107. Membrane stresses obtained by FEA are much higher than WRC and membrane plus bending stresses obtained by FEA are lower than WRC.

Keywords: FEA, junction stress, solid element, WRC 107, WRC 297

Procedia PDF Downloads 557