Search results for: symptom resolution time

Authors: Maitree Thamma, Witchupong Wiboonjaroen, Thanat Suknuan, Karan Homchat

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First order plus dead time (FOPDT) is a high dynamic system. Therefore, the controller must be intelligent. This paper presents the development and implementation of self-tuning Fuzzy-PID controller for controlling the FOPDT system. The water level process used represented FOPDT system and the mathematical model of the system was approximated by using System Identification toolbox in Matlab. The control programming and Fuzzy-PID algorithm used Matlab/Simulink and run on Microcontroller STM32.

Keywords: real-time control, self-tuning fuzzy-PID, FOPDT system, the water lever process

Procedia PDF Downloads 292

Authors: Jared R. Chapman

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This study introduces a type of motivational information system called an educational engagement information system (EEIS). An EEIS draws on principles of behavioral economics, motivation theory, and learning cognition theory to design information systems that help students want to improve their performance. This study compares academic outcomes for course sections taught by part- and full-time instructors both with and without an EEIS. Without an EEIS, students in the part-time instructor's course sections demonstrated significantly higher failure rates (a 143.8% increase) and dropout rates (a 110.4% increase) with significantly fewer students scoring a B- or higher (39.8% decrease) when compared to students in the course sections taught by a full-time instructor. It is concerning that students in the part-time instructor’s course without an EEIS had significantly lower academic outcomes, suggesting less understanding of the course content. This could impact retention and continuation in a major. With an EEIS, when comparing part- and full-time instructors, there was no significant difference in failure and dropout rates or in the number of students scoring a B- or higher in the course. In fact, with an EEIS, the failure and dropout rates were statistically identical for part- and full-time instructor courses. When using an EEIS (compared with not using an EEIS), the part-time instructor showed a 62.1% decrease in failures, a 61.4% decrease in dropouts, and a 41.7% increase in the number of students scoring a B- or higher in the course. We are unaware of other interventions that yield such large improvements in academic performance. This suggests that using an EEIS such as Delphinium may compensate for part-time instructors’ limitations of expertise, time, or rewards that can have a negative impact on students’ academic outcomes. The EEIS had only a minimal impact on failure rates (7.7% decrease) and dropout rates (18.8% decrease) for the full-time instructor. This suggests there is a ceiling effect for the improvements that an EEIS can make in student performance. This may be because experienced instructors are already doing the kinds of things that an EEIS does, such as motivating students, tracking grades, and providing feedback about progress. Additionally, full-time instructors have more time to dedicate to students outside of class than part-time instructors and more rewards for doing so. Using adjunct and other types of part-time instructors will likely remain a prevalent practice in higher education management courses. Given that using part-time instructors can have a negative impact on student graduation and persistence in a field of study, it is important to identify ways we can augment part-time instructors’ performance. We demonstrated that when part-time instructors use an EEIS, it can result in significantly lower students’ failure and dropout rates and an increase in the rate of students earning a B- or above; and bring their students’ performance to parity with the performance of students taught by a full-time instructor.

Keywords: gamification, engagement, motivation, academic outcomes

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Authors: Dries Dulsster

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This research we want to discuss the implications of the concept of ‘lalangue’ and illustrate its importance for lacanian psychoanalysis and its clinical practice. We will look at this concept through an in depth reading of Lacan’s later seminars, his lectures at the North-American universities and his study on James Joyce. We will illustrate the importance of this concept with a case study from a clinical practice. We will argue that the introduction of ‘lalangue’ has several theoretical and clinical implications that will radically change Lacans teachings. We will illustrate the distinction between language and lalangue. Language serves communication, but this is not the case with lalangue. We will claim that there is jouissance in language and will approach this by introducing the concept of ‘lalangue’. We will ask ourselves what the effect will be of this distinction and how we can use this in clinical practice. The concept of ‘lalangue’ will introduce a new way of thinking about the unconscious. It will force us to no longer view the unconscious as Symbolic, but as Imaginary or Real. Another implication will be the approach on the symptom, no longer approaching it as a formation of the unconscious. It will be renamed as ‘sinthome’, as function of the real. Last of all it will force us to rethink the lacanian interpretation and how we direct the treatment. The implications on a clinical level will be how we think about the lacanian interpretation and the direction of the treatment. We will no longer focus on language and meaning, but focus on jouissance and the ways in which the subject deals with this. We will illustrate this importance with a clinical case study. To summarize, the concept of lalangue forces us to radically rethink lacanian psychoanalysis, with major implications on a theoretical and clinical level. It introduces new concepts such as the real unconscious and the sinthome. It will also make us rethink the way we work as lacanian psychoanalysts.

Keywords: Lacan's later teaching, language, Lalangue, the unconscious

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Authors: Mingmei Zhang, Xinyong Li

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AgInS₂/SnS₂ (AIS) nanocomposites were synthesized by a simple hydrothermal method. The morphology and composition of the fabricated AIS nanocomposites were investigated by field-emission scanning electron microscopy (SEM), X-ray diffraction (XRD), high resolution transmission electron microscopy (HRTEM) and X-ray photoelectron spectroscopy (XPS). Moreover, the as-prepared AIS photocatalysts exhibited excellent photocatalytic activities for the degradation of Norfloxacin (NOR), mainly due to its high optical absorption and separation efficiency of photogenerated electron-hole pairs, as evidenced by UV–vis diffusion reflection spectra (DRS) and Surface photovoltage (SPV) spectra. Furthermore, the interfacial charges transfer mechanism was also discussed by DFT calculations.

Keywords: AIS nanocomposites, electron-hole pairs, charges transfer, DFTcaculations

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Authors: Jing Qingfeng, Wu Jiajia

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Due to the crowded orbits and shortage of frequency resources, utilizing of MIMO technology to improve spectrum efficiency and increase the capacity has become a necessary trend of broadband satellite communication. We analyze the main influenced factors and compare the BER performance of space-time block code (STBC) scheme and space-time trellis code (STTC) scheme. This paper emphatically studies the bit error rate (BER) performance of STTC and STBC under Rayleigh channel. The main emphasis is placed on the effects of the factors, such as terminal environment and elevation angles, on the BER performance of STBC and STTC schemes. Simulation results indicate that performance of STTC under Rayleigh channel is obviously improved with the increasing of transmitting and receiving antennas numbers, but the encoder state has little impact on the performance. Under Rayleigh channel, performance of Alamouti code is better than that of STTC.

Keywords: MIMO, space time block code (STBC), space time trellis code (STTC), Rayleigh channel

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Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

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Authors: Helen Pushkarskaya, David Tolin, Lital Ruderman, Ariel Kirshenbaum, J. MacLaren Kelly, Christopher Pittenger, Ifat Levy

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Obsessive-Compulsive Disorder (OCD) produces profound morbidity. Difficulties with decision making and intolerance of uncertainty are prominent clinical features of OCD. The nature and etiology of these deficits are poorly understood. We used a well-validated choice task, grounded in behavioral economic theory, to investigate differences in valuation and value-based choice during decision making under uncertainty in 20 unmedicated participants with OCD and 20 matched healthy controls. Participants’ choices were used to assess individual decision-making characteristics. Compared to controls, individuals with OCD were less consistent in their choices and less able to identify options that were unambiguously preferable. These differences correlated with symptom severity. OCD participants did not differ from controls in how they valued uncertain options when outcome probabilities were known (risk) but were more likely than controls to avoid uncertain options when these probabilities were imprecisely specified (ambiguity). These results suggest that the underlying neural mechanisms of valuation and value-based choices during decision-making are abnormal in OCD. Individuals with OCD show elevated intolerance of uncertainty, but only when outcome probabilities are themselves uncertain. Future research focused on the neural valuation network, which is implicated in value-based computations, may provide new neurocognitive insights into the pathophysiology of OCD. Deficits in decision-making processes may represent a target for therapeutic intervention.

Keywords: obsessive compulsive disorder, decision-making, uncertainty intolerance, risk aversion, ambiguity aversion, valuation

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Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

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In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: real-time spatial big data, quality of service, vertical partitioning, horizontal partitioning, matching algorithm, hamming distance, stream query

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Authors: Mohammad H. Fattahi

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Chaotic analysis has been performed on the river flow time series before and after applying the wavelet based de-noising techniques in order to investigate the noise content effects on chaotic nature of flow series. In this study, 38 years of monthly runoff data of three gauging stations were used. Gauging stations were located in Ghar-e-Aghaj river basin, Fars province, Iran. The noise level of time series was estimated with the aid of Gaussian kernel algorithm. This step was found to be crucial in preventing removal of the vital data such as memory, correlation and trend from the time series in addition to the noise during de-noising process.

Keywords: chaotic behavior, wavelet, noise reduction, river flow

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Authors: Olivier Delage, Hassan Bencherif, Alain Bourdier

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Signal decomposition approaches represent an important step in time series analysis, providing useful knowledge and insight into the data and underlying dynamics characteristics while also facilitating tasks such as noise removal and feature extraction. As most of observational time series are nonlinear and nonstationary, resulting of several physical processes interaction at different time scales, experimental time series have fluctuations at all time scales and requires the development of specific signal decomposition techniques. Most commonly used techniques are data driven, enabling to obtain well-behaved signal components without making any prior-assumptions on input data. Among the most popular time series decomposition techniques, most cited in the literature, are the empirical mode decomposition and its variants, the empirical wavelet transform and singular spectrum analysis. With increasing popularity and utility of these methods in wide ranging applications, it is imperative to gain a good understanding and insight into the operation of these algorithms. In this work, we describe all of the techniques mentioned above as well as their ability to denoise signals, to capture trends, to identify components corresponding to the physical processes involved in the evolution of the observed system and deduce the dimensionality of the underlying dynamics. Results obtained with all of these methods on experimental total ozone columns and rainfall time series will be discussed and compared

Keywords: denoising, empirical mode decomposition, singular spectrum analysis, time series, underlying dynamics, wavelet analysis

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Authors: Amitesh Goswami, Vishal Gulati, Annu Yadav

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In this paper, WEDM has been used to investigate the machining characteristics of Inconel-625 alloy. The machining characteristics namely material removal rate (MRR) and surface roughness (SR) have been investigated along with surface microstructure analysis using SEM and EDS of the machined surface. Taguchi’s L27 Orthogonal array design has been used by considering six varying input parameters viz. Pulse-on time (Ton), Pulse-off time (Toff), Spark Gap Set Voltage (SV), Peak Current (IP), Wire Feed (WF) and Wire Tension (WT) for the responses of interest. It has been found out that Pulse-on time (Ton) and Spark Gap Set Voltage (SV) are the most significant parameters affecting material removal rate (MRR) and surface roughness (SR) are. Microstructure analysis of workpiece was also done using Scanning Electron Microscope (SEM). It was observed that, variations in pulse-on time and pulse-off time causes varying discharge energy and as a result of which deep craters / micro cracks and large/ small number of debris were formed. These results were helpful in studying the effects of pulse-on time and pulse-off time on MRR and SR. Energy Dispersive Spectrometry (EDS) was also done to check the compositional analysis of the material and it was observed that Copper and Zinc which were initially not present in the Inconel 625, later migrated on the material surface from the brass wire electrode during machining

Keywords: MRR, SEM, SR, taguchi, Wire Electric Discharge Machining

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Authors: N. C. van der Merwe, J. Oosthuizen, M. F. Makhetha, J. Adams, B. K. Dajee, S-R. Schneider

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Women representing high-risk breast cancer families, who tested negative for pathogenic mutations in BRCA1 and BRCA2, are four times more likely to develop breast cancer compared to women in the general population. Sequencing of genes involved in genomic stability and DNA repair led to the identification of novel contributors to familial breast cancer risk. These include BLM and PALB2. Bloom's syndrome is a rare homozygous autosomal recessive chromosomal instability disorder with a high incidence of various types of neoplasia and is associated with breast cancer when in a heterozygous state. PALB2, on the other hand, binds to BRCA2 and together, they partake actively in DNA damage repair. Archived DNA samples of 66 BRCA1/2 negative high-risk breast cancer patients were retrospectively selected based on the presence of an extensive family history of the disease ( > 3 affecteds per family). All coding regions and splice-site boundaries of both genes were screened using High-Resolution Melting Analysis. Samples exhibiting variation were bi-directionally automated Sanger sequenced. The clinical significance of each variant was assessed using various in silico and splice site prediction algorithms. Comprehensive screening identified a total of 11 BLM and 26 PALB2 variants. The variants detected ranged from global to rare and included three novel mutations. Three BLM and two PALB2 likely pathogenic mutations were identified that could account for the disease in these extensive breast cancer families in the absence of BRCA mutations (BLM c.11T > A, p.V4D; BLM c.2603C > T, p.P868L; BLM c.3961G > A, p.V1321I; PALB2 c.421C > T, p.Gln141Ter; PALB2 c.508A > T, p.Arg170Ter). Conclusion: The study confirmed the contribution of pathogenic mutations in BLM and PALB2 to the familial breast cancer burden in South Africa. It explained the presence of the disease in 7.5% of the BRCA1/2 negative families with an extensive family history of breast cancer. Segregation analysis will be performed to confirm the clinical impact of these mutations for each of these families. These results justify the inclusion of both these genes in a comprehensive breast and ovarian next generation sequencing cancer panel and should be screened simultaneously with BRCA1 and BRCA2 as it might explain a significant percentage of familial breast and ovarian cancer in South Africa.

Keywords: Bloom Syndrome, familial breast cancer, PALB2, South Africa

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Authors: Mehmet Ekici

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In this study, the fading time affecting the mechanical properties and microstructures of vermicular cast iron were studied. Pig iron and steel scrap weighing about 12 kg were charged into the high-frequency induction furnace crucible and completely melted for production of vermicular cast iron. The slag was skimmed using a common flux. After fading time was set at 1. 3 and 5 minutes. In this way, three vermicular cast iron was produced that same composition but different phase structures. The microstructure of specimens was investigated, and uni-axial tensile test and the Charpy impact test were performed, and their micro-hardness measurements were done in order to characterize the mechanical behaviours of vermicular cast iron.

Keywords: vermicular cast iron, fading time, hardness, tensile test and impact test

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Authors: Ben G. Weber, Michael Mateas

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We present a case-based reasoning technique for selecting build orders in a real-time strategy game. The case retrieval process generalizes features of the game state and selects cases using domain-specific recall methods, which perform exact matching on a subset of the case features. We demonstrate the performance of the technique by implementing it as a component of the integrated agent framework of McCoy and Mateas. Our results demonstrate that the technique outperforms nearest-neighbor retrieval when imperfect information is enforced in a real-time strategy game.

Keywords: case based reasoning, real time strategy systems, requirements elicitation, requirement analyst, artificial intelligence

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Authors: Tatiana G. Smirnova, Stan G. Benjamin

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Rapid Update Cycle (RUC) land surface model (LSM) was a land-surface component in several generations of operational weather prediction models at the National Center for Environment Prediction (NCEP) at the National Oceanic and Atmospheric Administration (NOAA). It was designed for short-range weather predictions with an emphasis on severe weather and originally was intentionally simple to avoid uncertainties from poorly known parameters. Nevertheless, the RUC LSM, when coupled with the hourly-assimilating atmospheric model, can produce a realistic evolution of time-varying soil moisture and temperature, as well as the evolution of snow cover on the ground surface. This result is possible only if the soil/vegetation/snow component of the coupled weather prediction model has sufficient skill to avoid long-term drift. RUC LSM was first implemented in the operational NCEP Rapid Update Cycle (RUC) weather model in 1998 and later in the Weather Research Forecasting Model (WRF)-based Rapid Refresh (RAP) and High-resolution Rapid Refresh (HRRR). Being available to the international WRF community, it was implemented in operational weather models in Austria, New Zealand, and Switzerland. Based on the feedback from the US weather service offices and the international WRF community and also based on our own validation, RUC LSM has matured over the years. Also, a sea-ice module was added to RUC LSM for surface predictions over the Arctic sea-ice. Other modifications include refinements to the snow model and a more accurate specification of albedo, roughness length, and other surface properties. At present, RUC LSM is being tested in the regional application of the Unified Forecast System (UFS). The next generation UFS-based regional Rapid Refresh FV3 Standalone (RRFS) model will replace operational RAP and HRRR at NCEP. Over time, RUC LSM participated in several international model intercomparison projects to verify its skill using observed atmospheric forcing. The ESM-SnowMIP was the last of these experiments focused on the verification of snow models for open and forested regions. The simulations were performed for ten sites located in different climatic zones of the world forced with observed atmospheric conditions. While most of the 26 participating models have more sophisticated snow parameterizations than in RUC, RUC LSM got a high ranking in simulations of both snow water equivalent and surface temperature. However, ESM-SnowMIP experiment also revealed some issues in the RUC snow model, which will be addressed in this paper. One of them is the treatment of grid cells partially covered with snow. RUC snow module computes energy and moisture budgets of snow-covered and snow-free areas separately by aggregating the solutions at the end of each time step. Such treatment elevates the importance of computing in the model snow cover fraction. Improvements to the original simplistic threshold-based approach have been implemented and tested both offline and in the coupled weather model. The detailed description of changes to the snow cover fraction and other modifications to RUC soil and snow parameterizations will be described in this paper.

Keywords: land-surface models, weather prediction, hydrology, boundary-layer processes

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history seismic analysis is supposed to be the most accurate method to predict the seismic demand of structures. On the other hand, the required computational time of this method toward achieving the result is its main deficiency. While being applied in optimization process, in which the structure must be analyzed thousands of time, reducing the required computational time of seismic analysis of structures makes the optimization algorithms more practical. Apparently, the invented approximate methods produce some amount of errors in comparison with exact time history analysis but the recently proposed method namely, Complete Quadratic Combination (CQC) and Sum Root of the Sum of Squares (SRSS) drastically reduces the computational time by combination of peak responses in each mode. In the present research, the Basic Modal Displacement (BMD) method is introduced and applied towards estimation of seismic demand of main structure. Seismic demand of sampled structure is estimated by calculation of modal displacement of basic structure (in which the modal displacement has been calculated). Shear steel sampled structures are selected as case studies. The error applying the introduced method is calculated by comparison of the estimated seismic demands with exact time history dynamic analysis. The efficiency of the proposed method is demonstrated by application of three types of earthquakes (in view of time of peak ground acceleration).

Keywords: time history dynamic analysis, basic modal displacement, earthquake-induced demands, shear steel structures

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Authors: M. Duran Toksari, Berrin Ucarkus

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In this paper, we propose two algorithms to optimally solve makespan and total completion time scheduling problems with learning effect and job dependent delivery times in a single machine environment. The delivery time is the extra time to eliminate adverse effect between the main processing and delivery to the customer. In this paper, we introduce the job dependent delivery times for some single machine scheduling problems with position dependent learning effect, which are makespan are total completion. The results with respect to two algorithms proposed for solving of the each problem are compared with LINGO solutions for 50-jobs, 100-jobs and 150-jobs problems. The proposed algorithms can find the same results in shorter time.

Keywords: delivery Times, learning effect, makespan, scheduling, total completion time

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Authors: Matthieu-P. Schapranow

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Recruitment of participants for clinical trials requires the screening of a big number of potential candidates, i.e. the testing for trial-specific inclusion and exclusion criteria, which is a time-consuming and complex task. Today, a significant amount of time is spent on identification of adequate trial participants as their selection may affect the overall study results. We introduce a unique patient eligibility metric, which allows systematic ranking and classification of candidates based on trial-specific filter criteria. Our web application enables real-time analysis of patient data and assessment of candidates using freely definable inclusion and exclusion criteria. As a result, the overall time required for identifying eligible candidates is tremendously reduced whilst additional degrees of freedom for evaluating the relevance of individual candidates are introduced by our contribution.

Keywords: in-memory technology, clinical trials, screening, eligibility metric, data analysis, clustering

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Authors: Dewi Tristantini, Jason Jonathan

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Coronary Artery Disease (CAD) is one of the deathliest diseases which is caused by atherosclerosis. Atherosclerosis is a disease that plaque builds up inside the arteries. Plaque is made up of fat, cholesterol, calcium, platelet, and other substances found in blood. The current treatment of atherosclerosis is to provide antiplatelet therapy treatment, but such treatments often cause gastrointestinal irritation, muscle pain and hormonal imbalance. Mimusops elengi L.’s leaves can be utilized as a natural and cheap antiplatelet’s source because it contains flavonoids such as quertecin. Antiplatelet aggregation effect of Mimusops elengi L.’s leaves’ wet extract was measured by bleeding time on DDY strain mice with the test substances were given orally during the period of 8 days. The bleeding time was measured on first day and 9th day. Empirically, the dose which is used for humans is 8.5 g of leaves in 600 ml of water. This dose is equivalent to 2.1 g of leaves in 350 ml of water for mice. The extract was divided into 3 doses for mice: 0.05 ml/day; 0.1 ml/day; 0.2 ml/day. After getting the percentage of the increase in bleeding time, data were analyzed by analysis of variance test (Anova), followed by individual comparison within the groups by LSD test. The test substances above respectively increased bleeding time 21%, 62%, and 128%. As the conclusion, the 0.02 ml/day dose of Mimusops elengi L.’s leaves’ wet extract could increase bleeding time better than clopidogrel as positive controls with 110% increase in bleeding time.

Keywords: antiplatelets, atheroschlerosis, bleeding time, Mimusops elengi

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Authors: Fernando Araujo, Sandra Cardoso, Fátima Fonseca, Sandra Cavaca

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A debureaucratization strategy for the Portuguese Health Service was assumed by the Executive Board of the SNS, in deep articulation with the Shared Services of the Ministry of Health. Two of the main dimensions were focused on sick leaves (SL), that transform primary health care (PHC) in administrative institutions, limiting access to patients. The self-declaration of illness (SDI) project, through the National Health Service Contact Centre (SNS24), began on May 1, 2023, and has already resulted in the issuance of more than 300,000 SDI without the need to allocate resources from the National Health Service (NHS). This political decision allows each citizen, in a maximum 2 times/year, and 3 days each time, if ill, through their own responsibility, report their health condition in a dematerialized way, and by this way justified the absence to work, although by Portuguese law in these first three days, there is no payment of salary. Using a digital approach, it is now feasible without the need to go to the PHC and occupy the time of the PHC only to obtain an SL. Through this measure, bureaucracy has been reduced, and the system has been focused on users, improving the lives of citizens and reducing the administrative burden on PHC, which now has more consultation times for users who need it. The second initiative, which began on March 1, 2024, allows the SL to be issued in emergency departments (ED) of public hospitals and in the health institutions of the social and private sectors. This project is intended to allow the user who has suffered a situation of acute urgent illness and who has been observed in an ED of a public hospital or in a private or social entity no longer need to go to PHC only to apply for the respective SL. Since March 1, 54,453 SLs have been issued, 242 in private or social sector institutions and 6,918 in public hospitals, of which 134 were in ED and 47,292 in PHC. This approach has proven to be technically robust, allows immediate resolution of problems and differentiates the performance of doctors. However, it is important to continue to qualify the proper functioning of the ED, preventing non-urgent users from going there only to obtain SL. Thus, in order to make better use of existing resources, it was operationalizing this extension of its issuance in a balanced way, allowing SL to be issued in the ED of hospitals only to critically ill patients or patients referred by INEM, SNS24, or PHC. In both cases, an intense public campaign was implemented to explain the way it works and the benefits for patients. In satisfaction surveys, more than 95% of patients and doctors were satisfied with the solutions, asking for extensions to other areas. The administrative simplification agenda of the NHS continues its effective development. For the success of this debureaucratization agenda, the key factors are effective communication and the ability to reach patients and health professionals in order to increase health literacy and the correct use of NHS.

Keywords: debureaucratization strategy, self-declaration of illness, sick leaves, SNS24

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Authors: Sajad Shokohuyar, Mahsa Zomorrodi Anbaji, Saghar Pouyan Shad

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According to fast technology growth, modern banking tries to decrease going to banks’ branches and increase customers’ consent. One of the problems which banks face is securing customer’s password. The banks’ solution is one time password creation system. In this research by adapting from acceptance of technology model theory, assesses factors that are effective on banking in Iran especially in using one time password machine by one of the private banks of Iran customers. The statistical population is all of this bank’s customers who use electronic banking service and one time password technology and the questionnaires were distributed among members of statistical population in 5 selected groups of north, south, center, east and west of Tehran. Findings show that confidential preservation, education, ease of utilization and advertising and informing has positive relations and distinct hardware and age has negative relations.

Keywords: security, electronic banking, one time password, information technology

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Authors: Samitharathana R. Wadigala

Abstract:

The peace will not be established until the self-consciousness would reveal in the human beings. In this nuclear age, the establishment of a lasting peace on the earth represents the primary condition for the preservation of human civilization and survival of human beings. Nothing perhaps is so important and indispensable as the achievement and maintenance of peace in the modern world today. Peace in today’s world implies much more than the mere absence of war and violence. In the interdependent world of today the United Nations needs to be representative of the modern world and democratic in its functioning because it came into existence to save the generations from the scourge of war and conflict. Buddhism is the religion of peaceful co-existence and philosophy of enlightenment. Violence and conflict from the perspective of the Buddhist theory of interdependent origination (Paṭiccasamuppāda) are same with everything else in the world a product of causes and conditions. Buddhism is totally compatible with the congenial and peaceful global order. The canonical literature, doctrines, and philosophy of Buddhism are the best suited for inter-faith dialogue, harmony, and universal peace. Even today Buddhism can resurrect the universal brotherhood, peaceful co-existence and harmonious surroundings in the comity of nations. With its increasing vitality in regions around the world, many people today turn to Buddhism for relief and guidance at the time when peace seems to be a deferred dream more than ever. From a Buddhist point of view the roots of all unwholesome actions (Conflict) i. e. greed, hatred and delusion are viewed as the root cause of all human conflicts. Conflict often emanates from attachment to material things: pleasures, property, territory, wealth, economic dominance or political superiority. Buddhism has some particularly rich resources for deployment in dissolving conflict. Buddhism addresses the Buddhist perspective on the causes of conflict and ways to resolve conflict to realize world peace. The world has enough to satisfy every body’s needs but not every body’s greed.

Keywords: Buddhism, conflict-violence, peace, self-consciousness

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Authors: Panupat Chaiworn, Soraya lama

Abstract:

We study the motion of particles in cylinders which are subjected to a sinusoidal vertical vibration. We measure the rising time of a large intruder from the bottom of the container to free surface of the bed particles and find that the rising time as a function of intruder density increases to a maximum and then decreases monotonically. The result is qualitatively accord to the previous findings in experiments using relative humidity of the bed particles and found speed convection of the bed particles containers it moving slowly, and the rising time of the intruder where a minimal instead of maximal rising time in the small density region was found. Our experimental results suggest that the topology of the container plays an important role in the Brazil nut effect.

Keywords: granular particles, Brazil nut effect, cylinder container, vertical vibration, convection

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Authors: Yujie Zhou, Hee-Seong Byun, Sang-In Bak, Eui-Joon Kil, Kyung Joo Min, Vivek Chavan, Won Kyong Cho, Sukchan Lee, Seung-Woo Hong, Tae-Sun Park

Abstract:

Fast neutron irradiation (FNI) can cause mutations on plant genome but, in the most of cases, these irradiated plants have not shown significant characteristics phenotypically. In this study, we utilized RNA-Seq to generate a high-resolution transcriptome map of the tomato (Solanum lycopersicum) genome effected by FNI. To quantify the different transcription levels in tomato irradiated by FNI, tomato seeds were irradiated by using MC-50 cyclotron (KIRAMS, Korea) for 0, 30 and 90 minutes, respectively. To investigate the effects on the pre-soaking condition, experimental groups were divided into dry and soaked seeds, which were soaked for 8 hours before irradiation. There was no noticeable difference in the percentage germination (PG) among dry seeds, while irradiated soaked seeds have about 10 % lower PG compared to the unirradiated control group. Using whole transcriptome sequencing by HiSeq 2000, we analyzed the differential gene expression in response to different time of FNI in dry and soaked seeds. More than 1.4 million base pair reads were mapped onto the tomato reference genome and the expression pattern differences between irradiated and unirradiated seeds were assessed. In 0, 30 and 90 minutes irradiation, 12,135, 28,495 and 28,675 transcripts were generated, respectively. Gene ontology analysis suggested the different enrichment of transcripts involved in response to different FNI. The present study showed that FNI effects on plant gene expression, which can become a new parameters for evaluating the responses against FNI on plants. In addition, the comparative analysis of differentially expressed genes in D and S seeds by FNI will also give us a chance to deep explore novel candidate genes for FNI, which could be a good model system to understand the mechanisms behind the adaption of plant to space biology research.

Keywords: tomato (solanum lycopersicum), fast neutron irradiation, RNA-sequence, transcriptome expression

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Authors: H. R. Fazlollahi

Abstract:

Dark Energy origin is unknown and so describing this mysterious component in large scale structure needs to manipulate our theories in general relativity. Although in most models, dark energy arises from extra terms through modifying Einstein-Hilbert action, maybe its origin traces back to fundamental aspects of ground energy of space-time given in quantum mechanics. Hence, diluting space-time in general relativity with quantum mechanics properties leads to the Karolyhazy relation corresponding energy density of quantum fluctuations of space-time. Through generalized uncertainty principle and an eye to Karolyhazy approach in this study we extend energy density of quantum fluctuations of space-time. Also, the application of this idea is considered in late time evolution and we have shown how extra term in generalized uncertainty principle plays as a plausible interaction term role in suggested model.

Keywords: generalized uncertainty principle, karolyhazy approach, agegraphic dark energy, cosmology

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Authors: Zhongzhen Luo, Saeid Habibi, Martin v. Mohrenschildt

Abstract:

Self-driving vehicle require a high level of situational awareness in order to maneuver safely when driving in real world condition. This paper presents a LiDAR based real time perception system that is able to process sensor raw data for multiple target detection and tracking in dynamic environment. The proposed algorithm is nonparametric and deterministic that is no assumptions and priori knowledge are needed from the input data and no initializations are required. Additionally, the proposed method is working on the three-dimensional data directly generated by LiDAR while not scarifying the rich information contained in the domain of 3D. Moreover, a fast and efficient for real time clustering algorithm is applied based on a radially bounded nearest neighbor (RBNN). Hungarian algorithm procedure and adaptive Kalman filtering are used for data association and tracking algorithm. The proposed algorithm is able to run in real time with average run time of 70ms per frame.

Keywords: lidar, segmentation, clustering, tracking

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Authors: Vikram Singh

Abstract:

The objective of the study was to study the effectiveness of common yoga protocol on reaction time (simple visual reaction time-SVRT measured in milliseconds/seconds) of male football players in the age group of 15 to 21 years. The 40 boys were randomly assigned into two groups i.e. control and experimental. SVRT for both the groups were measured on day-1 and post intervention (common yoga protocol here) was measured after 45 days of training to the experimental group only. One way ANOVA (Univariate analysis) and Independent t-test using SPSS 23 statistical package was applied to get and analyze the results. There was a significant difference after 45 days of yoga protocol in simple visual reaction time of experimental group (p = .032), t (33.05) = 3.881, p = .000 (two-tailed). Null hypothesis (that there would be no post measurement differences in reaction times of control and experimental groups) was rejected. Where p<.05. Therefore alternate hypothesis was accepted.

Keywords: footballers, t-test, yoga protocol, reaction time

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Authors: G. Tamulevičius, A. Serackis, T. Sledevič, D. Navakauskas

Abstract:

We consider the biggest challenge in speech recognition – noise reduction. Traditionally detected transient noise pulses are removed with the corrupted speech using pulse models. In this paper we propose to cope with the problem directly in Dynamic Time Warping domain. Bidirectional Dynamic Time Warping algorithm for the recognition of isolated words impacted by transient noise pulses is proposed. It uses simple transient noise pulse detector, employs bidirectional computation of dynamic time warping and directly manipulates with warping results. Experimental investigation with several alternative solutions confirms effectiveness of the proposed algorithm in the reduction of impact of noise on recognition process – 3.9% increase of the noisy speech recognition is achieved.

Keywords: transient noise pulses, noise reduction, dynamic time warping, speech recognition

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Authors: Varis Ransibrahmanakul, Doug Pirhalla, Scott Sheridan, Cameron Lee

Abstract:

U.S. coastal areas and ecosystems are facing multiple sea level rise threats and effects: heavy rain events, cyclones, and changing wind and weather patterns all influence coastal flooding, sedimentation, and erosion along critical barrier islands and can strongly impact habitat resiliency and water quality in protected habitats. These impacts are increasing over time and have accelerated the need for new tracking techniques, models and tools of flood risk to support enhanced preparedness for coastal management and mitigation. To address this issue, NOAA National Ocean Service (NOS) evaluated new metrics from satellite altimetry AVISO/Copernicus and MODIS IR flood extents to isolate nodes atmospheric variability indicative of elevated sea level and nuisance flood events. Using de-trended time series of cross-shelf sea surface heights (SSH), we identified specific Self Organizing Maps (SOM) nodes and transitions having a strongest regional association with oceanic spatial patterns (e.g., heightened downwelling favorable wind-stress and enhanced southward coastal transport) indicative of elevated coastal sea levels. Results show the impacts of the inverted barometer effect as well as the effects of surface wind forcing; Ekman-induced transport along broad expanses of the U.S. eastern coastline. Higher sea levels and corresponding localized flooding are associated with either pattern indicative of enhanced on-shore flow, deepening cyclones, or local- scale winds, generally coupled with an increased local to regional precipitation. These findings will support an integration of satellite products and will inform seasonal outlook model development supported through NOAAs Climate Program Office and NOS office of Center for Operational Oceanographic Products and Services (CO-OPS). Overall results will prioritize ecological areas and coastal lab facilities at risk based on numbers of nuisance flood projected and inform coastal management of flood risk around low lying areas subjected to bank erosion.

Keywords: AVISO satellite altimetry SSHA, MODIS IR flood map, nuisance flood, remote sensing of flood

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Authors: Kalpana Dahiya

Abstract:

This paper discusses a two-level hierarchical time minimization transportation problem, which is an important class of transportation problems arising in industries. This problem has been studied by various researchers, and a number of polynomial time iterative algorithms are available to find its solution. All the existing algorithms, though efficient, have some shortcomings. The current study proposes an alternate solution algorithm for the problem that is more efficient in terms of computational time than the existing algorithms. The results justifying the underlying theory of the proposed algorithm are given. Further, a detailed comparison of the computational behaviour of all the algorithms for randomly generated instances of this problem of different sizes validates the efficiency of the proposed algorithm.

Keywords: global optimization, hierarchical optimization, transportation problem, concave minimization

Procedia PDF Downloads 162