Search results for: temporal correlation

Authors: Supattra Kanchanopast

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The purpose of this study was to study the relationship between customer satisfaction and customer loyalty through social media of service business. This study collected data from 187 customers who have used social media of service business to buy product or service in Thailand. Statistics including frequency, percentage, standard deviation and Person’s Correlation test were used. The finding revealed that the majority of the respondents were female, 25-40 years old, graduated the bachelor degree, had monthly income 15,000-25,000 Baht and worked in private sectors. The mostly respondents have reserved the accommodation/homestay/hotel through Facebook about 3-4 times. The hypothesis testing disclosed that the satisfaction in customer invitation and data presentation perspective had a correlation with the level of customer loyalty: recommendation to others in terms of sharing. In addition, the satisfaction in customer relationship management perspective had a positive correlation with customer loyalty through social media of service business with respect to repeat purchase and recommendation to others at the 0.05 level of significance.

Keywords: customer satisfaction, customer loyalty, relationship, service business, social media

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Authors: Shreya Borthakur, Aastha Vartak

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This Electroencephalogram (EEG) project on Rapid Visual Serial Processing (RSVP) paradigm explores the temporal dynamics of visual attention processing in response to rapidly presented visual stimuli. The study builds upon previous research that used real-world images in RSVP tasks to understand the emergence of object representations in the human brain. The objectives of the research include investigating the differences in accuracy and reaction times between 5 Hz and 20 Hz presentation rates, as well as examining the prominent brain waves, particularly alpha and beta waves, associated with the attention task. The pre-processing and data analysis involves filtering EEG data, creating epochs for target stimuli, and conducting statistical tests using MATLAB, EEGLAB, Chronux toolboxes, and R. The results support the hypotheses, revealing higher accuracy at a slower presentation rate, faster reaction times for less complex targets, and the involvement of alpha and beta waves in attention and cognitive processing. This research sheds light on how short-term memory and cognitive control affect visual processing and could have practical implications in fields like education.

Keywords: RSVP, attention, visual processing, attentional blink, EEG

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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Authors: Rosy Chaudhary, Pushpa Parajuli

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Background and Objectives: Informational support to family members has a significant potential for reducing this distress related to hospitalization of their patient into the critical care unit, enabling them to cope better and support the patient. The objective of the study is to assess family members’ perception of informational support, anxiety, satisfaction with care and to reveal the association with selected socio-demographic variables and to investigate the correlation between informational support, anxiety and satisfaction with care. Materials and Methods: A descriptive cross-sectional study was conducted in 39 family caregivers of patients admitted in critical care unit of BPKIHS(B.P. Koirala Institute of Health Sciences). Consecutive sampling technique was used wherein data was collected over duration of one month using interview schedule. Descriptive and inferential statistics were used. Results: The mean age of the respondents was 34.97 ± 10.64 and two third (66.70%) were male. Mean score for informational support was 25.72(SD = 5.66; theoretical range of 10 - 40). Mean anxiety was 10.41 (SD = 5.02; theoretical range of 7 - 21). Mean score for satisfaction with care was 40.77 (SD = 6.77; theoretical range of 14 - 64). A moderate positive correlation was found between informational support and satisfaction with care (r = 0.551, p < .001) and a moderate negative correlation was found between anxiety and satisfaction with care (r = -0.590; p = 0.000). No relationship was noted between informational support and anxiety. Conclusion: The informational support and satisfaction of the family caregivers with the care provided to their patients was satisfactory. More than three fourth of the family caregivers had anxiety; the factors associated being educational status of the caregivers, the family income and duration of visiting hours. There was positive correlation between informational support and satisfaction with care provided justifying the need for comprehensive information to the family caregivers by the health personnel. There was negative correlation between anxiety and satisfaction with care.

Keywords: anxiety, caregivers, critical care unit, informational support, family

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Authors: Rabia Munsaf Khan, Eshrat Fatima

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The analysis of the spatial extent and temporal change of vegetation cover using remotely sensed data is of critical importance to agricultural sciences. Pakistan, being an agricultural country depends on this resource as it makes 70% of the GDP. The case study is of Lal Suhanra National Park, which is not only the biggest forest reserve of Pakistan but also of Asia. The study is performed using different temporal images of Landsat. Also, the results of Landsat are cross-checked by using Sentinel-2 imagery as it has both higher spectral and spatial resolution. Vegetation can easily be detected using NDVI which is a common and widely used index. It is an important vegetation index, widely applied in research on global environmental and climatic change. The images are then classified to observe the change occurred over 15 years. Vegetation cover maps of 2000 and 2016 are used to generate the map of vegetation change detection for the respective years and to find out the changing pattern of vegetation cover. Also, the NDVI values aided in the detection of percentage decrease in vegetation cover. The study reveals that vegetation cover of the area has decreased significantly during the year 2000 and 2016.

Keywords: Landsat, normalized difference vegetation index (NDVI), sentinel 2, Greenland monitoring

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Authors: N. Norazlimi, R. Ramli

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A study was conducted to determine the diversity and abundance of shorebird species habituating the mudflat area of Jeram Beach and Remis Beach, Selangor, Peninsular Malaysia. Direct observation technique (using binoculars and video camera) was applied to record the presence of bird species in the sampling sites from August 2013 until July 2014. A total of 32 species of shorebird were recorded during both migratory and non-migratory seasons. Of these, eleven species (47.8%) are migrants, six species (26.1%) have both migrant and resident populations, four species (17.4%) are vagrants and two species (8.7%) are residents. The compositions of the birds differed significantly in all months (χ2=84.35, p<0.001). There is a significant difference in avian abundance between migratory and non-migratory seasons (Mann-Whitney, t=2.39, p=0.036). The avian abundance were differed significantly in Jeram and Remis Beaches during migratory periods (t=4.39, p=0.001) but not during non-migratory periods (t=0.78, p=0.456). Shorebird diversity was also affected by tidal cycle. There is a significance difference between high tide and low tide (Mann-Whitney, t=78.0, p<0.005). Frequency of disturbance also affected the shorebird distribution (Mann-Whitney, t=57.0, p= 0.0134). Therefore, this study concluded that tides and disturbances are two factors that affecting temporal distribution of shorebird in mudflats area.

Keywords: biodiversity, distribution, migratory birds, direct observation

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Authors: Jérémie Ochin

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Soccer analytics are built on two data sources: the frame-by-frame position of each player on the terrain and the sequences of events, such as ball drive, pass, cross, shot, throw-in... With more than 2000 ball-events per soccer game, their precise and exhaustive annotation, based on a monocular video stream such as a TV broadcast, remains a tedious and costly manual task. State-of-the-art methods for spatio-temporal action detection from a monocular video stream, often based on 3D convolutional neural networks, are close to reach levels of performances in mean Average Precision (mAP) compatibles with the automation of such task. Nevertheless, to meet their expectation of exhaustiveness in the context of data analytics, such methods must be applied in a regime of high recall – low precision, using low confidence score thresholds. This setting unavoidably leads to the detection of false positives that are the product of the well documented overconfidence behaviour of neural networks and, in this case, their limited access to contextual information and understanding of the game: their predictions are highly unstructured. Based on the assumption that professional soccer players’ behaviour, pose, positions and velocity are highly interrelated and locally driven by the player performing a ball-action, it is hypothesized that the addition of information regarding surrounding player’s appearance, positions and velocity in the prediction methods can improve their metrics. Several methods are compared to build a proper representation of the game surrounding a player, from handcrafted features of the local graph, based on domain knowledge, to the use of Graph Neural Networks trained in an end-to-end fashion with existing state-of-the-art 3D convolutional neural networks. It is shown that the inclusion of information regarding surrounding players helps reaching higher metrics.

Keywords: fine-grained action recognition, human action recognition, convolutional neural networks, graph neural networks, spatio-temporal action recognition

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Authors: Ashneel Ajay Singh, Anish Maharaj, Havish Naidu, Michelle Kumar

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Mangrove patches are the foundation species located in the estuarine land areas. These patches provide a nursery, food source and protection for numerous aquatic, intertidal and well as land-based organisms. Mangroves also help in coastal protection, maintain water clarity and are one of the biggest sinks for blue carbon sequestration. In the Pacific Island countries, numerous coastal communities have a heavy socioeconomic dependence on coastal resources and mangroves play a key ecological and economical role in structuring the availability of these resources. Fiji has a large mangrove patch located in the Votua area of the Ba province. Globally, mangrove population continues to decline with the changes in climatic conditions and anthropogenic activities. Baseline information through wetland maps and time series change are essential references for development of effective mangrove management plans. These maps reveal the status of the resource and the effects arising from anthropogenic activities and climate change. In this study, we used remote sensing and GIS tools for mapping and temporal change detection over a period of >20 years in Votua, Fiji using Landsat imagery. Landsat program started in 1972 initially as Earth Resources Technology Satellite. Since then it has acquired millions of images of Earth. This archive allows mapping of temporal changes in mangrove forests. Mangrove plants consisted of the species Rhizophora stylosa, Rhizophora samoensis, Bruguiera gymnorrhiza, Lumnitzera littorea, Heritiera littoralis, Excoecaria agallocha and Xylocarpus granatum. Change detection analysis revealed significant reduction in the mangrove patch over the years. This information serves as a baseline for the development and implementation of effective management plans for one of Fiji’s biggest mangrove patches.

Keywords: climate change, GIS, Landsat, mangrove, temporal change

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Authors: L. Q. Yuan, J. Yang, A. Siddiqui

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A new regression uncertainty analysis methodology was applied to determine the uncertainties of the critical heat flux (CHF) power correlation for an advanced 43-element bundle design, which was developed by Canadian Nuclear Laboratories (CNL) to achieve improved economics, resource utilization and energy sustainability. The new methodology is considered more appropriate than the traditional methodology in the assessment of the experimental uncertainty associated with regressions. The methodology was first assessed using both the Monte Carlo Method (MCM) and the Taylor Series Method (TSM) for a simple linear regression model, and then extended successfully to a non-linear CHF power regression model (CHF power as a function of inlet temperature, outlet pressure and mass flow rate). The regression uncertainty assessed by MCM agrees well with that by TSM. An equation to evaluate the CHF power regression uncertainty was developed and expressed as a function of independent variables that determine the CHF power.

Keywords: CHF experiment, CHF correlation, regression uncertainty, Monte Carlo Method, Taylor Series Method

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Authors: Barbora Chmelova, Radek Sachl

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Gangliosides are amphipathic membrane lipids. Due to the composition of bulky oligosaccharide chains containing one or more sialic acids linked to the hydrophobic ceramide base, gangliosides are classified among glycosphingolipids. This unique structure induces a high self-aggregating tendency of gangliosides and, therefore, the formation of nanoscopic clusters called nanodomains. Gangliosides are preferentially present in an extracellular membrane leaflet of all human tissues and thus have an impact on a huge number of biological processes, such as intercellular communication, cell signalling, membrane trafficking, and regulation of receptor activity. Defects in their metabolism, impairment of proper ganglioside function, or changes in their organization lead to serious health conditions such as Alzheimer´s and Parkinson´s diseases, autoimmune diseases, tumour growth, etc. This work mainly focuses on ganglioside organization into nanodomains and their dynamics within the plasma membrane. Current research investigates static ganglioside nanodomains characterization; nevertheless, the information about their diffusion is missing. In our study, fluorescence correlation spectroscopy is implemented together with stimulated emission depletion (STED-FCS), which combines the diffraction-unlimited spatial resolution with high temporal resolution. By comparison of the experiments performed on model vesicles containing 4 % of either GM1, GM2, or GM3 and Monte Carlo simulations of diffusion on the plasma membrane, the description of ganglioside clustering, diffusion of nanodomains, and even diffusion of ganglioside molecules inside investigated nanodomains are described.

Keywords: gangliosides, nanodomains, STED-FCS, flourescence microscopy, membrane diffusion

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Authors: Elham Zabetian Targhi, Niusha Fardnava, Saba Saghafi

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Urban resilience to Corona Virus has become a major concern for cities these days. Our country also has not been safe from the destructive effects of this virus in social, economic, physical, governance, and management dimensions; and according to official statistics, hundreds of thousands of people in Iran have been infected with this virus and tens of thousands have died so far. Therefore, to measure urban resilience to this pandemic, some criteria and sub-criteria were developed based on the authors’ documentary and field studies, and their significance or weights were determined using analytical-comparative research method using a questionnaire of paired or L-Saati comparisons from the viewpoint of experts in urban sciences and urban development using AHP hierarchical analysis in EXPERT CHOICE software. Then, designing a questionnaire with a five-point Likert scale, the satisfaction of Tehran residents with the extracted criteria and sub-criteria was measured and the correlation between the important criteria in each dimension was assessed using correlation tests in SPSS16 software. According to the obtained results of AHP analysis and the scores of each sub-criterion, the weight of all criteria was normal. In the next stage, according to the pairwise correlation tests between the important criteria in each dimension from the viewpoint of urban science experts and Tehran residents, it was concluded that the reliability of the correlation between the criteria is 99%. In all the cases, the P-value or the same significance level was less than 0.05, which indicated the significance of the pairwise relations between the variables.

Keywords: Urban Resilience, Pandemics, Corona Virus (Covid-19), Criteria.

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Authors: Hubert Klar

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High double excitation of two-electron atoms has been investigated using hyperpherical coordinates within a modified adiabatic expansion technique. This modification creates a novel fictitious force leading to a spontaneous exchange symmetry breaking at high double excitation. The Pauli principle must therefore be regarded as approximation valid only at low excitation energy. Threshold electron scattering from high Rydberg states shows an unexpected time reversal symmetry breaking. At threshold for double escape we discover a broad (few eV) Cooper pair.

Keywords: correlation, resonances, threshold ionization, Cooper pair

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Authors: Yoko Katsumata, Takashi Horikoshi, Noriaki Fukuzumi, Shoji Yamaguchi

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This study examined some positive sensations that caused human to experience an intense feeling or sensitivity from Venetian Masks. We surveyed 102 Japanese university students (male; 85, female; 17) about their sensitivity impressions toward Venetian Masks using sensitivity questionnaire. We used questionnaires to examine the relevance to transformation desire at Venetian masks by means of correlation analysis. The positive correlation coefficient was observed between sensitivity impressions and transformation desire.

Keywords: Venetian Masks, sensitivity impression, transformation desire, Japan

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Authors: Muhammad Yaqub Olatunde

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Arabic linguistic science is redirecting its focus towards the analysis and description of social, regional, and temporal varieties of social, regional, and temporal varieties in order to show how they vary in pronunciation, vocabulary, and grammar. This is not to say that the traditional Arabic linguists did not mention scores of dialectical variations but such works focused on the geographical boundaries of the Arabic speaking countries. There is need for a comprehensive survey of various Arabic dialects within the boundary of Arabic speaking countries and outside showing both the similarities and differences of linguistic and extra linguistic elements. This study therefore examines the syllable structure and process in noun and verb in the shuwa Arabic dialect speaking in North East Nigeria [mainly in Borno state]. The work seeks to establish the facts about this phenomenon, using auto- segmental analysis. These facts are compared, where necessary; using possible alternative analysis, with what operate in other related dialects within and outside Arabic speaking countries. The interaction between epenthesis and germination in the language also generate an interesting issue. The paper then conclude that syllable structure and process in the language need to recognize the existence of complex onset and a complex rhyme producing a consonant cluster in the former and a closed syllable in the letter. This emerges as result of resyllabification, which is motivated by these processes.

Keywords: Arabic, dialect, linguistics, processes, resyllabification

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Authors: Yalda Zarnegarnia, Shari Messinger

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Receiver operating characteristic (ROC) curves have been widely used in medical research to illustrate the performance of the biomarker in correctly distinguishing the diseased and non-diseased groups. Correlated biomarker data arises in study designs that include subjects that contain same genetic or environmental factors. The information about correlation might help to identify family members at increased risk of disease development, and may lead to initiating treatment to slow or stop the progression to disease. Approaches appropriate to a case-control design matched by family identification, must be able to accommodate both the correlation inherent in the design in correctly estimating the biomarker’s ability to differentiate between cases and controls, as well as to handle estimation from a matched case control design. This talk will review some developed methods for ROC curve estimation in settings with correlated data from case control design and will discuss the limitations of current methods for analyzing correlated familial paired data. An alternative approach using Conditional ROC curves will be demonstrated, to provide appropriate ROC curves for correlated paired data. The proposed approach will use the information about the correlation among biomarker values, producing conditional ROC curves that evaluate the ability of a biomarker to discriminate between diseased and non-diseased subjects in a familial paired design.

Keywords: biomarker, correlation, familial paired design, ROC curve

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Authors: Rhenan D. Estacio

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This research presents the career decision making difficulty and emotional quotient of one hundred fifty (150) college students of City College of Angeles, Academic Year 2016-2017. Independent sample T-test and Pearson r correlation were done to shifter and non-shifter in terms of their career decision making difficulty and emotional quotient. A significant positive correlation revealed (r=.302) on career decision making difficulty and emotional quotient. Also, a significant negative correlation revealed (r=-.329) on career decision making difficulty and a moderating variable which is age. The finding significantly shows that emotional quotient was associated and adds a significant incremental variance with career decision making difficulty. Moreover, age shows a moderating effect on career decision making difficulty by having a significant decline and increment on variables. Furthermore, categorization of career decision making difficulty and emotional quotient of said participants are described in this study. In addition, career guidance interventions were suggested based on the results of this study.

Keywords: career, decision-making, difficulty, emotional, quotient

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Authors: Safa A. Mohammed Ali, Ammar S. Ahamed, Mohammed Khair Abdalla

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The objectives of this study were to estimate the means and genetic parameters of birth and weaning weight of calves of pure Holstein-Friesian cows raised in Sudan. The traits studied were:*Weight at birth *Weight at weaning. The study also included some of the important factors that affected these traits. The data were analyzed using Harvey’s Least Squares and Maximum Likelihood programme. The results obtained showed that the overall mean weight at birth of the calves under study was 34.36±0.94kg. Male calves were found to be heavier than females; the difference between the sexes was highly significant (P<0.001). The mean weight at birth of male calves was 34.27±1.17 kg while that of females was 32.51±1.14kg. The effect of sex of calves, sire and parity of dam were highly significant (P<0.001). The overall mean of weight at weaning was 67.10 ± 5.05 kg, weight at weaning was significantly (p<0.001) effected by sex of calves, sire, year and season of birth have highly significant (P<0.001) effect on either trait. Also estimates heritabilities of birth weight was (0.033±0.015) lower than heritabilities of weaning weight (0.224±0.039), and genetic correlation was 0.563, the phenotypic correlation 0.281, and the environmental correlation 0.268.

Keywords: birth, weaning, weight, friesian

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Authors: Chao Hsing Yeh, Wei Chun Lin

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Background: Current management of aromatase inhibitor-induced arthralgia (AIA) in postmenopausal breast cancer survivors (PBCS) has limited effect. Method: In this prospective randomized clinical trial (RCT), a 4-week APA treatment was used to manage AIA. Twenty PBCS participated. After baseline data was collected, participants were waited for a month before they receive APA at a convenient time once a week for 4 weeks. Blood samples from participants in both groups were collected at baseline and after 4 weeks of treatment. The primary outcomes included: pain intensity, pain interference, stiffness, and physical function. Results: After the 4-week APA treatment, the pro-inflammatory cytokines and chemokines display a trend of mean percentage reduction (i.e., -22% in IL-1α, -4% in IL-1β, -1% in IL-2, -3% in IL-6, -19% in IL-12, -9% in Eotaxin, and -2% in MCP-1). The anti-inflammatory cytokine IL-10 and IL-13 (i.e., 5% in IL-10 and 29% in IL-13) increased from pre- to post-APA treatment. Significant positive correlation of percentage mean change was observed between symptom severity and eotaxin (ρ = 0.56; p < 0.01) & MCP-1 (ρ = 0.65; p < 0.01). Interference and chemokines (eotaxin & MIP-1) also shows positive correlation (ρ = 0.48; p < 0.01 & ρ = 0.39; p < 0.05). Another positive correlation was found between worst pain and chemokines (eotaxin, ρ = 0.48; p < 0.01 & MIP-1, ρ = 0.39; p < 0.05). Additionally, interference also shows positive correlation among IL-1α (ρ = 0.36; p < 0.05) and IL-β (ρ = 0.33; p < 0.05). Conclusion: These findings suggest that APA intervention may inhibit inflammation of AIA patients and chemokine could be one of the key factors of AIA symptom improvement.

Keywords: acupressure, cytokine, pain management, breast cancer survivors

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Authors: Masoumeh Moghbel

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Nowadays, carbon dioxide which is produced by human activities is considered as the main effective factor in the global warming occurrence. Regarding to the role of CO2 and its ability in trapping the heat, the main objective of this research is study the effect of atmospheric CO2 (which is recorded in Manaloa) on variations of temperature parameters (daily mean temperature, minimum temperature and maximum temperature) in 5 meteorological stations in Iran which were selected according to the latitude and altitude in 40 years statistical period. Firstly, the trend of temperature parameters was studied by Regression and none-graphical Man-Kendal methods. Then, relation between temperature variations and CO2 were studied by Correlation technique. Also, the impact of CO2 amount on temperature in different atmospheric levels (850 and 500 hpa) was analyzed. The results illustrated that correlation coefficient between temperature variations and CO2 in low latitudes and high altitudes is more significant rather than other regions. it is important to note that altitude as the one of the main geographic factor has limitation in affecting the temperature variations, so that correlation coefficient between these two parameters in 850 hpa (r=0.86) is more significant than 500 hpa (r = 0.62).

Keywords: altitude, atmospheric carbon dioxide, latitude, temperature variations

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Authors: Punwath Prum

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Superfund site is recognized publicly to be a severe environmental problem to surrounding communities and biodiversity due to its hazardous chemical waste from industrial activities. It contaminates the soil and water but also is a leading potential point-source pollution affecting ecosystem in watershed areas from chemical substances. The risks of Superfund site on watershed can be effectively measured by utilizing publicly available data and geospatial analysis by free and open source application. This study analyzed the vegetation change within high risked contaminated watersheds in Wisconsin. The high risk watersheds were measured by which watershed contained high number Superfund sites. The study identified two potential risk watersheds in Lafayette and analyzed the temporal changes of vegetation within the areas based on Normalized difference vegetation index (NDVI) analysis. The raster statistic was used to compare the change of NDVI value over the period. The analysis results showed that the NDVI value within the Superfund sites’ boundary has a significant lower value than nearby surrounding and provides an analogy for environmental hazard affect by the chemical contamination in Superfund site.

Keywords: soil contamination, spatial analysis, watershed

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Authors: I-Hui Hsieh, Yu-Hsuan Hu

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The powerful effect of music is often associated with changes in physiological responses such as heart rate and respiration. Previous studies demonstrate that Mayer waves of blood pressure, the spontaneous rhythm occurring at 0.1 Hz, corresponds to a progressive crescendo of the musical phrase. However, music contain dynamic changes in temporal and spectral features. As such, it remains unclear which aspects of musical structures optimally affect synchronization of cardiovascular rhythms. This study investigates the independent contribution of spectral pattern, temporal pattern, and dissonance level on synchronization of cardiovascular rhythms. The regularity of acoustical patterns occurring at a periodic rhythm of 0.1 Hz is hypothesized to elicit the strongest coherence of cardiovascular rhythms. Music excerpts taken from twelve pieces of Western classical repertoire were modulated to contain varying degrees of pattern regularity of the acoustic envelope structure. Three levels of dissonance were manipulated by varying the harmonic structure of the accompanying chords. Electrocardiogram and photoplethysmography signals were recorded for 5 minutes of baseline and simultaneously while participants listen to music excerpts randomly presented over headphones in a sitting position. Participants were asked to indicate the pleasantness of each music excerpt by adjusting via a slider presented on screen. Analysis of the Fourier spectral power of blood pressure around 0.1 Hz showed a significant difference between music excerpts characterized by spectral and temporal pattern regularity compared to the same content in random pattern. Phase coherence between heart rate and blood pressure increased significantly during listening to spectrally-regular phrases compared to its matched control phrases. The degree of dissonance of the accompanying chord sequence correlated with level of coherence between heart rate and blood pressure. Results suggest that low-level auditory features of music can entrain coherence of autonomic physiological variables. These findings have potential implications for using music as a clinical and therapeutic intervention for regulating cardiovascular functions.

Keywords: cardiovascular rhythms, coherence, dissonance, pattern regularity

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Authors: Yoon Suh Song

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Though music education can broaden one’s capacity for mathematical performance, many countries lag behind in music education. Little empirical evidence is found to identify the connection between math and music. Therefore, this research was set out to explore what music-related variables are associated with mathematical performance. The result of our analysis is as follows: A Pearson's Correlation analysis revealed that PISA math score is strongly correlated with students' Intelligence Quotient (IQ). This lays the foundation for further research as to what factors in students’ IQ lead to a better performance in math.

Keywords: music education, mathematical performance, education, IQ

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Authors: P. S. Hsi, Y. F. Wang, Y. F. Ho, P. C. Hung

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The aim of the present study was to explore the dermal exposure assessment model of chemicals that have been developed abroad and to evaluate the feasibility of chemical dermal exposure assessment model for manufacturing industry in Taiwan. We conducted and analyzed six semi-quantitative risk management tools, including UK - Control of substances hazardous to health ( COSHH ) Europe – Risk assessment of occupational dermal exposure ( RISKOFDERM ), Netherlands - Dose related effect assessment model ( DREAM ), Netherlands – Stoffenmanager ( STOFFEN ), Nicaragua-Dermal exposure ranking method ( DERM ) and USA / Canada - Public Health Engineering Department ( PHED ). Five types of manufacturing industry were selected to evaluate. The Monte Carlo simulation was used to analyze the sensitivity of each factor, and the correlation between the assessment results of each semi-quantitative model and the exposure factors used in the model was analyzed to understand the important evaluation indicators of the dermal exposure assessment model. To assess the effectiveness of the semi-quantitative assessment models, this study also conduct quantitative dermal exposure results using prediction model and verify the correlation via Pearson's test. Results show that COSHH was unable to determine the strength of its decision factor because the results evaluated at all industries belong to the same risk level. In the DERM model, it can be found that the transmission process, the exposed area, and the clothing protection factor are all positively correlated. In the STOFFEN model, the fugitive, operation, near-field concentrations, the far-field concentration, and the operating time and frequency have a positive correlation. There is a positive correlation between skin exposure, work relative time, and working environment in the DREAM model. In the RISKOFDERM model, the actual exposure situation and exposure time have a positive correlation. We also found high correlation with the DERM and RISKOFDERM models, with coefficient coefficients of 0.92 and 0.93 (p<0.05), respectively. The STOFFEN and DREAM models have poor correlation, the coefficients are 0.24 and 0.29 (p>0.05), respectively. According to the results, both the DERM and RISKOFDERM models are suitable for performance in these selected manufacturing industries. However, considering the small sample size evaluated in this study, more categories of industries should be evaluated to reduce its uncertainty and enhance its applicability in the future.

Keywords: dermal exposure, risk management, quantitative estimation, feasibility evaluation

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Authors: Y. Zheng, M. Busi, A. F. Pedersen, M. A. Beltran, C. Gundlach

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X-ray phase contrast imaging has shown to yield a better contrast compared to conventional attenuation X-ray imaging, especially for soft tissues in the medical imaging energy range. This can potentially lead to better diagnosis for patients. However, phase contrast imaging has mainly been performed using highly brilliant Synchrotron radiation, as it requires high coherence X-rays. Many research teams have demonstrated that it is also feasible using a laboratory source, bringing it one step closer to clinical use. Nevertheless, the requirement of fine gratings and high precision stepping motors when using a laboratory source prevents it from being widely used. Recently, a random phase object has been proposed as an analyzer. This method requires a much less robust experimental setup. However, previous studies were done using a particular X-ray source (liquid-metal jet micro-focus source) or high precision motors for stepping. We have been working on a much simpler setup with just small modification of a commercial bench-top micro-CT (computed tomography) scanner, by introducing a piece of sandpaper as the phase analyzer in front of the X-ray source. However, it needs a suitable algorithm for speckle tracking and 3D reconstructions. The precision and sensitivity of speckle tracking algorithm determine the resolution of the system, while the 3D reconstruction algorithm will affect the minimum number of projections required, thus limiting the temporal resolution. As phase contrast imaging methods usually require much longer exposure time than traditional absorption based X-ray imaging technologies, a dynamic phase contrast micro-CT with a high temporal resolution is particularly challenging. Different reconstruction methods, including neural network based techniques, will be evaluated in this project to increase the temporal resolution of the phase contrast micro-CT. A Monte Carlo ray tracing simulation (McXtrace) was used to generate a large dataset to train the neural network, in order to address the issue that neural networks require large amount of training data to get high-quality reconstructions.

Keywords: micro-ct, neural networks, reconstruction, speckle-based x-ray phase contrast

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Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

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Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

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Authors: Nima Shafaghi, Gunay Anlaş, C. Can Aydiner

Abstract:

A realistic understanding of martensitic phase transition under complex stress states is key for accurately describing the mechanical behavior of shape memory alloys (SMAs). Particularly regarding the sharply changing stress fields at the tip of a crack, the size, nature and shape of transformed zones are of great interest. There is significant variation among various analytical models in their predictions of the size and shape of the transformation zone. As the fully transformed region remains inside a very small boundary at the tip of the crack, experimental validation requires microscopic resolution. Here, the crack tip vicinity of NiTi compact tension specimen has been monitored in situ with microscopic image correlation with 20x magnification. With nominal 15 micrometer grains and 0.2 micrometer per pixel optical resolution, the strains at the crack tip are mapped with intra-grain detail. The transformation regions are then deduced using an equivalent strain formulation.

Keywords: digital image correlation, fracture, martensitic phase transition, mode I, NiTi, transformation zone

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Authors: Saif Khan Sunny, Md. Masud-ul-alam

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This study presents the association of photosynthetic pigment: chlorophyll-a (chl-a) and physical parameters: sea surface temperature (SST), dissolved oxygen (DO), sea surface salinity (SSS), and total dissolved solids (TDS) in the northeastern Bay of Bengal. At 15 sampling stations in the bay near the eastern coast of Teknaf, photosynthetic pigment and environmental variables were measured for surface water where acetone extraction was used for ch-a. Samples of seawater were taken in March 2021, where chlorophyll-a content varies from 0.554 to 9.696 mg/m3 in surface water over the sampling site. Higher concentrations may be attributable to the nutrient supply of hatcheries and the delivery of fluvial input. The observed SST, DO, SSS, and TDS in the north-eastern Bay of Bengal are 26.65 to 28.6 °C, 6.26 to 8.03 mg/l, 29.3 to 33.1 PSU, and 22.4 to 25.3 ppm, respectively. Temperature and chl-a had a positive association (0.18), according to an analysis of the cross-correlation matrix. Again, a negative correlation (0.34) between dissolved oxygen and temperature is significant at p < 0.05. Total dissolved solids and dissolved oxygen have a significant negative correlation (0.70) where p is < 0.001.

Keywords: photosynthetic pigment, nutrient supply, chlorophyll, physical parameters

Procedia PDF Downloads 90

Authors: Kseniya Gladun

Abstract:

Tactile stimulation of a dorsal side of the wrist can have a strong impact on our attitude toward physical objects such as pleasant and unpleasant impact. This study explored different aspects of tactile perception to investigate atypical touch sensitivity in children with autism spectrum disorder (ASD). This study included 40 children with ASD and 40 healthy children aged 5 to 9 years. We recorded rsEEG (sampling rate of 250 Hz) during 20 min using EEG amplifier “Encephalan” (Medicom MTD, Taganrog, Russian Federation) with 19 AgCl electrodes placed according to the International 10–20 System. The electrodes placed on the left, and right mastoids served as joint references under unipolar montage. The registration of EEG v19 assignments was carried out: frontal (Fp1-Fp2; F3-F4), temporal anterior (T3-T4), temporal posterior (T5-T6), parietal (P3-P4), occipital (O1-O2). Subjects were passively touched by 4 types of tactile stimuli on the left wrist. Our stimuli were presented with a velocity of about 3–5 cm per sec. The stimuli materials and procedure were chosen for being the most "pleasant," "rough," "prickly" and "recognizable". Type of tactile stimulation: Soft cosmetic brush - "pleasant" , Rough shoe brush - "rough", Wartenberg pin wheel roller - "prickly", and the cognitive tactile stimulation included letters by finger (most of the patient’s name ) "recognizable". To designate the moments of the stimuli onset-offset, we marked the moment when the moment of the touch began and ended; the stimulation was manual, and synchronization was not precise enough for event-related measures. EEG epochs were cleaned from eye movements by ICA-based algorithm in EEGLAB plugin for MatLab 7.11.0 (Mathwork Inc.). Muscle artifacts were cut out by manual data inspection. The response to tactile stimuli was significantly different in the group of children with ASD and healthy children, which was also depended on type of tactile stimuli and the severity of ASD. Amplitude of Alpha rhythm increased in parietal region to response for only pleasant stimulus, for another type of stimulus ("rough," "thorny", "recognizable") distinction of amplitude was not observed. Correlation dimension D2 was higher in healthy children compared to children with ASD (main effect ANOVA). In ASD group D2 was lower for pleasant and unpleasant compared to the background in the right parietal area. Hilbert transform changes in the frequency of the theta rhythm found only for a rough tactile stimulation compared with healthy participants only in the right parietal area. Children with autism spectrum disorders and healthy children were responded to tactile stimulation differently with specific frequency distribution alpha and theta band in the right parietal area. Thus, our data supports the hypothesis that rsEEG may serve as a sensitive index of altered neural activity caused by ASD. Children with autism have difficulty in distinguishing the emotional stimuli ("pleasant," "rough," "prickly" and "recognizable").

Keywords: autism, tactile stimulation, Hilbert transform, pediatric electroencephalography

Procedia PDF Downloads 250

Authors: Zohreh Marbooti, Rezvan Khavari

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Groundwater as an essential part of natural resources seems to be an important issue in environmental engineering, so preservation and purification of it can have a critical value for any community. This paper investigates the concentration of elements of Pb, Cd, As, Se. For ground water in Behbahan (a city on south west of Iran), to this purpose a group of 30 wells were studied to examine the concentration of the elements of Pb, Cd, As, Se, and also to determine PH, EC, TDS, temperature and the ions of HCO32-, SO42-, Cl-, Na+, Mg2+, Ca2+, K+ for the wells. Results of the analyses show that the concentration of the elements of Pb, As and, Cd in 33,13,56 percent of the wells respectively and Se in all the samples were greater than normal range of WHO. Since there is a low correlation between Pb and major ions of (HCO32-, SO42-, Cl-, Na+, Mg2+, Ca2+, K+) it can be revealed that Pb overconcentration caused by human contamination. Relative great correlation between Se and the ions showed that Se derived from Gypsum and Dolomit. The big correlation between As and major cations and onions, imply that As can originate from dissolution and liquidation of mineral evaporation in the zone. The high rate of Cadmium concentration in urban sewagewater is due to the small industries, workshops and, mills wastewater.

Keywords: heavy elements, underground water, pollution, waste water

Procedia PDF Downloads 560

Authors: Azadeh Golshan, Craig Evans, Phillip Geary, Abigail Morrow, Zoe Rogers, Marcel Maeder

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22 physicochemical variables have been determined in water samples collected weekly from January to December in 2013 from three sampling stations located within a major drinking water reservoir. Classical Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) analysis was used to investigate the environmental factors associated with the physico-chemical variability of the water samples at each of the sampling stations. Matrix augmentation MCR-ALS (MA-MCR-ALS) was also applied, and the two sets of results were compared for interpretative clarity. Links between these factors, reservoir inflows and catchment land-uses were investigated and interpreted in relation to chemical composition of the water and their resolved geographical distribution profiles. The results suggested that the major factors affecting reservoir water quality were those associated with agricultural runoff, with evidence of influence on algal photosynthesis within the water column. Water quality variability within the reservoir was also found to be strongly linked to physical parameters such as water temperature and the occurrence of thermal stratification. The two methods applied (MCR-ALS and MA-MCR-ALS) led to similar conclusions; however, MA-MCR-ALS appeared to provide results more amenable to interpretation of temporal and geological variation than those obtained through classical MCR-ALS.

Keywords: drinking water reservoir, multivariate analysis, physico-chemical parameters, water quality

Procedia PDF Downloads 291