Search results for: significant wave data

Authors: Nasir Mehmood, Muhammad Yar Khan, Anam Javeed

Abstract:

This study aims to scrutinize the dynamics which tend to impact customer’s purchasing intention of Islamic credit card and nexus of product’s knowledge and religiosity with the attitude of potential Islamic credit card’s customer. The theory of reasoned action strengthened the idea that intentions due to its proven predictive power are most likely to instigate intended consumer behavior. Particularly, the study examines the relationships of perceived financial cost (PFC), subjective norms (SN), and attitude (ATT) with the intention to purchase Islamic credit cards. Using a convenience sampling approach, data have been collected from 450 customers of banks located in Rawalpindi and Islamabad. A five-point Likert scale self-administered questionnaire was used to collect the data. The data were analyzed using the Statistical Package of Social Sciences (SPSS) through the procedures of principal component and multiple regression analysis. The results suggested that customer’s religiosity and product knowledge are strong indicators of attitude towards buying Islamic credit cards. Likewise, subjective norms, attitude, and perceived financial cost have a significant positive impact on customers’ purchase intent of Islamic bank’s credit cards. This study models a useful path for future researchers to further investigate the underlined phenomenon along with a variety of psychodynamic factors which are still in its infancy, at least in the Pakistani banking sector. The study also provides an insight to the practitioners and Islamic bank managers for directing their efforts toward educating customers regarding the use of Islamic credit cards and other financial products.

Keywords: attitude, Islamic credit card, religiosity, subjective norms

Procedia PDF Downloads 144

Authors: Mohamed Abdalla Saleem, Hana Ellafi

Abstract:

The study area is located in the eastern part of the Sirt Basin, in the Sarir-Hameimat arm of the basin, south of Amal High. The area covers the northern part of the Hamemat Trough and the Rakb High. All of these tectonic elements are part of the major and common tectonics that were created when the old Sirt Arch collapsed, and most of them are trending NW-SE. This study has been conducted to investigate the subsurface structures and the sedimentology characterization of the area and attempt to define its development tectonically and stratigraphically. About 7600 land gravity measurements, 22500 gridded magnetic data, and petrographic core data from some wells were used to investigate the subsurface structural features both vertically and laterally. A third-order separation of the regional trends from the original Bouguer gravity data has been chosen. The residual gravity map reveals a significant number of high anomalies distributed in the area, separated by a group of thick sediment centers. The reduction to the pole magnetic map also shows nearly the same major trends and anomalies in the area. Applying the further interpretation filters reveals that these high anomalies are sourced from different depth levels; some are deep-rooted, and others are intruded igneous bodies within the sediment layers. The petrographic sedimentology study for some wells in the area confirmed the presence of these igneous bodies and defined their composition as most likely to be gabbro hosted by marine shale layers. Depth investigation of these anomalies by the average depth spectrum shows that the average basement depth is about 7.7 km, while the top of the intrusions is about 2.65 km, and some near-surface magnetic sources are about 1.86 km. The depth values of the magnetic anomalies and their location were estimated specifically using the 3D Euler deconvolution technique. The obtained results suggest that the maximum depth of the sources is about 4938m. The total horizontal gradient of the magnetic data shows that the trends are mostly extending NW-SE, others are NE-SW, and a third group has an N-S extension. This variety in trend direction shows that the area experienced different tectonic regimes throughout its geological history.

Keywords: sirt basin, tectonics, gravity, magnetic

Procedia PDF Downloads 66

Authors: Maria Fernanda Ordoñez Martinez, Alvaro Mauricio Montenegro

Abstract:

This work presents a statistical methodology for measuring and founding constructs in Latent Semantic Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations present on Item Response Theory. More precisely, we propose initially reducing dimensionality with specific use of Principal Component Analysis for the linguistic data and then, producing axes of groups made from a clustering analysis of the semantic data. This approach allows the user to give meaning to previous clusters and found the real latent structure presented by data. The methodology is applied in a set of real semantic data presenting impressive results for the coherence, speed and precision.

Keywords: semantic analysis, factorial analysis, dimension reduction, penalized logistic regression

Procedia PDF Downloads 443

Authors: Aminat Sheriff Owolabi

Abstract:

This study focused on what and how viewers perceive female portrayal in Nigerian Hip Hop music video based on scholars’ submission that Hip Hop music video is one of the media contents that objectifies women the most. However, this study examined how female artistes are portrayed sexually in Nigerian Hip Hop music videos. A model was developed in this study to examine the relationship between viewers’ perceptions and female portrayal in Nigerian Hip Hop music videos and from this model; three hypotheses were formulated and tested. Objectification theory of the psychology was also used to examine the manner at which women are portrayed in Nigerian Hip Hop Music as well as the relationship between the perceived portrayal and viewers’ perceptions. Survey research method was equally employed to gather data from 300 undergraduates in Kwara State and two Nigerian Hip Hop music producers who form the population of this study. From the result of the analyzed data and the tested hypotheses, it was discovered that there is a significant relationship between portrayal of female artistes in Nigerian Hip Hop music and viewers’ perception. As part of the suggestions, further study should include examination of how other media content portrays women.

Keywords: female artistes, Hip Hop, objectification, portrayal

Procedia PDF Downloads 280

Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

Abstract:

Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

Procedia PDF Downloads 196

Authors: Hao-Wei Fu, Chung-Feng Kao

Abstract:

In the era of rapid technological advancement, information technology (IT) has become integral to modern life, exerting significant influence across diverse sectors and serving as a catalyst for development in various industries. Within agriculture, the integration of IT offers substantial benefits, notably enhancing operational efficiency. Real-time monitoring systems, for instance, have been widely embraced in agriculture, effectively improving crop management practices. This study specifically addresses the management of rice panicle fertilizer, presenting the development of a web application tailored to handle data associated with rice panicle fertilizer management. Leveraging the normalized difference red edge index, this application optimizes the quantity of rice panicle fertilizer used, providing recommendations to agricultural stakeholders and service providers in the agricultural information sector. The overarching objective is to minimize costs while maximizing yields. Furthermore, a robust database system has been established to store and manage relevant data for future reference in rice cultivation management. Additionally, the study utilizes the Representational State Transfer software architectural style to construct an application programming interface (API), facilitating data creation, retrieval, updating, and deletion for users via the HyperText Transfer Protocol methods. Future plans involve integrating this API with third-party services to incorporate it into larger frameworks, thus catering to the diverse requirements of various third-party services.

Keywords: application programming interface, HyperText Transfer Protocol, nitrogen fertilizer intelligent management, web-based application

Procedia PDF Downloads 61

Authors: Maria Georgiou

Abstract:

This study examined whether there was a statistically significant difference between pretest and posttest achievement scores for students who received multimedia-based instructions in science. The paired samples t-test was used to address the research question and to establish whether there was a significant difference between pretest and posttest scores that may have occurred based on the students’ learning experience with multimedia technology. Findings indicated that there was a significant difference in students’ achievement scores before and after a multimedia-based instruction. Students’ achievement scores were increased by approximately two points, after students received multimedia-based instruction. On a paired samples t-test, a high level of significance was found, p = 0.000. Opportunities to learn with multimedia are more likely to result in sustained improvements in student achievement and a deeper understanding of science content. Multimedia can make learning more active and student-centered and activate student motivation.

Keywords: constructivist learning, hyperstudio, multimedia, multimedia-based instruction

Procedia PDF Downloads 162

Authors: Mohammadamin Hashemi, Mohammadreza Kashizadeh

Abstract:

Droughts pose a significant threat to sustainable water resource management, agriculture, and socioeconomic sectors, particularly in the field of climate change. This study investigates drought simulation using rainfall-runoff modelling in the Cuneo district, Italy, over the past 60-year period. The study leverages the TUW model, a lumped conceptual rainfall-runoff model with a semi-distributed operation capability. Similar in structure to the widely used Hydrologiska Byråns Vattenbalansavdelning (HBV) model, the TUW model operates on daily timesteps for input and output data specific to each catchment. It incorporates essential routines for snow accumulation and melting, soil moisture storage, and streamflow generation. Multiple catchments' discharge data within the Cuneo district form the basis for thorough model calibration employing the Kling-Gupta Efficiency (KGE) metric. A crucial metric for reliable drought analysis is one that can accurately represent low-flow events during drought periods. This ensures that the model provides a realistic picture of water availability during these critical times. Subsequent validation of monthly discharge simulations thoroughly evaluates overall model performance. Beyond model development, the investigation delves into drought analysis using the robust Standardized Runoff Index (SRI). This index allows for precise characterization of drought occurrences within the study area. A meticulous comparison of observed and simulated discharge data is conducted, with particular focus on low-flow events that characterize droughts. Additionally, the study explores the complex interplay between land characteristics (e.g., soil type, vegetation cover) and climate variables (e.g., precipitation, temperature) that influence the severity and duration of hydrological droughts. The study's findings demonstrate successful calibration of the TUW model across most catchments, achieving commendable model efficiency. Comparative analysis between simulated and observed discharge data reveals significant agreement, especially during critical low-flow periods. This agreement is further supported by the Pareto coefficient, a statistical measure of goodness-of-fit. The drought analysis provides critical insights into the duration, intensity, and severity of drought events within the Cuneo district. This newfound understanding of spatial and temporal drought dynamics offers valuable information for water resource management strategies and drought mitigation efforts. This research deepens our understanding of drought dynamics in the Cuneo region. Future research directions include refining hydrological modelling techniques and exploring future drought projections under various climate change scenarios.

Keywords: hydrologic extremes, hydrological drought, hydrological modelling, machine learning, rainfall-runoff modelling

Procedia PDF Downloads 41

Authors: Kenneth O. Otasowie, Matthew Ikuabe, Clinton Aigbavboa, Ayodeji Oke

Abstract:

Construction project cost are not only made up of production costs. This cost comprises of many other elements such as the preparation of a bidding document, cost estimations, drafting contractual agreements and monitoring that contractual obligations are met. Several studies have stressed the need for transaction costs (TC) to be defined in a way that covers all phases of a project and not only the pre-contract phase. Hence, this study aims to appraise transaction cost in South African (SA) construction projects by assessing what constitutes transaction cost, influencing factors and possible optimisation measures. A survey design was adopted. A total number of eighty (80) questionnaires were administered to quantity surveyors, procurement managers and project managers in Guateng Province, SA and seventy-two (72) were returned and found suitable for analysis. Collected data was analysed using percentage, mean item score, standard deviation, one-sample t-test. The findings show that external technical interaction, uncertainty, human factors are the most significant constituents of TC in SA, while technical competency, experience in similar project type and project characteristics are the leading influencing factors. Furthermore, understanding project characteristics, clear communication and technically competent project teams are most of the significant measures for optimising TC in SA construction projects. Therefore, this study recommends that a competent project team and a clear communication are fundamental to proper management of TC in SA construction projects.

Keywords: construction projects, project cost, South Africa, transaction cost

Procedia PDF Downloads 99

Authors: Ya-Ching Wang, Yi-Maun Subeq

Abstract:

Background: There is a lack of evidence to understand differences in risk for developing breast cancer between sexual minority women and heterosexual women in Taiwan. The purpose of this study is to compare differences in risk for developing breast cancer between the two groups of Taiwanese women. Methods: An online cross-sectional survey was used to collect data. A total of 238 Taiwanese women (mean age 30.69 years old, SD=8.231, range 20-60) were recruited between December 2016 and February 2017, including 115 heterosexual women and 123 sexual minority women. Results: There were no significant differences between heterosexual women and sexual minority women in body mass index, history of non-malignant breast disease, age at menarche and menopause, use of hormone replacement therapy, use of hormone replacement therapy, nor the prevalence of breast cancer. The sexual minority women had higher rates of current drinking, smoking and using breast-bindings and also reported exercise more a week; the heterosexual women had higher rates of pregnancy, children, breastfeed, miscarriages, abortion and use of birth control pills. Discussion/Conclusion: There were significant differences between heterosexual women and sexual minority women in reproductive factors and behavioral risk factors for the development of breast cancer. In particular, the finding that the sexual minority women had higher rate of using breast-bindings (56.6%) than the heterosexual women (4.7%) should be further explore, in order to understand whether long-term breast compression is associated with the development of breast cancer.

Keywords: breast cancer, risk, sexual orientation, Taiwan

Procedia PDF Downloads 365

Authors: Ross J. Maestas

Abstract:

Biofuels are derived from multiple renewable bioenergy feedstocks including animal fats, wood, starchy grains, and oil seeds. Transportation agencies have considered growing the latter two on underutilized and nontraditional lands that they manage, such as in the Right of Way (ROW), abandoned weigh stations, and at maintenance yards. These crops provide the opportunity to generate revenue or supplement fuel once converted and offer a solution to increasing fuel costs and instability by creating a ‘home-grown’ alternative. Biofuels are non-toxic, biodegradable, and emit less Green House Gasses (GHG) than fossil fuels, therefore allowing agencies to meet sustainability goals and regulations. Furthermore, they enable land managers to achieve soil erosion and roadside aesthetic strategies. The research sought to understand if the cultivation of a biofuel feedstock within the Arkansas State Highway Transportation Department’s (AHTD) managed and marginalized lands is feasible by identifying potential land areas and crops. To determine potential plots the parcel data was downloaded from Arkansas’s GIS office. ArcGIS was used to query the data for all variations of the names of property owned by AHTD and a KML file was created that identifies the queried parcel data in Google Earth. Furthermore, biofuel refineries in the state were identified to optimize the harvest to transesterification process. Agricultural data was collected from federal and state agencies and universities to assess various oil seed crops suitable for conversion and suited to grow in Arkansas’s climate and ROW conditions. Research data determined that soybean is the best adapted biofuel feedstock for Arkansas with camelina and canola showing possibilities as well. Agriculture is Arkansas’s largest industry and soybean is grown in over half of the state’s counties. Successful cultivation of a feedstock in the aforementioned areas could potentially offer significant employment opportunity for which the skilled farmers already exist. Based on compiled data, AHTD manages 21,489 acres of marginalized land. The result of the feasibility assessment offer suggestions and guidance should AHTD decide to further investigate this type of initiative.

Keywords: Arkansas highways, biofuels, renewable energy initiative, marginalized lands

Procedia PDF Downloads 329

Authors: Norman Sinnigen, Igor Izyurov, Marina Krylova, Hamidreza Jamalabadi, Sarah Alizadeh, Martin Walter

Abstract:

Background: EEG is a non-invasive brain activity recording technique with a high temporal resolution that allows the use of real-time applications, such as neurofeedback. However, EEG data are susceptible to electrooculographic (EOG) and electromyography (EMG) artifacts (i.e., jaw clenching, teeth squeezing and forehead movements). Due to their non-stationary nature, these artifacts greatly obscure the information and power spectrum of EEG signals. Many EEG artifact correction methods are too time-consuming when applied to low-density EEG and have been focusing on offline processing or handling one single type of EEG artifact. A software-only real-time method for correcting multiple types of EEG artifacts of high-density EEG remains a significant challenge. Methods: We demonstrate an improved approach for automatic real-time EEG artifact correction of EOG and EMG artifacts. The method was tested on three healthy subjects using 64 EEG channels (Brain Products GmbH) and a sampling rate of 1,000 Hz. Captured EEG signals were imported in MATLAB with the lab streaming layer interface allowing buffering of EEG data. EMG artifacts were detected by channel variance and adaptive thresholding and corrected by using channel interpolation. Real-time independent component analysis (ICA) was applied for correcting EOG artifacts. Results: Our results demonstrate that the algorithm effectively reduces EMG artifacts, such as jaw clenching, teeth squeezing and forehead movements, and EOG artifacts (horizontal and vertical eye movements) of high-density EEG while preserving brain neuronal activity information. The average computation time of EOG and EMG artifact correction for 80 s (80,000 data points) 64-channel data is 300 – 700 ms depending on the convergence of ICA and the type and intensity of the artifact. Conclusion: An automatic EEG artifact correction algorithm based on channel variance, adaptive thresholding, and ICA improves high-density EEG recordings contaminated with EOG and EMG artifacts in real-time.

Keywords: EEG, muscle artifacts, ocular artifacts, real-time artifact correction, real-time ICA

Procedia PDF Downloads 180

Authors: M. Graus, K. Westhoff, X. Xu

Abstract:

The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: data analytics, green production, industrial energy management, optimization, renewable energies, simulation

Procedia PDF Downloads 435

Authors: Murniwati, Nurul Khairiyah, Putri Ovieza Maizar

Abstract:

The association between general and oral health is clearly important, particularly in adults with medical conditions. Many of the medical systemic conditions are either caused or aggravated by poor oral hygiene and vice versa. Hypertension is one of common medical systemic problem which has been a public health concern worldwide due to its known consequences. Those consequences must be related to oral health status as well, whether it may cause or worsen the oral health conditions. The objective of this study was to find out the association between hypertension and oral health status in adults. This study was an analytical observational study by using cross-sectional method. A total of 42 adults both male and female in Padusunan Village, Pariaman, West Sumatra, Indonesia were selected as subjects by using purposive sampling. Manual sphygmomanometer was used to measure blood pressure and dental examination was performed to calculate the decayed, missing, and filled teeth (DMFT) scores in order to represent oral health status. The data obtained was analyzed statistically using One Way ANOVA to determine the association between hypertensive adults and their oral health status. The result showed that majority age of the subjects was ranging from 51-70 years (40.5%). Based on blood pressure examination, 57.1% of subjects were classified to prehypertension. Overall, the mean of DMFT score calculated in normal, prehypertension and hypertension group was not considered statistically significant. There was no significant association (p>0.05) between hypertension and oral health status in adults.

Keywords: blood pressure, hypertension, DMFT, oral health status

Procedia PDF Downloads 328

Authors: K. Umbleja, M. Ichino, H. Yaguchi

Abstract:

In this paper, we propose a coloring method for multivariate data visualization by using parallel coordinates based on dissimilarity and tree structure information gathered during hierarchical clustering. The proposed method is an extension for proximity-based coloring that suffers from a few undesired side effects if hierarchical tree structure is not balanced tree. We describe the algorithm by assigning colors based on dissimilarity information, show the application of proposed method on three commonly used datasets, and compare the results with proximity-based coloring. We found our proposed method to be especially beneficial for symbolic data visualization where many individual objects have already been aggregated into a single symbolic object.

Keywords: data visualization, dissimilarity-based coloring, proximity-based coloring, symbolic data

Procedia PDF Downloads 170

Authors: Narendra Kumar

Abstract:

This study uses data from the ‘National Family Health Survey (NFHS-3) 2005-06’ to investigate the predictors of infant and child mortality among low economic households in East and Northeast region. The cross tabulation, life table survival estimates and Cox proportional hazard model techniques have been used to estimate the predictors of infant and child mortality. The life table survival estimates for infant and child mortality shows that infant mortality in female child is lower in comparison to male child but with child mortality, the rates are higher for female in comparison to male child and the Cox proportional hazard model also give highly significant in female in comparison to male child. The infant and child mortality rates among poor households highest in the Central region followed by North and Northeast region and the lowest in South region in comparison to all regions of India. Education of respondent has been found a significant characteristics in both analyzes, further birth interval, respondent occupation, caste/tribe and place of delivery has substantial impact on infant and child mortality among low economic households in East and Northeast region. Finally these findings specified that an increase in parents’ education, improve health care services and improve socioeconomic conditions of low economic households which should in turn raise infant and child survival and should decrease child mortality among low economic households in India.

Keywords: infant, child, mortality, socio-economic, India

Procedia PDF Downloads 307

Authors: Seonaid Hume, Gordon Dobie, Graeme West

Abstract:

Detecting and localizing radioactive sources is a necessity for safe and secure decommissioning of nuclear facilities. An important aspect for the management of the sort-and-segregation process is establishing the spatial distributions and quantities of the waste radionuclides, their type, corresponding activity, and ultimately classification for disposal. The data received from surveys directly informs decommissioning plans, on-site incident management strategies, the approach needed for a new cell, as well as protecting the workforce and the public. Manual classification of nuclear waste from a nuclear cell is time-consuming, expensive, and requires significant expertise to make the classification judgment call. Also, in-cell decommissioning is still in its relative infancy, and few techniques are well-developed. As with any repetitive and routine tasks, there is the opportunity to improve the task of classifying nuclear waste using autonomous systems. Hence, this paper proposes a new framework for the automatic classification of nuclear waste. This framework consists of five main stages; 3D spatial mapping and object detection, object classification, radiological mapping, source localisation based on gathered evidence and finally, waste classification. The first stage of the framework, 3D visual mapping, involves object detection from point cloud data. A review of related applications in other industries is provided, and recommendations for approaches for waste classification are made. Object detection focusses initially on cylindrical objects since pipework is significant in nuclear cells and indeed any industrial site. The approach can be extended to other commonly occurring primitives such as spheres and cubes. This is in preparation of stage two, characterizing the point cloud data and estimating the dimensions, material, degradation, and mass of the objects detected in order to feature match them to an inventory of possible items found in that nuclear cell. Many items in nuclear cells are one-offs, have limited or poor drawings available, or have been modified since installation, and have complex interiors, which often and inadvertently pose difficulties when accessing certain zones and identifying waste remotely. Hence, this may require expert input to feature match objects. The third stage, radiological mapping, is similar in order to facilitate the characterization of the nuclear cell in terms of radiation fields, including the type of radiation, activity, and location within the nuclear cell. The fourth stage of the framework takes the visual map for stage 1, the object characterization from stage 2, and radiation map from stage 3 and fuses them together, providing a more detailed scene of the nuclear cell by identifying the location of radioactive materials in three dimensions. The last stage involves combining the evidence from the fused data sets to reveal the classification of the waste in Bq/kg, thus enabling better decision making and monitoring for in-cell decommissioning. The presentation of the framework is supported by representative case study data drawn from an application in decommissioning from a UK nuclear facility. This framework utilises recent advancements of the detection and mapping capabilities of complex radiation fields in three dimensions to make the process of classifying nuclear waste faster, more reliable, cost-effective and safer.

Keywords: nuclear decommissioning, radiation detection, object detection, waste classification

Procedia PDF Downloads 200

Authors: Niu Shu Fen

Abstract:

Sleep disturbance is highly prevalent among shift-working nurses. We aimed to evaluate whether aerobic exercise (i.e., walking combined with jogging) improves objective Sleepparameters among female nurses at the end of an 8-week exercise program and 4 weeks after study completion. This single-blinded, parallel design, randomized controlled trial was conducted in the floor classroom of a would-be medical center in northern Taiwan. Sixtyeligible female nurses were randomly assigned to either aerobic exercise (n = 30) or usual care (n = 30) group. The moderate-intensity aerobic exercise program was performed over 5days (60 min per day) a week for 8 weeks after work hours. Objective sleep outcomes including total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE), were retrieved using an Actigraph device. A generalized estimated equation model was used for data analyses. The aerobic exercise group had significant improvements in TST and SE at 4 weeks and 8 weeks compared with baseline evaluation(TST: B = 70.49 and 55.96, both p < 0.001; SE: B = 5.21 and 3.98, p < 0.001 and 0.002).Significant between-group differences were observed in SOL and WASO at 4 weeks but not8 weeks compared with the baseline evaluation (SOL: B = −7.18, p = 0.03; WASO: B =−11.38, p = 0.008). The positive lasting effects for TST were observed only until the 4-week follow-up. To improve sleep quality and quantity, we encourage female nurses to regularly perform moderate-intensity aerobic exercise.

Keywords: sleep quality, aerobic exercise, nurses, shift work

Procedia PDF Downloads 144

Authors: Antonina A. Shumakova, Sergey A. Khotimchenko

Abstract:

The relevance of research is associated, on the one hand, with an ever-increasing volume of production and the expansion of the scope of application of engineered nanomaterials (ENMs), and on the other hand, with the lack of sufficient scientific information on the nature of the interactions of nanoparticles (NPs) with components of biogenic and abiogenic origin. In particular, studying the effect of ENMs (TiO2 NPs, SiO2 NPs, Al2O3 NPs, fullerenol) on the toxicometric characteristics of common contaminants such as lead and cadmium is an important hygienic task, given the high probability of their joint presence in food products. Data were obtained characterizing a multidirectional change in the toxicity of model toxicants when they are co-administered with various types of ENMs. One explanation for this fact is the difference in the adsorption capacity of ENMs, which was further studied in in vitro studies. For this, a method was proposed based on in vitro modeling of conditions simulating the environment of the small intestine. It should be noted that the obtained data are in good agreement with the results of in vivo experiments: - with the combined administration of lead and TiO2 NPs, there were no significant changes in the accumulation of lead in rat liver; in other organs (kidneys, spleen, testes and brain), the lead content was lower than in animals of the control group; - studying the combined effect of lead and Al2O3 NPs, a multiple and significant increase in the accumulation of lead in rat liver was observed with an increase in the dose of Al2O3 NPs. For other organs, the introduction of various doses of Al2O3 NPs did not significantly affect the bioaccumulation of lead; - with the combined administration of lead and SiO2 NPs in different doses, there was no increase in lead accumulation in all studied organs. Based on the data obtained, it can be assumed that at least three scenarios of the combined effects of ENMs and chemical contaminants on the body: - ENMs quite firmly bind contaminants in the gastrointestinal tract and such a complex becomes inaccessible (or inaccessible) for absorption; in this case, it can be expected that the toxicity of both ENMs and contaminants will decrease; - the complex formed in the gastrointestinal tract has partial solubility and can penetrate biological membranes and / or physiological barriers of the body; in this case, ENMs can play the role of a kind of conductor for contaminants and, thus, their penetration into the internal environment of the body increases, thereby increasing the toxicity of contaminants; - ENMs and contaminants do not interact with each other in any way, therefore the toxicity of each of them is determined only by its quantity and does not depend on the quantity of another component. Authors hypothesized that the degree of adsorption of various elements on the surface of ENMs may be a unique characteristic of their action, allowing a more accurate understanding of the processes occurring in a living organism.

Keywords: absorption, cadmium, engineered nanomaterials, lead

Procedia PDF Downloads 87

Authors: Stephen Rathinaraj Benjamin, Flavio Colmati Junior, Maria Izabel Florindo Guedes, Rosa Amalia Fireman Dutra

Abstract:

A new enzymatic electrochemical biosensor based on multiwall carbon nanotubes and cerium oxide nanoparticles for the detection of rutin has been developed. The cerium oxide nanoparticles /HRP/ multiwall carbon nanotubes/ carbon paste electrode (HRP/ CeO2/MWCNTs/CPE) was prepared by ensuing addition of MWCNTs and HRP on the CPE, followed by the mixing with cerium oxide nanoparticles. Surface physical characteristics of the modified electrode and the electrochemical properties of the composite were investigated by scanning electron microscopy (SEM), transmission electron microscopy (TEM), cylic voltammetry (CV), differential pulse voltammetry (DPV) and square wave voltammetry (SWV). The HRP/ CeO2/MWCNTs/CPE showed good selectivity, stability and reproducibility, which was further applied to detect rutin tablet and capsule samples with satisfactory results.

Keywords: cerium dioxide nanoparticles, horseradish peroxidase, multiwall carbon nanotubes, rutin

Procedia PDF Downloads 393

Authors: Lorato Itumeleng Kenosi

Abstract:

Background: Negative attitudes towards the mentally ill are widespread and a course for concern as they have a detrimental impact on individuals affected by mental illness. A possible avenue for changing attitudes towards mental illness is through mental health literacy. In a college or university setting, an abnormal psychology course may be introduced in an attempt to change student’s attitudes towards the mentally ill. Objective: To determine if and how students’ attitudes towards the mentally ill change as a result of taking a course in abnormal psychology. Methods: Twenty nine (29) students were recruited from an abnormal psychology class at the University of Botswana. Attitude Scale for Mental Illness (ASMI) questionnaire was administered to participants at the beginning and end of the semester. SPSS was employed to analyze data. Pooled means were used to determine whether the student’s attitudes towards mental illness were negative or positive. A mean of 2.5 translated to negative attitude for both total attitude and attitudes in different domains of the scale. Paired sample t-test was then used to assess whether any changes noted in attitudes were statistically significant or not. Statistical significance was assumed at p < 0.05. Results: Students’ general attitude towards mental illness remained positive although the pooled mean value increased from 2.08 to 2.24. The change was not statistically significant. In relation to different sub scales, the values of the pooled means for all the sub scales showed an increase although the changes were not statistically significant except for the Stereotyping sub scale (p = 0.031). The stereotyping domain reflected a statistically significant change in student’s attitude from positive attitude to negative (X² = 2.06 to X² = 2.55). For the pessimistic prediction domain, students consistently showed a negative attitude (X² = 3.34 to X² = 3.55). The other 4 domains indicated that students had positive attitude toward mentally ill throughout. Discussion: Abnormal psychology students have a positive attitude towards the mentally ill generally. This could be attributed to the fact that all students in the abnormal psychology course are majoring in psychology and research has shown that interest in psychology can affect one’s attitude towards mental illness. The students continuously held the view that people with mental illness are unlikely to improve as evidenced by a high score for Pessimistic prediction domain for both pre and post-test. Students initially had no stereotyping attitude towards the mentally ill, but at the end of the course, they were of the opinion that people with mental illness can be defined in a certain behavioural pattern and mental ability. This results could be an indication that students have learnt well how to differentiate abnormal from normal behaviour not necessarily that students had developed a negative attitude. Conclusion: A course in abnormal psychology does have an impact on the students’ attitudes towards the mentally ill. The impact does not solely depend on knowledge of mental illness but also on several other factors such as contact with the mentally ill, interest in psychology, and teaching methods. However, it should be noted that sometimes improved knowledge in mental illness can be misunderstood for a negative attitude. For example, stereotyping attitudes may be a reflection of the ability to differentiate between abnormal and normal behaviour.

Keywords: attitudes, mental illness, psychopathology, students

Procedia PDF Downloads 286

Authors: A. Chennai, M. Yahia, H. Boussenan

Abstract:

Our study was designed to highlight changes in certain biochemical parameters such as (CH, TG, HDL, TGO, TGP, LDL, and CRP), hormones (FSH, LH, PRL, TSH, and leptin), in women who suffer from over weight and fertile controls as well as the research for potential pathophysiological link between obesity and infertility in this population of women. This practical work has been focused on a population of 24 over weight infertile women, compared to control subjects without any pathology causing disturbance parameters to be studied to determine the contribution of obesity in the etiology of infertility. The assay results revealed a highly significant difference between the two groups in the serum levels of CH, TG, HDL, and TGO TGP (P <0.0001) as well as the rate of LDL (p=0.0017) and CRP (p=0.02). Hormonal profile also shows a significant difference between the two groups (P<0.0001) for LH and leptin but no difference was found for serum TSH. A significant correlation between leptin and FSH, LH, and FSH, age and LH, PRL and age and between HDL and CRP. The present study suggests that obesity is associated with infertility, but no direct pathophysiological link between obesity and infertility has been determined. More in-depth studies are needed to determine the exact mechanism by which overweight leads to female infertility.

Keywords: fertility, obesity, hormones, biochemical, pathophysiological

Procedia PDF Downloads 412

Authors: Mohammad Mokhtari, Mehdi Masoodi, Parvaneh Faridi

Abstract:

history of tsunami generating earthquakes along the Makran Subduction Zone provides evidence of the potential tsunami hazard for the whole coastal area. In comparison with other subduction zone in the world, the Makran region of southern Pakistan and southeastern Iran remains low seismicity. Also, it is one of the least studied area in the northwest of the Indian Ocean regarding tsunami studies. We present a review of studies dealing with the historical /and ongoing palaeotsunamis supported by IGCP of UNESCO in the Makran Subduction Zone. The historical tsunami presented here includes about nine tsunamis in the Makran Subduction Zone, of which over 7 tsunamis occur in the eastern Makran. Tsunami is not as common in the western Makran as in the eastern Makran, where a database of historical events exists. The historically well-documented event is related to the 1945 earthquake with a magnitude of 8.1moment magnitude and tsunami in the western and eastern Makran. There are no details as to whether a tsunami was generated by a seismic event before 1945 off western Makran. But several potentially large tsunamigenic events in the MSZ before 1945 occurred in 325 B.C., 1008, 1483, 1524, 1765, 1851, 1864, and 1897. Here we will present new findings from a historical point of view, immediately, we would like to emphasize that the area needs to be considered with higher research investigation. As mentioned above, a palaeotsunami (geological evidence) is now being planned, and here we will present the first phase result. From a risk point of view, the study shows as preliminary achievement within 20 minutes the wave reaches to Iranian as well Pakistan and Oman coastal zone with very much destructive tsunami waves capable of inundating destructive effect. It is important to note that all the coastal areas of all states surrounding the MSZ are being developed very rapidly, so any event would have a devastating effect on this region. Although several papers published about modelling, seismology, tsunami deposits in the last decades; as Makran is a forgotten subduction zone, more data such as the main crustal structure, fault location, and its related parameter are required.

Keywords: historical tsunami, Indian ocean, makran subduction zone, palaeotsunami

Procedia PDF Downloads 131

Authors: Hina Kausher, Sangita Srivastava

Abstract:

In India, there is a lack of standard, systematic sizing approach for producing readymade garments. Garments manufacturing companies use their own created size tables by modifying international sizing charts of ready-made garments. The purpose of this study is to tabulate the anthropometric data which covers the variety of figure proportions in both height and girth. 3,000 data has been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from some states of India to produce the sizing system suitable for clothing manufacture and retailing. This data is used for the statistical analysis of body measurements, the formulation of sizing systems and body measurements tables. Factor analysis technique is used to filter the control body dimensions from a large number of variables. Decision tree-based data mining is used to cluster the data. The standard and structured sizing system can facilitate pattern grading and garment production. Moreover, it can exceed buying ratios and upgrade size allocations to retail segments.

Keywords: anthropometric data, data mining, decision tree, garments manufacturing, sizing systems, ready-made garments

Procedia PDF Downloads 133

Authors: Da Tao, Tieyan Wang, Mingfu Qin

Abstract:

While social robots have been increasingly developed and rapidly applied in our daily life, how robots should interact with humans is still an urgent problem to be explored. Appropriate use of interactive behavior is likely to create a good user experience in human-robot interaction situations, which in turn can improve people’s acceptance of robots. This paper aimed to systematically and quantitatively examine the effects of several important situational factors (i.e., interaction distance, interaction posture, and feedback style) on user experience during human-robot interaction. A three-factor mixed designed experiment was adopted in this study, where subjects were asked to interact with a social robot in different interaction situations by combinations of varied interaction distance, interaction posture, and feedback style. A set of data on users’ behavioral performance, subjective perceptions, and eye movement measures were tracked and collected, and analyzed by repeated measures analysis of variance. The results showed that the three situational factors showed no effects on behavioral performance in tasks during human-robot interaction. Interaction distance and feedback style yielded significant main effects and interaction effects on the proportion of fixation times. The proportion of fixation times on the robot is higher for negative feedback compared with positive feedback style. While the proportion of fixation times on the robot generally decreased with the increase of the interaction distance, it decreased more under the positive feedback style than under the negative feedback style. In addition, there were significant interaction effects on pupil diameter between interaction distance and posture. As interaction distance increased, mean pupil diameter became smaller in side interaction, while it became larger in frontal interaction. Moreover, the three situation factors had significant interaction effects on user acceptance of the interaction mode. The findings are helpful in the underlying mechanism of user experience in human-robot interaction situations and provide important implications for the design of robot behavioral expression and for optimal strategies to improve user experience during human-robot interaction.

Keywords: social robots, human-robot interaction, interaction posture, interaction distance, feedback style, user experience

Procedia PDF Downloads 132

Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

Procedia PDF Downloads 54

Authors: Vishnu Nagendra, Marten Van Der Veen, Stefania Giodini

Abstract:

Effective humanitarian logistics operations are a cornerstone in the success of disaster relief operations. However, for effectiveness, they need to be demand driven and supported by adequate data for prioritization. Without this data operations are carried out in an ad hoc manner and eventually become chaotic. The current availability of geospatial data helps in creating models for predictive damage and vulnerability assessment, which can be of great advantage to logisticians to gain an understanding on the nature and extent of the disaster damage. This translates into actionable information on the demand for relief goods, the state of the transport infrastructure and subsequently the priority areas for relief delivery. However, due to the unpredictable nature of disasters, the accuracy in the models need improvement which can be done using remote sensing data from UAVs (Unmanned Aerial Vehicles) or satellite imagery, which again come with certain limitations. This research addresses the need for a framework to combine data from different sources to support humanitarian logistic operations and prediction models. The focus is on developing a workflow to combine data from satellites and UAVs post a disaster strike. A three-step approach is followed: first, the data requirements for logistics activities are made explicit, which is done by carrying out semi-structured interviews with on field logistics workers. Second, the limitations in current data collection tools are analyzed to develop workaround solutions by following a systems design approach. Third, the data requirements and the developed workaround solutions are fit together towards a coherent workflow. The outcome of this research will provide a new method for logisticians to have immediately accurate and reliable data to support data-driven decision making.

Keywords: unmanned aerial vehicles, damage prediction models, remote sensing, data driven decision making

Procedia PDF Downloads 378

Authors: Jane O. Munonye

Abstract:

Climate change has both negative and positive effects in agricultural production. For agriculture to be sustainable in adverse climate change condition, some natural measures are needed. The issue is to produce more food with available natural resources and reduce the contribution of agriculture to climate change. The study reviewed climate change and sustainable agriculture in southeast Nigeria. Data from the study were from secondary sources. Ten scientific papers were consulted and data for the review were collected from three. The objectives of the paper were as follows: to review the effect of climate change on one major arable crop in southeast Nigeria (yam; Dioscorea rotundata); evident of climate change impact and methods for sustainable agricultural production in adverse weather condition. Some climatic parameter as sunshine, relative humidity and rainfall have negative relationship with yam production and significant at 10% probability. Crop production was predicted to decline by 25% per hectare by 2060 while livestock production has increased the incidence of diseases and pathogens as the major effect to agriculture. Methods for sustainable agriculture and damage of natural resources by climate change were highlighted. Agriculture needs to be transformed as climate changes to enable the sector to be sustainable. There should be a policy in place to facilitate the integration of sustainability in Nigeria agriculture.

Keywords: agriculture, climate change, sustainability, yam

Procedia PDF Downloads 326

Authors: J. Das, T. S. Mahule, V. V. Srinivasu

Abstract:

Electron spin resonance (ESR) study at 9.45 GHz and a field modulation frequency of 100Hz was performed on bulk polycrystalline samples of Mn:TM (Fe/Ni) and Mn:RE (Gd/Sm) co doped ZnO samples with composition Zn1-xMn:TM/RE)xO synthesised by solid state reaction route and sintered at 500 0C temperature. The room temperature microwave absorption data collected by sweeping the DC magnetic field from -500 to 9500 G for the Mn:Fe and Mn:Ni co doped ZnO samples exhibit a rarely reported non resonant low field absorption (NRLFA) in addition to a strong absorption at around 3350G, usually associated with ferromagnetic resonance (FMR) satisfying Larmor’s relation due to absorption in the full saturation state. Observed low field absorption is distinct to ferromagnetic resonance even at low temperature and shows hysteresis. Interestingly, it shows a phase opposite with respect to the main ESR signal of the samples, which indicates that the low field absorption has a minimum value at zero magnetic field whereas the ESR signal has a maximum value. The major resonance peak as well as the peak corresponding to low field absorption exhibit asymmetric nature indicating magnetic anisotropy in the sample normally associated with intrinsic ferromagnetism. Anisotropy parameter for Mn:Ni codoped ZnO sample is noticed to be quite higher. The g values also support the presence of oxygen vacancies and clusters in the samples. These samples have shown room temperature ferromagnetism in the SQUID measurement. However, in rare earth (RE) co doped samples (Zn1-x (Mn: Gd/Sm)xO), which show paramagnetic behavior at room temperature, the low field microwave signals are not observed. As microwave currents due to itinerary electrons can lead to ohmic losses inside the sample, we speculate that more delocalized 3d electrons contributed from the TM dopants facilitate such microwave currents leading to the loss and hence absorption at the low field which is also supported by the increase in current with increased micro wave power. Besides, since Fe and Ni has intrinsic spin polarization with polarisability of around 45%, doping of Fe and Ni is expected to enhance the spin polarization related effect in ZnO. We emphasize that in this case Fe and Ni doping contribute to polarized current which interacts with the magnetization (spin) vector and get scattered giving rise to the absorption loss.

Keywords: co-doping, electron spin resonance, hysteresis, non-resonant microwave absorption

Procedia PDF Downloads 314

Authors: Abdullahi Jibrin, Aishetu Abdulkadir

Abstract:

The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. The F-test value for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.

Keywords: allometriy, biomass, carbon stock , model, regression equation, woodland, inventory

Procedia PDF Downloads 448