Search results for: data acquisition

Authors: Fariea Bakul, Chhanda Karmaker

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The present study was designed to investigate the effects of parental bonding on adult’s cognitive emotion regulation and also to investigate gender differences in parental bonding and cognitive emotion regulation. Data were collected by using convenience sampling technique from 100 adult students (50 males and 50 females) of different universities of Dhaka city, ages between 20 to 25 years, using Bengali version of Parental Bonding Inventory and Bengali version of Cognitive Emotion Regulation Questionnaire. The obtained data were analyzed by using multiple regression analysis and independent samples t-test. The results revealed that fathers care (β =0.317, p < 0.05) was only significantly positively associated with adult’s cognitive emotion regulation. Adjusted R² indicated that the model explained 30% of the variance in adult’s adaptive cognitive emotion regulation. No significant association was found between parental bonding and less adaptive cognitive emotion regulations. Results from independent samples t-test also revealed that there was no significant gender difference in both parental bonding and cognitive emotion regulations.

Keywords: cognitive emotion regulation, parental bonding, parental care, parental over-protection

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Authors: Humraaz Kaja, Kofi Mensah, Frasia Oosthuizen

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Background and Aim: Vilazodone was approved in 2011 as an antidepressant to treat the major depressive disorder. As a relatively new drug, it is not clear if all adverse effects have been identified. The aim of this study was to review the adverse effects reported to the WHO Programme for International Drug Monitoring (PIDM) in order to add to the knowledge about the safety profile and adverse effects caused by vilazodone. Method: Data on adverse effects reported for vilazodone was obtained from the database VigiAccess managed by PIDM. Data was extracted from VigiAccess using Excel® and analyzed using descriptive statistics. The data collected was compared to the patient information leaflet (PIL) of Viibryd® and the FDA documents to determine adverse drug reactions reported post-marketing. Results: A total of 9708 adverse events had been recorded on VigiAccess, of which 6054 were not recorded on the PIL and the FDA approval document. Most of the reports were received from the Americas and were for adult women aged 45-64 years (24%, n=1059). The highest number of adverse events reported were for psychiatric events (19%; n=1889), followed by gastro-intestinal effects (18%; n=1839). Specific psychiatric disorders recorded included anxiety (316), depression (208), hallucination (168) and agitation (142). The systematic review confirmed several psychiatric adverse effects associated with the use of vilazodone. The findings of this study suggested that these common psychiatric adverse effects associated with the use of vilazodone were not known during the time of FDA approval of the drug and is not currently recorded in the patient information leaflet (PIL). Conclusions: In summary, this study found several adverse drug reactions not recorded in documents emanating from clinical trials pre-marketing. This highlights the importance of continued post-marketing surveillance of a drug, as well as the need for further studies on the psychiatric adverse events associated with vilazodone in order to improve the safety profile.

Keywords: adverse drug reactions, pharmacovigilance, post-marketing surveillance, vilazodone

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Authors: S. M. Kulkarni, D. S. Bormane, S. L. Nalbalwar

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The rapid development in the technology have dramatic impact on the medical health care field. Medical data base obtained with latest machines like CT Machine, MRI scanner requires large amount of memory storage and also it requires large bandwidth for transmission of data in telemedicine applications. Thus, there is need for video compression. As the database of medical images contain number of frames (slices), hence while coding of these images there is need of motion estimation. Motion estimation finds out movement of objects in an image sequence and gets motion vectors which represents estimated motion of object in the frame. In order to reduce temporal redundancy between successive frames of video sequence, motion compensation is preformed. In this paper three step search (TSS) block matching algorithm is implemented on different types of video sequences. It is shown that three step search algorithm produces better quality performance and less computational time compared with exhaustive full search algorithm.

Keywords: block matching, exhaustive search motion estimation, three step search, video compression

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Authors: Aslina Asnawi, A. Amidah Amrawaty, Nirwana

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This article examines the relationship of local culture on the ability to access finance on beef cattle farmer. The local culture in this study associated with the values held by the farmer community so far and affect the character of farmers both in his personal life and his relationship with the surrounding environment. The data was collected by using interview and questionnaire instrument. Data were analyzed using descriptive analysis and correlation analysis. The result show that local culture identified in this study include: honesty, cleverness, decency, firmness, hard work, and shame. It’s important result that local culture has been associated with the ability to access financing for beef cattle farmers. The higher values are adopted and maintained by farmers will increase their ability to obtain loans from both informal and formal institutions. Strengthening the local culture is important because it affects the character of farmers who became one of the considerations for lenders other than collateral, capacity and capital is precisely the financing constraints for them.

Keywords: access funding, beef cattle farmers, character, local culture

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Authors: Meghry Nazarian, Ibrahim Duyar

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Effective management of a diverse workforce in the United Arab Emirates (UAE) presents peculiar importance as two-thirds of residents are expatriates who have diverse ethnic and cultural backgrounds. Like any other organization in the country, UAE schools have become upmost diverse settings in the world. The purpose of this study was to examine whether principals’ cultural intelligence has direct and indirect (moderating) influences on teachers’ perceived diversity climate. A quantitative causal-comparative research design was employed to analyze the data. Participants included random samples of principals and teachers working in the private and charter schools in the Emirate of Abu Dhabi. The data-gathering online questionnaires included previously developed and validated scales as the measures of study variables. More specifically, the multidimensional short-form measure of Cultural Intelligence (CQ) and the diversity climate scale were used to measure the study variables. Multivariate statistics, including the analysis of multivariate analysis of variance (MANCOVA) and structural equation modeling (SEM), were employed to examine the relationships between the study variables. The preliminary analyses of data showed that principals and teachers have differing views of diversity management and climate in schools. Findings also showed that principals’ cultural intelligence has both direct and moderating influences on teachers’ perceived diversity climate. The study findings are expected to inform policymakers and practicing educational leaders in addressing diversity management in a country where the majority of the residents are the minority who have diverse ethnic and cultural backgrounds.

Keywords: diversity management, united arab emirates, school principals’ cultural intelligence (CQ), teachers’ perceived diversity climate

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Authors: Pius Babuna

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Sustainable water use is important for the existence of the human race. Water resources carrying capacity (WRCC) measures the sustainability of water use; however, the calculation and optimization of WRCC remain challenging. This study used a mathematical model (the Logistics Growth of Water Resources -LGWR) and a linear objective function to model water sustainability. We tested the validity of the models using data from Ghana. Total freshwater resources, water withdrawal, and population data were used in MATLAB. The results show that the WRCC remains sustainable until the year 2132 ±18, when half of the total annual water resources will be used. The optimized water treatment cost suggests that Ghana currently wastes GHȼ 1115.782± 50 cedis (~$182.21± 50) per water treatment plant per month or ~ 0.67 million gallons of water in an avoidable loss. Adopting an optimized water treatment scheme and a watershed management approach will help sustain the WRCC.

Keywords: water resources carrying capacity, smart water management, optimization, sustainable water use, water withdrawal

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Authors: Zhenmin Tao, Jasper De Smet, Koen Laurijssen, Jeroen Stuyts, Sonja Sioncke

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Today, the quality of knowledge management (KM)become one of the underpinning factors in the success of an organization, as it determines the effectiveness of capitalizing the organization’s knowledge. Overall, KMin an organization consists of five aspects: (knowledge) creation, validation, presentation, distribution, and application. Among others, KM in research institutes is considered as the cornerstone as their activities cover all five aspects. Furthermore, KM in a research institute facilitates the steering committee to envision the future roadmap, identify knowledge gaps, and make decisions on future research directions. Likewise, KMis even more challenging in industrial research institutes. From a technical perspective, technology advancement in the past decades calls for combinations of breadth and depth in expertise that poses challenges in talent acquisition and, therefore, knowledge creation. From a regulatory perspective, the strict intellectual property protection from industry collaborators and/or the contractual agreements made by possible funding authoritiesform extra barriers to knowledge validation, presentation, and distribution. From a management perspective, seamless KM activities are only guaranteed by inter-disciplinary talents that combine technical background knowledge, management skills, and leadership, let alone international vision. From a financial perspective, the long feedback period of new knowledge, together with the massive upfront investment costs and low reusability of the fixed assets, lead to low RORC (return on research capital) that jeopardize KM practice. In this study, we aim to address the challenges, practices, and opportunitiesof KM in Flanders Make – a leading European research institute specialized in the manufacturing industry. In particular, the analyses encompass an internal KM project which involves functionalities ranging from management to technical domain experts. This wide range of functionalities provides comprehensive empirical evidence on the challenges and practices w.r.t.the abovementioned KMaspects. Then, we ground our analysis onto the critical dimensions ofKM–individuals, socio‐organizational processes, and technology. The analyses have three steps: First, we lay the foundation and define the environment of this study by briefing the KM roles played by different functionalities in Flanders Make. Second, we zoom in to the CoreLab MotionS where the KM project is located. In this step, given the technical domains covered by MotionS products, the challenges in KM will be addressed w.r.t. the five KM aspects and three critical dimensions. Third, by detailing the objectives, practices, results, and limitations of the MotionSKMproject, we justify the practices and opportunities derived in the execution ofKMw.r.t. the challenges addressed in the second step. The results of this study are twofold: First, a KM framework that consolidates past knowledge is developed. A library based on this framework can, therefore1) overlook past research output, 2) accelerate ongoing research activities, and 3) envision future research projects. Second, the challenges inKM on both individual (actions) level and socio-organizational level (e.g., interactions between individuals)are identified. By doing so, suggestions and guidelines will be provided in KM in the context of industrial research institute. To this end, the results in this study are reflected towards the findings in existing literature.

Keywords: technical knowledge management framework, industrial research institutes, individual knowledge management, socio-organizational knowledge management.

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Authors: Berhanu Keno Terfa

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Flash floods are among the most dangerous natural disasters that pose a significant threat to human existence. They occur frequently and can cause extensive damage to homes, infrastructure, and ecosystems while also claiming lives. Although flash floods can happen anywhere in the world, their impact is particularly severe in developing countries due to limited financial resources, inadequate drainage systems, substandard housing options, lack of early warning systems, and insufficient preparedness. To address these challenges, a comprehensive study has been undertaken to analyze and map flood inundation using Geographic Information System (GIS) techniques by considering various factors that contribute to flash flood resilience and developing effective mitigation strategies. Key factors considered in the analysis include slope, drainage density, elevation, Curve Number, rainfall patterns, land-use/cover classes, and soil data. These variables were computed using ArcGIS software platforms, and data from the Sentinel-2 satellite image (with a 10-meter resolution) were utilized for land-use/cover classification. Additionally, slope, elevation, and drainage density data were generated from the 12.5-meter resolution of the ALOS Palsar DEM, while other relevant data were obtained from the Ethiopian Meteorological Institute. By integrating and regularizing the collected data through GIS and employing the analytic hierarchy process (AHP) technique, the study successfully delineated flash flood hazard zones (FFHs) and generated a suitable land map for urban agriculture. The FFH model identified four levels of risk in Bishoftu City: very high (2106.4 ha), high (10464.4 ha), moderate (1444.44 ha), and low (0.52 ha), accounting for 15.02%, 74.7%, 10.1%, and 0.004% of the total area, respectively. The results underscore the vulnerability of many residential areas in Bishoftu City, particularly the central areas that have been previously developed. Accurate spatial representation of flood-prone areas and potential agricultural zones is crucial for designing effective flood mitigation and agricultural production plans. The findings of this study emphasize the importance of flood risk mapping in raising public awareness, demonstrating vulnerability, strengthening financial resilience, protecting the environment, and informing policy decisions. Given the susceptibility of Bishoftu City to flash floods, it is recommended that the municipality prioritize urban agriculture adaptation, proper settlement planning, and drainage network design.

Keywords: remote sensing, flush flood hazards, Bishoftu, GIS.

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Authors: Alejandra Torres-Landa López

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Introduction: Can architecture students be creative in spaces conformed by an educational infrastructure build with paradigms of the past?, this question and others related are answered in this paper as it presents the PhD research: An anthropic conflict in Mexican Higher Education Institutes, problems and challenges of the educational infrastructure in teaching and learning History of Architecture. This research was finished in 2013 and is one of the first studies conducted nationwide in Mexico that analysis the educational infrastructure impact in learning architecture; its objective was to identify which elements of the educational infrastructure of Mexican Higher Education Institutes where architects are formed, hinder or contribute to the teaching and learning of History of Architecture; how and why it happens. The methodology: A mixed methodology was used combining quantitative and qualitative analysis. Different resources and strategies for data collection were used, such as questionnaires for students and teachers, interviews to architecture research experts, direct observations in Architecture classes, among others; the data collected was analyses using SPSS and MAXQDA. The veracity of the quantitative data was supported by the Cronbach’s Alpha Coefficient, obtaining a 0.86, figure that gives the data enough support. All the above enabled to certify the anthropic conflict in which Mexican Universities are. Major findings of the study: Although some of findings were probably not unknown, they haven’t been systematized and analyzed with the depth to which it’s done in this research. So, it can be said, that the educational infrastructure of most of the Higher Education Institutes studied, is a barrier to the educational process, some of the reasons are: the little morphological variation of space, the inadequate control of lighting, noise, temperature, equipment and furniture, the poor or none accessibility for disable people; as well as the absence, obsolescence and / or insufficiency of information technologies are some of the issues that generate an anthropic conflict understanding it as the trouble that teachers and students have to relate between them, in order to achieve significant learning). It is clear that most of the educational infrastructure of Mexican Higher Education Institutes is anchored to paradigms of the past; it seems that they respond to the previous era of industrialization. The results confirm that the educational infrastructure of Mexican Higher Education Institutes where architects are formed, is perceived as a "closed container" of people and data; infrastructure that becomes a barrier to teaching and learning process. Conclusion: The research results show it's time to change the paradigm in which we conceive the educational infrastructure, it’s time to stop seen it just only as classrooms, workshops, laboratories and libraries, as it must be seen from a constructive, urban, architectural and human point of view, taking into account their different dimensions: physical, technological, documental, social, among others; so the educational infrastructure can become a set of elements that organize and create spaces where ideas and thoughts can be shared; to be a social catalyst where people can interact between each other and with the space itself.

Keywords: educational infrastructure, impact of space in learning architecture outcomes, learning environments, teaching architecture, learning architecture

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Authors: O. Benturki, A. Benturki

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Activated carbon was prepared from Jujube seeds by chemical activation with potassium hydroxide (KOH), followed by pyrolysis at 800°C. Batch studies were conducted for kinetic, thermodynamic and equilibrium studies on the adsorption of phenol (P) and 2-4 dichlorophenol (2-4 DCP) from aqueous solution, than the adsorption capacities followed the order of 2-4 dichlorophenol > phenol. The operating variables studied were initial phenols concentration, contact time, temperature and solution pH. Results show that the pH value of 7 is favorable for the adsorption of phenols. The sorption data have been analyzed using Langmuir and Freundlich isotherms. The isotherm data followed Langmuir Model. The adsorption processes conformed to the pseudo-second-order rate kinetics. Thermodynamic parameters such as enthalpy, entropy and Gibb’s free energy changes were also calculated and it was found that the sorption of phenols by Jujuba seeds activated carbon was a spontaneous process The maximum adsorption efficiency of phenol and 2-4 dichlorophenol was 142.85 mg.g−1 and 250 mg.g−1, respectively.

Keywords: activated carbon, adsorption, isotherms, Jujuba seeds, phenols, langmuir

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Authors: Hyun-Woo Cho

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Continuous monitoring of industrial plants is one of necessary tasks when it comes to ensuring high-quality final products. In terms of monitoring and diagnosis, it is quite critical and important to detect some incipient abnormal events of manufacturing processes in order to improve safety and reliability of operations involved and to reduce related losses. In this work a new multivariate statistical online diagnostic method is presented using a case study. For building some reference models an empirical discriminant model is constructed based on various past operation runs. When a fault is detected on-line, an on-line diagnostic module is initiated. Finally, the status of the current operating conditions is compared with the reference model to make a diagnostic decision. The performance of the presented framework is evaluated using a dataset from complex industrial processes. It has been shown that the proposed diagnostic method outperforms other techniques especially in terms of incipient detection of any faults occurred.

Keywords: data mining, empirical model, on-line diagnostics, process fault, process monitoring

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Authors: Yi-Lin Chen, Sheng-Jou Hung, Tsunglin Liu

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Adaptive immune system recognizes a wide range of antigens via expressing a large number of structurally distinct T cell and B cell receptor genes. The distinct receptor genes arise from complex rearrangements called V(D)J recombination, and constitute the immune repertoire. A common method of profiling immune repertoire is via amplifying recombined receptor genes using multiple primers and high-throughput sequencing. This multiplex-PCR approach is efficient; however, the resulting repertoire can be distorted because of primer bias. To eliminate primer bias, 5’ RACE is an alternative amplification approach. However, the application of RACE approach is limited by its low efficiency (i.e., the majority of data are non-regular receptor sequences, e.g., containing intronic segments) and lack of the convenient tool for analysis. We propose a computational tool that can correctly identify non-regular receptor sequences in RACE data via aligning receptor sequences against the whole gene instead of only the exon regions as done in all other tools. Using our tool, the remaining regular data allow for an accurate profiling of immune repertoire. In addition, a RACE approach is improved to yield a higher fraction of regular T-cell receptor sequences. Finally, we quantify the degree of primer bias of a multiplex-PCR approach via comparing it to the RACE approach. The results reveal significant differences in frequency of VJ combination by the two approaches. Together, we provide a new experimental and computation pipeline for an unbiased profiling of immune repertoire. As immune repertoire profiling has many applications, e.g., tracing bacterial and viral infection, detection of T cell lymphoma and minimal residual disease, monitoring cancer immunotherapy, etc., our work should benefit scientists who are interested in the applications.

Keywords: immune repertoire, T-cell receptor, 5' RACE, high-throughput sequencing, sequence alignment

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Authors: Narottam Puri, Bishnu Panigrahi, Narayan Pendse

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Background: Clinical Outcomes are the globally agreed upon, evidence-based measurable changes in health or quality of life resulting from the patient care. Reporting of outcomes and its continuous monitoring provides an opportunity for both assessing and improving the quality of patient care. In 2012, International Consortium Of HealthCare Outcome Measurement (ICHOM) was founded which has defined global Standard Sets for measuring the outcome of various treatments. Method: Monitoring of Clinical Outcomes was identified as a pillar of Fortis’ core value of Patient Centricity. The project was started as an in-house developed Clinical Outcomes Reporting Portal by the Fortis Medical IT team. Standard sets of Outcome measurement developed by ICHOM were used. A pilot was run at Fortis Escorts Heart Institute from Aug’13 – Dec’13.Starting Jan’14, it was implemented across 11 hospitals of the group. The scope was hospital-wide and major clinical specialties: Cardiac Sciences, Orthopedics & Joint Replacement were covered. The internally developed portal had its limitations of report generation and also capturing of Patient related outcomes was restricted. A year later, the company provisioned for an ICHOM Certified Software product which could provide a platform for data capturing and reporting to ensure compliance with all ICHOM requirements. Post a year of the launch of the software; Fortis Healthcare has become the 1st Healthcare Provider in Asia to publish Clinical Outcomes data for the Coronary Artery Disease Standard Set comprising of Coronary Artery Bypass Graft and Percutaneous Coronary Interventions) in the public domain. (Jan 2016). Results: This project has helped in firmly establishing a culture of monitoring and reporting Clinical Outcomes across Fortis Hospitals. Given the diverse nature of the healthcare delivery model at Fortis Network, which comprises of hospitals of varying size and specialty-mix and practically covering the entire span of the country, standardization of data collection and reporting methodology is a huge achievement in itself. 95% case reporting was achieved with more than 90% data completion at the end of Phase 1 (March 2016). Post implementation the group now has one year of data from its own hospitals. This has helped identify the gaps and plan towards ways to bridge them and also establish internal benchmarks for continual improvement. Besides the value created for the group includes: 1. Entire Fortis community has been sensitized on the importance of Clinical Outcomes monitoring for patient centric care. Initial skepticism and cynicism has been countered by effective stakeholder engagement and automation of processes. 2. Measuring quality is the first step in improving quality. Data analysis has helped compare clinical results with best-in-class hospitals and identify improvement opportunities. 3. Clinical fraternity is extremely pleased to be part of this initiative and has taken ownership of the project. Conclusion: Fortis Healthcare is the pioneer in the monitoring of Clinical Outcomes. Implementation of ICHOM standards has helped Fortis Clinical Excellence Program in improving patient engagement and strengthening its commitment to its core value of Patient Centricity. Validation and certification of the Clinical Outcomes data by an ICHOM Certified Supplier adds confidence to its claim of being leaders in this space.

Keywords: clinical outcomes, healthcare delivery, patient centricity, ICHOM

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Authors: Somaye Ghafarpour, Kamran Yazdanbakhsh, Mohamad Reza Zarbakhsh, Simin Hosseinian, Samira Ghafarpour

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Unsatisfactory sleep quality is one of the most common complications of pregnancy, which can predispose mothers to postpartum depression, requiring implementing effective psychological interventions to prevent and modify behaviors accentuating sleep problems. This study was a randomized clinical controlled trial with a pre-test/post-test design aiming to investigate the effectiveness of sleep behavioral interventions during the third trimester of pregnancy on sleep quality and postpartum depression. A total of 50 pregnant mothers in the 26-30 weeks of pregnancy suffering from sleep problems (based on the score obtained from the Pittsburgh Sleep Questionnaire) were randomized into two groups (control and intervention, n= 25 per group). The data were collected using interviews, the Pittsburgh Sleep Quality Index (PSQI), and the Edinburgh Postnatal Depression Scale (EPDS) were used. The participants in the intervention group received eight 60-minute sessions of combinational training for behavioral therapy techniques. At the end of the intervention and four weeks after delivery, sleep quality and postpartum depression were evaluated. Considering that the Kolmogorov Smirnov test confirmed the normal distribution of the data, the independent t-test and analysis of covariance were used to analyze the data, showing that the behavioral interventions were effective on the overall sleep quality after delivery (p=0.001); however, no statistically significant effects were observed on postpartum depression, the sub-scales of sleep disorders, and daily functioning (p>0.05). Considering the potential effectiveness of behavioral interventions in improving sleep quality and alleviating insomnia symptoms, it is recommended to implement such measures as an effective intervention to prevent or treat these problems during prenatal and postnatal periods.

Keywords: behavioral interventions, sleep quality, postpartum depression, pregnancy, delivery

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Authors: Danlei Yang, Luofeng Huang

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The integration of digital twin technology with renewable energy systems offers an innovative approach to predicting and optimising performance throughout the entire lifecycle. A digital twin is a continuously updated virtual replica of a real-world entity, synchronised with data from its physical counterpart and environment. Many digital twin companies today claim to have mature digital twin products, but their focus is primarily on equipment visualisation. However, the core of a digital twin should be its model, which can mirror, shadow, and thread with the real-world entity, which is still underdeveloped. For a floating solar energy system, a digital twin model can be defined in three aspects: (a) the physical floating solar energy system along with environmental factors such as solar irradiance and wave dynamics, (b) a digital model powered by artificial intelligence (AI) algorithms, and (c) the integration of real system data with the AI-driven model and a user interface. The experimental setup for the floating solar energy system, is designed to replicate real-ocean conditions of floating solar installations within a controlled laboratory environment. The system consists of a water tank that simulates an aquatic surface, where a floating catamaran structure supports a solar panel. The solar simulator is set up in three positions: one directly above and two inclined at a 45° angle in front and behind the solar panel. This arrangement allows the simulation of different sun angles, such as sunrise, midday, and sunset. The solar simulator is positioned 400 mm away from the solar panel to maintain consistent solar irradiance on its surface. Stability for the floating structure is achieved through ropes attached to anchors at the bottom of the tank, which simulates the mooring systems used in real-world floating solar applications. The floating solar energy system's sensor setup includes various devices to monitor environmental and operational parameters. An irradiance sensor measures solar irradiance on the photovoltaic (PV) panel. Temperature sensors monitor ambient air and water temperatures, as well as the PV panel temperature. Wave gauges measure wave height, while load cells capture mooring force. Inclinometers and ultrasonic sensors record heave and pitch amplitudes of the floating system’s motions. An electric load measures the voltage and current output from the solar panel. All sensors collect data simultaneously. Artificial neural network (ANN) algorithms are central to developing the digital model, which processes historical and real-time data, identifies patterns, and predicts the system’s performance in real time. The data collected from various sensors are partly used to train the digital model, with the remaining data reserved for validation and testing. The digital twin model combines the experimental setup with the ANN model, enabling monitoring, analysis, and prediction of the floating solar energy system's operation. The digital model mirrors the functionality of the physical setup, running in sync with the experiment to provide real-time insights and predictions. It provides useful industrial benefits, such as informing maintenance plans as well as design and control strategies for optimal energy efficiency. In long term, this digital twin will help improve overall solar energy yield whilst minimising the operational costs and risks.

Keywords: digital twin, floating solar energy system, experiment setup, artificial intelligence

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Authors: Ivo Zution Goncalves, Christopher M. U. Neale, Hiran Medeiros, Everardo Mantovani, Natalia Souza

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Multispectral and thermal infrared imagery from satellite sensors coupled with climate and soil datasets were used to estimate evapotranspiration and biomass in center pivots planted to maize in Brazil during the 2016 season. The hybrid remote sensing based model named Spatial EvapoTranspiration Modelling Interface (SETMI) was applied using multispectral and thermal infrared imagery from the Landsat Thematic Mapper instrument. Field data collected by the IRRIGER center pivot management company included daily weather information such as maximum and minimum temperature, precipitation, relative humidity for estimating reference evapotranspiration. In addition, soil water content data were obtained every 0.20 m in the soil profile down to 0.60 m depth throughout the season. Early season soil samples were used to obtain water-holding capacity, wilting point, saturated hydraulic conductivity, initial volumetric soil water content, layer thickness, and saturated volumetric water content. Crop canopy development parameters and irrigation application depths were also inputs of the model. The modeling approach is based on the reflectance-based crop coefficient approach contained within the SETMI hybrid ET model using relationships developed in Nebraska. The model was applied to several fields located in Minas Gerais State in Brazil with approximate latitude: -16.630434 and longitude: -47.192876. The model provides estimates of real crop evapotranspiration (ET), crop irrigation requirements and all soil water balance outputs, including biomass estimation using multi-temporal satellite image inputs. An interpolation scheme based on the growing degree-day concept was used to model the periods between satellite inputs, filling the gaps between image dates and obtaining daily data. Actual and accumulated ET, accumulated cold temperature and water stress and crop water requirements estimated by the model were compared with data measured at the experimental fields. Results indicate that the SETMI modeling approach using data assimilation, showed reliable daily ET and crop water requirements for maize, interpolated between remote sensing observations, confirming the applicability of the SETMI model using new relationships developed in Nebraska for estimating mainly ET and water requirements in Brazil under tropical conditions.

Keywords: basal crop coefficient, irrigation, remote sensing, SETMI

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Authors: Ximena Castillo, Jaime Pizarro

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This research describes the development of a very cheap mesoporous silica material similar to hexagonal mesoporous silica (HMS) and using a silicate extract as precursor. This precursor is obtained from cheap fly ash by an easy calcination process at 850 °C and a green extraction with water. The obtained mesoporous fly ash material had a surface area of 282 m2 g-1 and a pore size of 5.7 nm. It was functionalized with ethylene diamino moieties via the well-known SAMMS method, followed by a DRIFT analysis that clearly showed the successful functionalization. An excellent adsorbent was obtained for the adsorption of sulfate anions by the solid’s modification with copper forming a copper-ethylenediamine complex. The adsorption of sulfates was studied in a batch system ( experimental conditions: pH=8.0; 5 min). The kinetics data were adjusted according to a pseudo-second order model with a high coefficient of linear regression at different initial concentrations. The adsorption isotherm that best fitted the experimental data was the Freundlich model. The maximum sulfate adsorption capacity of this very cheap fly ash based adsorbent was 146.1 mg g-1, 3 times greater than the values reported in literature and commercial adsorbent materials.

Keywords: fly ash, mesoporous materials, SAMMS, sulfate

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Authors: Rauha Salam

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In Pakistan, over the past decade, the notion of what counts as a true ‘masculine and feminine’ behaviour has become more complicated with the inspection of social media. Given its strong religious and socio-cultural norms, patriarchal values are entrenched in the local and cultural traditions of the Pakistani society and regulate the social value of gender. However, the increasing use of internet among Pakistani men and women, especially in the form of social media uses by the youth, is increasingly becoming disruptive and challenging to the strict modes of behavioural monitoring and control both at familial and state level. Facebook, being the prime social media communication platform in Pakistan, provide its users a relatively ‘safe’ place to embrace how they want to be perceived by their audience. Moreover, the availability of an array of semiotic resources (e.g. the videos, audios, visuals and gifs) on Facebook makes it possible for the users to create a virtual identity that allows them to describe themselves in detail. By making use of Multimodal Discourse Analysis, I aimed to investigate how men and women in Pakistan construct their gendered identities multimodally (visually and linguistically) through their Facebook posts and how these semiotic modes are interconnected to communicate specific meanings. In case of the female data, the analysis showed an ambivalence as females were found to be conforming to the existing socio-cultural norms of the society and they were also employing social media platforms to deviate from traditional gendered patterns and to voice their opinions simultaneously. Similarly, the male data highlighted the reproduction of the prevalent cultural models of masculinity. However, there were instances in the data that showed a digression from the standard norms and there is a (re)negotiation of the traditional patriarchal representations.

Keywords: Facebook, Gendered Identities, Multimodal Discourse Analysis, Pakistan

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Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

Procedia PDF Downloads 91

Authors: Sarono, Hamim Zaky Hadibasyir, dan Ridho Kurniawan

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Estimation of paddy production is one of the areas that can be examined using the techniques of remote sensing and geographic information systems (GIS) in the field of agriculture. The purpose of this research is to know the amount of the paddy production estimation and how remote sensing and geographic information systems (GIS) are able to perform analysis of paddy production estimation in Tegalallang and Payangan Sub district, Bali Province, Indonesia. The method used is the method of land suitability. This method associates a physical parameters which are to be embodied in the smallest unit of a mapping that represents a mapping unit in a particular field and connecting with its field productivity. Analysis of estimated production using standard land suitability from FAO using matching technique. The parameters used to create the land unit is slope (FAO), climate classification (Oldeman), landform (Prapto Suharsono), and soil type. Land use map consist of paddy and non paddy field information obtained from Geo-eye 1 imagery using visual interpretation technique. Landsat image of the Data used for the interpretation of the landform, the classification of the slopes obtained from high point identification with method of interpolation spline, whereas climate data, soil, use secondary data originating from institutions-related institutions. The results of this research indicate Tegallalang and Payangan Districts in known wetland suitability consists of S1 (very suitable) covering an area of 2884,7 ha with the productivity of 5 tons/ha and S2 (suitable) covering an area of 482,9 ha with the productivity of 3 tons/ha. The sum of paddy production estimation as a results in both districts are 31.744, 3 tons in one year.

Keywords: production estimation, paddy, remote sensing, geography information system, land suitability

Procedia PDF Downloads 342

Authors: Anurag Savarnya

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The reliability of the various parts of electric mining shovel has been assessed through the application of Weibull Model. The study was initiated to find reliability of components of electric mining shovel. The paper aims to optimize the reliability of components and increase the life cycle of component. A multilevel decomposition of the electric mining shovel was done and maintenance records were used to evaluate the failure data and appropriate system characterization was done to model the system in terms of reasonable number of components. The approach used develops a mathematical model to assess the reliability of the electric mining shovel components. The model can be used to predict reliability of components of the hydraulic mining shovel and system performance. Reliability is an inherent attribute to a system. When the life-cycle costs of a system are being analyzed, reliability plays an important role as a major driver of these costs and has considerable influence on system performance. It is an iterative process that begins with specification of reliability goals consistent with cost and performance objectives. The data were collected from an Indian open cast coal mine and the reliability of various components of the electric mining shovel has been assessed by following a Weibull Model.

Keywords: reliability, Weibull model, electric mining shovel

Procedia PDF Downloads 514

Authors: Arzyana Sunkar, Yanto Santosa

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The expansions of independent smallholdings in Indonesia are feared to increase the negative ecological impacts of oil palm plantation on biodiversity. Hence, research is required to identify the conservation importance of independent smallholder oil palm plantations on biodiversity. This paper discussed the role of independent smallholdings in the conservation of biodiversity in oil palm plantations and to compare it with High Conservation Value Forest as a conservation standard of RSPO. The research was conducted from March to April 2016. Data on biodiversity were collected on 16 plantations and 8 private oil palm plantations in the Districts of Kampar, Pelalawan, Kuantan, Singingi and Siak of Riau Province, Indonesia. In addition, data on community environmental perceptions of both smallholder plantation and High Conservation Value (HCV) Forest were also collected. Species that were observed were birds and earthworms. Data on birds were collected using transect method, while identification of earthworm was determine by taking some soil samples and counting the number of individual earthworm found for each worm species. The research used direct interview with oil palm owners and community members, as well as direct observation to examine the environmental conditions of each plantation. In general, field observation and measurement have found that birds species richness was higher in the forested HCV Forest. Nevertheless, if compared to non-forested HCV, bird’s species richness was higher in the independent smallholdings. On the other hand, different results were observed for earthworm, where the density was higher in the independent smallholdings than in the HCV. It can be concluded from this research that managing independent smallholder oil palm plantations and forested HCV forest could enhance biodiversity conservation. The results of this study justified the importance of retaining forested area to safeguard biodiversity in oil palm plantation.

Keywords: biodiversity conservation, high conservation value forest, independent smallholdings, oil palm plantations

Procedia PDF Downloads 224

Authors: Seyed Hossein Alavi, Farshad Ghazalian, Soghra Jamshidi

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The present study was done with the purpose of considering mental health and general purpose of describing and comparing depression level of athlete and non-athlete male students educational year of 2012 Research method in this study in proportion to the selective title, descriptive method is causative – comparative. Research samples were selected randomly from B.A students of different fields including 500 students. Average mean of research samples was between 20 to 25 years. Data collection tool is questionnaire of depression measurement of Aroun Beck (B.D.I) that analyzes and measures 21 aspects of depression in 6 ranges. Operation related to analysis of statistical data to extraction of results was done by SPSS software. To extraction of research obtained by comparison of depression level mean, show that the hypothesis of the research (H_1) based on the existence of the significance scientific difference was supported and showed that there’s a significance difference between depression level of athlete male students in comparison with depression level of non-athlete male students. Thus, depression level of athlete male students was lower in comparison with depression level of non-athlete male students.

Keywords: depression, athlete students, non-athlete students

Procedia PDF Downloads 479

Authors: Behrooz Daneshmand

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Software Defined Networking (SDN) is designed to meet the future needs of 5G mobile networks. The SDN architecture offers a new solution that involves separating the control plane from the data plane, which is usually paired together. Network functions traditionally performed on specific hardware can now be abstracted and virtualized on any device, and a centralized software-based administration approach is based on a central controller, facilitating the development of modern applications and services. These plan standards clear the way for a more adaptable, speedier, and more energetic network beneath computer program control compared with a conventional network. We accept SDN gives modern inquire about openings to security, and it can significantly affect network security research in numerous diverse ways. Subsequently, the SDN architecture engages systems to effectively screen activity and analyze threats to facilitate security approach modification and security benefit insertion. The segregation of the data planes and control and, be that as it may, opens security challenges, such as man-in-the-middle attacks (MIMA), denial of service (DoS) attacks, and immersion attacks. In this paper, we analyze security threats to each layer of SDN - application layer - southbound interfaces/northbound interfaces - controller layer and data layer. From a security point of see, the components that make up the SDN architecture have a few vulnerabilities, which may be abused by aggressors to perform noxious activities and hence influence the network and its administrations. Software-defined network assaults are shockingly a reality these days. In a nutshell, this paper highlights architectural weaknesses and develops attack vectors at each layer, which leads to conclusions about further progress in identifying the consequences of attacks and proposing mitigation strategies.

Keywords: software-defined networking, security, SDN, 5G/IMT-2020

Procedia PDF Downloads 100

Authors: Amina Lyria Deghal Cheridi, Abla Chaker, Ahcene Loubar

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Relap5 system code is one among powerful tools, which is used in the area of design and safety evaluation. This work aims to simulate the behavior of a radiant steam boiler at the steady-state conditions using Relap5 code system. To perform this study, a detailed Relap5 model is built including all the parts of the steam boiler. The control and regulation systems are also considered. To reproduce the most important parameters and phenomena with an acceptable accuracy and fidelity, a strong qualification work is undertaken concerning the facility nodalization. It consists of making a comparison between the code results and the plant available data in steady-state operation mode. Therefore, the model qualification results at the steady-state are in good agreement with the steam boiler experimental data. The steam boiler Relap5 model has proved satisfactory; and the model was capable of predicting the main thermal-hydraulic steady-state conditions of the steam boiler.

Keywords: industrial steam boiler, model qualification, natural circulation, relap5/mod3.2, steady state simulation

Procedia PDF Downloads 273

Authors: F. Massri, M. Shkarneh, B. Almassri

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Water scarcity and increasing water demand especially for residential use are major challenges facing Palestine. The need to accurately forecast water consumption is useful for the planning and management of this natural resource. The main objective of this paper is to (i) study the major factors influencing the water consumption in Palestine, (ii) understand the general pattern of Household water consumption, (iii) assess the possible changes in household water consumption and suggest appropriate remedies and (iv) develop prediction model based on the Artificial Neural Network to the water consumption in Palestinian cities. The paper is organized in four parts. The first part includes literature review of household water consumption studies. The second part concerns data collection methodology, conceptual frame work for the household water consumption surveys, survey descriptions and data processing methods. The third part presents descriptive statistics, multiple regression and analysis of the water consumption in the two Palestinian cities. The final part develops the use of Artificial Neural Network for modeling the water consumption in Palestinian cities.

Keywords: water management, demand forecasting, consumption, ANN, Ramallah

Procedia PDF Downloads 219

Authors: Issa M. Shehabat, Huda F. Y. Nimri

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This paper aims to study the relationship between knowledge management in its processes, including knowledge creation, knowledge sharing, knowledge organization, and knowledge application, and business intelligence tools, including OLAP, data mining, and data warehouse, and their impact on the decision-making process in the banking sector in Jordan. A total of 200 questionnaires were distributed to the sample of the study. The study hypotheses were tested using the statistical package SPSS. Study findings suggest that decision-making processes were positively related to knowledge management processes. Additionally, the components of business intelligence had a positive impact on decision-making. The study recommended conducting studies similar to this study in other sectors such as the industrial, telecommunications, and service sectors to contribute to enhancing understanding of the role of the knowledge management processes and business intelligence tools.

Keywords: business intelligence, knowledge management, decision making, Jordan, banking sector

Procedia PDF Downloads 144

Authors: Delna Shroff

Abstract:

Merchant shipping is an occupation with a high rate of fatal injuries caused by organizational accidents and maritime disasters. In most accident investigations, the leader’s actions are under scrutiny and point out the necessity to investigate the leader’s decisions in critical conditions. While several leadership studies have been carried out in the past, there is a tendency for most research to focus on holders of formal positions. The unit of analysis in most studies has been the ‘individual.’ A need is, therefore, felt to adopt a practice-based perspective of leadership, understand how leadership emerges to affect maritime safety. This paper explores the phenomenon of distributed leadership among seafarers more holistically. It further examines the role of one form of distributed leadership, that is, planfully aligned leadership in the emergency response of the team. A mixed design will be applied. In the first phase, the data gathered by way of semi-structured interviews will be used to explore the seafarer’s implicit understanding of leadership. The data will be used to develop a conceptual framework of distributed leadership, specific to the maritime context. This framework will be used to develop a simulation. Experimental design will be used to examine the relationship between planfully aligned leadership and emergency response of the team members during navigation. Findings show that planfully aligned leadership significantly and positively predicts the emergency response of team members. Planfully aligned leadership leads to a better emergency response of the team members as compared to authoritarian leadership. In the third qualitative phase, additional data will be gathered through semi-structured interviews to further validate the findings to gain a more complete understanding of distributed leadership and its relation to emergency response. Above are the predictive results; the study expects to be a cornerstone of safety leadership research and has important implications for leadership development and training within the maritime industry.

Keywords: authoritarian leadership, distributed leadership, emergency response , planfully aligned leadership

Procedia PDF Downloads 175

Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection

Procedia PDF Downloads 453

Authors: Anujendra, Parag Kumar Guha Thakurta

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The data transmission between mobile hosts and base stations (BSs) in Mobile networks are often vulnerable to failure. Thus, efficient link connectivity, in terms of the services of both base stations and communication channels of the network, is required in wireless mobile networks to achieve highly reliable data transmission. In addition, it is observed that the number of blocked hosts is increased due to insufficient number of channels during heavy load in the network. Under such scenario, the channels are allocated accordingly to offer a reliable communication at any given time. Therefore, a reliability-based channel allocation model with acceptable system performance is proposed as a MOO problem in this paper. Two conflicting parameters known as Resource Reuse factor (RRF) and the number of blocked calls are optimized under reliability constraint in this problem. The solution to such MOO problem is obtained through NSGA-II (Non-dominated Sorting Genetic Algorithm). The effectiveness of the proposed model in this work is shown with a set of experimental results.

Keywords: base station, channel, GA, pareto-optimal, reliability

Procedia PDF Downloads 408