Search results for: real-time data
21631 Production Increase of C-Central Wells Baher Essalm-Libya
Authors: Walid Ben Husein, Emad Krekshi, Malek Essnni
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The Bahr Essalam gas-condensate field is located off the Libyan coast and is currently being produced by Mellitah Oil and Gas (MOG). Gas and condensate are produced from the Bahr Essalam reservoir through a mixture of platform and subsea wells, with the subsea wells being gathered at the western manifolds and delivered to the Sabratha platform via a 22-inch pipeline. Gas is gathered and dehydrated on the Sabratha platform and then delivered to the Mellitah gas plant via an existing 36-inch gas export pipeline. The condensate separated on the Sabratha platform will be delivered to the Mellitah gas plant via an existing 10-inch export pipeline. The Bahr Essalam Phase II project includes 2 production wells (CC16 & CC17) at C-Central A connected to the Sabratha platform via a new 10.9 km long 10”/14” production pipeline. Production rates from CC16 and CC17 have exceeded the maximum planned rate of 40 MMSCFD per well. A hydrothermal analysis was conducted to review and Verify input data, focusing on the variation of flowing well head as a function of flowrate as well as Review available input data against the previous design input data to determine the extent of change. The steady-state and transient simulations performed with Olga yielded coherent results and confirmed the possibility of achieving flow rates of up to 60MMSCFD per well without exceeding the design temperatures, pressures, and velocities.Keywords: Bahr Essalam, Mellitah Oil and Gas, production flow rates, steady state, transient, OLGA.
Procedia PDF Downloads 1021630 Exploring the Travel Preferences of Generation Z: A Look into the Next Generation of Tourists
Authors: M. Panidou, F. Kilipiris, E. Christou, K. Alexandris
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This study focuses on Generation Z, the next generation of tourists born between 1996 and 2012. Given their significant population size, Generation Z is expected to have a substantial impact on the travel and tourism sector. Therefore, understanding their travel preferences is crucial for businesses in the hospitality and tourism industry. By examining their travel preferences, this research aims to identify the unique characteristics and motivations of this generation when it comes to travel. This study used a quantitative method, and primary data was collected through a survey (online questionnaire), while secondary data was gathered from academic literature, industry reports, and online sources to provide a comprehensive analysis of the topic. The sample of the study was 100 Greek individuals aged between 18-26 years old. The data was analyzed with the support of SPSS software. The findings of the research indicated that technology, sustainability, and budget-friendly options are essential components for attracting and retaining Generation Z tourists. These preferences highlight the importance of incorporating innovative technologies, promoting sustainable practices, and offering affordable travel options to effectively engage this market niche. This research contributes to the field of hospitality and tourism businesses by providing valuable insights into the travel preferences of Generation Z. By understanding their distinct features and preferences; businesses can tailor their strategies and marketing efforts to effectively engage and retain this market segment. Considering the limitations of the sample size, future studies could aim for a larger and more diverse sample to enhance the generalizability of the findings.Keywords: gen Z, technology, travel preferences, sustainability
Procedia PDF Downloads 8621629 A Secure Routing Algorithm for Underwater Wireless Sensor Networks
Authors: Seyed Mahdi Jameii
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Underwater wireless sensor networks have been attracting the interest of many researchers lately, and the past three decades have beheld the rapid progress of underwater acoustic communication. One of the major problems in underwater wireless sensor networks is how to transfer data from the moving node to the base stations and choose the optimized route for data transmission. Secure routing in underwater wireless sensor network (UWCNs) is necessary for packet delivery. Some routing protocols are proposed for underwater wireless sensor networks. However, a few researches have been done on secure routing in underwater sensor networks. In this article, a secure routing protocol is provided to resist against wormhole and sybil attacks. The results indicated acceptable performance in terms of increasing the packet delivery ratio with regards to the attacks, increasing network lifetime by creating balance in the network energy consumption, high detection rates against the attacks, and low-end to end delay.Keywords: attacks, routing, security, underwater wireless sensor networks
Procedia PDF Downloads 41821628 Factors Predicting Preventive Behavior for Osteoporosis in University Students
Authors: Thachamon Sinsoongsud, Noppawan Piaseu
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This predictive study was aimed to 1) describe self efficacy for risk reduction and preventive behavior for osteoporosis, and 2) examine factors predicting preventive behavior for osteoporosis in nursing students. Through purposive sampling, the sample included 746 nursing students in a public university in Bangkok, Thailand. Data were collected by a self-reported questionnaire on self efficacy and preventive behavior for osteoporosis. Data were analyzed using descriptive statistics and multiple regression analysis with stepwise method. Results revealed that majority of the students were female (98.3%) with mean age of 19.86 + 1.26 years. The students had self efficacy and preventive behavior for osteoporosis at moderate level. Self efficacy and level of education could together predicted 35.2% variance of preventive behavior for osteoporosis (p< .001). Results suggest approaches for promoting preventive behavior for osteoporosis through enhancing self efficacy among nursing students in a public university in Bangkok, Thailand.Keywords: osteoporosis, self-efficacy, preventive behavior, nursing students
Procedia PDF Downloads 37821627 Design, Construction And Validation Of A Simple, Low-cost Phi Meter
Authors: Gabrielle Peck, Ryan Hayes
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The use of a phi meter allows for definition of equivalence ratio during a fire test. Previous phi meter designs have used expensive catalysts and had restricted portability due to the large furnace and requirement for pure oxygen. The new design of the phi meter did not require the use of a catalyst. The furnace design was based on the existing micro-scale combustion calorimetry (MCC) furnace and operating conditions based on the secondary oxidizer furnace used in the steady state tube furnace (SSTF). Preliminary tests were conducted to study the effects of varying furnace temperatures on combustion efficiency. The SSTF was chosen to validate the phi meter measurements as it can both pre-set and independently quantify the equivalence ratio during a test. The data were in agreement with the data obtained on the SSTF. It was also validated by a comparison of CO2 yields obtained from the SSTF oxidizer and those obtained by the phi meter. The phi meter designed and constructed in this work was proven to work effectively on a bench-scale. The phi meter was then used to measure the equivalence ratio on a series of large-scale ISO 9705 tests for numerous fire conditions. The materials used were a range of non-homogenous materials such as polyurethane. The measurements corresponded accurately to the data collected, showing the novel design can be used from bench to large-scale tests to measure equivalence ratio. This cheaper, more portable, safer and easier to use phi meter design will enable more widespread use and the ability to quantify fire conditions of tests, allowing for better understanding of flammability and smoke toxicity.Keywords: phi meter, smoke toxicity, fire condition, ISO9705, novel equipment
Procedia PDF Downloads 10321626 Uncertainty Assessment in Building Energy Performance
Authors: Fally Titikpina, Abderafi Charki, Antoine Caucheteux, David Bigaud
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The building sector is one of the largest energy consumer with about 40% of the final energy consumption in the European Union. Ensuring building energy performance is of scientific, technological and sociological matter. To assess a building energy performance, the consumption being predicted or estimated during the design stage is compared with the measured consumption when the building is operational. When valuing this performance, many buildings show significant differences between the calculated and measured consumption. In order to assess the performance accurately and ensure the thermal efficiency of the building, it is necessary to evaluate the uncertainties involved not only in measurement but also those induced by the propagation of dynamic and static input data in the model being used. The evaluation of measurement uncertainty is based on both the knowledge about the measurement process and the input quantities which influence the result of measurement. Measurement uncertainty can be evaluated within the framework of conventional statistics presented in the \textit{Guide to the Expression of Measurement Uncertainty (GUM)} as well as by Bayesian Statistical Theory (BST). Another choice is the use of numerical methods like Monte Carlo Simulation (MCS). In this paper, we proposed to evaluate the uncertainty associated to the use of a simplified model for the estimation of the energy consumption of a given building. A detailed review and discussion of these three approaches (GUM, MCS and BST) is given. Therefore, an office building has been monitored and multiple sensors have been mounted on candidate locations to get required data. The monitored zone is composed of six offices and has an overall surface of 102 $m^2$. Temperature data, electrical and heating consumption, windows opening and occupancy rate are the features for our research work.Keywords: building energy performance, uncertainty evaluation, GUM, bayesian approach, monte carlo method
Procedia PDF Downloads 45921625 An Investigation of the Association between Pathological Personality Dimensions and Emotion Dysregulation among Virtual Network Users: The Mediating Role of Cyberchondria Behaviors
Authors: Mehdi Destani, Asghar Heydari
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Objective: The present study aimed to investigate the association between pathological personality dimensions and emotion dysregulation through the mediating role of Cyberchondria behaviors among users of virtual networks. Materials and methods: A descriptive–correlational research method was used in this study, and the statistical population consisted of all people active on social network sites in 2020. The sample size was 300 people who were selected through Convenience Sampling. Data collection was carried out in a survey method using online questionnaires, including the "Difficulties in Emotion Regulation Scale" (DERS), Personality Inventory for DSM-5 Brief Form (PID-5-BF), and Cyberchondria Severity Scale Brief Form (CSS-12). Data analysis was conducted using Pearson's Correlation Coefficient and Structural Equation Modeling (SEM). Findings: Findings suggested that pathological personality dimensions and Cyberchondria behaviors have a positive and significant association with emotion dysregulation (p<0.001). The presented model had a good fit with the data. The variable “pathological personality dimensions” with an overall effect (p<0.001, β=0.658), a direct effect (p<0.001, β=0.528), and an indirect mediating effect through Cyberchondria Behaviors (p<.001), β=0.130), accounted for emotion dysregulation among virtual network users. Conclusion: The research findings showed a necessity to pay attention to the pathological personality dimensions as a determining variable and Cyberchondria behaviors as a mediator in the vulnerability of users of social network sites to emotion dysregulation.Keywords: cyberchondria, emotion dysregulation, pathological personality dimensions, social networks
Procedia PDF Downloads 10421624 Investigating Activity Recognition Using 9-Axis Sensors and Filters in Wearable Devices
Authors: Jun Gil Ahn, Jong Kang Park, Jong Tae Kim
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In this paper, we analyze major components of activity recognition (AR) in wearable device with 9-axis sensors and sensor fusion filters. 9-axis sensors commonly include 3-axis accelerometer, 3-axis gyroscope and 3-axis magnetometer. We chose sensor fusion filters as Kalman filter and Direction Cosine Matrix (DCM) filter. We also construct sensor fusion data from each activity sensor data and perform classification by accuracy of AR using Naïve Bayes and SVM. According to the classification results, we observed that the DCM filter and the specific combination of the sensing axes are more effective for AR in wearable devices while classifying walking, running, ascending and descending.Keywords: accelerometer, activity recognition, directiona cosine matrix filter, gyroscope, Kalman filter, magnetometer
Procedia PDF Downloads 33321623 Using Multi-Level Analysis to Identify Future Trends in Small Device Digital Communication Examinations
Authors: Mark A. Spooner
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The growth of technological advances in the digital communications industry has dictated the way forensic examination laboratories receive, analyze, and report on digital evidence. This study looks at the trends in a medium sized digital forensics lab that examines small communications devices (i.e., cellular telephones, tablets, thumb drives, etc.) over the past five years. As law enforcement and homeland security organizations budgets shrink, many agencies are being asked to perform more examinations with less resources available. Using multi-level statistical analysis using five years of examination data, this research shows the increasing technological demand trend. The research then extrapolates the current data into the model created and finds a continued exponential growth curve of said demands is well within the parameters defined earlier on in the research.Keywords: digital forensics, forensic examination, small device, trends
Procedia PDF Downloads 19921622 Investigation of Clustering Algorithms Used in Wireless Sensor Networks
Authors: Naim Karasekreter, Ugur Fidan, Fatih Basciftci
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Wireless sensor networks are networks in which more than one sensor node is organized among themselves. The working principle is based on the transfer of the sensed data over the other nodes in the network to the central station. Wireless sensor networks concentrate on routing algorithms, energy efficiency and clustering algorithms. In the clustering method, the nodes in the network are divided into clusters using different parameters and the most suitable cluster head is selected from among them. The data to be sent to the center is sent per cluster, and the cluster head is transmitted to the center. With this method, the network traffic is reduced and the energy efficiency of the nodes is increased. In this study, clustering algorithms were examined in terms of clustering performances and cluster head selection characteristics to try to identify weak and strong sides. This work is supported by the Project 17.Kariyer.123 of Afyon Kocatepe University BAP Commission.Keywords: wireless sensor networks (WSN), clustering algorithm, cluster head, clustering
Procedia PDF Downloads 51321621 Analysis of Road Risk in Four French Overseas Territories Compared with Metropolitan France
Authors: Mohamed Mouloud Haddak, Bouthayna Hayou
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Road accidents in French overseas territories have been understudied, with relevant data often collected late and incompletely. Although these territories account for only 3% to 4% of road traffic injuries in France, their unique characteristics merit closer attention. Despite lower mobility and, consequently, lower exposure to road risks, the actual road risk in Overseas France is as high or even higher than in Metropolitan France. Significant disparities exist not only between Metropolitan France and Overseas territories but also among the overseas territories themselves. The varying population densities in these regions do not fully explain these differences, as each territory has its own distinct vulnerabilities and road safety challenges. This analysis, based on BAAC data files from 2005 to 2018 for both Metropolitan France and the overseas departments and regions, examines key variables such as gender, age, type of road user, type of obstacle hit, type of trip, road category, traffic conditions, weather, and location of accidents. Logistic regression models were built for each region to investigate the risk factors associated with fatal road accidents, focusing on the probability of being killed versus injured. Due to insufficient data, Mayotte and the Overseas Communities (French Polynesia and New Caledonia) were not included in the models. The findings reveal that road safety is worse in the overseas territories compared to Metropolitan France, particularly for vulnerable road users such as pedestrians and motorized two-wheelers. These territories present an accident profile that sits between that of Metropolitan France and middle-income countries. A pressing need exists to standardize accident data collection between Metropolitan and Overseas France to allow for more detailed comparative analyses. Further epidemiological studies could help identify the specific road safety issues unique to each territory, particularly with regards to socio-economic factors such as social cohesion, which may influence road safety outcomes. Moreover, the lack of data on new modes of travel, such as electric scooters, and the absence of socio-economic details of accident victims complicate the evaluation of emerging risk factors. Additional research, including sociological and psychosocial studies, is essential for understanding road users' behavior and perceptions of road risk, which could also provide valuable insights into accident trends in peri-urban areas in France.Keywords: multivariate logistic regression, french overseas regions, road safety, road traffic accidents, territorial inequalities
Procedia PDF Downloads 1121620 Analysis of Developments in the Understanding of In-Service Training in Turkish Public Administration: Personnel Management to Human Resource Management
Authors: Sema Müge Özdemiray
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In line with the new public management approach to provide effective and efficient services necessary to achieve the social goals of public institutions, employees must have the knowledge and skills required by the age. In conjunction with the transition from personnel management to human resources management, it is seen that there is a change in the understanding of in-service training, the understanding of "required in-service training" has switched to the understanding of "continuous in-service training". However, in terms of in-service training in Turkey, it seems to be trouble at the point of adopting to change. The main purpose of this study is to primarily create a conceptual framework of in-service training and subsequently determine, analyze and discuss the developments and problems faced by in-service training in Turkey in the transition from personnel management to human resources management. In accordance with this purpose, the necessary data of this study were collected using qualitative approaches. Observation and document analysis was used and content analysis was performed on the data gathered in the study. The results of this study, according to data such as the number of institutions requesting in-service training, allocated budget of in-service training, the number of people participating in such training, transition of personnel management to human resources management should not lead to a paradigm shift in Turkey’s understanding of in-service training, although this is compulsory for public institutions in accordance with the law in Turkey. In-service training in Turkish public administration is still not implemented effectively and is seen as a social activity for employees and a formality for institutions.Keywords: Human resources management, in service training, personnel management, public institutions
Procedia PDF Downloads 31921619 Ethical Leadership and Individual Creativity: The Mediating Role of Psychological Safety
Authors: Hyeondal Jeong, Yoonjung Baek
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This study examines the relationship between ethical leadership and individual creativity and focused on mediating effects of psychological safety. In order to clarify the mechanism of ethical leadership, psychological safety of the members was set as a mediator. Using data gathered from a sample of 150 employees. For data analysis, exploratory factor analysis, correlation analysis, hierarchical regression analysis and Sobel-Test were performed. The results showed that ethical leadership had a positive effect on psychological safety and individual creativity, and psychological safety had a positive mediating effect. Since the mediating effect of psychological safety has been confirmed, we need to find ways to improve the psychological safety of the members in terms of organizational management. Psychological safety has a positive effect on individual creativity, which can have a positive impact on innovation throughout the organization.Keywords: ethical leadership, creativity, psychological safety, ethics management, innovative behaviors
Procedia PDF Downloads 24921618 Ensemble Machine Learning Approach for Estimating Missing Data from CO₂ Time Series
Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold
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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network
Procedia PDF Downloads 14021617 Investigation of Cavitation in a Centrifugal Pump Using Synchronized Pump Head Measurements, Vibration Measurements and High-Speed Image Recording
Authors: Simon Caba, Raja Abou Ackl, Svend Rasmussen, Nicholas E. Pedersen
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It is a challenge to directly monitor cavitation in a pump application during operation because of a lack of visual access to validate the presence of cavitation and its form of appearance. In this work, experimental investigations are carried out in an inline single-stage centrifugal pump with optical access. Hence, it gives the opportunity to enhance the value of CFD tools and standard cavitation measurements. Experiments are conducted using two impellers running in the same volute at 3000 rpm and the same flow rate. One of the impellers used is optimized for lower NPSH₃% by its blade design, whereas the other one is manufactured using a standard casting method. The cavitation is detected by pump performance measurements, vibration measurements and high-speed image recordings. The head drop and the pump casing vibration caused by cavitation are correlated with the visual appearance of the cavitation. The vibration data is recorded in an axial direction of the impeller using accelerometers recording at a sample rate of 131 kHz. The vibration frequency domain data (up to 20 kHz) and the time domain data are analyzed as well as the root mean square values. The high-speed recordings, focusing on the impeller suction side, are taken at 10,240 fps to provide insight into the flow patterns and the cavitation behavior in the rotating impeller. The videos are synchronized with the vibration time signals by a trigger signal. A clear correlation between cloud collapses and abrupt peaks in the vibration signal can be observed. The vibration peaks clearly indicate cavitation, especially at higher NPSHA values where the hydraulic performance is not affected. It is also observed that below a certain NPSHA value, the cavitation started in the inlet bend of the pump. Above this value, cavitation occurs exclusively on the impeller blades. The impeller optimized for NPSH₃% does show a lower NPSH₃% than the standard impeller, but the head drop starts at a higher NPSHA value and is more gradual. Instabilities in the head drop curve of the optimized impeller were observed in addition to a higher vibration level. Furthermore, the cavitation clouds on the suction side appear more unsteady when using the optimized impeller. The shape and location of the cavitation are compared to 3D fluid flow simulations. The simulation results are in good agreement with the experimental investigations. In conclusion, these investigations attempt to give a more holistic view on the appearance of cavitation by comparing the head drop, vibration spectral data, vibration time signals, image recordings and simulation results. Data indicates that a criterion for cavitation detection could be derived from the vibration time-domain measurements, which requires further investigation. Usually, spectral data is used to analyze cavitation, but these investigations indicate that the time domain could be more appropriate for some applications.Keywords: cavitation, centrifugal pump, head drop, high-speed image recordings, pump vibration
Procedia PDF Downloads 18021616 A Semiparametric Approach to Estimate the Mode of Continuous Multivariate Data
Authors: Tiee-Jian Wu, Chih-Yuan Hsu
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Mode estimation is an important task, because it has applications to data from a wide variety of sources. We propose a semi-parametric approach to estimate the mode of an unknown continuous multivariate density function. Our approach is based on a weighted average of a parametric density estimate using the Box-Cox transform and a non-parametric kernel density estimate. Our semi-parametric mode estimate improves both the parametric- and non-parametric- mode estimates. Specifically, our mode estimate solves the non-consistency problem of parametric mode estimates (at large sample sizes) and reduces the variability of non-parametric mode estimates (at small sample sizes). The performance of our method at practical sample sizes is demonstrated by simulation examples and two real examples from the fields of climatology and image recognition.Keywords: Box-Cox transform, density estimation, mode seeking, semiparametric method
Procedia PDF Downloads 28521615 Threat Analysis: A Technical Review on Risk Assessment and Management of National Testing Service (NTS)
Authors: Beenish Urooj, Ubaid Ullah, Sidra Riasat
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National Testing Service-Pakistan (NTS) is an agency in Pakistan that conducts student success appraisal examinations. In this research paper, we must present a security model for the NTS organization. The security model will depict certain security countermeasures for a better defense against certain types of breaches and system malware. We will provide a security roadmap, which will help the company to execute its further goals to maintain security standards and policies. We also covered multiple aspects in securing the environment of the organization. We introduced the processes, architecture, data classification, auditing approaches, survey responses, data handling, and also training and awareness of risk for the company. The primary contribution is the Risk Survey, based on the maturity model meant to assess and examine employee training and knowledge of risks in the company's activities.Keywords: NTS, risk assessment, threat factors, security, services
Procedia PDF Downloads 7021614 Enhancing Healthcare Delivery in Low-Income Markets: An Exploration of Wireless Sensor Network Applications
Authors: Innocent Uzougbo Onwuegbuzie
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Healthcare delivery in low-income markets is fraught with numerous challenges, including limited access to essential medical resources, inadequate healthcare infrastructure, and a significant shortage of trained healthcare professionals. These constraints lead to suboptimal health outcomes and a higher incidence of preventable diseases. This paper explores the application of Wireless Sensor Networks (WSNs) as a transformative solution to enhance healthcare delivery in these underserved regions. WSNs, comprising spatially distributed sensor nodes that collect and transmit health-related data, present opportunities to address critical healthcare needs. Leveraging WSN technology facilitates real-time health monitoring and remote diagnostics, enabling continuous patient observation and early detection of medical issues, especially in areas with limited healthcare facilities and professionals. The implementation of WSNs can enhance the overall efficiency of healthcare systems by enabling timely interventions, reducing the strain on healthcare facilities, and optimizing resource allocation. This paper highlights the potential benefits of WSNs in low-income markets, such as cost-effectiveness, increased accessibility, and data-driven decision-making. However, deploying WSNs involves significant challenges, including technical barriers like limited internet connectivity and power supply, alongside concerns about data privacy and security. Moreover, robust infrastructure and adequate training for local healthcare providers are essential for successful implementation. It further examines future directions for WSNs, emphasizing innovation, scalable solutions, and public-private partnerships. By addressing these challenges and harnessing the potential of WSNs, it is possible to revolutionize healthcare delivery and improve health outcomes in low-income markets.Keywords: wireless sensor networks (WSNs), healthcare delivery, low-Income markets, remote patient monitoring, health data security
Procedia PDF Downloads 3721613 Structural Health Monitoring of Offshore Structures Using Wireless Sensor Networking under Operational and Environmental Variability
Authors: Srinivasan Chandrasekaran, Thailammai Chithambaram, Shihas A. Khader
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The early-stage damage detection in offshore structures requires continuous structural health monitoring and for the large area the position of sensors will also plays an important role in the efficient damage detection. Determining the dynamic behavior of offshore structures requires dense deployment of sensors. The wired Structural Health Monitoring (SHM) systems are highly expensive and always needs larger installation space to deploy. Wireless sensor networks can enhance the SHM system by deployment of scalable sensor network, which consumes lesser space. This paper presents the results of wireless sensor network based Structural Health Monitoring method applied to a scaled experimental model of offshore structure that underwent wave loading. This method determines the serviceability of the offshore structure which is subjected to various environment loads. Wired and wireless sensors were installed in the model and the response of the scaled BLSRP model under wave loading was recorded. The wireless system discussed in this study is the Raspberry pi board with Arm V6 processor which is programmed to transmit the data acquired by the sensor to the server using Wi-Fi adapter, the data is then hosted in the webpage. The data acquired from the wireless and wired SHM systems were compared and the design of the wireless system is verified.Keywords: condition assessment, damage detection, structural health monitoring, structural response, wireless sensor network
Procedia PDF Downloads 27621612 Comparative Study of Sound Intensity in Individuals Diagnosed with Antisocial Personality Disorder and Normal People
Authors: Nadia Warmilee
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This study is s descriptive-analytical research and it aims at studying sound intensity in individuals with antisocial personality disorder and ordinary persons. Data were collected from experimental and control groups by interviews and a field research. Population was all male Iranian with antisocial personality disorder that three of them (a murderer and two individuals with antisocial personality disorder (APD) who have not committed any crimes yet) were selected purposefully. They were compared to three non-affected people. PRAAT software has been used to analyze the data. Results of this study show that there is a significant relationship between dysthymia and sound intensity values. Antisocial personality disorder also affects sound intensity fluctuations. The values of sound intensity are higher in non-affected people than affected one whilst these values are more monotonous. T-test was used to study significance or in significance of sound intensity difference in producing vowels.Keywords: Acoustics, Sound Intensity, Antisocial Personality Disorder, Psycholinguistics
Procedia PDF Downloads 13021611 Understanding the Safety Impacts of Imbalances in Truck Parking Supply and Demand
Authors: Rahil Saeedi
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The imbalance in truck parking supply and demand can create important safety issues for truck drivers and the public. Research has shown that breaks at specific intervals can increase drivers’ alertness by reducing the monotony of the task. However, if fatigued truck drivers are unable to find a safe parking spot for rest, they may continue to drive or choose to park at remote and insecure areas or undesignated locations. All of these situations pose serious safety and security risks to truck drivers and other roadway users. This study uses 5-year truck crash data in Ohio to develop and test a framework for identifying crashes that happen as a result of imbalances in truck parking supply and demand. The societal impacts of these crashes are then interpreted as monetary values, calculated using the costs associated with various crash severity levels.Keywords: truck parking, road safety, crash data, geofencing, driver fatigue, undesignated parking
Procedia PDF Downloads 16721610 Extending Image Captioning to Video Captioning Using Encoder-Decoder
Authors: Sikiru Ademola Adewale, Joe Thomas, Bolanle Hafiz Matti, Tosin Ige
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This project demonstrates the implementation and use of an encoder-decoder model to perform a many-to-many mapping of video data to text captions. The many-to-many mapping occurs via an input temporal sequence of video frames to an output sequence of words to form a caption sentence. Data preprocessing, model construction, and model training are discussed. Caption correctness is evaluated using 2-gram BLEU scores across the different splits of the dataset. Specific examples of output captions were shown to demonstrate model generality over the video temporal dimension. Predicted captions were shown to generalize over video action, even in instances where the video scene changed dramatically. Model architecture changes are discussed to improve sentence grammar and correctness.Keywords: decoder, encoder, many-to-many mapping, video captioning, 2-gram BLEU
Procedia PDF Downloads 10821609 Counter-Terrorism and Civil Society in Nigeria
Authors: Emeka Thaddues Njoku
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Since 2009, the Nigerian Government has established diverse counter-terrorism legislations and practices in response terrorism in North Eastern part of the country. However, these measures have hampered not only the ability of civil society organizations to sustain the autonomous spaces that define/locate them at the intersection between the state and public but also the balance between freedom and security. Hence, this study examines the various elements associated with the interface between the counter terrorism security framework of the government and the capacity of civil society organizations to carry out their mandates in Nigeria. In order to achieve this, the survey research of the ex-post facto type will be adopted using the multi-stage sampling technique. A total of two hundred (200) copies of questionnaire will be administered to members of the civil society organizations and 24 In-Depth Interviews (IDI) will be conducted for officials of security agencies, Ministry of Defence and operators of civil society organizations. Fifty respondents will be drawn from each civil society organisations in the areas of humanitarian assistance, human rights Advocacy, development-oriented, peace-building. Moreover, 24 interviewees drawn from the key members of the security agencies (6), Ministry of Defence (6) and 12 operators of civil society organizations-three respondents each will represent the four civil society organizations mentioned above. Also, secondary data will be used to complement In-depth Interview (IDI) sessions. All collected data will be coded and analysed using descriptive statistics of frequency counts and simple percentage in the Statistical Package for Social Science (SPSS). Content analysis will be used for the In-depth interview and secondary data.Keywords: counter-terrorism, civil society organizations, freedom, terrorism
Procedia PDF Downloads 39121608 Detecting Natural Fractures and Modeling Them to Optimize Field Development Plan in Libyan Deep Sandstone Reservoir (Case Study)
Authors: Tarek Duzan
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Fractures are a fundamental property of most reservoirs. Despite their abundance, they remain difficult to detect and quantify. The most effective characterization of fractured reservoirs is accomplished by integrating geological, geophysical, and engineering data. Detection of fractures and defines their relative contribution is crucial in the early stages of exploration and later in the production of any field. Because fractures could completely change our thoughts, efforts, and planning to produce a specific field properly. From the structural point of view, all reservoirs are fractured to some point of extent. North Gialo field is thought to be a naturally fractured reservoir to some extent. Historically, natural fractured reservoirs are more complicated in terms of their exploration and production efforts, and most geologists tend to deny the presence of fractures as an effective variable. Our aim in this paper is to determine the degree of fracturing, and consequently, our evaluation and planning can be done properly and efficiently from day one. The challenging part in this field is that there is no enough data and straightforward well testing that can let us completely comfortable with the idea of fracturing; however, we cannot ignore the fractures completely. Logging images, available well testing, and limited core studies are our tools in this stage to evaluate, model, and predict possible fracture effects in this reservoir. The aims of this study are both fundamental and practical—to improve the prediction and diagnosis of natural-fracture attributes in N. Gialo hydrocarbon reservoirs and accurately simulate their influence on production. Moreover, the production of this field comes from 2-phase plan; a self depletion of oil and then gas injection period for pressure maintenance and increasing ultimate recovery factor. Therefore, well understanding of fracturing network is essential before proceeding with the targeted plan. New analytical methods will lead to more realistic characterization of fractured and faulted reservoir rocks. These methods will produce data that can enhance well test and seismic interpretations, and that can readily be used in reservoir simulators.Keywords: natural fracture, sandstone reservoir, geological, geophysical, and engineering data
Procedia PDF Downloads 9321607 Chemometric Estimation of Inhibitory Activity of Benzimidazole Derivatives by Linear Least Squares and Artificial Neural Networks Modelling
Authors: Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević, Lidija R. Jevrić, Stela Jokić
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The subject of this paper is to correlate antibacterial behavior of benzimidazole derivatives with their molecular characteristics using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on the inhibitory activity of benzimidazole derivatives against Staphylococcus aureus. The data were processed by linear least squares (LLS) and artificial neural network (ANN) procedures. The LLS mathematical models have been developed as a calibration models for prediction of the inhibitory activity. The quality of the models was validated by leave one out (LOO) technique and by using external data set. High agreement between experimental and predicted inhibitory acivities indicated the good quality of the derived models. These results are part of the CMST COST Action No. CM1306 "Understanding Movement and Mechanism in Molecular Machines".Keywords: Antibacterial, benzimidazoles, chemometric, QSAR.
Procedia PDF Downloads 31621606 Use of Sentiel-2 Data to Monitor Plant Density and Establishment Rate of Winter Wheat Fields
Authors: Bing-Bing E. Goh
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Plant counting is a labour intensive and time-consuming task for the farmers. However, it is an important indicator for farmers to make decisions on subsequent field management. This study is to evaluate the potential of Sentinel-2 images using statistical analysis to retrieve information on plant density for monitoring, especially during critical period at the beginning of March. The model was calibrated with in-situ data from 19 winter wheat fields in Republic of Ireland during the crop growing season in 2019-2020. The model for plant density resulted in R2 = 0.77, RMSECV = 103 and NRMSE = 14%. This study has shown the potential of using Sentinel-2 to estimate plant density and quantify plant establishment to effectively monitor crop progress and to ensure proper field management.Keywords: winter wheat, remote sensing, crop monitoring, multivariate analysis
Procedia PDF Downloads 16121605 Impact of Television on the Coverage of Lassa Fever Disease in Nigeria
Authors: H. Shola Adeosun, F. Ajoke Adebiyi
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This study appraises the impact of television on the coverage of Lassa Fever disease. The objectives of the study are to find out whether television is an effective tool for raising awareness about Lassa fever shapes the perception of members of the public. The research work was based on the theoretical foundation of Agenda – setting and reinforcement theory. Survey research method was adopted in the study to elicit data from the residents of Obafemi Owode Local Government, area of Ogun state. Questionnaire and oral interview were adopted as a tool for data gathering. Simple random sampling techniques were used to draw a sample for this study. Out of filled 400 questionnaires distributed to the respondents. 37 of them were incorrectly filled and returned at the stipulated time. This is about (92.5% Tables, percentages, and figures were used to analyse and interpret the data and hypothesis formulation for this study revealed that Lassa fever diseases with higher media coverage were considered more serious and more representative of a disease and estimated to have lower incidents, than diseases less frequently found in the media. Thus, 92% of the respondents agree that they have access to television coverage of Lassa fever disease led to exaggerated perceptions of personal vulnerability. It, therefore, concludes that there is a need for relevant stakeholders to ensure better community health education and improved housing conditions in southwestern Nigeria, with an emphasis on slum areas and that Nigeria need to focus on the immediate response, while preparing for the future because a society or community is all about the people who inhabit. Therefore every effort must be geared towards their society and survival.Keywords: impact, television, coverage, Lassa fever disease
Procedia PDF Downloads 21221604 Presenting a Model in the Analysis of Supply Chain Management Components by Using Statistical Distribution Functions
Authors: Ramin Rostamkhani, Thurasamy Ramayah
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One of the most important topics of today’s industrial organizations is the challenging issue of supply chain management. In this field, scientists and researchers have published numerous practical articles and models, especially in the last decade. In this research, to our best knowledge, the discussion of data modeling of supply chain management components using well-known statistical distribution functions has been considered. The world of science owns mathematics, and showing the behavior of supply chain data based on the characteristics of statistical distribution functions is innovative research that has not been published anywhere until the moment of doing this research. In an analytical process, describing different aspects of functions including probability density, cumulative distribution, reliability, and failure function can reach the suitable statistical distribution function for each of the components of the supply chain management. It can be applied to predict the behavior data of the relevant component in the future. Providing a model to adapt the best statistical distribution function in the supply chain management components will be a big revolution in the field of the behavior of the supply chain management elements in today's industrial organizations. Demonstrating the final results of the proposed model by introducing the process capability indices before and after implementing it alongside verifying the approach through the relevant assessment as an acceptable verification is a final step. The introduced approach can save the required time and cost to achieve the organizational goals. Moreover, it can increase added value in the organization.Keywords: analyzing, process capability indices, statistical distribution functions, supply chain management components
Procedia PDF Downloads 8721603 Evaluation of Two Earliness Cotton Genotypes in Three Ecological Regions
Authors: Gholamhossein Hosseini
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Two earliness cotton genotypes I and II, which had been developed by hybridization and backcross methods between sindise-80 as an early maturing gene parent and two other lines i.e. Red leaf and Bulgare-557 as a second parent, are subjected to different environmental conditions. The early maturing genotypes with coded names of I and II were compared with four native cotton cultivars in randomized complete block design (RCBD) with four replications in three ecological regions of Iran from 2016-2017. Two early maturing genotypes along with four native cultivars viz. Varamin, Oltan, Sahel and Arya were planted in Agricultural Research Station of Varamin, Moghan and Kashmar for evaluation. Earliness data were collected for six treatments during two years in the three regions except missing data for the second year of Kashmar. Therefore, missed data were estimated and imputed. For testing the homogeneity of error variances, each experiment at a given location or year is analyzed separately using Hartley and Bartlett’s Chi-square tests and both tests confirmed homogeneity of variance. Combined analysis of variance showed that genotypes I and II were superior in Varamin, Moghan and Kashmar regions. Earliness means and their interaction effects were compared with Duncan’s multiple range tests. Finally combined analysis of variance showed that genotypes I and II were superior in Varamin, Moghan and Kashmar regions. Earliness means and their interaction effects are compared with Duncan’s multiple range tests.Keywords: cotton, combined, analysis, earliness
Procedia PDF Downloads 14121602 Compliance and Assessment Process of Information Technology in Accounting, in Turkey
Authors: Kocakaya Eda, Argun Doğan
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This study analyzed the present state of information technology in the field of accounting by bibliometric analysis of scientific studies on the impact on the transformation of e-billing and tax managementin Turkey. With comparative bibliometric analysis, the innovation and positive effects of the process that changed with e-transformation in the field of accounting with e-transformation in businesses and the information technologies used in accounting and tax management were analyzed comparatively. By evaluating the data obtained as a result of these analyzes, suggestions on the use of information technologies in accounting and tax management and the positive and negative effects of e-transformation on the analyzed activities of the enterprises were emphasized. With the e-transformation, which will be realized with the most efficient use of information technologies in Turkey. The synergy and efficiency of IT technology developments in avcoounting and finance should be revealed in the light of scientific data, from the smallest business to the largest economic enterprises.Keywords: information technologies, E-invoice, E-Tax management, E-transformation, accounting programs
Procedia PDF Downloads 120