Search results for: urban road network

Authors: Eslam Mohammed Abdelkader, Mohamed Marzouk, Tarek Zayed

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Infrastructure systems are crucial to every aspect of life on Earth. Existing Infrastructure is subjected to degradation while the demands are growing for a better infrastructure system in response to the high standards of safety, health, population growth, and environmental protection. Bridges play a crucial role in urban transportation networks. Moreover, they are subjected to high level of deterioration because of the variable traffic loading, extreme weather conditions, cycles of freeze and thaw, etc. The development of Bridge Management Systems (BMSs) has become a fundamental imperative nowadays especially in the large transportation networks due to the huge variance between the need for maintenance actions, and the available funds to perform such actions. Deterioration models represent a very important aspect for the effective use of BMSs. This paper presents a probabilistic time-based model that is capable of predicting the condition ratings of the concrete bridge decks along its service life. The deterioration process of the concrete bridge decks is modeled using semi-Markov process. One of the main challenges of the Markov Chain Decision Process (MCDP) is the construction of the transition probability matrix. Yet, the proposed model overcomes this issue by modeling the sojourn times based on some probability density functions. The sojourn times of each condition state are fitted to probability density functions based on some goodness of fit tests such as Kolmogorov-Smirnov test, Anderson Darling, and chi-squared test. The parameters of the probability density functions are obtained using maximum likelihood estimation (MLE). The condition ratings obtained from the Ministry of Transportation in Quebec (MTQ) are utilized as a database to construct the deterioration model. Finally, a comparison is conducted between the Markov Chain and semi-Markov chain to select the most feasible prediction model.

Keywords: bridge management system, bridge decks, deterioration model, Semi-Markov chain, sojourn times, maximum likelihood estimation

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Authors: Cecil Blake, Tolu Kayode-Adedeji, Innocent Chiluwa, Charles Iruonagbe

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National, regional and international security threats have dominated the twenty-first century thus far. Insurgencies that utilize “terrorism” as their primary strategy pose the most serious threat to global security. States in turn adopt terrorist strategies to resist and even defeat insurgents who invoke the legitimacy of statehood to justify their action. In short, the era is dominated by the use of terror tactics by state and non-state actors. Globally, there is a powerful network of groups involved in insurgencies using Islam as the bastion for their cause. In Africa, there are Boko Haram, Al Shabaab and Al Qaeda in the Maghreb representing Islamic groups utilizing terror strategies and tactics to prosecute their wars. The task at hand is to discover and to use multiple ways of handling the present security threats, including novel approaches to policy formulation, implementation, monitoring and evaluation that would pay significant attention to the important role of culture and communication strategies germane for discursive means of conflict resolution. In other to achieve this, the proposed research would address inter alia, root causes of insurgences that predicate their mission on Islamic tenets particularly in Africa; discursive and non-discursive counter-terrorism approaches fashioned by African governments, continental supra-national and regional organizations, recruitment strategies by major non-sate actors in Africa that rely solely on terrorist strategies and tactics and sources of finances for the groups under study. A major anticipated outcome of this research is a contribution to answers that would lead to the much needed stability required for development in African countries experiencing insurgencies carried out by the use of patterned terror strategies and tactics. The nature of the research requires the use of triangulation as the methodological tool.

Keywords: counter-terrorism, discourse, Nigeria, security, terrorism

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Authors: Rishabh Nagpal, Riya Uchagaonkar, Venkata Naga Narasimha Ashish Mernedi, Ahmed Hambaba

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The rapid evolution of technology in the communication sector continually seeks to bridge the gap between different communities, notably between the deaf community and the hearing world. This project develops a comprehensive American Sign Language (ASL) recognition system, leveraging the advanced capabilities of convolutional neural networks (CNNs) and vision transformers (ViTs) to interpret and translate ASL in real-time. The primary objective of this system is to provide an effective communication tool that enables seamless interaction through accurate sign language interpretation. The architecture of the proposed system integrates dual networks -VGG16 for precise spatial feature extraction and vision transformers for contextual understanding of the sign language gestures. The system processes live input, extracting critical features through these sophisticated neural network models, and combines them to enhance gesture recognition accuracy. This integration facilitates a robust understanding of ASL by capturing detailed nuances and broader gesture dynamics. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing diverse ASL signs, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced ASL recognition system and lays the groundwork for future innovations in assistive communication technologies.

Keywords: sign language, computer vision, vision transformer, VGG16, CNN

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Authors: Nazaitul Idya Hamzah, Muhammad Syafiq Mazli, Maszatul Akmar Mustafa

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The peak demand forecast is crucial to identify the future generation plant up needed in the long-term capacity planning analysis for Peninsular Malaysia as well as for the transmission and distribution network planning activities. Currently, peak demand forecast (in Mega Watt) is derived from the generation forecast by using load factor assumption. However, a forecast using this method has underperformed due to the structural changes in the economy, emerging trends and weather uncertainty. The dynamic changes of these drivers will result in many possible outcomes of peak demand for Peninsular Malaysia. This paper will look into the independent model of peak demand forecasting. The model begins with the selection of driver variables to capture long-term growth. This selection and construction of variables, which include econometric, emerging trend and energy variables, will have an impact on the peak forecast. The actual framework begins with the development of system energy and load shape forecast by using the system’s hourly data. The shape forecast represents the system shape assuming all embedded technology and use patterns to continue in the future. This is necessary to identify the movements in the peak hour or changes in the system load factor. The next step would be developing the peak forecast, which involves an iterative process to explore model structures and variables. The final step is combining the system energy, shape, and peak forecasts into the hourly system forecast then modifying it with the forecast adjustments. Forecast adjustments are among other sales forecasts for electric vehicles, solar and other adjustments. The framework will result in an hourly forecast that captures growth, peak usage and new technologies. The advantage of this approach as compared to the current methodology is that the peaks capture new technology impacts that change the load shape.

Keywords: hourly load profile, load forecasting, long term peak demand forecasting, peak demand

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Authors: V. Thomas, O. Delaune, W. Hennig, S. Hoover

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Measurement of radioactive isotopes of atmospheric xenon is used to detect, locate and identify any confined nuclear tests as part of the Comprehensive Nuclear Test-Ban Treaty (CTBT). In this context, the Alternative Energies and French Atomic Energy Commission (CEA) has developed a fixed device to continuously measure the concentration of these fission products, the SPALAX process. During its atmospheric transport, the radioactive xenon will undergo a significant dilution between the source point and the measurement station. Regarding the distance between fixed stations located all over the globe, the typical volume activities measured are near 1 mBq m⁻³. To avoid the constraints induced by atmospheric dilution, the development of a mobile detection system is in progress; this system will allow on-site measurements in order to confirm or infringe a suspicious measurement detected by a fixed station. Furthermore, this system will use beta/gamma coincidence measurement technique in order to drastically reduce environmental background (which masks such activities). The detector prototype consists of a gas cell surrounded by two large silicon wafers, coupled with two square NaI(Tl) detectors. The gas cell has a sample volume of 30 cm³ and the silicon wafers are 500 µm thick with an active surface area of 3600 mm². In order to minimize leakage current, each wafer has been segmented into four independent silicon pixels. This cell is sandwiched between two low background NaI(Tl) detectors (70x70x40 mm³ crystal). The expected Minimal Detectable Concentration (MDC) for each radio-xenon is in the order of 1-10 mBq m⁻³. Three 4-channels digital acquisition modules (Pixie-NET) are used to process all the signals. Time synchronization is ensured by a dedicated PTP-network, using the IEEE 1588 Precision Time Protocol. We would like to present this system from its simulation to the laboratory tests.

Keywords: beta/gamma coincidence technique, low level measurement, radioxenon, silicon pixels

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Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

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Authors: F. Moghtaderi, M. Burke, J. Troelsen

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There has been a significant decline in active travel as well as the massive increase use of car-dependent travel mode in many countries during past two decades. Evidential risks for people’s physical and mental health problems are followed by this increased use of motorized travel mode. These problems range from overweight and obesity to increasing air pollution. In response to these rising concerns, local councils and other interested organizations around the world have introduced a variety of initiatives regarding reduce the dominance of cars for the daily journeys. However, the nature of these kinds of interventions, which related to the human behavior, make lots of complexities. People’s travel behavior and changing this behavior, has two different aspects. People’s attitudes and perceptions toward the sustainable and healthy modes of travel, and motorized travel modes (especially private car use) is one these two aspects. The other one related to people’s behavior change processes. There are no comprehensive model in order to guide policy interventions to increase the level of succeed of such interventions. A comprehensive theoretical framework is required in accordance to facilitate and guide the processes of data collection and analysis to achieve the best possible guidelines for policy makers. Regarding this gaps in the travel behavior change research, this paper attempted to identify and suggest a multidimensional framework in order to facilitate planning interventions. A structured mixed-method is suggested regarding the expand the scope and improve the analytic power of the result according to the complexity of human behavior. In order to recognize people’s attitudes, a theory with the focus on people’s attitudes towards a particular travel behavior was needed. The literature around the theory of planned behavior (TPB) was the most useful, and had been proven to be a good predictor of behavior change. Another aspect of the research, related to the people’s decision-making process regarding explore guidelines for the further interventions. Therefore, a theory was needed to facilitate and direct the interventions’ design. The concept of the transtheoretical model of behavior change (TTM) was used regarding reach a set of useful guidelines for the further interventions with the aim to increase active travel and sustainable modes of travel. Consequently, a combination of these two theories (TTM and TPB) had presented as an appropriate concept to identify and design implemented travel behavior change interventions.

Keywords: behavior change theories, theoretical framework, travel behavior change interventions, urban research

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Authors: Sultan Ahmad Azizi, Gaurang J. Joshi

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Urban transportation has come to lime light in recent times due to deteriorating travel quality. The economic growth of India has boosted significant rise in private vehicle ownership in cities, whereas public transport systems have largely been ignored in metropolitan cities. Even though there is latent demand for public transport systems like organized bus services, most of the metropolitan cities have unsustainably low share of public transport. Unfortunately, Indian metropolitan cities have failed to maintain balance in mode share of various travel modes in absence of timely introduction of mass transit system of required capacity and quality. As a result, personalized travel modes like two wheelers have become principal modes of travel, which cause significant environmental, safety and health hazard to the citizens. Of late, the policy makers have realized the need to improve public transport system in metro cities for sustaining the development. However, the challenge to the transit planning authorities is to design a transit system for cities that may attract people to switch over from their existing and rather convenient mode of travel to the transit system under the influence of household socio-economic characteristics and the given travel pattern. In this context, the fast-growing industrial city of Surat is taken up as a case for the study of likely shift to bus transit. Deterioration of public transport system of bus after 1998, has led to tremendous growth in two-wheeler traffic on city roads. The inadequate and poor service quality of present bus transit has failed to attract the riders and correct the mode use balance in the city. The disaggregate travel behavior for trip generations and the travel mode choice has been studied for the West Adajan residential sector of city. Mode specific utility functions are calibrated under multi-nominal logit environment for two-wheeler, cars and auto rickshaws with respect to bus transit using SPSS. Estimation of shift to bus transit is carried indicate an average 30% of auto rickshaw users and nearly 5% of 2W users are likely to shift to bus transit if service quality is improved. However, car users are not expected to shift to bus transit system.

Keywords: bus transit, disaggregate travel nehavior, mode choice Behavior, public transport

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Authors: Yongjun Kim

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Since the agreement on the historicity of historical Buddha in eastern India, the beginning, heyday and decline of Buddhism in Early India have been discussed in urbanization, commercialism and state formation context, in short, Weberian socio-politico frame. Recent Scholarship, notably in archaeology and anthropology, has proposed ‘re-materialization of Buddhism in Early India’ based on what Buddhist had actually done rather than what they should do according to canonical teachings or philosophies. But its historical narrations still remain with a domain of socio-politico meta-narrative which tends to unjustifiably dismiss the naturally existing heterogeneity and often chaotic dynamic of diverse agencies, landscape perceptions, localized traditions, etc. An author will argue the multiplicity of theoretical standpoints for the reconstruction on the Buddhism in Early India. For this, at first, the diverse agencies, localized traditions, landscape patterns of Buddhist communities and monasteries in Trans-Himalayan regions; focusing Zanskar Valley and Spiti Valley in India will be illustrated based on an author’s field work. And then an author will discuss this anthropological landscape analysis is better appropriated with textual and archaeological evidences on the tension between urban monastic and forest Buddhism, the phenomena of sacred landscape, cemetery, garden, natural cave along with socio-economic landscape, the demographic heterogeneity in Early India. Finally, it will be attempted to compare between anthropological landscape of present Trans-Himalayan and archaeological one of ancient Western India. The study of Buddhism in Early India has hardly been discussed through multivalent theoretical archaeology and anthropology of religion, thus traditional and recent scholarship have produced historical meta-narrative though heterogeneous among them. The multidisciplinary approaches of textual critics, archaeology and anthropology will surely help to deconstruct the grand and all-encompassing historical description on Buddhism in Early India and then to reconstruct the localized, behavioral and multivalent narratives. This paper expects to highlight the importance of lesser-studied Buddhist archaeological sites and the dynamic views on religious landscape in Early India with a help of critical anthropology of religion.

Keywords: analogy by living traditions, Buddhism in Early India, landscape analysis, meta-narrative

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Authors: Beryl Rene R. Lopez, Lesley Anne M. Lipat, Rhogene Barbette C. Lirio, Laurice Joy H. Llanes, Karl Philippe M. Llapitan, Einstein James R. Lopez, Socorro S. GuanHing

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Background: Measles remain as one of the most common childhood diseases despite the availability of the vaccine that is safe and cost-effective. Because of morbidity and mortality associated with the recent measles outbreak in the Philippines, there is an increasing concern from the health care professionals. Objective: The purpose of this study is to determine the relationship between the compliance of Filipino mothers to measles vaccination and their health beliefs when grouped according to the given socio-demographic factors using a researcher-made questionnaire. Research Methodology: This research utilized the descriptive-correlational research design. With the use of purposive sampling technique, the study involved 200 Filipino mothers aged 18 years old and above excluding those who are healthcare professionals with children aged 2-3 years old with either urban or rural as their settlements. Pre-testing was done prior to the actual data gathering. A questionnaire composed of 26 items involving socio-demographic, compliance, and health beliefs was distributed to the sample population. Statistical analysis was done with the use of Exploratory Factor Analysis (EFA) for the first research question and Structural Equation Model (SEM) for the second research question. Results: Four dimensions were generated with the use of EFA namely: Vulnerability-Oriented Beliefs (VOB), Knowledge-Oriented Beliefs (KOB), Accessibility-Oriented Beliefs (AOB), and Outcomes-Oriented Beliefs (OOB). These were then correlated with the mothers’ socio-demographic factors (age, educational attainment, the area of residence, the number of children, and family income) and their compliance to the measles vaccination schedule. Results showed significant and direct relationships between area of residence and compliance, family income and compliance, KOB and compliance, education and KOB, KOB and VOB, KOB and OOB, AOB and KOB, AOB and OOB, AOB and VOB, and lastly, OOB and VOB. Conclusion: The Knowledge – Oriented Belief dimension greatly influence compliance to measles vaccination. Other determinants of compliance like the area of residence, educational attainment, and family income significantly increase the Filipino mothers’ likelihood of compliance to measles vaccination, which have implications to health education.

Keywords: socio-demographic, health beliefs, compliance, measles vaccination

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Authors: M. Ntšolo, D. Kalumba, N. Lefu, G. Letlatsa

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Rock mass damage due to shear tectonic activity has been investigated largely in geoscience where fluid transport is of major interest. However, little has been studied on the effect of shear zones on rock mass behavior and its impact on stability of rock slopes. At Letšeng Diamonds open pit mine in Lesotho, the shear zone composed of sheared kimberlite material, calcite and altered basalt is forming part of the haul ramp into the main pit cut 3. The alarming rate at which the shear zone is deteriorating has triggered concerns about both local and global stability of pit the walls. This study presents the numerical modelling of the open pit slope affected by shear zone at Letšeng Diamond Mine (LDM). Analysis of the slope involved development of the slope model by using a two-dimensional finite element code RS2. Interfaces between shear zone and host rock were represented by special joint elements incorporated in the finite element code. The analysis of structural geological mapping data provided a good platform to understand the joint network. Major joints including shear zone were incorporated into the model for simulation. This approach proved successful by demonstrating that continuum modelling can be used to evaluate evolution of stresses, strain, plastic yielding and failure mechanisms that are consistent with field observations. Structural control due to geological shear zone structure proved to be important in its location, size and orientation. Furthermore, the model analyzed slope deformation and sliding possibility along shear zone interfaces. This type of approach can predict shear zone deformation and failure mechanism, hence mitigation strategies can be deployed for safety of human lives and property within mine pits.

Keywords: numerical modeling, open pit mine, shear zone, slope stability

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Authors: Betül Ersoy, Deniz Özalp Kizilay, Gül Gümüşer, Fatma Taneli

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Introduction: Peak bone mass is reached in late adolescence in females. Age at menarche influences estrogen exposure, which plays a vital role in bone metabolism. The relationship between age at menarche and bone mineral density (BMD) is still controversial. In this study, we investigated the relationship between age at menarche, BMD, socioeconomic status (SES) and body composition in female university student. Participant and methods: A total of 138 healthy girls at late adolescence period (mean age 20.13±0.93 years, range 18-22) were included in this university school-based cross-sectional study in the urban area western region of Turkey. Participants have been randomly selected to reflect the university students studying in all faculties. We asked relevant questions about socioeconomic status and age at menarche to female university students. Students were grouped into three SES as lower, middle and higher according to the educational and occupational levels of their parents using Hollingshead index. Height and weight were measured. Body Mass Index (BMI) (kg/m2 ) was calculated. Dual energy X-ray absorptiometry (DXA) was performed using the Lunar DPX series, and BMD and body composition were evaluated. Results: The mean age of menarche of female university student included in the study was 13.09.±1.3 years. There was no significant difference between the three socioeconomic groups in terms of height, body weight, age at menarche, BMD [BMD (gr/cm2 ) (L2-L4) and BMD (gr/cm2 ) (total body)], and body composition (lean tissue, fat tissue, total fat, and body fat) (p>0.05). While no correlation was found between the age at menarche and any parameter (p>0.05), a positive significant correlation was found between lean tissue and BMD L2-L4 (r=0.286, p=0.01). When the relationships were evaluated separately according to socioeconomic status, there was a significant correlation between BMDL2-L4 (r: 0.431, p=0.005) and lean tissue in females with low SES, while this relationship disappeared in females with middle and high SES. Conclusion: Age at menarche did not change according to socioeconomic status, nor did BMD and body composition in female at late adolescents. No relationship was found between age at menarche and BMD and body composition determined by DEXA in female university student who were close to reaching peak bone mass. The results suggested that especially BMDL2-L4 might increase as lean tissue increases.

Keywords: bone, osteoposis, menarche, dexa

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Authors: Win Zaw Hein, Khin Sandar Linn, Su Su Yi Mon, Yoshitaka Goto

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The Earth ionosphere is located at the altitude of about 70 km to several 100 km from the ground, and it is composed of ions and electrons called plasma. In the ionosphere, these plasma makes delay in GPS (Global Positioning System) signals and reflect in radio waves. The delay along the signal path from the satellite to the receiver is directly proportional to the total electron content (TEC) of plasma, and this delay is the largest error factor in satellite positioning and navigation. Sounding observation from the top and bottom of the ionosphere was popular to investigate such ionospheric plasma for a long time. Recently, continuous monitoring of the TEC using networks of GNSS (Global Navigation Satellite System) observation stations, which are basically built for land survey, has been conducted in several countries. However, in these stations, multi-frequency support receivers are installed to estimate the effect of plasma delay using their frequency dependence and the cost of multi-frequency support receivers are much higher than single frequency support GPS receiver. In this research, single frequency GPS receiver was used instead of expensive multi-frequency GNSS receivers to measure the ionospheric plasma variation such as vertical TEC distribution. In this measurement, single-frequency support ublox GPS receiver was used to probe ionospheric TEC. The location of observation was assigned at Mandalay Technological University in Myanmar. In the method, the ionospheric TEC distribution is represented by polynomial functions for latitude and longitude, and parameters of the functions are determined by least-squares fitting on pseudorange data obtained at a known location under an assumption of thin layer ionosphere. The validity of the method was evaluated by measurements obtained by the Japanese GNSS observation network called GEONET. The performance of measurement results using single-frequency of GPS receiver was compared with the results by dual-frequency measurement.

Keywords: ionosphere, global positioning system, GPS, ionospheric delay, total electron content, TEC

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Authors: Nikica Mihaljević

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Published in 2023, "Tre ciotole. Rituali per un anno di crisi" is a collection of short stories completely disconnected from one another in regard to topics and the representation of characters. However, these short stories complete and somehow continue each other in a particular way. The book happens to be Murgia's last book, as the author died a few months later after the book's publication and it appears as a kind of summary of all her previous literary works. Namely, in her previous publications, Murgia already stressed certain characters' particularities, such as solitude and alienation from others, which are at the center of attention in this literary work, too. What all the stories present in "Tre ciotole" have in common is the dealing with characters' identity and self-awareness through the challenges they confront and the way the characters live their emotions in relation to the surrounding space. Although the challenges seem similar, the spatial element around the characters is different, but it confirms each time that characters' emotions, and, consequently, their self-awareness, can be formed and built only through their connection and relation to the surrounding space. In that way, the reader creates an imaginary network of complex relations among characters in all the short stories, which gives him/her the opportunity to search for a way to break out of the usual patterns that tend to be repeated while characters focus on building self-awareness. The aim of the paper is to determine and analyze the role of spatial elements in the creation of characters' emotions and in the process of self-awareness. As the spatial element changes or gets transformed and/or substituted, in the same way, we notice the arise of the unconscious desire for self-harm in the characters, which damages their self-awareness. Namely, the characters face a crisis that they cannot control by inventing other types of crises that can be controlled. That happens to be their way of acting in order to find the way out of the identity crisis. Consequently, we expect that the results of the analysis point out the similarities in the short stories in characters' depiction as well as to show the extent to which the characters' identities depend on the surrounding space in each short story. In this way, the results will highlight the importance of spatial elements in characters' identity formation in Michela Murgia's short stories and also summarize the importance of the whole Murgia's literary opus.

Keywords: Italian literature, short stories, environment, spatial element, emotions, characters

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Authors: Sameer A. Pathan, Biswadev Mitra, Salman Mirza, Umais Momin, Zahoor Ahmed, Lubna G. Andraous, Dharmesh Shukla, Mohammed Y. Shariff, Magid M. Makki, Tinsy T. George, Saad S. Khan, Stephen H. Thomas, Peter A. Cameron

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Study objective: Emergency physician’s (EP) ability to identify hydronephrosis on point-of-care ultrasound (POCUS) has been assessed in the past using CT scan as the reference standard. We aimed to assess EP interpretation of POCUS to identify and grade the hydronephrosis in a direct comparison with the consensus-interpretation of POCUS by radiologists, and also to compare the EP and radiologist performance using CT scan as the criterion standard. Methods: Using data from a POCUS databank, a prospective interpretation study was conducted at an urban academic emergency department. All POCUS exams were performed on patients presenting with renal colic to the ED. Institutional approval was obtained for conducting this study. All the analyses were performed using Stata MP 14.0 (Stata Corp, College Station, Texas). Results: A total of 651 patients were included, with paired sets of renal POCUS video clips and the CT scan performed at the same ED visit. Hydronephrosis was reported in 69.6% of POCUS exams by radiologists and 72.7% of CT scans (p=0.22). The κ for consensus interpretation of POCUS between the radiologists to detect hydronephrosis was 0.77 (0.72 to 0.82) and weighted κ for grading the hydronephrosis was 0.82 (0.72 to 0.90), interpreted as good to very good. Using CT scan findings as the criterion standard, Eps had an overall sensitivity of 81.1% (95% CI: 79.6% to 82.5%), specificity of 59.4% (95% CI: 56.4% to 62.5%), PPV of 84.3% (95% CI: 82.9% to 85.7%), and NPV of 53.8% (95% CI: 50.8% to 56.7%); compared to radiologist sensitivity of 85.0% (95% CI: 82.5% to 87.2%), specificity of 79.7% (95% CI: 75.1% to 83.7%), PPV of 91.8% (95% CI: 89.8% to 93.5%), and NPV of 66.5% (95% CI: 61.8% to 71.0%). Testing for a report of moderate or high degree of hydronephrosis, specificity of EP was 94.6% (95% CI: 93.7% to 95.4%) and to 99.2% (95% CI: 98.9% to 99.5%) for identifying severe hydronephrosis alone. Conclusion: EP POCUS interpretations were comparable to the radiologists for identifying moderate to severe hydronephrosis using CT scan results as the criterion standard. Among patients with moderate or high pre-test probability of ureteric calculi, as calculated by the STONE-score, the presence of moderate to severe (+LR 6.3 and –LR 0.69) or severe hydronephrosis (+LR 54.4 and –LR 0.57) was highly diagnostic of the stone disease. Low dose CT is indicated in such patients for evaluation of stone size and location.

Keywords: renal colic, point-of-care, ultrasound, bedside, emergency physician

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Authors: Divyani Redhu, Manisha Rathaur

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India has emerged as a very lucrative market for the smartphones in a very short span of time. The number of smartphone users here is growing massively with each passing day. Also, the expansion of internet services to far corners of the nation has also given a push to the smartphone revolution in India. Millennial, also known as Generation Y or the Net Generation is the generation born between the early 1980s and mid-1990s (some definitions extending further to early 2000s). Spanning roughly over 15 years, different social classes, cultures, and continents; it is irrational to imagine that millennial have a unified identity. But still, it cannot be denied that the growing millennial population is not only young but is highly tech-savvy too. It is not just the appearance of the device that today; we call it ‘smart’. Rather, it is the numerous tasks and functions that it can perform which has led its name to evolve as that of a ‘smartphone’. From usual tasks that were earlier performed by a simple mobile phone like making calls, sending messages, clicking photographs, recording videos etc.; today, the time has come where most of our day – to – day tasks are being taken care of by our all-time companion, i.e. smartphones. From being our alarm clock to being our note-maker, from our watch to our radio, our book-reader to our reminder, smartphones are present everywhere. Smartphone has now become an essential device for particularly the millennial to communicate not only with their friends but also with their family, colleagues, and teachers. The study by the researchers would be quantitative in nature. For the same, a survey would be conducted in particularly the capital of India, i.e. Delhi and the National Capital Region (NCR), which is the metropolitan area covering the entire National Capital Territory of Delhi and urban areas covering states of Haryana, Uttarakhand, Uttar Pradesh and Rajasthan. The tool of the survey would be a questionnaire and the number of respondents would be 200. The results derived from the study would primarily focus on the increasing reach of smartphones in India, smartphones as technological innovation and convergent tools, smartphone usage pattern of millennial in India, most used applications by the millennial, the average time spent by them, the impact of smartphones on the personal interactions of millennial etc. Thus, talking about the smartphone technology and the millennial in India, it would not be wrong to say that the growth, as well as the potential of the smartphones in India, is still immense. Also, very few technologies have made it possible to give a global exposure to the users and smartphone, if not the only one is certainly an immensely effective one that comes to the mind in this case.

Keywords: Delhi – NCR, India, millennial, smartphone

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Authors: Susanne Gustafsson

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Life-history research is an extraordinarily fruitful method to use for social analysis and gendered health analysis in particular. Its potential is illustrated through a case study drawn from a Swedish project. It reveals an old type of masculinity that faces difficulties when carrying out two sets of demands simultaneously, as a worker/manager and as a father/husband. The paper illuminates the historical transformation of masculinity and the consequences of this for health. We draw on the idea of the “changing faces of masculinity” to explore the dynamism and complexity of gendered health. An empirical case is used for its illustrative abilities. Jan, a middle-level manager and father employed in the energy sector in urban Sweden is the subject of this paper. Jan’s story is one of 32 semi-structured interviews included in an extended study focusing on well-being at work. The results reveal a face of masculinity conceived of in middle-level management as tacitly linked to the neoliberal doctrine. Over a couple of decades, the idea of “flexibility” was turned into a valuable characteristic that everyone was supposed to strive for. This resulted in increased workloads. Quite a few employees, and managers, in particular, find themselves working both day and night. This may explain why not having enough time to spend with children and family members is a recurring theme in the data. Can this way of doing be linked to masculinity and health? The first author’s research has revealed that the use of gender in health science is not sufficiently or critically questioned. This lack of critical questioning is a serious problem, especially since ways of doing gender affect health. We suggest that gender reproduction and gender transformation are interconnected, regardless of how they affect health. They are recognized as two sides of the same phenomenon, and minor movements in one direction or the other become crucial for understanding its relation to health. More or less, at the same time, as Jan’s masculinity was reproduced in response to workplace practices, Jan’s family position was transformed—not totally but by a degree or two, and these degrees became significant for the family’s health and well-being. By moving back and forth between varied events in Jan’s biographical history and his sociohistorical life span, it becomes possible to show that in a time of gender transformations, power relations can be renegotiated, leading to consequences for health.

Keywords: changing faces of masculinity, gendered health, life-history research method, subverter

Procedia PDF Downloads 113

Authors: Mapatsakon Sarapat, Mongkol Ketwongsa, Somchat Sonasang, Preecha Yupapin

Abstract:

The designed and performed preliminary tests on a space-time control circuit using a two-level system circuit with a 4-5 cm diameter microstrip for realistic teleportation have been demonstrated. It begins by calculating the parameters that allow a circuit that uses the alternative current (AC) at a specified frequency as the input signal. A method that causes electrons to move along the circuit perimeter starting at the speed of light, which found satisfaction based on the wave-particle duality. It is able to establish the supersonic speed (faster than light) for the electron cloud in the middle of the circuit, creating a timeline and propulsive force as well. The timeline is formed by the stretching and shrinking time cancellation in the relativistic regime, in which the absolute time has vanished. In fact, both black holes and white holes are created from time signals at the beginning, where the speed of electrons travels close to the speed of light. They entangle together like a capsule until they reach the point where they collapse and cancel each other out, which is controlled by the frequency of the circuit. Therefore, we can apply this method to large-scale circuits such as potassium, from which the same method can be applied to form the system to teleport living things. In fact, the black hole is a hibernation system environment that allows living things to live and travel to the destination of teleportation, which can be controlled from position and time relative to the speed of light. When the capsule reaches its destination, it increases the frequency of the black holes and white holes canceling each other out to a balanced environment. Therefore, life can safely teleport to the destination. Therefore, there must be the same system at the origin and destination, which could be a network. Moreover, it can also be applied to space travel as well. The design system will be tested on a small system using a microstrip circuit system that we can create in the laboratory on a limited budget that can be used in both wired and wireless systems.

Keywords: quantum teleportation, black-white hole, time, timeline, relativistic electronics

Procedia PDF Downloads 75

Authors: Vaibhav Rathi, Soumen Maity, Achu R. Sekhar, Abhijit Banerjee

Abstract:

Construction sector in India is extremely resource and carbon intensive. It contributes to significantly to national greenhouse emissions. At the resource end the industry consumes significant portions of the output from mining. Resources such as sand and soil are most exploited and their rampant extraction is becoming constant source of impact on environment and society. Cement is another resource that is used in abundance in building and construction and has a direct impact on limestone resources. Though India is rich in cement grade limestone resource, efforts have to be made for sustainable consumption of this resource to ensure future availability. Use of these resources in high volumes in India is a result of rapid urbanization. More cities have grown to a population of million plus in the last decade and million plus cities are growing further. To cater to needs of growing urban population of construction activities are inevitable in the coming future thereby increasing material consumption. Increased construction will also lead to substantial increase in end of life waste generation from Construction and Demolition (C&D). Therefore proper management of C&D waste has the potential to reduce environmental pollution as well as contribute to the resource efficiency in the construction sector. The present study deals with estimation, characterisation and documenting current management practices of C&D waste in 10 Indian cities of different geographies and classes. Based on primary data the study draws conclusions on the potential of C&D waste to be used as an alternative to primary raw materials. The estimation results show that India generates 716 million tons of C&D waste annually, placing the country as second largest C&D waste generator in the world after China. The study also aimed at utilization of C&D waste in to building materials. The waste samples collected from various cities have been used to replace 100% stone aggregates in paver blocks without any decrease in strength. However, management practices of C&D waste in cities still remains poor instead of notification of rules and regulations notified for C&D waste management. Only a few cities have managed to install processing plant and set up management systems for C&D waste. Therefore there is immense opportunity for management and reuse of C&D waste in Indian cities.

Keywords: building materials, construction and demolition waste, cities, environmental pollution, resource efficiency

Procedia PDF Downloads 304

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 127

Authors: T. Jayanthi, K. Velusamy, H. Seetha, S. A. V. Satya Murty

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Verification and Validation of Simulated Process Model is the most important phase of the simulator life cycle. Evaluation of simulated process models based on Verification and Validation techniques checks the closeness of each component model (in a simulated network) with the real system/process with respect to dynamic behaviour under steady state and transient conditions. The process of Verification and validation helps in qualifying the process simulator for the intended purpose whether it is for providing comprehensive training or design verification. In general, model verification is carried out by comparison of simulated component characteristics with the original requirement to ensure that each step in the model development process completely incorporates all the design requirements. Validation testing is performed by comparing the simulated process parameters to the actual plant process parameters either in standalone mode or integrated mode. A Full Scope Replica Operator Training Simulator for PFBR - Prototype Fast Breeder Reactor has been developed at IGCAR, Kalpakkam, INDIA named KALBR-SIM (Kalpakkam Breeder Reactor Simulator) wherein the main participants are engineers/experts belonging to Modeling Team, Process Design and Instrumentation and Control design team. This paper discusses the Verification and Validation process in general, the evaluation procedure adopted for PFBR operator training Simulator, the methodology followed for verifying the models, the reference documents and standards used etc. It details out the importance of internal validation by design experts, subsequent validation by external agency consisting of experts from various fields, model improvement by tuning based on expert’s comments, final qualification of the simulator for the intended purpose and the difficulties faced while co-coordinating various activities.

Keywords: Verification and Validation (V&V), Prototype Fast Breeder Reactor (PFBR), Kalpakkam Breeder Reactor Simulator (KALBR-SIM), steady state, transient state

Procedia PDF Downloads 266

Authors: Parisa Afshin, Terje Grønning

Abstract:

Norway, similar to many other countries, has set the focus of its policies in creating new strong and highly innovative sectors in recent years, as the oil and gas sector profitability is declining. Biotechnology sector in Norway has a great potential, especially in marine-biotech and cancer medicine. However, Norway being a periphery faces especial challenges in the path of creating internationally well-known biotech sector and an international knowledge hub. The aim of this article is to analyze the progress of the Norwegian biotechnology industry, its pathway to build up an innovation network and conduct collaborative innovation based on its initial conditions and its own advantage and disadvantages. The findings have important implications not only for politicians and academic in understanding the infrastructure of biotechnology sector in the country, but it has important lessons for other periphery countries or regions aiming in creating strong biotechnology sector and catching up with the strong internationally-recognized regions. Data and methodology: To achieve the main goal of this study, information has been collected via secondary resources such as web pages and annual reports published by the officials and mass media along with interviews were used. The data were collected with the goal to shed light on a brief history and current status of Norway biotechnology sector, as well as geographic distribution of biotech industry, followed by the role of academic and industry collaboration and public policies in Norway biotech. As knowledge is the key input in innovation, knowledge perspective of the system such as knowledge flow in the sector regarding the national and regional innovation system has been studied. Primary results: The internationalization has been an important element in development of periphery regions' innovativeness enabling them to overcome their weakness while putting more weight on the importance of regional policies. Following such findings, suggestions on policy decision and international collaboration, regarding national and regional system of innovation, has been offered as means of promoting strong innovative sector.

Keywords: biotechnology sector, knowledge-based industry, national innovation system, regional innovation system

Procedia PDF Downloads 225

Authors: Mariia Khramova, Sergio Martinez, Duc Nguyen

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Modern electronic devices, particularly smartphones, are characterised by extremely high environmental footprint and short product lifecycle. Every year manufacturers release new models with even more superior performance, which pushes the customers towards new purchases. As a result, millions of devices are being accumulated in the urban mine. To tackle these challenges the concept of circular economy has been introduced to promote repair, reuse and recycle of electronics. In this case, electronic devices, that previously ended up in landfills or households, are getting the second life, therefore, reducing the demand for new raw materials. Smartphone reuse is gradually gaining wider adoption partly due to the price increase of flagship models, consequently, boosting circular economy implementation. However, along with reuse of communication device, circular economy approach needs to ensure the data of the previous user have not been 'reused' together with a device. This is especially important since modern smartphones are comparable with computers in terms of performance and amount of data stored. These data vary from pictures, videos, call logs to social security numbers, passport and credit card details, from personal information to corporate confidential data. To assess how well the data privacy requirements are followed on smartphones second-hand market, a sample of 100 Android smartphones has been purchased from IT Asset Disposition (ITAD) facilities responsible for data erasure and resell. Although devices should not have stored any user data by the time they leave ITAD, it has been possible to retrieve the data from 19% of the sample. Applied techniques varied from manual device inspection to sophisticated equipment and tools. These findings indicate significant barrier in implementation of circular economy and a limitation of smartphone reuse. Therefore, in order to motivate the users to donate or sell their old devices and make electronic use more sustainable, data privacy on second-hand smartphone market should be significantly improved. Presented research has been carried out in the framework of sustainablySMART project, which is part of Horizon 2020 EU Framework Programme for Research and Innovation.

Keywords: android, circular economy, data privacy, second-hand phones

Procedia PDF Downloads 128

Authors: Sameer Masood, Lucas Chartier

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Head injuries are a commonly encountered presentation in emergency departments (ED) and the Choosing Wisely Canada (CWC) campaign was released in June 2015 in an attempt to decrease imaging utilization for patients with minor head injuries. The impact of the CWC campaign on imaging utilization for head injuries has not been explored in the ED setting. In our study, we describe the characteristics of patients with head injuries presenting to a tertiary care academic ED and the impact of the CWC campaign on CT head utilization. This retrospective cohort study used linked databases from the province of Ontario, Canada to assess emergency department visits with a primary diagnosis of head injury made between June 1, 2014 and Aug 31, 2016 at the University Health Network in Toronto, Canada. We examined the number of visits during the study period, the proportion of patients that had a CT head performed before and after the release of the CWC campaign, as well as mode of arrival, and disposition. There were 4,322 qualifying visits at our site during the study period. The median presenting age was 44.12 years (IQR 27.83,67.45), the median GCS was 15 (IQR 15,15) and the majority of patients presenting had intermediate acuity (CTAS 3). Overall, 43.17% of patients arrived via ambulance, 49.24 % of patients received a CT head and 10.46% of patients were admitted. Compared to patients presenting before the CWC campaign release, there was no significant difference in the rate of CT heads after the CWC (50.41% vs 47.68%, P = 0.07). There were also no significant differences between the two groups in mode of arrival (ambulance vs ambulatory) (42.94% vs 43.48%, P = 0.72) or admission rates (9.85% vs 11.26%, P = 0.15). However, more patients belonged to the high acuity groups (CTAS 1 or 2) in the post CWC campaign release group (12.98% vs 8.11% P <0.001). Visits for head injuries make up a significant proportion of total ED visits and approximately half of these patients receive CT imaging in the ED. The CWC campaign did not seem to impact imaging utilization for head injuries in the 14 months following its launch. Further efforts, including local quality improvement initiatives, are likely needed to increase adherence to its recommendation and reduce imaging utilization for head injuries.

Keywords: choosing wisely, emergency department, head injury, quality improvement

Procedia PDF Downloads 225

Authors: Oyatayo Kehinde Taofik, Ndabula Christopher

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Drainage basins are a central theme in the green economy. The rising challenges in flooding, erosion or sediment transport and sedimentation threaten the green economy. This has led to increasing emphasis on quantitative analysis of drainage basin parameters for better understanding, estimation and prediction of fluvial responses and, thus associated hazards or disasters. This can be achieved through direct measurement, characterization, parameterization, or modeling. This study applied the Remote Sensing and Geographic Information System approach of parameterization and characterization of the morphometric variables of Katsina – Ala basin using a 30 m resolution Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM). This was complemented with topographic and hydrological maps of Katsina-Ala on a scale of 1:50,000. Linear, areal and relief parameters were characterized. The result of the study shows that Ala and Udene sub-watersheds are 4th and 5th order basins, respectively. The stream network shows a dendritic pattern, indicating homogeneity in texture and a lack of structural control in the study area. Ala and Udene sub-watersheds have the following values for elongation ratio, circularity ratio, form factor and relief ratio: 0.48 / 0.39 / 0.35/ 9.97 and 0.40 / 0.35 / 0.32 / 6.0. They also have the following values for drainage texture and ruggedness index of 0.86 / 0.011 and 1.57 / 0.016. The study concludes that the two sub-watersheds are elongated, suggesting that they are susceptible to erosion and, thus higher sediment load in the river channels, which will dispose the watersheds to higher flood peaks. The study also concludes that the sub-watersheds have a very coarse texture, with good permeability of subsurface materials and infiltration capacity, which significantly recharge the groundwater. The study recommends that efforts should be put in place by the Local and State Governments to reduce the size of paved surfaces in these sub-watersheds by implementing a robust agroforestry program at the grass root level.

Keywords: erosion, flood, mitigation, morphometry, watershed

Procedia PDF Downloads 87

Authors: Sakineh Nouri Saeidlou, Fatemeh Rezaiegoyjeloo, Parvin Ayremlou, Fariba Babaie

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Introduction: Childhood overweight and obesity is a major public health problem in both developed and developing countries. Overweight and obesity in children may have severe consequences later in adolescence and adulthood. The aim of current study was to determine the prevalence trend of overweight and obesity in school-aged children from 2009 to 2011. Methods: The present study was a population-based study and conducted in three consecutive years, from 2009 to 2011. The study population included all of primary, secondary and high school children in rural and urban regions of West Azarbijan province in West-North of Iran. Body mass index (BMI), the ratio of weight to height squared [weight (kg)]/ [height (m)]2, was calculated to the nearest decimal place. Overweight and obesity were classified using CDC recommendations for age and sex: a BMI 85th–95th percentile was classified as overweight and a BMI>95th percentile was classified as obese. All statistical analyses were performed using the Excel Software. Descriptive statistics were used to characterize the sample in different time periods. The prevalence was calculated as the ratio of number present cases to a given population number in a given subgroup at a given time. Results: Overall, 165740, 145146 and 146203 school children were assessed at 2009, 2010 and 2011, respectively. Prevalence of overweight in primary school children among girls were 52.83, 86.93 and 116.36 and for boys were 57.07, 53.4 and 93.55 per 1000 person in 2009, 2010 and 2011 years ,respectively. The prevalence of obesity in secondary school children for girls were 22.26, 27.75 and 28.43 and 26.52, 25.72 and 35.85 for boys per 1000 person in 2009, 2010 and 2011, respectively, The highest prevalence of overweight was 77.58, 142.4 and 126.46 per 1000 person among primary, secondary and high school children, respectively, in 2011. The lowest prevalence of obesity was 12.52, 24.1 and 21.61 per 1000 person among primary, secondary and high school children, respectively, in 2009. Conclusion: However, the rapid increase in both obesity and overweight should have a special attention. Research on prevalence trend of overweight and obesity in children is poorly reported in Iran. So that, future studies need to follow-up on the associations between overweight and obesity with health outcomes when children develop and reach adolescence and adulthood.

Keywords: overweight, obesity, school children, prevalence trend, Iran

Procedia PDF Downloads 341

Authors: Gholba Niranjan Dilip, Anil Kumar

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Conduct of accurate reliable mapping of oil palm plantations and census of individual palm trees is a huge challenge. This study addresses this challenge and developed an optimized solution implemented deep learning techniques on remote sensing data. The oil palm is a very important tropical crop. To improve its productivity and land management, it is imperative to have accurate census over large areas. Since, manual census is costly and prone to approximations, a methodology for automated census using panchromatic images from Cartosat-2, SkySat and World View-3 satellites is demonstrated. It is selected two different study sites in Indonesia. The customized set of training data and ground-truth data are created for this study from Cartosat-2 images. The pre-trained model of Single Shot MultiBox Detector (SSD) Lite MobileNet V2 Convolutional Neural Network (CNN) from the TensorFlow Object Detection API is subjected to transfer learning on this customized dataset. The SSD model is able to generate the bounding boxes for each oil palm and also do the counting of palms with good accuracy on the panchromatic images. The detection yielded an F-Score of 83.16 % on seven different images. The detections are buffered and dissolved to generate polygons demarcating the boundaries of the oil palm plantations. This provided the area under the plantations and also gave maps of their location, thereby completing the automated census, with a fairly high accuracy (≈100%). The trained CNN was found competent enough to detect oil palm crowns from images obtained from multiple satellite sensors and of varying temporal vintage. It helped to estimate the increase in oil palm plantations from 2014 to 2021 in the study area. The study proved that high-resolution panchromatic satellite image can successfully be used to undertake census of oil palm plantations using CNNs.

Keywords: object detection, oil palm tree census, panchromatic images, single shot multibox detector

Procedia PDF Downloads 160

Authors: Muhammad Abid

Abstract:

The ultimate goal of this research was to produce a cold galvanizing compound (CGC) at reduced pigment volume concentration (PVC) to protect metallic structures from corrosion. The influence of the partial replacement of Zn dust by nano-layered graphene (NGr) and Zn metal nanoparticles on the electrochemical, morphological, rheological, and mechanical properties of CGC was investigated. EIS was used to explore the electrochemical nature of coatings. The EIS results revealed that the partial replacement of Zn by NGr and Zn nanoparticles enhanced the cathodic protection at reduced PVC (4:1) by improving the electrical contact between the Zn particles and the metal substrate. The Tafel scan was conducted to support the cathodic behaviour of the coatings. The sample formulated solely with Zn at PVC 4:1 was found to be dominated in physical barrier characteristics over cathodic protection. By increasing the concentration of NGr in the formulation, the corrosion potential shifted towards a more negative side. The coating with 1.5% NGr showed the highest galvanic action at reduced PVC. FE-SEM confirmed the interconnected network of conducting particles. The coating without NGr and Zn nanoparticles at PVC 4:1 showed significant gaps between the Zn dust particles. The novelty was evidenced when micrographs showed the consistent distribution of NGr and Zn nanoparticles all over the surface, which acted as a bridge between spherical Zn particles and provided cathodic protection at a reduced PVC. The layered structure of graphene also improved the physical shielding effect of the coatings, which limited the diffusion of electrolytes and corrosion products (oxides/hydroxides) into the coatings, which was reflected by the salt spray test. The rheological properties of coatings showed good liquid/fluid properties. All the coatings showed excellent adhesion but had different strength values. A real-time scratch resistance assessment showed all the coatings had good scratch resistance.

Keywords: protective coatings, anti-corrosion, galvanization, graphene, nanomaterials, polymers

Procedia PDF Downloads 96

Authors: M. S. Aparna, Pushparaj Shetty D.

Abstract:

Nowadays social networking sites have become so popular that the producers or the sellers look for these sites as one of the best options to target the right audience to market their products. There are several tools available to monitor or analyze the social networks. Our task is to identify the right community web pages and find out the behavior analysis of the members by using these tools and formulate an appropriate strategy to market the products or services to achieve the set goals. The advertising becomes more effective when the information of the product/ services come from a known source. The strategy explores great buying influence in the audience on referral marketing. Our methodology proceeds with critical budget analysis and promotes viral influence propagation. In this context, we encompass the vital bits of budget evaluation such as the number of optimal seed nodes or primary influential users activated onset, an estimate coverage spread of nodes and maximum influence propagating distance from an initial seed to an end node. Our proposal for Buyer Prediction mathematical model arises from the urge to perform complex analysis when the probability density estimates of reliable factors are not known or difficult to calculate. Order Statistics and Buyer Prediction mapping function guarantee the selection of optimal influential users at each level. We exercise an efficient tactics of practicing community pages and user behavior to determine the product enthusiasts on social networks. Our approach is promising and should be an elementary choice when there is little or no prior knowledge on the distribution of potential buyers on social networks. In this strategy, product news propagates to influential users on or surrounding networks. By applying the same technique, a user can search friends who are capable to advise better or give referrals, if a product interests him.

Keywords: viral marketing, social network analysis, community web pages, buyer prediction, influence propagation, budget constraints

Procedia PDF Downloads 262

Authors: Siti Napsiyah, Ismet Firdaus, Lisma Dyawati Fuaida, Ellies Sukmawati

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This paper examines the existence, role, and challenge of Family Service Agency, in Bahasa Indonesia known as Lembaga Konsultasi Kesejahteraan Keluarga (LK3) of Syarif Hidayatullah State Islamic University (UIN) Jakarta. It has been established since 2012. It is an official agency under the Ministry of Social Affairs of Indonesia. The establishment of LK3 aims to provide psychosocial services for families of students who has psychosocial problem in their life. The study also aims to explore the trend of psychosocial problems of its client (student) for the past three years (2014-2016). The research method of the study is using a qualitative social work research method. A review of selected data of the client of LK3 UIN Syarif Hidayatullah Jakarta around five main issues: Family background, psychosocial mapping, potential resources, student coping mechanism strategy, client strength and network. The study also uses a review of academic performance report as well as an interview and observation. The findings show that the trend of psychosocial problems of the client of LK3 UIN Syarif Hidayatullah Jakarta vary as follow: bad academic performance, low income family, broken home, domestic violence, disability, mental disorder, sexual abuse, and the like. LK3 UIN Syarif Hidayatullah Jakarta has significant roles to provide psychosocial support and services for the survival of the students to deal with their psychosocial problems. Social worker of LK3 performs indigenous social work practice: individual counseling, family counseling, group therapy, home visit, case conference, Islamic Spiritual Approach, and Spiritual Emotional Freedom Technique (SEPT).

Keywords: psychosocial, indigenizing social work, resiliency, coping mechanism

Procedia PDF Downloads 262