Search results for: urban network space

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: 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: 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

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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

Procedia PDF Downloads 127

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

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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

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Authors: Guenther Schuh, Michael Riesener, Frederic Diels

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Nowadays, manufacturing companies are faced with the challenge of meeting heterogeneous customer requirements in short product life cycles with a variety of product functions. So far, some of the functional requirements remain unknown until late stages of the product development. A way to handle these uncertainties is the highly iterative product development (HIP) approach. By structuring the development project as a highly iterative process, this method provides customer oriented and marketable products. There are first approaches for combined, hybrid models comprising deterministic-normative methods like the Stage-Gate process and empirical-adaptive development methods like SCRUM on a project management level. However, almost unconsidered is the question, which development scopes can preferably be realized with either empirical-adaptive or deterministic-normative approaches. In this context, a development scope constitutes a self-contained section of the overall development objective. Therefore, this paper focuses on a methodology that deals with the uncertainty of requirements within the early development stages and the corresponding selection of the most appropriate development approach. For this purpose, internal influencing factors like a company’s technology ability, the prototype manufacturability and the potential solution space as well as external factors like the market accuracy, relevance and volatility will be analyzed and combined into an Agile-Indicator. The Agile-Indicator is derived in three steps. First of all, it is necessary to rate each internal and external factor in terms of the importance for the overall development task. Secondly, each requirement has to be evaluated for every single internal and external factor appropriate to their suitability for empirical-adaptive development. Finally, the total sums of internal and external side are composed in the Agile-Indicator. Thus, the Agile-Indicator constitutes a company-specific and application-related criterion, on which the allocation of empirical-adaptive and deterministic-normative development scopes can be made. In a last step, this indicator will be used for a specific clustering of development scopes by application of the fuzzy c-means (FCM) clustering algorithm. The FCM-method determines sub-clusters within functional clusters based on the empirical-adaptive environmental impact of the Agile-Indicator. By means of the methodology presented in this paper, it is possible to classify requirements, which are uncertainly carried out by the market, into empirical-adaptive or deterministic-normative development scopes.

Keywords: agile, highly iterative development, agile-indicator, product development

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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

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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: 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

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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: Monika Zalewska

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Hans Kelsen was a versatile legal thinker whose achievements in the fields of legal theory, international law, and the theory of democracy are remarkable. All of the fields tackled by Kelsen are regarded as part of his “pure theory of law.” While the link between international law and Kelsen’s pure theory of law is apparent, the same cannot be said about the link between the theory of democracy and his pure theory of law. On the contrary, the general thinking concerning Kelsen’s thought is that it can be used to legitimize authoritarian regimes. The aim of this presentation is to address this concern by identifying the common ground between Kelsen’s pure theory of law and his theory of democracy and to show that they are compatible in a way that his pure theory of law and authoritarianism cannot be. The conceptual analysis of the purity of Kelsen’s theory and his goal of creating ideology-free legal science hints at how Kelsen’s pure theory of law and the theory of democracy are brought together. The presentation will first demonstrate that these two conceptions have common underlying values and meta-ethical convictions. Both are founded on relativism and a rational worldview, and the aim of both is peaceful co-existence. Second, it will be demonstrated that the separation of law and morality provides the maximum space for deliberation within democratic processes. The conclusion of this analysis is that striking similarities exist between Kelsen’s legal theory and his theory of democracy. These similarities are grounded in the Enlightenment tradition and its values, including rationality, a scientific worldview, tolerance, and equality. This observation supports the claim that, for Kelsen, legal positivism and the theory of democracy are not two separate theories but rather stem from the same set of values and from Kelsen’s relativistic worldview. Furthermore, three main issues determine Kelsen’s orientation toward a positivistic and democratic outlook. The first, which is associated with personality type, is the distinction between absolutism and relativism. The second, which is associated with the values that Kelsen favors in the social order, is peace. The third is legality, which creates the necessary condition for democracy to thrive and reveals that democracy is capable of fulfilling Kelsen’s ideal of law at its fullest. The first two categories exist in the background of Kelsen’s pure theory of law, while the latter is an inherent part of Kelsen’s concept of law. The analysis of the text concerning natural law doctrine and democracy indicates that behind the technical language of Kelsen’s pure theory of law is a strong concern with the trends that appeared after World War I. Despite his rigorous scientific mind, Kelsen was deeply humanistic. He tried to create a powerful intellectual weapon to provide strong arguments for peaceful coexistence and a rational outlook in Europe. The analysis provided by this presentation facilitates a broad theoretical, philosophical, and political understanding of Kelsen’s perspectives and, consequently, urges a strong endorsement of Kelsen’s approach to constitutional democracy.

Keywords: hans kelsen, democracy, legal positivism, pure theory of law

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Authors: Rajashree Bothale, Venkateswara Rao

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Indian Himalayas also known as third pole with 0.9 Million SQ km area, contain the largest reserve of ice and snow outside poles and affect global climate and water availability in the perennial rivers. The variations in the extent of snow are indicative of climate change. The snow melt is sensitive to climate change (warming) and also an influencing factor to the climate change. A study of the spatio-temporal dynamics of snow cover and melt/freeze conditions is carried out using space based observations in visible and microwave bands. An analysis period of 2003 to 2015 is selected to identify and map the changes and trend in snow cover using Indian Remote Sensing (IRS) Advanced Wide Field Sensor (AWiFS) and Moderate Resolution Imaging Spectroradiometer(MODIS) data. For mapping of wet snow, microwave data is used, which is sensitive to the presence of liquid water in the snow. The present study uses Ku-band scatterometer data from QuikSCAT and Oceansat satellites. The enhanced resolution images at 2.25 km from the 13.6GHz sensor are used to analyze the backscatter response to dry and wet snow for the period of 2000-2013 using threshold method. The study area is divided into three major river basins namely Brahmaputra, Ganges and Indus which also represent the diversification in Himalayas as the Eastern Himalayas, Central Himalayas and Western Himalayas. Topographic variations across different zones show that a majority of the study area lies in 4000–5500 m elevation range and the maximum percent of high elevated areas (>5500 m) lies in Western Himalayas. The effect of climate change could be seen in the extent of snow cover and also on the melt/freeze status in different parts of Himalayas. Melt onset day increases from east (March11+11) to west (May12+15) with large variation in number of melt days. Western Himalayas has shorter melt duration (120+15) in comparison to Eastern Himalayas (150+16) providing lesser time for melt. Eastern Himalaya glaciers are prone for enhanced melt due to large melt duration. The extent of snow cover coupled with the status of melt/freeze indicating solar radiation can be used as precursor for monsoon prediction.

Keywords: Indian Himalaya, Scatterometer, Snow Melt/Freeze, AWiFS, Cryosphere

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Authors: Haiqin Zhou, Robin Irons

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The introduction of hydrogen into local networks may, in many cases, require the initial operation of those systems on natural gas/hydrogen blends, either because of a lack of sufficient hydrogen to allow a 100% conversion or because existing infrastructure imposes limitations on the % hydrogen that can be burned before the end-use technologies are replaced. In many systems, the largest number of end-use technologies are small-scale but numerous appliances used for domestic and industrial heating and cooking. In such a scenario, it is important to understand exactly how much hydrogen can be introduced into these appliances before their performance becomes unacceptable and what imposes that limitation. This study seeks to explore a range of significantly higher hydrogen blends and a broad range of factors that might limit operability or environmental acceptability. We will present tests from a burner designed for space heating and optimized for natural gas as an increasing % of hydrogen blends (increasing from 25%) were burned and explore the range of parameters that might govern the acceptability of operation. These include gaseous emissions (particularly NOx and unburned carbon), temperature, flame length, stability and general operational acceptability. Results will show emissions, Temperature, and flame length as a function of thermal load and percentage of hydrogen in the blend. The relevant application and regulation will ultimately determine the acceptability of these values, so it is important to understand the full operational envelope of the burners in question through the sort of extensive parametric testing we have carried out. The present dataset should represent a useful data source for designers interested in exploring appliance operability. In addition to this, we present data on two factors that may be absolutes in determining allowable hydrogen percentages. The first of these is flame blowback. Our results show that, for our system, the threshold between acceptable and unacceptable performance lies between 60 and 65% mol% hydrogen. Another factor that may limit operation, and which would be important in domestic applications, is the acoustic performance of these burners. We will describe a range of operational conditions in which hydrogen blend burners produce a loud and invasive ‘screech’. It will be important for equipment designers and users to find ways to avoid this or mitigate it if performance is to be deemed acceptable.

Keywords: blends, operational, domestic appliances, future system operation.

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Authors: Naveen Porika, Snigdho Majumdar, Niraj Sethi

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Water, food and energy securities are emerging as increasingly important and vital issues for India and the world. Hyderabad urban agglomeration (HUA), the capital city of Andhra Pradesh State in India, is the sixth largest city has a population of about 8.2 million. The Musi River, which is a tributary of Krishna river flows from west to east right through the heart of Hyderabad, about 80% of the water used by people is released back as sewage, which flows back into Musi every day with detrimental effects on the environment and people downstream of the city. The average daily sewage generated in Hyderabad city is 950 MLD, however, treatment capacity exists only for 541 Million Liters per Day (MLD) but only 407 MLD of sewage is treated. As a result, 543 MLD of sewage daily flows into Musi river. Hyderabad’s current estimated water demand stands at 320 Million Gallons per Day (MGD). However, its installed capacity is merely 270 MGD; by 2020 estimated demand will grow to 400 MGD. There is huge gap between current supply and demand, and this is likely to widen by 2021. Developing new fresh water sources is a challenge for Hyderabad, as the fresh water sources are few and far from the City (about 150-200 km) and requires excessive pumping. The constraints presented above make the conventional alternatives for supply augmentation unsustainable and unattractive .One such dependable and captive source of easily available water is the treated sewage. With proper treatment, water of desired quality can be recovered from the waste water (sewage) for recycle and reuse. Hyderabad Amberpet sewage treatment of capacity 339 MLD is Asia’s largest sewage treatment plant. Tertiary sewage treatment Standard basic engineering modules of 30 MLD,60 MLD, 120MLD & 180 MLD for sewage treatment plants has been developed which are utilized for developing Sewage Reclamation & Reuse model in Asia’s largest sewage treatment plant. This paper will focus on Hyderabad Water Supply & Demand, Sewage Generation & Treatment, Technical aspects of Tertiary Sewage Treatment and Utilization of developed standard modules for reclamation & reuse of treated sewage to overcome the deficit of 130 MGD as projected by 2021.

Keywords: water reclamation, reuse, Andhra Pradesh, hyderabad, musi river, sewage, demand and supply, recycle, Amberpet, 339 MLD, engineering modules, tertiary treatment

Procedia PDF Downloads 618

Authors: Bruna P. De Souza, Ricardo C. De Almeida

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In some cities in the State of Parana – Brazil and in other countries atmospheric bromeliads (Tillandsia spp - Bromeliaceae) are considered weeds in trees, electric power lines, satellite dishes and other artificial supports. In this study, a numerical model was developed to simulate the seed dispersal of the Tillandsia recurvata species by wind with the objective of evaluating seeds displacement in the city of Ponta Grossa – PR, Brazil, since it is considered that the region is already infested. The model simulates the dispersal of each individual seed integrating parameters from the atmospheric boundary layer (ABL) and the local wind, simulated by the Weather Research Forecasting (WRF) mesoscale atmospheric model for the 2012 to 2015 period. The dispersal model also incorporates the approximate number of bromeliads and source height data collected from most infested electric power lines. The seeds terminal velocity, which is an important input data but was not available in the literature, was measured by an experiment with fifty-one seeds of Tillandsia recurvata. Wind is the main dispersal agent acting on plumed seeds whereas atmospheric turbulence is a determinant factor to transport the seeds to distances beyond 200 meters as well as to introduce random variability in the seed dispersal process. Such variability was added to the model through the application of an Inverse Fast Fourier Transform to wind velocity components energy spectra based on boundary-layer meteorology theory and estimated from micrometeorological parameters produced by the WRF model. Seasonal and annual wind means were obtained from the surface wind data simulated by WRF for Ponta Grossa. The mean wind direction is assumed to be the most probable direction of bromeliad seed trajectory. Moreover, the atmospheric turbulence effect and dispersal distances were analyzed in order to identify likely regions of infestation around Ponta Grossa urban area. It is important to mention that this model could be applied to any species and local as long as seed’s biological data and meteorological data for the region of interest are available.

Keywords: atmospheric turbulence, bromeliad, numerical model, seed dispersal, terminal velocity, wind

Procedia PDF Downloads 142

Authors: Ricardo Hugo Gonzalez, Amanda Figueiredo Vasconcelos, Francisco Loureiro Neto Monteiro, Yara Luiza Freitas Silva, Ana Cristina Lindsay, Márcia Maria Tavares Machado

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The use of sport as an integration mean is a very important tool regarding the social involvement of children and teenagers in a vulnerability situation. This study aims to report the experiences of a multidisciplinary program that intends to improve the quality of life of children and teenagers in Fortaleza, in the Northeast of Brazil. More than 400 children and teenagers aging 11 and 16 years participated in this study. Poor communities experience many particular difficulties in the urban centers such as violence, poor housing conditions, unemployment, lack in health care and deficient physical education in school. Physical education, physiotherapy, odontology, medicine and pharmacy students are responsible for the activities in the project supervised by a general coordinator and a counselor teacher of each academic unit. There are classes about team sports like basketball and soccer. Lectures about sexual behavior and sexually transmitted diseases are ministered beside the ones about oral health education, basic life support education, first aids, use and care with pharmaceuticals and orientations about healthy nutrition. In order to get the children’s family closer, monthly informative lectures are ministered. There is also the concern about reflecting the actions and producing academic paperwork such as graduation final projects and books. The number of participants has oscillated lately, and one of the causes is the lack of practicing physical activities and sports regularly. However, 250 teenagers have participated regularly for at least two years. These teenagers have shown a healthier lifestyle and a better physical fitness profile. The resources for maintaining the project come from the Pro-Reitoria of Extension, Federal University of Ceara, as well as from the PROEXT/MEC, Federal Government. Actions of this nature need to be done thinking for long periods so the effects results can become effective. Public and private investments are needed due to low socioeconomic families who are most vulnerable and have fewer opportunities to enhance to health prevention services.

Keywords: children and teenagers, health, multidisciplinary program, quality of life

Procedia PDF Downloads 244

Authors: Richard Ren

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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 130

Authors: Selam M. Tefera

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Soil constitutes a crucial component of rural and urban environments. This fact is making role of heavy and trace elements in the soil system an issue of global concern. Heavy metals constitute an ill-defined group of inorganic chemical hazards, whose main source is anthropogenic activities mainly related to fabrications. This accumulation of heavy metals soils can prove toxic to the environment. The application of biochar to soil is one way of immobilizing these contaminants through sorption by exploiting the high surface area of this material among its other essential properties. This research examined the ability of sugar cane straw, an organic waste material from sugar farm, derived biochar and ash to remediate soil contaminated with heavy metals mainly Chromium and Zinc from the effluent of electroplating industry. Biochar was produced by varying the temperature from 300 °C to 500 °C and ash at 700 °C. The highest yield (50%) was obtained at the lowest temperature (300 °C). The proximate analysis showed ash content of 42.8%, ultimate analysis with carbon content of 67.18%, the Hydrogen to Carbon ratio of 0.54 and the results from FTIR analysis disclosed the organic nature of biochar. Methylene blue absorption indicated its fine surface area and pore structure, which increases with severity of temperature. Biochar was mixed with soil with at a ration varying from 4% w/w to 10% w/w of soil, and the response variables were determined at a time interval of 150 days, 180 days, and 210 days. As for ash (10% w/w), the characterization was performed at incubation time of 210 days. The results of pH indicated that biochar (9.24) had a notable liming capacity of acidic soil (4.8) by increasing it to 6.89 whereas ash increased it to 7.5. The immobilization capacity of biochar was found to effected mostly by the highest production temperature (500 °C), which was 75.5% for chromium and 80.5% for nickel. In addition, ash was shown to possess an outstanding immobilization capacity of 95.5% and 90.5% for Chromium and Nickel, respectively. All in all, the results from these methods showed that biochar produced from this specific biomass possesses the typical functional groups that enable it to store carbon, the appropriate pH that could remediate acidic soil, a fine amount of macro and micro nutrients that would aid plant growth.

Keywords: biochar, biomass, heavy metal immobalization, soil remediation

Procedia PDF Downloads 145

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 267

Authors: Farnoosh Davarian

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The present research focuses on organizing the cooperation of units constrained by demand response (DR) programs, considering ancillary services in the P-Q power market. Moreover, it provides a comprehensive exploration of the effects of demand reduction and redistribution across several predefined scenarios (in three pre-designed demand response programs, for example, ranging from 5% to 20%) on system voltage and losses in a smart distribution system (in the studied network, distributed energy resources (DERs) such as synchronous distributed generators and wind turbines offer their active and reactive power for the proposed market).GAMS, a specialized software for high-powered modeling, is used for optimizing linear, nonlinear, and integer programming challenges. GAMS modeling is separate from its solution method, which is a notable feature. Thus, by providing changes in the solver, it is possible to solve the model using various methods (linear, nonlinear, integer, etc.). Finally, the combined active and reactive market challenge in smart distribution systems, considering renewable distributed sources and demand response programs in GAMS, will be evaluated. The active and reactive power trading by the distribution company is carried out in the wholesale market. What is demanded is active power. By using the buy-back/payment program, it is possible for responsive loads or aggregators to participate in the market. The objective function of the proposed market is to minimize the price of active and reactive power for DERs and distribution companies and the penalty cost for CO2 emissions and the cost of the buy-back/payment program. In this research, the objective function is to minimize the cost of active and reactive power from distributed generation sources and distribution companies, the cost of carbon dioxide emissions, and the cost of the buy-back/payment program. The effectiveness of the proposed method has been evaluated in a case study.

Keywords: consumer behavior, demand response, pollution cost, combined active and reactive market

Procedia PDF Downloads 10

Authors: Parisa Afshin, Terje Grønning

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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 226

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 227

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 91

Authors: Mukesh Lal Das, Muthukumar Muthuchamy

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Climate change Adaptation strategy (AS) is a scientific approach to dealing with the impacts of climate change (CC). Efforts are being made to contain the global emission of greenhouse gas within threshold limits, thereby limiting the rise of global temperature to an optimal level. Global Climate change is a spontaneous process; therefore, reversing the damage would take decades. The climate change adaptation strategy recommended by various stakeholders could be a key to resilience for biodiversity. The Indian Government has constituted the panel to synthesize the climate change action report at the federal and state levels. This review scavenged the published literature on the Western Ghats hotspots. And highlight the adaptation strategy recommended by diverse scientific actors to conserve biodiversity. It also reviews the grey literature adopted by state and federal governments and its effectiveness in mitigating the impacts on biodiversity. We have narrowed the scope of interest to the state action report by 6 Indian states such as Gujarat, Maharashtra, Goa, Karnataka, Kerala and Tamil Nadu, which host Western Ghats global biodiversity hotspot. Western Ghats(WGs) act as the water tower to the peninsular part of India, and its extensive watershed caters to the water demand of the Industry sector, Agriculture and urban community. Conservation of WGs is the key to the prosperity of Peninsular India. The global scientific community suggested more than 600+ Climate change adaptation strategies for the policymakers, stakeholders, and other state actors to take proactive actions. The preliminary analysis of the federal and the state action plan on climate change in the wake of CC indicate inadequacy in motion as per recommended scientific adaptation strategies. Tamil Nadu and Kerala state constitute nine effective adaptation strategies out of the 40+ recommended for Western Ghats conservation. And other four states' adaptation strategies are deficient, confusing and vague. Western Ghats' resilience capacity will soon or might have reached its threshold, and the frequency of severe drought and flash floods might upsurge manifold in the decades to come. The lack of a clear roadmap to climate change adaptation strategies in the federal and state action stirred us to identify the gap and address it by offering a holistic approach to WGs biodiversity conservation.

Keywords: adaptation strategy, biodiversity conservation, climate change, resilience, Western Ghats

Procedia PDF Downloads 107

Authors: Ni Tang, Jinping Zhang

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An effective and sustainable volunteer team is needed to create a more available blood supply system. In order to promote the sustainable development of blood donation in Zhejiang Province, China, a “three-exemption” policy was proposed in 2014: blood donors who received the National Award for unpaid blood donation may government-invested and funded parks, scenic spots and other places for free, visit non-profit medical institutions for free outpatient fees, and be exempted from urban public transportation fees. As the policy has been in place for seven years, this study evaluated the effectiveness of the policy by comparing the increasing rate of blood donation in Hangzhou (capital city of Zhejiang) before and after the policy using the intermittent time series analysis. The blood donation in Anhui, a Province near Zhejiang, was also compared as a negative control. Blood donation data from 2012 to 2018 were obtained from the donation center's official websites. The increasing rate of blood donation volume since 2012 in Hangzhou is 34.37 units/month, and after 2014, the increasing rate additionally increases 71.69 (p=0.1442), which indicating a statistically non-significant change after the policy. While as a negative control, in Anhui, the increasing rate of blood donation volume since 2012 is -163.3 unit/month, and the increasing rate additionally increases 167.2 (p=5.63e-07) after 2014. The result shows that the three-exemption policy had a certain level of impact on encouraging volunteers to donate blood, but the effect was not substantial. One possible reason for the ineffectiveness of the policy might be a lack of public awareness of the policy. On the other hand, this policy mainly waived unnecessary life expenses, such as fares and scenic entrance fees, and requires a certain number of blood donations, registration procedures, and blood donation certificates. Perhaps, reducing life-related expenses such as oil, water and electricity, could better attract people to participate in blood donation. This current study on the three-exemption policy provides a new direction for promoting people's blood donation. Incentive policies may require greater publicity and incentives. In order to better ensure the operation of the blood donation system, other policies, especially incentive policies, should be further explored.

Keywords: blood donation, policy, Zhejiang, unpaid blood donation, three-exemption policy

Procedia PDF Downloads 212

Authors: Abdulkarem Qasem Dammag, Basema Qasim Dammag, Jian Dai

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Change in Land use and Land cover (LU/LC) has a profound impact on the area's natural, economic, and ecological development, and the search for drivers of land cover change is one of the fundamental issues of LU/LC change. The study aimed to assess the temporal and Spatio-temporal dynamics of LU/LC in the past and to predict the future using Landsat images by exploring the characteristics of different LU/LC types. Spatio-temporal patterns of LU/LC change in Ibb Governorate, Yemen, were analyzed based on RS and GIS from 1990, 2005, and 2020. A socioeconomic survey and key informant interviews were used to assess potential drivers of LU/LC. The results showed that from 1990 to 2020, the total area of vegetation land decreased by 5.3%, while the area of barren land, grassland, built-up area, and waterbody increased by 2.7%, 1.6%, 1.04%, and 0.06%, respectively. Based on socio-economic surveys and key informant interviews, natural factors had a significant and long-term impact on land change. In contrast, site construction and socio-economic factors were the main driving forces affecting land change in a short time scale. The analysis results have been linked to the CA-Markov Land Use simulation and forecasting model for the years 2035 and 2050. The simulation results revealed from the period 2020 to 2050, the trend of dynamic changes in land use, where the total area of barren land decreased by 7.0% and grassland by 0.2%, while the vegetation land, built-up area, and waterbody increased by 4.6%, 2.6%, and 0.1 %, respectively. Overall, these findings provide LULC's past and future trends and identify drivers, which can play an important role in sustainable land use planning and management by balancing and coordinating urban growth and land use and can also be used at the regional level in different levels to provide as a reference. In addition, the results provide scientific guidance to government departments and local decision-makers in future land-use planning through dynamic monitoring of LU/LC change.

Keywords: LU/LC change, CA-Markov model, driving forces, change detection, LU/LC change simulation

Procedia PDF Downloads 66

Authors: Gholba Niranjan Dilip, Anil Kumar

Abstract:

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 162