Search results for: magnetic field measurement

Authors: E. Keramaris, V. Kanakoudis

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In this study the water flow in an open channel over a sharp-crested weir is investigated experimentally. For this reason a series of laboratory experiments were performed in an open channel with a sharp-crested weir. The maximum head expected over the weir, the total upstream water height and the downstream water height of the impact in the constant bed of the open channel were measured. The discharge was measured using a tank put right after the open channel. In addition, the discharge and the upstream velocity were also calculated using already known equations. The main finding is that the relative error percentage for the majority of the experimental measurements is ± 4%, meaning that the calculation of the discharge with a sharp-crested weir gives very good results compared to the numerical results from known equations.

Keywords: sharp-crested weir, weir height, flow measurement, open channel flow

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Authors: Yana Snegireva

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Carbonate reservoirs are known for their heterogeneity, resulting from various geological processes such as diagenesis and fracturing. These complexities may cause great challenges in understanding fluid flow behavior and predicting the production performance of naturally fractured reservoirs. The investigation of carbonate reservoirs is crucial, as many petroleum reservoirs are naturally fractured, which can be difficult due to the complexity of their fracture networks. This can lead to geological uncertainties, which are important for global petroleum reserves. The problem outlines the key challenges in carbonate reservoir modeling, including the accurate representation of fractures and their connectivity, as well as capturing the impact of fractures on fluid flow and production. Traditional reservoir modeling techniques often oversimplify fracture networks, leading to inaccurate predictions. Therefore, there is a need for a modern approach that can capture the complexities of carbonate reservoirs and provide reliable predictions for effective reservoir management and production optimization. The modern approach to carbonate reservoir modeling involves the utilization of the hybrid fracture modeling approach, including the discrete fracture network (DFN) method and implicit fracture network, which offer enhanced accuracy and reliability in characterizing complex fracture systems within these reservoirs. This study focuses on the application of the hybrid method in the Nepsko-Botuobinskaya anticline of the Eastern Siberia field, aiming to prove the appropriateness of this method in these geological conditions. The DFN method is adopted to model the fracture network within the carbonate reservoir. This method considers fractures as discrete entities, capturing their geometry, orientation, and connectivity. But the method has significant disadvantages since the number of fractures in the field can be very high. Due to limitations in the amount of main memory, it is very difficult to represent these fractures explicitly. By integrating data from image logs (formation micro imager), core data, and fracture density logs, a discrete fracture network (DFN) model can be constructed to represent fracture characteristics for hydraulically relevant fractures. The results obtained from the DFN modeling approaches provide valuable insights into the East Siberia field's carbonate reservoir behavior. The DFN model accurately captures the fracture system, allowing for a better understanding of fluid flow pathways, connectivity, and potential production zones. The analysis of simulation results enables the identification of zones of increased fracturing and optimization opportunities for reservoir development with the potential application of enhanced oil recovery techniques, which were considered in further simulations on the dual porosity and dual permeability models. This approach considers fractures as separate, interconnected flow paths within the reservoir matrix, allowing for the characterization of dual-porosity media. The case study of the East Siberia field demonstrates the effectiveness of the hybrid model method in accurately representing fracture systems and predicting reservoir behavior. The findings from this study contribute to improved reservoir management and production optimization in carbonate reservoirs with the use of enhanced and improved oil recovery methods.

Keywords: carbonate reservoir, discrete fracture network, fracture modeling, dual porosity, enhanced oil recovery, implicit fracture model, hybrid fracture model

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Authors: Joelle Hawa, Michael Gilding

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The role of interest as a driver of action has been an on-going debate in the sociological sciences. This paper shows evidence as to how economic actors frame their environment in terms of interests and goals to take action. It introduces the concept of 'dynamic actor compass', a cognitive tool that is socially contingent and allows economic actors to navigate their environment, evaluate the level of alignment of interests and goals with other players, and decide whether or not they are willing to rely on, collaborate or partner with others in the field. The paper builds on Kaplan’s model of framing contests and integrates Max Weber’s interests, and ideas construct as well as Beckert’s concept of fictional expectations. The author illustrates this conceptual framework in the case of MedTech entrepreneurs’ capital raising activities in Australia. The study adopts a grounded theory methodology, running in-depth interviews with 24 MedTech entrepreneurs in order to examine their decision-making processes and actions to finance their innovation trajectory. The findings show that participants take into account material and ideal interests and goals that they impose adapt or negotiate with other actors in their environment. These interactions affect the way MedTech entrepreneurs perceive other funders in the field, influencing their capital raising strategies.

Keywords: expectations, financing innovation, frames, goals, interest-oriented action, managerial cognition

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Authors: A. T. Asutosh, J. Woo, M. Kouhirostami, M. Sam, A. Khantawang, C. Cuales, W. Ryor, C. Kibert

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Climate change and global warming vortex have grown to alarming proportions. Therefore, the need for a shift in the conceptualization of energy production is paramount. Energy practices have been created in the current situation. Fossil fuels continue their prominence, at the expense of renewable sources. Despite this abundance, a large percentage of the world population still has no access to electricity but there have been encouraging signs in global movement from nonrenewable to renewable energy but means to reverse climate change have been elusive. Worldwide, organizations have put tremendous effort into innovation. Conferences and exhibitions act as a platform that allows a broad exchange of information regarding trends in the renewable energy field. The Solar Power International (SPI) conference and exhibition is a gathering of concerned activists, and probably the largest convention of its kind. This study investigates current development in the renewable energy field, analyzing means by which industry is being applied to the issue. In reviewing the 2019 SPI conference, it was found innovations in recycling and assessing the environmental impacts of the solar products that need critical attention. There is a huge movement in the electrical storage but there exists a large gap in the development of security systems. This research will focus on solar energy, but impacts will be relevant to the entire renewable energy market.

Keywords: climate change, renewable energy, solar, trends, research, solar power international, SPI

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Authors: Luís M. João, Patrício Langa

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The article reviews the literature on quality assurance (QA) in African higher education studies (HES) conducted through a bibliometric mapping of published papers between 1999 and 2019. Specifically, the article highlights the nuances of knowledge production in four scientific databases: Scopus, Web of Science (WoS), African Journal Online (AJOL), and Google Scholar. The analysis included 531 papers, of which 127 are from Scopus, 30 are from Web of Science, 85 are from African Journal Online, and 259 are from Google Scholar. In essence, 284 authors wrote these papers from 231 institutions and 69 different countries (i.e., Africa=54 and outside Africa=15). Results indicate the existing knowledge. This analysis allows the readers to understand the growth and development of the field during the two-decade period, identify key contributors, and observe potential trends or gaps in the research. The paper employs bibliometric mapping as its primary analytical lens. By utilizing this method, the study quantitatively assesses the publications related to QA in African HES, helping to identify patterns, collaboration networks, and disparities in research output. The bibliometric approach allows for a systematic and objective analysis of large datasets, offering a comprehensive view of the knowledge production in the field. Furthermore, the study highlights the lack of shared resources available to enhance quality in higher education institutions (HEIs) in Africa. This finding underscores the importance of promoting collaborative research efforts, knowledge exchange, and capacity building within the region to improve the overall quality of higher education. The paper argues that despite the growing quantity of QA research in African higher education, there are challenges related to citation impact and access to high-impact publication avenues for African researchers. It emphasises the need to promote collaborative research and resource-sharing to enhance the quality of HEIs in Africa. The analytical lenses of bibliometric mapping and the examination of publication players' scenarios contribute to a comprehensive understanding of the field and its implications for African higher education.

Keywords: Africa, bibliometric research, higher education studies, quality assurance, scientific database, systematic review

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Authors: Leonel Lipa Cusi, Enrique Nestor Pasquel Carbajal, Laura Marina Navarro Alvarado, José Del Álamo Carazas

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This research analyses the accuracy of the ultrasound and the pulse echo ultrasound technic to find voids and to measure thickness of concrete elements. These mentioned air voids are simulated by polystyrene expanded and hollow containers of thin thickness made of plastic or cardboard of different sizes and shapes. These targets are distributed strategically inside concrete at different depths. For this research, a shear wave pulse echo ultrasonic device of 50 KHz is used to scan the concrete elements. Despite the small measurements of the concrete elements and because of voids’ size are near the half of the wavelength, pre and post processing steps like voltage, gain, SAFT, envelope and time compensation were made in order to improve imaging results.

Keywords: ultrasonic, concrete, thickness, pulse echo, void

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Authors: Tawfig Alghbaili

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LP3D Field is located near the center of the Sirt Basin in the Marada Trough approximately 215 km south Marsa Al Braga City. The Marada Trough is bounded on the west by a major fault, which forms the edge of the Beda Platform, while on the east, a bounding fault marks the edge of the Zelten Platform. The main reservoir in the LP3D Field is Upper Paleocene Beda Formation. The Beda Formation is mainly limestone interbedded with shale. The reservoir average thickness is 117.5 feet. To develop a better understanding of the characterization and distribution of the Beda reservoir, quantitative seismic data interpretation has been done, and also, well logs data were analyzed. Six reflectors corresponding to the tops of the Beda, Hagfa Shale, Gir, Kheir Shale, Khalifa Shale, and Zelten Formations were picked and mapped. Special work was done on fault interpretation part because of the complexities of the faults at the structure area. Different attribute analyses were done to build up more understanding of structures lateral extension and to view a clear image of the fault blocks. Time to depth conversion was computed using velocity modeling generated from check shot and sonic data. The simplified stratigraphic cross-section was drawn through the wells A1, A2, A3, and A4-LP3D. The distribution and the thickness variations of the Beda reservoir along the study area had been demonstrating. Petrophysical analysis of wireline logging also was done and Cross plots of some petrophysical parameters are generated to evaluate the lithology of reservoir interval. Structure and Stratigraphic Framework was designed and run to generate different model like faults, facies, and petrophysical models and calculate the reservoir volumetric. This study concluded that the depth structure map of the Beda formation shows the main structure in the area of study, which is north to south faulted anticline. Based on the Beda reservoir models, volumetric for the base case has been calculated and it has STOIIP of 41MMSTB and Recoverable oil of 10MMSTB. Seismic attributes confirm the structure trend and build a better understanding of the fault system in the area.

Keywords: LP3D Field, Beda Formation, reservoir models, Seismic attributes

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Authors: Mareye Zeleke Mekonen

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The Kafficho language has distinct issues in information retrieval because of its restricted resources and dearth of standardized methods. In this endeavor, with the cooperation and support of linguists and native speakers, we investigate the creation of information retrieval systems specifically designed for the Kafficho language. The Kafficho information retrieval system allows Kafficho speakers to access information easily in an efficient and effective way. Our objective is to conduct an information retrieval experiment using 220 Kafficho text files, including fifteen sample questions. Tokenization, normalization, stop word removal, stemming, and other data pre-processing chores, together with additional tasks like term weighting, were prerequisites for the vector space model to represent each page and a particular query. The three well-known measurement metrics we used for our word were Precision, Recall, and and F-measure, with values of 87%, 28%, and 35%, respectively. This demonstrates how well the Kaffiho information retrieval system performed well while utilizing the vector space paradigm.

Keywords: Kafficho, information retrieval, stemming, vector space

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Authors: P. Sindhumole, K. Soumya, R. Renjimol

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Rice (Oryza sativa L.) is the major staple food crop over the world. It is prone to a number of biotic and abiotic stresses, out of which Bacterial Leaf Blight (BLB), caused by Xanthomonas oryzae pv. oryzae, is the most rampant. Management of this disease through chemicals or any other means is very difficult. The best way to control BLB is by the development of Host Plant Resistance. BLB resistance is not an activity of a single gene but it involves a cluster of more than thirty genes reported. Among these, Xa5 and Xa13 genes are two important ones, which can be diagnosed through marker assisted selection using closely linked molecular markers. During 2014, the first phase of field screening using forty traditional rice genotypes was carried out and twenty resistant symptomless genotypes were identified. Molecular characterisation of these genotypes using RM 122 SSR marker revealed the presence of Xa5 gene in thirteen genotypes. Forty-two traditional rice genotypes were used for the second phase of field screening for BLB resistance. Among these, sixteen resistant genotypes were identified. These genotypes, along with two susceptible check genotypes, were subjected to marker assisted selection for Xa13 gene, using the linked STS marker RG-136. During this process, presence of Xa13 gene could be detected in ten resistant genotypes. In future, these selected genotypes can be directly utilised as donors in Marker assisted breeding programmes for BLB resistance in rice.

Keywords: oryza sativa, SSR, STS, marker, disease, breeding

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Authors: Ajmal Khan Kassi, Humayun Javed, Tariq Mukhtar

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The research was conducted to screen out resistance and susceptibility of okra varieties against Helicoverpa armigera under field conditions 2016. In this experiment, the different management practices viz. release Trichogramma chilonis, hoeing, and weeding, clipping, and lufenuron were tested individually and with all possible combinations for the controlling of American bollworm at 3 diverse localities viz. University research farm Koont, National Agriculture Research Centre (NARC) and farmer field Taxila by using resistant variety Arka Anamika. All the treatment combinations regarding damage of shoot and fruit showed significant results. The minimum fruit infestation, i.e., 3.20% and 3.58% was recorded with combined treatment (i.e., T. chilonis + hoeing + weeding + lufenuron) in two different localities. The minimum shoot infestation, i.e., 7.18%, 7.08%, and 6.85% was also observed with (T. chilonis + hoeing + weeding + lufenuron) combined treatment at all three different localities. The above-combined treatment (T. chilonis + hoeing + weeding + lufenuron) also resulted in maximum yield at NARC and Taxila, i.e., 57.67 and 62.66 q/ha respectively. On the basis of combined treatment (i.e., T. chilonis + hoeing + weeding + lufenuron) in three different localities, Arka Anamika variety proved to be comparatively resistant against H. armigera. So this variety is recommended for the cultivation in Pothwar region to get maximum yield and minimum losses against H. armigera.

Keywords: okra, screening, combine treatment, Helicoverpa armigera

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Authors: Saud Al Taj

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Employer branding is considered as a useful tool for addressing the global-local problem facing complex organisations that have operations scattered across the globe and face challenges of dealing with the local environment alongside. Despite being an established field of study within the Western developed world, there is little empirical evidence concerning the relevance of employer branding to global companies that operate in the under-developed economies. This paper fills this gap by gaining rich insight into the implementation of employer branding programs in a foreign multinational operating in Pakistan dealing with the global-local problem. The study is qualitative in nature and employs semi-structured and focus group interviews with senior/middle managers and local frontline employees to deeply examine the phenomenon in case organisation. Findings suggest that authenticity is required in employer brands to enable them to respond to the local needs thereby leading to the resolution of the global-local problem. However, the role of signaling theory is key to the development of authentic employer brands as it stresses on the need to establish an efficient and effective signaling environment wherein signals travel in both directions (from signal designers to receivers and backwards) and facilitate firms with the global-local problem. The paper also identifies future avenues of research for the employer branding field.

Keywords: authenticity, counter-signals, employer branding, global-local problem, signaling theory

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Authors: O. Maklouf, Ahmed Abdulla

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A general decline in the cost, size, and power requirements of electronics is accelerating the adoption of integrated GPS/INS technologies in consumer applications such Land Vehicle Navigation. Researchers are looking for ways to eliminate additional components from product designs. One possibility is to drop one or more of the relatively expensive gyroscopes from microelectromechanical system (MEMS) versions of inertial measurement units (IMUs). For land vehicular use, the most important gyroscope is the vertical gyro that senses the heading of the vehicle and two horizontal accelerometers for determining the velocity of the vehicle. This paper presents a simplified integration algorithm for strap down (ParIMU)\GPS combination, with data post processing for the determination of 2-D components of position (trajectory), velocity and heading. In the present approach we have neglected earth rotation and gravity variations, because of the poor gyroscope sensitivities of the low-cost IMU and because of the relatively small area of the trajectory.

Keywords: GPS, ParIMU, INS, Kalman filter

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Authors: Yasser Aldali

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The scope of this paper is to evaluate and compare the potential of LS-PV (Large Scale Photovoltaic Power Plant) power generation systems in the southern region of Libya at Al-Kufra for both stationary and tracking systems. A Microsoft Excel-VBA program has been developed to compute slope radiation, dew-point, sky temperature, and then cell temperature, maximum power output and module efficiency of the system for stationary system and for tracking system. The results for energy production show that the total energy output is 114GWh/year for stationary system and 148 GWh/year for tracking system. The average module efficiency for the stationary system is 16.6% and 16.2% for the tracking system. The values of electricity generation capacity factor (CF) and solar capacity factor (SCF) for stationary system were found to be 26% and 62.5% respectively and 34% and 82% for tracking system. The GCR (Ground Cover Ratio) for a stationary system is 0.7, which corresponds to a tilt angle of 24°. The GCR for tracking system was found to be 0.12. The estimated ground area needed to build a 50MW PV plant amounts to approx. 0.55 km2 for a stationary PV field constituted by HIT PV arrays and approx. 91 MW/km2. In case of a tracker PV field, the required ground area amounts approx. 2.4k m2 and approx. 20.5 MW/km2.

Keywords: large scale photovoltaic power plant, two-axis tracking system, stationary system, landscape impact

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Authors: Stella C. Okenu, Stephen O. Adikwu, Martins E. Okoro

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The geothermal energy resource potential of the Lower Benue Trough (LBT) in Nigeria was evaluated in this study using spectral analysis of high-resolution aeromagnetic (HRAM) data. The reduced to the equator aeromagnetic data was divided into sixteen (16) overlapping blocks, and each of the blocks was analyzed to obtain the radial averaged power spectrum which enabled the computation of the top and centroid depths to magnetic sources. The values were then used to assess the Curie Point Depth (CPD), geothermal gradients, and heat flow variations in the study area. Results showed that CPD varies from 7.03 to 18.23 km, with an average of 12.26 km; geothermal gradient values vary between 31.82 and 82.50°C/km, with an average of 51.21°C/km, while heat flow variations range from 79.54 to 206.26 mW/m², with an average of 128.02 mW/m². Shallow CPD zones that run from the eastern through the western and southwestern parts of the study area correspond to zones of high geothermal gradient values and high subsurface heat flow distributions. These areas signify zones associated with anomalous subsurface thermal conditions and are therefore recommended for detailed geothermal energy exploration studies.

Keywords: geothermal energy, curie-point depth, geothermal gradient, heat flow, aeromagnetic data, LBT

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Authors: Mohammad Hossein Khasmafkan Nezam, Nader Chavoshi Boroujeni, Mohamad Reza Veshaghi

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Quality management is dominated by rational paradigms for the measurement and management of quality, but these paradigms start to ‘break down’, when faced with the inherent complexity of managing quality in intensely competitive changing environments. In this article, the various theoretical paradigms employed to manage quality are reviewed and the advantages and limitations of these paradigms are highlighted. A major implication of this review is that when faced with complexity, an ideological stance to any single strategy paradigm for total quality environmental management is ineffective. We suggest that as complexity increases and we envisage intensely competitive changing environments there will be a greater need to consider a multi-paradigm integrationist view of strategy for TQEM.

Keywords: total quality management (TQM), total quality environmental management (TQEM), ideologies (philosophy), theoretical paradigms

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Authors: Cristina Costa-Lobo, Carla B. Vestena, Filomena E. Ponte

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Creativity and intelligence are concepts that have aroused very expressive interest in the field of educational sciences and the field of psychological science since the middle of the last century since they have a great impact on the potential and well-being of individuals. However, due to progress in cognitive and positive psychology, there has been a growing interest in the psychoeducational domain of intelligence and creativity in the last decade. In this theoretical work, are analyzed comparatively the theoretical models that relate the intelligence and the creativity, are analyzed several psychoeducational intervention programs that have been implemented with a view to the promotion of creativity and signal possibilities, realities and ironies around the psychological evaluation of intelligence and creativity. In order to reach a broad perspective on creativity, the evidence is presented that points the need to evaluate different psychological domains. The psychoeducational intervention programs addressed have, with a common characteristic, the full stimulation of the creative potential of the participants, assumed as a highly valued capacity at the present time. The results point to the systematize that all interventions in the ambit of creativity have two guiding principles: all individuals can be creative, and creativity is a capacity that can be stimulated. This work refers to the importance of stimulus creativity in educational contexts, to the usefulness and pertinence of the creation, the implementation, and monitoring of flexible curricula, adapted to the educational needs of students, promoting a collaborative work among teachers, parents, students, psychologists, managers and educational administrators.

Keywords: creativity, intelligence, psychoeducational intervention programs, psychological evaluation, educational contexts

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Authors: Saeed Ur Rehman Chaudhry

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The objectives of the study are to reconstruct sequence stratigraphic framework and petrophysical analysis of the reservoir marked by using sequence stratigraphy of Sawan Gas Field. The study area lies in Central Indus Basin, District Khairpur, Sindh province, Pakistan. The study area lies tectonically in an extensional regime. Lower Goru Formation and Sembar Formation act as a reservoir and source respectively. To achieve objectives, data set of seismic lines, consisting of seismic lines PSM96-114, PSM96-115, PSM96-133, PSM98-201, PSM98-202 and well logs of Sawan-01, Sawan-02 and Gajwaro-01 has been used. First of all interpretation of seismic lines has been carried out. Interpretation of seismic lines shows extensional regime in the area and cut entire Cretaceous section. Total of seven reflectors has been marked on each seismic line. Lower Goru Formation is thinning towards west. Seismic lines also show eastward tilt of stratigraphy due to uplift at the western side. Sequence stratigraphic reconstruction has been done by integrating seismic and wireline log data. Total of seven sequence boundaries has been interpreted between the top of Chiltan Limestone to Top of Lower Goru Formation. It has been observed on seismic lines that Sembar Formation initially generated shelf margin profile and then ramp margin on which Lower Goru deposition took place. Shelf edge deltas and slope fans have been observed on seismic lines, and signatures of slope fans are also observed on wireline logs as well. Total of six sequences has been interpreted. Stratigraphic and sequence stratigraphic correlation has been carried out by using Sawan 01, Sawan 02 and Gajwaro 01 and a Low Stand Systems tract (LST) within Lower Goru C sands has been marked as a zone of interest. The petrophysical interpretation includes shale volume, effective porosity, permeability, saturation of water and hydrocarbon. On the basis of good effective porosity and hydrocarbon saturation petrophysical analysis confirms that the LST in Sawan-01 and Sawan-02 has good hydrocarbon potential.

Keywords: petrophysical analysis, reservoir potential, Sawan Gas Field, sequence stratigraphy

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Authors: J. T. Pitale, S. Ghassab, H. Ay, N. Berme

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Biomechanics researchers commonly use marker-based optical motion capture (MoCap) systems to extract human body kinematic data. These systems use cameras to detect passive or active markers placed on the subject. The cameras use triangulation methods to form images of the markers, which typically require each marker to be visible by at least two cameras simultaneously. Cameras in a conventional optical MoCap system are mounted at a distance from the subject, typically on walls, ceiling as well as fixed or adjustable frame structures. To accommodate for space constraints and as portable force measurement systems are getting popular, there is a need for smaller and smaller capture volumes. When the efficacy of a MoCap system is investigated, it is important to consider the tradeoff amongst the camera distance from subject, pixel density, and the field of view (FOV). If cameras are mounted relatively close to a subject, the area corresponding to each pixel reduces, thus increasing the image resolution. However, the cross section of the capture volume also decreases, causing reduction of the visible area. Due to this reduction, additional cameras may be required in such applications. On the other hand, mounting cameras relatively far from the subject increases the visible area but reduces the image quality. The goal of this study was to develop a quantitative methodology to investigate marker occlusions and optimize camera placement for a given capture volume and subject postures using three-dimension computer-aided design (CAD) tools. We modeled a 4.9m x 3.7m x 2.4m (LxWxH) MoCap volume and designed a mounting structure for cameras using SOLIDWORKS (Dassault Systems, MA, USA). The FOV was used to generate the capture volume for each camera placed on the structure. A human body model with configurable posture was placed at the center of the capture volume on CAD environment. We studied three postures; initial contact, mid-stance, and early swing. The human body CAD model was adjusted for each posture based on the range of joint angles. Markers were attached to the model to enable a full body capture. The cameras were placed around the capture volume at a maximum distance of 2.7m from the subject. We used the Camera View feature in SOLIDWORKS to generate images of the subject as seen by each camera and the number of markers visible to each camera was tabulated. The approach presented in this study provides a quantitative method to investigate the efficacy and efficiency of a MoCap camera setup. This approach enables optimization of a camera setup through adjusting the position and orientation of cameras on the CAD environment and quantifying marker visibility. It is also possible to compare different camera setup options on the same quantitative basis. The flexibility of the CAD environment enables accurate representation of the capture volume, including any objects that may cause obstructions between the subject and the cameras. With this approach, it is possible to compare different camera placement options to each other, as well as optimize a given camera setup based on quantitative results.

Keywords: motion capture, cameras, biomechanics, gait analysis

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Authors: Wang Zhiwei, Wang Weiwu

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The process of urbanization in China has entered a critical period of transformation from urban expansion and construction to delicate urban design, thus forming a new direction in the field of urban design. So far, catalyst theory has become a prominent guiding strategy in urban planning and design. In this paper, under the background of urban renewal, catalyst theory is taken as the guiding ideology to explore the method of urban design in shouxian county. Firstly, this study briefly introduces and analyzes the catalyst theory. Through field investigation, it is found that the city has a large number of idle Spaces, such as abandoned factories and schools. In the design, the idle Spaces in the county town are utilized and interlinked in space, and functional interaction is carried out from the pattern of the county town. On the one hand, the results showed that the catalyst theory can enhance the vitality of the linear street space with a small amount of monomer construction. On the other hand, the city can also increase the cultural and economic sites of the city without damaging the historical relics and the sense of alterations of the ancient city, to improve the quality of life and quality of life of citizens. The city micro-transformation represented by catalyst theory can help ancient cities like shouxian to realize the activation of the old city and realize the gradual development.

Keywords: catalytic theory, urban design, China's ancient city, Renaissance

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Authors: Musa H. Arslan

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Strengthening of the existing seismically deficient reinforced concrete (RC) buildings is an important issue in earthquake prone regions. Addition of RC shear wall as infill or external walls into the structural system has been a commonly preferred strengthening technique since the Big Erzincan Earthquake occurred in Turkey, 1992. The newly added rigid infill walls act primarily as shear walls and relieve the non-ductile existing frames from being subjected to large shear demands providing that new RC inner or external walls are adequately anchored to the existing weak RC frame. The performance of the RC shear walls-RC weak frame connections by steel anchor dowels depends on some parameters such as compressive strength of the existing RC frame concrete, diameter and embedment length of anchored rebar, type of rebar, yielding stress of bar, properties of used chemicals, position of the anchor bars in RC. In this study, application problems of the steel anchor dowels have been checked with some field studies such as tensile test. Two different RC buildings which will be strengthened were selected, and before strengthening, some tests have been performed in the existing RC buildings. According to the field observation and experimental studies, if the concrete compressive strength is lower than 10 MPa, the performance of the anchors is reduced by 70%.

Keywords: anchor dowel, concrete, damage, reinforced concrete, shear wall, frame

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Authors: Sayed Obeidullah Abrar

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Nanosensor is the combination of two terms nanoparticles and sensors. These are chemical or physical sensor constructed using nanoscale components, usually microscopic or submicroscopic in size. These sensors are very sensitive and can detect single virus particle or even very low concentrations of substances that could be potentially harmful. Nanosensors have a large scope of research especially in the field of medical sciences, military applications, pharmaceuticals etc.

Keywords: HIV/AIDS, nanosensors, DNA, RNA

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Authors: Aly Elshafei, Daniela Romano

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With the development of autonomous vehicles, a human-machine interaction (HMI) system is needed for a safe transition of control when a takeover request (TOR) is required. An important part of the HMI system is the ability to monitor the level of situational awareness (SA) of any driver in real-time, in different scenarios, and without any pre-calibration. Presenting state-of-the-art machine learning models used to measure SA is the purpose of this systematic review. Investigating the limitations of each type of sensor, the gaps, and the most suited sensor and computational model that can be used in driving applications. To the author’s best knowledge this is the first literature review identifying online and offline classification methods used to measure SA, explaining which measurements are subject or session-specific, and how many classifications can be done with each classification model. This information can be very useful for researchers measuring SA to identify the most suited model to measure SA for different applications.

Keywords: situational awareness, autonomous driving, gaze metrics, EEG, ECG

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Authors: M. Salih Taci, N. Tayebi, I. Bozkır

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In this paper, the equivalent circuit of the ideal single-phase power transformer with its appropriate voltage current measurement was presented. The calculated values of the voltages and currents of the different connections single phase normal transformer and the results of the simulation process are compared. As it can be seen, the calculated results are the same as the simulated results. This paper includes eight possible different transformer connections. Depending on the desired voltage level, step-down and step-up application transformer is considered. Modelling and analysis of a system consisting of an equivalent source, transformer (primary and secondary), and loads are performed to investigate the combinations. The obtained values are simulated in PSpice environment and then how the currents, voltages and phase angle are distributed between them is explained based on calculation.

Keywords: transformer, simulation, equivalent model, parallel series combinations

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Authors: Niki K. Burns, James R. Pearson, Paul G. Stevenson, Xavier A. Conlan

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In Australian state Victoria, synthetic cannabinoids have recently been made illegal under an amendment to the drugs, poisons and controlled substances act 1981. Identification of synthetic cannabinoids in popular brands of ‘incense’ and ‘potpourri’ has been a difficult and challenging task due to the sample complexity and changes observed in the chemical composition of the cannabinoids of interest. This study has developed analytical methodology for the targeted extraction and determination of synthetic cannabinoids available pre-ban. A simple solvent extraction and solid phase extraction methodology was developed that selectively extracted the cannabinoid of interest. High performance liquid chromatography coupled with UV‐visible and chemiluminescence detection (acidic potassium permanganate and tris (2,2‐bipyridine) ruthenium(III)) were used to interrogate the synthetic cannabinoid products. Mass spectrometry and nuclear magnetic resonance spectroscopy were used for structural elucidation of the synthetic cannabinoids. The tris(2,2‐bipyridine)ruthenium(III) detection was found to offer better sensitivity than the permanganate based reagents. In twelve different brands of herbal incense, cannabinoids were extracted and identified including UR‐144, XLR 11, AM2201, 5‐F‐AKB48 and A796‐260.

Keywords: electrospray mass spectrometry, high performance liquid chromatography, solid phase extraction, synthetic cannabinoids

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Authors: Tallal Abdel Karim Bouzir, Nourdinne Zemmouri, Djihed Berkouk

Abstract:

In this research, a quantitative assessment of the urban sound environment of the city of Biskra, Algeria, was conducted. To determine the quality of the soundscape based on in-situ measurement, using a Landtek SL5868P sound level meter in 47 points, which have been identified to represent the whole city. The result shows that the urban noise level varies from 55.3 dB to 75.8 dB during the weekdays and from 51.7 dB to 74.3 dB during the weekend. On the other hand, we can also note that 70.20% of the results of the weekday measurements and 55.30% of the results of the weekend measurements have levels of sound intensity that exceed the levels allowed by Algerian law and the recommendations of the World Health Organization. These very high urban noise levels affect the quality of life, the acoustic comfort and may even pose multiple risks to people's health.

Keywords: road traffic, noise pollution, sound intensity, public health

Procedia PDF Downloads 265

Authors: Hasliza A. Rahim, Fareq Malek, Nur A. M. Affendi, Azuwa Ali, Norshafinash Saudin, Latifah Mohamed

Abstract:

This paper presents the experimental investigation of on-body channel fading at 2.45 GHz considering two effects of the user body movement; stationary and mobile. A pair of body-worn antennas was utilized in this measurement campaign. A statistical analysis was performed by comparing the measured on-body path loss to five well-known distributions; lognormal, normal, Nakagami, Weibull and Rayleigh. The results showed that the average path loss of moving arm varied higher than the path loss in sitting position for upper-arm-to-left-chest link, up to 3.5 dB. The analysis also concluded that the Nakagami distribution provided the best fit for most of on-body static link path loss in standing still and sitting position, while the arm movement can be best described by log-normal distribution.

Keywords: on-body channel communications, fading characteristics, statistical model, body movement

Procedia PDF Downloads 353

Authors: Rabia Mushtaq, Uroosa Javaid

Abstract:

It has been observed that health professionals are at higher danger of stress in light of the fact that being a specialist is physically and emotionally demanding. The study aimed to investigate the relationship between workplace stress and mental wellbeing among health professionals. Sample of 120 male and female health professionals belonging to two age groups, i.e., early adulthood and middle adulthood, was employed through purposive sampling technique. Job stress scale, mindful attention awareness scale, and Warwick Edinburgh mental wellbeing scales were used for the measurement of study variables. Results of the study indicated that job stress has a significant negative relationship with mental wellbeing among health professionals. The current study opened the door for more exploratory work on mindfulness among health professionals. Yielding outcomes helped in consolidating adapting procedures among workers to improve their mental wellbeing and lessen the job stress.

Keywords: health professionals, job stress, mental wellbeing, mindfulness

Procedia PDF Downloads 172

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 124

Authors: Sandro Bartolini, Alessandro Mecocci, Alessio Medaglini

Abstract:

The growing popularity of systems based on unmanned aerial vehicles (UAVs) is highlighting their vulnerability, particularly in relation to the positioning system used. Typically, UAV architectures use the civilian GPS, which is exposed to a number of different attacks, such as jamming or spoofing. This is why it is important to develop alternative methodologies to accurately estimate the actual UAV position without relying on GPS measurements only. In this paper, we propose a position estimate method for UAVs based on monocular visual odometry. We have developed a flight control system capable of keeping track of the entire trajectory travelled, with a reduced dependency on the availability of GPS signals. Moreover, the simplicity of the developed solution makes it applicable to a wide range of commercial drones. The final goal is to allow for safer flights in all conditions, even under cyber-attacks trying to deceive the drone.

Keywords: visual odometry, autonomous uav, position measurement, autonomous outdoor flight

Procedia PDF Downloads 215

Authors: Mohammad Mardi

Abstract:

Generally, the resistivity is high in oil layer and low in water layer. Yet there are intervals of oil-bearing zones showing low resistivity, high porosity, and low resistance. In the typical example, well A (depth: 4341.5-4372.0m), both Spectral Gamma Ray (SGR) and Corrected Gamma Ray (CGR) are relatively low; porosity varies from 12-22%. Above 4360 meters, the reservoir shows the conventional positive difference between deep and shallow resistivity with high resistance; below 4360m, the reservoir shows a negative difference with low resistance, especially at depths of 4362.4 meters and 4371 meters, deep resistivity is only 2Ω.m, and the CAST-V imaging map shows that there are low resistance substances contained in the pores or matrix in the reservoirs of this interval. The rock slice analysis data shows that the pyrite volume is 2-3% in the interval 4369.08m-4371.55m. A comprehensive analysis on the volume of shale (Vsh), porosity, invasion features of resistivity, mud logging, and mineral volume indicates that the possible causes for the negative difference between deep and shallow resistivities with relatively low resistance are erosional pores, caves, micritic texture and the presence of pyrite. Full-bore Drill Stem Test (DST) verified 4991.09 bbl/d in this interval. To identify and thoroughly characterize low resistivity intervals coring, Nuclear Magnetic Resonance (NMR) logging and further geological evaluation are needed.

Keywords: low resistivity pay, carbonates petrophysics, microporosity, porosity

Procedia PDF Downloads 163