Search results for: proposed module

Authors: Namratha Pai, K. Vasantharaj, K. Haribabu

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Our Team is developing an innovative cost effective biological technique to desulfurize crude oil. ’Sulphur’ is found to be present in crude oil samples from .05% - 13.95% and its elimination by industrial methods is expensive currently. Materials required :- Alicyclobacillus acidoterrestrius, potato dextrose agar, oxygen, Pyragallol and inert gas(nitrogen). Method adapted and proposed:- 1) Growth of bacteria studied, energy needs. 2) Compatibility with crude-oil. 3) Reaction rate of bacteria studied and optimized. 4) Reaction development by computer simulation. 5) Simulated work tested by building the reactor. The method being developed requires the use of bacteria Alicyclobacillus acidoterrestrius - an acidothermophilic heterotrophic, soil dwelling aerobic, Sulfur bacteria. The bacteria are fed to crude oil in a unique manner. Its coated onto potato dextrose agar beads, cultured for 24 hours (growth time coincides with time when it begins reacting) and fed into the reactor. The beads are to be replenished with O2 by passing them through a jacket around the reactor which has O2 supply. The O2 can’t be supplied directly as crude oil is inflammable, hence the process. Beads are made to move around based on the concept of fluidized bed reactor. By controlling the velocity of inert gas pumped , the beads are made to settle down when exhausted of O2. It is recycled through the jacket where O2 is re-fed and beads which were inside the ring substitute the exhausted ones. Crude-oil is maintained between 1 atm-270 M Pa pressure and 45°C treated with tartaric acid (Ph reason for bacteria growth) for optimum output. Bacteria being of oxidising type react with Sulphur in crude-oil and liberate out SO4^2- and no gas. SO4^2- is absorbed into H2O. NaOH is fed once reaction is complete and beads separated. Crude-oil is thus separated of SO4^2-, thereby Sulphur, tartaric acid and other acids which are separated out. Bio-corrosion is taken care of by internal wall painting (phenolepoxy paints). Earlier methods used included use of Pseudomonas and Rhodococcus species. They were found to be inefficient, time and energy consuming and reduce the fuel value as they fed on skeleton.

Keywords: alicyclobacillus acidoterrestrius, potato dextrose agar, fluidized bed reactor principle, reaction time for bacteria, compatibility with crude oil

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Authors: Ghufran Ahmed, Muhammad Osama Siddiqui, Shahbaz Siddiqui, Rauf Ahmad Shams Malick, Faisal Khan, Mubashir Khan

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In this paper, a machine learning-based approach for early prediction of diseases in cows is proposed. Different ML algos are applied to extract useful patterns from the available dataset. Technology has changed today’s world in every aspect of life. Similarly, advanced technologies have been developed in livestock and dairy farming to monitor dairy cows in various aspects. Dairy cattle monitoring is crucial as it plays a significant role in milk production around the globe. Moreover, it has become necessary for farmers to adopt the latest early prediction technologies as the food demand is increasing with population growth. This highlight the importance of state-ofthe-art technologies in analyzing how important technology is in analyzing dairy cows’ activities. It is not easy to predict the activities of a large number of cows on the farm, so, the system has made it very convenient for the farmers., as it provides all the solutions under one roof. The cattle industry’s productivity is boosted as the early diagnosis of any disease on a cattle farm is detected and hence it is treated early. It is done on behalf of the machine learning output received. The learning models are already set which interpret the data collected in a centralized system. Basically, we will run different algorithms on behalf of the data set received to analyze milk quality, and track cows’ health, location, and safety. This deep learning algorithm draws patterns from the data, which makes it easier for farmers to study any animal’s behavioral changes. With the emergence of machine learning algorithms and the Internet of Things, accurate tracking of animals is possible as the rate of error is minimized. As a result, milk productivity is increased. IoT with ML capability has given a new phase to the cattle farming industry by increasing the yield in the most cost-effective and time-saving manner.

Keywords: IoT, machine learning, health care, dairy cows

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Authors: Alex Fedoseyev

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This study explores Generalized Hydrodynamic Equations (GHE) for the simulation of turbulent flows. The GHE was derived from the Generalized Boltzmann Equation (GBE) by Alexeev (1994). GBE was obtained by first principles from the chain of Bogolubov kinetic equations and considered particles of finite dimensions, Alexeev (1994). The GHE has new terms, temporal and spatial fluctuations compared to the Navier-Stokes equations (NSE). These new terms have a timescale multiplier τ, and the GHE becomes the NSE when τ is zero. The nondimensional τ is a product of the Reynolds number and the squared length scale ratio, τ=Re*(l/L)², where l is the apparent Kolmogorov length scale, and L is a hydrodynamic length scale. The turbulence phenomenon is not well understood and is not described by NSE. An additional one or two equations are required for the turbulence model, which may have to be tuned for specific problems. We show that, in the case of the GHE, no additional turbulence model is needed, and the turbulent velocity profile is obtained from the GHE. The 2D turbulent channel and circular pipe flows were investigated using a numerical solution of the GHE for several cases. The solutions are compared with the experimental data in the circular pipes and 2D channels by Nicuradse (1932, Prandtl Lab), Hussain and Reynolds (1975), Wei and Willmarth (1989), Van Doorne (2007), theory by Wosnik, Castillo and George (2000), and the relevant experiments on Superpipe setup at Princeton, data by Zagarola (1996) and Zagarola and Smits (1998), the Reynolds number is from Re=7200 to Re=960000. The numerical solution data compared well with the experimental data, as well as with the approximate analytical solution for turbulent flow in channel Fedoseyev (2023). The obtained results confirm that the Alexeev generalized hydrodynamic theory (GHE) is in good agreement with the experiments for turbulent flows. The proposed approach is limited to 2D and 3D axisymmetric channel geometries. Further work will extend this approach by including channels with square and rectangular cross-sections.

Keywords: comparison with experimental data. generalized hydrodynamic equations, numerical solution, turbulent boundary layer, turbulent flow in channel

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Authors: Laurent Pitteloud, Jörg Meier

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Piled raft foundations represent an efficient and reliable technique for transferring high vertical and horizontal loads to the subsoil. Piled raft foundations were success­fully implemented for several high-rise buildings world­wide over the last decades. For the structural design of this foundation type the stiffnesses of both the piles and the raft have to be deter­mined for the static (e.g. dead load, live load) and the dynamic load cases (e.g. earthquake). In this context the question often arises, to which proportion wind loads are to be considered as dynamic loads. Usually a piled raft foundation has to be monitored in order to verify the design hypotheses. As an additional benefit, the analysis of this monitoring data may lead to a better under­standing of the behaviour of this foundation type for future projects in similar subsoil conditions. In case the measurement frequency is high enough, one may also draw conclusions on the effect of wind loading on the piled raft foundation. For a 41-storey office building in Basel, Switzerland, the preliminary design showed that a piled raft foundation was the best solution to satisfy both design requirements, as well as economic aspects. A high-frequency monitoring of the foundation including pile loads, vertical stresses under the raft, as well as pore water pressures was performed over 5 years. In windy situations the analysis of the measure­ments shows that the pile load increment due to wind consists of a static and a cyclic load term. As piles and raft react with different stiffnesses under static and dynamic loading, these measure­ments are useful for the correct definition of stiffnesses of future piled raft foundations. This paper outlines the design strategy and the numerical modelling of the aforementioned piled raft foundation. The measurement results are presented and analysed. Based on the findings, comments and conclusions on the definition of pile and raft stiffnesses for vertical and wind loading are proposed.

Keywords: design, dynamic, foundation, monitoring, pile, raft, wind load

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Authors: Amèdédjihundé H. J. Hounnou, Frédéric Dubas, François-Xavier Fifatin, Didier Chamagne, Antoine Vianou

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This paper presents the techno-economic evaluation of run-of-river small-hydropower plants. In this regard, a multi-objective optimization procedure is proposed for the optimal sizing of the hydropower plants, and NSGAII is employed as the optimization algorithm. Annual generated energy and investment cost are considered as the objective functions, and number of generator units (n) and nominal turbine flow rate (Q_T) constitute the decision variables. Site of Yeripao in Benin is considered as the case study. We have categorized the river of this site using its environmental characteristics: gross head, and first quartile, median, third quartile and mean of flow. Effects of each decision variable on the objective functions are analysed. The results gave Pareto Front which represents the trade-offs between annual energy generation and the investment cost of hydropower plants, as well as the recommended optimal solutions. We noted that with the increase of the annual energy generation, the investment cost rises. Thus, maximizing energy generation is contradictory with minimizing the investment cost. Moreover, we have noted that the solutions of Pareto Front are grouped according to the number of generator units (n). The results also illustrate that the costs per kWh are grouped according to the n and rise with the increase of the nominal turbine flow rate. The lowest investment costs per kWh are obtained for n equal to one and are between 0.065 and 0.180 €/kWh. Following the values of n (equal to 1, 2, 3 or 4), the investment cost and investment cost per kWh increase almost linearly with increasing the nominal turbine flowrate while annual generated. Energy increases logarithmically with increasing of the nominal turbine flowrate. This study made for the Yeripao river can be applied to other rivers with their own characteristics.

Keywords: hydropower plant, investment cost, multi-objective optimization, number of generator units

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Authors: D. Sigirli

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The Receiver Operating Characteristic (ROC) curve is a commonly used statistical tool for evaluating the diagnostic performance of screening and diagnostic test with continuous or ordinal scale results which aims to predict the presence or absence probability of a condition, usually a disease. When the test results were measured as numeric values, sensitivity and specificity can be computed across all possible threshold values which discriminate the subjects as diseased and non-diseased. There are infinite numbers of possible decision thresholds along the continuum of the test results. The ROC curve presents the trade-off between sensitivity and the 1-specificity as the threshold changes. The empirical ROC curve which is a non-parametric estimator of the ROC curve is robust and it represents data accurately. However, especially for small sample sizes, it has a problem of variability and as it is a step function there can be different false positive rates for a true positive rate value and vice versa. Besides, the estimated ROC curve being in a jagged form, since the true ROC curve is a smooth curve, it underestimates the true ROC curve. Since the true ROC curve is assumed to be smooth, several smoothing methods have been explored to smooth a ROC curve. These include using kernel estimates, using log-concave densities, to fit parameters for the specified density function to the data with the maximum-likelihood fitting of univariate distributions or to create a probability distribution by fitting the specified distribution to the data nd using smooth versions of the empirical distribution functions. In the present paper, we aimed to propose a smooth ROC curve estimation based on the boundary corrected kernel function and to compare the performances of ROC curve smoothing methods for the diagnostic test results coming from different distributions in different sample sizes. We performed simulation study to compare the performances of different methods for different scenarios with 1000 repetitions. It is seen that the performance of the proposed method was typically better than that of the empirical ROC curve and only slightly worse compared to the binormal model when in fact the underlying samples were generated from the normal distribution.

Keywords: empirical estimator, kernel function, smoothing, receiver operating characteristic curve

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Authors: Michael A. Sprayberry, Vincent C. Paquit

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Process parameter optimization in metal powder bed electron beam melting (MPBEBM) is crucial to ensure the technology's repeatability, control, and industry-continued adoption. Despite continued efforts to address the challenges via the traditional design of experiments and process mapping techniques, there needs to be more successful in an on-the-fly optimization framework that can be adapted to MPBEBM systems. Additionally, data-intensive physics-based modeling and simulation methods are difficult to support by a metal AM alloy or system due to cost restrictions. To mitigate the challenge of resource-intensive experiments and models, this paper introduces a Multi-Objective Reinforcement Learning (MORL) methodology defined as an optimization problem for MPBEBM. An off-policy MORL framework based on policy gradient is proposed to discover optimal sets of beam power (P) – beam velocity (v) combinations to maintain a steady-state melt pool depth and phase transformation. For this, an experimentally validated Eagar-Tsai melt pool model is used to simulate the MPBEBM environment, where the beam acts as the agent across the P – v space to maximize returns for the uncertain powder bed environment producing a melt pool and phase transformation closer to the optimum. The culmination of the training process yields a set of process parameters {power, speed, hatch spacing, layer depth, and preheat} where the state (P,v) with the highest returns corresponds to a refined process parameter mapping. The resultant objects and mapping of returns to the P-v space show convergence with experimental observations. The framework, therefore, provides a model-free multi-objective approach to discovery without the need for trial-and-error experiments.

Keywords: additive manufacturing, metal powder bed fusion, reinforcement learning, process parameter optimization

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Authors: Sela Adjei

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This paper aims to rationalize the need for media policy implementation and copyright enforcement to address various challenges faced within Ghana’s film industry. After Ghana transitioned to democratic rule in 1992, critics and media professionals advocated a national media policy. This advocacy subsequently resulted in agitation for media deregulation and loosening of grip on state-owned media organizations. The reinstatement of constitutional rule in 1992 paved the way for the state to lax its monopoly of the media within the democratic context of a free market economy. The National Media Commission proposed a media policy and broadcast bill which was presented to parliament but has still not been passed into law. This legislative lapse partly contributed to the influx of unregulated foreign content. Accessible foreign media content subsequently promoted a system of unfair competition that radically undermined locally produced content, putting a generation of thriving film producers out of work. Drawing on reflections from a series of structured interviews, focus group discussions and creative workshops, the findings of this study maintain that the various challenges confronting Ghanaian filmmakers is centred around inadequate funding opportunities, copyright violation and policy implementation issues. Using the film industry structure and value chain analysis, the various challenges faced by the selected film producers were discussed and critically analyzed. A significant aspect of this study is the solution-driven approach adopted in outlining the practical recommendations that will boost the aesthetic, cultural and economic value of Ghanaian film productions. Based on the discussions and conclusions drawn with the various stakeholders within Ghana’s creative industries, the paper makes a strong case for firm state regulation, copyright enforcement and policy implementation to grow Ghana’s film industry.

Keywords: film, value, copyright, media, policy, culture, regulation, economy

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Authors: Lota Largavista

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This study entitled, ‘The Organizational Structure, Development Features, and Metadiscoursal Elements in the Expository Writing of Freshman College Writers’ aimed to examine essays written by college students. It seeks to examine the organizational structure and development features of the essays and describe their defining characteristics, the linguistic elements at both macrostructural and microstructural discourse levels and the types of textual and interpersonal metadiscourse markers that are employed in order to negotiate meanings with their prospective readers. The different frameworks used to analyze the essays include Toulmin’s ( 1984) model for argument structure, Olson’s ( 2003) three-part essay structure; Halliday and Matthiesen (2004) in Herriman (2011) notions of thematic structure, Danes (1974) thematic progression or method of development, Halliday’s (2004) concept of grammatical and lexical cohesion ;Hyland’s (2005) metadiscourse strategies; and Chung and Nation’s( 2003) four-step scale for technical vocabulary. This descriptive study analyzes qualitatively and quantitatively how freshman students generally express their written compositions. Coding of units is done to determine what linguistic features are present in the essays. Findings revealed that students’ expository essays observe a three-part structure having all three moves, the Introduction, the Body and the Conclusion. Stance assertion, stance support, and emerging moves/strategies are found to be employed in the essays. Students have more marked themes on the essays and also prefer constant theme progression as their method of development. The analysis of salient linguistic elements reveals frequently used cohesive devices and metadiscoursal strategies. Based on the findings, an instructional learning plan is being proposed. This plan is characterized by a genre approach that focuses on expository and linguistic conventions.

Keywords: metadiscourse, organization, theme progression, structure

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Authors: Chenhao Zhu

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Quantitative mapping is playing a growing role in guiding urban planning, such as using a heat map created by CFX, CFD2000, or Envi-met, to adjust the master plan. However, there is no effective quantitative link between the mappings and planning formation. So, in many cases, the decision-making is still based on the planner's subjective interpretation and understanding of these mappings, which limits the improvement of scientific and accuracy brought by the quantitative mapping. Therefore, in this paper, an effort has been made to give a methodology of building a parametric link between the mapping and planning formation. A parametric planning process based on radiant mapping has been proposed for creating an urban green system. In the first step, a script is written in Grasshopper to build a road network and form the block, while the Ladybug Plug-in is used to conduct a radiant analysis in the form of mapping. Then, the research creatively transforms the radiant mapping from a polygon into a data point matrix, because polygon is hard to engage in the design formation. Next, another script is created to select the main green spaces from the road network based on the criteria of radiant intensity and connect the green spaces' central points to generate a green corridor. After that, a control parameter is introduced to adjust the corridor's form based on the radiant intensity. Finally, a green system containing greenspace and green corridor is generated under the quantitative control of the data matrix. The designer only needs to modify the control parameter according to the relevant research results and actual conditions to realize the optimization of the green system. This method can also be applied to much other mapping-based analysis, such as wind environment analysis, thermal environment analysis, and even environmental sensitivity analysis. The parameterized link between the mapping and planning will bring about a more accurate, objective, and scientific planning.

Keywords: parametric link, mapping, urban green system, radiant intensity, planning strategy, grasshopper

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Authors: P. Y. Chiang, Y. H. Chen, Y. J. Lin, C. C. Chang, W. C. Hsu

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The number of the elderly in the world population and the rate of falls in this increasing numbers of older people are increasing. Decreasing muscle strength and an increasing risk of falling are associated with the ageing process. Because the effects of seated stepping training on the walking performance in the elderly remain unclear, the main purpose of the proposed study is to perform electromyography analysis during walking and seated stepping in the elderly. Four surface EMG electrodes were sticked on the surface of lower limbs muscles, including vastus lateralis (VL), and gastrocnemius (GT) of both sides. Before test, maximal voluntary contraction (MVC) of the respective muscle was obtained using manual muscle testing. The analog raw data of EMG signals were digitized with a sampling frequency of 2000 Hz. The signals were fully rectified and the linear envelope were calculated. Stepping motion cycle was separated into two phases by stepping timing (ST) and pedal return timing (PRT). ST refer to the time when the pedal marker reached the highest height, representing the contra-lateral leg was going to release the pedal. PRT refer to the time when the pedal marker reached the lowest height, representing the contra-lateral leg was going to step the pedal. We assumed that ST acted the same role in initial contact during walking, and PRT for toe-off. The period from ST to next PRT was called pushing phase (PP), during which the leg would start to step with resistance, and we compare this phase with the stance phase in level walking. The period from PRT to next ST was called returning phase (RP), during which leg would not have any resistance in this phase, and we compare this phase with the swing phase in level walking. VL and Gastro muscular activation had similar patterns in both side. The ability may transfer to those needed during loading response, mid-stance and terminal swing phase. User needed to make more effort in stepping compared with walking with similar timing; thus the strengthening of the VL and Gastro may be helpful to improve the walking endurance and efficiency for the elderly.

Keywords: elderly, electromyography, seated stepping, walking

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Authors: Aleksandra Majchrzak, Katarzyna Baruch, Monika Sobolewska, Bartlomiej Chojnacki, Adam Pilch

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Scaled modeling is very common in the areas of science such as aerodynamics or fluid mechanics, since defining characteristic numbers enables to determine relations between objects under test and their models. In acoustics, scaled modeling is aimed mainly at investigation of room acoustics, sound insulation and sound absorption phenomena. Despite such a range of application, there is no method developed that would enable scaling acoustical perforated panels freely, maintaining their sound absorption coefficient in a desired frequency range. However, conducted theoretical and numerical analyses have proven that it is not physically possible to obtain given sound absorption coefficient in a desired frequency range by directly scaling only all of the physical dimensions of a perforated panel, according to a defined characteristic number. This paper is a continuation of the research mentioned above and presents practical evaluation of theoretical and numerical analyses. The measurements of sound absorption coefficient of perforated panels were performed in order to verify previous analyses and as a result find the relations between full-scale perforated panels and their models which will enable to scale them properly. The measurements were conducted in a one-to-eight model of a reverberation chamber of Technical Acoustics Laboratory, AGH. Obtained results verify theses proposed after theoretical and numerical analyses. Finding the relations between full-scale and modeled perforated panels will allow to produce measurement samples equivalent to the original ones. As a consequence, it will make the process of designing acoustical perforated panels easier and will also lower the costs of prototypes production. Having this knowledge, it will be possible to emulate in a constructed model panels used, or to be used, in a full-scale room more precisely and as a result imitate or predict the acoustics of a modeled space more accurately.

Keywords: characteristic numbers, dimensional analysis, model study, scaled modeling, sound absorption coefficient

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Authors: Ibrahim Khan, Waqas Khalid

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The Healthcare sector is known to consume a higher proportion of total energy consumption in the HVAC market owing to an excessive cooling and heating requirement in maintaining human thermal comfort in indoor conditions, catering to patients undergoing treatment in hospital wards, rooms, and intensive care units. The indoor thermal comfort conditions in selected hospitals of Islamabad, Pakistan, were measured on a real-time basis with the collection of first-hand experimental data using calibrated sensors measuring Ambient Temperature, Wet Bulb Globe Temperature, Relative Humidity, Air Velocity, Light Intensity and CO2 levels. The Experimental data recorded was analyzed in conjunction with the Thermal Comfort Questionnaire Surveys, where the participants, including patients, doctors, nurses, and hospital staff, were assessed based on their thermal sensation, acceptability, preference, and comfort responses. The Recorded Dataset, including experimental and survey-based responses, was further analyzed in the development of a correlation between operative temperature, operative relative humidity, and other measured operative parameters with the predicted mean vote and adaptive predicted mean vote, with the adaptive temperature and adaptive relative humidity estimated using the seasonal data set gathered for both summer – hot and dry, and hot and humid as well as winter – cold and dry, and cold and humid climate conditions. The Machine Learning Logistic Regression Algorithm was incorporated to train the operative experimental data parameters and develop a correlation between patient sensations and the thermal environmental parameters for which a new ML-based adaptive thermal comfort model was proposed and developed in our study. Finally, the accuracy of our model was determined using the K-fold cross-validation.

Keywords: predicted mean vote, thermal comfort, energy management, logistic regression, machine learning

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Authors: Nazi Pharsadanishvili, Anastasia Kitiashvili

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The importance of studying the social-psychological features of people living in poverty is often emphasized in international research. Building a multidimensional economic framework for reducing poverty grounded in people’s experiences and values is the main goal of famous Poverty Research Centers (such as Oxford Poverty and Human Development Initiative, Abdul Latif Jameel Poverty Action Lab). The aims of the proposed research are to investigate the following characteristics of socially vulnerable people living in Georgia: 1) The features of the perceived stigma of poverty; 2) economic system justification and social justice beliefs; 3) Perceived social mobility and actual attempts at upward social mobility. Qualitative research was conducted to address the indicated research goals and descriptive research questions. Conducting in-depth interviews was considered to be the most appropriate method to capture the vivid feelings and experiences of people living in poverty. 17 respondents (registered in the unified database of socially vulnerable families) participated in in-depth interviews. According to the research results, socially vulnerable people living in Georgia perceive stigma targeted toward them. Two sub-dimensions were identified in perceived stigma: experienced stigma and internalized stigma. Experienced stigma reflects the instances of being discriminated and perceptions of negative treatment from other members of society. Internalized stigma covers negative personal emotions, the feelings of shame, the fear of future stigmatization, and self-isolation. The attitudes and justifications of the existing economic system affect people’s attempts to cope with poverty. Complex analysis of those results is important during the planning and implementing of social welfare reforms. Particularly, it is important to implement poverty stigma reduction mechanisms and help socially vulnerable people to see real perspectives on upward social mobility.

Keywords: coping with poverty, economic system justification, perceived stigma of poverty, upward social mobility

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Authors: L. Wei Sheng, M. T. Noor Syazwanee, C. J. Carolyna, M. Amiruddin, M. Pauziah

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This paper exhibits the alternatives towards active suspension systems revised based on the classical passive suspension system to improve comfort and handling performance. An active Magneto rheological (MR) suspension system is proposed as to explore the active based suspension system to enhance performance given its freedom to independently specify the characteristics of load carrying, handling, and ride quality. Malaysian quarter car with two degrees of freedom (2DOF) system is designed and constructed to simulate the actions of an active vehicle suspension system. The structure of a conventional twin-tube shock absorber is modified both internally and externally to comprehend with the active suspension system. The shock absorber peripheral structure is altered to enable the assembling and disassembling of the damper through a non-permanent joint whereby the stress analysis of the designed joint is simulated using Finite Element Analysis. Simulation on the internal part where an electrified copper coil of 24AWG is winded is done using Finite Element Method Magnetics to measure the magnetic flux density inside the MR damper. The primary purpose of this approach is to reduce the vibration transmitted from the effects of road surface irregularities while maintaining solid manoeuvrability. The aim of this research is to develop an intelligent control system of a consecutive damping automotive suspension system. The ride quality is improved by means of the reduction of the vertical body acceleration caused by the car body when it experiences disturbances from speed bump and random road roughness. Findings from this research are expected to enhance the quality of ride which in return can prevent the deteriorating effect of vibration on the vehicle condition as well as the passengers’ well-being.

Keywords: active suspension, FEA, magneto rheological damper, Malaysian quarter car model, vibration control

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Authors: Smita Chaudhary

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Traffic in India are observed uncontrolled, and are characterized by chaotic (not follows the lane discipline) traffic situation. Bus Rapid Transit (BRT) has emerged as a viable option to enhance transportation capacity and provide increased levels of mobility and accessibility. At present in Ahmadabad there are as many intersections which face the congestion and delay at signalized intersection due to transit (BRT) lanes. Most of the intersection in spite of being signalized is operated manually due to the conflict between BRT buses and heterogeneous traffic. Though BRTS in Ahmadabad has an exclusive lane of its own but with this comes certain limitations which Ahmadabad is facing right now. At many intersections in Ahmadabad due to these conflicts, interference, and congestion both heterogeneous traffic as well as transit buses suffer traffic delays of remarkable 3-4 minutes at each intersection which has a become an issue of great concern. There is no provision of BRT bus priority due to which existing signals have their least role to play in managing the traffic that ultimately call for manual operation. There is an immense decrement in the daily ridership of BRTS because people are finding this transit mode no more time saving in their routine, there is an immense fall in ridership ultimately leading to increased number of private vehicles, idling of vehicles at intersection cause air and noise pollution. In order to bring back these commuters’ transit facilities need to be improvised. Classified volume count survey, travel time delay survey was conducted and revised signal design was done for whole study stretch having three intersections and one roundabout, later one intersection was simulated in order to see the effect of giving priority to BRT on side street queue length and travel time for heterogeneous traffic. This paper aims at suggesting the recommendations in signal cycle, introduction of intermittent priority for transit buses, simulation of intersection in study stretch with proposed signal cycle using VISSIM in order to make this transit amenity feasible and attracting for commuters in Ahmadabad.

Keywords: BRT, priority, Ridership, Signal, VISSIM

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Authors: Leila Baghaarabani, Parvin Razzaghi, Mennatolla Magdy Mostafa, Ahmad Albaqsami, Al Warith Al Rushaidi, Masoud Al Rawahi

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Predicting the interaction between drugs and their molecular targets is pivotal for advancing drug development processes. Due to the time and cost limitations, computational approaches have emerged as an effective approach to drug-target interaction (DTI) prediction. Most of the introduced computational based approaches utilize the drug molecule and protein sequence as input. This study does not only utilize these inputs, it also introduces a protein representation developed using a masked protein language model. In this representation, for every individual amino acid residue within the protein sequence, there exists a corresponding probability distribution that indicates the likelihood of each amino acid being present at that particular position. Then, the similarity between each pair of amino acids is computed to create a similarity matrix. To encode the knowledge of the similarity matrix, Bi-Level Routing Attention (BiFormer) is utilized, which combines aspects of transformer-based models with protein sequence analysis and represents a significant advancement in the field of drug-protein interaction prediction. BiFormer has the ability to pinpoint the most effective regions of the protein sequence that are responsible for facilitating interactions between the protein and drugs, thereby enhancing the understanding of these critical interactions. Thus, it appears promising in its ability to capture the local structural relationship of the proteins by enhancing the understanding of how it contributes to drugprotein interactions, thereby facilitating more accurate predictions. To evaluate the proposed method, it was tested on two widely recognized datasets: Davis and KIBA. A comprehensive series of experiments was conducted to illustrate its effectiveness in comparison to cutting edge techniques.

Keywords: BiFormer, transformer, protein language processing, self-attention mechanism, binding affinity, drug target interaction, similarity matrix, protein masked representation, protein language model

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Authors: Lailial Muhtifah, Sirtul Marhamah

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This article forwards the conceptual framework of continuous academic lecturer model in Islamic higher education (IHE). It is intended to make a contribution to the broader issue of how the concept of excellence can promote adherence to standards in higher education and drive quality enhancement. This model reveals a process and steps to increase performance and achievement of excellence regular lecturer gradually. Studies in this model are very significant to realize excellence academic culture in IHE. Several steps were identified from previous studies through literature study and empirical findings. A qualitative study was conducted at institute. Administrators and lecturers were interviewed, and lecturers learning communities observed to explore institute culture policies, and procedures. The original in this study presents and called Continuous Academic Lecturer Model (CALM) with its components, namely Standard, Quality, and Excellent as the basis for this framework (SQE). Innovation Excellence Framework requires Leaders to Support (LS) lecturers to achieve a excellence culture. So, the model named CALM-SQE+LS. Several components of performance and achievement of CALM-SQE+LS Model should be disseminated and cultivated to all lecturers in university excellence in terms of innovation. The purpose of this article is to define the concept of “CALM-SQE+LS”. Originally, there were three components in the Continuous Academic Lecturer Model i.e. standard, quality, and excellence plus leader support. This study is important to the community as specific cases that may inform educational leaders on mechanisms that may be leveraged to ensure successful implementation of policies and procedures outline of CALM with its components (SQE+LS) in institutional culture and professional leader literature. The findings of this study learn how continuous academic lecturer is part of a group's culture, how it benefits in university. This article blends the available criteria into several sub-component to give new insights towards empowering lecturer the innovation excellence at the IHE. The proposed conceptual framework is also presented.

Keywords: continuous academic lecturer model, excellence, quality, standard

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Authors: Carl-Philipp Valentin Beichert, Marcel Seger

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Digital transformation and climate change require small and medium-sized enterprises (SME) to rethink their way of doing business. Inter-firm collaboration is recognized as helpful means of promoting innovation and competitiveness. In this context, collaborations with start-ups offer valuable opportunities through their innovative products, services, and business models. SMEs, and in particular German craft enterprises, play an important role in the country’s society and economy. Companies in this heterogeneous economic sector have unique characteristics and are limited in their ability to innovate due to their small size and lack of resources. Collaborating with start-ups could help to overcome these shortcomings. To investigate how collaborations emerge and what factors are decisive to successfully drive collaboration, we apply an explorative, qualitative research design. A sample of ten case studies was selected, with the collaboration between a start-up and a craft enterprise forming the unit of analysis. Semi-structured interviews with 20 company representatives allow for a two-sided perspective on the respective collaboration. The interview data is enriched by publicly available data and three expert interviews. As a result, objectives, initiation practices, applied collaboration types, barriers, as well as key success factors could be identified. The results indicate a three-phase collaboration process comprising an initiation, concept, and partner phase (ICP). The ICP framework proposed accordingly highlights the success factors (personal fit, communication, expertise, structure, network) for craft enterprises and start-ups for each collaboration phase. The role of a mediator in the start-up company, with strong expertise in the respective craft sector, is considered an important lever for overcoming barriers such as cultural and communication differences. The ICP framework thus provides promising directions for further research and can help practitioners establish successful collaborations.

Keywords: open innovation, SME, craft businesses, startup collaboration, qualitative research

Procedia PDF Downloads 92

Authors: Alaa Hamed Salama, Rehab Nabil Shamma

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Introduction: Polymeric micelles that can deliver drug to intended sites of the eye have attracted much scientific attention recently. The aim of this study was to review the aqueous-based formulation of drug-loaded polymeric micelles that hold significant promise for ophthalmic drug delivery. This study investigated the synergistic performance of mixed polymeric micelles made of linear and branched poly (ethylene oxide)-poly (propylene oxide) for the more effective encapsulation of Lornoxicam (LX) as a hydrophobic model drug. Methods: The co-micellization process of 10% binary systems combining different weight ratios of the highly hydrophilic poloxamers; Synperonic® PE/P84, and Synperonic® PE/F127 and the hydrophobic poloxamine counterpart (Tetronic® T701) was investigated by means of photon correlation spectroscopy and cloud point. The drug-loaded micelles were tested for their solubilizing capacity towards LX. Results: Results showed a sharp solubility increase from 0.46 mg/ml up to more than 4.34 mg/ml, representing about 136-fold increase. Optimized formulation was selected to achieve maximum drug solubilizing power and clarity with lowest possible particle size. The optimized formulation was characterized by 1HNMR analysis which revealed complete encapsulation of the drug within the micelles. Further investigations by histopathological and confocal laser studies revealed the non-irritant nature and good corneal penetrating power of the proposed nano-formulation. Conclusion: LX-loaded polymeric nanomicellar formulation was fabricated allowing easy application of the drug in the form of clear eye drops that do not cause blurred vision or discomfort, thus achieving high patient compliance.

Keywords: confocal laser scanning microscopy, Histopathological studies, Lornoxicam, micellar solubilization

Procedia PDF Downloads 447

Authors: Victor U. Odoemelam, Ihemdirim C. Unamba-Opara, Martins C. Anyanwuocha

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Antibiotics used as growth promoters in animal feeds have been criticized and banned in many nations due to possible development of both drug resistance, cross resistance and multiple resistances by consumers. Numerous additives are now being used or proposed as alternatives. A study to compare the effects of Ocimum gratissimum (Scent leaf) and antibiotic growth promoter (Oxytetracycline HCl) on growth performance and intestinal morphology of starter broiler birds was conducted using ninety six (96) days old broiler birds. The birds were randomly assigned to four treatments with each treatment comprising 24 birds replicated three times with 8 birds per replicate in a completely randomized design experiment. Four diets (T1 control diet without Oxytetracycline HCl and Ocimum gratissimum; T2 had Oxytetracycline HCl; T3 had 1% Ocimum gratissimum; T4 had 1.5% Ocimum gratissimum) were formulated and offered ad libitum to the respective birds. Data was collected on feed intake, body weight gain and feed conversion ratio (FCR) also Jejenal sections of the intestine were collected for examination of Villi length and Crypt depth at the end of starter phase. Results show that there were no significant difference (P>0.05) observed in feed intake and final body weight. However, feed conversion ratio (FCR) and daily weight gain significantly differed (P<0.05). T1, T2, and T4 were similar, however T2 differed (P<0.05) from T3. FCR followed the same pattern. Dietary treatment significantly (P<0.05) affected Villi length, Crypt depth and Villi length/crypt depth ratio. Birds fed OG containing diets, had significantly higher (P<0.05) villi length/crypt depth ratio. However, this did not translate to a significantly higher body weight gain or feed conversion ratio. It can be concluded that O. gratissimum can replace antibiotic growth promoter (Oxytetracycline HCl) since their effect on performance were similar.

Keywords: antibiotics, body weight, feed additives, intestinal morphology, phytogenics

Procedia PDF Downloads 542

Authors: Tara Moore

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Madagascar is one of the regions of the world with the highest biodiversity, with more than 600 new species discovered in just the last decade. In parallel with its record-breaking biodiversity, Madagascar is also the tenth poorest country in the world. The resultant socio-economic pressures are leading to a highly threatened environment. In particular, deforestation is at the core of biodiversity and ecosystem loss, primarily from slash and burn agriculture and illegal rosewood tree harvesting. Effective policy response is imperative for improved conservation in Madagascar. However, these changes cannot come from the current, unstable government institutions. After a violent and politically turbulent coup in 2009, any effort to defend Madagascar's biodiversity has been eclipsed by the high corruption of government bodies. This paper presents three policy options designed for a private donor to invest in conservation in Madagascar. The first proposed policy consists of payments for ecosystem services model, which involves paying local Malagasy women to reforest nearby territories. The second option is a micro-irrigation system proposal involving relocating local Malagasy out of the threatened forest region. The final proposition is captive breeding funding for the Madagascar Fauna and Flora Group, which could then lead to new reintroductions in the threatened northeastern rainforests. In the end, all three options present feasible, impactful options for a conservation-minded major donor. Ideally, the policy change would involve a combination of all three options, as each provides necessary development and conservation re-structuring goals. Option one, payments for ecosystem services, would be the preferred choice if there were only enough funding for one project. The payments for ecosystem services project both support local populations and promotes sustainable development while reforesting the threatened Marojejy National Park. Regardless of the chosen policy solution, any support from a donor will make a huge impact if it supports both sustainable development and biodiversity conservation.

Keywords: captive breeding, cnservation policy, lemur conservation, Madagascar conservation, payments for ecosystem services

Procedia PDF Downloads 133

Authors: Mst Shapna Akter, Hossain Shahriar

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One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. Every year, more and more software flaws are found, either internally in proprietary code or revealed publicly. These flaws are highly likely exploited and lead to system compromise, data leakage, or denial of service. C and C++ open-source code are now available in order to create a largescale, machine-learning system for function-level vulnerability identification. We assembled a sizable dataset of millions of opensource functions that point to potential exploits. We developed an efficient and scalable vulnerability detection method based on deep neural network models that learn features extracted from the source codes. The source code is first converted into a minimal intermediate representation to remove the pointless components and shorten the dependency. Moreover, we keep the semantic and syntactic information using state-of-the-art word embedding algorithms such as glove and fastText. The embedded vectors are subsequently fed into deep learning networks such as LSTM, BilSTM, LSTM-Autoencoder, word2vec, BERT, and GPT-2 to classify the possible vulnerabilities. Furthermore, we proposed a neural network model which can overcome issues associated with traditional neural networks. Evaluation metrics such as f1 score, precision, recall, accuracy, and total execution time have been used to measure the performance. We made a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information. We found that all of the deep learning models provide comparatively higher accuracy when we use semantic and syntactic information as the features but require higher execution time as the word embedding the algorithm puts on a bit of complexity to the overall system.

Keywords: cyber security, vulnerability detection, neural networks, feature extraction

Procedia PDF Downloads 88

Authors: Marek Kuźniewski, Magdalena B. Kaziuk , Danuta Fedak, Paulina Dumnicka, Ewa Stępień, Beata Kuśnierz-Cabala, Władysław Sułowicz

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Background: The high prevalence of cardiovascular morbidity and mortality among patients with chronic kidney disease (CKD) is observed especially in those undergoing dialysis. Osteoprotegerin (OPG) and its ligands, receptor activator of nuclear factor kappa-B ligand (RANKL) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) have been associated with cardiovascular complications. Our aim was to study their role as cardiovascular risk factors in stage 5 CKD patients. Methods: OPG, RANKL and TRAIL concentrations were measured in 69 hemodialyzed CKD patients and 35 healthy volunteers. In CKD patients, cardiovascular dysfunction was assessed with aortic pulse wave velocity (AoPWV), carotid artery intima-media thickness (CCA-IMT), coronary artery calcium score (CaSc) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) serum concentration. Cardiovascular and overall mortality data were collected during a 7-years follow-up. Results: OPG plasma concentrations were higher in CKD patients comparing to controls. Total soluble RANKL was lower and OPG/RANKL ratio higher in patients. Soluble TRAIL concentrations did not differ between the groups and OPG/TRAIL ratio was higher in CKD patients. OPG and OPG/TRAIL positively predicted long-term mortality (all-cause and cardiovascular) in CKD patients. OPG positively correlated with AoPWV, CCA-IMT and NT-proBNP whereas OPG/TRAIL with AoPWV and NT-proBNP. Described relationships were independent of classical and non-classical cardiovascular risk factors, with exception of age. Conclusions: Our study confirmed the role of OPG as a biomarker of cardiovascular dysfunction and a predictor of mortality in stage 5 CKD. OPG/TRAIL ratio can be proposed as a predictor of cardiovascular dysfunction and mortality.

Keywords: osteoprotegerin, tumor necrosis factor-related apoptosis-inducing ligand, receptor activator of nuclear factor kappa-B ligand, hemodialysis, chronic kidney disease, cardiovascular disease

Procedia PDF Downloads 334

Authors: Nwachukwu Ifeanyi

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Wind energy is a vital component of the global renewable energy portfolio, with wind turbines serving as the primary means of harnessing this abundant resource. However, the efficiency and stability of wind turbines remain critical challenges in maximizing energy output and ensuring long-term operational viability. This study proposes a comprehensive approach utilizing computational aerodynamics and aeromechanics to optimize wind turbine performance across multiple objectives. The proposed research aims to integrate advanced computational fluid dynamics (CFD) simulations with structural analysis techniques to enhance the aerodynamic efficiency and mechanical stability of wind turbine blades. By leveraging multi-objective optimization algorithms, the study seeks to simultaneously optimize aerodynamic performance metrics such as lift-to-drag ratio and power coefficient while ensuring structural integrity and minimizing fatigue loads on the turbine components. Furthermore, the investigation will explore the influence of various design parameters, including blade geometry, airfoil profiles, and turbine operating conditions, on the overall performance and stability of wind turbines. Through detailed parametric studies and sensitivity analyses, valuable insights into the complex interplay between aerodynamics and structural dynamics will be gained, facilitating the development of next-generation wind turbine designs. Ultimately, this research endeavours to contribute to the advancement of sustainable energy technologies by providing innovative solutions to enhance the efficiency, reliability, and economic viability of wind power generation systems. The findings have the potential to inform the design and optimization of wind turbines, leading to increased energy output, reduced maintenance costs, and greater environmental benefits in the transition towards a cleaner and more sustainable energy future.

Keywords: computation, robotics, mathematics, simulation

Procedia PDF Downloads 57

Authors: Andres F. Ramirez, Carlos F. Valencia

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The increasing interest in renewable energies strategies application and the path for diminishing the use of carbon related energy sources have encouraged the development of novel strategies for integration of solar energy into the electricity network. A correct inclusion of the fluctuating energy output of a photovoltaic (PV) energy system into an electric grid requires improvements in the forecasting and simulation methodologies for solar energy potential, and the understanding not only of the mean value of the series but the associated underlying stochastic process. We present a methodology for synthetic generation of solar irradiance (shortwave flux) and air temperature bivariate time series based on copula functions to represent the cross-dependence and temporal structure of the data. We explore the advantages of using this nonlinear time series method over traditional approaches that use a transformation of the data to normal distributions as an intermediate step. The use of copulas gives flexibility to represent the serial variability of the real data on the simulation and allows having more control on the desired properties of the data. We use discrete zero mass density distributions to assess the nature of solar irradiance, alongside vector generalized linear models for the bivariate time series time dependent distributions. We found that the copula autoregressive methodology used, including the zero mass characteristics of the solar irradiance time series, generates a significant improvement over state of the art strategies. These results will help to better understand the fluctuating nature of solar energy forecasting, the underlying stochastic process, and quantify the potential of a photovoltaic (PV) energy generating system integration into a country electricity network. Experimental analysis and real data application substantiate the usage and convenience of the proposed methodology to forecast solar irradiance time series and solar energy across northern hemisphere, southern hemisphere, and equatorial zones.

Keywords: copula autoregressive, solar irradiance forecasting, solar energy forecasting, time series generation

Procedia PDF Downloads 322

Authors: Yoni Elviandri, Vivi Fitriyanti, Agung Surya Wijaya, Suryani Humayyah, Muhammad Alif Azizi

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The massive development of computing power and internet access nowadays is marked by audiovisual games and computers which are known as electronic games, one of the examples is online games. This kind of game can be found everywhere in Indonesia, both in the cities and even the villages. In the present time, online games are becoming a popular games in various layers of the community, one of them does happen to elementary school students. As the online games spread over, the traditional games gradually fade away and even thought as an old-fashioned game. Contrary, traditional games actually have the better and higher educational values such as patience, honesty, integrity and togetherness value which cannot be found in online games which are more to individualist. A brand new set of education tools is necessary to provide a convenience, safe and fun place for children to play around but still contains educational values. One interesting example goes to Cilulaba is an agricultural-based playground. It is a good place for children to play and learn as it was planned to entertain children to play around as well as introducing agriculture to them. One of the games is a 1990’s well-known traditional game which its name is Congklak. Congklak is an agricultural-based traditional game and it also introduces the home garden to the children. Some of the Cilulaba’s aims are to protect the existence of nation’s cultural inheritance through Congklak traditional game, as a tool to introduce the agriculture to the children through the methods of Congklak traditional game and giving explanation related to the advantages of a “healthy home garden” to the children. The expected output from this place is to deliver a good understanding about agriculture to the children and make them begin to love it to make an aesthetic home garden and enhance the optimalisation usage of home garden that will support the availability of various edible plants in productive and health households. The proposed method in this Student Creative Program in Society Service is Participatory Rural Appraisal (PRA) method.

Keywords: Cilubaba, Congklak, traditional game, agricultural-based playground

Procedia PDF Downloads 440

Authors: W. A. Gonçalves, E. P. Souza, C. R. Alcântara

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The ISCCP-Tracking database offers an opportunity to study physical and morphological characteristics of Convective Systems based on geostationary meteorological satellites. This database contains 26 years of tracking of Convective Systems for the entire globe. Then, Tropical Squall Lines which occur in Brazil are certainly within the database. In this study, we propose a methodology for identification of these systems based on the ISCCP-Tracking database. A physical and morphological characterization of these systems is also shown. The proposed methodology is firstly based on the year of 2007. The Squall Lines were subjectively identified by visually analyzing infrared images from GOES-12. Based on this identification, the same systems were identified within the ISCCP-Tracking database. It is known, and it was also observed that the Squall Lines which occur on the north coast of Brazil develop parallel to the coast, influenced by the sea breeze. In addition, it was also observed that the eccentricity of the identified systems was greater than 0.7. Then, a methodology based on the inclination (based on the coast) and eccentricity (greater than 0.7) of the Convective Systems was applied in order to identify and characterize Tropical Squall Lines in Brazil. These thresholds were applied back in the ISCCP-Tracking database for the year of 2007. It was observed that other systems, which were not Squall Lines, were also identified. Then, we decided to call all systems identified by the inclination and eccentricity thresholds as Linear Convective Systems, instead of Squall Lines. After this step, the Linear Convective Systems were identified and characterized for the entire database, from 1983 to 2008. The physical and morphological characteristics of these systems were compared to those systems which did not have the required inclination and eccentricity to be called Linear Convective Systems. The results showed that the convection associated with the Linear Convective Systems seems to be more intense and organized than in the other systems. This affirmation is based on all ISCCP-Tracking variables analyzed. This type of methodology, which explores 26 years of satellite data by an objective analysis, was not previously explored in the literature. The physical and morphological characterization of the Linear Convective Systems based on 26 years of data is of a great importance and should be used in many branches of atmospheric sciences.

Keywords: squall lines, convective systems, linear convective systems, ISCCP-Tracking

Procedia PDF Downloads 299

Authors: Rahul Paul, Peter Mctaggart, Luke Skinner

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Maintaining public safety and network reliability are the core objectives of all electricity distributors globally. For many electricity distributors, managing vegetation clearances from their above ground assets (poles and conductors) is the most important and costly risk mitigation control employed to meet these objectives. Light Detection And Ranging (LiDAR) is widely used by utilities as a cost-effective method to inspect their spatially-distributed assets at scale, often captured using high powered LiDAR scanners attached to fixed wing or rotary aircraft. The resulting 3D point cloud model is used by these utilities to perform engineering grade measurements that guide the prioritisation of vegetation cutting programs. Advances in computer vision and machine-learning approaches are increasingly applied to increase automation and reduce inspection costs and time; however, real-world LiDAR capture variables (e.g., aircraft speed and height) create complexity, noise, and missing data, reducing the effectiveness of these approaches. This paper proposes a method for identifying each conductor from LiDAR data via clustering methods that can precisely reconstruct conductors in complex real-world configurations in the presence of high levels of noise. It proposes 3D catenary models for individual clusters fitted to the captured LiDAR data points using a least square method. An iterative learning process is used to identify potential conductor models between pole pairs. The proposed method identifies the optimum parameters of the catenary function and then fits the LiDAR points to reconstruct the conductors.

Keywords: point cloud, LİDAR data, machine learning, computer vision, catenary curve, vegetation management, utility industry

Procedia PDF Downloads 99

Authors: Rawan A. Abdelrazeq, Ahmed M. Khalafallah, Nabil A. Kartam

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Selection of competent contractors for construction projects is usually accomplished through competitive bidding or negotiated contracting in which the contract bid price is the basic criterion for selection. The evaluation of contractor’s safety performance is still not a typical criterion in the selection process, despite the existence of various safety prequalification procedures. There is a critical need for practical and automated systems that enable owners and decision makers to evaluate contractor safety performance, among other important contractor selection criteria. These systems should ultimately favor safety-conscious contractors to be selected by the virtue of their past good safety records and current safety programs. This paper presents an exploratory sequential mixed-methods approach to develop a framework for an automated decision support system that evaluates contractor safety performance based on a multitude of indicators and metrics that have been identified through a comprehensive review of construction safety research, and a survey distributed to domain experts. The framework is developed in three phases: (1) determining the indicators that depict contractor current and past safety performance; (2) soliciting input from construction safety experts regarding the identified indicators, their metrics, and relative significance; and (3) designing a decision support system using relational database models to integrate the identified indicators and metrics into a system that assesses and rates the safety performance of contractors. The proposed automated system is expected to hold several advantages including: (1) reducing the likelihood of selecting contractors with poor safety records; (2) enhancing the odds of completing the project safely; and (3) encouraging contractors to exert more efforts to improve their safety performance and practices in order to increase their bid winning opportunities which can lead to significant safety improvements in the construction industry. This should prove useful to decision makers and researchers, alike, and should help improve the safety record of the construction industry.

Keywords: construction safety, contractor selection, decision support system, relational database

Procedia PDF Downloads 279