Search results for: computer aided sport training

Authors: Julia Baker

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Development plays a major role in stopping biodiversity loss. But the ‘silo species’ protection of legislation (where certain species are protected while many are not) means that development can be ‘legally compliant’ and result in biodiversity loss. ‘Net Gain’ (NG) policies can help overcome this by making it an absolute requirement that development causes no overall loss of biodiversity and brings a benefit. However, offsetting biodiversity losses in one location with gains elsewhere is controversial because people suspect ‘offsetting’ to be an easy way for developers to buy their way out of conservation requirements. Yet the good practice principles (GPP) of offsetting provide several advantages over existing legislation for protecting biodiversity from development. This presentation describes the learning from implementing NG approaches based on GPP. It regards major upgrades of the UK’s transport networks, which involved removing vegetation in order to construct and safely operate new infrastructure. While low-lying habitats were retained, trees and other habitats disrupting the running or safety of transport networks could not. Consequently, achieving NG within the transport corridor was not possible and offsetting was required. The first ‘lessons learnt’ were on obtaining a commitment from business leaders to go beyond legislative requirements and deliver NG, and on the institutional change necessary to embed GPP within daily operations. These issues can only be addressed when the challenges that biodiversity poses for business are overcome. These challenges included: biodiversity cannot be measured easily unlike other sustainability factors like carbon and water that have metrics for target-setting and measuring progress; and, the mindset that biodiversity costs money and does not generate cash in return, which is the opposite of carbon or waste for example, where people can see how ‘sustainability’ actions save money. The challenges were overcome by presenting the GPP of NG as a cost-efficient solution to specific, critical risks facing the business that also boost industry recognition, and by using government-issued NG metrics to develop business-specific toolkits charting their NG progress whilst ensuring that NG decision-making was based on rich ecological data. An institutional change was best achieved by supporting, mentoring and training sustainability/environmental managers for these ‘frontline’ staff to embed GPP within the business. The second learning was from implementing the GPP where business partnered with local governments, wildlife groups and land owners to support their priorities for nature conservation, and where these partners had a say in decisions about where and how best to achieve NG. From this inclusive approach, offsetting contributed towards conservation priorities when all collaborated to manage trade-offs between: -Delivering ecologically equivalent offsets or compensating for losses of one type of biodiversity by providing another. -Achieving NG locally to the development whilst contributing towards national conservation priorities through landscape-level planning. -Not just protecting the extent and condition of existing biodiversity but ‘doing more’. -The multi-sector collaborations identified practical, workable solutions to ‘in perpetuity’. But key was strengthening linkages between biodiversity measures implemented for development and conservation work undertaken by local organizations so that developers support NG initiatives that really count.

Keywords: biodiversity offsetting, development, nature conservation planning, net gain

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Authors: Aihong Zhao, Priya Sastry, Mark L Field, Mohamad Bashir, Arvind Singh, David Richens

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Objectives: Intramural haematoma (IMH) is one of the pathologies, along with acute aortic dissection, that present as Acute Aortic Syndrome (AAS). Evidence suggests that unlike aortic dissection, some intramural haematomas may regress with medical management. However, intramural haematomas have been traditionally managed like acute aortic dissections. Given that some of these pathologies may regress with conservative management, it would be useful to be able to identify which of these may not need high risk emergency intervention. A computational aortic model was used in this study to try and identify intramural haematomas with risk of progression to aortic dissection. Methods: We created a computational model of the aorta with luminal blood flow. Reports in the literature have identified 11 mm as the radial clot thickness that is associated with heightened risk of progression of intramural haematoma. Accordingly, haematomas of varying sizes were implanted in the modeled aortic wall to test this hypothesis. The model was exposed to physiological blood flows and the stresses and strains in each layer of the aortic wall were recorded. Results: Size and shape of clot were seen to affect the magnitude of aortic stresses. The greatest stresses and strains were recorded in the intima of the model. When the haematoma exceeded 10 mm in all dimensions, the stress on the intima reached breaking point. Conclusion: Intramural clot size appears to be a contributory factor affecting aortic wall stress. Our computer simulation corroborates clinical evidence in the literature proposing that IMH diameter greater than 11 mm may be predictive of progression. This preliminary report suggests finite element modelling of the aortic wall may be a useful process by which to examine putative variables important in predicting progression or regression of intramural haematoma.

Keywords: intramural haematoma, acute aortic syndrome, finite element analysis,

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Authors: Abdul-Rahman Al-Ali

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As the number of mobile devices is growing exponentially, it is estimated to connect about 50 million devices to the Internet by the year 2020. At the end of this decade, it is expected that an average of eight connected devices per person worldwide. The 50 billion devices are not mobile phones and data browsing gadgets only, but machine-to-machine and man-to-machine devices. With such growing numbers of devices the Internet of Things (I.o.T) concept is one of the emerging technologies as of recently. Within the smart grid technologies, smart home appliances, Intelligent Electronic Devices (IED) and Distributed Energy Resources (DER) are major I.o.T objects that can be addressable using the IPV6. These objects are called the smart grid internet of things (SG-I.o.T). The SG-I.o.T generates big data that requires high-speed computing infrastructure, widespread computer networks, big data storage, software, and platforms services. A company’s utility control and data centers cannot handle such a large number of devices, high-speed processing, and massive data storage. Building large data center’s infrastructure takes a long time, it also requires widespread communication networks and huge capital investment. To maintain and upgrade control and data centers’ infrastructure and communication networks as well as updating and renewing software licenses which collectively, requires additional cost. This can be overcome by utilizing the emerging computing paradigms such as cloud computing. This can be used as a smart grid enabler to replace the legacy of utilities data centers. The talk will highlight the role of I.o.T, cloud computing services and their development models within the smart grid technologies.

Keywords: intelligent electronic devices (IED), distributed energy resources (DER), internet, smart home appliances

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Authors: S. MacDougall-Davis, S. Wysling, R. Willmore

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Background: The application of good non-technical skills, also known as crew resource management (CRM), is central to the delivery of safe, effective healthcare. The authors have been running remote trauma courses for over 10 years, primarily focussing on developing participants’ CRM in time-critical, high-stress clinical situations. The course has undergone an iterative process over the past 10 years. We employ a number of experiential learning techniques for improving CRM, including small group workshops, military command tasks, high fidelity simulations with reflective debriefs, and a ‘flipped classroom’, where participants are asked to create their own simulations and assess and debrief their colleagues’ CRM. We created a randomised simulation study to assess the impact of our course on UK medical students’ CRM, both at an individual and a teams level. Methods: Sixteen students took part. Four clinical scenarios were devised, designed to be of similar urgency and complexity. Professional moulage effects and experienced clinical actors were used to increase fidelity and to further simulate high-stress environments. Participants were block randomised into teams of 4; each team was randomly assigned to one pre-course simulation. They then underwent our 5 day remote trauma CRM course. Post-course, students were re-randomised into four new teams; each was randomly assigned to a post-course simulation. All simulations were videoed. The footage was reviewed by two independent CRM-trained assessors, who were blinded to the before/after the status of the simulations. Assessors used the internationally validated team emergency assessment measure (TEAM) to evaluate key areas of team performance, as well as a global outcome rating. Prior to the study, assessors had scored two unrelated scenarios using the same assessment tool, demonstrating 89% concordance. Participants also completed pre- and post-course questionnaires. Likert scales were used to rate individuals’ perceived NTS ability and their confidence to work in a team in time-critical, high-stress situations. Results: Following participation in the course, a significant improvement in CRM was observed in all areas of team performance. Furthermore, the global outcome rating for team performance was markedly improved (40-70%; mean 55%), thus demonstrating an impact at Level 4 of Kirkpatrick’s hierarchy. At an individual level, participants’ self-perceived CRM improved markedly after the course (35-70% absolute improvement; mean 55%), as did their confidence to work in a team in high-stress situations. Conclusion: Our study demonstrates that with a short, cost-effective course, using easily reproducible teaching sessions, it is possible to significantly improve participants’ CRM skills, both at an individual and, perhaps more importantly, at a teams level. The successful functioning of multi-disciplinary teams is vital in a healthcare setting, particularly in high-stress, time-critical situations. Good CRM is of paramount importance in these scenarios. The authors believe that these concepts should be introduced from the earliest stages of medical education, thus promoting a culture of effective CRM and embedding an early appreciation of the importance of these skills in enabling safe and effective healthcare.

Keywords: crew resource management, non-technical skills, training, simulation

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Authors: Phenphak Horadee, Rodchares Hanrinth, Saithip Suttiruksa

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Inappropriate use of antibiotics has happened in several hospitals, Thailand. Drug use evaluation (DUE) is one strategy to overcome this difficulty. However, most community hospitals still encounter incomplete evaluation resulting overuse of antibiotics with high cost. Consequently, drug-resistant bacteria have been rising due to inappropriate antibiotic use. The aim of this study was to involve stakeholders in conceptualizing, developing, and prioritizing a feasible intervention strategy to promote and support appropriate antibiotic prescribing in a community hospital, Thailand. Study antibiotics included four antibiotics such as Meropenem, Piperacillin/tazobactam, Amoxicillin/clavulanic acid, and Vancomycin. The study was conducted for the 1-year period between March 1, 2018, and March 31, 2019, in a community hospital in the northeastern part of Thailand. Concept mapping was used in a purposive sample, including doctors (one was an administrator), pharmacists, and nurses who involving drug use evaluation of antibiotics. In-depth interviews for each participant and survey research were conducted to seek the problems for inappropriate use of antibiotics based on drug use evaluation system. Seventy-seven percent of DUE reported appropriate antibiotic prescribing, which still did not reach the goal of 80 percent appropriateness. Meropenem led other antibiotics for inappropriate prescribing. The causes of the unsuccessful DUE program were classified into three themes such as personnel, lack of public relation and communication, and unsupported policy and impractical regulations. During the first meeting, stakeholders (n = 21) expressed the generation of interventions. During the second meeting, participants who were almost the same group of people in the first meeting (n = 21) were requested to independently rate the feasibility and importance of each idea and to categorize them into relevant clusters to facilitate multidimensional scaling and hierarchical cluster analysis. The outputs of analysis included the idealist, cluster list, point map, point rating map, cluster map, and cluster rating map. All of these were distributed to participants (n = 21) during the third meeting to reach consensus on an intervention model. The final proposed intervention strategy included 29 feasible and crucial interventions in seven clusters: development of information technology system, establishing policy and taking it into the action plan, proactive public relations of the policy, action plan and workflow, in cooperation of multidisciplinary teams in drug use evaluation, work review and evaluation with performance reporting, promoting and developing professional and clinical skill for staff with training programs, and developing practical drug use evaluation guideline for antibiotics. These interventions are relevant and fit to several intervention strategies for antibiotic stewardship program in many international organizations such as participation of the multidisciplinary team, developing information technology to support antibiotic smart use, and communication. These interventions were prioritized for implementation over a 1-year period. Once the possibility of each activity or plan is set up, the proposed program could be applied and integrated into hospital policy after evaluating plans. Effectiveness of each intervention could be promoted to other community hospitals to promote and support antibiotic smart use.

Keywords: antibiotic, concept mapping, drug use evaluation, multidisciplinary teams

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Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

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Existing buildings are permanently subjected to change, continuously renovated and repaired in their long service life. Old buildings are destroyed and their material and components are recycled or reused for constructing new ones. In this process, the importance of sustainability principles for building construction is obviously known and great significance must be attached to the consumption of resources, resulting effects on the environment and economic costs. Utilization strategies for extending buildings service life and delay in destroying have a positive effect on environment protection. In addition, simpler alterability or expandability of buildings’ structures and reducing energy and natural resources consumption have benefits for users, producers and the environment. To solve these problems, by applying theories of open building, structural components of some conventional building systems have been analyzed and then, a new geometry adaptive building system is developed which can transform and support different imposed loads. In order to achieve this goal, various research methods and tools such as professional and scientific literatures review, comparative analysis, case study and computer simulation were applied and data interpretation was implemented using descriptive statistics and logical arguments. Therefore, hypothesis and proposed strategies were evaluated and an adaptable and reusable 2-dimensional building system was presented which can respond appropriately to dwellers and end-users needs and provide reusability of structural components of building system in new construction or function. Investigations showed that this incremental building system can be successfully applied in achieving the architectural design objectives and by small modifications on components and joints, it is easy to obtain different and adaptable load-optimized component alternatives for flexible spaces.

Keywords: adaptability, durability, open building, service life, structural building system

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Authors: Felicity Aphiwe Mkhongi, Walter Musakwa

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Smallholder crop production is a defining factor in achieving food security, particularly at the household level. However, the number of abandoned arable fields is increasing in communal areas of South Africa. While substantial efforts have been devoted to addressing food insecurity in the country, ownership of arable land has not been supplemented with sustainable food production for households. This paper analyses household food security in the context of deagrarianization in two villages, Ambros (Eastern Cape) and Maramanzhi (Limpopo). Semi-structured questionnaires were administered to acquire both qualitative and quantitative data from 106 heads of households. The IBM SPSS Statistics 28.0 computer program was applied to complete data analysis. From the findings of the study, it was evident that compared to arable fields, a greater proportion of households own home-gardens with an average size of 2100m in Ambros and 3400m in Maramanzhi village. The majority of arable fields were abandoned, particularly in Ambros village. Household food access challenges were measured using the Household Food Insecurity Access Scale (HFIAS). This food security indicator revealed that the majority of households were mildly food insecure owing to food shortages emanating from insufficient monthly income and waning household crop production. Food was rated as a very important reason for engaging in cultivation in both villages of the study, but deagrarianization has eroded opportunities for increasing household crop production. Among other possible solutions, this study recommends that the government invest more in agriculture to allow for sustainable strategies that revive abandoned arable land, such as arable fields in communal areas of South Africa, as this could increase food production for households.

Keywords: cultivation, deagrarianization, food security, rural households, smallholder farmers

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Authors: Ramin Rezaei, Terry Ng, Abdollah Afjeh

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Near wake development of a wind turbine affects the aerodynamic loads on the tower and the wind turbine. Design considerations of both isolated wind turbines and wind farms must include unsteady wake flow conditions under which the turbines must operate. The consequent aerodynamic loads could lead to over design of wind turbines and adversely affect the cost of wind turbines and, in turn, the cost of energy produced by wind turbines. Reducing the weight of turbine rotors is particularly desirable since larger wind turbine rotors can be utilized without significantly increasing the cost of the supporting structure. Larger rotor diameters produce larger swept areas and consequently greater energy production from the wind thereby reducing the levelized cost of wind energy. To understand the development and structure of the near tower wake of a wind turbine, an experimental study was conducted to describe the flow field of the near wake for both upwind and downwind turbines. The study was conducted under controlled environment of a wind tunnel using a scaled model of a turbine. The NREL 5 MW reference wind turbine was used as a baseline design and was modified as necessary to design and build upwind and downwind scaled wind turbine models. This paper presents the results of the wind tunnel study using turbine models to quantify the near wake of upwind and downwind wind turbine configurations for various lengths of tower-to-turbine spacing. The variations of mean velocity and turbulence are measured using a computer-controlled, traversing hot wire probe. Additionally, smoke flow visualizations were conducted to qualitatively study the wake. The results show a more rapid dissipation of the near wake for an upwind configuration. The results can readily be incorporated into low fidelity system level turbine simulation tools to more accurately account for the wake on the aerodynamic loads of a upwind and downwind turbines.

Keywords: hot wire anemometry, near wake, upwind and downwind turbine. Hot wire anemometry, near wake, upwind and downwind turbine

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Authors: Wallyson Thomas, Zsombor Fulop, Attila Szilagyi

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Impact dampers are mainly used in the metal-mechanical industry in operations that generate too much vibration in the machining system. Internal turning processes become unstable during the machining of deep holes, in which the tool holder is used with long overhangs (high length-to-diameter ratios). The devices coupled with active dampers, are expensive and require the use of advanced electronics. On the other hand, passive impact dampers (PID – Particle Impact Dampers) are cheaper alternatives that are easier to adapt to the machine’s fixation system, once that, in this last case, a cavity filled with particles is simply added to the structure of the tool holder. The cavity dimensions and the diameter of the spheres are pre-determined. Thus, when passive dampers are employed during the machining process, the vibration is transferred from the tip of the tool to the structure of the boring bar, where it is absorbed by the fixation system. This work proposes to compare the behaviors of a conventional solid boring bar and a boring bar with a passive impact damper in turning while using the highest possible L/D (length-to-diameter ratio) of the tool and an Easy Fix fixation system (also called: Split Bushing Holding System). It is also intended to optimize the impact absorption parameters, as the filling percentage of the cavity and the diameter of the spheres. The test specimens were made of hardened material and machined in a Computer Numerical Control (CNC) lathe. The laboratory tests showed that when the cavity of the boring bar is totally filled with minimally spaced spheres of the largest diameter, the gain in absorption allowed of obtaining, with an L/D equal to 6, the same surface roughness obtained when using the solid boring bar with an L/D equal to 3.4. The use of the passive particle impact damper resulted in, therefore, increased static stiffness and reduced deflexion of the tool.

Keywords: active damper, fixation system, hardened material, passive damper

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Authors: Dmitriy Chernov, Maria Karavassilis, Suhyoun Youn, Amna Izhar, Devasenan Devendra

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Introduction and Background: A well-structured and comprehensive departmental induction improves patient safety and job satisfaction amongst doctors. The aims of our Project were as follows: 1. Assess the perceived preparedness of junior doctors starting their rotation in Acute Medicine at Watford General Hospital. 2. Develop a supplemental Induction Guide and Pocket reference in the form of an iOS mobile application. 3. To collect feedback after implementing the mobile application following a trial period of 8 weeks with a small cohort of junior doctors. Materials and Methods: A questionnaire was distributed to all new junior trainees starting in the department of Acute Medicine to assess their experience of current induction. A mobile Induction application was developed and trialled over a period of 8 weeks, distributed in addition to the existing didactic induction session. After the trial period, the same questionnaire was distributed to assess improvement in induction experience. Analytics data were collected with users’ consent to gauge user engagement and identify areas of improvement of the application. A feedback survey about the app was also distributed. Results: A total of 32 doctors used the application during the 8-week trial period. The application was accessed 7259 times in total, with the average user spending a cumulative of 37 minutes 22 seconds on the app. The most used section was Clinical Guidelines, accessed 1490 times. The App Feedback survey revealed positive reviews: 100% of participants (n=15/15) responded that the app improved their overall induction experience compared to other placements; 93% (n=14/15) responded that the app improved overall efficiency in completing daily ward jobs compared to previous rotations; and 93% (n=14/15) responded that the app improved patient safety overall. In the Pre-App and Post-App Induction Surveys, participants reported: a 48% improvement in awareness of practical aspects of the job; a 26% improvement of awareness on locating pathways and clinical guidelines; a 40% reduction of feelings of overwhelmingness. Conclusions and recommendations: This study demonstrates the importance of technology in Medical Education and Clinical Induction. The mobile application average engagement time equates to over 20 cumulative hours of on-the-job training delivered to each user, within an 8-week period. The most used and referred to section was clinical guidelines. This shows that there is high demand for an accessible pocket guide for this type of material. This simple mobile application resulted in a significant improvement in feedback about induction in our Department of Acute Medicine, and will likely impact workplace satisfaction. Limitations of the application include: post-app surveys had a small number of participants; the app is currently only available for iPhone users; some useful sections are nested deep within the app, lacks deep search functionality across all sections; lacks real time user feedback; and requires regular review and updates. Future steps for the app include: developing a web app, with an admin dashboard to simplify uploading and editing content; a comprehensive search functionality; and a user feedback and peer ratings system.

Keywords: mobile app, doctor induction, medical education, acute medicine

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Authors: Dana Zelicha

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A 6-week mindfulness programme was launched to improve the well being and performance of 20 managers (including the supervisor) of an international corporation in London. A unique assessment methodology was customised to the organisation’s needs, measuring four parameters: prioritising skills, listening skills, mindfulness levels and happiness levels. All parameters showed significant improvements (p < 0.01) post intervention, with a remarkable increase in listening skills and mindfulness levels. Although corporate mindfulness programmes have proven to be effective, the challenge remains the low engagement levels at home and the implementation of these tools beyond the scope of the intervention. This study has offered an innovative approach to enforce home engagement levels, which yielded promising results. The programme launched with a 2-day introduction intervention, which was followed by a 6-week training course (1 day a week; 2 hours each). Participants learned all basic principles of mindfulness such as mindfulness meditations, Mindfulness Based Stress Reduction (MBSR) techniques and Mindfulness Based Cognitive Therapy (MBCT) practices to incorporate into their professional and personal lives. The programme contained experiential mindfulness meditations and innovative mindfulness tools (OWBA-MT) created by OWBA - The Well Being Agency. Exercises included Mindful Meetings, Unitasking and Mindful Feedback. All sessions concluded with guided discussions and group reflections. One fundamental element of this programme was engagement level outside of the workshop. In the office, participants connected with a mindfulness buddy - a team member in the group with whom they could find support throughout the programme. At home, participants completed online daily mindfulness forms that varied according to weekly themes. These customised forms gave participants the opportunity to reflect on whether they made time for daily mindfulness practice, and to facilitate a sense of continuity and responsibility. At the end of the programme, the most engaged team member was crowned the ‘mindful maven’ and received a special gift. The four parameters were measured using online self-reported questionnaires, including the Listening Skills Inventory (LSI), Mindfulness Attention Awareness Scale (MAAS), Time Management Behaviour Scale (TMBS) and a modified version of the Oxford Happiness Questionnaire (OHQ). Pre-intervention questionnaires were collected at the start of the programme, and post-intervention data was collected 4-weeks following completion. Quantitative analysis using paired T-tests of means showed significant improvements, with a 23% increase in listening skills, a 22% improvement in mindfulness levels, a 12% increase in prioritising skills, and an 11% improvement in happiness levels. Participant testimonials exhibited high levels of satisfaction and the overall results indicate that the mindfulness programme substantially impacted the team. These results suggest that 6-week mindfulness programmes can improve employees’ capacities to listen and work well with others, to effectively manage time and to experience enhanced satisfaction both at work and in life. Limitations noteworthy to consider include the afterglow effect and lack of generalisability, as this study was conducted on a small and fairly homogenous sample.

Keywords: corporate mindfulness, listening skills, organisational well being, prioritising skills, mindful leadership

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Authors: Dagmawit Tewahido

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Purpose: This qualitative study was conducted to explore social norms around adolescent girls’ marriage practices in West Hararghe, Ethiopia, where early marriage is prohibited by law. Methods: Twenty Focus Group Discussions were conducted with Married and Unmarried adolescent girls, adolescent boys and parents of girls using locally developed vignettes. A total of 32 in-depth interviews were conducted with married and unmarried adolescent girls, husbands of adolescent girls and mothers-in-law. Key informant interviews were conducted with 36 district officials. Data analysis was assisted by Open Code computer software. The Social Norms Analysis Plot (SNAP) framework developed by CARE guided the development and analysis of vignettes. A thematic data analysis approach was utilized to summarize the data. Results: Early marriage is seen as a positive phenomenon in our study context, and girls who are not married by the perceived ideal age of 15 are socially sanctioned. They are particularly influenced by their peers to marry. Marrying early is considered a chance given by God and a symbol of good luck. The two common types of marriage are decided: 1) by adolescent girl and boy themselves without seeking parental permission (’Jalaa-deemaa’- meaning ‘to go along’), and 2) by just informing girl’s parents (‘Cabsaa’- meaning ‘to break the culture’). Relatives and marriage brokers also arrange early marriages. Girls usually accept the first marriage proposal regardless of their age. Parents generally tend not to oppose marriage arrangements chosen by their daughters. Conclusions: In the study context social norms encourage early marriage despite the existence of a law prohibiting marriage before the age of eighteen years. Early marriage commonly happens through consensual arrangements between adolescent girls and boys. Interventions to reduce early marriage need to consider the influence of Reference Groups on the decision makers for marriages, especially girls’ own peers.

Keywords: adolescent girls, social norms, early marriage, Ethiopia

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Authors: Hammache Nadir

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The scientific study of human learning and memory is now more than 125 years old. Psychologists have conducted thousands of experiments, correlational analyses, and field studies during this time, in addition to other research conducted by those from neighboring fields. A huge knowledge base has been carefully built up over the decades. Given this backdrop, we may ask ourselves: What great changes in education have resulted from this huge research base? How has the scientific study of learning and memory changed practices in education from those of, say, a century ago? Have we succeeded in building a translational educational science to rival medical science (in which biological knowledge is translated into medical practice) or types of engineering (in which, e.g., basic knowledge in chemistry is translated into products through chemical engineering)? The answer, I am afraid, is rather mixed. Psychologists and psychological research have influenced educational practice, but in fits and starts. After all, some of the great founders of American psychology—William James, Edward L. Thorndike, John Dewey, and others—are also revered as important figures in the history of education. And some psychological research and ideas have made their way into education—for instance, computer-based cognitive tutors for some specific topics have been developed in recent years—and in years past, such practices as teaching machines, programmed learning, and, in higher education, the Keller Plan were all important. These older practices have not been sustained. Was that because they failed or because of a lack of systematic research showing they were effective? At any rate, in 2012, we cannot point to a well-developed translational educational science in which research about learning and memory, thinking and reasoning, and related topics is moved from the lab into controlled field trials (like clinical trials in medicine) and the tested techniques, if they succeed, are introduced into broad educational practice. We are just not there yet, and one question that arises is how we could achieve a translational educational science.

Keywords: affective, education, cognition, pshychology

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Authors: Antonio Pizzarello, Oris Friesen

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Networks, such as the electric power grid, must demonstrate exemplary performance and integrity. Integrity depends on the quality of both the system design model and the deployed software. Integrity of the deployed software is key, for both the original versions and the many that occur throughout numerous maintenance activity. Current software engineering technology and practice do not produce adequate integrity. Distributed systems utilize networks where each node is an independent computer system. The connections between them is realized via a network that is normally redundantly connected to guarantee the presence of a path between two nodes in the case of failure of some branch. Furthermore, at each node, there is software which may fail. Self-stabilizing protocols are usually present that recognize failure in the network and perform a repair action that will bring the node back to a correct state. These protocols first introduced by E. W. Dijkstra are currently present in almost all Ethernets. Super stabilization protocols capable of reacting to a change in the network topology due to the removal or addition of a branch in the network are less common but are theoretically defined and available. This paper describes how to use the Software Integrity Assessment (SIA) methodology to analyze self-stabilizing software. SIA is based on the UNITY formalism for parallel and distributed programming, which allows the analysis of code for verifying the progress property p leads-to q that describes the progress of all computations starting in a state satisfying p to a state satisfying q via the execution of one or more system modules. As opposed to demonstrably inadequate test and evaluation methods SIA allows the analysis and verification of any network self-stabilizing software as well as any other software that is designed to recover from failure without external intervention of maintenance personnel. The model to be analyzed is obtained by automatic translation of the system code to a transition system that is based on the use of the weakest precondition.

Keywords: network, power grid, self-stabilization, software integrity assessment, UNITY, weakest precondition

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Authors: Durga Toshniwal, Lokesh Agrawal

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As the web continues to play an increasing role in information exchange, and conducting daily activities, computer users have become the target of miscreants which infects hosts with malware or adware for financial gains. Unfortunately, even a single visit to compromised web site enables the attacker to detect vulnerabilities in the user’s applications and force the downloading of multitude of malware binaries. We provide an approach to effectively scan the so-called drive-by downloads on the Internet. Drive-by downloads are result of URLs that attempt to exploit their visitors and cause malware to be installed and run automatically. To scan the web for malicious pages, the first step is to use a crawler to collect URLs that live on the Internet, and then to apply fast prefiltering techniques to reduce the amount of pages that are needed to be examined by precise, but slower, analysis tools (such as honey clients or antivirus programs). Although the technique is effective, it requires a substantial amount of resources. A main reason is that the crawler encounters many pages on the web that are legitimate and needs to be filtered. In this paper, to characterize the nature of this rising threat, we present implementation of a web crawler on Python, an approach to search the web more efficiently for pages that are likely to be malicious, filtering benign pages and passing remaining pages to antivirus program for detection of malwares. Our approaches starts from an initial seed of known, malicious web pages. Using these seeds, our system generates search engines queries to identify other malicious pages that are similar to the ones in the initial seed. By doing so, it leverages the crawling infrastructure of search engines to retrieve URLs that are much more likely to be malicious than a random page on the web. The results shows that this guided approach is able to identify malicious web pages more efficiently when compared to random crawling-based approaches.

Keywords: web crawler, malwares, seeds, drive-by-downloads, security

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 69

Authors: Jayanthi Rajendran

Abstract:

Experience is what makes a man perfect. Though we tend to learn many a different things in life through practice still we need to go an extra mile to gain experience which would be profitable only when it is integrated with regular practice. A clear phenomenal idea is that every teacher is a learner. The centralized idea of this paper would focus on the integrated practices carried out among the students of Jizan University which enhances learning through experiences. Integrated practices like student-directed activities, balanced curriculum, phonological based activities and use of consistent language would enlarge the vision and mission of students to earn experience through learning. Students who receive explicit instruction and guidance could practice the skills and strategies through student-directed activities such as peer tutoring and cooperative learning. The second effective practice is to use consistent language. Consistent language provides students a model for talking about the new concepts which also enables them to communicate without hindrances. Phonological awareness is an important early reading skill for all students. Students generally have phonemic awareness in their home language can often transfer that knowledge to a second language. And also a balanced curriculum requires instruction in all the elements of reading. Reading is the most effective skill when both basic and higher-order skills are included on a daily basis. Computer based reading and listening skills will empower students to understand a language in a better way. English language learners can benefit from sound reading instruction even before they are fully proficient in English as long as the instruction is comprehensible. Thus, if students have to be well equipped in learning they should foreground themselves in various integrated practices through multifarious experience for which teachers are moderators and trainers. This type of learning prepares the students for a constantly changing society which helps them to meet the competitive world around them for better employability fulfilling the vision and mission of the institution.

Keywords: consistent language, employability, phonological awareness, balanced curriculum

Procedia PDF Downloads 401

Authors: Ashok Kumar Lonavath, V. Sathish Kumar

Abstract:

Urban sprawl is the uncontrolled and uncoordinated outgrowth of towns and cities. The process of urban sprawl can be described by change in pattern over time, like proportional increase in built-up surface to population leading to rapid urban spatial expansion. Significant economic and livelihood opportunities in the urban areas results in lack of basic amenities due to the unplanned growth The patterns, processes, dynamic causes and consequences of sprawl can be explored and designed with the help of spatial planning support system. In India context the urban area is defined as the population more than 5000, density more than 400 persons per sq. km and 75% of the population is involved in non-agricultural occupations. India’s urban population is increasing at the rate of 2.35% pa. The class I town’s population of India according to 2011 census is 18.8% that accounts for 60.4% of total unban population. Similarly in Erstwhile Andhra Pradesh it is 22.9% which accounts for 68.8% of total urban population. Suryapet town has historical recognition as ‘Gate Way of Telangana’ in the Indian State of Andhra Pradesh. The Municipality was constituted in 1952 as Grade-III, later upgraded into Grade-II in 1984 and to Grade-I in 1998. The area is 35 Sq.kms. Three major tanks located in three different directions and Musi River is flowing from a distance of 8 kms. The average ground water table is about 50m below ground. It is a fast growing town with a population of 1, 06,805 and 25,448 households. Density is 3051pp sq km, It is a Class I city as per population census. It secured the ISO 14001-2004 certificate for establishing and maintaining an environment-friendly system for solid waste disposal. It is the first municipality in the country to receive such a certificate. It won HUDCO award under environment management, award of appreciation and cash from Ministry of Housing and Poverty Elevation from Government of India and undivided Andhra Pradesh under UN Human Settlement Programme, Greentech Excellance award, Supreme Courts appreciation for solid waste management. Foreign delegates from different countries and also from various other states of India visited Suryapet municipality for study tour and training programs as part of their official visit Suryapet is located at 17°5’ North Latitude and 79°37’ East Longitude. The average elevation is 266m, annual mean temperature is 36°C and average rainfall is 821.0 mm. The people of this town are engaged in Commercial and agriculture activities hence the town has become a centre for marketing and stocking agricultural produce. It is also educational centre in this region. The present paper on urban sprawl is a theoretical framework to analyze the interaction of planning and governance on the extent of outgrowth and level of services. The GIS techniques, SOI Toposheet, satellite imageries and image analysis techniques are extensively used to explore the sprawl and measure the urban land-use. This paper concludes outlining the challenges in addressing urban sprawl while ensuring adequate level of services that planning and governance have to ensure towards achieving sustainable urbanization.

Keywords: remote sensing, GIS, urban sprawl, urbanization

Procedia PDF Downloads 229

Authors: P. J. Sweeney, T. Ahtoniemi, J. Puoliväli, T. Laitinen, K. Lehtimäki, A. Nurmi, D. Wells

Abstract:

Duchenne muscular dystrophy (DMD) is caused by an X linked mutation in the dystrophin gene; lack of dystrophin causes a progressive muscle necrosis which leads to a progressive decrease in mobility in those suffering from the disease. The MDX mouse, a mutant mouse model which displays a frank dystrophinopathy, is currently widely employed in pre clinical efficacy models for treatments and therapies aimed at DMD. In general the end-points examined within this model have been based on invasive histopathology of muscles and serum biochemical measures like measurement of serum creatine kinase (sCK). It is established that a “critical period” between 4 and 6 weeks exists in the MDX mouse when there is extensive muscle damage that is largely sub clinical but evident with sCK measurements and histopathological staining. However, a full characterization of the MDX model remains largely incomplete especially with respect to the ability to aggravate of the muscle damage beyond the critical period. The purpose of this study was to attempt to aggravate the muscle damage in the MDX mouse and to create a wider, more readily translatable and discernible, therapeutic window for the testing of potential therapies for DMD. The study consisted of subjecting 15 male mutant MDX mice and 15 male wild-type mice to an intense chronic exercise regime that consisted of bi-weekly (two times per week) treadmill sessions over a 12 month period. Each session was 30 minutes in duration and the treadmill speed was gradually built up to 14m/min for the entire session. Baseline plasma creatine kinase (pCK), treadmill training performance and locomotor activity were measured after the “critical period” at around 10 weeks of age and again at 14 weeks of age, 6 months, 9 months and 12 months of age. In addition, kinematic gait analysis was employed using a novel analysis algorithm in order to compare changes in gait and fine motor skills in diseased exercised MDX mice compared to exercised wild type mice and non exercised MDX mice. In addition, a morphological and metabolic profile (including lipid profile), from the muscles most severely affected, the gastrocnemius muscle and the tibialis anterior muscle, was also measured at the same time intervals. Results indicate that by aggravating or exacerbating the underlying muscle damage in the MDX mouse by exercise a more pronounced and severe phenotype in comes to light and this can be picked up earlier by kinematic gait analysis. A reduction in mobility as measured by open field is not apparent at younger ages nor during the critical period, but changes in gait are apparent in the mutant MDX mice. These gait changes coincide with pronounced morphological and metabolic changes by non-invasive anatomical MRI and proton spectroscopy (1H-MRS) we have reported elsewhere. Evidence of a progressive asymmetric pathology in imaging parameters as well as in the kinematic gait analysis was found. Taken together, the data show that chronic exercise regime exacerbates the muscle damage beyond the critical period and the ability to measure through non-invasive means are important factors to consider when performing preclinical efficacy studies in the MDX mouse.

Keywords: Gait, muscular dystrophy, Kinematic analysis, neuromuscular disease

Procedia PDF Downloads 276

Authors: Dmytro Zubov, Francesco Volponi

Abstract:

In this paper, D-Wave quantum computing Ising model is used for the forecasting of positive extremes of daily mean air temperature. Forecast models are designed with two to five qubits, which represent 2-, 3-, 4-, and 5-day historical data respectively. Ising model’s real-valued weights and dimensionless coefficients are calculated using daily mean air temperatures from 119 places around the world, as well as sea level (Aburatsu, Japan). In comparison with current methods, this approach is better suited to predict heat wave values because it does not require the estimation of a probability distribution from scarce observations. Proposed forecast quantum computing algorithm is simulated based on traditional computer architecture and combinatorial optimization of Ising model parameters for the Ronald Reagan Washington National Airport dataset with 1-day lead-time on learning sample (1975-2010 yr). Analysis of the forecast accuracy (ratio of successful predictions to total number of predictions) on the validation sample (2011-2014 yr) shows that Ising model with three qubits has 100 % accuracy, which is quite significant as compared to other methods. However, number of identified heat waves is small (only one out of nineteen in this case). Other models with 2, 4, and 5 qubits have 20 %, 3.8 %, and 3.8 % accuracy respectively. Presented three-qubit forecast model is applied for prediction of heat waves at other five locations: Aurel Vlaicu, Romania – accuracy is 28.6 %; Bratislava, Slovakia – accuracy is 21.7 %; Brussels, Belgium – accuracy is 33.3 %; Sofia, Bulgaria – accuracy is 50 %; Akhisar, Turkey – accuracy is 21.4 %. These predictions are not ideal, but not zeros. They can be used independently or together with other predictions generated by different method(s). The loss of human life, as well as environmental, economic, and material damage, from extreme air temperatures could be reduced if some of heat waves are predicted. Even a small success rate implies a large socio-economic benefit.

Keywords: heat wave, D-wave, forecast, Ising model, quantum computing

Procedia PDF Downloads 500

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

Procedia PDF Downloads 90

Authors: Rahul Jain, Pradhir Parmar, Dhruvesh Patel

Abstract:

Planning and drawing are the important aspects of civil engineering. For testing theories about spatial location and interaction between land uses and related activities the computer based solution of urban models are used. The planner’s primary interest is in creation of 3D models of building and to obtain the terrain surface so that he can do urban morphological mappings, virtual reality, disaster management, fly through generation, visualization etc. 3D city models have a variety of applications in urban studies. Gujarat International Finance Tec-City (GIFT) is an ongoing construction site between Ahmedabad and Gandhinagar, Gujarat, India. It will be built on 3590000 m2 having a geographical coordinates of North Latitude 23°9’5’’N to 23°10’55’’ and East Longitude 72°42’2’’E to 72°42’16’’E. Therefore to develop 3D city models of GIFT city, the base map of the city is collected from GIFT office. Differential Geographical Positioning System (DGPS) is used to collect the Ground Control Points (GCP) from the field. The GCP points are used for the registration of base map in QGIS. The registered map is projected in WGS 84/UTM zone 43N grid and digitized with the help of various shapefile tools in QGIS. The approximate height of the buildings that are going to build is collected from the GIFT office and placed on the attribute table of each layer created using shapefile tools. The Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global (30 m X 30 m) grid data is used to generate the terrain of GIFT city. The Google Satellite Map is used to place on the background to get the exact location of the GIFT city. Various plugins and tools in QGIS are used to convert the raster layer of the base map of GIFT city into 3D model. The fly through tool is used for capturing and viewing the entire area in 3D of the city. This paper discusses all techniques and their usefulness in 3D city model creation from the GCP, base map, SRTM and QGIS.

Keywords: 3D model, DGPS, GIFT City, QGIS, SRTM

Procedia PDF Downloads 247

Authors: Thilini M. Yatanwala

Abstract:

CCTV (Closed-Circuit-Television) Surveillance System is being used in public places over decades and a large variety of data is being produced every moment. However, most of the CCTV data is stored in isolation without having integrity. As a result, identification of the behavior of suspicious people along with their location has become strenuous. This research was conducted to acquire more accurate and reliable timely information from the CCTV video records. The implemented system can identify human objects in public places based on outfit colors. Inter-process communication technologies were used to implement the CCTV camera network to track people in the premises. The research was conducted in three stages and in the first stage human objects were filtered from other movable objects available in public places. In the second stage people were uniquely identified based on their outfit colors and in the third stage an individual was continuously tracked in the CCTV network. A face detection algorithm was implemented using cascade classifier based on the training model to detect human objects. HAAR feature based two-dimensional convolution operator was introduced to identify features of the human face such as region of eyes, region of nose and bridge of the nose based on darkness and lightness of facial area. In the second stage outfit colors of human objects were analyzed by dividing the area into upper left, upper right, lower left, lower right of the body. Mean color, mod color and standard deviation of each area were extracted as crucial factors to uniquely identify human object using histogram based approach. Color based measurements were written in to XML files and separate directories were maintained to store XML files related to each camera according to time stamp. As the third stage of the approach, inter-process communication techniques were used to implement an acknowledgement based CCTV camera network to continuously track individuals in a network of cameras. Real time analysis of XML files generated in each camera can determine the path of individual to monitor full activity sequence. Higher efficiency was achieved by sending and receiving acknowledgments only among adjacent cameras. Suspicious incidents such as a person staying in a sensitive area for a longer period or a person disappeared from the camera coverage can be detected in this approach. The system was tested for 150 people with the accuracy level of 82%. However, this approach was unable to produce expected results in the presence of group of people wearing similar type of outfits. This approach can be applied to any existing camera network without changing the physical arrangement of CCTV cameras. The study of human identification and suspicious incident detection using outfit color analysis can achieve higher level of accuracy and the project will be continued by integrating motion and gait feature analysis techniques to derive more information from CCTV videos.

Keywords: CCTV surveillance, human detection and identification, image processing, inter-process communication, security, suspicious detection

Procedia PDF Downloads 183

Authors: Felix Darko-Amoah, Daniel Acquah

Abstract:

In contemporary ecosystems for developing countries like Ghana, the need to explore innovative solutions for sustainable livelihoods of farmers is more important than ever. With Ghana’s population growing steadily and the demand for food, fiber and shelter increasing, it is imperative that the construction industry and agriculture come together to address the challenges faced by farmers in the country. In order to enhance the livelihoods of cocoa farmers in Ghana, this paper provides an innovative strategy that aims to integrate the areas of civil engineering and cash crop agriculture. This study focuses on cocoa cultivation in poorer nations, where farmers confront a variety of difficulties include restricted access to financing, subpar infrastructure, and insufficient support services. We seek to improve farmers' access to financing, improve infrastructure, and provide support services that are essential to their success by combining the fields of building engineering and cocoa production. The findings of the study are beneficial to cocoa producers, community extension agents, and construction engineers. In order to accomplish our objectives, we conducted 307 of field investigations in particular cocoa growing communities in the Western Region of Ghana. Several studies have shown that there is a lack of adequate infrastructure and financing, leading to low yields, subpar beans, and low farmer profitability in developing nations like Ghana. Our goal is to give farmers access to better infrastructure, better financing, and support services that are crucial to their success through the fusion of construction engineering and cocoa production. Based on data gathered from the field investigations, the results show that the employment of appropriate technology and methods for developing structures, roads, and other infrastructure in rural regions is one of the essential components of this strategy. For instance, we find that using affordable, environmentally friendly materials like bamboo, rammed earth, and mud bricks can assist to cut expenditures while also protecting the environment. By applying simple relational techniques to the data gathered, the results also show that construction engineers are crucial in planning and building infrastructure that is appropriate for the local environment and circumstances and resilient to natural disasters like floods. Thus, the convergence of construction engineering and cash crop cultivation is another crucial component of the agriculture-construction interplay. For instance, farmers can receive financial assistance to buy essential inputs, such as seeds, fertilizer, and tools, as well as training in proper farming methods. Moreover, extension services can be offered to assist farmers in marketing their crops and enhancing their livelihoods and revenue. In conclusion, our analysis of responses from the 307 participants depicts that the combination of construction engineering and cash crop agriculture offers an innovative approach to improving farmers' livelihoods in cocoa farming communities in Ghana. In conclusion, by inculcating the findings of this study into core decision-making, policymakers can help farmers build sustainable and profitable livelihoods by addressing challenges such as limited access to financing, poor infrastructure, and inadequate support services.

Keywords: cocoa agriculture, construction engineering, farm buildings and equipment, improved livelihoods of farmers

Procedia PDF Downloads 90

Authors: Asrat M.Belachew, Tiago Pereira, Institute of Mathematics, Computer Sciences, Avenida Trabalhador São Carlense, 400, São Carlos, 13566-590, Brazil

Abstract:

Infectious diseases are among the most prominent threats to human beings. They cause morbidity and mortality to an individual and collapse the social, economic, and political systems of the whole world collectively. Mathematical models are fundamental tools and provide a comprehensive understanding of how infectious diseases spread and designing the control strategy to mitigate infectious diseases from the host population. Modeling the spread of infectious diseases using a compartmental model of inhomogeneous populations is good in terms of complexity. However, in the real world, there is a situation that accounts for heterogeneity, such as ages, locations, and contact patterns of the population which are ignored in a homogeneous setting. In this work, we study how classical an SEIR infectious disease spreading of the compartmental model can be extended by incorporating the mobility of population between heterogeneous cities during an outbreak of infectious disease. We have formulated an SEIR multi-cities epidemic spreading model using a system of 4k ordinary differential equations to describe the disease transmission dynamics in k-cities during the day and night. We have shownthat the model is epidemiologically (i.e., variables have biological interpretation) and mathematically (i.e., a unique bounded solution exists all the time) well-posed. We constructed the next-generation matrix (NGM) for the model and calculated the basic reproduction number R0for SEIR-epidemic spreading model with cities mobility. R0of the disease depends on the spectral radius mobility operator, and it is a threshold between asymptotic stability of the disease-free equilibrium and disease persistence. Using the eigenvalue perturbation theorem, we showed that sending a fraction of the population between cities decreases the reproduction number of diseases in interconnected cities. As a result, disease transmissiondecreases in the population.

Keywords: SEIR-model, mathematical model, city mobility, epidemic spreading

Procedia PDF Downloads 109

Authors: Liliia N. Butymova, Vladimir Y. Modorsky, Nikolai A. Shevelev

Abstract:

Prediction of vibration processes in gas transmittal units (GTU) is an urgent problem. Despite numerous scientific publications on the problem of vibrations in general, there are not enough works concerning FSI-modeling interaction processes between several deformable blades in gas-dynamic flow. Since it is very difficult to solve the problem in full scope, with all factors considered, a unidirectional dynamic coupled 1FSI model is suggested for use at the first stage, which would include, from symmetry considerations, two blades, which might be considered as the first stage of solving more general bidirectional problem. ANSYS CFX programmed multi-processor was chosen as a numerical computation tool. The problem was solved on PNRPU high-capacity computer complex. At the first stage of the study, blades were believed oscillating with the same frequency, although oscillation phases could be equal and could be different. At that non-stationary gas-dynamic forces distribution over the blades surfaces is calculated in run of simulation experiment. Oscillations in the “gas — structure” dynamic system are assumed to increase if the resultant of these gas-dynamic forces is in-phase with blade oscillation, and phase shift (φ=0). Provided these oscillation occur with phase shift, then oscillations might increase or decrease, depending on the phase shift value. The most important results are as follows: the angle of phase shift in inter-blade oscillation and the gas-dynamic force depends on the flow velocity, the specific inter-blade gap, and the shaft rotation speed; a phase shift in oscillation of adjacent blades does not always correspond to phase shift of gas-dynamic forces affecting the blades. Thus, it was discovered, that asynchronous oscillation of blades might cause either attenuation or intensification of oscillation. It was revealed that clocking effect might depend not only on the mutual circumferential displacement of blade rows and the gap between the blades, but also on the blade dynamic deformation nature.

Keywords: aeroelasticity, ANSYS CFX, oscillation, phase shift, clocking effect, vibrations

Procedia PDF Downloads 269

Authors: Susan Marie R. De La Cruz, Bernadette F. De La Cruz, Georgia D. Demavibas

Abstract:

This study determined the top 10 perceived students’ academic needs, personal needs, personal obstacles in achieving their academic goals, are as they need assistance, and their perceived feelings in math, reading and writing. The North Carolina State College, Student Support Services needs assessment survey was used. The respondents were the randomly chosen122Graduate school students. The top 10 academic needs are as follows: need to improve memory, communication skills, study habits, time management skills, career decisions, vocabulary, math skills, test taking skills, reading comprehension, and the need to reduce math anxiety. Top 10 personal needs are as follows: difficulty meeting deadline, difficulty managing money, inadequate computer skills, afraid of failing graduate school, difficulty participating in class/group discussions, absence from school, anxiety during exams, little or no experience with internet, personal counseling needs, and unsure of university academic procedures. Students’ top 10 perceived personal obstacles were as follows: issues surrounding sickness in family, lack of time management, lack of money, feeling tired, fears to speak in class, poor study habits, problems at home, late in class, too shy, and always feeling sick and easily distracted. Students felt need assistance in areas surrounding personal budget, stress management, motivation, anxiety, depressions, leadership development and goals/decision making. It is recommended that enrichment activities be provided to respond to students’ academic and personal needs. Also, Graduate School Guidance Counselor collaborates with other licensed Guidance Counselors in other colleges to have a well-coordinated and effective delivery of services responsive to students’ needs.

Keywords: academic needs, guidance counsellors, guidance service, needs assessment survey, personal needs, student services

Procedia PDF Downloads 337

Authors: Hiroshi Kinoshita, Yasuto Nakanishi, Ryuhei Okuno, Toshio Higashi

Abstract:

Various kinds of pegboards have been developed and used widely in research and clinics of rehabilitation for evaluation and training of patient’s hand function. A common measure in these peg boards is a total time of performance execution assessed by a tester’s stopwatch. Introduction of electrical and automatic measurement technology to the apparatus, on the other hand, has been delayed. The present work introduces the development of a pegboard with an electric sensor to detect moments of individual peg’s insertion and removal. The work also gives fundamental data obtained from a group of healthy young individuals who performed peg transfer tasks using the pegboard developed. Through trails and errors in pilot tests, two 10-hole peg-board boxes installed with a small photo-reflector and a DC amplifier at the bottom of each hole were designed and built by the present authors. The amplified electric analogue signals from the 20 reflectors were automatically digitized at 500 Hz per channel, and stored in a PC. The boxes were set on a test table at different distances (25, 50, 75, and 125 mm) in parallel to examine the effect of hole-to-hole distance. Fifty healthy young volunteers (25 in each gender) as subjects of the study performed successive fast 80 time peg transfers at each distance using their dominant and non-dominant hands. The data gathered showed a clear-cut light interruption/continuation moment by the pegs, allowing accurately (no tester’s error involved) and precisely (an order of milliseconds) to determine the pull out and insertion times of each peg. This further permitted computation of individual peg movement duration (PMD: from peg-lift-off to insertion) apart from hand reaching duration (HRD: from peg insertion to lift-off). An accidental drop of a peg led to an exceptionally long ( < mean + 3 SD) PMD, which was readily detected from an examination of data distribution. The PMD data were commonly right-skewed, suggesting that the median can be a better estimate of individual PMD than the mean. Repeated measures ANOVA using the median values revealed significant hole-to-hole distance, and hand dominance effects, suggesting that these need to be fixed in the accurate evaluation of PMD. The gender effect was non-significant. Performance consistency was also evaluated by the use of quartile variation coefficient values, which revealed no gender, hole-to-hole, and hand dominance effects. The measurement reliability was further examined using interclass correlation obtained from 14 subjects who performed the 25 and 125 mm hole distance tasks at two 7-10 days separate test sessions. Inter-class correlation values between the two tests showed fair reliability for PMD (0.65-0.75), and for HRD (0.77-0.94). We concluded that a sensor peg board developed in the present study could provide accurate (excluding tester’s errors), and precise (at a millisecond rate) time information of peg movement separated from that used for hand movement. It could also easily detect and automatically exclude erroneous execution data from his/her standard data. These would lead to a better evaluation of hand dexterity function compared to the widely used conventional used peg boards.

Keywords: hand, dexterity test, peg movement time, performance consistency

Procedia PDF Downloads 134

Authors: Beatriz González-rodrigo, Diego Hidalgo-leiva, Omar Flores, Claudia Germoso, Maribel Jiménez-martínez, Laura Navas-sánchez, Belén Orta, Nicola Tarque, Orlando Hernández- Rubio, Miguel Marchamalo, Juan Gregorio Rejas, Belén Benito-oterino

Abstract:

Cities facing seismic hazard necessitate detailed risk assessments for effective urban planning and vulnerability identification, ensuring the safety and sustainability of urban infrastructure. Comprehensive studies involving seismic hazard, vulnerability, and exposure evaluations are pivotal for estimating potential losses and guiding proactive measures against seismic events. However, broad-scale traditional risk studies limit consideration of specific local threats and identify vulnerable housing within a structural typology. Achieving precise results at neighbourhood levels demands higher resolution seismic hazard exposure, and vulnerability studies. This research aims to bolster sustainability and safety against seismic disasters in three Central American and Caribbean capitals. It integrates geospatial techniques and artificial intelligence into seismic risk studies, proposing cost-effective methods for exposure data collection and damage prediction. The methodology relies on prior seismic threat studies in pilot zones, utilizing existing exposure and vulnerability data in the region. Emphasizing detailed building attributes enables the consideration of behaviour modifiers affecting seismic response. The approach aims to generate detailed risk scenarios, facilitating prioritization of preventive actions pre-, during, and post-seismic events, enhancing decision-making certainty. Detailed risk scenarios necessitate substantial investment in fieldwork, training, research, and methodology development. Regional cooperation becomes crucial given similar seismic threats, urban planning, and construction systems among involved countries. The outcomes hold significance for emergency planning and national and regional construction regulations. The success of this methodology depends on cooperation, investment, and innovative approaches, offering insights and lessons applicable to regions facing moderate seismic threats with vulnerable constructions. Thus, this framework aims to fortify resilience in seismic-prone areas and serves as a reference for global urban planning and disaster management strategies. In conclusion, this research proposes a comprehensive framework for seismic risk assessment in high-risk urban areas, emphasizing detailed studies at finer resolutions for precise vulnerability evaluations. The approach integrates regional cooperation, geospatial technologies, and adaptive fragility curve adjustments to enhance risk assessment accuracy, guiding effective mitigation strategies and emergency management plans.

Keywords: assessment, behaviour modifiers, emergency management, mitigation strategies, resilience, vulnerability

Procedia PDF Downloads 68