Search results for: power system stability

Authors: Tiffany Baetens, Sophie Halliez, Luc Buée, Emiliano Pallecchi, Vincent Thomy, Steve Arscott

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We demonstrate here a viable stretchable bio-microelectromechanical systems (BioMEMS) technology for use with biological studies concerned with the effect of high mechanical strains on living cells. An example of this is traumatic brain injury (TBI) where neurons are damaged with physical force to the brain during, e.g., accidents and sports. Robust, miniaturized integrated systems are needed by biologists to be able to study the effect of TBI on neuron cells in vitro. The major challenges in this area are (i) to develop micro, and nanofabrication processes which are based on stretchable substrates and to (ii) create systems which are robust and performant at very high mechanical strain values—sometimes as high as 100%. At the time of writing, such processes and systems were rapidly evolving subject of research and development. The BioMEMS which we present here is composed of an elastomer substrate (low Young’s modulus ~1 MPa) onto which is patterned robust electrodes and insulators. The patterning of the thin films is achieved using standard photolithography techniques directly on the elastomer substrate—thus making the process generic and applicable to many materials’ in based systems. The chosen elastomer used is commercial ‘Sylgard 184’ polydimethylsiloxane (PDMS). It is spin-coated onto a silicon wafer. Multistep ultra-violet based photolithography involving commercial photoresists are then used to pattern robust thin film metallic electrodes (chromium/gold) and insulating layers (parylene) on the top of the PDMS substrate. The thin film metals are deposited using thermal evaporation and shaped using lift-off techniques The BioMEMS has been characterized mechanically using an in-house strain-applicator tool. The system is composed of 12 electrodes with one reference electrode transversally-orientated to the uniaxial longitudinal straining of the system. The electrical resistance of the electrodes is observed to remain very stable with applied strain—with a resistivity approaching that of evaporated gold—up to an interline strain of ~50%. The mechanical characterization revealed some interesting original properties of such stretchable BioMEMS. For example, a Poisson effect induced electrical ‘self-healing’ of cracking was identified. Biocompatibility of the commercial photoresist has been studied and is conclusive. We will present the results of the BioMEMS, which has also characterized living cells with a commercial Multi Electrode Array (MEA) characterization tool (Multi Channel Systems, USA). The BioMEMS enables the cells to be strained up to 50% and then characterized electrically and optically.

Keywords: BioMEMS, elastomer, electrical impedance measurements of living cells, high mechanical strain, microfabrication, stretchable systems, thin films, traumatic brain injury

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

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

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

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Authors: Ali Cheraghian, Farshid Hajati, Soheila Gheisari, Yongsheng Gao

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In this paper, we present a novel 2.5D face recognition method based on Gabor Discrete Cosine Transform (GDCT). In the proposed method, the Gabor filter is applied to extract feature vectors from the texture and the depth information. Then, Discrete Cosine Transform (DCT) is used for dimensionality and redundancy reduction to improve computational efficiency. The system is combined texture and depth information in the decision level, which presents higher performance compared to methods, which use texture and depth information, separately. The proposed algorithm is examined on publically available Bosphorus database including models with pose variation. The experimental results show that the proposed method has a higher performance compared to the benchmark.

Keywords: Gabor filter, discrete cosine transform, 2.5d face recognition, pose

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Authors: Marianna Nigra, Maicol Negrello

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Efficiency, productivity, and sustainability are important factors for structure and the application of processes in green building. Various previous studies have addressed efficiency, productivity, and sustainability separately. This research study aims to investigate the implications of these three factors taking together. Frequency analysis and the ranking techniques are carried out to explore the connection between these factors. The interconnection matrix has been developed and functional grouping is made based upon data from expert opinion and field professionals. The existence of a relationship, the type of relationship and the scaled impact have been drawn. Additionally, a system diagram has been developed to show the variable correlation. The results of expert opinion show that efficiency, productivity, and sustainability have a stronger impact on green buildings.

Keywords: green roof regulation, architecture, climate adaptation, resilience, innovation management

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Authors: Kadam Bhambri, Neena Gupta

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All optical wavelength conversion is essential in present day optical networks for transparent interoperability, contention resolution, and wavelength routing. The incorporation of all optical wavelength convertors leads to better utilization of the network resources and hence improves the efficiency of optical networks. Wavelength convertors that can work with Dispersion Managed (DM) solitons are attractive due to their superior transmission capabilities. In this paper, wavelength conversion for dispersion managed soliton signals was demonstrated at 100 Gbps through semiconductor optical amplifier and an optical filter. The wavelength conversion was achieved for a 1550 nm input signal to1555nm output signal. The output signal was measured in terms of BER, Q factor and system margin.    

Keywords: all optical wavelength conversion, dispersion managed solitons, semiconductor optical amplifier, cross gain modultation

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Authors: Margarita Zavala, Gabriel Chavira, José González, Jorge Orozco, Julio Rolón, Roberto Pichardo

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Adolescence is a neuralgic stage in the formation of every human being, generally this stage is when the middle school level is studied. In 2006, Mexico incorporated 'mentoring' space to assist students in their integration and participation in life. In public middle schools, it is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. With this, they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: adolescence, mentoring, middle school students, mentoring system support

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Authors: Farzaneh Sasanpour, Saeed Amini Varaki

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Resilience is an important goal for cities as urban areas face an increasing range of challenges in the 21st century; therefore, according to the characteristics of risks, adopting an approach that responds to sensitive conditions in the risk management process is the resilience of cities. In the meantime, most of the resilience assessments have dealt with natural hazards and less attention has been paid to pandemics.In the covid-19 pandemic, the country of Iran and especially the metropolis of Tehran, was not immune from the crisis caused by its effects and consequences and faced many challenges. One of the methods that can increase the resilience of Tehran's metropolis against possible crises in the future is future studies. This research is practical in terms of type. The general pattern of the research will be descriptive-analytical and from the point of view that it is trying to communicate between the components and provide urban resilience indicators with pandemic crises and explain the scenarios, its future studies method is exploratory. In order to extract and determine the key factors and driving forces effective on the resilience of Tehran's urban areas against pandemic crises (Covid-19), the method of structural analysis of mutual effects and Micmac software was used. Therefore, the primary factors and variables affecting the resilience of Tehran's urban areas were set in 5 main factors, including physical-infrastructural (transportation, spatial and physical organization, streets and roads, multi-purpose development) with 39 variables based on mutual effects analysis. Finally, key factors and variables in five main areas, including managerial-institutional with five variables; Technology (intelligence) with 3 variables; economic with 2 variables; socio-cultural with 3 variables; and physical infrastructure, were categorized with 7 variables. These factors and variables have been used as key factors and effective driving forces on the resilience of Tehran's urban areas against pandemic crises (Covid-19), in explaining and developing scenarios. In order to develop the scenarios for the resilience of Tehran's urban areas against pandemic crises (Covid-19), intuitive logic, scenario planning as one of the future research methods and the Global Business Network (GBN) model were used. Finally, four scenarios have been drawn and selected with a creative method using the metaphor of weather conditions, which is indicative of the general outline of the conditions of the metropolis of Tehran in that situation. Therefore, the scenarios of Tehran metropolis were obtained in the form of four scenarios: 1- solar scenario (optimal governance and management leading in smart technology) 2- cloud scenario (optimal governance and management following in intelligent technology) 3- dark scenario (optimal governance and management Unfavorable leader in intelligence technology) 4- Storm scenario (unfavorable governance and management of follower in intelligence technology). The solar scenario shows the best situation and the stormy scenario shows the worst situation for the Tehran metropolis. According to the findings obtained in this research, city managers can, in order to achieve a better tomorrow for the metropolis of Tehran, in all the factors and components of urban resilience against pandemic crises by using future research methods, a coherent picture with the long-term horizon of 2050, from the path Provide urban resilience movement and platforms for upgrading and increasing the capacity to deal with the crisis. To create the necessary platforms for the realization, development and evolution of the urban areas of Tehran in a way that guarantees long-term balance and stability in all dimensions and levels.

Keywords: future research, resilience, crisis, pandemic, covid-19, Tehran

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Authors: Zohra Aziz Ali Manjiyani, Renju Thomas Jacob, Keerthan Kumar

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This project develops a hand movement monitoring system, which feeds the data into the computer and gives the 3D image rotation according to the direction of the tilt and hence monitoring the movement of the hand in context to its tilt. Advancement of MEMS Technology has enabled us to get very small and low-cost accelerometer ICs which is based on capacitive principle. Accelerometer based Tilt sensor ADXL335 is used in this paper, based on MEMS technology and the project emphasis on the development of the MEMS-based accelerometer to measure the tilt, interfacing the hardware with the LabVIEW and showing the 3D rotation to the user, which is in his understandable form and tilt data can be saved in the computer. It provides an experience of working on emerging technologies like MEMS and design software like LabVIEW.

Keywords: MEMS accelerometer, tilt sensor ADXL335, LabVIEW simulation, 3D animation

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Authors: M. Eickermann, M. K. Class, J. Junk

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Winter oilseed rape, Brassica napus L., is characterized by a high number of herbicide applications. Therefore, its cultivation can lead to massive contamination of ground water and soil by herbicide and their metabolites. A multi-side long-term field experiment (EFFO, Efficient crop rotation) was set-up in Luxembourg to quantify these effects. Based on soil sampling and laboratory analysis, preliminary results showed reduced dehydrogenase activities of several soil organisms due to herbicide treatments. This effect is highly depending on the soil type. Relation between the dehydrogenase activity and the amount of microbial carbon showed higher variability on the test side with loamy Brown Earth, based on Bunter than on those with sandy-loamy Brown Earth, based on calciferous Sandstone.

Keywords: cropping system, dehydrogenase activity, herbicides, mechanical weed control, oilseed rape

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Authors: Kairat Kurakbayev, Dina Gungor, Adil Ashirbekov, Assel Kambatyrova

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Kazakhstan, a post-Soviet economy located in the Central Asia, is making great efforts to internationalize its national system of education. The country is very ambitious in making the national economy internationally competitive and education has become one of the main pillars of the nation’s strategic development plan for 2030. This paper discusses the role of professional teacher development in upgrading the secondary education curriculum with the introduction of English as a medium of instruction (EMI) in grades 10-11 grades. Having Kazakh as the state language and Russian as the official language, English bears a status of foreign language in the country. The development of trilingual education is very high on the agenda of the Ministry of Education and Science. It is planned that by 2019 STEM-related subjects – Biology, Chemistry, Computing and Physics – will be taught in EMI. Introducing English-medium education appears to be a very drastic reform and the teaching cadre is the key driver here. At the same time, after the collapse of the Soviet Union, the teaching profession is still struggling to become attractive in the eyes of the local youth. Moreover, the quality of Kazakhstan’s secondary education is put in question by OECD national review reports. The paper presents a case study of the nation-wide professional development programme arranged for 5 010 school teachers so that they could be able to teach their content subjects in English starting from 2019 onwards. The study is based on the mixed methods research involving the data derived from the surveys and semi-structured interviews held with the programme participants, i.e. school teachers. The findings of the study imply the significance of the school teachers’ attitudes towards the top-down reform of trilingual education. The qualitative research data reveal the teachers’ beliefs about advantages and disadvantages of having their content subjects (e.g. Biology or Chemistry) taught in EMI. The study highlights teachers’ concerns about their professional readiness to implement the top-down reform of English-medium education and discusses possible risks of academic underperforming on the part of students whose English language proficiency is not advanced. This paper argues that for the effective implementation of the English-medium education in secondary schools, the state should adopt a comprehensive approach to upgrading the national academic system where teachers’ attitudes and beliefs play the key role in making the trilingual education policy effective. The study presents lessons for other national academic systems considering to transfer its secondary education to English as a medium of instruction.

Keywords: teacher education, teachers' beliefs, trilingual education, case study

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Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

Procedia PDF Downloads 115

Authors: Lalith Edirisinghe, Zhihong Jin, A.W. Wijeratne, Hansa Edirisinghe, Lakshmi Ranwala Rashika Mudunkotuwa

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A paradigm shift in container inventory management (CIM) is a long-awaited industry need. Virtual container yard (VCY) is a concept developed in 2013 and its primary objective is to minimize shipping transport cost through implementing container exchange between carriers. Shipping lines always try to maintain lower container idle time and provide higher customer satisfaction. However, it is disappointing to note that carriers turn a blind eye to the escalating cost resulted from the present inefficient CIM mechanism. The cost of empty container management is simply transferred to the importers and exporters as freight adjustments. It also creates an environmental hazard. Therefore, it has now become a problem for the society. Therefore, a paradigm shift may be required as the present CIM system is not working for common interests of human beings as it should be.

Keywords: collaboation, inventory, shipping, virtual container yard

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Authors: Hanane Sarnou, Sabri Koç

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In this paper, the interconnection between curriculum development for basic education and the use of information and communication technologies (ICTs) in the classroom referring to the Licence, Master's and Doctorate (LMD) benefits under such link will be presented and analysed. This study seeks to achieve to what extent LMD, competency-based approach (CBA) and ICTs use are interrelated. Likewise, the data collected from the responses of our teachers and learners who are concerned with LMD impact on their learning and teaching through interviews will be discussed, analysed, and classified. This paper is divided into two sections. The first section is about the curriculum development for basic education and its relation with higher education under the LMD and its link with ICTs in the university while the second section is about the classification of learners’ and teachers’ positive/negative responses concerning their positive or negative attitudes towards the ICT integration. The focus will be on the positive aspects of students’ expectations, opinions and assumptions regarding the integration of ICTs into the classroom under LMD and CBA.

Keywords: LMD system, CBA approach, curriculum development, ICT

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Authors: Aabiah Nayeem, Fariha Shafiq, Mustabshra Aftab, Rabia Saman Pirzada, Samia Ghazala

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In this modern era of technology, the concept of Internet of Things is very popular in every domain. It is a widely distributed system of things in which the data collected from sensory devices is transmitted, analyzed locally/collectively then broadcasted to network where action can be taken remotely via mobile/web apps. Today’s mobile computing is also gaining importance as the services are provided during mobility. Through mobile computing, data are transmitted via computer without physically connected to a fixed point. The challenge is to provide services with high speed and security. Also, the data gathered from the mobiles must be processed in a secured way. Mobile computing is strongly influenced by internet of things. In this paper, we have discussed security issues and challenges of internet of things and mobile computing and we have compared both of them on the basis of similarities and dissimilarities.

Keywords: embedded computing, internet of things, mobile computing, wireless technologies

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Authors: Sana Iqbal

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The female voice in Sufi poetry has been studied as a symbol of humility and devotion. Throughout the centuries, the Sufi shrines have also sheltered women and have served as a source of emotional strength in times of difficulty. Although women have been central to Sufi Islam, female-led rituals and performances (of veneration) are rarely studied as acts of empowerment and symbols of healing. This is especially true for rituals performed in informal spaces, which require going beyond the shrine practices. The rituals and meanings associated with Khizr Khwaja (or Sindhi Hindu god Jhelelal) among women in Punjab can serve as a useful case study to unpack some of these meanings. The paper aims to shed light on female-led rituals among women from Punjab associated with the folkloric traditions associated with Khizar Khwaja, Zinda Pir, Jhulelal or river god in the South Asian region to protect mariners from possible risks (since trade was primarily dependent on water channels) or for inducing timely rain date back to the 10th century in Sindh. However, these meanings and associations have evolved and the paper thus aims to establish a relationship between this figure and the women in Punjab by analysing the findings from an ethnographic study. It traces the historical meanings and significance attached to the divine figure and the wells (informal spaces) associated with him since the rituals performed by women is now infused solely with seeking fertility or to be blessed with a successful pregnancy, as opposed to him being celebrated for other reasons in older times. These associations beg the question of what women gain out of these rituals and making offerings to the mysterious figure of Khizr. Anecdotal evidence in the form of interviews conducted in Bhakar and Talwandi (Punjab) during the summer of 2015 helped to explore the stories related to this legend while also allowing us to witness some of the female-led ritual practices. It can be said that the symbols adopted in the ritual practices invoke liminality for women, which is a blend of opposites. The paper argues that this liminality/journey has been used as a vehicle to transcend all worldly structures of power and it symbolically emphasises the richness of feminine love/devotion and grants healing to female devotees.

Keywords: transgression, gender, liminality, ritual

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Authors: Bhupinder Kaur, O. P. Pandey

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An automobile industry is using variety of materials for better comfort and utility. The present work describes the details of failure analysis done for windshield glass of a four-wheeler class. The failure occurred in two different models of the heavy duty class of four wheelers, which analysed separately. The company reported that the failure has occurred only in their rear windshield when vehicles parked under shade for several days. These glasses were characterised by dilatometer, differential thermal analyzer, and X-ray diffraction. The glasses were further investigated under scanning electron microscope with energy dispersive X-ray spectroscopy and X-ray dot mapping. The microstructural analysis of the glasses done at the surface as well as at the fractured area indicates that carbon as an impurity got segregated as banded structure throughout the glass. Since carbon absorbs higher heat, it causes thermal mismatch to the entire glass system, and glass shattered down. In this work, the details of sequential analysis done to predict the cause of failure are present.

Keywords: failure, windshield, thermal mismatch, carbon

Procedia PDF Downloads 243

Authors: Jaeyoung Lee

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Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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Authors: Rafeqah Raslan, Mastura AbdManaf, Junaidah Jai, Istikamah Subuki, Ana Najwa Mustapa

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The volatile citronella essential oil was encapsulated by simple coacervation and complex coacervation using gum Arabic and gelatin as wall material. Glutaraldehyde was used in the methodology as crosslinking agent. The citronella standard calibration graph was developed with R2 equal to 0.9523 for the accurate determination of encapsulation efficiency and release study. The release kinetic was analyzed based on Fick’s law of diffusion for polymeric system and linear graph of log fraction release over log time was constructed to determine the release rate constant, k and diffusion coefficient, n. Both coacervation methods in the present study produce encapsulation efficiency around 94%. The capsules morphology analysis supported the release kinetic mechanisms of produced capsules for both coacervation process.

Keywords: simple coacervation, complex coacervation, encapsulation efficiency, release kinetic study

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Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

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Current flooding risk modeling focuses on resilience, defined as the probability of recovery from a severe flooding event. However, the long-term damage to property and well-being by nuisance flooding and its long-term effects on communities are not typically included in risk assessments. An approach was developed to address the probability of recovering from a severe flooding event combined with the probability of community performance during a nuisance event. A consolidated model, namely the conflation flooding recovery (&FR) model, evaluates risk-coping mitigation strategies for communities based on the recovery time from catastrophic events, such as hurricanes or extreme surges, and from everyday nuisance flooding events. The &FR model assesses the variation contribution of each independent input and generates a weighted output that favors the distribution with minimum variation. This approach is especially useful if the input distributions have dissimilar variances. The &FR is defined as a single distribution resulting from the product of the individual probability density functions. The resulting conflated distribution resides between the parent distributions, and it infers the recovery time required by a community to return to basic functions, such as power, utilities, transportation, and civil order, after a flooding event. The &FR model is more accurate than averaging individual observations before calculating the mean and variance or averaging the probabilities evaluated at the input values, which assigns the same weighted variation to each input distribution. The main disadvantage of these traditional methods is that the resulting measure of central tendency is exactly equal to the average of the input distribution’s means without the additional information provided by each individual distribution variance. When dealing with exponential distributions, such as resilience from severe flooding events and from nuisance flooding events, conflation results are equivalent to the weighted least squares method or best linear unbiased estimation. The combination of severe flooding risk with nuisance flooding improves flood risk management for highly populated coastal communities, such as in South Florida, USA, and provides a method to estimate community flood recovery time more accurately from two different sources, severe flooding events and nuisance flooding events.

Keywords: community resilience, conflation, flood risk, nuisance flooding

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Authors: Jeanne Leblond, Warren Viricel, Amira Mbarek

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Although several products have reached the market, gene therapeutics are still in their first stages and require optimization. It is possible to improve their lacking efficiency by the use of carefully engineered vectors, able to carry the genetic material through each of the biological barriers they need to cross. In particular, getting inside the cell is a major challenge, because these hydrophilic nucleic acids have to cross the lipid-rich plasmatic and/or endosomal membrane, before being degraded into lysosomes. It takes less than one hour for newly endocytosed liposomes to reach highly acidic lysosomes, meaning that the degradation of the carried gene occurs rapidly, thus limiting the transfection efficiency. We propose to use a new pH-sensitive lipid able to change its conformation upon protonation at endosomal pH values, leading to the disruption of the lipidic bilayer and thus to the fast release of the nucleic acids into the cytosol. It is expected that this new pH-sensitive mechanism promote endosomal escape of the gene, thereby its transfection efficiency. The main challenge of this work was to design a preparation presenting fast-responding lipidic bilayer destabilization properties at endosomal pH 5 while remaining stable at blood pH value and during storage. A series of pH-sensitive lipids able to perform a conformational switch upon acidification were designed and synthesized. Liposomes containing these switchable lipids, as well as co-lipids were prepared and characterized. The liposomes were stable at 4°C and pH 7.4 for several months. Incubation with siRNA led to the full entrapment of nucleic acids as soon as the positive/negative charge ratio was superior to 2. The best liposomal formulation demonstrated a silencing efficiency up to 10% on HeLa cells, very similar to a commercial agent, with a lowest toxicity than the commercial agent. Using flow cytometry and microscopy assays, we demonstrated that drop of pH was required for the transfection efficiency, since bafilomycin blocked the transfection efficiency. Additional evidence was brought by the synthesis of a negative control lipid, which was unable to switch its conformation, and consequently exhibited no transfection ability. Mechanistic studies revealed that the uptake was mediated through endocytosis, by clathrin and caveolae pathways, as reported for previous lipid nanoparticle systems. This potent system was used for the treatment of hypercholesterolemia. The switchable lipids were able to knockdown PCSK9 expression on human hepatocytes (Huh-7). Its efficiency is currently evaluated on in vivo mice model of PCSK9 KO mice. In summary, we designed and optimized a new cationic pH-sensitive lipid for gene delivery. Its transfection efficiency is similar to the best available commercial agent, without the usually associated toxicity. The promising results lead to its use for the treatment of hypercholesterolemia on a mice model. Anticancer applications and pulmonary chronic disease are also currently investigated.

Keywords: liposomes, siRNA, pH-sensitive, molecular switch

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Authors: Tuisem Shimrah

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One general agreement on climate change is that its causes may be local but the effects are global. Indigenous people are subscribed to “low-carbon” traditional ways of life and as such they have contributed little to causes of climate change. On the contrary they are the most adversely affected by climate change due to their dependence on surrounding rich biological wealth as a source of their livelihood, health care, entertainment and cultural activities This paper deals with the results of the investigation of various adaptation strategies adopted to combat climate change by traditional community. The result shows effective ways of application of traditional knowledge and wisdom applied by Tangkhul traditional community at local and community level in remote areas in Northeast India. Four adaptation measures are being presented in this paper.

Keywords: adaptation, climate change, Northeast India, Tangkhul, traditional community

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Authors: Kasun P. Wijayaratna, Lauren Gardner, Taha Hossein Rashidi

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Undergraduate students entering university across the last 2 to 3 years tend to be born during the middle years of the 1990s. This generation of students has been exposed to the internet and the desire and dependency on technology since childhood. Brains develop based on environmental influences and technology has wired this generation of student to be attuned to sophisticated complex visual imagery, indicating visual forms of learning may be more effective than the traditional lecture or discussion formats. Furthermore, post-millennials perspectives on career are not focused solely on stability and income but are strongly driven by interest, entrepreneurship and innovation. Accordingly, it is important for educators to acknowledge the generational shift and tailor the delivery of learning material to meet the expectations of the students and the needs of industry. In the context of transport engineering, effectively teaching undergraduate students the basic principles of transport planning, traffic engineering and highway design is fundamental to the progression of the profession from a practice and research perspective. Recent developments in technology have transformed the discipline as practitioners and researchers move away from the traditional “pen and paper” approach to methods involving the use of computer programs and simulation. Further, enhanced accessibility of technology for students has changed the way they understand and learn material being delivered at tertiary education institutions. As a consequence, blended learning approaches, which aim to integrate face to face teaching with flexible self-paced learning resources, have become prevalent to provide scalable education that satisfies the expectations of students. This research study involved the development of a series of ‘Blended Learning’ initiatives implemented within an introductory transport planning and geometric design course, CVEN2401: Sustainable Transport and Highway Engineering, taught at the University of New South Wales, Australia. CVEN2401 was modified by conducting interactive polling exercises during lectures, including weekly online quizzes, offering a series of supplementary learning videos, and implementing a realistic design project that students needed to complete using modelling software that is widely used in practice. These activities and resources were aimed to improve the learning environment for a large class size in excess of 450 students and to ensure that practical industry valued skills were introduced. The case study compared the 2016 and 2017 student cohorts based on their performance across assessment tasks as well as their reception to the material revealed through student feedback surveys. The initiatives were well received with a number of students commenting on the ability to complete self-paced learning and an appreciation of the exposure to a realistic design project. From an educator’s perspective, blending the course made it feasible to interact and engage with students. Personalised learning opportunities were made available whilst delivering a considerable volume of complex content essential for all undergraduate Civil and Environmental Engineering students. Overall, this case study highlights the value of blended learning initiatives, especially in the context of large class size university courses.

Keywords: blended learning, highway design, teaching, transport planning

Procedia PDF Downloads 147

Authors: Susanne Gustafsson

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

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

Procedia PDF Downloads 106

Authors: Sachin Kumar

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Fuzzy fractional diffusion equation is widely useful to depict different physical processes arising in physics, biology, and hydrology. The motive of this article is to deal with the fuzzy fractional diffusion equation. We study a mathematical model of fuzzy space-time fractional diffusion equation in which unknown function, coefficients, and initial-boundary conditions are fuzzy numbers. First, we find out a fuzzy operational matrix of Legendre polynomial of Caputo type fuzzy fractional derivative having a non-singular Mittag-Leffler kernel. The main advantages of this method are that it reduces the fuzzy fractional partial differential equation (FFPDE) to a system of fuzzy algebraic equations from which we can find the solution of the problem. The feasibility of our approach is shown by some numerical examples. Hence, our method is suitable to deal with FFPDE and has good accuracy.

Keywords: fractional PDE, fuzzy valued function, diffusion equation, Legendre polynomial, spectral method

Procedia PDF Downloads 196

Authors: Athanase Gahungu, Karen Freeman

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Different groups of stakeholders expect the evaluation of an international, grant-funded program to inform them of the worth of the program - the funder, the agency operating the program and its community, and the citizens of the country where the program is implemented. This paper summarizes the challenges that intercultural teams of researchers faced as they crisscrossed a host country while evaluating a teaching and learning materials program, and offers useful tips for effective collaboration. Firstly, was recommended that the teams be representative of the cultures involved, and have the required research and program evaluation skills. Secondly, cultures involved must consistently establish and maintain a shared performance system. Thirdly, successful team members must be self-aware, inter-culturally knowledgeable, not just in communication, but in conceptualizing the political and social context of international grant-funded projects.

Keywords: program evaluation, international collaboration, intercultural, shared performance

Procedia PDF Downloads 532

Authors: Nguyen The Hoang Anh, Tran Huy Hoang, Vu Tat Thang, T. T. Quyen Bui

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Mental state classification is an important step for realizing a control system based on electroencephalography (EEG) signals which could benefit a lot of paralyzed people including the locked-in or Amyotrophic Lateral Sclerosis. Considering that EEG signals are nonstationary and often contaminated by various types of artifacts, classifying thoughts into correct mental states is not a trivial problem. In this work, our contribution is that we present and realize a novel model which integrates different techniques: Independent component analysis (ICA), relative wavelet energy, and support vector machine (SVM) for the same task. We applied our model to classify thoughts in two types of experiment whether with two or three mental states. The experimental results show that the presented model outperforms other models using Artificial Neural Network, K-Nearest Neighbors, etc.

Keywords: EEG, ICA, SVM, wavelet

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Authors: Anton Stadler, Thorsten Ike

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In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.

Keywords: low density, optical flow, upward smoke motion, video based smoke detection

Procedia PDF Downloads 349

Authors: Kacper Tomasz Kröber-Mulawa

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This paper will address the topic of data ownership from an economic perspective, and examples of economic limitations of data property rights will be provided, which have been identified using methods and approaches of economic analysis of law. To properly build a background for the economic focus, in the beginning a short perspective of data and data ownership in the EU’s legal system will be provided. It will include a short introduction to its political and social importance and highlight relevant viewpoints. This will stress the importance of a Single Market for data but also far-reaching regulations of data governance and privacy (including the distinction of personal and non-personal data, data held by public bodies and private businesses). The main discussion of this paper will build upon the briefly referred to legal basis as well as methods and approaches of economic analysis of law.

Keywords: antitrust, data, data ownership, digital economy, property rights

Procedia PDF Downloads 75

Authors: Amin Mojiri, Lou Ziyang

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Constructed wetland (CW) is a reasonable method to treat waste water. Current study was carried out to co-treat landfill leachate and domestic waste water using a CW system. Typha domingensis was transplanted to CW, which encloses two substrate layers of adsorbents named ZELIAC and zeolite. Response surface methodology and central composite design were employed to evaluate experimental data. Contact time (h) and leachate to waste water mixing ratio (%; v/v) were selected as independent factors. Phenols and manganese removal were selected as dependent responses. At optimum contact time (48.7 h) and leachate to waste water mixing ratio (20.0%), removal efficiencies of phenols and manganese removal efficiencies were 90.5%, and 89.4%, respectively.

Keywords: constructed wetland, Manganese, phenols, Thypha domingensis

Procedia PDF Downloads 318

Authors: Diego Tancara, Raul Coto, Ariel Norambuena, Hoseein T. Dinani, Felipe Fanchini

Abstract:

Quantum machine learning is a growing research field that aims to perform machine learning tasks assisted by a quantum computer. Kernel-based quantum machine learning models are paradigmatic examples where the kernel involves quantum states, and the Gram matrix is calculated from the overlapping between these states. With the kernel at hand, a regular machine learning model is used for the learning process. In this paper we investigate the quantum support vector machine and quantum kernel ridge models to predict the degree of non-Markovianity of a quantum system. We perform digital quantum simulation of amplitude damping and phase damping channels to create our quantum dataset. We elaborate on different kernel functions to map the data and kernel circuits to compute the overlapping between quantum states. We observe a good performance of the models.

Keywords: quantum, machine learning, kernel, non-markovianity

Procedia PDF Downloads 172