Search results for: Kevin Thomas

Authors: Francis Zerd, Brian E. Moore, Atuganile E. Malango, Patrick W. Hosokawa, Kevin O. Lillehei, Laurence Lemery Mchome, D. Ryan Ormond

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Introduction: Since neuropathologic diagnosis in the developing world is hampered by limitations in technical infrastructure, trained laboratory personnel, and subspecialty-trained pathologists, the use of telepathology for diagnostic support, second-opinion consultations, and ongoing training holds promise as a means of addressing these challenges. This research aims to assess the utility of static teleneuropathology in improving neuropathologic diagnoses in low- and middle-income countries. Methods: Consecutive neurosurgical biopsy and resection specimens obtained at Muhimbili National Hospital in Tanzania between July 1, 2018, and June 30, 2019, were selected for retrospective, blinded static-image neuropathologic review followed by on-site review by an expert neuropathologist. Results: A total of 75 neuropathologic cases were reviewed. The agreement of static images and on-site glass diagnosis was 71% with strict criteria and 88% with less stringent criteria. This represents an overall improvement in diagnostic accuracy from 36% by general pathologists to 71% by a neuropathologist using static telepathology (or 76% to 88% with less stringent criteria). Conclusions: Telepathology offers a suitable means of providing diagnostic support, second-opinion consultations, and ongoing training to pathologists practicing in resource-limited countries. Moreover, static digital teleneuropathology is an uncomplicated, cost-effective, and reliable way to achieve these goals.

Keywords: neuropathology, resource-limited settings, static image, Tanzania, teleneuropathology

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Authors: Hanno Schmidt, Assaf Malik, Anne Bicker, Gesa Poetzsch, Aaron Avivi, Imad Shams, Thomas Hankeln

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The blind subterranean mole rat Spalax shows a remarkable tolerance to hypoxia, cancer-resistance and longevity. Unravelling the genomic basis of these adaptations will be important for biomedical applications. RNA-Seq gene expression data were obtained from normoxic and hypoxic Spalax and rat liver tissue. Hypoxic Spalax broadly downregulates genes from major liver function pathways. This energy-saving response is likely a crucial adaptation to low oxygen levels. In contrast, the hypoxiasensitive rat shows massive upregulation of energy metabolism genes. Candidate genes with plausible connections to the mole rat’s phenotype, such as important key genes related to hypoxia-tolerance, DNA damage repair, tumourigenesis and ageing, are substantially higher expressed in Spalax than in rat. Comparative liver transcriptomics highlights the importance of molecular adaptations at the gene regulatory level in Spalax and pinpoints a variety of starting points for subsequent functional studies.

Keywords: cancer, hypoxia, longevity, transcriptomics

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Authors: Ali A. Sayadi, Thomas R. Neitzert, G. Charles Clifton

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Lightweight concrete is being used in the construction industry as a building material in its own right. Ultra-lightweight concrete can be applied as a filler and support material for the manufacturing of composite building materials. This paper is about the development of a stable and reproducible ultra-lightweight concrete with the inclusion of poly-lactic acid (PLA) beads and assessing the feasibility of PLA as a lightweight aggregate that will deliver advantages such as a more eco-friendly concrete and a non-petroleum polymer aggregate. In total, sixty-three samples were prepared and the effectiveness of mineral admixture, curing conditions, water-cement ratio, PLA ratio, EPS ratio and perlite ratio on compressive strength of perlite concrete are studied. The results show that PLA particles are sensitive to alkali environment of cement paste and considerably shrank and lost their strength. A higher compressive strength and a lower density was observed when expanded polystyrene (EPS) particles replaced PLA beads. In addition, a set of equations is proposed to estimate the water-cement ratio, cement content and compressive strength of perlite concrete.

Keywords: perlite concrete, poly-lactic acid (pla), expanded polystyrene (eps), concrete

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Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as vital physiological signs, images, and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision-making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful in influencing the judgement of clinical sentiment in ICU clinical notes. This paper introduces two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of clinical transformer models that can reliably predict clinical sentiment for notes of COVID patients in the ICU. We train the model on clinical notes for COVID-19 patients, a type of notes that were not previously seen by clinicalBERT, and Bio_Discharge_Summary_BERT. The model, which was based on clinicalBERT achieves higher predictive accuracy (Acc 93.33%, AUC 0.98, and precision 0.96 ). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and precision 0.92 ).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation

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Authors: Sabahattin Comertpay, Sandra Pastorino, Rosanna Mezzapelle, Mika Tanji, Oriana Strianese, Andrea Napolitano, Tracey Weigel, Joseph Friedberg, Paul Sugarbaker, Thomas Krausz, Ena Wang, Amy Powers, Giovanni Gaudino, Harvey I. Pass, Fatmagul Ozcelik, Barbara L. Parsons, Haining Yang, Michele Carbone

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Tumors are thought to be monoclonal in origin. This paradigm arose decades ago, primarily from the study of hematopoietic malignancies and sarcomas. The clonal origin of malignant mesothelioma (MM), a deadly cancer resistant to the current therapies, has not been investigated. Examination of the pleura from patients with MM shows often the presence of multiple pleural nodules, raising the question of whether they represent independent or metastatic growth processes. To investigate the clonality patterns of MM, we used the HUMARA (Human Androgen Receptor) assay to examine 14 sporadic and 2 familial Malignant Mesotheliomas (MM). Of 16 specimens studied, 15 were informative and 14/15 revealed two electrophoretically distinct methylated HUMARA alleles, indicating a polyclonal origin for these tumors. This discovery has important clinical implications, because an accurate assessment of tumor clonality is key to the design of novel molecular strategies for the treatment of MM.

Keywords: malignant mesothelioma, clonal origin, HUMARA, sarcomas

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Authors: Tobias Horstmann, Thomas Le Garrec, Daniel-Ciprian Mincu, Emmanuel Lévêque

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Despite the efficiency and low dissipation of the stream-collide formulation of the Lattice Boltzmann (LB) algorithm, which is nowadays implemented in many commercial LBM solvers, there are certain situations, e.g. mesh transition, in which a classical finite-volume or finite-difference formulation of the LB algorithm still bear advantages. In this paper, we present an algorithm that combines the node-based streaming of the distribution functions with a second-order finite volume discretization of the advection term of the BGK-LB equation on a uniform D2Q9 lattice. It is shown that such a coupling is possible for a multi-domain approach as long as the overlap, or buffer zone, between two domains, is achieved on at least 2Δx. This also implies that a direct coupling (without buffer zone) of a stream-collide and finite-volume LB algorithm on a single grid is not stable. The critical parameter in the coupling is the CFL number equal to 1 that is imposed by the stream-collide algorithm. Nevertheless, an explicit filtering step on the finite-volume domain can stabilize the solution. In a further investigation, we demonstrate how such a coupling can be used for mesh transition, resulting in an intrinsic conservation of mass over the interface.

Keywords: algorithm coupling, finite volume formulation, grid refinement, Lattice Boltzmann method

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Authors: Sandhya Rao

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Kevin Lynch’s Theory on Imeageability, let on explore a city in terms of five elements, Nodes, Paths, Edges, landmarks and Districts. What happens when we try to record the same data in an Indian context? What happens when we apply the same theory of Imageability to a complex shifting urban pattern of the Indian cities and how can we as Urban Designers demonstrate our role in the image building ordeal of these cities? The organizational patterns formed through mental images, of an Indian city is often diverse and intangible. It is also multi layered and temporary in terms of the spirit of the place. The pattern of images formed is loaded with associative meaning and intrinsically linked with the history and socio-cultural dominance of the place. The embedded memory of a place in one’s mind often plays an even more important role while formulating these images. Thus while deriving an image of a city one is often confused or finds the result chaotic. The images formed due to its complexity are further difficult to represent using a single medium. Under such a scenario it’s difficult to derive an output of an image constructed as well as make design interventions to enhance the legibility of a place. However, there can be a combination of tools and methods that allows one to record the key elements of a place through time, space and one’s user interface with the place. There has to be a clear understanding of the participant groups of a place and their time and period of engagement with the place as well. How we can translate the result obtained into a design intervention at the end, is the main of the research. Could a multi-faceted cognitive mapping be an answer to this or could it be a very transient mapping method which can change over time, place and person. How does the context influence the process of image building in one’s mind? These are the key questions that this research will aim to answer.

Keywords: imageability, organizational patterns, legibility, cognitive mapping

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Authors: Ahmed Amrani, Oussama Allali, Amira Ben Hamida, Felix Defrance, Stephanie Morland, Eva Pineau, Thomas Lacroix

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The energy planning process is a very complex task that involves several stakeholders and requires the consideration of several local and global factors and constraints. In order to optimize and simplify this process, we propose a tool-based iterative approach applied to district heating planning. We build our tool with the collaboration of a French territory using actual district data and implementing the European incentives. We set up an iterative process including data visualization and analysis, identification and extraction of information related to the area concerned by the operation, design of sustainable planning scenarios leveraging local renewable and recoverable energy sources, and finally, the evaluation of scenarios. The last step is performed by a dynamic digital twin replica of the city. Territory’s energy experts confirm that the tool provides them with valuable support towards sustainable energy planning.

Keywords: climate change, data management, decision support, digital twin, district heating, energy planning, renewables, smart city

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Authors: Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini

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In vapor cycle systems, the mass flow sensor plays a key role for different monitoring and control purposes. However, physical sensors can be inaccurate, heavy, cumbersome, expensive, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor, based on other standard sensors, is a good alternative. This paper has two main objectives. Firstly, a data-driven model using a convolutional neural network is proposed to estimate the mass flow of the compressor. We show that it significantly outperforms the standard polynomial regression model (thermodynamic maps) in terms of the standard MSE metric and engineer performance metrics. Secondly, a semi-automatic segmentation method is proposed to compute the engineer performance metrics for real datasets, as the standard MSE metric may pose risks in analyzing the dynamic behavior of vapor cycle systems.

Keywords: deep learning, convolutional neural network, vapor cycle system, virtual sensor

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Authors: Shanthi Thomas

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This research paper presents the current practices of teacher professional development, perceived as beneficial by teachers themselves, in a private secondary school in Brunei Darussalam. This is part of the findings of a larger qualitative study on teacher empowerment, using ethnographic methods for data collection, i.e. participant observation, interviews and document analysis. The field work was carried out over a period of six months in 2013. An analysis of the field data revealed multiple pathways of teacher professional development existing in the school. The results indicate that school leaders, the teacher community in the school, students, and the teachers themselves were the agents in a school that facilitated teacher empowerment. Besides contributing to the knowledge base on teacher professional development, the results of this study provides directions for educational policy makers in their efforts to enhance professional development in secondary schools of similar characteristics. For school leaders and the teacher community, these findings offer guidelines for maximizing the opportunities for these professional development practices, by strengthening collegiality and by using the existing structures optimally for the benefit of all concerned.

Keywords: colleagues and the wider teacher community, school leaders, self-driven professional development, teacher professional development

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Authors: Thomas P. Roper, Brad Forbes, Jurij Karlovšek

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Shear displacement along bedding defects is a well-recognised behaviour when tunnelling and mining in stratified rock. This deformation can affect the durability and integrity of installed rock bolts. In-situ monitoring of rock bolt deformation under bedding shear cannot be accurately derived from traditional strain gauge bolts as sensors are too large and spaced too far apart to accurately assess concentrated displacement along discrete defects. A possible solution to this is the use of fiber optic technologies developed for precision monitoring. Distributed Optic Sensor (DOS) embedded rock bolts were installed in a tunnel project with the aim of measuring the bolt deformation profile under significant shear displacements. This technology successfully measured the 3D strain distribution along the bolts when subjected to bedding shear and resolved the axial and lateral strain constituents in order to determine the deformational geometry of the bolts. The results are compared well with the current visual method for monitoring shear displacement using borescope holes, considering this method as suitable.

Keywords: distributed optical strain sensing, rock bolt, bedding shear, sandstone tunnel

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Authors: Merle Bischoff, Thomas Gries, Gunnar Seide

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Pesticides, which harm crop enemies, but can also interfere with the human body, are nowadays mostly used for crop spraying. Silica particles (SiO2) in the nanometer and micrometer scale offer a physical way to combat insects without harming humans and other mammals. Thereby, they allow foregoing pesticides, which can harm the environment. As silica particles are supplied as a powder or in a suspension to farmers, the silica use in large scale agriculture is not sufficient due to erosion through wind and rain. When silica is implemented in a textile’s surface (nanocompound), particles are locally bound and do resist erosion, but can function against bugs. By choosing polypropylene as a matrix polymer, the production of an inexpensive agritextile with an 'anti-bug' effect is made possible. In the Symposium the results of the manufacturing and filament spinning of silica nanocomposites from a polypropylene basis is compared to the fabrication from nanocomposites based on Polybutylene succinate, a biodegradable composite. The investigation focuses on the difference between degradable nanocomposite and stable nanocomposite. Focus will be laid on the filament characteristics as well as the degradation of the nanocompound to underline their potential use and application as an agricultural textile.

Keywords: agriculture, environment, insects, protection, silica, textile, nanocomposite

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Authors: Indrasen Raghupatruni, Michael Glora, Ralf Diekmann, Thomas Demmer

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As the trend in automotive technology is fast moving towards hybridization and electrification to curb emissions as well as to improve the fuel efficiency, air-conditioning systems in passenger cars have not caught up with this trend and still remain as the major energy consumers amongst others. Adsorption based air-conditioning systems, e.g. with silica-gel water pair, which are already in use for residential and commercial applications, are now being considered as a technology leap once proven feasible for the passenger cars. In this paper we discuss a methodology, challenges and feasibility of implementing an adsorption based air-conditioning system in a passenger car utilizing the exhaust waste heat. We also propose an optimized control strategy with interfaces to the engine control unit of the vehicle for operating this system with reasonable efficiency supported by our simulation and validation results in a prototype vehicle, additionally comparing to existing implementations, simulation based as well as experimental. Finally we discuss the influence of start-stop and hybrid systems on the operation strategy of the adsorption air-conditioning system.

Keywords: adsorption air-conditioning, feasibility study, optimized control strategy, prototype vehicle

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Authors: Mohit Gupta, Chialing Wei, Thomas Czerniawski

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In this paper, we have built a neural network that can detect walls on 2D sheets and subsequently create a 3D model in Revit using Dynamo. The training set includes 3500 labeled images, and the detection algorithm used is YOLO. Typically, engineers/designers make concentrated efforts to convert 2D cad drawings to 3D models. This costs a considerable amount of time and human effort. This paper makes a contribution in automating the task of 3D walls modeling. 1. Detecting Walls in 2D cad and generating 3D pop-ups in Revit. 2. Saving designer his/her modeling time in drafting elements like walls from 2D cad to 3D representation. An object detection algorithm YOLO is used for wall detection and localization. The neural network is trained over 3500 labeled images of size 256x256x3. Then, Dynamo is interfaced with the output of the neural network to pop-up 3D walls in Revit. The research uses modern technological tools like deep learning and artificial intelligence to automate the process of generating 3D walls without needing humans to manually model them. Thus, contributes to saving time, human effort, and money.

Keywords: neural networks, Yolo, 2D to 3D transformation, CAD object detection

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Authors: Benga Ebouele, Thomas Tengen

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Due to long lead time, work in process (WIP) inventory can manifest within the supply chain of most manufacturing system. It implies that there are lesser finished good on hand and more in the process because the work remains in the factory too long and cannot be sold to either customers The supply chain of most manufacturing system is then considered as inefficient as it take so much time to produce the finished good. Time consumed in each operation of the supply chain has an associated energy costs. Such phenomena can be harmful for a hybrid inventory system because a lot of space to store these semi-finished goods may be needed and one is not sure about the final energy cost of producing, holding and delivering the good to customers. The principle that reduces waste of energy within the supply chain of most manufacturing firms should therefore be available to all inventory managers in pursuit of profitability. Decision making by inventory managers in this condition is a modeling process, whereby a dynamical approach is used to depict, examine, specify and even operationalize the relationship between energy consumption and hybrid inventory level. The relationship between energy consumption and inventory level is established, which indicates a poor level of control and hence a potential for energy savings.

Keywords: dynamic modelling, energy used, hybrid inventory, supply chain

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Authors: Thomas Yeboah

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In recent times, micro-finance programmes targeting women have become the central means of donor poverty alleviation strategies. In view of the renewed focus on post-Millennium Development Goals (MDGs) poverty reduction strategies, there is the likelihood that funding might increase in the next coming decades to support different initiatives by donor agencies. In this paper, we critically examine the role of microfinance in shaping gender relations and empowerment outcomes of women. It is widely argued that providing and reaching out to women with credit methodologies serves as a means of increasing women’s bargaining power and challenging existing gender subordination thereby releasing them from power structures which dominate their lives. This paper cautions this view and instead show that the mainstream argument surrounding microfinance and gender empowerment is much complex than what the popular rhetoric preaches. Drawing on empirical cases on microfinance literature, we argue that lack of systematic strategy to incorporate men and the wider socio-cultural dynamics within which women’s lives are embedded radically constraints the empowerment potential of microcredit programmes and in some context may lead to unintended consequences for women.

Keywords: microfinance, empowerment, women, men, gender relations

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Authors: Jose Carlos Montemayor, Kendrick Thomas Angelo Santos

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Filipinos have been divided on President Rodrigo Duterte’s leadership ever since his election in 2016. This study aimed to gain a thorough, in-depth understanding of the opinions of Filipinos from different age and income brackets on these issues in order to address the lack of studies analysing the current Philippine political landscape. An interview tackling relevant national issues were conducted with twelve respondents from the intersections of four age groups and three income brackets. The government’s handling of some issues received mixed opinions, some had neutral viewpoints, while others had more unfavorable ones. The responses differed on three levels: (1) the general stance on an issue; (2) the strength of a stance; and (3) the factoring in of an issue in forming an overall perception on the administration’s performance. Contrary to previous studies on political thought, opinions varied greatly such that no unique set of viewpoints could be attributed to any of the defined age or income groups. These results will be most useful to political science researchers, political analysts, and candidates shaping their platforms for the upcoming elections. Future studies are recommended to tackle more national issues and to consider other factors that may affect political opinions and behavior.

Keywords: age groups, opinion formation, socioeconomic brackets, Philippine politics, Rodrigo Duterte

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Authors: Stephan Koehler, Thomas Friedli

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Performance measurement has evolved over time from a unidimensional short-term efficiency focused approach into a balanced multidimensional approach. Today, integrated performance measurement frameworks are often used to avoid local optimization and to encourage continuous improvement of an organization. In literature, the multidimensional characteristic of performance measurement is often described by competitive priorities. At the same time, on the highest abstraction level an effectiveness and efficiency dimension of performance measurement can be distinguished. This paper aims at a better understanding of the composition of effectiveness and efficiency and their relation in pharmaceutical quality control labs. The research comprises a lab-specific operationalization of effectiveness and efficiency and examines how the two dimensions are interlinked. The basis for the analysis represents a database of the University of St. Gallen including a divers set of 40 different pharmaceutical quality control labs. The research provides empirical evidence that labs with a high effectiveness also accompany a high efficiency. Lab effectiveness explains 29.5 % of the variance in lab efficiency. In addition, labs with an above median operational excellence performance have a statistically significantly higher lab effectiveness and lab efficiency compared to the below median performing labs.

Keywords: empirical study, operational excellence, performance measurement, pharmaceutical quality control lab

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Authors: V. S. Binu, Amitha Puranik, Sintomon Mathew, Sebin Thomas

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Globally, women are more vulnerable to various forms of crimes than males. The crimes that are directed specifically towards women are classified as crime against women. Crime against women in India is observed to increase year after year and according to the National Crime Records Bureau (NCRB) report, in 2014 there was an increase of 9.2% cases of crime against women compared to the previous year. The violence in a population depends on socio-demographic factors, unemployment, poverty, number of police officials etc. There are very few studies that explored to identify hotspots of various types of crime against women in India. Hotspots are geographical regions where the number of observed cases is more than the expected number for that region. It is important to identify the hotspots of crime against women in India in order to control and prevent violence against women in that region. The goal of this study is to identify the hotspots of crime against women in India using spatial data analysis techniques. For the present study, we used the district level data of various types of crime against women in India in the year 2011 published by NCRB and the 2011 Census population in each of these districts. The study used spatial scan statistic to identify the hotspots using SaTScan software.

Keywords: crime, hotspots, India, Satscan, Women

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Authors: Hiba Hamdi, Thomas Corpetti, Laure Roupioz, Xavier Briottet

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Air temperatures are generally higher in cities than in their rural surroundings. The overheating of cities is a direct consequence of increasing urbanization, characterized by the artificial filling of soils, the release of anthropogenic heat, and the complexity of urban geometry. This phenomenon, referred to as urban heat island (UHI), is more prevalent during heat waves, which have increased in frequency and intensity in recent years. In the context of global warming and urban population growth, helping urban planners implement UHI mitigation and adaptation strategies is critical. In practice, the study of UHI requires air temperature information at the street canyon level, which is difficult to obtain. Many urban air temperature simulation models have been proposed (mostly based on physics or statistics), all of which require a variety of input parameters related to urban morphology, land use, material properties, or meteorological conditions. In this paper, we build and evaluate a neural network model based on Urban Weather Generator (UWG) model simulations and data from meteorological stations that simulate air temperature over Toulouse, France, on days favourable to UHI.

Keywords: air temperature, neural network model, urban heat island, urban weather generator

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Authors: Nathenal Thomas Lambamo

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Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

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Authors: Kevin V. Bui, Richard A. Claytor, Elizabeth M. Priolo, Weihui Li

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Oxygen deprivation masks operate through the use of restricting valves as a means to reduce respiratory flow where flow is inversely proportional to the resistance applied. This produces the same effect as higher altitudes where lower pressure leads to reduced respiratory flow. Both increased resistance with restricting valves and reduce the pressure of higher altitudes make breathing difficultier and force breathing muscles (diaphragm and intercostal muscles) working harder. The process exercises these muscles, improves their strength and results in overall better breathing efficiency. Currently, these oxygen deprivation masks are purely mechanical devices without any electronic sensor to monitor the breathing condition, thus not be able to provide feedback on the breathing effort nor to evaluate the lung function. That is part of the reason that these masks are mainly used for high-level athletes to mimic training in higher altitude conditions, not suitable for patients or customers. The design aims to improve the current method of oxygen deprivation mask to include a larger scope of patients and customers while providing quantitative biometric data that the current design lacks. This will be accomplished by integrating sensors into the mask’s breathing valves along with data acquisition and Bluetooth modules for signal processing and transmission. Early stages of the sensor mask will measure breathing rate as a function of changing the air pressure in the mask, with later iterations providing feedback on flow rate. Data regarding breathing rate will be prudent in determining whether training or therapy is improving breathing function and quantify this improvement.

Keywords: oxygen deprivation mask, lung function, spirometer, Bluetooth

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Authors: Shahid Nishat, Keith Thomas

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E-government initiatives attract substantial public investments around the world. These investments are based on the premise of digital transformation of the public services, improved efficiency and transparency, and citizen participation in the social democratic processes. However, many e-Government projects, especially in developing countries, fail to achieve their intended outcomes, and a strong disparity exists between the investments made and outcomes achieved, often referred to as e-Government paradox. Further, there is lack of research on evaluating the impacts of e-Government in terms of public value it creates, which ultimately drives usage. This study aims to address these gaps by identifying key enablers of e-Government success and by proposing a public value based framework to examine impact of e-Government services. The study will extend Delone and McLean Information System (IS) Success model by integrating Technology Readiness (TR) characteristics to develop an integrated success model. Level of analysis will be mobile government applications, and the framework will be empirically tested using quantitative methods. The research will add to the literature on e-Government success and will be beneficial for governments, especially in developing countries aspiring to improve public services through the use of Information Communication Technologies (ICT).

Keywords: e-Government, IS success model, public value, technology adoption, technology readiness

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Authors: Haibo Zhao, Thomas Andre, Katherine Avery, Alper Kiziltas, Deborah Mielewski

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Silica aerogels were fabricated through a modified rapid supercritical extraction (RSCE) process. The silica aerogels were made using a tetramethyl orthosilicate precursor and then placed in a hot press and brought to the supercritical point of the solvent, ethanol. In order to control the pressure release without a pressure controller, a needle valve was used. The resulting aerogels were then characterized for their physical and chemical properties and compared to silica aerogels created using similar methods. The aerogels fabricated using this modified RSCE method were found to have similar properties to those in other papers using the unmodified RSCE method. Silica aerogel infused glass blanket composite, graphene reinforced silica aerogel composite were also successfully fabricated by this new method. The modified RSCE process and system is a prototype for better gas outflow control with a lower cost of equipment setup. Potentially, this process could be evolved to a continuous low-cost high-volume production process to meet automotive requirements.

Keywords: aerogel, automotive, rapid supercritical extraction process, low cost production

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Authors: Kevin William Taylor

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This work draws upon research in the fields of games development and mental health treatments to assess the influence that interactive entertainment has on the populous, and the potential of technology to affect areas of psychiatric assessment and treatment. It will use studies to establish the evolving direction of interactive media in the development of ‘digital self-identity,’ and how this can be incorporated into treatment to the benefit of psychiatry. It will determine that this approach will require collaborative production between developers and psychiatrists in order to ensure precise goals are met, improving the success of serious gaming for psychiatric assessment and treatment. Analysis documents the reach of video games across a growing global community of gamers, highlighting cases of the positives and negatives of video game usage. The games industry is largely oblivious to the psychological negatives, with psychiatrists encountering new conditions such as gaming addiction, which is now recognized by the World Health Organization. With an increasing amount of gamers worldwide, and an additional time per day invested in online gaming and character development, the concept of virtual identity as a means of expressing the id needs further study to ensure successful treatment. In conclusion, the assessment and treatment of game-related conditions are currently reactionary, and while some mental health professionals have begun utilizing interactive technologies to assist with the assessment and treatment of conditions, this study will determine how the success of these products can be enhanced. This will include collaboration between software developers and psychiatrists, allowing new avenues of skill-sharing in interactive design and development. Outlining how to innovate approaches to engagement will reap greater rewards in future interactive products developed for psychiatric assessment and treatment.

Keywords: virtual reality, virtual identity, interactivity, psychiatry

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Authors: Thomas Merciris, Mathieu Masquere, Yann Cressault, Pascale Petit

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The goal of an alternative current (AC) switching device is to allow the arc (created during the opening phase of the contacts) to extinguish at the current zero. The plasma temperature rate of cooling down, the electrical characteristic of the arc (current-voltage), and the rise rate of the transient recovery voltage (TRV) are critical parameters which influence the performance of a switching device. To simulate the thermal extinction of the arc and to obtain qualitative data on the processes responsible for this phenomenon, a 1D MHD fluid model in the air was developed and coupled to an external electric circuit. After thermal extinction, the dielectric strength of the hot air (< 4kK) was then estimated by the Bolsig+ software and the critical electric fields method with the temperature obtained by the MHD simulation. The influence of copper Cu and silver Ag vapors was investigated on the thermal and dielectric part of the simulation with various current forms (100A to 1kA). Finally, those values of dielectric strength have been compared to the experimental values obtained in the case of two separating silver contacts. The preliminary results seem to indicate the dielectric strength after multiples hundreds of microseconds is the same order of magnitude as experimentally found.

Keywords: MHD simulation, dielectric recovery, Bolsig+, silver vapors, copper vapors, breakers, electric arc

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Authors: Chaudhary Muhammad Aqdus Ilyas, Matthias Rehm, Kamal Nasrollahi, Thomas B. Moeslund

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This paper presents the investigation of data collection procedures, associated with robots when placed with traumatic brain injured (TBI) patients for rehabilitation purposes through facial expression and mood analysis. Rehabilitation after TBI is very crucial due to nature of injury and variation in recovery time. It is advantageous to analyze these emotional signals in a contactless manner, due to the non-supportive behavior of patients, limited muscle movements and increase in negative emotional expressions. This work aims at the development of framework where robots can recognize TBI emotions through facial expressions to perform rehabilitation tasks by physical, cognitive or interactive activities. The result of these studies shows that with customized data collection strategies, proposed framework identify facial and emotional expressions more accurately that can be utilized in enhancing recovery treatment and social interaction in robotic context.

Keywords: computer vision, convolution neural network- long short term memory network (CNN-LSTM), facial expression and mood recognition, multimodal (RGB-thermal) analysis, rehabilitation, robots, traumatic brain injured patients

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Authors: Franziska Moser, Martin Trautz, Anna-Lena Beger, Manuel Löwer, Jörg Feldhusen, Jürgen Prell, Alexandra Wormit, Björn Usadel, Christoph Kämpfer, Thomas-Benjamin Seiler, Henner Hollert

Abstract:

The demand for bio-based materials and components in architecture has increased in recent years due to society’s heightened environmental awareness. Nowadays, most components are being developed via a substitution approach, which aims at replacing conventional components with natural alternatives who are then being processed, shaped and manufactured to fit the desired application. This contribution introduces a novel approach to the development of bio-based products that decreases resource consumption and increases recyclability. In this approach, natural organisms like plants or trees are not being used in a processed form, but grow into a near net shape before then being harvested and utilized as building components. By minimizing the conventional production steps, the amount of resources used in manufacturing decreases whereas the recyclability increases. This paper presents the approach of technical product harvesting, explains the theoretical basis as well as the matching process of product requirements and biological properties, and shows first results of the growth manipulation studies.

Keywords: design with nature, eco manufacturing, sustainable construction materials, technical product harvesting

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Authors: Kevin Montanez, Patricia Garcia

Abstract:

The confinement and restrictions adopted to avoid an exponential spread of the COVID-19 have negatively impacted the Peruvian economy. In this context, Industries offering essential products could continue operating, but they have to follow safety protocols and implement strategies to ensure employee health. In view of the increasing internet access and mobile phone ownership, “Alerta Temprana”, a mobile app, was developed to self-report COVID-19 symptoms in the work context. In this study, the usability of the mobile app “Alerta Temprana” was evaluated from the perspective of health monitors and workers. In addition to reporting the metrics related to the usability of the application, the utility of the system is also evaluated from the monitors' perspective. In this descriptive study, the participants used the mobile app for two months. Afterwards, System Usability Scale (SUS) questionnaire was answered by the workers and monitors. A Usefulness questionnaire with open questions was also used for the monitors. The data related to the use of the application was collected during one month. Furthermore, descriptive statistics and bivariate analysis were used. The workers rated the application as good (70.39). In the case of the monitors, usability was excellent (83.0). The most important feature for the monitors were the emails generated by the application. The average interaction per user was 30 seconds and a total of 6172 self-reports were sent. Finally, a statistically significant association was found between the acceptability scale and the work area. The results of this study suggest that Alerta Temprana has the potential to be used for surveillance and health monitoring in any context of face-to-face modality. Participants reported a high degree of ease of use. However, from the perspective of workers, SUS cannot diagnose usability issues and we suggest we use another standard usability questionnaire to improve "Alerta Temprana" for future use.

Keywords: public health in informatics, mobile app, usability, self-report

Procedia PDF Downloads 71

Authors: Li Long, Thomas Ortlepp

Abstract:

A theoretical model for the optimization of thermopile sensor performance is developed for thermoelectric-based infrared radiation detection. It is shown that the performance of polycrystalline silicon film thermopile sensor can be optimized according to the thermoelectric quality factor, sensor layer structure factor, and sensor layout geometrical form factor. Based on the properties of electrons, phonons, grain boundaries, and their interactions, the thermoelectric quality factor of polycrystalline silicon is analyzed with the relaxation time approximation of the Boltzmann transport equation. The model includes the effect of grain structure, grain boundary trap properties, and doping concentration. The layer structure factor is analyzed with respect to the infrared absorption coefficient. The optimization of layout design is characterized by the form factor, which is calculated for different sensor designs. A double-layer polycrystalline silicon thermopile infrared sensor on a suspended membrane has been designed and fabricated with a CMOS-compatible process. The theoretical approach is confirmed by measurement results.

Keywords: polycrystalline silicon, relaxation time approximation, specific detectivity, thermal conductivity, thermopile infrared sensor

Procedia PDF Downloads 104