Search results for: Jonathan Thomas

Authors: Darshana Thomas, Edward Wilkie, James Irvine

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The Internet of things (IoT) is currently a highly researched topic, especially within the context of the smart home. These are small sensors that are capable of gathering data and transmitting it to a server. The majority of smart home products use protocols such as ZigBee or Bluetooth Low Energy (BLE). As these small sensors are increasing in number, the need to implement these with much more capable and ubiquitous transmission technology is necessary. The high power consumption is the reason that holds these small sensors back from using other protocols such as the most ubiquitous form of communication, WiFi. Comparing the power consumption of existing transmission technologies to one with WiFi inbuilt, would provide a better understanding for choosing between these technologies. We have developed a small IoT device with WiFi capability and proven that it is much more efficient than the first protocol, 433 MHz. We extend our work in this paper and compare WiFi power consumption with the other most widely used protocol BLE. The experimental results in this paper would conclude whether the developed prototype is capable in terms of power consumption to replace the existing protocol BLE with WiFi.

Keywords: bluetooth, internet of things (IoT), power consumption, WiFi

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Authors: Akansha Tyagi, Mehar S. Sidhu, Ankur Mandal, Sanjay Kapoor, Sunil Dahiya, Jan M. Rost, Thomas Pfeifer, Kamal P. Singh

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An all-reflective split and delay unit is designed for dispersion free measurement of broadband ultrashort pulses using a pair of reflective knife edge prism for splitting and recombining of the measuring pulse. It is based on symmetrical wavefront splitting of the measuring pulse having two separate arms to independently shape both split parts. We have validated our delay line with NIR –femtosecond pulse measurement centered at 800 nm using second harmonic-Interferometric frequency resolved optical gating (SH-IFROG). The delay line is compact, easy to align and provides attosecond stability and precision and thus make it more versatile for wide range of applications in ultrafast measurements. We envision that the present delay line will find applications in IR-IR controlling for high harmonic generation (HHG) and attosecond IR-XUV pump-probe measurements with solids and gases providing attosecond resolution and wide delay range.

Keywords: HHG, nonlinear optics, pump-probe spectroscopy, ultrafast metrology

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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: Mercy Chepkirui, Reuben Omondi, Paul Orina, Albert Getabu, Lewis Sitoki, Jonathan Munguti

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Globally, the decline in capture fisheries as a result of the growing population and increasing awareness of the nutritional benefits of white meat has led to the development of aquaculture. This is anticipated to meet the increasing call for more food for the human population, which is likely to increase further by 2050. Statistics showed that more than 50% of the global future fish diet will come from aquaculture. Aquaculture began commercializing some decades ago; this is accredited to technological advancement from traditional to modern cultural systems, including cage farming. Cage farming technology has been rapidly growing since its inception in Lake Victoria, Kenya. Currently, over 6,000 cages have been set up in Kenyan waters, and this offers an excellent opportunity for recognition of Kenya’s government tactic to eliminate food insecurity and malnutrition, create employment and promote a Blue Economy. However, being an open farming enterprise is likely to emit large bulk of waste hence altering the ecosystem integrity of the lake. This is through increased chlorophyll-a pigments, alteration of the plankton community, macroinvertebrates, fish genetic pollution, transmission of fish diseases and pathogens. Cage farming further increases the nutrient loads leading to the production of harmful algal blooms, thus negatively affecting aquatic and human life. Despite the ecological transformation, cage farming provides a platform for the achievement of the Sustainable Development Goals of 2030, especially the achievement of food security and nutrition. Therefore, there is a need for Integrated Multitrophic Aquaculture as part of Blue Transformation for ecosystem monitoring.

Keywords: aquaculture, ecosystem, blue economy, food security

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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: Michael Dare Asemoloye, Segun Gbolagade Jonathan, Rafiq Ahmad, Odunayo Joseph Olawuyi, D. O. Adejoye

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Fungi have potentials for degrading hydrocarbons through the secretion of different enzymes. Crude oil tolerance and degradation by Trichoderma harzianum was investigated in this study with its ability to produce peroxidase enzymes (LiP and MnP). Many fungal strains were isolated from rhizosphere of grasses growing on a crude oil spilled site, and the most frequent strain based on percentage incidence was further characterized using morphological and molecular characteristics. Molecular characterization was done through the amplification of Ribosomal-RNA regions of 18s (1609-1627) and 28s (287-266) using ITS1 and ITS4 combinations and it was identified using NCBI BLAST tool. The selected fungus was also subjected to an in-vitro tolerance test at crude oil concentrations of 5, 10, 15, 20 and 25% while 0% served as control. In addition, lignin peroxidase genes (lig1-6) and manganese peroxidase gene (mnp) were detected and expressed in this strain using RT-PCR technique, its peroxidase producing activities was also studied in aliquots (U/ml). This strain had highest incidence of 80%, it was registered in NCBI as Trichoderma harzianum asemoJ KY488466. The strain KY488466 responded to crude oil concentrations as it increase, the dose inhibition response percentage (DIRP) increased from 41.67 to 95.41 at 5 to 25 % crude oil concentrations. All the peroxidase genes are present in KY488466, and expressed with amplified 900-1000 bp through RT-PCR technique. In this strain, lig2, lig4 and mnp genes were over-expressed, lig 6 was moderately expressed, while none of the genes was under-expressed. The strain also produced 90±0.87 U/ml lignin peroxidase and 120±1.23 U/mil manganese peroxidase enzymes in aliquots. These results imply that KY488466 can tolerate and survive high crude oil concentration and could be exploited for bioremediation of oil-spilled soils, the produced peroxidase enzymes could also be exploited for other biotechnological experiments.

Keywords: crude oil, enzymes, expression, peroxidase genes, tolerance, Trichoderma harzianum

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Authors: Kushal Gowda Jayaram, Joseph Huret, Jonathan Quibel, Walter-John Chitty, Gilbert Henaff

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Thermal aging is one of the concerns for the long-term operation of nuclear power plants. Indeed, components in the primary circuit undergo thermal aging while exposed to the chemically active environment of Pressurized Water Reactors (PWRs) over time. Among the materials used in the reactor components, Alloy 690 can be found in some critical components for nuclear safety. Despite its importance, research on the effect of thermal aging on the microstructural changes and low cycle fatigue (LCF) behavior of Alloy 690 remains limited. This study aims to assess the impact of thermal aging on the fatigue life of Alloy 690. The as-received sample underwent aging at 420°C for 4000 hours, representing the equivalent aging of 60 years in reactor working conditions. First, the characterization of the area and density of intergranular and intragranular precipitates was performed to understand the microstructural changes in the aged specimen. Then, low cycle fatigue tests were conducted on the as received and aged samples at varying strain amplitudes. To investigate the influence of thermal aging on the fatigue behavior of Alloy 690, fracture surfaces were analyzed to estimate fatigue crack growth rates based on striation spacing measurements. Additionally, the axially cut fractured samples have undergone analysis using Electron Backscatter Diffraction (EBSD) to understand the effect of aging on strain localization near the crack path. Results indicate that while the characterization of the area and density of intergranular precipitates in the aged specimen (for 2000 hours, approximately 30 years) showed no significant changes, there was a slight increase in the area and density of intragranular precipitates under the same conditions.

Keywords: alloy 690, thermal aging, low cycle fatigue, precipitates

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Authors: Louise Moles, Steve Riley, Sarah D. Lichenstein, Marzieh Babaeianjelodar, Robert Kohler, Annie Cheng, Corey Horien Abigail Greene, Wenjing Luo, Jonathan Ahern, Bohan Xu, Yize Zhao, Chun Chieh Fan, R. Todd Constable, Sarah W. Yip

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Background: Risks for depression are myriad and include both genetic and brain-based factors. However, relationships between these systems are poorly understood, limiting understanding of disease etiology, particularly at the developmental level. Methods: We use a data-driven machine learning approach connectome-based predictive modeling (CPM) to identify functional connectivity signatures associated with polygenic risk scores for depression (DEP-PRS) among youth from the Adolescent Brain and Cognitive Development (ABCD) study across diverse brain states, i.e., during resting state, during affective working memory, during response inhibition, during reward processing. Results: Using 10-fold cross-validation with 100 iterations and permutation testing, CPM identified connectivity signatures of DEP-PRS across all examined brain states (rho’s=0.20-0.27, p’s<.001). Across brain states, DEP-PRS was positively predicted by increased connectivity between frontoparietal and salience networks, increased motor-sensory network connectivity, decreased salience to subcortical connectivity, and decreased subcortical to motor-sensory connectivity. Subsampling analyses demonstrated that model accuracies were robust across random subsamples of N’s=1,000, N’s=500, and N’s=250 but became unstable at N’s=100. Conclusions: These data, for the first time, identify neural networks of polygenic depression risk in a large sample of youth before the onset of significant clinical impairment. Identified networks may be considered potential treatment targets or vulnerability markers for depression risk.

Keywords: genetics, functional connectivity, pre-adolescents, depression

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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: Samuel Asiedu-Addo, Jonathan Annan, Yarhands Dissou Arthur

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The study aims to explore the relational effect of lecturers’ personal attribute on student’s interest in statistics. In this study personal attributes of lecturers’ such as lecturer’s dynamism, communication strategies and rapport in the classroom as well as applied knowledge during lecture were examined. Here, exploratory research design was used to establish the effect of lecturer’s personal attributes on student’s interest. Data were analyzed by means of confirmatory factor analysis and structural equation modeling (SEM) using the SmartPLS 3 program. The study recruited 376 students from the faculty of technical and vocational education of the University of Education Winneba Kumasi campus, and Ghana Technology University College as well as Kwame Nkrumah University of science and Technology. The results revealed that personal attributes of an effective lecturer were lecturer’s dynamism, rapport, communication and applied knowledge contribute (52.9%) in explaining students interest in statistics. Our regression analysis and structural equation modeling confirm that lecturers personal attribute contribute effectively by predicting student’s interest of 52.9% and 53.7% respectively. The paper concludes that the total effect of a lecturer’s attribute on student’s interest is moderate and significant. While a lecturer’s communication and dynamism were found to contribute positively to students’ interest, they were insignificant in predicting students’ interest. We further showed that a lecturer’s personal attributes such as applied knowledge and rapport have positive and significant effect on tertiary student’s interest in statistic, whilst lecturers’ communication and dynamism do not significantly affect student interest in statistics; though positively related.

Keywords: student interest, effective teacher, personal attributes, regression and SEM

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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: Jonathan K. Hill

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The transportation networks throughout Africa remain the only transportation infrastructure system in the world that is attacked by terrorists at a high frequency, so the international community can learn from each attack. The targeting of transportation should be recognized as a direct attack against a civilian population, so the international community should work to better understand the types of attacks utilized, the types of improvised explosive device designs adapted to transportation targets, and the ways the various modes of transportation have been attacked throughout the continent. Some countries have seen grenade attacks that have resulted in only injuries, while some countries have experienced large vehicle bombings that have resulted in hundreds of injuries and numerous deaths. With insurgencies, explosive devices have been small, complex, and generally target an enemy of the insurgency. With terrorist bombings, the explosive devices have been large, brazen, and targeted at civilian populations. And, these civilian populations are easily targeted within the transportation system. The presentation provided by Assess Africa LLC is titled ‘Evolution of Bombings Against Transportation Infrastructure’ and covers improvised explosive device characteristics, how improvised explosive devices have been adapted to transportation targets in Africa, analyses recent incidents, and provides some advice for effective protective measures. A main component of the improvised explosive device characteristics portion of the presentation focuses on the link between explosive device components, the intelligence network, and the bomb-builder’s network. By understanding the components, how the use of various components can be linked to a terrorist group’s capabilities, and how the bomb-builder acquires materials, the analysis of improvised explosive device attacks takes on a new direction – one that focuses on defeating the network instead of merely reviewing incidents of the past.

Keywords: Africa, bombings, critical infrastructure protection, transportation security

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Authors: Jonathan Matyenyika

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In recent years, automobile manufacturers have increasingly produced vehicles equipped with cutting-edge automotive electronic technology to match the fast-paced digital world of today; this has brought about various benefits in different business sectors that make use of these vehicles as a means of turning over a profit. In the logistics industry, vehicles equipped with this technology have proved to be very utilitarian; this paper focuses on the benefits automobile electronic equipped vehicles have in the logistics industry. Automotive vehicle manufacturers have introduced new technological electronic features to their vehicles to enhance and improve the overall performance, efficiency, safety and driver comfort. Some of these features have proved to be beneficial to logistics operators. To start with the introduction of adaptive cruise control in long-distance haulage vehicles, to see how this system benefits the drivers, we carried out research in the form of interviews with long-distance truck drivers with the main question being, what major difference have they experienced since they started to operate vehicles equipped with this technology to which most stated they had noticed that they are less tired and are able to drive longer distances as compared to when they used vehicles not equipped with this system. As a result, they can deliver faster and take on the next assignment, thus improving efficiency and bringing in more monetary return for the logistics company. Secondly, the introduction of electric hybrid technology, this system allows the vehicle to be propelled by electric power stored in batteries located in the vehicle instead of fossil fuel. Consequently, this benefits the logistic company as vehicles become cheaper to run as electricity is more affordable as compared to fossil fuel. The merging of electronic systems in vehicles has proved to be of great benefit, as my research proves that this can benefit the logistics industry in plenty of ways.

Keywords: logistics, manufacturing, hybrid technology, haulage vehicles

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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: Aidan Jacobsen, Morgan Motia, David Sam, Jonathan Mudge

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Background: The Centers for Disease Control (CDC) lists vaccine requirements for children under two years old to correlate with development markers. CDC lists the coverage by age 24 months to be at least 90% nationally and 84% for Rhode Island Blackstone Valley Community Health Center (BVCHC) in Central Falls, Rhode Island, currently has a completed vaccination rate of 51% for children by the age of 24 months. Current barriers to care for up to date well child vaccinations include lack of transportation, parental work, childcare, and other social stressors. Objective: Increase the vaccination rate of children under the age of 24 months at BVCHC. Conduct a literature review to identify the common barriers preventing children under 24 months from receiving vaccinations. Reduce the barriers to expand access to vaccination care for infants Methods: Setting: Blackstone Valley Community Health Center, Pawtucket, RI Participants: (n=41), Patients between the age of 20-24 months, not up to date with the CDC vaccination recommendations and without a future appointment. QI Intervention: Patients were contacted via phone and offered an appointment during extra Saturday clinic hours in order to receive up to date vaccine care. A Saturday vaccine clinic was established specifically for patients in need of vaccines and having identified barriers to care. Conclusions: Expanding clinic hours and targeting non vaccine up –to-date patients can increase the current standard of childhood immunizations at BVCHC. Overcoming barriers preventing childhood immunization can improve access to providing up to date vaccinations. Other barriers still deter from reaching the national standard of immunizations rates.

Keywords: vaccinations, well child care, barriers to care, social determinants of health

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Authors: Jonathan Martino, Kristof Harri

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In some cases, the increase in computing resources makes simulation methods more affordable. The increase in processing speed also allows real time analysis or even more rapid tests analysis offering a real tool for test prediction and design process optimization. Vibration tests are no exception to this trend. The so called ‘Virtual Vibration Testing’ offers solution among others to study the influence of specific loads, to better anticipate the boundary conditions between the exciter and the structure under test, to study the influence of small changes in the structure under test, etc. This article will first present a virtual vibration test modeling with a main focus on the shaker model and will afterwards present the experimental parameters determination. The classical way of modeling a shaker is to consider the shaker as a simple mechanical structure augmented by an electrical circuit that makes the shaker move. The shaker is modeled as a two or three degrees of freedom lumped parameters model while the electrical circuit takes the coil impedance and the dynamic back-electromagnetic force into account. The establishment of the equations of this model, describing the dynamics of the shaker, is presented in this article and is strongly related to the internal physical quantities of the shaker. Those quantities will be reduced into global parameters which will be estimated through experiments. Different experiments will be carried out in order to design an easy and practical method for the identification of the shaker parameters leading to a fully functional shaker model. An experimental modal analysis will also be carried out to extract the modal parameters of the shaker and to combine them with the electrical measurements. Finally, this article will conclude with an experimental validation of the model.

Keywords: lumped parameters model, shaker modeling, shaker parameters, state-space, virtual vibration

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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: Frederic Schenker, Jonathan J. Hendriks, Gianluca Nicchiotti

Abstract:

In a product industrialization perspective, the end-product shall always be at the peak of technological advancement and developed in the shortest time possible. Thus, the constant growth of complexity and a shorter time-to-market calls for important changes on both the technical and business level. Undeniably, the common understanding of the system is beclouded by its complexity which leads to the communication gap between the engineers and the sale department. This communication link is therefore important to maintain and increase the information exchange between departments to ensure a punctual and flawless delivery to the end customer. This evolution brings engineers to reason with more hindsight and plan ahead. In this sense, they use new viewpoints to represent the data and to express the model deliverables in an understandable way that the different stakeholder may identify their needs and ideas. This article focuses on the usage of Model-Based System Engineering (MBSE) in a perspective of system industrialization and reconnect the engineering with the sales team. The modeling method used and presented in this paper concentrates on displaying as closely as possible the needs of the customer. Firstly, by providing a technical solution to the sales team to help them elaborate commercial offers without omitting technicalities. Secondly, the model simulates between a vast number of possibilities across a wide range of components. It becomes a dynamic tool for powerful analysis and optimizations. Thus, the model is no longer a technical tool for the engineers, but a way to maintain and solidify the communication between departments using different views of the model. The MBSE contribution to cost optimization during New Product Introduction (NPI) activities is made explicit through the illustration of a case study describing the support provided by system models to architectural choices during the industrialization of a novel optical sensor.

Keywords: analytical model, architecture comparison, MBSE, product industrialization, SysML, system thinking

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Authors: Stephan Koehler, Thomas Friedli

Abstract:

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

Abstract:

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

Abstract:

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

Abstract:

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

Procedia PDF Downloads 59