Search results for: smart camera networks

Authors: Marcelo Sifuentes López

Abstract:

Strategic performance definition and follow-up processes have to be clear in order to provide value in today’s competitive world. Customer expectations must be linked to internal organization strategic objectives leading to profitability and supported by visibility and flexibility among others.By taking a whole picture of the supply chain, the executive, and its team will define the current supply chain situation and an insight into potential opportunities to improve processes and provide value to main stakeholders. A systematic performance evaluation process based on operational and financial indicators defined by customer requirements needs to be implemented and periodically reviewed in order to mitigate costs and risks on time.Supplier long term relationship and collaboration plays a key role using resources available, real-time communication, innovation and new ways to capitalize global opportunities like emerging markets; efforts have to focus on the reduction of uncertainties in supply and demand. Leadership has to promote consistency of communication and execution involving suppliers, customers, and the entire organization through the support of a strategic sourcing methodology that assure the targeted competitive strategy and sustainable growth. As customer requirements and expectations are met, results could be captured in a casual picture like a “selfie”; where outcomes could be perceived from any desired angle by them; or like most “selfies”, can be taken with a camera held at arm's length by a third party company rather than using a self-timer.

Keywords: supply chain management, competitive advantage, value creation, collaboration and innovation, global marketplace

Procedia PDF Downloads 442

Authors: Carole Salis, Marie F. Wilson, Fabrizio Murgia, Cristian Lai, Franco Atzori, Giulia M. Orrù

Abstract:

ANDASA is a knowledge management platform for the capitalization of knowledge and cultural assets for the artistic and cultural sectors. It was built based on the priorities expressed by the participating artists. Through mapping artistic activities and specificities, it enables to highlight various aspects of the artistic research and production. Such instrument will contribute to create networks and partnerships, as it enables to evidentiate who does what, in what field, using which methodology. The platform is accessible to network participants and to the general public.

Keywords: cultural promotion, knowledge representation, cultural maping, ICT

Procedia PDF Downloads 426

Authors: Jocelyn L. Alimondo, Juna O. Sabelo

Abstract:

This study explored the MTB-MLE implementation practices of teachers in one monolingual elementary school and one multilingual elementary school in Benguet, Philippines. It used phenomenological approach employing participant-observation, focus group discussion and individual interview. Data were gathered using a video camera, an audio recorder, and an FGD guide and were treated through triangulation and coding. From the data collected, varied ways in implementing the MTB-MLE program were noted. These are: Teaching using a hybrid first language, teaching using a foreign LOI, using translation and multilingual instruction, and using L2/L3 to unlock L1. However, these practices come with challenges such as the a conflict between the mandated LOI and what pupils need, lack of proficiency of teachers in the mandated LOI, facing unreceptive parents, stagnation of knowledge resulting from over-familiarity of input, and zero learning resulting from an incomprehensible language input. From the practices and challenges experienced by the teachers, a model of MTB-MLE approach, the 3L-in-one approach, to teaching was created to illustrate the practice which teachers claimed to be the best way to address the challenges besetting them while at the same time satisfying the academic needs of their pupils. From the findings, this paper concludes that despite the challenges besetting the teachers, they still displayed creativity in coming up with relevant teaching practices, the unreceptiveness of some teachers and parents sprung from the fact that they do not understand the real concept of MTB-MLE, greater challenges are being faced by teachers in multilingual school due to the diverse linguistic background of their clients, and the most effective approach in implementing MTB-MLE is the multilingual approach, allowing the use of the pupils’ mother tongue, L2 (Filipino), L3 (English), and other languages familiar to the students.

Keywords: MTB-MLE Philippines, MTB-MLE model, first language, multilingual instruction

Procedia PDF Downloads 424

Authors: Abdullah A. Al Orainy

Abstract:

Small cell backhaul solutions need to be cost-effective, scalable, and easy to install. This paper presents an overview of small cell backhaul technologies. Wireless solutions including TV white space, satellite, sub-6 GHz radio wave, microwave and mmWave with their backhaul characteristics are discussed. Recent research on issues like beamforming, backhaul architecture, precoding and large antenna arrays, and energy efficiency for dense small cell backhaul with mmWave communications is reviewed. Recent trials of 5G technologies are summarized.

Keywords: backhaul, small cells, wireless, 5G

Procedia PDF Downloads 512

Authors: Joy Cao, Min Zhou

Abstract:

Purpose: Acute Type A aortic dissection is a well-known cause of extremely high mortality rate. A highly accurate and cost-effective non-invasive predictor is critically needed so that the patient can be treated at earlier stage. Although various CFD approaches have been tried to establish some prediction frameworks, they are sensitive to uncertainty in both image segmentation and boundary conditions. Tedious pre-processing and demanding calibration procedures requirement further compound the issue, thus hampering their clinical applicability. Using the latest physics informed deep learning methods to establish an accurate and cost-effective predictor framework are amongst the main goals for a better Type A aortic dissection treatment. Methods: Via training a novel physics-informed deep residual network, with non-invasive 4D MRI displacement vectors as inputs, the trained model can cost-effectively calculate all these biomarkers: aortic blood pressure, WSS, and OSI, which are used to predict potential type A aortic dissection to avoid the high mortality events down the road. Results: The proposed deep learning method has been successfully trained and tested with both synthetic 3D aneurysm dataset and a clinical dataset in the aortic dissection context using Google colab environment. In both cases, the model has generated aortic blood pressure, WSS, and OSI results matching the expected patient’s health status. Conclusion: The proposed novel physics-informed deep residual network shows great potential to create a cost-effective, non-invasive predictor framework. Additional physics-based de-noising algorithm will be added to make the model more robust to clinical data noises. Further studies will be conducted in collaboration with big institutions such as Cleveland Clinic with more clinical samples to further improve the model’s clinical applicability.

Keywords: type-a aortic dissection, deep residual networks, blood flow modeling, data-driven modeling, non-invasive diagnostics, deep learning, artificial intelligence.

Procedia PDF Downloads 89

Authors: Fengmei Li, Li Xu, Guoliang Xia

Abstract:

Lysozyme is a catalytic enzyme that performs bacterial cell lysis by cleaving the β-1,4-glycosidic bond between N-acetylmuramic acid and N-acetylglucosamine of peptidoglycan in cell walls. In the present study, an invertebrate-type (i-type) lysozyme gene was cloned from Chinese mitten crab Eriocheir sinensis (designated as EsLysozyme) based on PCR-based rapid amplification of cDNA ends (RACE) technology. The full-length cDNA of EsLysozyme was of 831 bp. SMART and SIGNALP 3.0 program analysis revealed that EsLysozyme contained a signal peptide and a destabilase domain. The five amino acid residues (Tyr63, Trp64, Tyr91, His110, Pro114) and the conserved motif GSLSCG(P/Y)FQI and CL(E/L/R/H)C(I/M)C in i-type lysozymes were also found in EsLysozyme. The high similarity of EsLysozyme with L. vannamei lysozymes and phylogenetic analysis suggested that EsLysozyme should be a new member of i-type lysozyme family.

Keywords: i-type lysozyme, Eriocheir sinensis, cloning, characterization

Procedia PDF Downloads 296

Authors: H. Hafez, A. Mekkawy, R. Rostom

Abstract:

Around 10% of the world’s CO₂ emissions could be attributed to the operational energy of buildings; that is why more research is directed towards the use of rammed earth walls which is claimed to have enhanced thermal properties compared to conventional building materials. The objective of this paper is to outline how the thermal performance of rammed earth walls compares to conventional reinforced concrete skeleton and red brick in-fill walls. For this sake, the indoor temperature and relative humidity of a classroom built with rammed earth walls and a vaulted red brick roof in the area of Behbeit, Giza, Egypt were measured hourly over 6 months using smart sensors. These parameters for the rammed earth walls were later also compared against the values obtained using a 'DesignBuilder v5' model to verify the model assumptions. The thermal insulation of rammed earth walls was found to be 30% better than this of the redbrick infill, and the recorded data were found to be almost 90% similar to the modelled values.

Keywords: rammed earth, thermal insulation, indoor air quality, design builder

Procedia PDF Downloads 146

Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

Abstract:

Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

Procedia PDF Downloads 127

Authors: Asma Ameur, Dhafer Malouche

Abstract:

Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

Procedia PDF Downloads 136

Authors: J. L. Oliver, T. Agryzkov, L. Tortosa, J. Vicent, J. Santacruz

Abstract:

This paper aims to demonstrate how the use of Network Theory can be applied to a very interesting and complex urban situation: The parts of a city which may have some patrimonial value, but because of their lack of relevant architectural elements, they are not considered to be historic in a conventional sense. In this paper, we use the suburb of La Villaflora in the city of Quito, Ecuador as our case study. We first propose a system of indicators as a tool to characterize and quantify the historic value of a geographic area. Then, we apply these indicators to the suburb of La Villaflora and use Network Theory to understand and propose actions.

Keywords: graphs, mathematics, networks, urban studies

Procedia PDF Downloads 369

Authors: Mansoureh Zangiabadi, Shamil Velji, Rajendra Kelkar, Neal Wade, Volker Pickert

Abstract:

The EU has set itself a long-term goal of reducing greenhouse gas emissions by 80-95% of the 1990 levels by 2050 as set in the Energy Roadmap 2050. This paper reports on the European Union H2020 funded E-Lobster project which demonstrates tools and technologies, software and hardware in integrating the grid distribution, and the railway power systems with power electronics technologies (Smart Soft Open Point - sSOP) and local energy storage. In this context this paper describes the existing policies and regulatory frameworks of the energy market at European level with a special focus then at National level, on the countries where the members of the consortium are located, and where the demonstration activities will be implemented. By taking into account the disciplinary approach of E-Lobster, the main policy areas investigated includes electricity, energy market, energy efficiency, transport and smart cities. Energy storage will play a key role in enabling the EU to develop a low-carbon electricity system. In recent years, Energy Storage System (ESSs) are gaining importance due to emerging applications, especially electrification of the transportation sector and grid integration of volatile renewables. The need for storage systems led to ESS technologies performance improvements and significant price decline. This allows for opening a new market where ESSs can be a reliable and economical solution. One such emerging market for ESS is R+G management which will be investigated and demonstrated within E-Lobster project. The surplus of energy in one type of power system (e.g., due to metro braking) might be directly transferred to the other power system (or vice versa). However, it would usually happen at unfavourable instances when the recipient does not need additional power. Thus, the role of ESS is to enhance advantages coming from interconnection of the railway power systems and distribution grids by offering additional energy buffer. Consequently, the surplus/deficit of energy in, e.g. railway power systems, is not to be immediately transferred to/from the distribution grid but it could be stored and used when it is really needed. This will assure better energy management exchange between the railway power systems and distribution grids and lead to more efficient loss reduction. In this framework, to identify the existing policies and regulatory frameworks is crucial for the project activities and for the future development of business models for the E-Lobster solutions. The projections carried out by the European Commission, the Member States and stakeholders and their analysis indicated some trends, challenges, opportunities and structural changes needed to design the policy measures to provide the appropriate framework for investors. This study will be used as reference for the discussion in the envisaged workshops with stakeholders (DSOs and Transport Managers) in the E-Lobster project.

Keywords: light railway, electrical distribution network, Electrical Energy Storage, policy

Procedia PDF Downloads 135

Authors: Lamiek Abraham, Xinli Du, Yohan Noh, Polin Hsu, Tingting Wu, Tom Logan, Ifan Yen

Abstract:

In the field of minimally invasive, smart medical instruments such as catheters and guidewires are typically used at a remote distance to gain access to the diseased artery, often negotiating tortuous, complex, and diseased vessels in the process. Three optical fiber sensors with a diameter of 1.5mm each that are 120° apart from each other is proposed to be mounted into a catheter-based pump device with a diameter of 10mm. These sensors are configured to solve the challenges surgeons face during insertion through curvy major vessels such as the aortic arch. Moreover, these sensors deal with providing information on rubbing the walls and shape sensing. This study presents an experimental and mathematical models of the optical fiber sensors with 2 degrees of freedom. There are two eight gear-shaped tubes made up of 3D printed thermoplastic Polyurethane (TPU) material that are connected. The optical fiber sensors are mounted inside the first tube for protection from external light and used TPU material as a prototype for a catheter. The second tube is used as a flat reflection for the light intensity modulation-based optical fiber sensors. The first tube is attached to the linear guide for insertion and withdrawal purposes and can manually turn it 45° by manipulating the tube gear. A 3D hard material phantom was developed that mimics the aortic arch anatomy structure in which the test was carried out. During the insertion of the sensors into the 3D phantom, datasets are obtained in terms of voltage, distance, and position of the sensors. These datasets reflect the characteristics of light intensity modulation of the optical fiber sensors with a plane project of the aortic arch structure shape. Mathematical modeling of the light intensity was carried out based on the projection plane and experiment set-up. The performance of the system was evaluated in terms of its accuracy in navigating through the curvature and information on the position of the sensors by investigating 40 single insertions of the sensors into the 3D phantom. The experiment demonstrated that the sensors were effectively steered through the 3D phantom curvature and to desired target references in all 2 degrees of freedom. The performance of the sensors echoes the reflectance of light theory, where the smaller the radius of curvature, the more of the shining LED lights are reflected and received by the photodiode. A mathematical model results are in good agreement with the experiment result and the operation principle of the light intensity modulation of the optical fiber sensors. A prototype of a catheter using TPU material with three optical fiber sensors mounted inside has been developed that is capable of navigating through the different radius of curvature with 2 degrees of freedom. The proposed system supports operators with pre-scan data to make maneuverability and bendability through curvy major vessels easier, accurate, and safe. The mathematical modelling accurately fits the experiment result.

Keywords: Intensity modulated optical fiber sensor, mathematical model, plane projection, shape sensing.

Procedia PDF Downloads 252

Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

Abstract:

PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

Procedia PDF Downloads 149

Authors: Carly Madge, Melanie Zurba, Ryan Bullock

Abstract:

The Boreal Forest has experienced some of the most drastic climate change-induced temperature rises in Canada, with average winter temperatures increasing by 3°C since 1948. One of the main concerns of the province of Saskatchewan, and particularly wildfire managers, is the increased risk of wildfires due to climate change. With these concerns in mind Sakaw Askiy Management Inc., a forestry corporation located in Prince Albert, Saskatchewan with operations in the Boreal Forest biome, is developing wildfire risk reduction strategies that are supported by the shareholders of the corporation as well as the stakeholders of the Prince Albert Forest Management Area (which includes citizens, hunters, trappers, cottage owners, and outfitters). In the past, wildfire management strategies implemented through harvesting have been received with skepticism by some community members of Prince Albert. Engagement of the stakeholders of the Prince Albert Management Area through the development of the wildfire risk reduction strategies aims to reduce this skepticism and rebuild some of the trust that has been lost between industry and community. This research project works with the framework of social learning, which is defined as the learning that occurs when individuals come together to form a group with the purpose of understanding environmental challenges and determining appropriate responses to them. The project evaluates the social learning processes that occur through the development of the risk reduction strategies and how the learning has allowed Sakaw to work towards implementing the strategies into their forest harvesting plans. The incorporation of wildfire risk reduction strategies works to increase the adaptive capacity of Sakaw, which in this case refers to the ability to adjust to climate change, moderate potential damages, take advantage of opportunities, and cope with consequences. Using semi-structured interviews and wildfire workshop meetings shareholders and stakeholders shared their knowledge of wildfire, their main wildfire concerns, and changes they would like to see made in the Prince Albert Forest Management Area. Interviews and topics discussed in the workshops were inductively coded for themes related to learning, adaptive capacity, areas of concern, and preferred methods of wildfire risk reduction strategies. Analysis determined that some of the learning that has occurred has resulted through social interactions and the development of networks oriented towards wildfire and wildfire risk reduction strategies. Participants have learned new knowledge and skills regarding wildfire risk reduction. The formation of wildfire networks increases access to information on wildfire and the social capital (trust and strengthened relations) of wildfire personnel. Both factors can be attributed to increases in adaptive capacity. Interview results were shared with the General Manager of Sakaw, where the areas of concern and preferred strategies of wildfire risk reduction will be considered and accounted for in the implementation of new harvesting plans. This research also augments the growing conceptual and empirical evidence of the important role of learning and networks in regional wildfire risk management efforts.

Keywords: adaptive capacity, community-engagement, social learning, wildfire risk reduction

Procedia PDF Downloads 147

Authors: Arlett A. Rosado-Torres, Ismael Marino-Tapia

Abstract:

Changes in benthic cover of coral dominated systems to macroalgae dominance are widely studied worldwide. Watershed pollutants are potentially as important as overfishing causing phase shift. In certain regions of the world most of the continental inputs are through submarine groundwater discharges (SGD), which can play a significant ecological role because the concentration of its nutrients is usually greater that the one found in surface seawater. These stressors have adversely affected coral reefs, particularly in the Caribbean. Measurements of benthic cover (with video tracing, through a Go Pro camera), reef roughness (acoustic estimates with an Acoustic Doppler Current Velocity profiler and a differential GPS), thermohaline conditions (conductivity-temperature-depth (CTD) instrument) and nutrient measurements were taken in different sites in the reef lagoon of Puerto Morelos, Q. Roo, Mexico including those with influence of SGD and without it. The results suggest a link between SGD, macroalgae cover and structural complexity. Punctual water samples and data series from a CTD Diver confirm the presence of the SGD. On the site where the SGD is, the macroalgae cover is larger than in the other sites. To establish a causal link between this phase shift and SGD, the DELFT 3D hydrodynamic model (FLOW and WAVE modules) was performed under different environmental conditions and discharge magnitudes. The model was validated using measurements of oceanographic instruments anchored in the lagoon and forereef. The SGD is consistently favoring macroalgae populations and affecting structural complexity of the reef.

Keywords: hydrodynamic model, macroalgae, nutrients, phase shift

Procedia PDF Downloads 152

Authors: A. Bendarma, T. Jankowiak, A. Rusinek, T. Lodygowski, M. Klósak, S. Bouslikhane

Abstract:

The analysis of the mechanical characteristics and dynamic behavior of aluminum alloy sheet due to perforation tests based on the experimental tests coupled with the numerical simulation is presented. The impact problems (penetration and perforation) of the metallic plates have been of interest for a long time. Experimental, analytical as well as numerical studies have been carried out to analyze in details the perforation process. Based on these approaches, the ballistic properties of the material have been studied. The initial and residual velocities laser sensor is used during experiments to obtain the ballistic curve and the ballistic limit. The energy balance is also reported together with the energy absorbed by the aluminum including the ballistic curve and ballistic limit. The high speed camera helps to estimate the failure time and to calculate the impact force. A wide range of initial impact velocities from 40 up to 180 m/s has been covered during the tests. The mass of the conical nose shaped projectile is 28 g, its diameter is 12 mm, and the thickness of the aluminum sheet is equal to 1.0 mm. The ABAQUS/Explicit finite element code has been used to simulate the perforation processes. The comparison of the ballistic curve was obtained numerically and was verified experimentally, and the failure patterns are presented using the optimal mesh densities which provide the stability of the results. A good agreement of the numerical and experimental results is observed.

Keywords: aluminum alloy, ballistic behavior, failure criterion, numerical simulation

Procedia PDF Downloads 312

Authors: Joanna Dauner, Jan Friedrich, Linda Elsner, Kora Kimpel

Abstract:

Active materials such as Electroactive Polymers (EAPs) are promising for the development of novel shape-changing interfaces. This paper explores the potential of EAPs in a multilayer unimorph structure from a design perspective to investigate the visual qualities of the material for dynamic data visualization and data physicalization. We discuss various concepts of how the material can be used for this purpose. Multilayer unimorph EAPs are of particular interest to designers because they can be easily prototyped using everyday materials and tools. By changing the structure and geometry of the EAPs, their movement and behavior can be modified. We present the results of our preliminary user testing, where we evaluated different movement patterns. As a result, we introduce a prototype display built with EAPs for dynamic data physicalization. Finally, we discuss the potentials and drawbacks and identify further open research questions for the design discipline.

Keywords: electroactive polymer, shape-changing interfaces, smart material interfaces, data physicalization

Procedia PDF Downloads 99

Authors: B. Arzhanov, A. Correia, P. Delgado, J. Meireles

Abstract:

Due to the higher power loss levels in electronic components, the thermal design of PCBs (Printed Circuit Boards) of an assembled device becomes one of the most important quality factors in electronics. Nonetheless, some of leading causes of the microelectronic component failures are due to higher temperatures, the leakages or thermal-mechanical stress, which is a concern, is the reliability of microelectronic packages. This article presents an experimental approach to measure the junction temperature of exposed pad packages. The implemented solution is in a prototype phase, using a temperature-sensitive parameter (TSP) to measure temperature directly on the die, validating the numeric results provided by the Mechanical APDL (Ansys Parametric Design Language) under same conditions. The physical device-under-test is composed by a Thermal Test Chip (TTC-1002) and assembly in a QFN cavity, soldered to a test-board according to JEDEC Standards. Monitoring the voltage drop across a forward-biased diode, is an indirectly method but accurate to obtain the junction temperature of QFN component with an applied power range between 0,3W to 1.5W. The temperature distributions on the PCB test-board and QFN cavity surface were monitored by an infra-red thermal camera (Goby-384) controlled and images processed by the Xeneth software. The article provides a set-up to monitorize in real-time the junction temperature of ICs, namely devices with the exposed pad package (i.e. QFN). Presenting the PCB layout parameters that the designer should use to improve thermal performance, and evaluate the impact of voids in solder interface in the device junction temperature.

Keywords: quad flat no-Lead packages, exposed pads, junction temperature, thermal management and measurements

Procedia PDF Downloads 286

Authors: P. Siriarchawatana, K. Leungchavaphongse, N. Covavisaruch, K. Rojananuangnit, P. Boondaeng, N. Panyayingyong

Abstract:

Glaucoma is a disease that causes visual loss in adults. Glaucoma causes damage to the optic nerve and its overall pathophysiology is still not fully understood. Vasculopathy may be one of the possible causes of nerve damage. Photographic imaging of retinal vessels by fundus camera during eye examination may complement clinical management. This paper presents an innovation for measuring central light reflex width-to-retinal vessel diameter ratio (CRR) from digital retinal photographs. Using our edge detection technique, CRRs from glaucoma and normal eyes were compared to examine differences and associations. CRRs were evaluated on fundus photographs of participants from Mettapracharak (Wat Raikhing) Hospital in Nakhon Pathom, Thailand. Fifty-five photographs from normal eyes and twenty-one photographs from glaucoma eyes were included. Participants with hypertension were excluded. In each photograph, CRRs from four retinal vessels, including arteries and veins in the inferotemporal and superotemporal regions, were quantified using edge detection technique. From our finding, mean CRRs of all four retinal arteries and veins were significantly higher in persons with glaucoma than in those without glaucoma (0.34 vs. 0.32, p < 0.05 for inferotemporal vein, 0.33 vs. 0.30, p < 0.01 for inferotemporal artery, 0.34 vs. 0.31, p < 0.01 for superotemporal vein, and 0.33 vs. 0.30, p < 0.05 for superotemporal artery). From these results, an increase in CRRs of retinal vessels, as quantitatively measured from fundus photographs, could be associated with glaucoma.

Keywords: glaucoma, retinal vessel, central light reflex, image processing, fundus photograph, edge detection

Procedia PDF Downloads 325

Authors: Duncan Wallace, M-Tahar Kechadi

Abstract:

In recent years, Machine Learning (ML) approaches have been successfully applied to an analysis of patient symptom data in the context of disease diagnosis, at least where such data is well codified. However, much of the data present in Electronic Health Records (EHR) are unlikely to prove suitable for classic ML approaches. Furthermore, as scores of data are widely spread across both hospitals and individuals, a decentralized, computationally scalable methodology is a priority. The focus of this paper is to develop a method to predict outliers in an out-of-hours healthcare provision center (OOHC). In particular, our research is based upon the early identification of patients who have underlying conditions which will cause them to repeatedly require medical attention. OOHC act as an ad-hoc delivery of triage and treatment, where interactions occur without recourse to a full medical history of the patient in question. Medical histories, relating to patients contacting an OOHC, may reside in several distinct EHR systems in multiple hospitals or surgeries, which are unavailable to the OOHC in question. As such, although a local solution is optimal for this problem, it follows that the data under investigation is incomplete, heterogeneous, and comprised mostly of noisy textual notes compiled during routine OOHC activities. Through the use of Deep Learning methodologies, the aim of this paper is to provide the means to identify patient cases, upon initial contact, which are likely to relate to such outliers. To this end, we compare the performance of Long Short-Term Memory, Gated Recurrent Units, and combinations of both with Convolutional Neural Networks. A further aim of this paper is to elucidate the discovery of such outliers by examining the exact terms which provide a strong indication of positive and negative case entries. While free-text is the principal data extracted from EHRs for classification, EHRs also contain normalized features. Although the specific demographical features treated within our corpus are relatively limited in scope, we examine whether it is beneficial to include such features among the inputs to our neural network, or whether these features are more successfully exploited in conjunction with a different form of a classifier. In this section, we compare the performance of randomly generated regression trees and support vector machines and determine the extent to which our classification program can be improved upon by using either of these machine learning approaches in conjunction with the output of our Recurrent Neural Network application. The output of our neural network is also used to help determine the most significant lexemes present within the corpus for determining high-risk patients. By combining the confidence of our classification program in relation to lexemes within true positive and true negative cases, with an inverse document frequency of the lexemes related to these cases, we can determine what features act as the primary indicators of frequent-attender and non-frequent-attender cases, providing a human interpretable appreciation of how our program classifies cases.

Keywords: artificial neural networks, data-mining, machine learning, medical informatics

Procedia PDF Downloads 131

Authors: Sabah Khan

Abstract:

The idea of universal Islam tends to exaggerate the extent of homogeneity in Islamic beliefs and practices across Muslim communities. In the age of migration, various Muslim communities are in diaspora. The immediate implication of this is what happens to Islam in diaspora? How Islam gets represented in new forms? Such pertinent questions need to be dealt with. This paper shall draw on the idea of religious transnationalism, primarily transnational Islam. There are multiple ways to conceptualize transnational phenomenon with reference to Islam in terms of flow of people, transnational organizations and networks; Ummah oriented solidarity and the new Muslim public sphere. This paper specifically deals with the new Muslim public sphere. It primarily refers to the space and networks enabled by new media and communication technologies, whereby Muslim identity and Islamic normativity are rehearsed, debated by people in different locales. A new sense of public is emerging across Muslim communities, which needs to be contextualized. This paper uses both primary and secondary data. Primary data elicited through content analysis of audio-visuals on social media and secondary sources of information ranging from books, articles, journals, etc. The basic aim of the paper is to focus on the emerging Muslim public sphere and the role of media in expanding public spheres of Islam. It also explores how Muslims in diaspora negotiate Islam and Islamic practices through media and the new Muslim public sphere. This paper cogently weaves in discussions firstly, of re-intellectualization of Islamic discourse in the public sphere. In other words, how Muslims have come to reimagine their collective identity and critically look at fundamental principles and authoritative tradition. Secondly, the emerging alternative forms of Islam by young Muslims in diaspora. In other words, how young Muslims search for unorthodox ways and media for religious articulation, including music, clothing and TV. This includes transmission and distribution of Islam in diaspora in terms of emerging ‘media Islam’ or ‘soundbite Islam’. The new Muslim public sphere has offered an arena to a large number of participants to critically engage with Islam, which leads not only to a critical engagement with traditional forms of Islamic authority but also emerging alternative forms of Islam and Islamic practices.

Keywords: Islam, media, Muslims, public sphere

Procedia PDF Downloads 270

Authors: Somayeh Pashaee

Abstract:

The ever-increasing growth of the Internet and the development of information and communication technology have prompted the politicians of different countries to use virtual networks as an efficient tool for their foreign policy. The communication of governments and countries, even in the farthest places from each other, through electronic networks, has caused vast changes in the way of statecraft and governance. Importantly, in the meantime, diplomacy, which is always based on information and communication, has been affected by the new prevailing conditions and new technologies more than other areas and has faced greater changes. The emergence of virtual space and the formation of new communication tools in the field of public diplomacy has led to the redefinition of the framework of diplomacy and politics in the international arena and the appearance of a new aspect of diplomacy called digital diplomacy. Digital diplomacy is in the concept of changing relations from a face-to-face and traditional way to a non-face-to-face and new way, and its purpose is to solve foreign policy issues using virtual space. Digital diplomacy, by affecting diplomatic procedures and its change, explains the role of technology in the visualization and implementation of diplomacy in different ways. The purpose of this paper is to investigate the position of digital diplomacy in the public diplomacy of the Islamic Republic of Iran. The paper tries to answer these two questions in a descriptive-analytical way, considering the progress of communication and the role of virtual space in the service of diplomacy, what is the approach of the Islamic Republic of Iran towards digital diplomacy and the use of a new way of establishing foreign relations in public diplomacy? What capacities and damages are facing the country after the use of this type of new diplomacy? In this paper, various theoretical concepts in the field of public diplomacy and modern diplomacy, including Geoff Berridge, Charles Kegley, Hans Tuch and Ronald Peter Barston, as well as the theoretical framework of Marcus Holmes on digital diplomacy, will be used as a conceptual basis to support the analysis. As a result, in order to better achieve the political goals of the country, especially in foreign policy, the approach of the Islamic Republic of Iran to public diplomacy with a focus on digital diplomacy should be strengthened and revised. Today, only emphasizing on advancing diplomacy through traditional methods may weaken Iran's position in the public opinion level from other countries.

Keywords: digital diplomacy, public diplomacy, islamic republic of Iran, foreign policy, opportunities and challenges

Procedia PDF Downloads 113

Authors: Xiping Wang，Shuran Yao, Liqin Dai

Abstract:

Many studies report the winter is getting warmer and the minimum air temperature is obviously rising as the important climate warming evidences. The exacerbated air temperature fluctuation tending to bring more severe weather variation is another important consequence of recent climate change which induced more disasters to crop growth in quite a certain regions. Hebei Province is an important winter wheat growing province in North of China that recently endures more winter freezing injury influencing the local winter wheat crop management. A winter wheat freezing injury assessment Bayesian Network framework was established for the objectives of estimating, assessing and predicting winter wheat freezing disasters in Hebei Province. In this framework, the freezing disasters was classified as three severity degrees (SI) among all the three types of freezing, i.e., freezing caused by severe cold in anytime in the winter, long extremely cold duration in the winter and freeze-after-thaw in early season after winter. The factors influencing winter wheat freezing SI include time of freezing occurrence, growth status of seedlings, soil moisture, winter wheat variety, the longitude of target region and, the most variable climate factors. The climate factors included in this framework are daily mean and range of air temperature, extreme minimum temperature and number of days during a severe cold weather process, the number of days with the temperature lower than the critical temperature values, accumulated negative temperature in a potential freezing event. The Bayesian Network model was evaluated using actual weather data and crop records at selected sites in Hebei Province using real data. With the multi-stage influences from the various factors, the forecast and assessment of the event-based target variables, freezing injury occurrence and its damage to winter wheat production, were shown better scoped by Bayesian Network model.

Keywords: bayesian networks, climatic change, freezing Injury, winter wheat

Procedia PDF Downloads 408

Authors: Ani Wilson Uchenna, Ogbonna Chikodi

Abstract:

This study examined the impact of artificial intelligence driven applications on banks’ performance in West Africa using Nigeria and Ghana as case studies. Specifically, the study examined the extent to which deployment of smart automated teller machine impacts the banks’ net worth within the reference period in Nigeria and Ghana. It ascertained the impact of point of sale on banks’ net worth within the reference period in Nigeria and Ghana. Thirdly, it verified the extent to which webpay services can influence banks’ performance in Nigeria and Ghana and finally, determined the impact of mobile pay services on banks’ performance in Nigeria and Ghana. The study used automated teller machine (ATM), Point of sale services (POS), Mobile pay services (MOP) and Web pay services (WBP) as proxies for explanatory variables while Bank net worth was used as explained variable for the study. The data for this study were sourced from central bank of Nigeria (CBN) Statistical Bulletin as well as Bank of Ghana (BoGH) Statistical Bulletin, Ghana payment systems oversight annual report and world development indicator (WDI). Furthermore, the mixed order of integration observed from the panel unit test result justified the use of autoregressive distributed lag (ARDL) approach to data analysis which the study adopted. While the cointegration test showed the existence of cointegration among the studied variables, bound test result justified the presence of long-run relationship among the series. Again, ARDL error correction estimate established satisfactory (13.92%) speed of adjustment from long run disequilibrium back to short run dynamic relationship. The study found that while Automated teller machine (ATM) had statistically significant impact on bank net worth (BNW) of Nigeria and Ghana, point of sale services application (POS) statistically and significantly impact on bank net worth within the study period, mobile pay services application was statistically significant in impacting the changes in the bank net worth of the countries of study while web pay services (WBP) had no statistically significant impact on bank net worth of the countries of reference. The study concluded that artificial intelligence driven application have significant an positive impact on bank performance with exception of web pay which had negative impact on bank net worth. The study recommended that management of banks both in Nigerian and Ghanaian should encourage more investments in AI-powered smart ATMs aimed towards delivering more secured banking services in order to increase revenue, discourage excessive queuing in the banking hall, reduced fraud and minimize error in processing transaction. Banks within the scope of this study should leverage on modern technologies to checkmate the excesses of the private operators POS in order to build more confidence on potential customers. Government should convert mobile pay services to a counter terrorism tool by ensuring that restrictions on over-the-counter withdrawals to a minimum amount is maintained and place sanctions on withdrawals above that limit.

Keywords: artificial intelligence (ai), bank performance, automated teller machines (atm), point of sale (pos)

Procedia PDF Downloads 7

Authors: Siwei Chang, Heng Li, Haitao Wu, Xin Fang

Abstract:

Construction robots are receiving more and more attention as a promising solution to the manpower shortage issue in the construction industry. The development of intelligent control techniques that assist in controlling the robots to avoid transparency and reflected building obstacles is crucial for guaranteeing the adaptability and flexibility of mobile construction robots in complex construction environments. With the boom of computer vision techniques, a number of studies have proposed vision-based methods for transparent obstacle avoidance to improve operation accuracy. However, vision-based methods are also associated with disadvantages such as high computational costs. To provide better perception and value evaluation, this study aims to analyze the performance of vision-based techniques for avoiding transparent building obstacles. To achieve this, commonly used sensors, including a lidar, an ultrasonic sensor, and a USB camera, are equipped on the robotic platform to detect obstacles. A Raspberry Pi 3 computer board is employed to compute data collecting and control algorithms. The turtlebot3 burger is employed to test the programs. On-site experiments are carried out to observe the performance in terms of success rate and detection distance. Control variables include obstacle shapes and environmental conditions. The findings contribute to demonstrating how effectively vision-based obstacle avoidance strategies for transparent building obstacle avoidance and provide insights and informed knowledge when introducing computer vision techniques in the aforementioned domain.

Keywords: construction robot, obstacle avoidance, computer vision, transparent obstacle

Procedia PDF Downloads 80

Authors: C. Slim

Abstract:

This paper presents an integrated model, which hybridized data envelopment analysis (DEA) and support vector machine (SVM) together, to class countries according to their efficiency and performance. This model takes into account aspects of multi-dimensional indicators, decision-making hierarchy and relativity of measurement. Starting from a set of indicators of performance as exhaustive as possible, a process of successive aggregations has been developed to attain an overall evaluation of a country’s competitiveness.

Keywords: Artificial Neural Networks (ANN), Support vector machine (SVM), Data Envelopment Analysis (DEA), Aggregations, indicators of performance

Procedia PDF Downloads 338

Authors: Amirmozafar Benshams, Khatere Kashmari, Farzad Hatami, Mesbah Saybani

Abstract:

Shape memory alloys with high capability of energy dissipation and large deformation bearing with return ability to their original shape without too much hysteresis strain have opened their place among the other damping systems as smart materials. Ninitol which is the most well-known and most used alloy material from the shape memory alloys family, has high resistance and fatigue and is coverage for large deformations. Shape memory effect and super-elasticity by shape alloys like Nitinol, are the reasons of the high power of these materials in energy depreciation. Thus, these materials are suitable for use in reciprocating dynamic loading conditions. The experiments results showed that Nitinol wires with small diameter have greater energy dissipation capability and by increase of diameter and thickness the damping capability and energy dissipation increase.

Keywords: shape memory alloys, shape memory effect, super elastic effect, nitinol, energy dissipation

Procedia PDF Downloads 515

Authors: Li Feng

Abstract:

In IEEE 802.11 networks, it is well known that the traditional time-domain contention often leads to low channel utilization. The first frequency-domain contention scheme, the time to frequency (T2F), has recently been proposed to improve the channel utilization and has attracted a great deal of attention. In this paper, we survey the latest research progress on the weighed frequency-domain contention. We present the basic ideas, work principles of these related schemes and point out their differences. This paper is very useful for further study on frequency-domain contention.

Keywords: 802.11, wireless LANs, frequency-domain contention, T2F

Procedia PDF Downloads 459

Authors: Muhammad Dawood Idrees, Maria Hafeez, Arsalan Ansari

Abstract:

Toll tax collection is the earliest method of tax collection and revenue generation. This revenue is utilized for the development of roads networks, maintenance, and connecting to roads and highways across the country. Pakistan is one of the biggest countries, covers a wide area of land, roads networks, and motorways are important source of connecting cities. Every day millions of people use motorways, and they have to stop at toll plazas to pay toll tax as majority of toll plazas are manually collecting toll tax. The purpose of this study is to calculate the waiting time of vehicles at Karachi Hyderabad (M-9) motorway. As Karachi is the biggest city of Pakistan and hundreds of thousands of people use this route to approach other cities. Currently, toll tax collection is manual system which is a major cause for long time waiting at toll plaza. This study calculates the waiting time of vehicles, fuel consumed in waiting time, manpower employed at toll plaza as all process is manual, and it also leads to mental and physical fatigue of driver. All wastages of sources are also calculated, and a most feasible automatic toll tax collection system is proposed which is not only beneficial to reduce waiting time but also beneficial in reduction of fuel, reduction of manpower employed, and reduction in physical and mental fatigue. A cost comparison in terms of wastages is also shown between manual and automatic toll tax collection system (E-Z Pass). Results of this study reveal that, if automatic tool collection system is implemented at Karachi to Hyderabad motorway (M-9), there will be a significance reduction in waiting time of vehicles, which leads to reduction of fuel consumption, environmental pollution, mental and physical fatigue of driver. All these reductions are also calculated in terms of money (Pakistani rupees) and it is obtained that millions of rupees can be saved by using automatic tool collection system which will lead to improve the economy of country.

Keywords: toll tax collection, waiting time, wastages, driver fatigue

Procedia PDF Downloads 151

Authors: Atiya Khan

Abstract:

Recent research on the condition of school education in India has reaffirmed the importance of quality teacher professional development, especially in light of the rapid changes in teaching methods, learning theories, curriculum, and major shifts in information and technology that education systems are experiencing around the world. However, the quality of programs of teacher professional development in India is often uneven, in some cases non-existing. The educational authorities in India have long recognized this and have developed a range of programs to assist in-service teacher education. But, these programs have been mostly inadequate at improving the quality of teachers in India. Policy literature and reports indicate that the unevenness of these programs and more generally the lack of quality teacher professional development in India are due to factors such as a large number of teachers, budgetary constraints, top-down decision making, teacher overload, lack of infrastructure, and little or no follow-up. The disparity between the government stated goals for quality teacher professional development in India and its inability to meet the learning needs of teachers suggests that new interventions are needed. The realization that globalization has brought about an increase in the social, cultural, political and economic interconnectedness between countries has also given rise to transnational opportunities for education systems, such as India’s, aiming to build their capacity to support teacher professional development. Moreover, new developments in communication technologies seem to present a plausible means of achieving high-quality professional development for teachers through the creation of social learning spaces, such as transnational learning networks. This case study investigates the potential of one such transnational learning network to support the quality of teacher professional development in India, namely the Australia-Asia BRIDGE School Partnerships Project. It explores the participation of some fifteen teachers and their principals from BRIDGE participating schools in Delhi region of India; focusing on their professional development expectations from the BRIDGE program and account for their experiences in the program, in order to determine the program’s potential for the professional development of teachers in this study.

Keywords: case study, Australia-Asia BRIDGE Project, teacher professional development, transnational learning networks

Procedia PDF Downloads 266