Search results for: Galileo new advanced features

Authors: Osamu Igawa, Hiroshi Kouchiwa, Yuji Ito

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In recent years, a reconstruction project for sewer pipelines has been progressing in Japan with the aim of renewing old sewer culverts. However, it is difficult to secure a sufficient base area for shafts in an urban area because many streets are narrow with a complex layout. As a result, construction in such urban areas is generally very demanding. In urban areas, there is a strong requirement for a safe, reliable and economical construction method that does not disturb the public’s daily life and urban activities. With this in mind, we developed a new construction method called the 'shield switching type micro-tunneling method' which integrates the micro-tunneling method and shield method. In this method, pipeline is constructed first for sections that are gently curved or straight using the economical micro-tunneling method, and then the method is switched to the shield method for sections with a sharp curve or a series of curves without establishing an intermediate shaft. This paper provides the information, features and construction examples of this newly developed method.

Keywords: micro-tunneling method, secondary lining applied RC segment, sharp curve, shield method, switching type

Procedia PDF Downloads 386

Authors: Andy Zhang, Awnik Roy, Trevor B. Chen, Bibik Oleksandr, Subodh Adhikari, Paul S. Hsu

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The durability of a combustor in gas-turbine enginesrequiresa good control of its component temperatures. Since the temperature of combustion gases frequently exceeds the melting point of the combustion liner walls, an efficient air-cooling system is significantly important to elongatethe lifetime of liner walls. To determine the effectiveness of the air-cooling system, accurate 2D surface temperature measurement of combustor liner walls is crucial for advanced engine development. Traditional diagnostic techniques for temperature measurement, such as thermocouples, thermal wall paints, pyrometry, and phosphors, have shown disadvantages, including being intrusive and affecting local flame/flow dynamics, potential flame quenching, and physical damages to instrumentation due to harsh environments inside the combustor and strong optical interference from strong combustion emission in UV-Mid IR wavelength. To overcome these drawbacks, a compact and small borescope long-wave-infrared (LWIR) sensor is developed to achieve two-dimensional high-spatial resolution, high-fidelity thermal imaging of 2D surface temperature in gas-turbine engines, providing the desired engine component temperature distribution. The compactLWIRborescope sensor makes it feasible to promote the durability of combustor in gas-turbine engines.

Keywords: borescope, engine, long-wave-infrared, sensor

Procedia PDF Downloads 116

Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

Procedia PDF Downloads 239

Authors: Palanisamy Samyraj, Sriram Yogesh, Kishore Kumar, Vaishak Cibi

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The project is about design and analysis of crankshaft using Al-Al2O3 composite material. The project is mainly concentrated across two areas one is to design and analyze the composite material, and the other is to work on the practical model. Growing competition and the growing concern for the environment has forced the automobile manufactures to meet conflicting demands such as increased power and performance, lower fuel consumption, lower pollution emission and decrease noise and vibration. Metal matrix composites offer good properties for a number of automotive components. The work reports on studies on Al-Al2O3 as the possible alternative material for a crank shaft. These material have been considered for use in various components in engines due to the high amount of strength to weight ratio. These materials are significantly taken into account for their light weight, high strength, high specific modulus, low co-efficient of thermal expansion, good air resistance properties. In addition high specific stiffness, superior high temperature, mechanical properties and oxidation resistance of Al2O3 have developed some advanced materials that are Al-Al2O3 composites. Crankshafts are used in automobile industries. Crankshaft is connected to the connecting rod for the movement of the piston which is subjected to high stresses which cause the wear of the crankshaft. Hence using composite material in crankshaft gives good fuel efficiency, low manufacturing cost, less weight.

Keywords: metal matrix composites, Al-Al2O3, high specific modulus, strength to weight ratio

Procedia PDF Downloads 260

Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

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In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

Procedia PDF Downloads 445

Authors: Chaliya Wamaloon, Malee Chaisaena, Nusara Prasertsri

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Informal caregivers providing home-based palliative and end-of-life (EOL) care to people with advanced cancer is needed, however, there has not been develop caregiver skills for the EOL in cancer patients. The aim of this research was to study the model development of caregiver skills for the EOL in cancer patients. Mixed methods research was conducted in 3 phases. All subjects were in Ubon Rathchathani Cancer Hospital including 30 EOL cancer patient caregivers, 30 EOL cancer patients, and 111 health care professionals who provided care for the EOL cancer patients and 30 EOL target participants who had been trained to be cancer patient caregivers. The research tools were questionnaires, semi structured interviews, and caregiver skills questionnaires. Data were analyzed by using percentage, mean, standard deviation, pair t-test, and content analysis. The result from this study showed the model development of caregiver skills for cancer patients consisted of 9 domains skills: 1. monitoring, 2. interpreting, 3. making decisions, 4. taking action, 5. making adjustments, 6. providing hands-on care, 7. accessing resources, 8. working together with the ill patients, and 9. navigating the healthcare system. The model composed of skills development curriculum for cancer patient caregivers, Manual of palliative care for caregivers, diary of health care records for cancer patients, and the evaluation model of development of caregiver skills for EOL cancer patients. The results of the evaluation in the development model of caregiver skills for EOL cancer patients showed that the caregivers were satisfied with the model of development for caregiver skills at a high level. The comparison of the caregiver skills before and after obtaining the development of caregivers skills revealed that it improved at a statistically significant level (p < 0.05).

Keywords: caregiver, caregiver skills, cancer patients, end of life

Procedia PDF Downloads 154

Authors: Alireza Behfar, Mohammad Mahdavi

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Nowadays, in the light of progress in the world of science, technology and communications, mastery of learning international languages is a sure and needful matter. In learning any language as a second language, progress and achieving a desirable level in speaking is indeed important for approximately all learners. In this research, we find out how preparation can influence L2 learners' oral fluency with respect to individual differences in working memory capacity. The participants consisted of sixty-one advanced L2 learners including MA students of TEFL at Isfahan University as well as instructors teaching English at Sadr Institute in Isfahan. The data collection consisted of two phases: A working memory test (reading span test) and a picture description task, with a one-month interval between the two tasks. Speaking was elicited through speech generation task in which the individuals were asked to discuss four topics emerging in two pairs. The two pairs included one simple and one complex topic and was accompanied by planning time and without any planning time respectively. Each topic was accompanied by several relevant pictures. L2 fluency was assessed based on preparation. The data were then analyzed in terms of the number of syllables, the number of silent pauses, and the mean length of pauses produced per minute. The study offers implications for strategies to improve learners’ both fluency and working memory.

Keywords: two factors, fluency, working memory capacity, preparation, L2 speech production reading span test picture description

Procedia PDF Downloads 213

Authors: Hassan Athari, Alireza Ruhi Sales, Amin Pourafshar, Seyyed Mehdi Pestei, Marc. A. Rosen

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In order to achieve high efficiency and high specific work with lower emissions, the use of advanced gas turbine cycles for power generation is useful and advantageous. Here, evaporative inlet air cooling is analyzed thermodynamically in the form of air film blade cooling of gas turbines. As the ambient temperature increases during summer months, the performance of gas turbines particularly the output power and energy efficiency are significantly decreased. The utilization of evaporative inlet cooling in gas turbine cycles increases gas turbine performance, which can assist to solve the problem in meeting the increasing demands for electrical power and offsetting shortages during peak load times. In the present research, because of the importance of turbine blade cooling, the turbine is investigated with cold compressed air used for cooling the turbine blades. The investigation of the basic and modified cycles shows that, by adding an evaporative cooler to a simple gas turbine cycle, for a turbine inlet temperature of 1400 °C, an ambient temperature of 45 °C and a relative humidity of 15%, the specific work can reach 331 (kJ/kg air), while the maximum specific work of a simple cycle for the same conditions is 273.7 (kJ/kg air). The exergy results reveal that the highest exergy destruction occurs in the combustion chamber, where the large temperature differences and highly exothermic chemical reactions are the main sources of the irreversibility.

Keywords: energy, exergy, wet compression, air-film cooling blade, gas turbine

Procedia PDF Downloads 130

Authors: Samaneh Pouyanfar, Michael Oliff

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Nowadays, customer satisfaction and discovering the superior services, are counted as vital issues in most manufacturing and services companies. In these terms, gaining the competitive advantage by a business depends on products and services which are able to cause the customer satisfaction. Given the importance of this subject, this paper tries to investigate the correlation between components of customer satisfaction and gaining the competitive advantage by the business. For this purpose, after reviewing the research literature and doing deep interviews with authors and active people in the industry, based on the variables affecting the customer satisfaction and determinant components of business competitive advantage, research questionnaire was prepared. In sum, 96 executives of PARS-KHAZAR Company were asked in a survey. The results of P.L.S. Test for the research structure analysis showed that the measuring tools in terms of technical features, like convergent and divergent validity and compound reliability were very appropriate. Moreover the results showed that, the structure of products and factors related to foundation, has affected the competitive advantage performance positively and significantly; but the influence of structure of services and business environment on competitive advantage was not confirmed.

Keywords: customer satisfaction, competitive advantage, products, foundation, home appliances

Procedia PDF Downloads 261

Authors: Insiya Kapasi, Roshni Udyavar Yehuda

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Cluster Redevelopment is a new concept in the city of Mumbai. Its regulations were laid down by the government in 2009. The concept of cluster redevelopment encompasses a group of buildings defined by a boundary as specified by the municipal authority (in this case, Mumbai), which may be dilapidated or approved for redevelopment. The study analyses the effect of cluster redevelopment in the form of renewal of old group of buildings as compared to refurbishment or restoration - on energy consumption. The methodology includes methods of assessment to determine increase or decrease in energy consumption in cluster redevelopment based on different criteria such as carpet area of the units, building envelope and its architectural elements. Results show that as the area and number of units increase the Energy consumption increases and the EPI (energy performance index) decreases as compared to the base case. The energy consumption per unit area declines by 29% in the proposed cluster redevelopment as compared to the original settlement. It is recommended that although the development is spacious and provides more light and ventilation, aspects such as glass type, traditional architectural features and consumer behavior are critical in the reduction of energy consumption.

Keywords: Cluster Redevelopment, Energy Consumption, Energy Efficiency, Typologies

Procedia PDF Downloads 136

Authors: Safia Bashir, Zulfiqar Memon

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During the last decade, renewable energy sources in particular solar photovoltaic (PV) has gained increased attention. Therefore, various PV converters topologies have emerged. Among this topology, the modular multilevel converter (MMC) is considered as one of the most promising topologies for the grid-connected PV system due to its modularity and transformerless features. When it comes to the safe operation of MMC, the balancing of the Submodules Voltages (SMs) plays a critical role. This paper proposes a balancing approach based on space vector PWM (SVPWM). Unlike the existing techniques, this method generates the switching vectors for the MMC by using only one SVPWM for the upper arm. The lower arm switching vectors are obtained by finding the complement of the upper arm switching vectors. The use of one SVPWM not only simplifies the calculation but also helped in reducing the circulating current in the MMC. The proposed method is varied through simulation using Matlab/Simulink and compared with other available modulation methods. The results validate the ability of the suggested method in balancing the SMs capacitors voltages and reducing the circulating current which will help in reducing the power loss of the PV system.

Keywords: capacitor voltage balancing, circulating current, modular multilevel converter, PV system

Procedia PDF Downloads 144

Authors: Mehrdad Gholami, Shima Behkami, Sharifuddin B. Md. Zain, Firdaus A. B. Kamaruddin

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Starting from the first application of a microwave oven for sample preparation in 1975 for the purpose of wet ashing of biological samples using a domestic microwave oven, many microwave-assisted dissolution vessels have been developed. The advanced vessels are armed with special safety valve that release the excess of pressure while the vessels are in critical conditions due to applying high power of microwave. Nevertheless, this releasing of pressure may cause lose of volatile elements. In this study Teflon bottles are designed with relatively thicker wall compared to commercial ones and a silicone based polymer was used to prepare an O-ring which plays the role of safety valve. In this design, eight vessels are located in an ABS holder to keep them stable and safe. The advantage of these vessels is that they need only 2 mL of HNO3 and 1mL H2O2 to digest different environmental samples, namely, sludge, apple leave, peach leave, spinach leave and tomato leave. In order to investigate the performance of this design an ICP-MS instrument was applied for multi elemental analysis of 20 elements on the SRM of above environmental samples both using this design and a commercial microwave digestion design. Very comparable recoveries were obtained from this simple design with the commercial one. Considering the price of ultrapure chemicals and the amount of them which normally is about 8-10 mL, these simple vessels with the procedures that will be discussed in detail are very cost effective and very suitable for environmental studies.

Keywords: inductively coupled plasma mass spectroscopy (ICP-MS), PTFE vessels, Teflon bombs, microwave digestion, trace element

Procedia PDF Downloads 320

Authors: Xiaohan Ye

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Under the new normal situation, some urban spaces with the industrial base and regional features in Zhejiang, China have been selected to build a characteristic town, a kind of environmentally-friendly development platform with city-industry integrated, in an attempt to achieve the most optimized layout of productivity with the least space resource. After analysis on the connotation, mechanism and mode of characteristic town in Zhejiang, it is suggested in this paper that characteristic town should take improving the regional ecological environment as an important object in planning strategy from the perspective of ecological concept. Improved environmental quality, optimized resource allocation, and compact industrial distribution should be realized so as to drive the regional green and sustainable development. Finally, this paper analyzes location selection, industrial distribution, spatial organization and environment construction based on the exploration of the dream town of Zhejiang province, the first batch of provincial-level characteristic towns to demonstrate how to apply the ecological concept to the design of characteristic town.

Keywords: characteristic town, ecological concept, Hangzhou dream town, planning strategy

Procedia PDF Downloads 299

Authors: António J. R. Neves, Rui Garcia, Paulo Dias, Alina Trifan

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With the aging of the world population and the continuous growth in technology, service robots are more and more explored nowadays as alternatives to healthcare givers or personal assistants for the elderly or disabled people. Any service robot should be capable of interacting with the human companion, receive commands, navigate through the environment, either known or unknown, and recognize objects. This paper proposes an approach for object recognition based on the use of depth information and color images for a service robot. We present a study on two of the most used methods for object detection, where 3D data is used to detect the position of objects to classify that are found on horizontal surfaces. Since most of the objects of interest accessible for service robots are on these surfaces, the proposed 3D segmentation reduces the processing time and simplifies the scene for object recognition. The first approach for object recognition is based on color histograms, while the second is based on the use of the SIFT and SURF feature descriptors. We present comparative experimental results obtained with a real service robot.

Keywords: object detection, feature, descriptors, SIFT, SURF, depth images, service robots

Procedia PDF Downloads 525

Authors: Orit Zeevy-Solovey

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Grammar has traditionally been taught for its own sake, emphasizing rules and drills. However, in recent years, more emphasis is given to communicative competence. Current research suggests that form-focused instruction is notably efficient when incorporated in a meaningful communicative context. It is maintained that writing tasks related to the students’ academic fields will encourage them to express themselves openly in topics that are close to their hearts, without feeling too uneasy about grammatical forms. The teacher can further reduce students’ apprehension of grammar by announcing that credit will be given for merely doing the task and that grammar mistakes will not affect the grade. Students’ linguistic errors can then be corrected by giving metalinguistic feedback which involves providing learners with some kind of explicit remark about the nature of the errors they have made. Research has also shown that learners’ developmental readiness is an important factor influencing the effectiveness of written corrective feedback. Larger effect sizes appear as the proficiency level is higher. The purposes of this paper are to demonstrate how grammar can be taught indirectly through writing tasks, and more specifically, how the use of metalinguistic written corrective feedback given to advanced English as a Foreign Language (EFL) students can raise their linguistic awareness. Since errors are not directly corrected, the students have to work out the corrections needed through exploring grammar books and websites. Longitudinal studies of metalinguistic written corrective feedback comparing the number of errors in students’ first and fourth compositions have shown a decrease in errors.

Keywords: EFL, linguistic awareness, metalinguistic corrective feedback, teaching grammar through writing

Procedia PDF Downloads 117

Authors: Erika Humphreys

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The effectiveness of treating anxiety with Reiki is explored within ten quantitative studies. The methodology utilized for a critical appraisal and systematic review of the literature is explained with inclusion and exclusion criteria. The theoretical framework for the project is grounded in the work of Hildegard Peplau, whose nursing theory based on the therapeutic use of self is foundational for Reiki implementation. A thorough critique of the literature is conducted for key components of robustness and believability. This critique is conducted using a structured guide addressing synthesized strengths and weaknesses of the body of literature. A synthesis of the literature explores the findings of the studies. This synthesis reports on Reiki’s effectiveness in treating anxiety within a variety of patient settings and populations, its effect on subscales of anxiety, physiological manifestations of anxiety, and pain associated with anxiety. Cultural considerations affecting Reiki’s potential effectiveness are discussed. Gaps in the literature are examined, including the studies’ narrow sample population, lack of participant exclusionary factors for controlled outcome data, and the lack of studies across time. Implications for future research are discussed with recommendations for expanded research that includes a broader variety of settings, age groups, and patient diagnoses, including anxiety disorders, for research data that is transferable. Implications for further practice for the advanced practice registered nurse (APRN) are explored, with the potential benefits for both providers and patients, including improved patient satisfaction and expansion of provider treatment modalities.

Keywords: Reiki, anxiety, complementary alternative medicine, pandemic

Procedia PDF Downloads 142

Authors: K. Soldatova, Y. Galerkin

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A loading factor performance is necessary for the modeling of centrifugal compressor gas dynamic performance curve. Measured loading factors are linear function of a flow coefficient at an impeller exit. The performance does not depend on the compressibility criterion. To simulate loading factor performances, the authors present two parameters: a loading factor at zero flow rate and an angle between an ordinate and performance line. The calculated loading factor performances of non-viscous are linear too and close to experimental performances. Loading factor performances of several dozens of impellers with different blade exit angles, blade thickness and number, ratio of blade exit/inlet height, and two different type of blade mean line configuration. There are some trends of influence, which are evident – comparatively small blade thickness influence, and influence of geometry parameters is more for impellers with bigger blade exit angles, etc. Approximating equations for both parameters are suggested. The next phase of work will be simulating of experimental performances with the suggested approximation equations as a base.

Keywords: loading factor performance, centrifugal compressor, impeller, modeling

Procedia PDF Downloads 335

Authors: Wiseman Emmanuel Nkhomah, Chiyembekezo Kachimanga, Julia Huggins, Fabien Munyaneza

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Background: Partners In Health – Malawi introduced one of Operational Researches called Primary Health Care (PHC) Surveys in 2020, which seeks to assess progress of delivery of care in the district. The study consists of 5 long surveys, namely; Facility assessment, General Patient, Provider, Sick Child, Antenatal Care (ANC), primarily conducted in 4 health facilities in Neno district. These facilities include Neno district hospital, Dambe health centre, Chifunga and Matope. Usually, these annual surveys are conducted from January, and the target is to present final report by June. Once data is collected and analyzed, there are a series of reviews that take place before reaching final report. In the first place, the manual process took over 9 months to present final report. Initial findings reported about 76.9% of the data that added up when cross-checked with paper-based sources. Purpose: The aim of this approach is to run away from manually pulling the data, do fresh analysis, and reporting often associated not only with delays in reporting inconsistencies but also with poor quality of data if not done carefully. This automation approach was meant to utilize features of new technologies to create visualizations, reports, and dashboards in Power BI that are directly fished from the data source – CommCare hence only require a single click of a ‘refresh’ button to have the updated information populated in visualizations, reports, and dashboards at once. Methodology: We transformed paper-based questionnaires into electronic using CommCare mobile application. We further connected CommCare Mobile App directly to Power BI using Application Program Interface (API) connection as data pipeline. This provided chance to create visualizations, reports, and dashboards in Power BI. Contrary to the process of manually collecting data in paper-based questionnaires, entering them in ordinary spreadsheets, and conducting analysis every time when preparing for reporting, the team utilized CommCare and Microsoft Power BI technologies. We utilized validations and logics in CommCare to capture data with less errors. We utilized Power BI features to host the reports online by publishing them as cloud-computing process. We switched from sharing ordinary report files to sharing the link to potential recipients hence giving them freedom to dig deep into extra findings within Power BI dashboards and also freedom to export to any formats of their choice. Results: This data automation approach reduced research timelines from the initial 9 months’ duration to 5. It also improved the quality of the data findings from the original 76.9% to 98.9%. This brought confidence to draw conclusions from the findings that help in decision-making and gave opportunities for further researches. Conclusion: These results suggest that automating the research data process has the potential of reducing overall amount of time spent and improving the quality of the data. On this basis, the concept of data automation should be taken into serious consideration when conducting operational research for efficiency and decision-making.

Keywords: reporting, decision-making, power BI, commcare, data automation, visualizations, dashboards

Procedia PDF Downloads 105

Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

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This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

Procedia PDF Downloads 117

Authors: Waddah S. Abdullah, Saleh M. Al-Sarem

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Electrokinetic remediation of contaminated soils has undoubtedly proven to be one of the most efficient techniques used to clean up soils contaminated with polar contaminants (such as heavy metals) and nonpolar organic contaminants. It can efficiently be used to clean up low permeability mud, wastewater, electroplating wastes, sludge, and marine dredging. EK processes have proved to be superior to other conventional methods, such as the pump and treat, and soil washing, since these methods are ineffective in such cases. This paper describes the use of electrokinetic remediation to clean up soils contaminated with nickel. Open cells, as well as advanced cylindrical cells, were used to perform electrokinetic experiments. Azraq green clay (low permeability soil, taken from the east part of Jordan) was used for the experiments. The clayey soil was spiked with 500 ppm of nickel. The EK experiments were conducted under direct current of 80 mA and 50 mA. Chelating agents (NaEDTA), disodium ethylene diamine-tetra-ascetic acid was used to enhance the electroremediation processes. The effect of carbonates presence in soils was, also, investigated by use of sodium carbonate. pH changes in the anode and the cathode compartments were controlled by using buffer solutions. The results showed that the average removal efficiency was 64%, for the Nickel spiked saturated clayey soil.Experiment results have shown that carbonates retarded the remediation process of nickel contaminated soils. Na-EDTA effectively enhanced the decontamination process, with removal efficiency increased from 64% without using the NaEDTA to over 90% after using Na-EDTA.

Keywords: buffer solution, contaminated soils, EDTA enhancement, electrokinetic processes, Nickel contaminated soil, soil remediation

Procedia PDF Downloads 232

Authors: Hyunbin Choi, Jihyeon Noh, Changwon Lim

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In this paper, we propose SiamMask++, an architecture that performs layer-wise aggregation and depth-wise cross-correlation and introduce multi-RPN module and multi-MASK module to improve EAO (Expected Average Overlap), a representative performance evaluation metric for Visual Object Tracking (VOT) challenge. The proposed architecture, SiamMask++, has two versions, namely, bi_SiamMask++, which satisfies the real time (56fps) on systems equipped with GPUs (Titan XP), and rf_SiamMask++, which combines mask refinement modules for EAO improvements. Tests are performed on VOT2016, VOT2018 and VOT2019, the representative datasets of Visual Object Tracking tasks labeled as rotated bounding boxes. SiamMask++ perform better than SiamMask on all the three datasets tested. SiamMask++ is achieved performance of 62.6% accuracy, 26.2% robustness and 39.8% EAO, especially on the VOT2018 dataset. Compared to SiamMask, this is an improvement of 4.18%, 37.17%, 23.99%, respectively. In addition, we do an experimental in-depth analysis of how much the introduction of features and multi modules extracted from the backbone affects the performance of our model in the VOT task.

Keywords: visual object tracking, video, deep learning, layer wise aggregation, Siamese network

Procedia PDF Downloads 134

Authors: Ana Vieira, Fernando Lau, João Pedro Mortágua, Luís Cruz, Rui Santos

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The air transport impact on environment is more than ever a limitative obstacle to the aeronautical industry continuous growth. Over the last decades, considerable effort has been carried out in order to obtain quieter aircraft solutions, whether by changing the original design or investigating more silent maneuvers. The noise propagated by rotating surfaces is one of the most important sources of annoyance, being present in most aerial vehicles. Bearing this is mind, CEIIA developed a new computational chain for noise prediction with in-house software tools to obtain solutions in relatively short time without using excessive computer resources. This work is based on the new acoustic tool, which aims to predict the rotor noise generated during steady and maneuvering flight, making use of the flexibility of the C language and the advantages of GPU programming in terms of velocity. The acoustic tool is based in the Formulation 1A of Farassat, capable of predicting two important types of noise: the loading and thickness noise. The present work describes the most important features of the acoustic tool, presenting its most relevant results and framework analyses for helicopters and UAV quadrotors.

Keywords: rotor noise, acoustic tool, GPU Programming, UAV noise

Procedia PDF Downloads 387

Authors: Hongyu Chen, Li Jiang

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Ubiquitous anomalies endanger the security of our system con- stantly. They may bring irreversible damages to the system and cause leakage of privacy. Thus, it is of vital importance to promptly detect these anomalies. Traditional supervised methods such as Decision Trees and Support Vector Machine (SVM) are used to classify normality and abnormality. However, in some case, the abnormal status are largely rarer than normal status, which leads to decision bias of these methods. Generative adversarial network (GAN) has been proposed to handle the case. With its strong generative ability, it only needs to learn the distribution of normal status, and identify the abnormal status through the gap between it and the learned distribution. Nevertheless, existing GAN-based models are not suitable to process data with discrete values, leading to immense degradation of detection performance. To cope with the discrete features, in this paper, we propose an efficient GAN-based model with specifically-designed loss function. Experiment results show that our model outperforms state-of-the-art models on discrete dataset and remarkably reduce the overhead.

Keywords: GAN, discrete feature, Wasserstein distance, multiple intermediate layers

Procedia PDF Downloads 111

Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

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Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

Procedia PDF Downloads 365

Authors: Emel Kızılkaya Aydogan, Mihrimah Ozmen, Yılmaz Delice

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In recent days, there is a change and the ongoing development of the telecommunications sector in the global market. In this sector, churn analysis techniques are commonly used for analysing why some customers terminate their service subscriptions prematurely. In addition, customer churn is utmost significant in this sector since it causes to important business loss. Many companies make various researches in order to prevent losses while increasing customer loyalty. Although a large quantity of accumulated data is available in this sector, their usefulness is limited by data quality and relevance. In this paper, a cost-sensitive feature selection framework is developed aiming to obtain the feature reducts to predict customer churn. The framework is a cost based optional pre-processing stage to remove redundant features for churn management. In addition, this cost-based feature selection algorithm is applied in a telecommunication company in Turkey and the results obtained with this algorithm.

Keywords: churn prediction, data mining, decision-theoretic rough set, feature selection

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Authors: B. Karabuluter, O. Karaduman

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Connected-Vehicles consists of intelligent vehicles, each of which can communicate with each other. Smart Cities are the most prominent application area of intelligent vehicles that can communicate with each other. The most important goal that is desired to be realized in Smart Cities planned for facilitating people's lives is to make transportation more comfortable and safe with intelligent/autonomous/driverless vehicles communicating with each other. In order to ensure these, the city must have communication infrastructure in the first place, and the vehicles must have the features to communicate with this infrastructure and with each other. In this context, intelligent transport studies to solve all transportation and traffic problems in classical cities continue to increase rapidly. In this study, current connected-vehicle applications developed for smart cities are considered in terms of communication techniques, vehicular networking, IoT, urban transportation implementations, intelligent traffic management, road safety, self driving. Taxonomies and assessments performed in the work show the trend of studies in inter-vehicle communication systems in smart cities and they are contributing to by ensuring that the requirements in this area are revealed.

Keywords: smart city, connected vehicles, infrastructures, VANET, wireless communication, intelligent traffic management

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Authors: Vallejo Michael, Acuña Edgar, Roa Juan David, Peñuela Rosa, Parra Alejandra, Casallas Daniela, Rodriguez Sheyla

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Congenital Zika Virus Syndrome is an entity composed by a variety of birth defects presented in newborns that have been exposed to the Zika Virus during pregnancy. The syndrome characteristic features are severe microcephaly, cerebral tissue abnormalities, ophthalmological abnormalities such as uveitis and chorioretinitis, arthrogryposis, clubfoot deformity and muscular tone abnormalities. The confirmatory test is the Reverse transcription polymerase chain reaction (RT-PCR) associated to the physical findings. Here we present the case of a newborn with microcephaly whose mother presented a confirmed Zika Virus infection during the third trimester of pregnancy, despite of the evident findings and the history of Zika infection the RT-PCR in amniotic and cerebrospinal fluid of the newborn was negative. RT-PCR has demonstrated a low sensibility in samples with low viral loads, reason why, we propose a clinical diagnosis in patients with clinical history of Zika Virus infection during pregnancy accompanied by evident clinical manifestations of the child.

Keywords: congenital, Zika virus, microcephaly, reverse transcriptase polymerase chain reaction

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Authors: Kelvin Lo

Abstract:

Nowadays, numerical modelling in geotechnical engineering is very common but sophisticated. Many advanced input settings and considerable computational efforts are required to optimize the design to reduce the construction cost. To optimize a design, it usually requires huge numerical models. If the optimization is conducted manually, there is a potentially dangerous consequence from human errors, and the time spent on the input and data extraction from output is significant. This paper presents an automation process introduced to numerical modelling (Plaxis 2D) of a trench excavation supported by a secant-pile retaining structure for a top-down tunnel project. Python code is adopted to control the process, and numerical modelling is conducted automatically in every 20m chainage along the 200m tunnel, with maximum retained height occurring in the middle chainage. Python code continuously changes the geological stratum and excavation depth under groundwater flow conditions in each 20m section. It automatically conducts trial and error to determine the required pile length and the use of props to achieve the required factor of safety and target displacement. Once the bending moment of the pile exceeds its capacity, it will increase in size. When the pile embedment reaches the default maximum length, it will turn on the prop system. Results showed that it saves time, increases efficiency, lowers design costs, and replaces human labor to minimize error.

Keywords: automation, numerical modelling, Python, retaining structures

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Authors: Hamed Afrasiab, Saeed Khodaygan

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Prediction of machining process capability in the design stage plays a key role to reach the precision design and manufacturing of mechanical products. Inaccuracies in machining process lead to errors in position and orientation of machined features on the part, and strongly affect the process capability in the final quality of the product. In this paper, an efficient systematic approach is given to investigate the machining errors to predict the manufacturing errors of the parts and capability prediction of corresponding machining processes. A mathematical formulation of fixture locators modeling is presented to establish the relationship between the part errors and the related sources. Based on this method, the final machining errors of the part can be accurately estimated by relating them to the combined dimensional and geometric tolerances of the workpiece – fixture system. This method is developed for uncertainty analysis based on the Worst Case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the Monte Carlo simulation results.

Keywords: process capability, machining error, dimensional and geometrical tolerances, uncertainty analysis

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Authors: Monika Paleczna, Barbara Szmigielska

Abstract:

The period of adolescence is a time when young people are becoming more and more active and conscious users of the digital world. One of the most frequently undertaken activities by them is computer games. Young players can choose from a wide range of games, including action, adventure, strategy, and logic games. The main aim of this study is to answer the question about the motivation of teenage players. The basic question is what motivates young players to play computer games and what motivates them to play a particular game. Fifty adolescents aged 15-17 participated in the study. They completed a questionnaire in which they determined what motivates them to play, how often they play computer games, and what type of computer games they play most often. It was found that entertainment and learning English are among the most important motives. The most important specific features related to a given game are the knowledge of its previous parts and the ability to play for free. The motives chosen by the players will be described in relation to the concepts of internal and external as well as approach and avoidance motivation. An additional purpose of this study is to present data concerning preferences regarding the type of games and the amount of time they spend playing.

Keywords: computer games, motivation, game preferences, adolescence

Procedia PDF Downloads 162