Search results for: adaptive soc estimation

Authors: Autcha Araveeporn

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This paper presents a study about a nonparametric regression model consisting of a smoothing spline method and a penalized spline regression method. We also compare the techniques used for estimation and prediction of nonparametric regression model. We tried both methods with crude oil prices in dollars per barrel and the Stock Exchange of Thailand (SET) index. According to the results, it is concluded that smoothing spline method performs better than that of penalized spline regression method.

Keywords: nonparametric regression model, penalized spline regression method, smoothing spline method, Stock Exchange of Thailand (SET)

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Authors: Kurniawan Adha, Wan Ismail Wan Yusoff, Luluan Almanna Lubis

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Preventing hazardous events during oil and gas operation is an important contribution of accurate pore pressure data. The availability of pore pressure data also contribute in reducing the operation cost. Suggested methods in pore pressure estimation were mostly complex by the many assumptions and hypothesis used. Basic properties which may have significant impact on estimation model are somehow being neglected. To date, most of pore pressure determinations are estimated by data model analysis and rarely include laboratory analysis, stratigraphy study or core check measurement. Basically, this study developed a model that might be applied to investigate the changes of pore pressure and effective stress due to hydrocarbon production. In general, this paper focused velocity model effect of pore pressure and effective stress changes due to hydrocarbon production with illustrated by changes in saturation. The core samples from Miri field from Sarawak Malaysia ware used in this study, where the formation consists of sandstone reservoir. The study area is divided into sixteen (16) layers and encompassed six facies (A-F) from the outcrop that is used for stratigraphy sequence model. The experimental work was firstly involving data collection through field study and developing stratigraphy sequence model based on outcrop study. Porosity and permeability measurements were then performed after samples were cut into 1.5 inch diameter core samples. Next, velocity was analyzed using SONIC OYO and AutoLab 500. Three (3) scenarios of saturation were also conducted to exhibit the production history of the samples used. Results from this study show the alterations of velocity for different saturation with different actions of effective stress and pore pressure. It was observed that sample with water saturation has the highest velocity while dry sample has the lowest value. In comparison with oil to samples with oil saturation, water saturated sample still leads with the highest value since water has higher fluid density than oil. Furthermore, water saturated sample exhibits velocity derived parameters, such as poisson’s ratio and P-wave velocity over S-wave velocity (Vp/Vs) The result shows that pore pressure value ware reduced due to the decreasing of fluid content. The decreasing of pore pressure result may soften the elastic mineral frame and have tendency to possess high velocity. The alteration of pore pressure by the changes in fluid content or saturation resulted in alteration of velocity value that has proportionate trend with the effective stress.

Keywords: pore pressure, effective stress, production, miri formation

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Authors: S. Jagadeesh Kumar

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This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

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Authors: A. Boulanoir, B. Ould Bouamama, A. Debiane, N. Achour

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The paper deals with robust Fault Detection and isolation with respect to parameter uncertainties based on linear fractional transformation form (LFT) Bond graph. The innovative interest of the proposed methodology is the use only one representation for systematic generation of robust analytical redundancy relations and adaptive residual thresholds for sensibility analysis. Furthermore, the parameter uncertainties are introduced graphically in the bond graph model. The methodology applied to the nonlinear industrial Electro-Mechanical Actuators (EMA) used in avionic systems, has determined first the structural monitorability analysis (which component can be monitored) with given instrumentation architecture with any need of complex calculation and secondly robust fault indicators for online supervision.

Keywords: bond graph (BG), electro mechanical actuators (EMA), fault detection and isolation (FDI), linear fractional transformation (LFT), mechatronic systems, parameter uncertainties, avionic system

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Authors: A. Brahma

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Analysis of deferred deformations of concrete under sustained load shows that the creep has a leading role on deferred deformations of concrete structures. Knowledge of the creep characteristics of concrete is a Necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable deformation in pre-stressed concrete or reinforced and the appropriate steps can be taken in design to accommodate this movement. In this study, we propose a prediction model that involves the acting principal parameters on the deferred behaviour of concrete structures. For the estimation of the model parameters Levenberg-Marquardt method has proven very satisfactory. A confrontation between the experimental results and the predictions of models designed shows that it is well suited to describe the evolution of the creep of concrete structures.

Keywords: concrete structure, creep, modelling, prediction

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Authors: Deon de Jager, Yahya Zweiri, Dimitrios Makris

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The three most important components in the cognitive architecture for cognitive robotics is memory representation, memory recall, and action-selection performed by the executive. In this paper, action selection, performed by the executive, is defined as a memory quantification and optimization process. The methodology describes the real-time construction of episodic memory through semantic memory optimization. The optimization is performed by set-based particle swarm optimization, using an adaptive entropy memory quantification approach for fitness evaluation. The performance of the approach is experimentally evaluated by simulation, where a UAV is tasked with the collection and delivery of a medical package. The experiments show that the UAV dynamically uses the episodic memory to autonomously control its velocity, while successfully completing its mission.

Keywords: cognitive robotics, semantic memory, episodic memory, maximum entropy principle, particle swarm optimization

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Authors: Dongho Kim, Sung Choi, Kyowoong Pee, Youngsik Cho, Seungwoo Jeong, Soo-Ho Kim

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This study is about the orbital TIG welding robot system which travels on the guide rail installed on the pipe, and welds and tracks the pipe seam using the LVS (Laser Vision Sensor) joint profile data. The orbital welding robot system consists of the robot, welder, controller, and LVS. Moreover we can define the relationship between welding travel speed and wire feed speed, and we can make the linear equation using the maximum and minimum amount of weld metal. Using the linear equation we can determine the welding travel speed and the wire feed speed accurately corresponding to the area of weld captured by LVS. We applied this orbital TIG welding robot system to the stainless steel or duplex pipe on DSME (Daewoo Shipbuilding and Marine Engineering Co. Ltd.,) shipyard and the result of radiographic test is almost perfect. (Defect rate: 0.033%).

Keywords: adaptive welding, automatic welding, pipe welding, orbital welding, laser vision sensor, LVS, welding D/B

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Authors: Rozan El-Khateeb

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This literature review examines the effectiveness of therapy programs that utilize play as an intervention for reducing symptoms associated with Autism Spectrum Disorder (ASD). Play-based therapy approaches provide a child-centered and developmentally appropriate framework to address the core symptoms of ASD, including social communication deficits, restricted and repetitive behaviors, and sensory sensitivities. The review explores various play-based therapy strategies and their impact on improving social skills, communication abilities, adaptive behaviors, and overall functioning in individuals with ASD. The findings suggest that play-based therapy programs hold promise as effective interventions for reducing symptoms and enhancing the quality of life for individuals with ASD. However, further research is necessary to establish standardized protocols, identify optimal dosage and duration, and evaluate long-term outcomes.

Keywords: autism, ABA, play, NET, systematic review

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Authors: Meriem Taleb, Ghania Tail, Fatma Zohra Kara, Brahim Djedouani, T. Moussa

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Forensic entomology has grown immensely as a discipline in the past thirty years. The main purpose of forensic entomology is to establish the post mortem interval or PMI. Three days after the death, insect evidence is often the most accurate and sometimes the only method of determining elapsed time since death. This work presents the estimation of the PMI in an experiment to test the reliability of the accumulated degree days (ADD) method and the application of this method in a real case. The study was conducted at the Laboratory of Entomology at the National Institute for Criminalistics and Criminology of the National Gendarmerie, Algeria. The domestic rabbit Oryctolagus cuniculus L. was selected as the animal model. On 08th July 2012, the animal was killed. Larvae were collected and raised to adulthood. Estimation of oviposition time was calculated by summing up average daily temperatures minus minimum development temperature (also specific to each species). When the sum is reached, it corresponds to the oviposition day. Weather data were obtained from the nearest meteorological station. After rearing was accomplished, three species emerged: Lucilia sericata, Chrysomya albiceps, and Sarcophaga africa. For Chrysomya albiceps species, a cumulation of 186°C is necessary. The emergence of adults occured on 22nd July 2012. A value of 193.4°C is reached on 9th August 2012. Lucilia sericata species require a cumulation of 207°C. The emergence of adults occurred on 23rd, July 2012. A value of 211.35°C is reached on 9th August 2012. We should also consider that oviposition may occur more than 12 hours after death. Thus, the obtained PMI is in agreement with the actual time of death. We illustrate the use of this method during the investigation of a case of a decaying human body found on 03rd March 2015 in Bechar, South West of Algerian desert. Maggots were collected and sent to the Laboratory of Entomology. Lucilia sericata adults were identified on 24th March 2015 after emergence. A sum of 211.6°C was reached on 1st March 2015 which corresponds to the estimated day of oviposition. Therefore, the estimated date of death is 1st March 2015 ± 24 hours. The estimated PMI by accumulated degree days (ADD) method seems to be very precise. Entomological evidence should always be used in homicide investigations when the time of death cannot be determined by other methods.

Keywords: forensic entomology, accumulated degree days, postmortem interval, diptera, Algeria

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Authors: S. A. Naeini, A. Khalili

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Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: settlement, Subway Line, FLAC3D, ANFIS Method

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Authors: Yul Y. Nazaruddin, Anas Y. Widiaribowo, Satriyo Nugroho

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Boiler is one of the critical unit in a petrochemical plant. Steam produced by the boiler is used for various processes in the plant such as urea and ammonia plant. An alternative method to optimize the boiler combustion system is presented in this paper. Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is applied to model the boiler using real-time operational data collected from a boiler unit of the petrochemical plant. Nonlinear equation obtained is then used to optimize the air to fuel ratio using Genetic Algorithm, resulting an optimal ratio of 15.85. This optimal ratio is then maintained constant by ratio controller designed using inverse dynamics based on ANFIS. As a result, constant value of oxygen content in the flue gas is obtained which indicates more efficient combustion process.

Keywords: ANFIS, boiler, combustion process, genetic algorithm, optimization.

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Authors: Oksana Domkina

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According to the modern economic theory, human capital became one of the main production factors and the most promising direction of investment, as such investment provides opportunity of obtaining high and long-term economic and social effects. Informational technology (IT) sector is the representative of this new economy which is most dependent on human capital as the main competitive factor. So the question for this sector is not whether investment in development of personal should be made, but what are the most effective ways of executing it and who has to pay for the education: Worker, company or government. In this paper we examine the IT sector, describe the labor market of IT workers and its development, and analyze the risks that IT companies may face if they invest in the development of their workers and what factors influence it. The main problem and difficulty of quantitative estimation of risk of investment in human capital of a company and its forecasting is human factor. Human behavior is often unpredictable and complex, so it requires specific approaches and methods of assessment. To build a comprehensive method of estimation of the risk of investment in human capital of a company considering human factor, we decided to use the method of analytic hierarchy process (AHP), that initially was created and developed. We separated three main group of factors: Risks related to the worker, related to the company, and external factors. To receive data for our research, we conducted a survey among the HR departments of Ukrainian IT companies used them as experts for the AHP method. Received results showed that IT companies mostly invest in the development of their workers, although several hire only already qualified personnel. According to the results, the most significant risks are the risk of ineffective training and the risk of non-investment that are both related to the firm. The analysis of risk factors related to the employee showed that, the factors of personal reasons, motivation, and work performance have almost the same weights of importance. Regarding internal factors of the company, there is a high role of the factor of compensation and benefits, factors of interesting projects, team, and career opportunities. As for the external environment, one of the most dangerous factor of risk is competitor activities, meanwhile the political and economical situation factor also has a relatively high weight, which is easy to explain by the influence of severe crisis in Ukraine during 2014-2015. The presented method allows to take into consideration all main factors that affect the risk of investment in human capital of a company. This gives a base for further research in this field and allows for a creation of a practical framework for making decisions regarding the personnel development strategy and specific employees' development plans for the HR departments.

Keywords: risks, personnel development, investment in development, factors of risk, risk of investment in development, IT, analytic hierarchy process, AHP

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Authors: Elana Mahboub, Lamar Bakhurji, Hind Alhindi, Sara Alesayi

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Duolingo is a revolutionary language learning platform that offers an interactive and accessible learning experience. Its gamified approach makes language learning engaging and enjoyable, with a diverse range of languages available. The platform's adaptive learning system tailors lessons to individual proficiency levels, ensuring a personalized and efficient learning journey. The incorporation of multimedia elements enhances the learning experience and promotes practical language application. Duolingo's success is attributed to its mobile accessibility, offering basic access to language courses for free, with optional premium features for those seeking additional resources. Research shows positive outcomes for users, and the app's global impact extends beyond individual learning to formal language education initiatives. Duolingo is a transformative force in language education, breaking down barriers and making language learning an attainable goal for millions worldwide.

Keywords: duolingo, artificial intelligence, artificial intelligence in duolingo, benefit of artificial intelligence

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Authors: Shuen-Tai Wang, Hsi-Ya Chang

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Cloud virtualization technologies are becoming more and more prevalent, cloud users usually encounter the problem of how to access to the virtualized remote desktops easily over the web without requiring the installation of special clients. To resolve this issue, we took advantage of the HTML5 technology and developed web-based remote desktop. It permits users to access the terminal which running in our cloud platform from anywhere. We implemented a sketch of web interface following the cloud computing concept that seeks to enable collaboration and communication among users for high performance computing. Given the development of remote desktop virtualization, it allows to shift the user’s desktop from the traditional PC environment to the cloud platform, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. This is also made possible by the low administrative costs as well as relatively inexpensive end-user terminals and reduced energy expenses.

Keywords: virtualization, remote desktop, HTML5, cloud computing

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Authors: Daniil Karzanov

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This paper studies the effect of quarterly earnings reports on the stock price. The profitability of the stock is modeled by geometric Brownian diffusion and the Constant Elasticity of Variance model. We fit several variations of stochastic differential equations to the pre-and after-report period using the Maximum Likelihood Estimation and Grid Search of parameters method. By examining the change in the model parameters after reports’ publication, the study reveals that the reports have enough evidence to be a structural breakpoint, meaning that all the forecast models exploited are not applicable for forecasting and should be refitted shortly.

Keywords: stock market, earnings reports, financial time series, structural breaks, stochastic differential equations

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Authors: Ruben Lopez-Rodriguez

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In a microgrid, diverse energy sources (both renewable and non-renewable) are combined with energy storage units to form a localized power system. Microgrids function as independent entities, capable of meeting the energy needs of specific areas or communities. This paper introduces a Model Predictive Control (MPC) approach tailored for grid-connected microgrids, aiming to optimize their operation. The formulation employs Mixed-Integer Programming (MIP) to find optimal trajectories. This entails the fulfillment of continuous and binary constraints, all while accounting for commutations between various operating conditions such as storage unit charge/discharge, import/export from/towards the main grid, as well as asset connection/disconnection. To validate the proposed approach, a microgrid case study is conducted, and the simulation results are compared with those obtained using a rule-based strategy.

Keywords: microgrids, mixed logical dynamical systems, mixed-integer optimization, model predictive control

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Authors: I Made Ginarsa, Agung Budi Muljono, I Made Ari Nrartha

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Transient voltage response appears in power system operation when an additional loading is forced to load bus of power systems. In this research, improvement of transient voltage response is done by using power system stabilizer-static var compensator (PSS-SVC) based on adaptive neuro-fuzzy inference system (ANFIS)-algorithm. The main function of the PSS is to add damping component to damp rotor oscillation through automatic voltage regulator (AVR) and excitation system. Learning process of the ANFIS is done by using off-line method where data learning that is used to train the ANFIS model are obtained by simulating the PSS-SVC conventional. The ANFIS model uses 7 Gaussian membership functions at two inputs and 49 rules at an output. Then, the ANFIS-PSS and ANFIS-SVC models are applied to power systems. Simulation result shows that the response of transient voltage is improved with settling time at the time of 4.25 s.

Keywords: improvement, transient voltage, PSS-SVC, ANFIS, settling time

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Authors: Yuanyuan Liu, Yuanqing Wang, Di Li

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Carbon dioxide (CO2) emissions mitigation from road construction activities is one of the potential pathways to deal with climate change due to its higher use of materials, machinery energy consumption, and high quantity of vehicle and equipment fuels for transportation and on-site construction activities. Aiming to assess the environmental impact of the road infrastructure construction activities and to identify hotspots of emissions sources, this study developed a life-cycle CO2 emissions assessment framework covering three stages of material production, to-site and on-site transportation under the guidance of the principle of LCA ISO14040. Then streamlined inventory analysis on sub-processes of each stage was conducted based on the budget files from cases of highway projects in China. The calculation results were normalized into functional unit represented as ton per km per lane. Then a comparison between the amount of emissions from each stage, and sub-process was made to identify the major contributor in the whole highway lifecycle. In addition, the calculating results were used to be compared with results in other countries for understanding the level of CO2 emissions associated with Chinese road infrastructure in the world. The results showed that materials production stage produces the most of the CO2 emissions (for more than 80%), and the production of cement and steel accounts for large quantities of carbon emissions. Life cycle CO2 emissions of fuel and electric energy associated with to-site and on-site transportation vehicle and equipment are a minor component of total life cycle CO2 emissions from highway project construction activities. Bridges and tunnels are dominant large carbon contributor compared to the road segments. The life cycle CO2 emissions of road segment in highway project in China are slightly higher than the estimation results of highways in European countries and USA, about 1500 ton per km per lane. In particularly, the life cycle CO2 emissions of road pavement in majority cities all over the world are about 500 ton per km per lane. However, there is obvious difference between the cities when the estimation on life cycle CO2 emissions of highway projects included bridge and tunnel. The findings of the study could offer decision makers a more comprehensive reference to understand the contribution of road infrastructure to climate change, especially understand the contribution from road infrastructure construction activities in China. In addition, the identified hotspots of emissions sources provide the insights of how to reduce road carbon emissions for development of sustainable transportation.

Keywords: carbon dioxide emissions, construction activities, highway, life cycle assessment

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Authors: Jana, Walah, Salma, Dareen

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This study looks at how the game-based learning platform Kahoot! has changed education, with a particular emphasis on how it incorporates artificial intelligence (AI). From humanly made questions to AI-driven features that improve the learning process, Kahoot! has changed since its 2013 introduction. The software successfully engages educators and students by delivering adaptive learning paths, regulating content, and offering individualized tests. This study also highlights the AI features of Kahoot! by contrasting it with comparable platforms like Quizizz, Socrative, Gimkit, and Nearpod. User satisfaction with Kahoot!'s "PDF to Story" and "Story Text Enhancer" functions ranges from moderate to high, according to a review of user input; yet, there are still issues with consistent accuracy and usability. The results demonstrate how AI can improve learning's effectiveness, adaptability, and interactivity while offering useful insights for educators and developers seeking to optimize educational tools.

Keywords: PDF to story feature, story text enhancer, AI-driven learning, interactive content creation

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Authors: Chia-Ling Li

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The scope of this article includes the production of 10,000 metric tons of non-phthalate per annum. The production process will include hydrogenation, separation, purification, and recycling of unprocessed feedstock. Based on experimental data, conversion and selectivity were chosen as reaction model parameters. The synthesis and separation processes of non-phthalate and phthalate were established by using Aspen Plus software. The article will be divided into six parts: estimation of physical properties, integration of production processes, purification case study, utility consumption, economic feasibility study and identification of bottlenecks. The purities of products was higher than 99.9 wt. %. Process parameters have important guiding significance to the commercialization of hydrogenation of phthalate.

Keywords: economic analysis, hydrogenation, non-phthalate, process simulation

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Authors: Amhimmid Mohammed Saffour, Abdelkader Salama

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Filtering is a part of image enhancement techniques, it is used to enhance certain details such as edges in the image that are relevant to the application. Additionally, filtering can even be used to eliminate unwanted components of noise. Medical images typically contain salt and pepper noise and Poisson noise. This noise appears to the presence of minute grey scale variations within the image. In this paper, different filters techniques namely (Median, Wiener, Rank order3, Rank order5, and Average) were applied on CT medical images (Brain and chest). We using all these filters to remove salt and pepper noise from these images. This type of noise consists of random pixels being set to black or white. Peak Signal to Noise Ratio (PSNR), Mean Square Error r(MSE) and Histogram were used to evaluated the quality of filtered images. The results, which we have achieved shows that, these filters, are more useful and they prove to be helpful for general medical practitioners to analyze the symptoms of the patients with no difficulty.

Keywords: CT imaging, median filter, adaptive filter and average filter, MATLAB

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Authors: Chaouch Souad, Abdou Latifa, Larbi Chrifi Alaoui

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This paper deals with sensorless backstepping control of induction motor using MRAS technique associated to sliding mode approach. A high order genetic algorithm structure is used to approximate a control law designed by the Backstepping technique, and to find the best parameters globally optimized. However, the Backstepping control approach is unsuitable for high performance applications because the need of a speed sensor for increased accuracy and the absence of any error decay mechanism. In this paper a nonlinear observer, obtained by combining sliding mode structure and model reference adaptive system (MRAS), is designed for the rotor flux and rotor speed estimations. To validate the proposed method, the results are presented for showing the improved drive characteristics and performances.

Keywords: Backstepping Control, Induction Motor, Genetic Algorithm, Sliding Mode observer

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Authors: M. B. Neace, Xin GAo

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Small entrepreneurs are ubiquitous. Regardless of location their success depends on several behavioral characteristics and several market conditions. In this concept paper, we extend this paradigm to include elements from the science of chaos. Our observations, research findings, literature search and intuition lead us to the proposition that all entrepreneurs seek increasing returns, as did the many small entrepreneurs we have interviewed over the years. There will be a few whose initial perturbations may create tsunami-like waves of increasing returns over time resulting in very large market consequences–the butterfly impact. When small entrepreneurs perturb the market-place and their initial efforts take root a series of phase-space transitions begin to occur. They sustain the stream of increasing returns by scaling up. Chaos theory contributes to our understanding of this phenomenon. Sustaining and nourishing increasing returns of small entrepreneurs as complex adaptive systems requires scaling. In this paper we focus on the most critical element of the small entrepreneur scaling process–the mindset of the owner-operator.

Keywords: entrepreneur, increasing returns, scaling, chaos

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Authors: Mohammad A. Obeidat, Ayman M. Mansour

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Capturing the dynamic behavior of the heart to improve control performance, enhance robustness, and support diagnosis is very important in establishing real time models for the heart. Control Techniques and strategies have been utilized to improve system costs, reliability, and estimation accuracy for different types of systems such as biomedical, industrial, and other systems that required tuning input/output relation and/or monitoring. Simulations are performed to illustrate potential applications of the technology. In this research, a new control technology scheme is used to enhance the performance of the Af system and meet the design specifications.

Keywords: atrial fibrillation, dynamic behavior, closed loop, signal, filter

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Authors: Afroze Ibrahim Baqapuri, Ilya Trofimov

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Sponsored search is a multi-billion dollar industry and makes up a major source of revenue for search engines (SE). Click-through-rate (CTR) estimation plays a crucial role for ads selection, and greatly affects the SE revenue, advertiser traffic and user experience. We propose a novel architecture of solving CTR prediction problem by combining artificial neural networks (ANN) with decision trees. First, we compare ANN with respect to other popular machine learning models being used for this task. Then we go on to combine ANN with MatrixNet (proprietary implementation of boosted trees) and evaluate the performance of the system as a whole. The results show that our approach provides a significant improvement over existing models.

Keywords: neural networks, sponsored search, web advertisement, click prediction, click-through rate

Procedia PDF Downloads 574

Authors: Ruxandra Aursulesei, David O’Callaghan, Cian Ryan, Diarmaid O’Cualain, Viktor Varkarakis, Alina Sultana, Joseph Lemley

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Human errors caused by drowsiness are among the leading causes of road accidents. Neurobiological research gives information about the electrical signals emitted by neurons firing within the brain. Electrical signal frequencies can be determined by attaching bio-sensors to the head surface. By observing the electrical impulses and the rhythmic interaction of neurons with each other, we can predict the mental state of a person. In this paper, we aim to better understand intersubject and intrasubject variability in terms of electrophysiological patterns that occur at the onset of drowsiness and their evolution with the decreasing of vigilance. The purpose is to lay the foundations for an algorithm that detects the onset of drowsiness before the physical signs become apparent.

Keywords: electroencephalography, drowsiness, ADAS, annotations, clinician

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Authors: Akram Khaleghei, Ghosheh Balagh, Viliam Makis

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In this paper, we investigate the residual life prediction problem for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model with unknown parameters. The parameter estimation procedure based on an EM algorithm is developed and the formulas for the conditional reliability function and the mean residual life are derived, illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, residual life prediction

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Authors: G. Karakaya, C. Türker, M. Anaklı

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It is necessary to test to see if optical devices such as camera, night vision devices are working properly. Therefore, a precision biaxial rotary system (gimbal) is required for mounting Unit Under Test, UUT. The Gimbal systems can be utilized for precise positioning of the UUT; hence, optical test can be performed with high accuracy. The weight of UUT, which is placed outside the axis of rotation, causes an off-axis moment to the mounting armature. The off-axis moment can act against the direction of movement for some orientation, thus the electrical motor, which rotates the gimbal axis, has to apply higher level of torque to guide and stabilize the system. Moreover, UUT and its mounting fixture to the gimbal can be changed, which causes change in applied resistance moment to the gimbals electrical motor. In this study, a preloaded spring is added to the gimbal system for minimizing applied off axis moment with the help of four bar mechanism. Two different possible methods for preloading spring are introduced and system optimization is performed to eliminate all moment which is created by off axis weight.

Keywords: adaptive, balancing, gimbal, mechanics, spring

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Authors: Marie Bieber, Fabrice Cosson, Olivier Schmitt

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Europe's Global Navigation Satellite System, Galileo, provides worldwide positioning and navigation services. The satellites in space are only one part of the Galileo system. An extensive ground infrastructure is essential to oversee the satellites and ensure accurate navigation signals. High reliability and availability of the entire Galileo system are crucial to continuously provide positioning information of high quality to users. Outages are tracked, and operational availability is regularly assessed. A highly flexible and adaptive tool has been developed to automate the Galileo system availability analysis. Not only does it enable a quick availability consolidation, but it also provides first steps towards improving the data quality of maintenance tickets used for the analysis. This includes data import and data preparation, with a focus on processing strings used for classification and identifying faulty data. Furthermore, the tool allows to handle a low amount of data, which is a major constraint when the aim is to provide accurate statistics.

Keywords: availability, data quality, system performance, Galileo, aerospace

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Authors: Nadezda Sergunicheva, Victoria Vasilenko

Abstract:

The emotional sphere is one of the most important aspects of the child's development and significant factor in his psychological well-being. Present research aims to identify the relationships between emotional characteristics of preschoolers and parameters of family interaction: emotional interaction, parental styles, family adaptation, and cohesion. The study involved 40 people from Saint-Petersburg: 20 children (10 boys and 10 girls) from 5 to 6 years, Mage = 5 years 4 months and 20 mothers. Methods used were: Test 'Emotional identification' by E.Izotova, Empathy test by T. Gavrilova, Children's fears test by A. Zakharov, M. Panfilova, 'Parent-child emotional interaction questionnaire' by E. Zakharova, 'Analysis of family relationships questionnaire by E. Eidemiller and V. Yustitskis, Family Adaptation and Cohesion Scales (FACES III) by D. X. Olson, J. Portner, I. Lavi. Сorrelation analysis revealed that the higher index of underdevelopment of parental feelings, the lower the child’s ability to identify emotions (p < 0,05), but at the same time, the higher ability to understand emotional states (p < 0,01), as in the case of hypoprotection (p < 0,05). Two last correlations can be explained by compensatory mechanism. This is also confirmed by negative correlations between maternal educational uncertainty and child’s ability to understand emotional states and between indulgence and child’s ability to perceive emotional states (p < 0,05). The more pronounced the phobia of a child's loss, the higher egocentric nature of child’s empathy (p < 0,05). The child’s fears have the greatest number of relationships with the characteristics of family interaction. The more pronounced mother’s positive feelings in interaction, emotional support, acceptance of himself as a parent, desire for physical contact with child and the more adaptive the family system, the less the total number of child’s fears (p < 0,05). The more the mother's ability to perceive the child's state, positive feelings in interaction, emotional support (p < 0,01), unconditional acceptance of the child, acceptance of himself as a parent and the desire for physical contact (p < 0,05), the less the amount child’s spatial fears. Socially-mediated fears are associated with less pronounced mother's positive feelings in interaction, less emotional support and deficiency of demands, obligations (p < 0,05). Fears of animals and fairy-tale characters positively correlated with the excessive demands, obligations and excessive sanctions (p < 0,05). The more emotional support (p < 0,01), mother's ability to perceive the child's state, positive feelings in interaction, unconditional acceptance of the child, acceptance of himself as a parent (p < 0,05), the less the amount child’s fears of nightmares. This kind of fears is positively correlated with excessive demands, prohibitions (p < 0,05). The more adaptive the family system (p < 0,01), the higher family cohesion, mother's acceptance of himself as a parent and preference to childish traits (p < 0,05), the less fear of death. Thus, the children's fears have the closest relationships with the characteristics of family interaction. The severity of fears, especially spatial, is connected, first of all, with the emotional side of the mother-parent interaction. Fears of animals and fairy-tale characters are associated with some characteristics of the parental styles, connected with the rigor of mothers. Correlations of the emotional identification are contradictory and require further clarification. Research is supported by RFBR №18-013-00990.

Keywords: emotional characteristics, family interaction, fears, parental styles, preschoolers

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