Search results for: edge detection algorithm

Authors: Mateusz Paszko, Mirosław Wendeker, Adam Majczak

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Every material body that temperature is higher than 0K (absolute zero) emits infrared radiation to the surroundings. Infrared radiation is highly meaningful in military aviation, especially in military applications of helicopters. Helicopters, in comparison to other aircraft, have much lower flight speeds and maneuverability, which makes them easy targets for actual combat assets like infrared-guided missiles. When designing new helicopter types, especially for combat applications, it is essential to pay enormous attention to infrared emissions of the solid parts composing the helicopter’s structure, as well as to exhaust gases egressing from the engine’s exhaust system. Due to their high temperature, exhaust gases, egressed to the surroundings are a major factor in infrared radiation emission and, in consequence, detectability of a helicopter performing air combat operations. Protection of the helicopter in flight from early detection, tracking and finally destruction can be realized in many ways. This paper presents the analysis of possibilities to decrease the infrared radiation level that is emitted to the environment by helicopter in flight, by cooling exhaust in special ejection-based coolers. The paper also presents the concept 3D model and results of numeric analysis of ejective-based cooler cooperation with PA-10W turbine engine. Numeric analysis presented promising results in decreasing the infrared emission level by PA W-3 helicopter in flight.

Keywords: exhaust cooler, helicopter propulsion, infrared radiation, stealth

Procedia PDF Downloads 348

Authors: Obiora E. Anisiji, Jeremiah L. Chukwuneke, Chinonso H. Achebe, Paul C. Okolie

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This work developed a mathematical model of a biogas plant from a mechanistic point of view, for urban area clean energy requirement. It aimed at integrating thermodynamics; which deals with the direction in which a process occurs and Biochemical kinetics; which gives the understanding of the rates of biochemical reaction. The mathematical formulation of the proposed gas plant follows the fundamental principles of thermodynamics, and further analysis were accomplished to develop an algorithm for evaluating the plant performance preferably in terms of daily production capacity. In addition, the capacity of the plant is equally estimated for a given cycle of operation and presented in time histories. A nominal 1500m3 biogas plant was studied characteristically and its performance efficiency evaluated. It was observed that the rate of biogas production is essentially a function of enthalpy ratio, the reactor temperature, pH, substrate concentration, rate of degradation of the biomass, and the accumulation of matter in the system due to bacteria growth. The results of this study conform to a very large extent with reported empirical data of some existing plant and further model validations were conducted in line with classical records found in literature.

Keywords: anaerobic digestion, biogas plant, biogas production, bio-reactor, energy, fermentation, rate of production, temperature, therm

Procedia PDF Downloads 435

Authors: Itti Bist, Snehasis Bhakta, Di Jiang, Tia E. Keyes, Aaron Martin, Robert J. Forster, James F. Rusling

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DNA damage from metabolites of lipophilic drugs and pollutants, generated by enzymes, represents a major toxicity pathway in humans. These metabolites can react with DNA to form either 8-oxo-7,8-dihydro-2-deoxyguanosine (8-oxodG), which is the oxidative product of DNA or covalent DNA adducts, both of which are genotoxic and hence considered important biomarkers to detect cancer in humans. Therefore, detecting reactions of metabolites with DNA is an effective approach for the safety assessment of new chemicals and drugs. Here we describe a novel electrochemiluminescent (ECL) sensor array which can detect DNA oxidation and chemical DNA damage in a single array, facilitating a more accurate diagnostic tool for genotoxicity screening. Layer-by-layer assembly of DNA and enzyme are assembled on the pyrolytic graphite array which is housed in a microfluidic device for sequential detection of two type of the DNA damages. Multiple enzyme reactions are run on test compounds using the array, generating toxic metabolites in situ. These metabolites react with DNA in the films to cause DNA oxidation and chemical DNA damage which are detected by ECL generating osmium compound and ruthenium polymer, respectively. The method is further validated by the formation of 8-oxodG and DNA adduct using similar films of DNA/enzyme on magnetic bead biocolloid reactors, hydrolyzing the DNA, and analyzing by liquid chromatography-mass spectrometry (LC-MS). Hence, this combined DNA/enzyme array/LC-MS approach can efficiently explore metabolic genotoxic pathways for drugs and environmental chemicals.

Keywords: biosensor, electrochemiluminescence, DNA damage, microfluidic array

Procedia PDF Downloads 368

Authors: Husain Rajib, K. S. Kishor, D. G. Jewel

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Background: Uncorrected refractive error is a common cause of preventable visual impairment in pediatric age group which can be lead to blindness but early detection of visual impairment can reduce the problem that will have good effective in education and more involve in social activities. Glasses are the cheapest and commonest form of correction of refractive errors. To achieve this, patient must exhibit good compliance to spectacle wear. Patient’s attitude and perception of glasses and eye health could affect compliance. Material and method: A Prospective community based cross sectional study was designed in order to evaluate the knowledge, attitude and practices about refractive errors and eye health amongst the primary school going children. Result: Among 140 respondents, 72 were males and 68 were females. We found 50 children were myopic and out of them 26 were male and 24 were female, 27 children were hyperopic and out of them 14 were male and 13 were female. About 63 children were astigmatic and out of them 32 were male and 31 were female. The level of knowledge, attitude was satisfactory. The attitude of the students, teachers and parents was cooperative which helps to do cycloplegic refraction. Practice was not satisfactory due to social stigma and information gap. Conclusion: Knowledge of refractive error and acceptance of glasses for the correction of uncorrected refractive error. Public awareness program such as vision screening program, eye camp, and teachers training program are more beneficial for wearing and prescribing spectacle.

Keywords: refractive error, stigma, knowledge, attitude, practice

Procedia PDF Downloads 264

Authors: Mohammed Cherifi, Abderrahmane Benbrik, Siham Laouar-Meftah, Denis Lemonnier

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The present study was conducted to numerically investigate the interaction of non-gray-gas radiation with opposed mixed convection in a vertical two-sided lid-driven square cavity. The opposing flows are simultaneously generated by the vertical boundary walls which slide at a constant speed and the natural convection due to the gradient temperature of differentially heated cavity. The horizontal walls are thermally insulated and perfectly reflective. The enclosure is filled with air-H2O-CO2 gas mixture, which is considered as a non-gray, absorbing, emitting and not scattering medium. The governing differential equations are solved by a finite-volume method, by adopting the SIMPLER algorithm for pressure–velocity coupling. The radiative transfer equation (RTE) is solved by the discrete ordinates method (DOM). The spectral line weighted sum of gray gases model (SLW) is used to account for non-gray radiation properties. Three cases of the effects of radiation (transparent, gray and non-gray medium) are studied. Comparison is also made with the parametric studies of the effect of the mixed convection parameter, Ri (0.1, 1, 10), on the fluid flow and heat transfer have been performed.

Keywords: opposed mixed convection, non-gray-gas radiation, two-sided lid-driven cavity, discrete ordinate method, SLW model

Procedia PDF Downloads 320

Authors: Yih-Chien Chen, Yue-Xuan Du, Min-Zhe Weng

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Carbon monoxide is a substance produced by the incomplete combustion. It is toxic even at concentrations of less than 100ppm. Since it is colorless and odorless, it is difficult to detect. CO sensors have been developed using a variety of physical mechanisms, including semiconductor oxides, solid electrolytes, and organic semiconductors. Many works have focused on using semiconducting sensors composed of sensitive layers such as ZnO, TiO₂, and NiO with high sensitivity for gases. However, these sensors working at high temperatures increased their power consumption. On the other hand, the dielectric resonator (DR) is attractive for gas detection due to its large surface area and sensitivity for external environments. Materials that are to be employed in sensing devices must have a high-quality factor. Numerous researches into the fergusonite-type structure and related ceramic systems have explored. Extensive research into RENbO₄ ceramics has explored their potential application in resonators, filters, and antennas in modern communication systems, which are operated at microwave frequencies. Nd(Ti₀.₅W₀.₅)O₄ ceramics were synthesized herein using the conventional mixed-oxide method. The Nd(Ti₀.₅W₀.₅)O₄ ceramics were prepared using the conventional solid-state method. Dielectric constants (εᵣ) of 15.4-19.4 and quality factor (Q×f) of 3,600-11,100 GHz were obtained at sintering temperatures in the range 1425-1525°C for 4 h. The dielectric properties of the Nd(Ti₀.₅W₀.₅)O₄ ceramics at microwave frequencies were found to vary with the sintering temperature. For a further understanding of these microwave dielectric properties, they were analyzed by densification, X-ray diffraction (XRD), and by making microstructural observations.

Keywords: dielectric constant, dielectric resonators, sensors, quality factor

Procedia PDF Downloads 260

Authors: Karel Šebesta, Jiří Žáček, Matuš Salva, Mohammad Housam

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Drivers of agricultural vehicles are exposed to continuous vibration caused by driving over rough terrain. The long-term effects of these vibrations could start with a decreased level of vigilance at work and could reach the level of several health problems. Therefore, eliminating the vibration to maximize the comfort of the driver is essential for better/longer performance. One of the modern damping systems, which can deal with this problem is the Semi-active (S/A) suspension system featuring a Magnetorheological (MR) damper. With this damper, the damping level can be adjusted using varying currents through the coil. Adjustments of the damping force can be carried out continuously based on the evaluated data (position and acceleration of seat) by the control algorithm. The advantage of this system is the wide dynamic range and the high speed of force response time. Compared to other S/A or active systems, the MR damper does not need as much electrical power, and the system is much simpler. This paper aims to prove the effectiveness of this damping system used in the tractor seat. The vibration testing stand was designed and manufactured specifically for this type of research, which is used to simulate vibrations with constant amplitude at variable frequency.

Keywords: magnetorheological damper, semi-active suspension, seat scissor mechanism, sky-hook

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Authors: Muhammad Younas, Sidra Sawati, M. Razzaq Athar

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Organizational development history reveals that it has ever been a challenge to identify and fathom the role of talent management, career development and compensation management towards employees’ retention and organizational performance. Organizations strive hard to measure the impact of all those factors which affect employee retention and organizational performance. Researchers have worked in great deal in order to know the relationship of independent variables i.e. Talent Management, Career Development and Compensation Management on dependent variables i.e. Employee Retention and Organizational Performance. Employees adorned with latest skills with long lasting loyalty play a significant role towards successful achievement of short term as well as long term goals of the organizations. Retention of valuable and resourceful employees for a longer time is equally essential for meeting the set goals. The organizations which spend reasonable chunk of their resources for taking such measures that help to retain their employees through talent management and satisfactory career development always enjoy a competitive edge over their competitors. Human resource is regarded as one of the most precious and difficult resource to management. It has its own needs and requirement. It becomes an easy prey to monotony when lacks career development. Wants and aspirations of this resource are seldom met completely but can be managed through career development and compensation management. In this era of competition, organizations have to take viable steps to management their resources especially human resource. Top management and Managers keep on working for an amenable solution in order to address the challenges relating career development and compensation management as their ultimate goal is to ensure the organizational performance on optimum level. The current study was conducted to examine the impact of Talent Management, Career Development and Compensation Management towards Employees Retention and Organizational Performance with mediating effect of Employees Motivation in Service Sector of Pakistan. The current study is based on Resource Based View (RBV) and Ability Motivation Opportunity (AMO) theories. It explains that by increasing internal resources we can manage employee talent, career development through compensation management and employee motivation more effectively. It will result in effective execution of HRM practices for employee retention enabling an organization to achieve and sustain competitive advantage through optimal performance. Data collection was made through a structured questionnaire which was based upon adopted instruments after testing reliability and validity. A total 300 employees of 30 firms in service sector of Pakistan were sampled through non-probability sampling technique. Regression analysis revealed that talent management, career development and compensation management have significant positive impact on employee retention and perceived organizational performance. The results further showed that employee motivation have a significant mediating effect on employee retention and organizational performance. The interpretation of the findings and limitations, theoretical and managerial implications are also discussed.

Keywords: career development, compensation management, employee retention, organizational performance, talent management

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Traditional optimization methods like evolutionary algorithms are widely used in production processes to find an optimal or near-optimal solution of control parameters based on the simulated environment space of a process. These algorithms are computationally intensive and therefore do not provide the opportunity for real-time optimization. This paper utilizes the Deep Reinforcement Learning (DRL) framework to find an optimal or near-optimal solution for control parameters. A model based on maximum a posteriori policy optimization (Hybrid-MPO) that can handle both numerical and categorical parameters is used as a benchmark for comparison. A comparative study shows that DRL can find optimal solutions of similar quality as compared to evolutionary algorithms while requiring significantly less time making them preferable for real-time optimization. The results are confirmed in a large-scale validation study on datasets from production and other fields. A trained XGBoost model is used as a surrogate for process simulation. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, evolutionary algorithms, production process optimization, real-time optimization, hybrid-MPO

Procedia PDF Downloads 112

Authors: Tsegahun Manyazewal, Francesco Marinucci, Getachew Belay, Abraham Tesfaye, Gonfa Ayana, Amaha Kebede, Tsegahun Manyazewal, Francesco Marinucci, Getachew Belay, Abraham Tesfaye, Gonfa Ayana, Amaha Kebede, Yewondwossen Tadesse, Susan Lehman, Zelalem Temesgen

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In-service health trainings in Sub-Saharan Africa are mostly content-centered with higher disconnection with the real practice in the facility. This study intended to evaluate in-service training approach aimed to strengthen health care human resources. A combined web-based and face-to-face training was designed and piloted in Ethiopia with the diagnosis of tuberculosis. During the first part, which lasted 43 days, trainees accessed web-based material and read without leaving their work; while the second part comprised a one-day hands-on evaluation. Trainee’s competency was measured using multiple-choice questions, written-assignments, exercises and hands-on evaluation. Of 108 participants invited, 81 (75%) attended the course and 71 (88%) of them successfully completed. Of those completed, 73 (90%) scored a grade from A to C. The approach was effective to transfer knowledge and turn it into practical skills. In-service health training should transform from a passive one-time-event to a continuous behavioral change of participants and improvements on their actual work.

Keywords: Ethiopia, health care, Mycobacterium tuberculosis, training

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Authors: Hironori Karachi, Haruka Yamashita

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Recently, the system of quick response (QR) code is getting popular. Many companies introduce new QR code payment services and the services are competing with each other to increase the number of users. For increasing the number of users, we should grasp the difference of feature of the demographic information, usage information, and value of users between services. In this study, we conduct an analysis of real-world data provided by Nomura Research Institute including the demographic data of users and information of users’ usages of two services; LINE Pay, and PayPay. For analyzing such data and interpret the feature of them, Nonnegative Matrix Factorization (NMF) is widely used; however, in case of the target data, there is a problem of the missing data. EM-algorithm NMF (EMNMF) to complete unknown values for understanding the feature of the given data presented by matrix shape. Moreover, for comparing the result of the NMF analysis of two matrices, there is Discriminant NMF (DNMF) shows the difference of users features between two matrices. In this study, we combine EMNMF and DNMF and also analyze the target data. As the interpretation, we show the difference of the features of users between LINE Pay and Paypay.

Keywords: data science, non-negative matrix factorization, missing data, quality of services

Procedia PDF Downloads 131

Authors: Karthiyayini Nagarajan, P. V. Ramakrishna

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Radar Imaging techniques provides extensive applications in the field of remote sensing, majorly Synthetic Aperture Radar (SAR) that provide high resolution target images. This paper work puts forward the effective and realizable signal generation and processing for SAR images. The major units in the system include camera, signal generation unit, signal processing unit and display screen. The real radio channel is replaced by its mathematical model based on optical image to calculate a reflected signal model in real time. Signal generation realizes the algorithm and forms the radar reflection model. Signal processing unit provides range and azimuth resolution through matched filtering and spectrum analysis procedure to form radar image on the display screen. The restored image has the same quality as that of the optical image. This SAR imaging system has been designed and implemented using MATLAB and Quartus II tools on Stratix III device as a System (Lab Bench) that works in real time to study/investigate on radar imaging rudiments and signal processing scheme for educational and research purposes.

Keywords: synthetic aperture radar, radio reflection model, lab bench, imaging engineering

Procedia PDF Downloads 498

Authors: Omid Adibi, Nategheh Najafpour, Bijan Farhanieh, Hossein Afshin

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Gas release from the pipelines is one of the main factors in the gas industry accidents. Released gas ejects from the pipeline as a free jet and in the growth process, the fuel gets mixed with the ambient air. Accordingly, an accidental spark will release the chemical energy of the mixture with an explosion. Gas explosion damages the equipment and endangers the life of staffs. So due to importance of safety in gas industries, prevision of accident can reduce the number of the casualties. In this paper, natural gas leakages from the low pressure pipelines are studied in two steps: 1) the simulation of mixing process and identification of flammable zones and 2) the simulation of wind effects on the mixing process. The numerical simulations were performed by using the finite volume method and the pressure-based algorithm. Also, for the grid generation the structured method was used. The results show that, in just 6.4 s after accident, released natural gas could penetrate to 40 m in vertical and 20 m in horizontal direction. Moreover, the results show that the wind speed is a key factor in dispersion process. In fact, the wind transports the flammable zones into the downstream. Hence, to improve the safety of the people and human property, it is preferable to construct gas facilities and buildings in the opposite side of prevailing wind direction.

Keywords: flammable zones, gas pipelines, numerical simulation, wind effects

Procedia PDF Downloads 166

Authors: Kun Chen, Yan Wang, Yangyu Zhao, Shufang Li, Lian Chen, Xiaoyue Guo, Jue Zhang, Jing Fang

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The coupling strength between uterine electromyography (UEMG) and Fetal heart rate (FHR) signals during peripartum reflects the fetal biophysical activities. Therefore, UEMG-FHR coupling characterization is instructive in assessing placenta function. This study introduced a physiological marker named elevated frequency of UEMG-FHR coupling (E-UFC) and explored its predictive value for pregnancies complicated by pre-eclampsia and small for gestational age (SGA). Placental insufficiency patients (n=12) and healthy volunteers (n=24) were recruited and participated. UEMG and FHR were recorded non-invasively by a trans-abdominal device in women at term with singleton pregnancy (32-37 weeks) from 10:00 pm to 8:00 am. The product of the wavelet coherence and the wavelet cross-spectral power between UEMG and FHR was used to weight these two effects in order to quantify the degree of the UEMG-FHR coupling. E-UFC was exacted from the resultant spectrogram by calculating the mean value of the high-coherence (r > 0.5) frequency band. Results showed the high-coherence between UEMG and FHR was observed in the frequency band (1/512-1/16Hz). In addition, E-UFC in placental insufficiency patients was weaker compared to healthy controls (p < 0.001) at group level. These findings suggested the proposed approach could be used to quantitatively characterize the fetal biophysical activities, which is beneficial for early detection of placental insufficiency and reduces the occurrence of adverse pregnancy.

Keywords: uterine electromyography, fetal heart rate, coupling analysis, wavelet analysis

Procedia PDF Downloads 202

Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

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The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

Procedia PDF Downloads 119

Authors: A. Ramalho, L. Romeiro, R. Ventura, A. Suleman

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A real-time path planning framework for Unmanned Air Vehicles, and in particular multi-rotors is proposed. The framework is designed to provide feasible trajectories from the current UAV position to a goal state, taking into account constraints such as obstacle avoidance, problem kinematics, and vehicle limitations such as maximum speed and maximum acceleration. The framework computes feasible paths online, allowing to avoid new, unknown, dynamic obstacles without fully re-computing the trajectory. These features are achieved using an iterative process in which the robot computes and optimizes the trajectory while performing the mission objectives. A first trajectory is computed using a modified Rapidly-Exploring Random Tree (RRT) algorithm, that provides trajectories that respect a maximum curvature constraint. The trajectory optimization is accomplished using the Interior Point Optimizer (IPOPT) as a solver. The framework has proven to be able to compute a trajectory and optimize to a locally optimal with computational efficiency making it feasible for real-time operations.

Keywords: interior point optimization, multi-rotors, online path planning, rapidly exploring random trees, trajectory optimization

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Authors: Aaron Derner

Abstract:

Unlike the histories of France, the UK, or even Spain, the Russian colonial past often dissolves before the seemingly more salient Cold War figurations or Soviet dissolution. The obvious explanation behind Caucasian states’ roles—that of Russian-propped governments obeying the whims of their patron—is but the latest instance of such oversight. Where the results of colonial social and cultural interactions are indelibly stamped across France, Algeria, and every other former (and current) French holding, so to are the Muscovite and Russian colonial ambitions embedded within the modern politics and cultures of both Russia and the Caucasus. Russian colonial artefacts are enhanced and perhaps granted an additional social explanatory edge over those of the ‘typical’ colonizers, by the cyclical adoration for and noisy rejection of European cultural markers over the centuries, along with the somewhat unusual composition of the Cossacks: Russia’s main agents of colonialization within the Caucasian frontier. The story of Russia and Chechnya, of all the Caucasus, is of the manufacture of social and individual identity through “modes of subjectification” inherent within the region’s colonial history and driven by the triangular interactions between three main groups: the Cossacks, the Caucasian Mountain Tribes, and the Russian Metropol. Together, interactions between these social groups worked to shape and transform the lifestyles and institutional pathologies that constitute the Russian and Chechen states and the politics between them. At the core of this (Western) state-building is the simultaneous and seemingly contradictory desire to be more Western and emulate Western cultural and political practices while also desperately grasping for a uniquely Russian identity. This sits somewhat ironically against the backdrop that Russia hosted a frontier-based settler society and had established that distinctly European feature of settler colonialism early in its history—arguably establishing a claim to being the most “colonial” of the colonial powers. There is no doubt that these forces worked to shape contemporary Russian political and social identity—apparent in the mythic popularity of the Cossack in Russian literature, politics, and academic discourse. What needs to be expanded from the current narrative, however, is that beyond the Cossack identity’s attractiveness on the grounds of its tones of freedom and resistance to unjust authority, the identity is rooted in the imperial ambitions and colonial experiences of the Russian state, and is, therefore, a direct marker of domination and subjectification. Adding an unusual dimension to this not-uncommon cultural progression, the Russian state needed to colonize both the Caucases and the Russian Cossacks, appropriating them in much the same way they appropriated the Circassian mountain tribes. The focus of this paper is not to tell yet another story of how one culture entered an area to overpower another but how a ‘powerful,’ ‘modern,’ ‘Western(ish)’ culture was profoundly and continually changed through its contact with a group of tribal ‘savages’ and ‘braves.’

Keywords: Russia, chechnya, subjectification, caucasus, cossacks, Ukraine

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Authors: Khaled Nagaty, Heba Nagaty, Gerard McKee

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A signature is a behavioral biometric that is used for authenticating users in most financial and legal transactions. Signatures can be easily forged by skilled forgers. Therefore, it is essential to verify whether a signature is genuine or forged. The aim of any signature verification algorithm is to accommodate the differences between signatures of the same person and increase the ability to discriminate between signatures of different persons. This work presented in this paper proposes an automatic signature verification system to indicate whether a signature is genuine or not. The system comprises four phases: (1) The pre-processing phase in which image scaling, binarization, image rotation, dilation, thinning, and connecting ridge breaks are applied. (2) The feature extraction phase in which global and local features are extracted. The local features are minutiae points, curvature orientation, and curve plateau. The global features are signature area, signature aspect ratio, and Hu moments. (3) The post-processing phase, in which false minutiae are removed. (4) The classification phase in which features are enhanced before feeding it into the classifier. k-nearest neighbors and support vector machines are used. The classifier was trained on a benchmark dataset to compare the performance of the proposed offline signature verification system against the state-of-the-art. The accuracy of the proposed system is 92.3%.

Keywords: signature, ridge breaks, minutiae, orientation

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Authors: Y. L. Hor, H. S. Chu, V. P. Bui

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Composite material is widely used to replace conventional material, especially in the aerospace industry to reduce the weight of the devices. It is formed by combining reinforced materials together via adhesive bonding to produce a bulk material with alternated macroscopic properties. In bulk composites, degradation may occur in microscopic scale, which is in each individual reinforced fiber layer or especially in its matrix layer such as delamination, inclusion, disbond, void, cracks, and porosity. In this paper, we focus on the detection of defect in matrix layer which the adhesion between the composite plies is in contact but coupled through a weak bond. In fact, the adhesive defects are tested through various nondestructive methods. Among them, pulsed phase thermography (PPT) has shown some advantages providing improved sensitivity, large-area coverage, and high-speed testing. The aim of this work is to develop an efficient numerical model to study the application of PPT to the nondestructive inspection of weak bonding in composite material. The resulting thermal evolution field is comprised of internal reflections between the interfaces of defects and the specimen, and the important key-features of the defects presented in the material can be obtained from the investigation of the thermal evolution of the field distribution. Computational simulation of such inspections has allowed the improvement of the techniques to apply in various inspections, such as materials with high thermal conductivity and more complex structures.

Keywords: pulsed phase thermography, weak bond, composite, CFRP, computational modelling, optimization

Procedia PDF Downloads 176

Authors: Zahra Abdolkarimi, Naser Zourikalatehsamad,

Abstract:

Up to 40 years ago, after recognition of epilepsy, it was generally believed that these attacks occurred randomly and suddenly. However, thanks to the advance of mathematics and engineering, such attacks can be predicted within a few minutes or hours. In this way, various algorithms for long-term prediction of the time and frequency of the first attack are presented. In this paper, by considering the nonlinear nature of brain signals and dynamic recorded brain signals, ANFIS model is presented to predict the brain signals, since according to physiologic structure of the onset of attacks, more complex neural structures can better model the signal during attacks. Contribution of this work is the co-evolution algorithm for optimization of ANFIS network parameters. Our objective is to predict brain signals based on time series obtained from brain signals of the people suffering from epilepsy using ANFIS. Results reveal that compared to other methods, this method has less sensitivity to uncertainties such as presence of noise and interruption in recorded signals of the brain as well as more accuracy. Long-term prediction capacity of the model illustrates the usage of planted systems for warning medication and preventing brain signals.

Keywords: co-evolution algorithms, brain signals, time series, neural networks, ANFIS model, physiologic structure, time prediction, epilepsy suffering, illustrates model

Procedia PDF Downloads 283

Authors: Karthiyayini Nagarajan, P. V. RamaKrishna

Abstract:

Radar Imaging techniques provides extensive applications in the field of remote sensing, majorly Synthetic Aperture Radar(SAR) that provide high resolution target images. This paper work puts forward the effective and realizable signal generation and processing for SAR images. The major units in the system include camera, signal generation unit, signal processing unit and display screen. The real radio channel is replaced by its mathematical model based on optical image to calculate a reflected signal model in real time. Signal generation realizes the algorithm and forms the radar reflection model. Signal processing unit provides range and azimuth resolution through matched filtering and spectrum analysis procedure to form radar image on the display screen. The restored image has the same quality as that of the optical image. This SAR imaging system has been designed and implemented using MATLAB and Quartus II tools on Stratix III device as a System(lab bench) that works in real time to study/investigate on radar imaging rudiments and signal processing scheme for educational and research purposes.

Keywords: synthetic aperture radar, radio reflection model, lab bench

Procedia PDF Downloads 468

Authors: Mo-Se Lee, Cheol-Hwi Ahn, Kee-Young Kwahk, Hyunchul Ahn

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Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN (Convolutional Neural Network), which is known as effective solution for recognizing and classifying images, has been popularly applied to classification and prediction problems in various fields. In this study, we try to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. In specific, we propose to apply CNN as the binary classifier that predicts stock market direction (up or down) by using a graph as its input. That is, our proposal is to build a machine learning algorithm that mimics a person who looks at the graph and predicts whether the trend will go up or down. Our proposed model consists of four steps. In the first step, it divides the dataset into 5 days, 10 days, 15 days, and 20 days. And then, it creates graphs for each interval in step 2. In the next step, CNN classifiers are trained using the graphs generated in the previous step. In step 4, it optimizes the hyper parameters of the trained model by using the validation dataset. To validate our model, we will apply it to the prediction of KOSPI200 for 1,986 days in eight years (from 2009 to 2016). The experimental dataset will include 14 technical indicators such as CCI, Momentum, ROC and daily closing price of KOSPI200 of Korean stock market.

Keywords: convolutional neural network, deep learning, Korean stock market, stock market prediction

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Authors: Hendradi Hardhienata, Tony Sumaryada, Sri Setyaningsih

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Current progress in the field of nonlinear optics has enabled precise surface characterization in semiconductor materials. Nonlinear optical techniques are favorable due to their nondestructive measurement and ability to work in nonvacuum and ambient conditions. The advance of the bond hyperpolarizability models opens a wide range of nanoscale surface investigation including the possibility to detect molecular orientation at the surface of silicon and zincblende semiconductors, investigation of electric field induced second harmonic fields at the semiconductor interface, detection of surface impurities, and very recently, study surface defects such as twin boundary in wurtzite semiconductors. In this work, we show using nonlinear optical techniques, e.g. nonlinear bond models how arbitrary polarization of the incoming electric field in Rotational Anisotropy Spectroscopy experiments can provide more information regarding the origin of the nonlinear sources in zincblende and wurtzite semiconductor structure. In addition, using hyperpolarizability consideration, we describe how the nonlinear susceptibility tensor describing SHG can be well modelled using only few parameter because of the symmetry of the bonds. We also show how the third harmonic intensity feature shows considerable changes when the incoming field polarization angle is changed from s-polarized to p-polarized. We also propose a method how to investigate surface reconstruction and defects in wurtzite and zincblende structure at the nanoscale level.

Keywords: surface characterization, bond model, rotational anisotropy spectroscopy, effective hyperpolarizability

Procedia PDF Downloads 158

Authors: Wai Ho Darrell Kwok

Abstract:

Building entities are valuable assets of a society, however, all of them are suffered from the ravages of weather and time. Facilitating onerous maintenance activities is the only way to either maintain or enhance the value and contemporary standard of the premises. By the way, maintenance budget is always bounded by the corresponding threshold limit. In order to optimize the limited resources allocation in carrying out maintenance, there is a substantial need to prioritize maintenance work. This paper reveals the application of Fuzzy AHP in a Facilities Management Company determining the maintenance priorities on the basis of predetermined criteria, viz., Building Status (BS), Effects on Fabrics (EF), Effects on Sustainability (ES), Effects on Users (EU), Importance of Usage (IU) and Physical Condition (PC) in dealing with categorized 8 predominant building components maintenance aspects for building premises. From the case study, it is found that ‘building exterior repainting or re-tiling’, ‘spalling concrete repair works among exterior area’ and ‘lobby renovation’ are the top three maintenance priorities from facilities manager and maintenance expertise personnel. Through the application of the Fuzzy AHP for maintenance priorities decision algorithm, a more systemic and easier comparing scalar linearity factors being explored even in considering other multiple criteria decision scenarios of building maintenance issue.

Keywords: building maintenance, fuzzy AHP, maintenance priority, multi-criteria decision making

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Authors: Cheng-Jhe Lee, Chiun-Chieh Hsu

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Due to the rapid development of the Internet and the increased availability of digital documents, the excessive information on the Internet has led to information overflow problem. In order to solve these problems for effective information retrieval, document clustering in text mining becomes a popular research topic. Clustering is the unsupervised classification of data items into groups without the need of training data. Many conventional document clustering methods perform inefficiently for large document collections because they were originally designed for relational database. Therefore they are impractical in real-world document clustering and require special handling for high dimensionality and high volume. We propose the FIHC (Frequent Itemset-based Hierarchical Clustering) method, which is a hierarchical clustering method developed for document clustering, where the intuition of FIHC is that there exist some common words for each cluster. FIHC uses such words to cluster documents and builds hierarchical topic tree. In this paper, we combine FIHC algorithm with ontology to solve the semantic problem and mine the meaning behind the words in documents. Furthermore, we use the closed frequent itemsets instead of only use frequent itemsets, which increases efficiency and scalability. The experimental results show that our method is more accurate than those of well-known document clustering algorithms.

Keywords: FIHC, documents clustering, ontology, closed frequent itemset

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Authors: David Oluwole Moses, Odeyemi Adebowale Toba, Olawale Adetunji Kola

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Candida auris, an emerging fungus, has been reported in more than 30 countries around the world since its first detection in 2009. Due to its several virulence factors, resistance to antifungals, and persistence in hospital settings, Candida auris has been reported to cause treatment-failure infections. This study was therefore carried out to determine the incidence of Candida auris in a tertiary hospital in Ekiti State, Nigeria. In this study, a total of 115 samples were screened for Candida species using cultural and molecular methods. The carriage of virulence factors and antifungal resistance among C. auris was detected using standard microbiological methods. Candida species isolated from the samples were 15 (30.0%) in clinical samples and 22 (33.85%) in hospital equipment screened. Non-albicans Candida accounted for 3 (20%) and 8 (36.36%) among the isolates from the clinical samples and equipment, respectively. Only five of the non-albicans Candida isolates were C. auris. All the isolates produced biofilm, gelatinase, and hemolysin, while none produced germ tubes. Two of the isolates were resistant to all the antifungals tested. Also, all the isolates were resistant to fluconazole and itraconazole. Nystatin appeared to be the most effective among the tested antifungals. The isolation of Candida auris is being reported for the second time in Nigeria, further confirming that the fungus has spread beyond Lagos and Ibadan, where it was first reported. The extent of the spread of the nosocomial fungus needed to be further investigated and curtailed in Nigeria before its outbreak in healthcare facilities.

Keywords: candida auris, virulence factors, antifungals, pathogen, hospital, infection

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Authors: Marek Dlapa

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The algebraic approach is applied to the control of the HiMAT (Highly Maneuverable Aircraft Technology). The objective is to find a robust controller which guarantees robust stability and decoupled control of longitudinal model of a scaled remotely controlled vehicle version of the advanced fighter HiMAT. Control design is performed by decoupling the nominal MIMO (multi-input multi-output) system into two identical SISO (single-input single-output) plants which are approximated by a 4th order transfer function. The algebraic approach is then used for pole placement design, and the nominal closed-loop poles are tuned so that the peak of the µ-function is minimal. As an optimization tool, evolutionary algorithm Differential Migration is used in order to overcome the multimodality of the cost function yielding simple controller with decoupling for nominal plant which is compared with the D-K iteration through simulations of standard longitudinal manoeuvres documenting decoupled control obtained from algebraic approach for nominal plant as well as worst case perturbation.

Keywords: algebraic approach, evolutionary computation, genetic algorithms, HiMAT, robust control, structured singular value

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Authors: Sahar Jahani, Meryem Ayse Yucel, David Boas, Seyed Kamaledin Setarehdan

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Near-infrared spectroscopy allows monitoring of oxy- and deoxy-hemoglobin concentration changes associated with hemodynamic response function (HRF). HRF is usually affected by natural physiological hemodynamic (systemic interferences) which occur in all body tissues including brain tissue. This makes HRF extraction a very challenging task. In this study, we used Kalman filter based on a general linear model (GLM) of brain activity to define the proportion of systemic interference in the brain hemodynamic. The performance of the proposed algorithm is evaluated in terms of the peak to peak error (Ep), mean square error (MSE), and Pearson’s correlation coefficient (R2) criteria between the estimated and the simulated hemodynamic responses. This technique also has the ability of real time estimation of single trial functional activations as it was applied to classify finger tapping versus resting state. The average real-time classification accuracy of 74% over 11 subjects demonstrates the feasibility of developing an effective functional near infrared spectroscopy for brain computer interface purposes (fNIRS-BCI).

Keywords: hemodynamic response function, functional near-infrared spectroscopy, adaptive filter, Kalman filter

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Authors: Maciej Szeląg, Stanisław Fic

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The impact of elevated temperatures on the construction materials manifests in change of their physical and mechanical characteristics. Stresses and thermal deformations that occur inside the volume of the material cause its progressive degradation as temperature increase. Finally, the reactions and transformations of multiphase structure of cementitious composite cause its complete destruction. A particularly dangerous phenomenon is the impact of thermal shock – a sudden high temperature load. The thermal shock leads to a high value of the temperature gradient between the outer surface and the interior of the element in a relatively short time. The result of mentioned above process is the formation of the cracks and scratches on the material’s surface and inside the material. The article describes the use of computer image analysis techniques to identify and assess the structure of the cluster cracks on the surfaces of modified cement pastes, caused by thermal shock. Four series of specimens were tested. Two Portland cements were used (CEM I 42.5R and CEM I 52,5R). In addition, two of the series contained metakaolinite as a replacement for 10% of the cement content. Samples in each series were made in combination of three w/b (water/binder) indicators of respectively 0.4; 0.5; 0.6. Surface cracks of the samples were created by a sudden temperature load at 200°C for 4 hours. Images of the cracked surfaces were obtained via scanning at 1200 DPI; digital processing and measurements were performed using ImageJ v. 1.46r software. In order to examine the cracked surface of the cement paste as a system of closed clusters – the dispersal systems theory was used to describe the structure of cement paste. Water is used as the dispersing phase, and the binder is used as the dispersed phase – which is the initial stage of cement paste structure creation. A cluster itself is considered to be the area on the specimen surface that is limited by cracks (created by sudden temperature loading) or by the edge of the sample. To describe the structure of cracks two stereological parameters were proposed: A ̅ – the cluster average area, L ̅ – the cluster average perimeter. The goal of this study was to compare the investigated stereological parameters with the mechanical properties of the tested specimens. Compressive and tensile strength testes were carried out according to EN standards. The method used in the study allowed the quantitative determination of defects occurring in the examined modified cement pastes surfaces. Based on the results, it was found that the nature of the cracks depends mainly on the physical parameters of the cement and the intermolecular interactions on the dispersal environment. Additionally, it was noted that the A ̅/L ̅ relation of created clusters can be described as one function for all tested samples. This fact testifies about the constant geometry of the thermal cracks regardless of the presence of metakaolinite, the type of cement and the w/b ratio.

Keywords: cement paste, cluster cracks, elevated temperature, image analysis, metakaolinite, stereological parameters

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Authors: Tong He, Long Chen, Irag Mantegh, Wen-Fang Xie

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This paper proposes an image-based obstacle avoidance and tracking target identification strategy in GPS-degraded or GPS-denied environment for an Unmanned Aerial Vehicle (UAV). The traditional force algorithm for obstacle avoidance could produce local minima area, in which UAV cannot get away obstacle effectively. In order to eliminate it, an artificial potential approach based on harmonic potential is proposed to guide the UAV to avoid the obstacle by using the vision system. And image-based visual servoing scheme (IBVS) has been adopted to implement the proposed obstacle avoidance approach. In IBVS, the pixel accuracy is a key factor to realize the obstacle avoidance. In this paper, the deep reinforcement learning framework has been applied by reducing pixel errors through constant interaction between the environment and the agent. In addition, the combination of OpenTLD and Tensorflow based on neural network is used to identify the type of tracking target. Numerical simulation in Matlab and ROS GAZEBO show the satisfactory result in target identification and obstacle avoidance.

Keywords: image-based visual servoing, obstacle avoidance, tracking target identification, deep reinforcement learning, artificial potential approach, neural network

Procedia PDF Downloads 143