Search results for: real estate
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5125

Search results for: real estate

3025 Thermal Regions for Unmanned Aircraft Systems Route Planning

Authors: Resul Fikir

Abstract:

Unmanned Aircraft Systems (UAS) become indispensable parts of modern air power as force multiplier. One of the main advantages of UAS is long endurance. UAS have to take extra payloads to accomplish different missions but these payloads decrease endurance of aircraft because of increasing drag. There are continuing researches to increase the capability of UAS. There are some vertical thermal air currents, which can cause climb and increase endurance, in nature. Birds and gliders use thermals to gain altitude with no effort. UAS have wide wing which can use of thermals like birds and gliders. Thermal regions, which is area of 2000-3000 meter (1 NM), exist all around the world. It is free and clean source. This study analyses if thermal regions can be adopted and implemented as an assistant tool for UAS route planning. First and second part of study will contain information about the thermal regions and current applications about UAS in aviation and climbing performance with a real example. Continuing parts will analyze the contribution of thermal regions to UAS endurance. Contribution is important because planning declaration of UAS navigation rules will be in 2015.

Keywords: airways, thermals, UAS, UAS roadmap

Procedia PDF Downloads 409
3024 Genotyping of G/P No Typable Group a Rotavirus Strains Revealed G2 and G9 Genotype Circulations in Moroccan Children Fully Vaccinated with Rotarix™

Authors: H. Boulahyaoui, S. Alaoui Amine, C. Loutfi, H. El Annaz, N. Touil, El M. El Fahim, S. Mrani

Abstract:

Three Moroccan children fully vaccinated with Rotarix™ have been hospitalized for Rotavirus Gastroenteritis (RVGE) in the pediatric division of the Farabi Hospital, Oujda. Rotavirus G/P genotypes could not be typed because of their delayed crossing threshold (Ct) resolute with a group A rotavirus (RVA) real time RT-PCR. These strains were adapted to cell culture. All viruses replicated and caused extensive cytopathic effects after four or five passages in MA104 cell lines. Significant improvements have been obtained in the amount of viral particles. Each virus multiplied to a high titer (7.5 TCID50/ml). VP7 and VP4 partial gene sequencing revealed distinct genotypes compared to the Rotarix(®) vaccine strain. Two strains were of G2P[4] genotype whereas the third was G9P[8] genotype. Virus isolation while labor intensive, is recommended as a second test, especially when higher sensitivity for conventional RVA genotyping RT-PCR is needed. VP7 antigenic similarities between these strains and Rotarix were determined.

Keywords: esacpe-vaccine, Morocco, Rotarix, G2P[4], G9P[8]

Procedia PDF Downloads 316
3023 Two Stage Assembly Flowshop Scheduling Problem Minimizing Total Tardiness

Authors: Ali Allahverdi, Harun Aydilek, Asiye Aydilek

Abstract:

The two stage assembly flowshop scheduling problem has lots of application in real life. To the best of our knowledge, the two stage assembly flowshop scheduling problem with total tardiness performance measure and separate setup times has not been addressed so far, and hence, it is addressed in this paper. Different dominance relations are developed and several algorithms are proposed. Extensive computational experiments are conducted to evaluate the proposed algorithms. The computational experiments have shown that one of the algorithms performs much better than the others. Moreover, the experiments have shown that the best performing algorithm performs much better than the best existing algorithm for the case of zero setup times in the literature. Therefore, the proposed best performing algorithm not only can be used for problems with separate setup times but also for the case of zero setup times.

Keywords: scheduling, assembly flowshop, total tardiness, algorithm

Procedia PDF Downloads 332
3022 The Role of Social Networking in Activating the Participation of Youth in the Community

Authors: Raya Hamed Hial Al Maamari

Abstract:

The gulf societies have been undergoing radical changes because of the technology transfer. It altered the humanities attitudes. Especially, youth habits so they become a fond of using social networking. This study aimed to find out the ratio of social networking in Directing youth to participate with government institutions in decision-making and improving their societies. The study considered a descriptive study, social survey method was used on a sample of 100 young men from different gulf countries, using an electronic questionnaire, with some interviews with famous leaders of youth groups. Finally, the researchers suggested many effective views to activate youth efforts using social networks as an effective manner to plan for the development policy and Implemented accurately in the community. The findings illustrated that social networks play a vital role in encouraging youth to participate Enthusiastically in providing the service. As it notices these networks contain large numbers of youth. Therefore, the influences become widely and feasible. Moreover, the study indicated the fact that most of youth teamwork started in these social networks. Then, it has been growing to the real society.

Keywords: social work, volunteering, youth, community

Procedia PDF Downloads 323
3021 Application of Deep Learning in Colorization of LiDAR-Derived Intensity Images

Authors: Edgardo V. Gubatanga Jr., Mark Joshua Salvacion

Abstract:

Most aerial LiDAR systems have accompanying aerial cameras in order to capture not only the terrain of the surveyed area but also its true-color appearance. However, the presence of atmospheric clouds, poor lighting conditions, and aerial camera problems during an aerial survey may cause absence of aerial photographs. These leave areas having terrain information but lacking aerial photographs. Intensity images can be derived from LiDAR data but they are only grayscale images. A deep learning model is developed to create a complex function in a form of a deep neural network relating the pixel values of LiDAR-derived intensity images and true-color images. This complex function can then be used to predict the true-color images of a certain area using intensity images from LiDAR data. The predicted true-color images do not necessarily need to be accurate compared to the real world. They are only intended to look realistic so that they can be used as base maps.

Keywords: aerial LiDAR, colorization, deep learning, intensity images

Procedia PDF Downloads 146
3020 Teaching for Knowledge Transfer: Best Practices from a Graduate-Level Educational Psychology Distance Learning Program

Authors: Bobby Hoffman

Abstract:

One measure of effective instruction is the ability to solve authentic, real-world problems by effectively transferring and applying classroom and textbook knowledge. While many students can productively earn high grades and learn course content, they are not always able to apply the knowledge they gain. As such, this quasi-experimental study compared the comprehensive exit exam results of learners across instructional modalities who completed a prominent graduate-level educational psychology program. ANCOVA revealed superior knowledge transfer for blended-learning students compared to those who completed distance education and significantly greater transfer of declarative, procedural, and self-regulatory knowledge by the blended-learning students. This paper briefly summarizes the study results while highlighting evidence-based programmatic and course level modifications that were implemented to specifically address the transfer of learning and practical application of educational psychology knowledge.

Keywords: assessment, distance learning, educational psychology, knowledge transfer

Procedia PDF Downloads 162
3019 Nondestructive Testing for Reinforced Concrete Buildings with Active Infrared Thermography

Authors: Huy Q. Tran, Jungwon Huh, Kiseok Kwak, Choonghyun Kang

Abstract:

Infrared thermography (IRT) technique has been proven to be a good method for nondestructive evaluation of concrete material. In the building, a broad range of applications has been used such as subsurface defect inspection, energy loss, and moisture detection. The purpose of this research is to consider the qualitative and quantitative performance of reinforced concrete deteriorations using active infrared thermography technique. An experiment of three different heating regimes was conducted on a concrete slab in the laboratory. The thermal characteristics of the IRT method, i.e., absolute contrast and observation time, are investigated. A linear relationship between the observation time and the real depth was established with a well linear regression R-squared of 0.931. The results showed that the absolute contrast above defective area increases with the rise of the size of delamination and the heating time. In addition, the depth of delamination can be predicted by using the proposal relationship of this study.

Keywords: concrete building, infrared thermography, nondestructive evaluation, subsurface delamination

Procedia PDF Downloads 271
3018 Age Estimation Using Destructive and Non-Destructive Dental Methods on an Archeological Human Sample from the Poor Claire Nunnery in Brussels, Belgium

Authors: Pilar Cornejo Ulloa, Guy Willems, Steffen Fieuws, Kim Quintelier, Wim Van Neer, Patrick Thevissen

Abstract:

Dental age estimation can be performed both in living and deceased individuals. In anthropology, few studies have tested the reliability of dental age estimation methods complementary to the usually applied osteological methods. Objectives: In this study, destructive and non-destructive dental age estimation methods were applied on an archeological sample in order to compare them with the previously obtained anthropological age estimates. Materials and Methods: One hundred and thirty-four teeth from 24 individuals were analyzed using Kvaal, Kvaal and Solheim, Bang and Ramm, Lamendin, Gustafson, Maples, Dalitz and Johanson’s methods. Results: A high variability and wider age ranges than the ones previously obtained by the anthropologist could be observed. Destructive methods had a slightly higher agreement than the non-destructive. Discussion: Due to the heterogeneity of the sample and the lack of the real age at death, the obtained results were not representative, and it was not possible to suggest one dental age estimation method over another.

Keywords: archeology, dental age estimation, forensic anthropology, forensic dentistry

Procedia PDF Downloads 348
3017 Research of Intrinsic Emittance of Thermal Cathode with Emission Nonuniformity

Authors: Yufei Peng, Zhen Qin, Jianbe Li, Jidong Long

Abstract:

The thermal cathode is widely used in accelerators, FELs and kinds of vacuum electronics. However, emission nonuniformity exists due to surface profile, material distribution, temperature variation, crystal orientation, etc., which will cause intrinsic emittance growth, brightness decline, envelope size augment, device performance deterioration or even failure. To understand how emittance is manipulated by emission nonuniformity, an intrinsic emittance model consisting of contributions from macro and micro surface nonuniformity is developed analytically based on general thermal emission model at temperature limited regime according to a real 3mm cathode. The model shows relative emittance increased about 50% due to temperature variation, and less than 5% from several kinds of micro surface nonuniformity which is much smaller than other research. Otherwise, we also calculated emittance growth combining with Monte Carlo method and PIC simulation, experiments of emission uniformity and emittance measurement are going to be carried out separately.

Keywords: thermal cathode, electron emission fluctuation, intrinsic emittance, surface nonuniformity, cathode lifetime

Procedia PDF Downloads 283
3016 Desktop High-Speed Aerodynamics by Shallow Water Analogy in a Tin Box for Engineering Students

Authors: Etsuo Morishita

Abstract:

In this paper, we show shallow water in a tin box as an analogous simulation tool for high-speed aerodynamics education and research. It is customary that we use a water tank to create shallow water flow. While a flow in a water tank is not necessarily uniform and is sometimes wavy, we can visualize a clear supercritical flow even when we move a body manually in stationary water in a simple shallow tin box. We can visualize a blunt shock wave around a moving circular cylinder together with a shock pattern around a diamond airfoil. Another interesting analogous experiment is a hydrodynamic shock tube with water and tea. We observe the contact surface clearly due to color difference of the two liquids those are invisible in the real gas dynamics experiment. We first revisit the similarities between high-speed aerodynamics and shallow water hydraulics. Several educational and research experiments are then introduced for engineering students. Shallow water experiments in a tin box simulate properly the high-speed flows.

Keywords: aerodynamics compressible flow, gas dynamics, hydraulics, shock wave

Procedia PDF Downloads 285
3015 A Convolution Neural Network PM-10 Prediction System Based on a Dense Measurement Sensor Network in Poland

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

Abstract:

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

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

Procedia PDF Downloads 129
3014 The Link between Money Market and Economic Growth in Nigeria: Vector Error Correction Model Approach

Authors: Uyi Kizito Ehigiamusoe

Abstract:

The paper examines the impact of money market on economic growth in Nigeria using data for the period 1980-2012. Econometrics techniques such as Ordinary Least Squares Method, Johanson’s Co-integration Test and Vector Error Correction Model were used to examine both the long-run and short-run relationship. Evidence from the study suggest that though a long-run relationship exists between money market and economic growth, but the present state of the Nigerian money market is significantly and negatively related to economic growth. The link between the money market and the real sector of the economy remains very weak. This implies that the market is not yet developed enough to produce the needed growth that will propel the Nigerian economy because of several challenges. It was therefore recommended that government should create the appropriate macroeconomic policies, legal framework and sustain the present reforms with a view to developing the market so as to promote productive activities, investments, and ultimately economic growth.

Keywords: economic growth, investments, money market, money market challenges, money market instruments

Procedia PDF Downloads 329
3013 An Investigation Into an Essential Property of Creativity, Which Is the First-Person Experience

Authors: Ukpaka Paschal

Abstract:

Margret Boden argues that a creative product is one that is new, surprising, and valuable as a result of the combination, exploration, or transformation involved in producing it. Boden uses examples of artificial intelligence systems that fit all of these criteria and argues that real creativity involves autonomy, intentionality, valuation, emotion, and consciousness. This paper provides an analysis of all these elements in order to try to understand whether they are sufficient to account for creativity, especially human creativity. This paper focuses on Generative Adversarial Networks (GANs), which is a class of artificial intelligence algorithms that are said to have disproved the common perception that creativity is something that only humans possess. This paper will then argue that Boden’s listed properties of creativity, which capture the creativity exhibited by GANs, are not sufficient to account for human creativity, and this paper will further identify “first-person phenomenological experience” as an essential property of human creativity. The rationale behind the proposed essential property is that if creativity involves comprehending our experience of the world around us into a form of self-expression, then our experience of the world really matters with regard to creativity.

Keywords: artificial intelligence, creativity, GANs, first-person experience

Procedia PDF Downloads 110
3012 Nanocomposite Metal Material: Study of Antimicrobial and Catalytic Properties

Authors: Roman J. Jedrzejczyk, Damian K. Chlebda, Anna Dziedzicka, Rafal Wazny, Agnieszka Domka, Maciej Sitarz, Przemyslaw J. Jodlowski

Abstract:

The aim of this study was to obtain antimicrobial material based on thin zirconium dioxide coatings on structured reactors doped with metal nanoparticles using the sonochemical sol-gel method. As a result, dense, uniform zirconium dioxide films were obtained on the kanthal sheets which can be used as support materials in antimicrobial converters with sophisticated shapes. The material was characterised by physicochemical methods, such as AFM, SEM, EDX, XRF, XRD, XPS and in situ Raman and DRIFT spectroscopy. In terms of antimicrobial activity, the material was tested by ATP/AMP method using model microbes isolated from the real systems. The results show that the material can be potentially used in the market as a good candidate for active package and as active bulkheads of climatic systems. The mechanical tests showed that the developed method is an efficient way to obtain durable converters with high antimicrobial activity against fungi and bacteria.

Keywords: antimicrobial properties, kanthal steel, nanocomposite, zirconium oxide

Procedia PDF Downloads 186
3011 On-Line Data-Driven Multivariate Statistical Prediction Approach to Production Monitoring

Authors: Hyun-Woo Cho

Abstract:

Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

Procedia PDF Downloads 341
3010 Location Management in Wireless Sensor Networks with Mobility

Authors: Amrita Anil Agashe, Sumant Tapas, Ajay Verma Yogesh Sonavane, Sourabh Yeravar

Abstract:

Due to advancement in MEMS technology today wireless sensors network has gained a lot of importance. The wide range of its applications includes environmental and habitat monitoring, object localization, target tracking, security surveillance etc. Wireless sensor networks consist of tiny sensor devices called as motes. The constrained computation power, battery power, storage capacity and communication bandwidth of the tiny motes pose challenging problems in the design and deployment of such systems. In this paper, we propose a ubiquitous framework for Real-Time Tracking, Sensing and Management System using IITH motes. Also, we explain the algorithm that we have developed for location management in wireless sensor networks with the aspect of mobility. Our developed framework and algorithm can be used to detect emergency events and safety threats and provides warning signals to handle the emergency.

Keywords: mobility management, motes, multihop, wireless sensor networks

Procedia PDF Downloads 402
3009 Agricultural Waste Recovery For Industrial Effluent Treatment And Environmental Protection

Authors: Salim Ahmed

Abstract:

In many countries, water pollution from industrial effluents is a real problem. It may have a negative impact on the environment. To minimize the adverse effects of these contaminants, various methods are used to improve effluent purification, including physico-chemical processes such as adsorption.The present study focuses on applying a naturally biodegradable adsorbent based on argan (southern Morocco) in a physico-chemical adsorption process to reduce the harmful effects of pollutants on the environment. Tests were carried out with the cationic dye methylene blue (MB) and revealed that removal is significantly higher within the first 15 minutes. The parameters studied in this study are adsorbent mass and concentration. The Freundlich model provides an excellent example of the adsorption phenomenon of BMs over argan powder. The results of this study show that argan kernels are a highly beneficial alternative for local communities, as they help to achieve a triple objective: pollution reduction, waste recovery and water recycling.

Keywords: environmental protection, activated carbon, water treatment, adsorption

Procedia PDF Downloads 49
3008 Communication Apprehension among College Students in United Arab Emirates: A Case Study of Undergraduate Students of Abu Dhabi University

Authors: Nunna Venkata Prasad, Maryam Amoke Folarin, Muhammad Ali Shaukat Sham

Abstract:

A quantitative investigation was conducted to explore the communication apprehension among undergraduate students of Abu Dhabi University. Communication apprehension (CA) is an individual’s level of fear or anxiety associated with either real or anticipated communication with another person or persons. All individuals experience some level of communication apprehension. A total of 100 participants selected through a stratified sampling method, which includes 50 males and 50 females participated in the study. The research was conducted by distributing the personal report of communication apprehension questionnaire, randomly amongst these students. Results were affirmative with previous researches conducted. Demographics, age, or college year did not make any significant differences amongst the undergraduate students. More students were found to have high CA with public speaking rather than other scenarios. And lesser students were found to have high CA level with one-on-one conversations although a significant number of them still tested to have high CA with interpersonal communications.

Keywords: communication apprehension, interpersonal communication, oral communication, public speaking

Procedia PDF Downloads 166
3007 Internal Capital Market Efficiency Study Based on Improved Cash Flow Sensitivity Coefficient - Take Tomorrow Group as an Example

Authors: Peng Lu, Liu Ting

Abstract:

Because of the difficulty of financing from the external capital market, the reorganization and merger of private enterprises have formed a family group, seeking the help of the internal capital market to alleviate the capital demand. However, the inefficiency of the internal capital market can damage the effect it should have played, and even hinder the development of enterprises. This paper takes the "Tomorrow Group" as the research object to carry on the case analysis. After using the improved cash flow sensitivity coefficient to measure the efficiency of the internal capital market of Tomorrow Group, the inefficiency phenomenon is found. Then the analysis reveals that the reasons for its inefficiency include that the pyramidal equity structure is conducive to control, the separation of cash flow rights and control rights, the concentration of equity leads to poor balance, the abandonment of real industries and information asymmetry.

Keywords: tomorrow group, internal capital market, related-party transactions, Baotou tomorrow technology Co., LTD

Procedia PDF Downloads 116
3006 Linear Frequency Modulation-Frequency Shift Keying Radar with Compressive Sensing

Authors: Ho Jeong Jin, Chang Won Seo, Choon Sik Cho, Bong Yong Choi, Kwang Kyun Na, Sang Rok Lee

Abstract:

In this paper, a radar signal processing technique using the LFM-FSK (Linear Frequency Modulation-Frequency Shift Keying) is proposed for reducing the false alarm rate based on the compressive sensing. The LFM-FSK method combines FMCW (Frequency Modulation Continuous Wave) signal with FSK (Frequency Shift Keying). This shows an advantage which can suppress the ghost phenomenon without the complicated CFAR (Constant False Alarm Rate) algorithm. Moreover, the parametric sparse algorithm applying the compressive sensing that restores signals efficiently with respect to the incomplete data samples is also integrated, leading to reducing the burden of ADC in the receiver of radars. 24 GHz FMCW signal is applied and tested in the real environment with FSK modulated data for verifying the proposed algorithm along with the compressive sensing.

Keywords: compressive sensing, LFM-FSK radar, radar signal processing, sparse algorithm

Procedia PDF Downloads 457
3005 VTOL-Fw Mode-Transitioning UAV Design and Analysis

Authors: Feri̇t Çakici, M. Kemal Leblebi̇ci̇oğlu

Abstract:

In this study, an unmanned aerial vehicle (UAV) with level flight, vertical take-off and landing (VTOL) and mode-transitioning capability is designed and analyzed. The platform design combines both multirotor and fixed-wing (FW) conventional airplane structures and control surfaces; therefore named as VTOL-FW. The aircraft is modeled using aerodynamical principles and linear models are constructed utilizing small perturbation theory for trim conditions. The proposed method of control includes implementation of multirotor and airplane mode controllers and design of an algorithm to transition between modes in achieving smooth switching maneuvers between VTOL and FW flight. Thus, VTOL-FW UAV’s flight characteristics are expected to be improved by enlarging operational flight envelope through enabling mode-transitioning, agile maneuvers and increasing survivability. Experiments conducted in simulation and real world environments shows that VTOL-FW UAV has both multirotor and airplane characteristics with extra benefits in an enlarged flight envelope.

Keywords: aircraft design, linear analysis, mode transitioning control, UAV

Procedia PDF Downloads 375
3004 Traditional Chinese Medicine Treatment for Coronary Heart Disease: a Meta-Analysis

Authors: Yuxi Wang, Xuan Gao

Abstract:

Traditional Chinese medicine has been used in the treatment of coronary heart disease (CHD) for centuries, and in recent years, the research data on the efficacy of traditional Chinese medicine through clinical trials has gradually increased to explore its real efficacy and internal pharmacology. However, due to the complexity of traditional Chinese medicine prescriptions, the efficacy of each component is difficult to clarify, and pharmacological research is challenging. This study aims to systematically review and clarify the clinical efficacy of traditional Chinese medicine in the treatment of coronary heart disease through a meta-analysis. Based on PubMed, CNKI database, Wanfang data, and other databases, eleven randomized controlled trials and 1091 CHD subjects were included. Two researchers conducted a systematic review of the papers and conducted a meta-analysis supporting the positive therapeutic effect of traditional Chinese medicine in the treatment of CHD.

Keywords: coronary heart disease, Chinese medicine, treatment, meta-analysis

Procedia PDF Downloads 104
3003 Multi-Subpopulation Genetic Algorithm with Estimation of Distribution Algorithm for Textile Batch Dyeing Scheduling Problem

Authors: Nhat-To Huynh, Chen-Fu Chien

Abstract:

Textile batch dyeing scheduling problem is complicated which includes batch formation, batch assignment on machines, batch sequencing with sequence-dependent setup time. Most manufacturers schedule their orders manually that are time consuming and inefficient. More power methods are needed to improve the solution. Motivated by the real needs, this study aims to propose approaches in which genetic algorithm is developed with multi-subpopulation and hybridised with estimation of distribution algorithm to solve the constructed problem for minimising the makespan. A heuristic algorithm is designed and embedded into the proposed algorithms to improve the ability to get out of the local optima. In addition, an empirical study is conducted in a textile company in Taiwan to validate the proposed approaches. The results have showed that proposed approaches are more efficient than simulated annealing algorithm.

Keywords: estimation of distribution algorithm, genetic algorithm, multi-subpopulation, scheduling, textile dyeing

Procedia PDF Downloads 285
3002 Change Detection Method Based on Scale-Invariant Feature Transformation Keypoints and Segmentation for Synthetic Aperture Radar Image

Authors: Lan Du, Yan Wang, Hui Dai

Abstract:

Synthetic aperture radar (SAR) image change detection has recently become a challenging problem owing to the existence of speckle noises. In this paper, an unsupervised distribution-free change detection for SAR image based on scale-invariant feature transform (SIFT) keypoints and segmentation is proposed. Firstly, the noise-robust SIFT keypoints which reveal the blob-like structures in an image are extracted in the log-ratio image to reduce the detection range. Then, different from the traditional change detection which directly obtains the change-detection map from the difference image, segmentation is made around the extracted keypoints in the two original multitemporal SAR images to obtain accurate changed region. At last, the change-detection map is generated by comparing the two segmentations. Experimental results on the real SAR image dataset demonstrate the effectiveness of the proposed method.

Keywords: change detection, Synthetic Aperture Radar (SAR), Scale-Invariant Feature Transformation (SIFT), segmentation

Procedia PDF Downloads 371
3001 Physiological Effects on Scientist Astronaut Candidates: Hypobaric Training Assessment

Authors: Pedro Llanos, Diego García

Abstract:

This paper is addressed to expanding our understanding of the effects of hypoxia training on our bodies to better model its dynamics and leverage some of its implications and effects on human health. Hypoxia training is a recommended practice for military and civilian pilots that allow them to recognize their early hypoxia signs and symptoms, and Scientist Astronaut Candidates (SACs) who underwent hypobaric hypoxia (HH) exposure as part of a training activity for prospective suborbital flight applications. This observational-analytical study describes physiologic responses and symptoms experienced by a SAC group before, during and after HH exposure and proposes a model for assessing predicted versus observed physiological responses. A group of individuals with diverse Science Technology Engineering Mathematics (STEM) backgrounds conducted a hypobaric training session to an altitude up to 22,000 ft (FL220) or 6,705 meters, where heart rate (HR), breathing rate (BR) and core temperature (Tc) were monitored with the use of a chest strap sensor pre and post HH exposure. A pulse oximeter registered levels of saturation of oxygen (SpO2), number and duration of desaturations during the HH chamber flight. Hypoxia symptoms as described by the SACs during the HH training session were also registered. This data allowed to generate a preliminary predictive model of the oxygen desaturation and O2 pressure curve for each subject, which consists of a sixth-order polynomial fit during exposure, and a fifth or fourth-order polynomial fit during recovery. Data analysis showed that HR and BR showed no significant differences between pre and post HH exposure in most of the SACs, while Tc measures showed slight but consistent decrement changes. All subjects registered SpO2 greater than 94% for the majority of their individual HH exposures, but all of them presented at least one clinically significant desaturation (SpO2 < 85% for more than 5 seconds) and half of the individuals showed SpO2 below 87% for at least 30% of their HH exposure time. Finally, real time collection of HH symptoms presented temperature somatosensory perceptions (SP) for 65% of individuals, and task-focus issues for 52.5% of individuals as the most common HH indications. 95% of the subjects experienced HH onset symptoms below FL180; all participants achieved full recovery of HH symptoms within 1 minute of donning their O2 mask. The current HH study performed on this group of individuals suggests a rapid and fully reversible physiologic response after HH exposure as expected and obtained in previous studies. Our data showed consistent results between predicted versus observed SpO2 curves during HH suggesting a mathematical function that may be used to model HH performance deficiencies. During the HH study, real-time HH symptoms were registered providing evidenced SP and task focusing as the earliest and most common indicators. Finally, an assessment of HH signs of symptoms in a group of heterogeneous, non-pilot individuals showed similar results to previous studies in homogeneous populations of pilots.

Keywords: slow onset hypoxia, hypobaric chamber training, altitude sickness, symptoms and altitude, pressure cabin

Procedia PDF Downloads 105
3000 Parallel Tracking and Mapping of a Fleet of Quad-Rotor

Authors: M. Bazin, I. Bouguir, D. Combe, V. Germain, G. Lassade

Abstract:

The problem of managing a fleet of quad-rotor drones in a completely unknown environment is analyzed in the present paper. This work is following the footsteps of other studies about how should be managed the movements of a swarm of elements that have to stay gathered throughout their activities. In this paper we aim to demonstrate the limitations of a system where absolutely all the calculations and physical movements of our elements are done by one single external element. The strategy of control is an adaptive approach which takes into account the explored environment. This is made possible thanks to a set of command rules which can guide the drones through various missions with defined goal. The result of the mission is independent of the nature of environment and the number of drones in the fleet. This strategy is based on a simultaneous usage of different data: obstacles positions, real-time positions of all drones and relative positions between the different drones. The present work is made with the Robot Operating System and used several open-source projects on localization and usage of drones.

Keywords: cooperative guidance, distributed control, unmanned aerial vehicle, obstacle avoidance

Procedia PDF Downloads 290
2999 Generation of Automated Alarms for Plantwide Process Monitoring

Authors: Hyun-Woo Cho

Abstract:

Earlier detection of incipient abnormal operations in terms of plant-wide process management is quite necessary in order to improve product quality and process safety. And generating warning signals or alarms for operating personnel plays an important role in process automation and intelligent plant health monitoring. Various methodologies have been developed and utilized in this area such as expert systems, mathematical model-based approaches, multivariate statistical approaches, and so on. This work presents a nonlinear empirical monitoring methodology based on the real-time analysis of massive process data. Unfortunately, the big data includes measurement noises and unwanted variations unrelated to true process behavior. Thus the elimination of such unnecessary patterns of the data is executed in data processing step to enhance detection speed and accuracy. The performance of the methodology was demonstrated using simulated process data. The case study showed that the detection speed and performance was improved significantly irrespective of the size and the location of abnormal events.

Keywords: detection, monitoring, process data, noise

Procedia PDF Downloads 235
2998 Using A Blockchain-Based, End-to-End Encrypted Communication System Between Mobile Terminals to Improve Organizational Privacy

Authors: Andrei Bogdan Stanescu, Robert Stana

Abstract:

Creating private and secure communication channels between employees has become a critical aspect in order to ensure organizational integrity and avoid leaks of sensitive information. With the widespread use of modern methods of disrupting communication between users, real use-cases of advanced encryption mechanisms have emerged to avoid cyber-attackers that are willing to intercept private conversations between critical employees in an organization. This paper aims to present a custom implementation of a messaging application named “Whisper” that uses end-to-end encryption (E2EE) mechanisms and blockchain-related components to protect sensitive conversations and mitigate the risks of information breaches inside organizations. The results of this research paper aim to expand the areas of applicability of E2EE algorithms and integrations with private blockchains in chat applications as a viable method of enhancing intra-organizational communication privacy.

Keywords: end-to-end encryption, mobile communication, cryptography, communication security, data privacy

Procedia PDF Downloads 68
2997 Concept Drifts Detection and Localisation in Process Mining

Authors: M. V. Manoj Kumar, Likewin Thomas, Annappa

Abstract:

Process mining provides methods and techniques for analyzing event logs recorded in modern information systems that support real-world operations. While analyzing an event-log, state-of-the-art techniques available in process mining believe that the operational process as a static entity (stationary). This is not often the case due to the possibility of occurrence of a phenomenon called concept drift. During the period of execution, the process can experience concept drift and can evolve with respect to any of its associated perspectives exhibiting various patterns-of-change with a different pace. Work presented in this paper discusses the main aspects to consider while addressing concept drift phenomenon and proposes a method for detecting and localizing the sudden concept drifts in control-flow perspective of the process by using features extracted by processing the traces in the process log. Our experimental results are promising in the direction of efficiently detecting and localizing concept drift in the context of process mining research discipline.

Keywords: abrupt drift, concept drift, sudden drift, control-flow perspective, detection and localization, process mining

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2996 Presentation of HVA Faults in SONELGAZ Underground Network and Methods of Faults Diagnostic and Faults Location

Authors: I. Touaїbia, E. Azzag, O. Narjes

Abstract:

Power supply networks are growing continuously and their reliability is getting more important than ever. The complexity of the whole network comprises numerous components that can fail and interrupt the power supply for the end user. Underground distribution systems are normally exposed to permanent faults, due to specific construction characteristics. In these systems, visual inspection cannot be performed. In order to enhance service restoration, accurate fault location techniques must be applied. This paper describes the different faults that affect the underground distribution system of SONELGAZ (National Society of Electricity and Gas of Algeria), and cable fault location procedure with impulse reflection method (TDR), based in the analyses of the cable response of the electromagnetic impulse, allows cable fault prelocation. The results are obtained from real test in the underground distribution feeder from electrical network of energy distribution company of Souk-Ahras, in order to know the influence of cable characteristics in the types and frequency of faults.

Keywords: distribution networks, fault location, TDR, underground cable

Procedia PDF Downloads 515