Search results for: filtering and estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2180

Search results for: filtering and estimation

1430 Estimating the Impact of Appliance Energy Efficiency Improvement on Residential Energy Demand in Tema City, Ghana

Authors: Marriette Sakah, Samuel Gyamfi, Morkporkpor Delight Sedzro, Christoph Kuhn

Abstract:

Ghana is experiencing rapid economic development and its cities command an increasingly dominant role as centers of both production and consumption. Cities run on energy and are extremely vulnerable to energy scarcity, energy price escalations and health impacts of very poor air quality. The overriding concern in Ghana and other West African states is bridging the gap between energy demand and supply. Energy efficiency presents a cost-effective solution for supply challenges by enabling more coverage with current power supply levels and reducing the need for investment in additional generation capacity and grid infrastructure. In Ghana, major issues for energy policy formulation in residential applications include lack of disaggregated electrical energy consumption data and lack of thorough understanding with regards to socio-economic influences on energy efficiency investment. This study uses a bottom up approach to estimate baseline electricity end-use as well as the energy consumption of best available technologies to enable estimation of energy-efficiency resource in terms of relative reduction in total energy use for Tema city, Ghana. A ground survey was conducted to assess the probable consumer behavior in response to energy efficiency initiatives to enable estimation of the amount of savings that would occur in response to specific policy interventions with regards to funding and incentives provision targeted at households. Results show that 16% - 54% reduction in annual electricity consumption is reasonably achievable depending on the level of incentives provision. The saved energy could supply 10000 - 34000 additional households if the added households use only best available technology. Political support and consumer awareness are necessary to translate energy efficiency resources into real energy savings.

Keywords: achievable energy savings, energy efficiency, Ghana, household appliances

Procedia PDF Downloads 197
1429 Evaluation of Capacity of Bed Planted with Macrophytes for Wastewater Treatment of Biskra City, Algeria

Authors: Mimeche Leila, Debabeche Mahmoud

Abstract:

It is question to study and to value the possibility of settling the process of purification by plants (constructed wetland) to treat the domestic waste water of Biskra, city in a semi-arid environment with grave problems of. According to the bibliography, the process of treatment by plants is considered as more advantageous than the classic techniques. It is the use of beds with macrophytes where the purification is made by the combined action of plants and micro-organisms in a filtering bed. The micro-organisms which are aerobic bacteria and\or anaerobic have for main function to degrade the polluting materials. Plants in the macrophytes beds have for function to serve as support in the development of bacteria and to favour also their development. In this study, we present a preliminary experimental analysis of the potentialities of treatment of some macrpohytes plants, implanted in basins filled of gravel. Analyses physico chemical and bacteriological of the waste water indicate a good elimination of the polluting materials, and put in evidence the purifier power of these plants, in association with bacteria. The obtained results seem to be interesting and encourage deepening the study for other types of plants in other conditions.

Keywords: constructed wetlands, macrophytes, sewage treatment, wastewater

Procedia PDF Downloads 384
1428 Robust Data Image Watermarking for Data Security

Authors: Harsh Vikram Singh, Ankur Rai, Anand Mohan

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In this paper, we propose secure and robust data hiding algorithm based on DCT by Arnold transform and chaotic sequence. The watermark image is scrambled by Arnold cat map to increases its security and then the chaotic map is used for watermark signal spread in middle band of DCT coefficients of the cover image The chaotic map can be used as pseudo-random generator for digital data hiding, to increase security and robustness .Performance evaluation for robustness and imperceptibility of proposed algorithm has been made using bit error rate (BER), normalized correlation (NC), and peak signal to noise ratio (PSNR) value for different watermark and cover images such as Lena, Girl, Tank images and gain factor .We use a binary logo image and text image as watermark. The experimental results demonstrate that the proposed algorithm achieves higher security and robustness against JPEG compression as well as other attacks such as addition of noise, low pass filtering and cropping attacks compared to other existing algorithm using DCT coefficients. Moreover, to recover watermarks in proposed algorithm, there is no need to original cover image.

Keywords: data hiding, watermarking, DCT, chaotic sequence, arnold transforms

Procedia PDF Downloads 494
1427 The Effect of Manure Loaded Biochar on Soil Microbial Communities

Authors: T. Weber, D. MacKenzie

Abstract:

The script in this paper describes the use of advanced simulation environment using electronic systems (microcontroller, operational amplifiers, and FPGA). The simulation was used for non-linear dynamic systems behaviour with required observer structure working with parallel real-time simulation based on state-space representation. The proposed deposited model was used for electrodynamic effects including ionising effects and eddy current distribution also. With the script and proposed method, it is possible to calculate the spatial distribution of the electromagnetic fields in real-time and such systems. For further purpose, the spatial temperature distribution may also be used. With upon system, the uncertainties and disturbances may be determined. This provides the estimation of the more precise system states for the required system and additionally the estimation of the ionising disturbances that arise due to radiation effects in space systems. The results have also shown that a system can be developed specifically with the real-time calculation (estimation) of the radiation effects only. Electronic systems can take damage caused by impacts with charged particle flux in space or radiation environment. TID (Total Ionising Dose) of 1 Gy and Single Effect Transient (SET) free operation up to 50 MeVcm²/mg may assure certain functions. Single-Event Latch-up (SEL) results on the placement of several transistors in the shared substrate of an integrated circuit; ionising radiation can activate an additional parasitic thyristor. This short circuit between semiconductor-elements can destroy the device without protection and measurements. Single-Event Burnout (SEB) on the other hand, increases current between drain and source of a MOSFET and destroys the component in a short time. A Single-Event Gate Rupture (SEGR) can destroy a dielectric of semiconductor also. In order to be able to react to these processes, it must be calculated within a shorter time that ionizing radiation and dose is present. For this purpose, sensors may be used for the realistic evaluation of the diffusion and ionizing effects of the test system. For this purpose, the Peltier element is used for the evaluation of the dynamic temperature increases (dT/dt), from which a measure of the ionization processes and thus radiation will be detected. In addition, the piezo element may be used to record highly dynamic vibrations and oscillations to absorb impacts of charged particle flux. All available sensors shall be used to calibrate the spatial distributions also. By measured value of size and known location of the sensors, the entire distribution in space can be calculated retroactively or more accurately. With the formation, the type of ionisation and the direct effect to the systems and thus possible prevent processes can be activated up to the shutdown. The results show possibilities to perform more qualitative and faster simulations independent of space-systems and radiation environment also. The paper gives additionally an overview of the diffusion effects and their mechanisms.

Keywords: cattle, biochar, manure, microbial activity

Procedia PDF Downloads 89
1426 An Assessment of Health Hazards in Urban Communities: A Study of Spatial-Temporal Variations of Dengue Epidemic in Colombo, Sri Lanka

Authors: U. Thisara G. Perera, C. M. Kanchana N. K. Chandrasekara

Abstract:

Dengue is an epidemic which is spread by Aedes Egyptai and Aedes Albopictus mosquitoes. The cases of dengue show a dramatic growth rate of the epidemic in urban and semi urban areas spatially in tropical and sub-tropical regions of the world. Incidence of dengue has become a prominent reason for hospitalization and deaths in Asian countries, including Sri Lanka. During the last decade the dengue epidemic began to spread from urban to semi-urban and then to rural settings of the country. The highest number of dengue infected patients was recorded in Sri Lanka in the year 2016 and the highest number of patients was identified in Colombo district. Together with the commercial, industrial, and other supporting services, the district suffers from rapid urbanization and high population density. Thus, drainage and waste disposal patterns of the people in this area exert an additional pressure to the environment. The district is situated in the wet zone and thus low lying lands constitute the largest portion of the district. This situation additionally facilitates mosquito breeding sites. Therefore, the purpose of the present study was to assess the spatial and temporal distribution patterns of dengue epidemic in Kolonnawa MOH area (Medical Officer of Health) in the district of Colombo. The study was carried out using 615 recorded dengue cases in Kollonnawa MOH area during the south east monsoon season from May to September 2016. The Moran’s I and Kernel density estimation were used as analytical methods. The analysis of data was accomplished through the integrated use of ArcGIS 10.1 software packages along with Microsoft Excel analytical tool. Field observation was also carried out for verification purposes during the study period. Results of the Moran’s I index indicates that the spatial distribution of dengue cases showed a cluster distribution pattern across the area. Kernel density estimation emphasis that dengue cases are high where the population has gathered, especially in areas comprising housing schemes. Results of the Kernel Density estimation further discloses that hot spots of dengue epidemic are located in the western half of the Kolonnawa MOH area, which is close to the Colombo municipal boundary and there is a significant relationship with high population density and unplanned urban land use practices. Results of the field observation confirm that the drainage systems in these areas function poorly and careless waste disposal methods of the people further encourage mosquito breeding sites. This situation has evolved harmfully from a public health issue to a social problem, which ultimately impacts on the economy and social lives of the country.

Keywords: Dengue epidemic, health hazards, Kernel density, Moran’s I, Sri Lanka

Procedia PDF Downloads 286
1425 Design of Enhanced Adaptive Filter for Integrated Navigation System of FOG-SINS and Star Tracker

Authors: Nassim Bessaad, Qilian Bao, Zhao Jiangkang

Abstract:

The fiber optics gyroscope in the strap-down inertial navigation system (FOG-SINS) suffers from precision degradation due to the influence of random errors. In this work, an enhanced Allan variance (AV) stochastic modeling method combined with discrete wavelet transform (DWT) for signal denoising is implemented to estimate the random process in the FOG signal. Furthermore, we devise a measurement-based iterative adaptive Sage-Husa nonlinear filter with augmented states to integrate a star tracker sensor with SINS. The proposed filter adapts the measurement noise covariance matrix based on the available data. Moreover, the enhanced stochastic modeling scheme is invested in tuning the process noise covariance matrix and the augmented state Gauss-Markov process parameters. Finally, the effectiveness of the proposed filter is investigated by employing the collected data in laboratory conditions. The result shows the filter's improved accuracy in comparison with the conventional Kalman filter (CKF).

Keywords: inertial navigation, adaptive filtering, star tracker, FOG

Procedia PDF Downloads 65
1424 Optical Flow Based System for Cross Traffic Alert

Authors: Giuseppe Spampinato, Salvatore Curti, Ivana Guarneri, Arcangelo Bruna

Abstract:

This document describes an advanced system and methodology for Cross Traffic Alert (CTA), able to detect vehicles that move into the vehicle driving path from the left or right side. The camera is supposed to be not only on a vehicle still, e.g. at a traffic light or at an intersection, but also moving slowly, e.g. in a car park. In all of the aforementioned conditions, a driver’s short loss of concentration or distraction can easily lead to a serious accident. A valid support to avoid these kinds of car crashes is represented by the proposed system. It is an extension of our previous work, related to a clustering system, which only works on fixed cameras. Just a vanish point calculation and simple optical flow filtering, to eliminate motion vectors due to the car relative movement, is performed to let the system achieve high performances with different scenarios, cameras and resolutions. The proposed system just uses as input the optical flow, which is hardware implemented in the proposed platform and since the elaboration of the whole system is really speed and power consumption, it is inserted directly in the camera framework, allowing to execute all the processing in real-time.

Keywords: clustering, cross traffic alert, optical flow, real time, vanishing point

Procedia PDF Downloads 183
1423 A Novel Dual Band-pass filter Based On Coupling of Composite Right/Left Hand CPW and (CSRRs) Uses Ferrite Components

Authors: Mohammed Berka, Khaled Merit

Abstract:

Recent works on microwave filters show that the constituent materials such filters are very important in the design and realization. Several solutions have been proposed to improve the qualities of filtering. In this paper, we propose a new dual band-pass filter based on the coupling of a composite (CRLH) coplanar waveguide with complementary split ring resonators (CSRRs). The (CRLH) CPW is composed of two resonators, each one has an interdigital capacitor (CID) and two short-circuited stubs parallel to top ground plane. On the lower ground plane, we use defected ground structure technology (DGS) to engrave two (CSRRs) offered with different shapes and dimensions. Between the top ground plane and the substrate, we place a ferrite layer to control the electromagnetic coupling between (CRLH) CPW and (CSRRs). The global filter that has coplanar access will have a dual band-pass behavior around the magnetic resonances of (CSRRs). Since there’s no scientific or experimental result in the literature for this kind of complicated structure, it was necessary to perform simulation using HFSS Ansoft designer.

Keywords: complementary split ring resonators, coplanar waveguide, ferrite, filter, stub.

Procedia PDF Downloads 389
1422 Deep Learning for Recommender System: Principles, Methods and Evaluation

Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

Abstract:

Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

Procedia PDF Downloads 457
1421 Non-Invasive Imaging of Tissue Using Near Infrared Radiations

Authors: Ashwani Kumar Aggarwal

Abstract:

NIR Light is non-ionizing and can pass easily through living tissues such as breast without any harmful effects. Therefore, use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function. This blurred reconstructed image has been enhanced using a digital filter which is optimal in mean square sense.

Keywords: least-squares optimization, filtering, tomography, laser interaction, light scattering

Procedia PDF Downloads 300
1420 A Posterior Predictive Model-Based Control Chart for Monitoring Healthcare

Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

Abstract:

Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: average run length (ARL), bernoulli cusum (BC) chart, beta binomial posterior predictive (BBPP) distribution, clinical indicator (CI), healthcare organization (HCO), highest posterior density (HPD) interval

Procedia PDF Downloads 189
1419 Forensic Entomology in Algeria

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

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Forensic entomology is the use of insects and their arthropod relatives as silent witnesses to aid legal investigations by interpreting information concerning a death. The main purpose of forensic entomology is to establish the postmortem interval or PMI Postmortem interval is a matter of crucial importance in the investigations of homicide and other untimely deaths when the body found is after three days. Forensic entomology has grown immensely as a discipline in the past thirty years. In Algeria, forensic entomology was introduced in 2010 by the National Institute for Criminalistics and Criminology of the National Gendarmerie (NICC). However, all the work that has been done so far in this growing field in Algeria has been unknown at both the national and international levels. In this context, the aim of this paper is to describe the state of forensic entomology in Algeria. The Laboratory of Entomology of the NICC is the only one of its kind in Algeria. It started its activities in 2010, consisting of two specialists. The main missions of the laboratory are estimation of the PMI by the analysis of entomological evidence, and determination if the body was moved. Currently, the laboratory is performing different tasks such as the expert work required by investigators to estimate the PMI using the insects. The estimation is performed by the accumulated degree days method (ADD) in most of the cases except for those where the cadaver is in dry decay. To assure the quality of the entomological evidence, crime scene personnel are trained by the laboratory of Entomology of the NICC. Recently, undergraduate and graduate students have been studying carrion ecology and insect activity in different geographic locations of Algeria using rabbits and wild boar cadavers as animal models. The Laboratory of Entomology of the NICC has also been involved in some of these research projects. Entomotoxicology experiments are also conducted with the collaboration of the Toxicology Department of the NICC. By dint of hard work that has been performed by the Laboratory of Entomology of the NICC, official bodies have been adopting more and more the use of entomological evidence in criminal investigations in Algeria, which is commendable. It is important, therefore, that steps are taken to fill in the gaps in the knowledge necessary for entomological evidence to have a useful future in criminal investigations in Algeria.

Keywords: forensic entomology, corpse, insects, postmortem interval, expertise, Algeria

Procedia PDF Downloads 385
1418 Investigation of External Pressure Coefficients on Large Antenna Parabolic Reflector Using Computational Fluid Dynamics

Authors: Varun K, Pramod B. Balareddy

Abstract:

Estimation of wind forces plays a significant role in the in the design of large antenna parabolic reflectors. Reflector surface accuracies are very sensitive to the gain of the antenna system at higher frequencies. Hence accurate estimation of wind forces becomes important, which is primary input for design and analysis of the reflector system. In the present work, numerical simulation of wind flow using Computational Fluid Dynamics (CFD) software is used to investigate the external pressure coefficients. An extensive comparative study has been made between the CFD results and the published wind tunnel data for different wind angle of attacks (α) acting over concave to convex surfaces respectively. Flow simulations using CFD are carried out to estimate the coefficients of Drag, Lift and Moment for the parabolic reflector. Coefficients of pressures (Cp) over the front and the rear face of the reflector are extracted over surface of the reflector to study the net pressure variations. These resultant pressure variations are compared with the published wind tunnel data for different angle of attacks. It was observed from the CFD simulations, both convex and concave face of reflector system experience a band of pressure variations for the positive and negative angle of attacks respectively. In the published wind tunnel data, Pressure variations over convex surfaces are assumed to be uniform and vice versa. Chordwise and spanwise pressure variations were calculated and compared with the published experimental data. In the present work, it was observed that the maximum pressure coefficients for α ranging from +30° to -90° and α=+90° was lower. For α ranging from +45° to +75°, maximum pressure coefficients were higher as compared to wind tunnel data. This variation is due to non-uniform pressure distribution observed over front and back faces of reflector. Variations in Cd, Cl and Cm over α=+90° to α=-90° was in close resemblance with the experimental data.

Keywords: angle of attack, drag coefficient, lift coefficient, pressure coefficient

Procedia PDF Downloads 237
1417 Self-Tuning-Filter and Fuzzy Logic Control for Shunt Active Power Filter

Authors: Kaddari Faiza, Mazari Benyounes, Mihoub Youcef, Safa Ahmed

Abstract:

Active filtering of electric power has now become a mature technology for reactive power and harmonic compensation caused by the proliferation of power electronics devices used for industrial, commercial and residential purposes. The aim of this study is to enhance the power quality by improving the performances of shunt active power filter in harmonic mitigation to obtain sinusoidal source currents with very weak ripples. A power circuit configuration and control scheme for shunt active power filter are described with an improved method for harmonics compensation using self-tuning-filter for harmonics identification and fuzzy logic control to generate reference current. Simulation results (using MATLAB/SIMULINK) illustrates the compensation characteristics of the proposed control strategy. Analysis of these results proves the feasibility and effectiveness of this method to improve the power quality and also show the performances of fuzzy logic control which provides flexibility, high precision and fast response. The total harmonic distortion (THD %) for the simulations found to be within the recommended imposed IEEE 519-1992 harmonic standard.

Keywords: Active Powers Filter (APF), Self-Tuning-Filter (STF), fuzzy logic control, hysteresis-band control

Procedia PDF Downloads 711
1416 Intelligent Rheumatoid Arthritis Identification System Based Image Processing and Neural Classifier

Authors: Abdulkader Helwan

Abstract:

Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

Procedia PDF Downloads 517
1415 A Character Detection Method for Ancient Yi Books Based on Connected Components and Regressive Character Segmentation

Authors: Xu Han, Shanxiong Chen, Shiyu Zhu, Xiaoyu Lin, Fujia Zhao, Dingwang Wang

Abstract:

Character detection is an important issue for character recognition of ancient Yi books. The accuracy of detection directly affects the recognition effect of ancient Yi books. Considering the complex layout, the lack of standard typesetting and the mixed arrangement between images and texts, we propose a character detection method for ancient Yi books based on connected components and regressive character segmentation. First, the scanned images of ancient Yi books are preprocessed with nonlocal mean filtering, and then a modified local adaptive threshold binarization algorithm is used to obtain the binary images to segment the foreground and background for the images. Second, the non-text areas are removed by the method based on connected components. Finally, the single character in the ancient Yi books is segmented by our method. The experimental results show that the method can effectively separate the text areas and non-text areas for ancient Yi books and achieve higher accuracy and recall rate in the experiment of character detection, and effectively solve the problem of character detection and segmentation in character recognition of ancient books.

Keywords: CCS concepts, computing methodologies, interest point, salient region detections, image segmentation

Procedia PDF Downloads 110
1414 Estimation of Effective Mechanical Properties of Linear Elastic Materials with Voids Due to Volume and Surface Defects

Authors: Sergey A. Lurie, Yury O. Solyaev, Dmitry B. Volkov-Bogorodsky, Alexander V. Volkov

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The media with voids is considered and the method of the analytical estimation of the effective mechanical properties in the theory of elastic materials with voids is proposed. The variational model of the porous media is discussed, which is based on the model of the media with fields of conserved dislocations. It is shown that this model is fully consistent with the known model of the linear elastic materials with voids. In the present work, the generalized model of the porous media is proposed in which the specific surface properties are associated with the field of defects-pores in the volume of the deformed body. Unlike typical surface elasticity model, the strain energy density of the considered model includes the special part of the surface energy with the quadratic form of the free distortion tensor. In the result, the non-classical boundary conditions take modified form of the balance equations of volume and surface stresses. The analytical approach is proposed in the present work which allows to receive the simple enough engineering estimations for effective characteristics of the media with free dilatation. In particular, the effective flexural modulus and Poisson's ratio are determined for the problem of a beam pure bending. Here, the known voids elasticity solution was expanded on the generalized model with the surface effects. Received results allow us to compare the deformed state of the porous beam with the equivalent classic beam to introduce effective bending rigidity. Obtained analytical expressions for the effective properties depend on the thickness of the beam as a parameter. It is shown that the flexural modulus of the porous beam is decreased with an increasing of its thickness and the effective Poisson's ratio of the porous beams can take negative values for the certain values of the model parameters. On the other hand, the effective shear modulus is constant under variation of all values of the non-classical model parameters. Solutions received for a beam pure bending and the hydrostatic loading of the porous media are compared. It is shown that an analytical estimation for the bulk modulus of the porous material under hydrostatic compression gives an asymptotic value for the effective bulk modulus of the porous beam in the case of beam thickness increasing. Additionally, it is shown that the scale effects appear due to the surface properties of the porous media. Obtained results allow us to offer the procedure of an experimental identification of the non-classical parameters in the theory of the linear elastic materials with voids based on the bending tests for samples with different thickness. Finally, the problem of implementation of the Saint-Venant hypothesis for the transverse stresses in the porous beam are discussed. These stresses are different from zero in the solution of the voids elasticity theory, but satisfy the integral equilibrium equations. In this work, the exact value of the introduced surface parameter was found, which provides the vanishing of the transverse stresses on the free surfaces of a beam.

Keywords: effective properties, scale effects, surface defects, voids elasticity

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1413 Carotenoids a Biologically Important Bioactive Compound

Authors: Aarti Singh, Anees Ahmad

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Carotenoids comprise a group of isoprenoid pigments. Carotenes, xanthophylls and their derivatives have been found to play an important role in all living beings through foods, neutraceuticals and pharmaceuticals. α-carotene, β-carotene and β-cryptoxanthin play a vital role in humans to provide vitamin A source for the growth, development and proper functioning of immune system and vision. They are very crucial for plants and humans as they protect from photooxidative damage and are excellent antioxidants quenching singlet molecular oxygen and peroxyl radicals. Diet including more intake of carotenoids results in reduced threat of various chronic diseases such as cancer (lung, breast, prostrate, colorectal and ovarian cancers) and coronary heart diseases. The blue light filtering efficiency of the carotenoids in liposomes have been reported to be maximum in lutein followed by zeaxanthin, β-carotene and lycopene. Lycopene plays a vital role for the protection from CVD. Lycopene in serum is directly related to reduced risk of osteoporosis in postmenopausal women. Carotenoids have major role in the treatment of skin disorders. There is need to identify and isolate novel carotenoids from diverse natural sources for human health benefits.

Keywords: antioxidants, carotenoids, neutraceuticals, osteoporosis, pharmaceuticals

Procedia PDF Downloads 365
1412 Xen45 Gel Implant in Open Angle Glaucoma: Efficacy, Safety and Predictors of Outcome

Authors: Fossarello Maurizio, Mattana Giorgio, Tatti Filippo.

Abstract:

The most widely performed surgical procedure in Open-Angle Glaucoma (OAG) is trabeculectomy. Although this filtering procedure is extremely effective, surgical failure and postoperative complications are reported. Due to the its invasive nature and possible complications, trabeculectomy is usually reserved, in practice, for patients who are refractory to medical and laser therapy. Recently, a number of micro-invasive surgical techniques (MIGS: Micro-Invasive Glaucoma Surgery), have been introduced in clinical practice. They meet the criteria of micro-incisional approach, minimal tissue damage, short surgical time, reliable IOP reduction, extremely high safety profile and rapid post-operative recovery. Xen45 Gel Implant (Allergan, Dublin, Ireland) is one of the MIGS alternatives, and consists in a porcine gelatin tube designed to create an aqueous flow from the anterior chamber to the subconjunctival space, bypassing the resistance of the trabecular meshwork. In this study we report the results of this technique as a favorable option in the treatment of OAG for its benefits in term of efficacy and safety, either alone or in combination with cataract surgery. This is a retrospective, single-center study conducted in consecutive OAG patients, who underwent Xen45 Gel Stent implantation alone or in combination with phacoemulsification, from October 2018 to June 2019. The primary endpoint of the study was to evaluate the reduction of both IOP and number of antiglaucoma medications at 12 months. The secondary endpoint was to correlate filtering bleb morphology evaluated by means of anterior segment OCT with efficacy in IOP lowering and eventual further procedures requirement. Data were recorded on Microsoft Excel and study analysis was performed using Microsoft Excel and SPSS (IBM). Mean values with standard deviations were calculated for IOPs and number of antiglaucoma medications at all points. Kolmogorov-Smirnov test showed that IOP followed a normal distribution at all time, therefore the paired Student’s T test was used to compare baseline and postoperative mean IOP. Correlation between postoperative Day 1 IOP and Month 12 IOP was evaluated using Pearson coefficient. Thirty-six eyes of 36 patients were evaluated. As compared to baseline, mean IOP and the mean number of antiglaucoma medications significantly decreased from 27,33 ± 7,67 mmHg to 16,3 ± 2,89 mmHg (38,8% reduction) and from 2,64 ± 1,39 to 0,42 ± 0,8 (84% reduction), respectively, at 12 months after surgery (both p < 0,001). According to bleb morphology, eyes were divided in uniform group (n=8, 22,2%), subconjunctival separation group (n=5, 13,9%), microcystic multiform group (n=9, 25%) and multiple internal layer group (n=14, 38,9%). Comparing to baseline, there was no significative difference in IOP between the 4 groups at month 12 follow-up visit. Adverse events included bleb function decrease (n=14, 38,9%), hypotony (n=8, 22,2%) and choroidal detachment (n=2, 5,6%). All eyes presenting bleb flattening underwent needling and MMC injection. The higher percentage of patients that required secondary needling was in the uniform group (75%), with a significant difference between the groups (p=0,03). Xen45 gel stent, either alone or in combination with phacoemulsification, provided a significant lowering in both IOP and medical antiglaucoma treatment and an elevated safety profile.

Keywords: anterior segment OCT, bleb morphology, micro-invasive glaucoma surgery, open angle glaucoma, Xen45 gel implant

Procedia PDF Downloads 126
1411 Use of SUDOKU Design to Assess the Implications of the Block Size and Testing Order on Efficiency and Precision of Dulce De Leche Preference Estimation

Authors: Jéssica Ferreira Rodrigues, Júlio Silvio De Sousa Bueno Filho, Vanessa Rios De Souza, Ana Carla Marques Pinheiro

Abstract:

This study aimed to evaluate the implications of the block size and testing order on efficiency and precision of preference estimation for Dulce de leche samples. Efficiency was defined as the inverse of the average variance of pairwise comparisons among treatments. Precision was defined as the inverse of the variance of treatment means (or effects) estimates. The experiment was originally designed to test 16 treatments as a series of 8 Sudoku 16x16 designs being 4 randomized independently and 4 others in the reverse order, to yield balance in testing order. Linear mixed models were assigned to the whole experiment with 112 testers and all their grades, as well as their partially balanced subgroups, namely: a) experiment with the four initial EU; b) experiment with EU 5 to 8; c) experiment with EU 9 to 12; and b) experiment with EU 13 to 16. To record responses we used a nine-point hedonic scale, it was assumed a mixed linear model analysis with random tester and treatments effects and with fixed test order effect. Analysis of a cumulative random effects probit link model was very similar, with essentially no different conclusions and for simplicity, we present the results using Gaussian assumption. R-CRAN library lme4 and its function lmer (Fit Linear Mixed-Effects Models) was used for the mixed models and libraries Bayesthresh (default Gaussian threshold function) and ordinal with the function clmm (Cumulative Link Mixed Model) was used to check Bayesian analysis of threshold models and cumulative link probit models. It was noted that the number of samples tested in the same session can influence the acceptance level, underestimating the acceptance. However, proving a large number of samples can help to improve the samples discrimination.

Keywords: acceptance, block size, mixed linear model, testing order, testing order

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1410 Future Trends of Mechatronics Engineering in Pakistan

Authors: Aqeela Mir, Akhtar Nawaz Malik, Javaid Iqbal

Abstract:

The paper presents a survey based approach in order to observe the level of awareness regarding Mechatronics in society of Pakistan and the factors affecting the future development trend of Mechatronics in Pakistan. With the help of these surveys a new direction for making a Mathematical model for the future development trend of Mechatronics in Pakistan is also suggested.

Keywords: mechatronics society survey, future development trend of mechatronics in pakistan, probability estimation, mathematical model

Procedia PDF Downloads 491
1409 Exploring the Applications of Neural Networks in the Adaptive Learning Environment

Authors: Baladitya Swaika, Rahul Khatry

Abstract:

Computer Adaptive Tests (CATs) is one of the most efficient ways for testing the cognitive abilities of students. CATs are based on Item Response Theory (IRT) which is based on item selection and ability estimation using statistical methods of maximum information selection/selection from posterior and maximum-likelihood (ML)/maximum a posteriori (MAP) estimators respectively. This study aims at combining both classical and Bayesian approaches to IRT to create a dataset which is then fed to a neural network which automates the process of ability estimation and then comparing it to traditional CAT models designed using IRT. This study uses python as the base coding language, pymc for statistical modelling of the IRT and scikit-learn for neural network implementations. On creation of the model and on comparison, it is found that the Neural Network based model performs 7-10% worse than the IRT model for score estimations. Although performing poorly, compared to the IRT model, the neural network model can be beneficially used in back-ends for reducing time complexity as the IRT model would have to re-calculate the ability every-time it gets a request whereas the prediction from a neural network could be done in a single step for an existing trained Regressor. This study also proposes a new kind of framework whereby the neural network model could be used to incorporate feature sets, other than the normal IRT feature set and use a neural network’s capacity of learning unknown functions to give rise to better CAT models. Categorical features like test type, etc. could be learnt and incorporated in IRT functions with the help of techniques like logistic regression and can be used to learn functions and expressed as models which may not be trivial to be expressed via equations. This kind of a framework, when implemented would be highly advantageous in psychometrics and cognitive assessments. This study gives a brief overview as to how neural networks can be used in adaptive testing, not only by reducing time-complexity but also by being able to incorporate newer and better datasets which would eventually lead to higher quality testing.

Keywords: computer adaptive tests, item response theory, machine learning, neural networks

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1408 Automatic Product Identification Based on Deep-Learning Theory in an Assembly Line

Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

Abstract:

Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: deep-learning, image classification, image identification, industrial engineering.

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1407 A Review: Carotenoids a Biologically Important Bioactive Compound

Authors: Aarti Singh, Anees Ahmad

Abstract:

Carotenoids comprise a group of isoprenoid pigments. Carotenes, xanthophylls and their derivatives have been found to play an important role in all living beings through foods, neutraceuticals and pharmaceuticals. α-carotene, β-carotene and β-cryptoxanthin play a vital role in humans to provide vitamin A source for the growth, development and proper functioning of immune system and vision. They are very crucial for plants and humans as they protect from photooxidative damage and are excellent antioxidants quenching singlet molecular oxygen and peroxyl radicals. Diet including more intake of carotenoids results in reduced threat of various chronic diseases such as cancer (lung, breast, prostate, colorectal and ovarian cancers) and coronary heart diseases. The blue light filtering efficiency of the carotenoids in liposomes have been reported to be maximum in lutein followed by zeaxanthin, β-carotene and lycopene. Lycopene play a vital role for the protection from CVD. Lycopene in serum is directly related to reduced risk of osteoporosis in postmenopausal women. Carotenoids have the major role in the treatment of skin disorders. There is a need to identify and isolate novel carotenoids from diverse natural sources for human health benefits.

Keywords: antioxidants, carotenoids, neutraceuticals, osteoporosis, pharmaceuticals

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1406 Leukocyte Detection Using Image Stitching and Color Overlapping Windows

Authors: Lina, Arlends Chris, Bagus Mulyawan, Agus B. Dharmawan

Abstract:

Blood cell analysis plays a significant role in the diagnosis of human health. As an alternative to the traditional technique conducted by laboratory technicians, this paper presents an automatic white blood cell (leukocyte) detection system using Image Stitching and Color Overlapping Windows. The advantage of this method is to present a detection technique of white blood cells that are robust to imperfect shapes of blood cells with various image qualities. The input for this application is images from a microscope-slide translation video. The preprocessing stage is performed by stitching the input images. First, the overlapping parts of the images are determined, then stitching and blending processes of two input images are performed. Next, the Color Overlapping Windows is performed for white blood cell detection which consists of color filtering, window candidate checking, window marking, finds window overlaps, and window cropping processes. Experimental results show that this method could achieve an average of 82.12% detection accuracy of the leukocyte images.

Keywords: color overlapping windows, image stitching, leukocyte detection, white blood cell detection

Procedia PDF Downloads 291
1405 Generalization of Tau Approximant and Error Estimate of Integral Form of Tau Methods for Some Class of Ordinary Differential Equations

Authors: A. I. Ma’ali, R. B. Adeniyi, A. Y. Badeggi, U. Mohammed

Abstract:

An error estimation of the integrated formulation of the Lanczos tau method for some class of ordinary differential equations was reported. This paper is concern with the generalization of tau approximants and their corresponding error estimates for some class of ordinary differential equations (ODEs) characterized by m + s =3 (i.e for m =1, s=2; m=2, s=1; and m=3, s=0) where m and s are the order of differential equations and number of overdetermination, respectively. The general result obtained were validated with some numerical examples.

Keywords: approximant, error estimate, tau method, overdetermination

Procedia PDF Downloads 586
1404 Blocking of Random Chat Apps at Home Routers for Juvenile Protection in South Korea

Authors: Min Jin Kwon, Seung Won Kim, Eui Yeon Kim, Haeyoung Lee

Abstract:

Numerous anonymous chat apps that help people to connect with random strangers have been released in South Korea. However, they become a serious problem for young people since young people often use them for channels of prostitution or sexual violence. Although ISPs in South Korea are responsible for making inappropriate content inaccessible on their networks, they do not block traffic of random chat apps since 1) the use of random chat apps is entirely legal. 2) it is reported that they use HTTP proxy blocking so that non-HTTP traffic cannot be blocked. In this paper, we propose a service model that can block random chat apps at home routers. A service provider manages a blacklist that contains blocked apps’ information. Home routers that subscribe the service filter the traffic of the apps out using deep packet inspection. We have implemented a prototype of the proposed model, including a centralized server providing the blacklist, a Raspberry Pi-based home router that can filter traffic of the apps out, and an Android app used by the router’s administrator to locally customize the blacklist.

Keywords: deep packet inspection, internet filtering, juvenile protection, technical blocking

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1403 Mage Fusion Based Eye Tumor Detection

Authors: Ahmed Ashit

Abstract:

Image fusion is a significant and efficient image processing method used for detecting different types of tumors. This method has been used as an effective combination technique for obtaining high quality images that combine anatomy and physiology of an organ. It is the main key in the huge biomedical machines for diagnosing cancer such as PET-CT machine. This thesis aims to develop an image analysis system for the detection of the eye tumor. Different image processing methods are used to extract the tumor and then mark it on the original image. The images are first smoothed using median filtering. The background of the image is subtracted, to be then added to the original, results in a brighter area of interest or tumor area. The images are adjusted in order to increase the intensity of their pixels which lead to clearer and brighter images. once the images are enhanced, the edges of the images are detected using canny operators results in a segmented image comprises only of the pupil and the tumor for the abnormal images, and the pupil only for the normal images that have no tumor. The images of normal and abnormal images are collected from two sources: “Miles Research” and “Eye Cancer”. The computerized experimental results show that the developed image fusion based eye tumor detection system is capable of detecting the eye tumor and segment it to be superimposed on the original image.

Keywords: image fusion, eye tumor, canny operators, superimposed

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1402 Continuous Adaptive Robust Control for Non-Linear Uncertain Systems

Authors: Dong Sang Yoo

Abstract:

We consider nonlinear uncertain systems such that a priori information of the uncertainties is not available. For such systems, we assume that the upper bound of the uncertainties is represented as a Fredholm integral equation of the first kind and we propose an adaptation law that is capable of estimating the upper bound and design a continuous robust control which renders nonlinear uncertain systems ultimately bounded.

Keywords: adaptive control, estimation, Fredholm integral, uncertain system

Procedia PDF Downloads 464
1401 Designing a Patient Monitoring System Using Cloud and Semantic Web Technologies

Authors: Chryssa Thermolia, Ekaterini S. Bei, Stelios Sotiriadis, Kostas Stravoskoufos, Euripides G. M. Petrakis

Abstract:

Moving into a new era of healthcare, new tools and devices are developed to extend and improve health services, such as remote patient monitoring and risk prevention. In this concept, Internet of Things (IoT) and Cloud Computing present great advantages by providing remote and efficient services, as well as cooperation between patients, clinicians, researchers and other health professionals. This paper focuses on patients suffering from bipolar disorder, a brain disorder that belongs to a group of conditions called effective disorders, which is characterized by great mood swings.We exploit the advantages of Semantic Web and Cloud Technologies to develop a patient monitoring system to support clinicians. Based on intelligently filtering of evidence-knowledge and individual-specific information we aim to provide treatment notifications and recommended function tests at appropriate times or concluding into alerts for serious mood changes and patient’s non-response to treatment. We propose an architecture, as the back-end part of a cloud platform for IoT, intertwining intelligence devices with patients’ daily routine and clinicians’ support.

Keywords: bipolar disorder, intelligent systems patient monitoring, semantic web technologies, healthcare

Procedia PDF Downloads 488