Search results for: non-sorting genetic algorithm
1091 Massively-Parallel Bit-Serial Neural Networks for Fast Epilepsy Diagnosis: A Feasibility Study
Authors: Si Mon Kueh, Tom J. Kazmierski
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There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.Keywords: Artificial Neural Networks (ANN), bit-serial neural processor, FPGA, Neural Processing Element (NPE)
Procedia PDF Downloads 3161090 Mutations in rpoB, katG and inhA Genes: The Association with Resistance to Rifampicin and Isoniazid in Egyptian Mycobacterium tuberculosis Clinical Isolates
Authors: Ayman K. El Essawy, Amal M. Hosny, Hala M. Abu Shady
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The rapid detection of TB and drug resistance, both optimizes treatment and improves outcomes. In the current study, respiratory specimens were collected from 155 patients. Conventional susceptibility testing and MIC determination were performed for rifampicin (RIF) and isoniazid (INH). Genotype MTBDRplus assay, which is a molecular genetic assay based on the DNA-STRIP technology and specific gene sequencing with primers for rpoB, KatG, and mab-inhA genes were used to detect mutations associated with resistance to rifampicin and isoniazid. In comparison to other categories, most of rifampicin resistant (61.5%) and isoniazid resistant isolates (47.1%) were from patients relapsed in treatment. The genotypic profile (using Genotype MTBDRplus assay) of multi-drug resistant (MDR) isolates showed missing of katG wild type 1 (WT1) band and appearance of mutation band katG MUT2. For isoniazid mono-resistant isolates, 80% showed katG MUT1, 20% showed katG MUT1, and inhA MUT1, 20% showed only inhA MUT1. Accordingly, 100% of isoniazid resistant strains were detected by this assay. Out of 17 resistant strains, 16 had mutation bands for katG distinguished high resistance to isoniazid. The assay could clearly detect rifampicin resistance among 66.7% of MDR isolates that showed mutation band rpoB MUT3 while 33.3% of them were considered as unknown. One mono-resistant rifampicin isolate did not show rifampicin mutation bands by Genotype MTBDRplus assay, but it showed an unexpected mutation in Codon 531 of rpoB by DNA sequence analysis. Rifampicin resistance in this strain could be associated with a mutation in codon 531 of rpoB (based on molecular sequencing), and Genotype MTBDRplus assay could not detect the associated mutation. If the results of Genotype MTBDRplus assay and sequencing were combined, this strain shows hetero-resistance pattern. Gene sequencing of eight selected isolates, previously tested by Genotype MTBDRplus assay, could detect resistance mutations mainly in codon 315 (katG gene), position -15 in inhA promotes gene for isoniazid resistance and codon 531 (rpoB gene) for rifampicin resistance. Genotyping techniques allow distinguishing between recurrent cases of reinfection or reactivation and supports epidemiological studies.Keywords: M. tuberculosis, rpoB, KatG, inhA, genotype MTBDRplus
Procedia PDF Downloads 1581089 An Inverse Heat Transfer Algorithm for Predicting the Thermal Properties of Tumors during Cryosurgery
Authors: Mohamed Hafid, Marcel Lacroix
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This study aimed at developing an inverse heat transfer approach for predicting the time-varying freezing front and the temperature distribution of tumors during cryosurgery. Using a temperature probe pressed against the layer of tumor, the inverse approach is able to predict simultaneously the metabolic heat generation and the blood perfusion rate of the tumor. Once these parameters are predicted, the temperature-field and time-varying freezing fronts are determined with the direct model. The direct model rests on one-dimensional Pennes bioheat equation. The phase change problem is handled with the enthalpy method. The Levenberg-Marquardt Method (LMM) combined to the Broyden Method (BM) is used to solve the inverse model. The effect (a) of the thermal properties of the diseased tissues; (b) of the initial guesses for the unknown thermal properties; (c) of the data capture frequency; and (d) of the noise on the recorded temperatures is examined. It is shown that the proposed inverse approach remains accurate for all the cases investigated.Keywords: cryosurgery, inverse heat transfer, Levenberg-Marquardt method, thermal properties, Pennes model, enthalpy method
Procedia PDF Downloads 1931088 Non-Invasive Imaging of Tissue Using Near Infrared Radiations
Authors: Ashwani Kumar Aggarwal
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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 3091087 Fuzzy Multi-Objective Approach for Emergency Location Transportation Problem
Authors: Bidzina Matsaberidze, Anna Sikharulidze, Gia Sirbiladze, Bezhan Ghvaberidze
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In the modern world emergency management decision support systems are actively used by state organizations, which are interested in extreme and abnormal processes and provide optimal and safe management of supply needed for the civil and military facilities in geographical areas, affected by disasters, earthquakes, fires and other accidents, weapons of mass destruction, terrorist attacks, etc. Obviously, these kinds of extreme events cause significant losses and damages to the infrastructure. In such cases, usage of intelligent support technologies is very important for quick and optimal location-transportation of emergency service in order to avoid new losses caused by these events. Timely servicing from emergency service centers to the affected disaster regions (response phase) is a key task of the emergency management system. Scientific research of this field takes the important place in decision-making problems. Our goal was to create an expert knowledge-based intelligent support system, which will serve as an assistant tool to provide optimal solutions for the above-mentioned problem. The inputs to the mathematical model of the system are objective data, as well as expert evaluations. The outputs of the system are solutions for Fuzzy Multi-Objective Emergency Location-Transportation Problem (FMOELTP) for disasters’ regions. The development and testing of the Intelligent Support System were done on the example of an experimental disaster region (for some geographical zone of Georgia) which was generated using a simulation modeling. Four objectives are considered in our model. The first objective is to minimize an expectation of total transportation duration of needed products. The second objective is to minimize the total selection unreliability index of opened humanitarian aid distribution centers (HADCs). The third objective minimizes the number of agents needed to operate the opened HADCs. The fourth objective minimizes the non-covered demand for all demand points. Possibility chance constraints and objective constraints were constructed based on objective-subjective data. The FMOELTP was constructed in a static and fuzzy environment since the decisions to be made are taken immediately after the disaster (during few hours) with the information available at that moment. It is assumed that the requests for products are estimated by homeland security organizations, or their experts, based upon their experience and their evaluation of the disaster’s seriousness. Estimated transportation times are considered to take into account routing access difficulty of the region and the infrastructure conditions. We propose an epsilon-constraint method for finding the exact solutions for the problem. It is proved that this approach generates the exact Pareto front of the multi-objective location-transportation problem addressed. Sometimes for large dimensions of the problem, the exact method requires long computing times. Thus, we propose an approximate method that imposes a number of stopping criteria on the exact method. For large dimensions of the FMOELTP the Estimation of Distribution Algorithm’s (EDA) approach is developed.Keywords: epsilon-constraint method, estimation of distribution algorithm, fuzzy multi-objective combinatorial programming problem, fuzzy multi-objective emergency location/transportation problem
Procedia PDF Downloads 3121086 Modelling a Hospital as a Queueing Network: Analysis for Improving Performance
Authors: Emad Alenany, M. Adel El-Baz
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In this paper, the flow of different classes of patients into a hospital is modelled and analyzed by using the queueing network analyzer (QNA) algorithm and discrete event simulation. Input data for QNA are the rate and variability parameters of the arrival and service times in addition to the number of servers in each facility. Patient flows mostly match real flow for a hospital in Egypt. Based on the analysis of the waiting times, two approaches are suggested for improving performance: Separating patients into service groups, and adopting different service policies for sequencing patients through hospital units. The separation of a specific group of patients, with higher performance target, to be served separately from the rest of patients requiring lower performance target, requires the same capacity while improves performance for the selected group of patients with higher target. Besides, it is shown that adopting the shortest processing time and shortest remaining processing time service policies among other tested policies would results in, respectively, 11.47% and 13.75% reduction in average waiting time relative to first come first served policy.Keywords: queueing network, discrete-event simulation, health applications, SPT
Procedia PDF Downloads 1821085 Method of False Alarm Rate Control for Cyclic Redundancy Check-Aided List Decoding of Polar Codes
Authors: Dmitry Dikarev, Ajit Nimbalker, Alexei Davydov
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Polar coding is a novel example of error correcting codes, which can achieve Shannon limit at block length N→∞ with log-linear complexity. Active research is being carried to adopt this theoretical concept for using in practical applications such as 5th generation wireless communication systems. Cyclic redundancy check (CRC) error detection code is broadly used in conjunction with successive cancellation list (SCL) decoding algorithm to improve finite-length polar code performance. However, there are two issues: increase of code block payload overhead by CRC bits and decrease of CRC error-detection capability. This paper proposes a method to control CRC overhead and false alarm rate of polar decoding. As shown in the computer simulations results, the proposed method provides the ability to use any set of CRC polynomials with any list size while maintaining the desired level of false alarm rate. This level of flexibility allows using polar codes in 5G New Radio standard.Keywords: 5G New Radio, channel coding, cyclic redundancy check, list decoding, polar codes
Procedia PDF Downloads 2331084 Impact of CYP3A5 Polymorphism on Tacrolimus to Predict the Optimal Initial Dose Requirements in South Indian Renal Transplant Recipients
Authors: S. Sreeja, Radhakrishnan R. Nair, Noble Gracious, Sreeja S. Nair, M. Radhakrishna Pillai
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Background: Tacrolimus is a potent immunosuppressant clinically used for the long term treatment of antirejection of transplanted organs in liver and kidney transplant recipients though dose optimization is poorly managed. However, So far no study has been carried out on the South Indian kidney transplant patients. The objective of this study is to evaluate the potential influence of a functional polymorphism in CYP3A5*3 gene on tacrolimus physiological availability/dose ratio in South Indian renal transplant patients. Materials and Methods: Twenty five renal transplant recipients receiving tacrolimus were enrolled in this study. Their body weight, drug dosage, and therapeutic concentration of Tacrolimus were observed. All patients were on standard immunosuppressive regime of Tacrolimus-Mycophenolate mofetil along with steroids on a starting dose of Tac 0.1 mg/kg/day. CYP3A5 genotyping was performed by PCR followed with RFLP. Conformation of RFLP analysis and variation in the nucleotide sequence of CYP3A5*3 gene were determined by direct sequencing using a validated automated generic analyzer. Results: A significant association was found between tacrolimus per dose/kg/d and CYP3A5 gene (A6986G) polymorphism in the study population. The CYP3A5 *1/*1, *1/*3 and *3/*3 genotypes were detected in 5 (20 %), 5 (20 %) and 15 (60 %) of the 25 graft recipients, respectively. CYP3A5*3 genotypes were found to be a good predictor of tacrolimus Concentration/Dose ratio in kidney transplant recipients. Significantly higher L/D was observed among non-expressors 9.483 ng/mL(4.5- 14.1) as compared with the expressors 5.154 ng/mL (4.42-6.5 ) of CYP3A5. Acute rejection episodes were significantly higher for CYP3A5*1 homozygotes compared to patients with CYP3A5*1/*3 and CYP3A5*3/*3 genotypes (40 % versus 20 % and 13 %, respectively ). The dose normalized TAC concentration (ng/ml/mg/kg) was significantly lower in patients having CYP3A5*1/*3 polymorphism. Conclusion: This is the first study to extensively determine the effect of CYP3A5*3 genetic polymorphism on tacrolimus pharmacokinetics in South Indian renal transplant recipients and also shows that majority of our patients carry mutant allele A6986G in CYP3A5*3 gene. Identification of CYP3A5 polymorphism prior to transplantation could contribute to evaluate the appropriate initial dosage of tacrolimus for each patient.Keywords: kidney transplant patients, CYP3A5 genotype, tacrolimus, RFLP
Procedia PDF Downloads 2941083 Hate Speech Detection Using Machine Learning: A Survey
Authors: Edemealem Desalegn Kingawa, Kafte Tasew Timkete, Mekashaw Girmaw Abebe, Terefe Feyisa, Abiyot Bitew Mihretie, Senait Teklemarkos Haile
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Currently, hate speech is a growing challenge for society, individuals, policymakers, and researchers, as social media platforms make it easy to anonymously create and grow online friends and followers and provide an online forum for debate about specific issues of community life, culture, politics, and others. Despite this, research on identifying and detecting hate speech is not satisfactory performance, and this is why future research on this issue is constantly called for. This paper provides a systematic review of the literature in this field, with a focus on approaches like word embedding techniques, machine learning, deep learning technologies, hate speech terminology, and other state-of-the-art technologies with challenges. In this paper, we have made a systematic review of the last six years of literature from Research Gate and Google Scholar. Furthermore, limitations, along with algorithm selection and use challenges, data collection, and cleaning challenges, and future research directions, are discussed in detail.Keywords: Amharic hate speech, deep learning approach, hate speech detection review, Afaan Oromo hate speech detection
Procedia PDF Downloads 1661082 Role of Maternal Astaxanthin Supplementation on Brain Derived Neurotrophic Factor and Spatial Learning Behavior in Wistar Rat Offspring’s
Authors: K. M. Damodara Gowda
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Background: Maternal health and nutrition are considered as the predominant factors influencing brain functional development. If the mother is free of illness and genetic defects, maternal nutrition would be one of the most critical factors affecting the brain development. Calorie restrictions cause significant impairment in spatial learning ability and the levels of Brain Derived Neurotrophic Factor (BDNF) in rats. But, the mechanism by which the prenatal under-nutrition leads to impairment in brain learning and memory function is still unclear. In the present study, prenatal Astaxanthin supplementation on BDNF level, spatial learning and memory performance in the offspring’s of normal, calorie restricted and Astaxanthin supplemented rats was investigated. Methodology: The rats were administered with 6mg and 12 mg of astaxanthin /kg bw for 21 days following which acquisition and retention of spatial memory was tested in a partially-baited eight arm radial maze. The BDNF level in different regions of the brain (cerebral cortex, hippocampus and cerebellum) was estimated by ELISA method. Results: Calorie restricted animals treated with astaxanthin made significantly more correct choices (P < 0.05), and fewer reference memory errors (P < 0.05) on the tenth day of training compared to offsprings of calorie restricted animals. Calorie restricted animals treated with astaxanthin also made significantly higher correct choices (P < 0.001) than untreated calorie restricted animals in a retention test 10 days after the training period. The mean BDNF level in cerebral cortex, Hippocampus and cerebellum in Calorie restricted animals treated with astaxanthin didnot show significant variation from that of control animals. Conclusion: Findings of the study indicated that memory and learning was impaired in the offspring’s of calorie restricted rats which was effectively modulated by astaxanthin at the dosage of 12 mg/kg body weight. In the same way the BDNF level at cerebral cortex, Hippocampus and Cerebellum was also declined in the offspring’s of calorie restricted animals, which was also found to be effectively normalized by astaxanthin.Keywords: calorie restiction, learning, Memory, Cerebral cortex, Hippocampus, Cerebellum, BDNF, Astaxanthin
Procedia PDF Downloads 2301081 Therapeutic Effects of Guar Gum Nanoparticles in Oxazolone-Induced Atopic Dermatitis
Authors: Nandita Ghosh, Shinjini Mitra, Ena Ray Banerjee
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Atopic dermatitis (AD) is a chronic disease of the skin, involving itchy, reddish, and scaly lesions. It mainly affects children and has a high prevalence in developing countries. The AD may occur due to environmental or genetic factors. There is no permanent cure for the AD. Currently, all therapeutic strategies involve methods to simply alleviate the symptoms, and include lotions and corticosteroids, which have adverse effects. Use of phytochemicals and natural products has not yet been exploited fully. The particle used in this study is derived from Cyamopsis tetragonoloba, an edible polysaccharide with a galactomannan component. The mannose component mainly increases its specificity towards cellular uptake by mannose receptors, highly expressed by the macrophage. The aim of this study was to determine the therapeutic effect of guar gum nanoparticles (GN) in vitro and in vivo in the AD. To assess the wound healing capacity of the guar gum nanoparticle (GN), we first treated adherent NIH3T3 cells, with a scratch injury, with GN. GN successfully healed the wound caused by the scratch. In the in vivo experiment, Balb/c mice ear were topically treated with oxazolone (oxa) to induce AD and then were topically treated with GN. The ear thickness was increased significantly till day 28 on the treatment of Oxa. The GN application showed a significant decrease in the thickness as assessed on day 28. The total cell count of skin cells showed fold increase when treated with oxa, was again decreased on topical application of GN on the affected skin. The eosinophil count, as assessed by Giemsa staining was also increased when treated with oxa, GN application led to a significant decrease. The IgE level was assessed in the serum samples which showed that GN helped in restoring the alleviated IgE level. The T helper cells and the macrophage population showed increased percentage when treated with oxa, the GN application. This was examined by flow cytometry. The H&E staining of the ear tissue showed epidermal thickness in the oxa treated mice, GN application showed reduced cellular filtration followed by epidermal thickness. Thus our assays showed that GN was successful in alleviating the disease caused by Oxa when administered topically.Keywords: allergen, inflammation, nanodrug, wound
Procedia PDF Downloads 2391080 Study on Errors in Estimating the 3D Gaze Point for Different Pupil Sizes Using Eye Vergences
Authors: M. Pomianek, M. Piszczek, M. Maciejewski
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The binocular eye tracking technology is increasingly being used in industry, entertainment and marketing analysis. In the case of virtual reality, eye tracking systems are already the basis for user interaction with the environment. In such systems, the high accuracy of determining the user's eye fixation point is very important due to the specificity of the virtual reality head-mounted display (HMD). Often, however, there are unknown errors occurring in the used eye tracking technology, as well as those resulting from the positioning of the devices in relation to the user's eyes. However, can the virtual environment itself influence estimation errors? The paper presents mathematical analyses and empirical studies of the determination of the fixation point and errors resulting from the change in the size of the pupil in response to the intensity of the displayed scene. The article contains both static laboratory tests as well as on the real user. Based on the research results, optimization solutions were proposed that would reduce the errors of gaze estimation errors. Studies show that errors in estimating the fixation point of vision can be minimized both by improving the pupil positioning algorithm in the video image and by using more precise methods to calibrate the eye tracking system in three-dimensional space.Keywords: eye tracking, fixation point, pupil size, virtual reality
Procedia PDF Downloads 1291079 A Real Time Ultra-Wideband Location System for Smart Healthcare
Authors: Mingyang Sun, Guozheng Yan, Dasheng Liu, Lei Yang
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Driven by the demand of intelligent monitoring in rehabilitation centers or hospitals, a high accuracy real-time location system based on UWB (ultra-wideband) technology was proposed. The system measures precise location of a specific person, traces his movement and visualizes his trajectory on the screen for doctors or administrators. Therefore, doctors could view the position of the patient at any time and find them immediately and exactly when something emergent happens. In our design process, different algorithms were discussed, and their errors were analyzed. In addition, we discussed about a , simple but effective way of correcting the antenna delay error, which turned out to be effective. By choosing the best algorithm and correcting errors with corresponding methods, the system attained a good accuracy. Experiments indicated that the ranging error of the system is lower than 7 cm, the locating error is lower than 20 cm, and the refresh rate exceeds 5 times per second. In future works, by embedding the system in wearable IoT (Internet of Things) devices, it could provide not only physical parameters, but also the activity status of the patient, which would help doctors a lot in performing healthcare.Keywords: intelligent monitoring, ultra-wideband technology, real-time location, IoT devices, smart healthcare
Procedia PDF Downloads 1351078 Biological Control of Fusarium Crown and Root and Tomato (Solanum lycopersicum L.) Growth Promotion Using Endophytic Fungi from Withania somnifera L.
Authors: Nefzi Ahlem, Aydi Ben Abdallah Rania, Jabnoun-Khiareddine Hayfa, Ammar Nawaim, Mejda Daami-Remadi
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Fusarium Crown and Root Rot (FCRR) caused by Fusarium oxysporum f. sp. radicis-lycopersici (FORL) is a serious tomato (Solanum lycopersicum L.) disease in Tunisia. Its management is very difficult due to the long survival of its resting structures and to the luck of genetic resistance. In this work, we explored the wild Solanaceae species Withania somnifera, growing in the Tunisian Centre-East, as a potential source of biocontrol agents effective in FCRR suppression and tomato growth promotion. Seven fungal isolates were shown able to colonize tomato roots, crowns, and stems. Used as conidial suspensions or cell-free culture filtrates, all tested fungal treatments significantly enhanced tomato growth parameters by 21.5-90.3% over FORL-free control and by 27.6-93.5% over pathogen-inoculated control. All treatments significantly decreased the leaf and root damage index by 28.5-92.8 and the vascular browning extent 9.7-86.4% over FORL-inoculated and untreated control. The highest disease suppression ability (decrease by 86.4-92.8% in FCRR severity) over pathogen-inoculated control and by 81.3-88.8 over hymexazol-treated control) was expressed by I6 based treatments. This endophytic fungus was morphologically characterized and identified using rDNA sequencing gene as Fusarium sp. I6 (MG835371). This fungus was shown able to reduce FORL radial growth by 58.5–83.2% using its conidial suspension or cell-free culture filtrate. Fusarium sp. I6 showed chitinolytic, proteolytic and amylase activities. The current study clearly demonstrated that Fusarium sp. (I6) is a promising biocontrol candidate for suppressing FCRR severity and promoting tomato growth. Further investigations are required for elucidating its mechanism of action involved in disease suppression and plant growth promotion.Keywords: antifungal activity, associated fungi, Fusarium oxysporum f. sp. radicis-lycopersici, Withania somnifera, tomato growth
Procedia PDF Downloads 1401077 Neighborhood Graph-Optimized Preserving Discriminant Analysis for Image Feature Extraction
Authors: Xiaoheng Tan, Xianfang Li, Tan Guo, Yuchuan Liu, Zhijun Yang, Hongye Li, Kai Fu, Yufang Wu, Heling Gong
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The image data collected in reality often have high dimensions, and it contains noise and redundant information. Therefore, it is necessary to extract the compact feature expression of the original perceived image. In this process, effective use of prior knowledge such as data structure distribution and sample label is the key to enhance image feature discrimination and robustness. Based on the above considerations, this paper proposes a local preserving discriminant feature learning model based on graph optimization. The model has the following characteristics: (1) Locality preserving constraint can effectively excavate and preserve the local structural relationship between data. (2) The flexibility of graph learning can be improved by constructing a new local geometric structure graph using label information and the nearest neighbor threshold. (3) The L₂,₁ norm is used to redefine LDA, and the diagonal matrix is introduced as the scale factor of LDA, and the samples are selected, which improves the robustness of feature learning. The validity and robustness of the proposed algorithm are verified by experiments in two public image datasets.Keywords: feature extraction, graph optimization local preserving projection, linear discriminant analysis, L₂, ₁ norm
Procedia PDF Downloads 1451076 Reliability Analysis of Computer Centre at Yobe State University Using LRU Algorithm
Authors: V. V. Singh, Yusuf Ibrahim Gwanda, Rajesh Prasad
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In this paper, we focus on the reliability and performance analysis of Computer Centre (CC) at Yobe State University, Damaturu, Nigeria. The CC consists of three servers: one database mail server, one redundant and one for sharing with the client computers in the CC (called as a local server). Observing the different possibilities of the functioning of the CC, the analysis has been done to evaluate the various popular measures of reliability such as availability, reliability, mean time to failure (MTTF), profit analysis due to the operation of the system. The system can ultimately fail due to the failure of router, redundant server before repairing the mail server and switch failure. The system can also partially fail when a local server fails. The failed devices have restored according to Least Recently Used (LRU) techniques. The system can also fail entirely due to a cooling failure of the server, electricity failure or some natural calamity like earthquake, fire tsunami, etc. All the failure rates are assumed to be constant and follow exponential time distribution, while the repair follows two types of distributions: i.e. general and Gumbel-Hougaard family copula distribution.Keywords: reliability, availability Gumbel-Hougaard family copula, MTTF, internet data centre
Procedia PDF Downloads 5231075 Tape-Shaped Multiscale Fiducial Marker: A Design Prototype for Indoor Localization
Authors: Marcell Serra de Almeida Martins, Benedito de Souza Ribeiro Neto, Gerson Lima Serejo, Carlos Gustavo Resque Dos Santos
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Indoor positioning systems use sensors such as Bluetooth, ZigBee, and Wi-Fi, as well as cameras for image capture, which can be fixed or mobile. These computer vision-based positioning approaches are low-cost to implement, mainly when it uses a mobile camera. The present study aims to create a design of a fiducial marker for a low-cost indoor localization system. The marker is tape-shaped to perform a continuous reading employing two detection algorithms, one for greater distances and another for smaller distances. Therefore, the location service is always operational, even with variations in capture distance. A minimal localization and reading algorithm were implemented for the proposed marker design, aiming to validate it. The accuracy tests consider readings varying the capture distance between [0.5, 10] meters, comparing the proposed marker with others. The tests showed that the proposed marker has a broader capture range than the ArUco and QRCode, maintaining the same size. Therefore, reducing the visual pollution and maximizing the tracking since the ambient can be covered entirely.Keywords: multiscale recognition, indoor localization, tape-shaped marker, fiducial marker
Procedia PDF Downloads 1261074 On the Construction of Some Optimal Binary Linear Codes
Authors: Skezeer John B. Paz, Ederlina G. Nocon
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Finding an optimal binary linear code is a central problem in coding theory. A binary linear code C = [n, k, d] is called optimal if there is no linear code with higher minimum distance d given the length n and the dimension k. There are bounds giving limits for the minimum distance d of a linear code of fixed length n and dimension k. The lower bound which can be taken by construction process tells that there is a known linear code having this minimum distance. The upper bound is given by theoretic results such as Griesmer bound. One way to find an optimal binary linear code is to make the lower bound of d equal to its higher bound. That is, to construct a binary linear code which achieves the highest possible value of its minimum distance d, given n and k. Some optimal binary linear codes were presented by Andries Brouwer in his published table on bounds of the minimum distance d of binary linear codes for 1 ≤ n ≤ 256 and k ≤ n. This was further improved by Markus Grassl by giving a detailed construction process for each code exhibiting the lower bound. In this paper, we construct new optimal binary linear codes by using some construction processes on existing binary linear codes. Particularly, we developed an algorithm applied to the codes already constructed to extend the list of optimal binary linear codes up to 257 ≤ n ≤ 300 for k ≤ 7.Keywords: bounds of linear codes, Griesmer bound, construction of linear codes, optimal binary linear codes
Procedia PDF Downloads 7481073 Improving Cryptographically Generated Address Algorithm in IPv6 Secure Neighbor Discovery Protocol through Trust Management
Authors: M. Moslehpour, S. Khorsandi
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As transition to widespread use of IPv6 addresses has gained momentum, it has been shown to be vulnerable to certain security attacks such as those targeting Neighbor Discovery Protocol (NDP) which provides the address resolution functionality in IPv6. To protect this protocol, Secure Neighbor Discovery (SEND) is introduced. This protocol uses Cryptographically Generated Address (CGA) and asymmetric cryptography as a defense against threats on integrity and identity of NDP. Although SEND protects NDP against attacks, it is computationally intensive due to Hash2 condition in CGA. To improve the CGA computation speed, we parallelized CGA generation process and used the available resources in a trusted network. Furthermore, we focused on the influence of the existence of malicious nodes on the overall load of un-malicious ones in the network. According to the evaluation results, malicious nodes have adverse impacts on the average CGA generation time and on the average number of tries. We utilized a Trust Management that is capable of detecting and isolating the malicious node to remove possible incentives for malicious behavior. We have demonstrated the effectiveness of the Trust Management System in detecting the malicious nodes and hence improving the overall system performance.Keywords: CGA, ICMPv6, IPv6, malicious node, modifier, NDP, overall load, SEND, trust management
Procedia PDF Downloads 1791072 Steepest Descent Method with New Step Sizes
Authors: Bib Paruhum Silalahi, Djihad Wungguli, Sugi Guritman
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Steepest descent method is a simple gradient method for optimization. This method has a slow convergence in heading to the optimal solution, which occurs because of the zigzag form of the steps. Barzilai and Borwein modified this algorithm so that it performs well for problems with large dimensions. Barzilai and Borwein method results have sparked a lot of research on the method of steepest descent, including alternate minimization gradient method and Yuan method. Inspired by previous works, we modified the step size of the steepest descent method. We then compare the modification results against the Barzilai and Borwein method, alternate minimization gradient method and Yuan method for quadratic function cases in terms of the iterations number and the running time. The average results indicate that the steepest descent method with the new step sizes provide good results for small dimensions and able to compete with the results of Barzilai and Borwein method and the alternate minimization gradient method for large dimensions. The new step sizes have faster convergence compared to the other methods, especially for cases with large dimensions.Keywords: steepest descent, line search, iteration, running time, unconstrained optimization, convergence
Procedia PDF Downloads 5371071 Association between a Serotonin Re-Uptake Transporter Gene Polymorphism and Mucosal Serotonin Level in Women Patients with Irritable Bowel Syndrome and Healthy Control: A Pilot Study from Northern India
Authors: Sunil Kumar, Uday C. Ghoshal
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Background and aims: Serotonin (5-hydroxtryptamine, 5-HT) is an important factor in gut function, playing key roles in intestinal peristalsis and secretion, and in sensory signaling in the brain-gut axis. Removal from its sites of action is mediated by a specific protein called the serotonin reuptake transporter (SERT). Polymorphisms in the promoter region of the SERT gene have effects on transcriptional activity, resulting in altered 5-HT reuptake efficiency. Functional polymorphisms may underlie disturbance in gut function in individuals suffering with disorders such as irritable bowel syndrome (IBS). The aim of this study was to assess the potential association between SERT polymorphisms and the diarrhea predominant IBS (D-IBS) phenotype Subjects: A total of 36 northern Indian female patients and 55 female northern Indian healthy controls (HC) were subjected to genotyping. Methods: Leucocyte DNA of all subjects was analyzed by polymerase chain reaction based technologies for SERT polymorphisms, specifically the insertion/deletion polymorphism in the promoter (SERT-P). Statistical analysis was performed to assess association of SERT polymorphism allele with the D-IBS phenotype. Results: The frequency of distribution of SERT-P gene was comparable between female patients with IBS and HC (p = 0.086). However, frequency of SERT-P deletion/deletion genotype was significantly higher in female patients with D-IBS compared to C-IBS and A-IBS [17/19 (89.5%) vs. 4/12 (33.3%) vs. 1/5 (20%), p=0.001, respectively]. The mucosal level of serotonin was higher in D-IBS compared to C-IBS and A-IBS [Median, range (159.26, 98.78–212.1) vs. 110.4, 67.87–143.53 vs. 92.34, 78.8–166.3 pmol/mL, p=0.001, respectively]. The mucosal level of serotonin was higher in female patients with IBS with SERT-P deletion/deletion genotype compared deletion/insertion and insertion/insertion [157.65, 67.87–212.1 vs. 110.4, 78.1–143.32 vs. 100.5, 69.1–132.03 pmol/mL, p=0.001, respectively]. Patients with D-IBS with deletion/deletion genotype more often reported symptoms of abdominal pain, discomfort (p=0.025) and bloating (p=0.039). Symptoms development following lactose ingestion was strongly associated with D-IBS and SERT-P deletion/deletion genotype (p=0.004). Conclusions: Significant association was observed between D-IBS and the SERT-P deletion/deletion genotype, suggesting that the serotonin transporter is a potential candidate gene for D-IBS in women.Keywords: serotonin, SERT, inflammatory bowel disease, genetic polymorphism
Procedia PDF Downloads 3311070 Rare Diagnosis in Emergency Room: Moyamoya Disease
Authors: Ecem Deniz Kırkpantur, Ozge Ecmel Onur, Tuba Cimilli Ozturk, Ebru Unal Akoglu
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Moyamoya disease is a unique chronic progressive cerebrovascular disease characterized by bilateral stenosis or occlusion of the arteries around the circle of Willis with prominent arterial collateral circulation. The occurrence of Moyamoya disease is related to immune, genetic and other factors. There is no curative treatment for Moyamoya disease. Secondary prevention for patients with symptomatic Moyamoya disease is largely centered on surgical revascularization techniques. We present here a 62-year old male presented with headache and vision loss for 2 days. He was previously diagnosed with hypertension and glaucoma. On physical examination, left eye movements were restricted medially, both eyes were hyperemic and their movements were painful. Other neurological and physical examination were normal. His vital signs and laboratory results were within normal limits. Computed tomography (CT) showed dilated vascular structures around both lateral ventricles and atherosclerotic changes inside the walls of internal carotid artery (ICA). Magnetic resonance imaging (MRI) and angiography (MRA) revealed dilated venous vascular structures around lateral ventricles and hyper-intense gliosis in periventricular white matter. Ischemic gliosis around the lateral ventricles were present in the Digital Subtracted Angiography (DSA). After the neurology, ophthalmology and neurosurgery consultation, the patient was diagnosed with Moyamoya disease, pulse steroid therapy was started for vision loss, and super-selective DSA was planned for further investigation. Moyamoya disease is a rare condition, but it can be an important cause of stroke in both children and adults. It generally affects anterior circulation, but posterior cerebral circulation may also be affected, as well. In the differential diagnosis of acute vision loss, occipital stroke related to Moyamoya disease should be considered. Direct and indirect surgical revascularization surgeries may be used to effectively revascularize affected brain areas, and have been shown to reduce risk of stroke.Keywords: headache, Moyamoya disease, stroke, visual loss
Procedia PDF Downloads 2621069 Intelligent Rheumatoid Arthritis Identification System Based Image Processing and Neural Classifier
Authors: Abdulkader Helwan
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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 5271068 Incidence of Lymphoma and Gonorrhea Infection: A Retrospective Study
Authors: Diya Kohli, Amalia Ardeljan, Lexi Frankel, Jose Garcia, Lokesh Manjani, Omar Rashid
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Gonorrhea is the second most common sexually transmitted disease (STDs) in the United States of America. Gonorrhea affects the urethra, rectum, or throat and the cervix in females. Lymphoma is a cancer of the immune network called the lymphatic system that includes the lymph nodes/glands, spleen, thymus gland, and bone marrow. Lymphoma can affect many organs in the body. When a lymphocyte develops a genetic mutation, it signals other cells into rapid proliferation that causes many mutated lymphocytes. Multiple studies have explored the incidence of cancer in people infected with STDs such as Gonorrhea. For instance, the studies conducted by Wang Y-C and Co., as well as Caini, S and Co. established a direct co-relationship between Gonorrhea infection and incidence of prostate cancer. We hypothesize that Gonorrhea infection also increases the incidence of Lymphoma in patients. This research study aimed to evaluate the correlation between Gonorrhea infection and the incidence of Lymphoma. The data for the research was provided by a Health Insurance Portability and Accountability Act (HIPAA) compliant national database. This database was utilized to evaluate patients infected with Gonorrhea versus the ones who were not infected to establish a correlation with the prevalence of Lymphoma using ICD-10 and ICD-9 codes. Access to the database was granted by the Holy Cross Health, Fort Lauderdale for academic research. Standard statistical methods were applied throughout. Between January 2010 and December 2019, the query was analyzed and resulted in 254 and 808 patients in both the infected and control group, respectively. The two groups were matched by Age Range and CCI score. The incidence of Lymphoma was 0.998% (254 patients out of 25455) in the Gonorrhea group (patients infected with Gonorrhea that was Lymphoma Positive) compared to 3.174% and 808 patients in the control group (Patients negative for Gonorrhea but with Lymphoma). This was statistically significant by a p-value < 2.210-16 with an OR= 0.431 (95% CI 0.381-0.487). The patients were then matched by antibiotic treatment to avoid treatment bias. The incidence of Lymphoma was 1.215% (82 patients out of 6,748) in the Gonorrhea group compared to 2.949% (199 patients out of 6748) in the control group. This was statistically significant by a p-value <5.410-10 with an OR= 0.468 (95% CI 0.367-0.596). The study shows a statistically significant correlation between Gonorrhea and a reduced incidence of Lymphoma. Further evaluation is recommended to assess the potential of Gonorrhea in reducing Lymphoma.Keywords: gonorrhea, lymphoma, STDs, cancer, ICD
Procedia PDF Downloads 1881067 Evaluation of Cyclic Thermo-Mechanical Responses of an Industrial Gas Turbine Rotor
Authors: Y. Rae, A. Benaarbia, J. Hughes, Wei Sun
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This paper describes an elasto-visco-plastic computational modelling method which can be used to assess the cyclic plasticity responses of high temperature structures operating under thermo-mechanical loadings. The material constitutive equation used is an improved unified multi-axial Chaboche-Lemaitre model, which takes into account non-linear kinematic and isotropic hardening. The computational methodology is a three-dimensional framework following an implicit formulation and based on a radial return mapping algorithm. The associated user material (UMAT) code is developed and calibrated across isothermal hold-time low cycle fatigue tests for a typical turbine rotor steel for use in finite element (FE) implementation. The model is applied to a realistic industrial gas turbine rotor, where the study focuses its attention on the deformation heterogeneities and critical high stress areas within the rotor structure. The potential improvements of such FE visco-plastic approach are discussed. An integrated life assessment procedure based on R5 and visco-plasticity modelling, is also briefly addressed.Keywords: unified visco-plasticity, thermo-mechanical, turbine rotor, finite element modelling
Procedia PDF Downloads 1251066 Role of P53 Codon 72 Polymorphism and Mir-146a Rs2910164 Polymorphism in Cervical Cancer
Authors: Hossein Rassi, Marjan Moradi Fard, Masoud Houshmand
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Background: Cervical cancer is multistep disease that is thought to result from an interaction between genetic background and environmental factors. Human papillomavirus (HPV) infection is the leading risk factor for cervical intraepithelial neoplasia (CIN) and cervical cancer. In other hand, some of p53 and miRNA polymorphism may plays an important role in carcinogenesis. This study attempts to clarify the relation of p53 genotypes and miR-146a rs2910164 polymorphism in cervical lesions. Method: Forty two archival samples with cervical lesion retired from Khatam hospital and 40 sample from healthy persons used as control group. A simple and rapid method was used to detect the simultaneous amplification of the HPV consensus L1 region and HPV-16,-18, -11, -31, 33 and -35 along with the b-globin gene as an internal control. We use Multiplex PCR for detection of P53 and miR-146a rs2910164 genotypes in our lab. Finally, data analysis was performed using the 7 version of the Epi Info(TM) 2012 software and test chi-square(x2) for trend. Results: Cervix lesions were collected from 42 patients with Squamous metaplasia, cervical intraepithelial neoplasia, and cervical carcinoma. Successful DNA extraction was assessed by PCR amplification of b-actin gene (99bp). According to the results, p53 GG genotype and miR-146a rs2910164 CC genotype was significantly associated with increased risk of cervical lesions in the study population. In this study, we detected 13 HPV 18 from 42 cervical cancer. Conclusion: The connection between several SNP polymorphism and human virus papilloma in rare researches were seen. The reason of these differences in researches' findings can result in different kinds of races and geographic situations and also differences in life grooves in every region. The present study provided preliminary evidence that a p53 GG genotype and miR-146a rs2910164 CC genotype may effect cervical cancer risk in the study population, interacting synergistically with HPV 18 genotype. Our results demonstrate that the testing of p53 codon 72 polymorphism genotypes and miR-146a rs2910164 polymorphism genotypes in combination with HPV18 can serve as major risk factors in the early identification of cervical cancers. Furthermore, the results indicate the possibility of primary prevention of cervical cancer by vaccination against HPV18 in Iran.Keywords: cervical cancer, HPV18, p53 codon 72 polymorphism, miR-146a rs2910164 polymorphism
Procedia PDF Downloads 4521065 Optimal Scheduling of Load and Operational Strategy of a Load Aggregator to Maximize Profit with PEVs
Authors: Md. Shafiullah, Ali T. Al-Awami
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This project proposes optimal scheduling of imported power of a load aggregator with the utilization of EVs to maximize its profit. As with the increase of renewable energy resources, electricity price in competitive market becomes more uncertain and, on the other hand, with the penetration of renewable distributed generators in the distribution network the predicted load of a load aggregator also becomes uncertain in real time. Though there is uncertainties in both load and price, the use of EVs storage capacity can make the operation of load aggregator flexible. LA submits its offer to day-ahead market based on predicted loads and optimized use of its EVs to maximize its profit, as well as in real time operation it uses its energy storage capacity in such a way that it can maximize its profit. In this project, load aggregators profit maximization algorithm is formulated and the optimization problem is solved with the help of CVX. As in real time operation the forecasted loads differ from actual load, the mismatches are settled in real time balancing market. Simulation results compare the profit of a load aggregator with a hypothetical group of 1000 EVs and without EVs.Keywords: CVX, electricity market, load aggregator, load and price uncertainties, profit maximization, real time balancing operation
Procedia PDF Downloads 4101064 Introduction to Various Innovative Techniques Suggested for Seismic Hazard Assessment
Authors: Deepshikha Shukla, C. H. Solanki, Mayank K. Desai
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Amongst all the natural hazards, earthquakes have the potential for causing the greatest damages. Since the earthquake forces are random in nature and unpredictable, the quantification of the hazards becomes important in order to assess the hazards. The time and place of a future earthquake are both uncertain. Since earthquakes can neither be prevented nor be predicted, engineers have to design and construct in such a way, that the damage to life and property are minimized. Seismic hazard analysis plays an important role in earthquake design structures by providing a rational value of input parameter. In this paper, both mathematical, as well as computational methods adopted by researchers globally in the past five years, will be discussed. Some mathematical approaches involving the concepts of Poisson’s ratio, Convex Set Theory, Empirical Green’s Function, Bayesian probability estimation applied for seismic hazard and FOSM (first-order second-moment) algorithm methods will be discussed. Computational approaches and numerical model SSIFiBo developed in MATLAB to study dynamic soil-structure interaction problem is discussed in this paper. The GIS-based tool will also be discussed which is predominantly used in the assessment of seismic hazards.Keywords: computational methods, MATLAB, seismic hazard, seismic measurements
Procedia PDF Downloads 3321063 Quantum Decision Making with Small Sample for Network Monitoring and Control
Authors: Tatsuya Otoshi, Masayuki Murata
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With the development and diversification of applications on the Internet, applications that require high responsiveness, such as video streaming, are becoming mainstream. Application responsiveness is not only a matter of communication delay but also a matter of time required to grasp changes in network conditions. The tradeoff between accuracy and measurement time is a challenge in network control. We people make countless decisions all the time, and our decisions seem to resolve tradeoffs between time and accuracy. When making decisions, people are known to make appropriate choices based on relatively small samples. Although there have been various studies on models of human decision-making, a model that integrates various cognitive biases, called ”quantum decision-making,” has recently attracted much attention. However, the modeling of small samples has not been examined much so far. In this paper, we extend the model of quantum decision-making to model decision-making with a small sample. In the proposed model, the state is updated by value-based probability amplitude amplification. By analytically obtaining a lower bound on the number of samples required for decision-making, we show that decision-making with a small number of samples is feasible.Keywords: quantum decision making, small sample, MPEG-DASH, Grover's algorithm
Procedia PDF Downloads 721062 Adaptive Anchor Weighting for Improved Localization with Levenberg-Marquardt Optimization
Authors: Basak Can
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This paper introduces an iterative and weighted localization method that utilizes a unique cost function formulation to significantly enhance the performance of positioning systems. The system employs locators, such as Gateways (GWs), to estimate and track the position of an End Node (EN). Performance is evaluated relative to the number of locators, with known locations determined through calibration. Performance evaluation is presented utilizing low cost single-antenna Bluetooth Low Energy (BLE) devices. The proposed approach can be applied to alternative Internet of Things (IoT) modulation schemes, as well as Ultra WideBand (UWB) or millimeter-wave (mmWave) based devices. In non-line-of-sight (NLOS) scenarios, using four or eight locators yields a 95th percentile localization performance of 2.2 meters and 1.5 meters, respectively, in a 4,305 square feet indoor area with BLE 5.1 devices. This method outperforms conventional RSSI-based techniques, achieving a 51% improvement with four locators and a 52 % improvement with eight locators. Future work involves modeling interference impact and implementing data curation across multiple channels to mitigate such effects.Keywords: lateration, least squares, Levenberg-Marquardt algorithm, localization, path-loss, RMS error, RSSI, sensors, shadow fading, weighted localization
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