Search results for: bayesian parameter identification

Authors: Nadeen Felemban, Hamsa Banjer, Rabaah Jaafari

Abstract:

One of the most common hazards in the pharmaceutical industry is the chemical hazard, which can cause harm or develop occupational health diseases/illnesses due to chronic exposures to hazardous substances. Therefore, a chemical agent management system is required, including hazard identification, risk assessment, controls for specific hazards and inspections, to keep your workplace healthy and safe. However, routine management monitoring is also required to verify the effectiveness of the control measures. Moreover, Betamethasone Valerate and Clobetasol Propionate are some of the APIs (Active Pharmaceutical Ingredients) with highly hazardous classification-Occupational Hazard Category (OHC 4), which requires a full containment (ECA-D) during handling to avoid chemical exposure. According to Safety Data Sheet, those chemicals are reproductive toxicants (reprotoxicant H360D), which may affect female workers’ health and cause fatal damage to an unborn child, or impair fertility. In this study, qualitative (chemical Risk assessment-qCRA) was conducted to assess the chemical exposure during handling of Betamethasone Valerate and Clobetasol Propionate in pharmaceutical laboratories. The outcomes of qCRA identified that there is a risk of potential chemical exposure (risk rating 8 Amber risk). Therefore, immediate actions were taken to ensure interim controls (according to the Hierarchy of controls) are in place and in use to minimize the risk of chemical exposure. No open handlings should be done out of the Steroid Glove Box Isolator (SGB) with the required Personal Protective Equipment (PPEs). The PPEs include coverall, nitrile hand gloves, safety shoes and powered air-purifying respirators (PAPR). Furthermore, a quantitative assessment (personal air sampling) was conducted to verify the effectiveness of the engineering controls (SGB Isolator) and to confirm if there is chemical exposure, as indicated earlier by qCRA. Three personal air samples were collected using an air sampling pump and filter (IOM2 filters, 25mm glass fiber media). The collected samples were analyzed by HPLC in the BV lab, and the measured concentrations were reported in (ug/m3) with reference to Occupation Exposure Limits, 8hr OELs (8hr TWA) for each analytic. The analytical results are needed in 8hr TWA (8hr Time-weighted Average) to be analyzed using Bayesian statistics (IHDataAnalyst). The results of the Bayesian Likelihood Graph indicate (category 0), which means Exposures are de "minimus," trivial, or non-existent Employees have little to no exposure. Also, these results indicate that the 3 samplings are representative samplings with very low variations (SD=0.0014). In conclusion, the engineering controls were effective in protecting the operators from such exposure. However, routine chemical monitoring is required every 3 years unless there is a change in the processor type of chemicals. Also, frequent management monitoring (daily, weekly, and monthly) is required to ensure the control measures are in place and in use. Furthermore, a Similar Exposure Group (SEG) was identified in this activity and included in the annual health surveillance for health monitoring.

Keywords: occupational health and safety, risk assessment, chemical exposure, hierarchy of control, reproductive

Procedia PDF Downloads 153

Authors: Alena Skalon, Jennifer L. Beaudry

Abstract:

Eyewitness misidentifications can sometimes lead to wrongful convictions of innocent people. This occurs in part because jurors tend to believe confident eyewitnesses even when the identification took place under suggestive conditions. Empirical research demonstrated that jurors are often unaware of the factors that can influence the reliability of eyewitness identification. Most common legal safeguards that are designed to educate jurors about eyewitness evidence are judicial instructions and expert testimony. To date, very few studies assessed the effectiveness of judicial instructions and most of them found that judicial instructions make jurors more skeptical of eyewitness evidence or do not have any effect on jurors’ judgments. Similar results were obtained for expert testimony. However, none of the previous studies focused on the ability of legal safeguards to improve jurors’ assessment of evidence obtained from suggestive identification procedures—this is one of the gaps addressed by this paper. Furthermore, only three studies investigated whether legal safeguards improve the ultimate accuracy of jurors’ judgments—that is, whether after listening to judicial instructions or expert testimony jurors can differentiate between accurate and inaccurate eyewitnesses. This presentation includes two studies. Both studies used genuine eyewitnesses (i.e., eyewitnesses who watched the crime) and manipulated the suggestiveness of identification procedures. The first study manipulated the presence of judicial instructions; the second study manipulated the presence of one of two types of expert testimony: a traditional, verbal expert testimony or expert testimony accompanied by visual aids. All participant watched a video-recording of an identification procedure and of an eyewitness testimony. The results indicated that neither judicial instructions nor expert testimony affected jurors’ judgments. However, consistent with the previous findings, when the identification procedure was non-suggestive, jurors believed accurate eyewitnesses more often than inaccurate eyewitnesses. When the procedure was suggestive, jurors believed accurate and inaccurate eyewitnesses at the same rate. The paper will discuss the implications of these studies and directions for future research.

Keywords: expert testimony, eyewitness evidence, judicial instructions, jurors’ decision making, legal safeguards

Procedia PDF Downloads 155

Authors: Jihoon Lim, Patrick Kirchen, Ryozo Nagamune

Abstract:

This paper proposes a linear parameter-varying (LPV) controller capable of reducing nitrogen oxide (NOx) emissions with low ammonia (NH3) slip downstream of selective catalytic reduction (SCR) systems. SCR systems are widely adopted in diesel engines due to high NOx conversion efficiency. However, the nonlinearity of the SCR system and sensor uncertainty result in a challenging control problem. In order to overcome the control challenges, an LPV controller is proposed based on gain-scheduling parameters, that is, exhaust gas temperature and exhaust gas flow rate. Based on experimentally obtained data under the non-road transient driving cycle (NRTC), the simulations firstly show that the proposed controller yields high NOx conversion efficiency with a desired low NH3 slip. The performance of the proposed LPV controller is then compared with other controllers, including a gain-scheduling PID controller and a sliding mode controller. Additionally, the robustness is also demonstrated using the uncertainties ranging from 10 to 30%. The results show that the proposed controller is robustly stable under uncertainties.

Keywords: diesel engine, gain-scheduling control, linear parameter-varying, selective catalytic reduction

Procedia PDF Downloads 128

Authors: Ahmad Rabby

Abstract:

The demographic trend analyses of Bombay-duck from time series catch data using CMSY and BSM for the first time in Bangladesh. During 2000-2018, CMSY indicates average lowest production in 2000 and highest in 2018. This has been used in the estimation of prior biomass by the default rules. Possible 31030 viable trajectories for 3422 r-k pairs were found by the CMSY analysis and the final estimates for intrinsic rate of population increase (r) was 1.19 year-1 with 95% CL= 0.957-1.48 year-1. The carrying capacity(k) of Bombay-duck was 283×103 tons with 95% CL=173×103 - 464×103 tons and MSY was 84.3×103tons year-1, 95% CL=49.1×103-145×103 tons year-1. Results from Bayesian state-space implementation of the Schaefer production model (BSM) using catch & CPUE data, found catchabilitiy coefficient(q) was 1.63 ×10-6 from lcl=1.27×10-6 to ucl=2.10×10-6 and r= 1.06 year-1 with 95% CL= 0.727 - 1.55 year-1, k was 226×103 tons with 95% CL=170×103-301×103 tons and MSY was 60×103 tons year-1 with 95% CL=49.9 ×103- 72.2 ×103 tons year-1. Results for Bombay-duck fishery management based on BSM assessment from time series catch data illustrated that, Fmsy=0.531 with 95% CL =0.364 - 0.775 (if B > 1/2 Bmsy then Fmsy =0.5r); Fmsy=0.531 with 95% CL =0.364-0.775 (r and Fmsy are linearly reduced if B < 1/2Bmsy). Biomass in 2018 was 110×103 tons with 2.5th to 97.5th percentile=82.3-155×103 tons. Relative biomass (B/Bmsy) in last year was 0.972 from 2.5th percentile to 97.5th percentile=0.728 -1.37. Fishing mortality in last year was 0.738 with 2.5th-97.5th percentile=0.525-1.37. Exploitation F/Fmsy was 1.39, from 2.5th to 97.5th percentile it was 0.988 -1.86. The biological reference points of B/BMSY was smaller than 1.0, while F/FMSY was higher than 1.0 revealed an over-exploitation of the fishery, indicating that more conservative management strategies are required for Bombay-duck fishery.

Keywords: biological reference points, catchability coefficient, carrying capacity, intrinsic rate of population increase

Procedia PDF Downloads 105

Authors: O. O. Fola-Matthews, O. O. Soyinka, D. N. Bitalo

Abstract:

Nigeria is one of the major shark fishing nations in Africa, but its fisheries managers still record catch data in aggregates ‘sharks’ with no species-specific details. This is because most of the shark specimens look identical in morphology, and field identification of some closely related species is tricky. This study uses DNA barcoding as a method to identify shark species from five different landing areas off the Nigerian Coast. 100 dorsal fins were sampled in order to provide a Chondrichthyan sequence that would be matched to reference specimens in a DNA barcode database

Keywords: BOLD, DNA barcoding, nigeria, sharks

Procedia PDF Downloads 140

Authors: Mallikarjun Warad, C. M. Kalleshwaraswamy, P. R. Shashank

Abstract:

Studies were conducted to record the occurrence of different species of hairy caterpillar on different host plants in and around Shivamogga, Karnataka, India. Twelve genera of hairy caterpillars belonging to Arctiinae and Lymantriinae were recorded on different host plants and reared to adults in laboratory on their respective hosts. The Porthesia sp. feed on castor, Creatonotus gangis on cocoa, Perina nuda on fig, Pericalia ricini on pigeon pea, Utetheisa pulchella on sunhemp and Euproctis sp. on paddy and banana. Illustrations of immature and adults were made to associate them. Along with this, light traps were also set during the rainy season, to capture adults of hairy caterpillars. An illustrated identification key was provided for easy and accurate identification of adult of hairy caterpillars based on their morphological (male genitalial) characters. The study through a light on the existence of sexual dimorphism, polyphagous nature and diapause are the major hindrance in taxonomic identification. Hence, attempts were made to address these issues in the study.

Keywords: Erebidae, hairy caterpillars, male genitalia, taxonomy

Procedia PDF Downloads 172

Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

Abstract:

Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies

Keywords: crop yield, roughness coefficient, PAR, WRM model

Procedia PDF Downloads 385

Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa

Abstract:

Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)

Procedia PDF Downloads 284

Authors: Camilla Elphick, Graham Hole, Samuel Hutton, Graham Pike

Abstract:

Pupil size has been found to change irrespective of luminosity, suggesting that it can be used to make inferences about cognitive processes, such as cognitive load. To see whether identifying a target requires a different cognitive load to rejecting distractors, the effect of viewing a target (compared with viewing distractors) on pupil size was investigated using a sequential video lineup procedure with two lineup sessions. Forty one participants were chosen randomly via the university. Pupil sizes were recorded when viewing pre target distractors and post target distractors and compared to pupil size when viewing the target. Overall, pupil size was significantly larger when viewing the target compared with viewing distractors. In the first session, pupil size changes were significantly different between participants who identified the target (Hits) and those who did not. Specifically, the pupil size of Hits reduced significantly after viewing the target (by 26%), suggesting that cognitive load reduced following identification. The pupil sizes of Misses (who made no identification) and False Alarms (who misidentified a distractor) did not reduce, suggesting that the cognitive load remained high in participants who failed to make the correct identification. In the second session, pupil sizes were smaller overall, suggesting that cognitive load was smaller in this session, and there was no significant difference between Hits, Misses and False Alarms. Furthermore, while the frequency of Hits increased, so did False Alarms. These two findings suggest that the benefits of including a second session remain uncertain, as the second session neither provided greater accuracy nor a reliable way to measure it. It is concluded that pupil size is a measure of face recognition strength in the first session of a target present lineup procedure. However, it is still not known whether cognitive load is an adequate explanation for this, or whether cognitive engagement might describe the effect more appropriately. If cognitive load and cognitive engagement can be teased apart with further investigation, this would have positive implications for understanding eyewitness identification. Nevertheless, this research has the potential to provide a tool for improving the reliability of lineup procedures.

Keywords: cognitive load, eyewitness identification, face recognition, pupillometry

Procedia PDF Downloads 378

Authors: Rim Chang Hyon, Song Hak Jin, Song Kwang Hyok, Jong Ki Hun

Abstract:

The calibration of the articulated arm coordinate measuring machine (AACMM) is key to improving calibration accuracy and saving calibration time. To reduce the time consumed for calibration, we should choose the proper calibration gauges and develop a reasonable calibration method. In addition, we should get the exact optimal solution by accurately removing the rough errors within the experimental data. In this paper, we present a calibration method of the portable coordinate measuring arm (PCMA) using the 1.2m long bar guage with cone-holes. First, we determine the locations of the bar gauge and establish an optimal objective function for identifying the structural parameter errors. Next, we make a mathematical model of the calibration algorithm and present a new mathematical method to remove the rough errors within calibration data. Finally, we find the optimal solution to identify the kinematic parameter errors by using Levenberg-Marquardt algorithm. The experimental results show that our calibration method is very effective in saving the calibration time and improving the calibration accuracy.

Keywords: AACMM, kinematic model, parameter identify, measurement accuracy, calibration

Procedia PDF Downloads 46

Authors: Heri Kuswanto, Philipp Sibbertsen, Irhamah

Abstract:

A Wald type test to distinguish between long memory and ESTAR nonlinearity has been developed. The test uses a directed-Wald statistic to overcome the problem of restricted parameters under the alternative. The test is derived from a model specification i.e. allows the transition parameter to appear as a nuisance parameter in the transition function. A simulation study has been conducted and it indicates that the approach leads a test with good size and power properties to distinguish between stationary long memory and ESTAR.

Keywords: directed-Wald test, ESTAR, long memory, distinguish

Procedia PDF Downloads 450

Authors: Jonghoon Chun, Insung Kim, Jonghyun Lim, Gun Ro

Abstract:

We believe that it is possible to provide a solution to reduce patient safety accidents by displaying correct medical records and prescription information through interactive patient identification. Our system is based on the use of smart bands worn by patients and these bands communicate with the hybrid gateways which understand both BLE and Wifi communication protocols. Through the convergence of low-power Bluetooth (BLE) and hybrid gateway technology, which is one of short-range wireless communication technologies, we implement ‘Intelligent Patient Identification and Location Tracking System’ to prevent medical malfunction frequently occurring in medical institutions. Based on big data and IOT technology using MongoDB, smart band (BLE, NFC function) and hybrid gateway, we develop a system to enable two-way communication between medical staff and hospitalized patients as well as to store locational information of the patients in minutes. Based on the precise information provided using big data systems, such as location tracking and movement of in-hospital patients wearing smart bands, our findings include the fact that a patient-specific location tracking algorithm can more efficiently operate HIS (Hospital Information System) and other related systems. Through the system, we can always correctly identify patients using identification tags. In addition, the system automatically determines whether the patient is a scheduled for medical service by the system in use at the medical institution, and displays the appropriateness of the medical treatment and the medical information (medical record and prescription information) on the screen and voice. This work was supported in part by the Korea Technology and Information Promotion Agency for SMEs (TIPA) grant funded by the Korean Small and Medium Business Administration (No. S2410390).

Keywords: BLE, hybrid gateway, patient identification, IoT, safety management, smart band

Procedia PDF Downloads 286

Authors: Moh'd Alodat

Abstract:

In this paper, we discuss the power function distribution and derive the maximum likelihood estimator of its parameter as well as the reliability parameter. We derive the large sample properties of the estimators based on the selective order statistic scheme. We conduct simulation studies to investigate the significance of the selective order statistic scheme in our setup and to compare the efficiency of the new proposed estimators.

Keywords: fisher information, maximum likelihood estimator, power function distribution, ranked set sampling, selective order statistics sampling

Procedia PDF Downloads 437

Authors: Isaac Quiros-Fernandez, Angel Cid-Arregui

Abstract:

Tumor-reactive T cell receptors (TCRs) are being subject of intense investigation since they offer great potential in adoptive cell therapies against cancer. However, the identification of tumor-specific TCRs has proven challenging, for instance, due to the limited expansion capacity of tumor-infiltrating T cells (TILs) and the extremely low frequencies of tumor-reactive T cells in the repertoire of patients and healthy donors. We have developed an approach for rapid identification and characterization of neoepitope-reactive TCRs from the T cell repertoire of healthy donors. CD8 T cells isolated from multiple donors are subjected to a first sorting step after staining with HLA multimers carrying the peptide of interest. The isolated cells are expanded for two weeks, after which a second sorting is performed using the same peptide-HLA multimers. The cells isolated in this way are then processed for single-cell sequencing of their TCR alpha and beta chains. Newly identified TCRs are cloned in appropriate expression vectors for functional analysis on Jurkat, NK92, and primary CD8 T cells and tumor cells expressing the appropriate antigen. We have identified TCRs specifically binding HLA-A2 presenting epitopes of tumor antigens, which are capable of inducing TCR-mediated cell activation and cytotoxicity in target cancer cell lines. This method allows the identification of tumor-reactive TCRs in about two to three weeks, starting from peripheral blood samples of readily available healthy donors.

Keywords: cancer, TCR, tumor antigens, immunotherapy

Procedia PDF Downloads 39

Authors: Bandari Shankar, Yohannes Yirga

Abstract:

In this paper, the problem of heat and mass transfer in unsteady MHD boundary-layer flow of nanofluids over stretching sheet with a non uniform heat source/sink is considered. The unsteadiness in the flow and temperature is caused by the time-dependent stretching velocity and surface temperature. The unsteady boundary layer equations are transformed to a system of non-linear ordinary differential equations and solved numerically using Keller box method. The velocity, temperature, and concentration profiles were obtained and utilized to compute the skin-friction coefficient, local Nusselt number, and local Sherwood number for different values of the governing parameters viz. solid volume fraction parameter, unsteadiness parameter, magnetic field parameter, Schmidt number, space-dependent and temperature-dependent parameters for heat source/sink. A comparison of the numerical results of the present study with previously published data revealed an excellent agreement

Keywords: unsteady, heat and mass transfer, manetohydrodynamics, nanofluid, non-uniform heat source/sink, stretching sheet

Procedia PDF Downloads 247

Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

Abstract:

Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.

Keywords: runoff, roughness coefficient, PAR, WRM model

Procedia PDF Downloads 345

Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

Abstract:

Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

Procedia PDF Downloads 68

Authors: Mostafa ‘Neo’ Mohsenvand, Mohammad Rasool Izadi, Pattie Maes

Abstract:

EEG-based biometrics (user identification) has been explored on small datasets of no more than 157 subjects. Here we show that the accuracy of modern supervised methods falls rapidly as the number of users increases to a few thousand. Moreover, supervised methods require a large amount of labeled data for training which limits their applications in real-world scenarios where acquiring data for training should not take more than a few minutes. We show that using contrastive learning for pre-training, it is possible to maintain high accuracy on a dataset of 2130 subjects while only using a fraction of labels. We compare 5 different self-supervised tasks for pre-training of the encoder where our proposed method achieves the accuracy of 96.4%, improving the baseline supervised models by 22.75% and the competing self-supervised model by 3.93%. We also study the effects of the length of the signal and the number of channels on the accuracy of the user-identification models. Our results reveal that signals from temporal and frontal channels contain more identifying features compared to other channels.

Keywords: brainprint, contrastive learning, electroencephalo-gram, self-supervised learning, user identification

Procedia PDF Downloads 134

Authors: Anupuma Raina, Ajay Parkash

Abstract:

In forensic investigation, DNA analysis helps in the identification of a particular individual under investigation. A set of Short Tandem Repeats loci are widely used for individualization at a molecular level in forensic testing. STRs with tetrameric repeats of DNA are highly polymorphic and widely used for forensic DNA analysis. Identification of an individual became challenging for forensic examiners after Hematopoietic Stem Cell Transplantation. HSCT is a well-accepted and life-saving treatment to treat malignant and nonmalignant diseases. It involves the administration of healthy donor stem cells to replace the patient’s own unhealthy stem cells. A successful HSCT results in complete donor-derived cells in a patient’s hematopoiesis and hence have the capability to change the genetic makeup of the patient. Although an individual who has undergone HSCT and then committed a crime is a very rare situation, but not impossible. Keeping such a situation in mind, various biological samples like blood, buccal swab, and hair follicle were collected and studied after a certain interval of time after HSCT. Blood was collected from both the patient and the donor before the transplant. The DNA profile of both was analyzed using a short tandem repeat kit for autosomal chromosomes. Among all exhibits studied, only hair follicles were found to be the most suitable biological exhibit, as no donor DNA profile was observed for up to 90 days of study.

Keywords: chimerism, HSCT, STRs analysis, forensic identification

Procedia PDF Downloads 45

Authors: Qamar J. A. Khan, Fatma Ahmed Al Kharousi

Abstract:

A prey-predator eco-epidemiological model is studied where transmission of the disease between infected and uninfected prey is nonlinear. The interaction of the predator with infected and uninfected prey species depend on their numerical superiority. Harvesting of both uninfected and infected prey is considered. Stability analysis is carried out for equilibrium values. Using the parameter µ, the death rate of infected prey as a bifurcation parameter it is shown that Hopf bifurcation could occur. The theoretical results are compared with numerical results for different set of parameters.

Keywords: bifurcation, optimal harvesting, predator, prey, stability

Procedia PDF Downloads 273

Authors: Lotfi O. Gargab, Ruichong R. Zhang

Abstract:

A wave-based framework is presented for modeling seismic motion in multistory buildings and using measured response for system identification which can be utilized to extract important information regarding structure integrity. With one pair of building response at two locations, a generalized model response is formulated based on wave propagation features and expressed as frequency and time response functions denoted, respectively, as GFRF and GIRF. In particular, GIRF is fundamental in tracking arrival times of impulsive wave motion initiated at response level which is dependent on local model properties. Matching model and measured-structure responses can help in identifying model parameters and infer building properties. To show the effectiveness of this approach, the Millikan Library in Pasadena, California is identified with recordings of the Yorba Linda earthquake of September 3, 2002.

Keywords: system identification, continuous-discrete mass modeling, damage detection, post-earthquake

Procedia PDF Downloads 349

Authors: Konstantin Nefedev, Petr Andriushchenko

Abstract:

Usually under the frustrated magnetics, it understands such materials, in which ones the interaction between located magnetic moments or spins has competing character, and can not to be satisfied simultaneously. The most well-known and simplest example of the frustrated system is antiferromagnetic Ising model on the triangle. Physically, the existence of frustrations means, that one cannot select all three pairs of spins anti-parallel in the basic unit of the triangle. In physics of the interacting particle systems, the vector models are used, which are constructed on the base of the pair-interaction law. Each pair interaction energy between one-component vectors can take two opposite in sign values, excluding the case of zero. Mathematically, the existence of frustrations in system means that it is impossible to have all negative energies of pair interactions in the Hamiltonian even in the ground state (lowest energy). In fact, the frustration is the excitation, which leaves in system, when thermodynamics does not work, i.e. at the temperature absolute zero. The origin of the frustration is the presence at least of one ''unsatisfied'' pair of interacted spins (magnetic moments). The minimal relative quantity of these excitations (relative quantity of frustrations in ground state) can be used as parameter of frustration. If the energy of the ground state is Egs, and summary energy of all energy of pair interactions taken with a positive sign is Emax, that proposed frustration parameter pf takes values from the interval [0,1] and it is defined as pf=(Egs+Emax)/2Emax. For antiferromagnetic Ising model on the triangle pf=1/3. We calculated the parameters of frustration in thermodynamic limit for different 2D periodical structures of Ising dipoles, which were on the ribs of the lattice and interact by means of the long-range dipolar interaction. For the honeycomb lattice pf=0.3415, triangular - pf=0.2468, kagome - pf=0.1644. All dependencies of frustration parameter from 1/N obey to the linear law. The given frustration parameter allows to consider the thermodynamics of all magnetic systems from united point of view and to compare the different lattice systems of interacting particle in the frame of vector models. This parameter can be the fundamental characteristic of frustrated systems. It has no dependence from temperature and thermodynamic states, in which ones the system can be found, such as spin ice, spin glass, spin liquid or even spin snow. It shows us the minimal relative quantity of excitations, which ones can exist in system at T=0.

Keywords: frustrations, parameter of order, statistical physics, magnetism

Procedia PDF Downloads 147

Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

Abstract:

Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

Procedia PDF Downloads 137

Authors: Ali Al-Ghalib, Fouad Mohammad

Abstract:

The identification of damage in reinforced concrete structures subjected to incremental cracking performance exploiting vibration data is recognized as a challenging topic in the published and heavily cited literature. Therefore, this paper attempts to shine light on the extent of dynamic methods when applied to reinforced concrete beams simulated with various scenarios of defects. For this purpose, three different reinforced concrete beams are tested through the course of the study. The three beams are loaded statically to failure in incremental successive load cycles and later rehabilitated. After each static load stage, the beams are tested under free-free support condition using experimental modal analysis. The beams were all of the same length and cross-sectional area (2.0x0.14x0.09)m, but they were different in concrete compressive strength and the type of damage presented. The experimental modal parameters as damage identification parameters were showed computationally expensive, time consuming and require substantial inputs and considerable expertise. Nonetheless, they were proved plausible for the condition monitoring of the current case study as well as structural changes in the course of progressive loads. It was accentuated that a satisfactory localization and quantification for structural changes (Level 2 and Level 3 of damage identification problem) can only be achieved reasonably through considering frequencies and mode shapes of a system in a proper analytical model. A convenient post analysis process for various datasets of vibration measurements for the three beams is conducted in order to extract, check and correlate the basic modal parameters; namely, natural frequency, modal damping and mode shapes. The results of the extracted modal parameters and their combination are utilized and discussed in this research as quantification parameters.

Keywords: experimental modal analysis, damage identification, structural health monitoring, reinforced concrete beam

Procedia PDF Downloads 239

Authors: Iis Diatin, Yani Hadiroseyani, Muhammad Mujahid, Ahmad Teduh, Juang R. Matangaran

Abstract:

One of silica quarry managed by a mining company is located at Sukabumi District of West Java Province Indonesia with an area of approximately 70 hectares. Since 2013 this company stopped the mining activities. The company tries to restore the ecosystem post-mining with rehabilitation activities such as reclamation and revegetation of their ex-mining area. After three years planting the area the trees grown well. Not only planting some tree species but also some cover crop has covered the soil surface. There are two settling ponds located in the middle of the ex-mining area. Those settling pond were built in order to prevent the effect of acid mine drainage. Acid mine drainage (AMD) or the acidic water is created when sulphide minerals are exposed to air and water and through a natural chemical reaction produce sulphuric acid. AMD is the main pollutant at the open pit mining. The objective of the research was to analyze the effect of revegetation on water quality change at the settling pond. The physical and chemical of water quality parameter were measured and analysed at site and at the laboratory. Physical parameter such as temperature, turbidity and total organic matter were analyse. Also heavy metal and some other chemical parameter such as dissolved oxygen, alkalinity, pH, total ammonia nitrogen, nitrate and nitrite were analysed. The result showed that the acidity of first settling pond was higher than that of the second settling pond. Both settling pond water’s contained heavy metal. The turbidity and total organic matter were the parameter of water quality which become better after revegetation.

Keywords: acid mine drainage, ex-mining area, revegetation, settling pond, water quality

Procedia PDF Downloads 280

Authors: Shumaila Ehtisham

Abstract:

In Statistical Distribution Theory, considering an additional parameter to classical distributions is a usual practice. In this study, a new distribution referred to as α-Power Pareto distribution is introduced by including an extra parameter. Several properties of the proposed distribution including explicit expressions for the moment generating function, mode, quantiles, entropies and order statistics are obtained. Unknown parameters have been estimated by using maximum likelihood estimation technique. Two real datasets have been considered to examine the usefulness of the proposed distribution. It has been observed that α-Power Pareto distribution outperforms while compared to different variants of Pareto distribution on the basis of model selection criteria.

Keywords: α-power transformation, maximum likelihood estimation, moment generating function, Pareto distribution

Procedia PDF Downloads 193

Authors: R. M. Chandima Ratnayake, Daniel Dyakov

Abstract:

Super steel materials play vital role in construction and fabrication of structural, piping and pipeline components. They enable to minimize the life cycle costs in assuring the integrity of onshore and offshore operating systems. In this context, Duplex stainless steel (DSS) material related welding on constructions and fabrications play a significant role in maintaining and assuring integrity at an optimal expenditure over the life cycle of production and process systems as well as associated structures. In DSS welding, the factors such as gap geometry, shielding gas supply rate, welding current, and type of the welding process play a vital role on the final joint performance. Hence, an experimental investigation has been performed using engineering robust design approach (ERDA) to investigate the optimal settings that generate optimal super DSS (i.e. UNS S32750) joint performance. This manuscript illustrates the mathematical approach and experimental design, optimal parameter settings and results of verification experiment.

Keywords: duplex stainless steel welding, engineering robust design, mathematical framework, optimal parameter settings

Procedia PDF Downloads 394

Authors: R. Biondi, G. Dys, G. Ferone, T. Renard, M. Zysman

Abstract:

This paper describes an automated implementable system for impulsive signals detection and recognition. The system uses a Digital Signal Processing device for the detection and identification process. Here the system analyses the signals in real time in order to produce a particular response if needed. The system analyses the signals in real time in order to produce a specific output if needed. Detection is achieved through normalizing the inputs and comparing the read signals to a dynamic threshold and thus avoiding detections linked to loud or fluctuating environing noise. Identification is done through neuronal network algorithms. As a setup our system can receive signals to “learn” certain patterns. Through “learning” the system can recognize signals faster, inducing flexibility to new patterns similar to those known. Sound is captured through a simple jack input, and could be changed for an enhanced recording surface such as a wide-area recorder. Furthermore a communication module can be added to the apparatus to send alerts to another interface if needed.

Keywords: sound detection, impulsive signal, background noise, neural network

Procedia PDF Downloads 293

Authors: Eva Savy, Anthony Ruiz

Abstract:

In extrusion blow molding, there is great variability in product quality due to the sensitivity of the machine settings. These variations lead to unnecessary rejects and loss of time. Yet production control is a major challenge for companies in this sector to remain competitive within their market. Current quality control methods only apply to finished products (vision control, leak test...). It has been shown that material melt temperature, blowing pressure, and ambient temperature have a significant impact on the variability of product quality. Since blowing is a key step in the process, we have studied this parameter in this paper. The objective is to determine if airflow analysis allows the identification of quality problems before the full completion of the manufacturing process. We conducted tests to determine if it was possible to identify a leakage defect and an obstructed defect, two common defects on products. The results showed that it was possible to identify a leakage defect by airflow analysis.

Keywords: extrusion blow molding, signal, sensor, defects, detection

Procedia PDF Downloads 110

Authors: Yaser Miaji, Mohammad Sabbagh

Abstract:

Radio Frequency Identification (RFID) is a technology which shares a similar concept with bar code. With RFID, the electromagnetic or electrostatic coupling in the RF portion of the electromagnetic spectrum is used to transmit signals. Supply chain management is aimed to keep going long-term performance of individual companies and the overall supply chain by maximizing customer satisfaction with minimum costs. One of the major issues in the supply chain management is product loss or shrinkage. In order to overcome this problem, this system which uses Radio Frequency Identification (RFID) technology will be able to RFID track and identify where losses are occurring and enable effective traceability. RFID brings a new dimension to supply chain management by providing a more efficient way of being able to identify and track items at the various stages throughout the supply chain. This system has been developed and tested to prove that RFID technology can be used to improve traceability in supply chain at low cost. Due to its simplicity in interface program and database management system using Visual Basic and MS Excel or MS Access the system can be more affordable and implemented even by small and medium scale industries.

Keywords: supply chain, RFID, tractability, radio frequency identification

Procedia PDF Downloads 461