Miracle-dz/UniFAR-FTUs huggingface dataset:
PRELIMINARY ESTIMATION OF THE PROBABLE MAGNITUDE OF KOMÁROM 1763 EARTHQUAKE USING FRAGILITY FUNCTIONS

Pannonian Basin can be characterized as a moderate seismic region. One of the biggest known earthquakes in Hungary, which is located in the inner part of Pannonian Basin, occurred in Komárom in the 28 June of 1763. As result 91% buildings in Komárom were affected revealing damage states between light damage and total collapse. Surrounding cities were also affected as historical documental evidence supports. The earthquake was later characterized with uncertain magnitudes between 5.7 a 6.5, but the applied methods rely on the Modified Mercalli Intensity and then on empirical relationships to determine magnitude, completely disregarding the structural response analysis of real structures. Another estimation of the probable intensities of historical seismic events can be achieved if the behavior of real structures through dynamic structural analysis. The method exists and consists on modelling the structural damage due to the historical earthquake as a probabilistic event, where the relationship between the structural damage and ground motion intensity, magnitude and distance is represented by fragility functions. A version of this methodology is developed, validated and then applied for parametrical studies and preliminary estimations of the magnitude of the 1763 Komárom earthquake. To do so architectural archetypes are developed by combining structural seismic damage sources with historical surveying on historical buildings. A typical commoners’ house structural archetype is generated and modelled as 2D portal frame macromodels using OpenSees code and calibrated to simulate the in-plane shear behavior of historical adobe masonry infill walls. Incremental dynamic analysis is performed together with 30 site-specific ground motion records in order to generate analytical fragility functions for reported damage states. Historical damage reports are combined with structure specific probability-of-damage estimates and the sensitivity of the method is studied with plausible intervals of the damage estimates and different attenuation relationships. The posterior distribution of magnitude given a damage event is estimated using Bayes’ theorem. The formal framework for the use of prior distributions of distance and magnitude is presented for future developments. The framework of assumptions is tested in order to evaluate the relevance in reducing uncertainties as the calibration of the material and numerical models, material and geometric nonlinearities, the number and quality of structures falling into certain damage measures, and attenuation relations. A possible set of assumptions is interpreted from historical sources in order to assess the probable magnitude of the Komárom earthquake.
Correlation between Defect Density and Corrosion Parameter of Electrochemically Oxidized Aluminum

It has been recognized that a connection may exist between defects of oxide coating and its corrosion protection. Such a link has not been substantiated. We prepare two coatings of anodized aluminum oxide (AAO) and plasma electrolytic oxidation (PEO), and analyze them with Mott-Schottky plots and potentiodynamic polarization scans. The as-grown and annealed AAO coatings exhibit both p-type and n-type semiconductor behaviors. Polarization resistance of the AAO coating increases from (1.8 ± 1.7) × 108 to (4.3 ± 0.5) × 108 Ω·cm2, while corrosion current decreases from (6.1 ± 3.6) × 10−7 to (2.3 ± 0.9) × 10−7 A·cm−2, as annealing temperature increases from room temperature to 400 °C. The parameter analysis on AAO indicates a positive correlation between corrosion current and donor density, a negative correlation between polarization resistance and donor density. The attempt on correlating corrosion potential gives rise to considerable deviation from a linear fit. The results suggest protection of AAO hinges on its donor density, not acceptor. On the PEO coatings, only the n-type behavior is observed. Intriguingly, the donor density of PEO coating is influenced by the annealing temperature of its pre-anodized layer. The most resistant PEO coating, with pre-anodized and 400 °C annealed AAO, exhibits polarization resistance (2.1 ± 0.4) × 109 Ω·cm2 and corrosion current (1.7 ± 0.4) × 10−8 A·cm−2.
Performance Improvement of PV Systems’ Maximum Power Point Tracker Based on a Scanning PSO Particle Strategy

Partial shading of PV systems generates many peaks in the P–V curve. These peaks have one global peak (GP), the remaining being local peaks (LPs). Metaheuristic techniques such as PSO have proven superiority in capturing the GP and avoiding entrapment in an LP in comparison to conventional techniques. In case of partial shading conditions (PSC), the GP may change its position and value in the P–V curve and the PSO is unable to capture the GP unless they reinitialize. Reinitialization of PSO particles spends a long time for convergence; and it may cause premature convergence. This paper proposes a novel strategy for scanning the new position of the GP in case of PSC changes without a need for reinitialization. The proposed strategy sends a particle to the anticipated places of peaks to search for any peak with power greater than the current GP and when it locates this new GP it will move the PSO particles directly to the new GP. This strategy reduced the reinitialization time by 650% as compared to the time required for the random reinitialization of the conventional PSO technique. Moreover; this proposed strategy completely avoids the premature convergence associated with conventional PSO techniques.
ISSN 2320-5407 International Journal of Advanced Research (2015), Volume 3, Issue 2, 104-110

Fatima H. Abd Ali The present paper deals with the assessment of the concentrations and potential ecological risk of heavy metals in urban soil affected by various anthropogenic activities (Al-Karrada) within Baghdad city. The samples were subjected to HCl and HNO3 digestion, and an atomic absorption spectrophotometer was used to determine the concentrations of Cd, Cr, Cu, Ni, Pb and Zn.with the exception of Zn, all the soil samples displayed higher concentration than the calculated worldwide mean of unpolluted soil. Nemerow pollution index (16.33) felled in the seriously polluted domain with the soil environment quality classification of (Ps>3.0). The single potential ecological risk showed that soil contamination from Cd (672) had very high potential ecological risk, which translated into the high value of the comprehensive potential ecological risk value (720.63) in the study area.
Impact Of Transportation Barriers On High-Quality Anticoagulation Management In Underserved Patients

S AND SCIENTIFIC PRESENTATIONS (RECENT): 1. Patel R, Drozda K, Lee YM, Nutescu EA, Cavallari L. “Influence of cytochrome P4502C9 and vitamin k epoxide reductase complex subunit one variants on time to achieve first therapeutic international normalized ratio. ” Poster Presentation: 48 American Society of Health System Pharmacists Midyear Clinical Meeting. Orlando, FL, December 10, 2013. [Also presented at the UI Health Annual Quality Fair: University of Illinois at Chicago Hospital & Health Sciences System. Chicago, IL, November 8, 2013] 2. McDowell M, Patel R, Cavallari LH, Drozda K, Nutescu EA. “The impact of a pharmacist guided pharmacogenetics service on prediction of warfarin stable dose. ” Poster Presentation: 48 American Society of Health System Pharmacists Midyear Clinical Meeting. Orlando, FL, December 10, 2013. [Also presented at the UI Health Annual Quality Fair: University of Illinois at Chicago Hospital & Health Sciences System. Chicago, IL, November 8, 2013] 3. Duncan M, Bress A, Cavallari L, Nutescu EA, Drozda K, Galanter W. Clinical Decision Support for initial dosing of warfarin and promotion of pharmacogenetic testing. Poster Presentation: American Medical Informatics Association Annual Symposium. Washington, DC, November 16-20, 2013. 4. Bathija S, Walton S, Lau D, Galanter W, Schumock G, Nutescu EA. Patient outcomes with anticoagulation therapy after hip and knee replacement: comparison of two models of care. Poster Presentation: American College of Clinical Pharmacy Annual Meeting. Albuquerque, NM, October 13-16, 2013. Abstract published in: Pharmacotherapy 2013;33(10):e191/31E. 5. Manzoor B, Bautista A, Stamos T, Gao W, Nutescu EA. Outcomes of Systematic Anticoagulation Management in Pharmacist vs. Nurse Specialized Clinics. Poster Presentation: American College of Clinical Pharmacy Annual Meeting. Albuquerque, NM, October 13-16, 2013. Abstract published in: Pharmacotherapy 2013; 33(10):e229/157. 6. Labinov Y, DiDomenico R, Nutescu EA, Cavallari LH. Comparative accuracy of pharmacogenetic warfarin dosing algorithms and the warfarin dosing label plus clinical judgment. Poster Presentation: American College of Clinical Pharmacy Annual Meeting. Albuquerque, NM, October 13-16, 2013. Abstract published in: Pharmacotherapy 2013;33(10):e190/28.
A novel sensorless BLDC motor Drive based on the zero-cross point of the product of line voltages

This paper gives the analysis and development of a novel sensorless position sensing technique for six pulse Voltage Source Inverter (VSI) fed permanent magnet Brushless Direct Current (BLDC) motor. The proposed technique is based on the product of the line to line voltages. Commutation point of the VSI switch is achieved at difference of the line voltage zero. Proposed method for finding commutation point is speed independent, hence operation of this novel method good even at low speeds also. This proposed method requires voltage measurement only for implementation, no need of current measurements and derivative of current. This method has good performance from very low speed to high speed. Both experimental and simulation results show the validity of the novel proposed method.
Transformer Health Assessment Method Based on Loss Parameter Identification by Multivariate Linear Regression

In this paper, a state estimation method based on loss calculation is proposed, which reflects the change of transformer body parameters according to the loss and conducts health assessment. Based on the superposition theorem, the calculation formula of total loss of transformer considering harmonic loss is derived. Based on the actual experimental data, the mathematical model of the corresponding parameters is obtained by curve fitting method. The change mechanism is clarified and the accuracy of the calculation is verified. A method of parameter identification using multiple linear regression is proposed. Under the state of transformer operation, the parameters in the formula are calculated according to the actual operation data. The change of this parameter reflects the change of the health status of the transformer.
Efficient Traversability Mapping for Service Robots Using a Point-cloud Fast Filter

This paper proposes Point-cloud Fast Filter (PFF), an algorithm to process efficiently 3D data from point-cloud sensors in order to build traversability maps for service robots. Our method is intended to be integrated with a 2D mapping algorithm, enhancing 2D standard maps with enough traversability information for robot navigation in indoor structured environments. The method is agnostic to the 3D sensor or mapping algorithm used, and keeps computational requirements low. Thus, we enable middle-class computers and a wide variety of sensors to be employed for service robots, reducing the costs of the platform. We evaluate the performance of PFF with different 3D sensors on a real robot and its impact on mapping, comparing it with alternative 2D and 3D mapping approaches.
Design and Implementation of Automatic Welding Machine

In applications where heavy metal welding is performed, the short circuit welding current is very high. During these conditions, manual welding is difficult. Hence, using an automated welding system enhances the productivity and quality of welds, thus reducing dependency on skilled work force. In this manuscript one such mechanism of DC welding, where the welding electrode is automated with a voltage control algorithm is discussed. This algorithm is implemented by sensing the voltage across the electrodes and controls the welding action based on the logic implemented. Implementation of this automated system ensures, monitored time of contact between the job and electrode.
A Practical Estimation of Periodic Power Supply Induced Jitter for Clock Buffer Chains

This paper presents a simple but practically accurate analytical closed-form expression for estimation of periodical power supply induced jitter (PSIJ) in MOS clock buffer chains. The closed-form expression is algebraically simple requiring only a few circuit simulation results without the pre-knowledge of circuit SPICE parameters. The expression predicts MOS clock buffer’s period PSIJ and N-Cycle PSIJ. Compared to SPICE simulated jitter, the closed-form expression predicts PSIJ with a maximum +30% error, which is generally sufficient for early-stage clock-buffer jitter budgeting before circuit implementations. The expression can be hand calculated and is well suited for IC design and application engineers to quickly summarize jitter tolerances for clock distribution networks in high-speed PHYs such as DDRs and SERDESes.
Computational modeling of stigmatized behaviour in pro-vaccination and anti-vaccination discussions on social media

Much research has been done within the social sciences on the interpretation and influence of stigma on human behaviour and health, which result in out-of-group exclusion, distancing, cognitive separation, status loss, discrimination, in-group pressure, and often lead to disengagement, non-adherence to treatment plan, and prescriptions by the doctor. However, little work has been conducted on computational identification of stigma in general and in social media discourse in particular. In this paper, we develop the annotation scheme for stigma based on social science theories, and perform a corpus study on the data from Facebook groups on vaccination. The data from pro-vaccination and anti-vaccination discussion groups are annotated by trained annotators and by MTurk annotators. We analyze the annotations using LIWC (Linguistic Inquiry and Word Count) software and TF-IDF in order to identify differentiating features between stigmatizing vs. non-stigmatizing content. Our corpus study lays a valuable foundation in computational modeling of social stigma, as it can serve as validation/interpretation of the social science theories through the prism of laypeople understanding. The annotated corpora can be subsequently used for automatic stigma identification. Moreover, the annotation scheme can be applied to study stigma across different themes and diseases and can be utilized during public health informational campaigns and health interventions.
Classification of EEG-based Brain Waves for Motor Imagery using Support Vector Machine

Brain-computer interface (BCI) is a hardware and software communication system that allows controlling computers or external devices to utilize brain activity. BCI allows users to control computers or other devices using brain waves. The process of identifying patterns of brain activity depends on the classification algorithm. A portable BCI system classifiers need the ability to identify patterns obtained from electroencephalogram (EEG) channels. In this research, a reliable classification system was built using the Support Vector Machine (SVM) classification algorithm that are suitable for recognizing brain wave patterns. The SVM algorithm was implemented to identify five activity patterns from 4-channel EEG when performing different motor movements. The results show that SVM performance is reliable in recognizing and distinguishing those patterns based on the EEG’s gamma waves.
Real-Time Bidding with Soft Actor-Critic Reinforcement Learning in Display Advertising

The main task of advertising companies is to sell goods and services interesting to the user. Online auctions are the main mechanism for selecting ads to the user. Dynamic bidding allows advertiser to automatically calculate the bid that is profitable to set to maximize goals (for example, the number of clicks on an ad), depending on the user who sees the ad. In this case the advertiser must specify the budget of the ad and the optimization goal. During the advertising campaign the bid for each impression will be calculated by a special algorithm. In this paper, we propose a novel algorithm for calculating the dynamic bid for each impression of the ad in order to maximize the advertiser’s goals, which takes into account settings of the advertising campaign, budget, the ad lifetime and other parameters. This task is formulated as reinforcement learning problem, where states are the status of auction and parameters of the advertising campaign, the actions are bidding for each ad based on the input state. Every ad has an agent who observes the states all the time and calculates the bid for the impression. We evaluated the proposed model on real advertising campaigns in a large social network. Our method achieved average 26% improvement in comparison with the state-of-the-art approach.
An Overview on Design and Control Schemes of Microgrid

Generation of electricity using renewable energy sources helps in meeting the increased energy demand and also in protecting the environment from global warming and pollution as compared to energy generation using conventional energy sources. Microgrid plays a crucial role in integrating distributed generation with the utility grid. Microgrid can be viewed as a group of energy sources which are distributed across the consumers’ area, capable of connecting itself to the utility grid supplying power to the locality. This microgrid can work in either of the two modes: grid connected mode – where it is connected to the grid and supplies power to the load or islanded mode- where it is disconnected from the grid, and has to act independently. With invent in conversion technologies, microgrid uses more of renewable sources (PV, wind turbine, fuel cell etc.) as Distributed Generation (DG) units compared to conventional units like diesel and gas engines. It further requires energy storage units, usually batteries and super capacitors to store the energy since the renewable energy sources are intermittent in nature. The control of energy generation using these sources as well as coordination of these units with the entire system plays a crucial role in maintaining stability and reliable power supply. This paper presents the fundamentals of microgrid, types of microgrid and control schemes of a microgrid.
Computational Analysis of Structural Dynamics of EGFR and its Mutants

Non-small cell lung cancer (NSCLC) with activating epidermal growth factor receptor (EGFR) is a major cause of death worldwide. Tyrosine kinase inhibitors (TKIs) have been developed to target the EGFR, stop the downstream signaling and the tumor growth. Despite of initial good results, drug resistance is developed after one year due to a secondary mutation. The L858R, T790M mutation and their combination change the conformational redistribution of EGFR. To combat drug resistance caused by the T790M mutation, AZD9291 third generation drug was approved by the food and drug administration agency, FDA, USA. However, resistance to AZD9291 is developed due to C797S mutation. In this paper, we investigate the drug resistance due to these genomic variations. We perform molecular dynamics (MD) simulation for EGFR, EGFR with L858R single point mutation, EGFR with L858R and T790M double point mutation and EGFR with L858R, T790M and C797S triple point mutation. We apply principal component analysis PCA and clustering to the atomic trajectories of EGFR and its mutants and extract the dominant motions. The first PC captures 29.04%, 51.17% 53.79% and 51.67% variance in WT, L858R, T790M and C797S mutants, respectively. First 20 PCs are used to explain the dynamics of the system, that captures about 90% of the variance in the system. This shows that the mutation increases the variance which leads to structural and dynamical changes and can be one of the reasons for the drug resistance. Our results provide new insights to the conformational dynamics and structural changes in EGFR and its mutants, that can be helpful for understanding the drug resistance mechanism and designing future therapies for NSCLC patients.
Real-Time Traffic Light Management System with Manual Control

Congestion at road intersections is a widespread problem. Congestion is a result of improper management of traffic. To make this traffic management process less hectic and automated, Traffic Lights are used at intersections which are effective too. Various researches focus on making traffic lights more reliable and effective which include a) Survey System b) Induction Loops c) Proximity Sensors d) Image Classification. Every proposed technique computes the vehicle count using any technique and accordingly timing of lights is set. In this paper, a system has been proposed which primarily utilizes image classification and has three main parts: Vehicle Count using Image Classification, Decision making Algorithm and Manual Control. Real-time traffic is analysed using image processing and computed vehicle count is given as input to decision-making algorithm, in return algorithm sets the timing of green signal to a selected lane. The timing of signals can also be updated by utilising manual control unit of the system. The proposed system provides manual control to lights along with real-time analysis of traffic and performs 75% times better in comparison with the survey system.
OpenCL Implementation of Cannon’s Matrix Multiplication Algorithm on Intel Stratix 10 FPGAs

Stratix 10 FPGA cards have a good potential for the acceleration of HPC workloads since the Stratix 10 product line introduces devices with a large number of DSP and memory blocks. The high level synthesis of OpenCL codes can play a fundamental role for FPGAs in HPC, because it allows to implement different designs with lower development effort compared to hand optimized HDL. However, Stratix 10 cards are still hard to fully exploit using the Intel FPGA SDK for OpenCL. The implementation of designs with thousands of concurrent arithmetic operations often suffers from place and route problems that limit the maximum frequency or entirely prevent a successful synthesis. In order to overcome these issues for the implementation of the matrix multiplication, we formulate Cannon's matrix multiplication algorithm with regard to its efficient synthesis within the FPGA logic. We obtain a two-level block algorithm, where the lower level sub-matrices are multiplied using our Cannon's algorithm implementation. Following this design approach with multiple compute units, we are able to get maximum frequencies close to and above 300 MHz with high utilization of DSP and memory blocks. This allows for performance results above 1 TeraFLOPS.