Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical Methods for Pricing Multi-Asset Options

Numerical Methods for Pricing Multi-Asset Options Yuwei Chen Master of Science Graduate Department of Computer Science University of Toronto 2017 We consider the pricing of two-asset European and American options by numerical Partial Differential Equation (PDE) methods, and compare the results with certain analytical formulae. Two cases of options are tested: exchange option and spread option. For exchange options, the analytical formula considered is the (exact) Margrabe formula. For spread options, we consider Kirk’s formula and the formula by Li, Deng and Zhou. In pricing European two-asset options, the basic numerical PDE model is the two-dimensional Black-Scholes PDE. Different boundary conditions are considered, and the effect of them on the solution at various points of the grid is studied. Furthermore, various types of non-uniform grids are considered, aiming at reducing the error at certain areas of the grid. Moreover, the effect of the truncated domain on the PDE approximation is studied. We also discuss the effect of certain problem parameters, such as the length of maturity time, and the values of volatility and correlation, to the accuracy and convergence of the PDE approximations. The experiments indicate that the numerical PDE computed price and Greeks are second-order, for appropriately chosen grid discretizations. In the American pricing problem, the discrete penalty method is applied to the linear complementarity problem involving the two-dimensional Black-Scholes PDE and additional constraints. The convergence of the American Spread put option approximation computed with penalty iteration remains second-order, with the number of penalty iterations per timestep remaining small (2-3). We also consider an iterative method with preconditioning techniques for solving the arising large sparse linear system at each timestep, and show that this solution technique is asymptotically optimal.
Differential Compassing Helps Human&#8211;Robot Teams Navigate in Magnetically Disturbed Environments

In this paper, the authors describe a sensing method, called differential compassing, which can be applied to pursue leader/follower behaviors in the field of service robotics. Differential compassing is applied to integrate proximity/range sensing in robot systems, the operation of which can involve a hands-free interaction mode, where the robot (the follower) reacts to the movements of a walking user (the leader), so as to maintain close proximity to him. Differential compassing exploits two compasses, one of them on the leader and the other one on the follower. The simple idea behind this approach is that, if a magnetic disturbance affect the two compasses, one compass will be more influenced than the other, but heading errors may have similar magnitude
Traffic sign detection and recognition using neural networks and histogram based selection of segmentation method

Speed limit traffic sign detection is realized in two basic parts. The first part is the detection of traffic sign edge which includes the segmentation by means of a large set of different thresholds in different colour spaces. For each input image a convenient threshold and colour component from one of colour spaces is selected by the observation of the histogram of the whole image. Specially trained artificial neural network decides about the selection. In this way a system that is adaptable to different lighting conditions is obtained so that the segmentation is successfully carried out even in night lighting conditions where red colours prevail. After the segmentation in the first part the detection by means of the circular Hough transform is carried out in larger radius range and that is why the system is adaptable to the different sizes of the traffic sign. The second part is the recognition where the most important thing is the selection of real patterns and features. The first part, i.e. the detection module, results in one or two best graded circles in the segmented image of the reduced resolution. Now, the suitable frame is within the original image and it is reduced to a certain dimension and is transferred into the grey image. The system automatically prepares the inputs for NN in accordance with so obtained interior of the traffic sign. The method is experimentally verified using an image database of traffic signs. The initial results are encouraging.
Topology Control in Multiresolution Isosurface Extraction

Multiresolution modeling is a very important technique for interactive visualization of very large data sets. Multiresolution volume data structures allow the extraction of adaptively triangulated isosurfaces in large volume data sets at interactive frame rates, providing the user the ability to visualize the volume data in real-time. The isosurface is displayed at a coarse resolution for areas of low variance in the isovalue or for fast interaction, and at finer resolution for areas of high variability or detail inspections. Ideally, a coarse approximation of the isosurface has the same topological structure as in the highest resolution. Important topological properties such as the genus, or structure and number of connected components of an isosurface are often neglected in existing multiresolution isosurface extraction and rendering algorithms. This can result in sudden, and uncontrolled topological changes of the rendered isosurface whenever the global or local level-of-detail of the extracted isosurface changes. The scope of this paper is to propose an efficient technique which provides control over topological changes, in particular preservation of topolgical properties, in an interactive multiresolution isosurface extraction and rendering framework. We present two methods for topology preserving multiresolution isosurface extraction: the first is optimal in run-time and space cost, and the second is optimal with respect to the size of the extracted isosurface. Furthermore, we also present extensions of our method for controlled topology simplification.
Behavioral Inattention

Inattention is a central, unifying theme for much of behavioral economics. It permeates such disparate fields as microeconomics, macroeconomics, finance, public economics, and industrial organization. It enables us to think in a rather consistent way about behavioral biases, speculate about their origins, and trace out their implications for market outcomes.This survey first discusses the most basic models of attention, using a fairly unified framework. Then, it discusses the methods used to measure attention, which present a number of challenges on which a great deal of progress has been achieved, although much more work needs to be done. It then examines the various theories of attention, both behavioral and more Bayesian. It finally discusses some applications. For instance, inattention offers a way to write a behavioral version of basic microeconomics, as in consumer theory and Arrow-Debreu. A last section is devoted to open questions in the attention literature.This chapter is a pedagogical guide to the literature on attention. Derivations are self-contained. <br><br>Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at <a href="http://www.nber. org/papers/&#119;24096" TARGET="_blank">www.nber. org</a>. <br>
Response of Microbial Community to Long-Term Fertilization and Land Management in a Chinese Mollisol

Effects of long-term fertilization and land management on the microbial communities in a Chinese Mollisol were investigated by the determination of phospholipid fatty acids (PLFAs), soil microbial biomass C or N (Cmic or Nmic) and soil respiration. Compared to CK and NPK, farmyard manure (FYM) application and fallow constantly maintained high Cmic-to-Corg ratios, high Cmic (Nmic) and PLFAs contents, and low qCO2 value. Mere chemical NPK did not improve the nutrition status but promoted Corg loss and inhibited microbial growth. PCA of PLFAs showed that the microbial community structure in arable fields (with FYM or not) and fallow were significantly different from each other. The loading values for the individual PLFA showed that fungal PLFAs were mainly affected by fallow management, while most bacterial PLFAs were affected by FYM application. Keywords—phospholipid fatty acids (PLFAs); soil respiration; microbial biomass carbon or nitrogen (Cmic or Nmic); farmyard manure (FYM); chemical fertilizition; fallow; Mollisol
A Configurable Convolution Chip with Programmable Coefficients

This paper describes the architecture and implementation of a bit-level configurable convolver array. The systolic field supports configuration during operation in number of taps and coefficient word length. A chip has been designed in 1.5 ¿m CMOS using full custom design style which contains 112000 transistors on an active area of 45 mm2. The configurability consumes only 9% of that area. 50 MHz operating speed is expected from simulation. First test results have been obtained. An extension of the architecture for optimised calculation of transformations is also presented.
Detecting Emerging Space-Time Crime Patterns by Prospective STSS

Detecting crime patterns as they emerge in both space and time can enhance situational awareness amongst security agents and prevent epidemics of crimes in potential problematic areas (Neill and Gorr, 2007). Amongst others, space-time scan statistics (STSS) (Kulldorff et al. 2005) and space -time kernel (Nakaya and Yano, 2010) have been widely used in crime analysis. Stemmed on strong statistical theories, the STSS could provide the significance of the purported crime clusters, and this continues to gain huge popularities for crime hotspot analysis (LeBeau, 2000; Neill and Gorr, 2007; Uittenbogaard and Ceccato , 2011; Cheng and Williams, 2012; Gao et al. 2012). All these works applied STSS to crime clusters detection in a retrospective manner where all clusters within certain frame of time are detected. The approach was found to be very effective for historic analysis of crime outbreaks and near-repeat victimization. However, most STSS-based hotspot analyses were conducted at either region-wide and/or at monthly temporal granularity. This is not appropriate for city-based policing, which requires detailed spatial (local or micro) and temporal (daily) analysis. Few studies have actually attempted prospective detection of clusters with the aim of capturing their growth (emergence) in both space and time simultaneously so as to facilitate early prevention of the phenomenon in question. This was however seen only in epidemiology where outbreaks of diseases were detected employing this approach using the over-the-counter drug sales in Allegheny County from 2/13/04 2/12/05 (Neill et al., 2005). However, there is no quantitative evaluation of the significance of the emerging patterns and the rapidness of their emergence. Therefore, the aim of this research is to explore a prospective detection of emerging crime patterns at detailed spatial and temporal scales so as to facilitate proactive policing. In particular, we use the permutation STSS for the detailed crime emerging pattern detection and evaluate their significance as well as the rapidness of detection, by comparing the results with that of retrospective analysis.
An Improved Malicious Behaviour Detection Via k-Means and Decision Tree

Data Mining algorithm which is applied as an anomaly detection system has been considered as one of the essential techniques in malicious behaviour detection. Unfortunately, such detection system is known for its inclination in detecting a cyber-malicious activity more accurately (i.e. maximizing malicious and non-malicious behaviours detection) and has become a persistent limitation in the deployment of intrusion detection systems. Consequently, these constraints will affect a number of important performance factors such as the accuracy, detection rate and false alarms. In this research, KMDT proposed as an anomaly detection model that utilized k-means clustering and decision tree classifier to maximize the detection of malicious behaviours by scrutinizing packet headers. The k-means clustering employed for labelling and plots the whole behaviours into identical cluster, which characterized the behaviours into suspicious or non-suspicious composition. Subsequently, these dissimilar clustered behaviours are reordered within two classes of types such as malicious and non-malicious via decision tree classifier. KMDT is a profitable finding which improved the anomaly detection performance in identifying suspicious and non-suspicious behaviours as well as characterizes it into malicious and non-malicious behaviours more accurately. These criteria have been validated by the result from the experiments throughout banking system environment dataset 2016. KMDT have detected more malicious behaviours accurately as contrast to discrete and diversely combined methods.
TASIS: Trend analysis system for international standards

Recently, text mining has risen as an advanced technology that analyzes meaningful trends and topics in document collections. Despite its increasing use in various research areas, there have not been previous studies using document collections of international standards. In this paper, we propose the Trend Analysis System for International Standards (TASIS), which automatically performs topic modeling and trend analysis on document collections of the International Telecommunication Union Telecommunication Standardization Sector (ITU-T) Recommendations, based on a latent dirichlet allocation (LDA) algorithm. For providing Web services, the TASIS performs topic modeling by exploiting user-defined parameters, such as the number of topics and iterations, and the results show a list of the documents that each keyword in the topic is included in. The TASIS also describes a TreeMap with the size of the extracted topic as a graphical expression for easier understanding.
Autonomous takeoff and landing of a quadcopter

This paper presents an implementation method for an autonomous take-off and landing with a quadcopter on a stationary platform. The altitude measurement is improved with a Lidar, an inertial unit and a Kalman filter. Equations shown for a take-off and landing path use position and velocity commands. A non linear Backsteping robust control law is used. The entire system is programmed in C/C++ with ROS.
Effects of harmonics on distribution transformers

Proliferation of harmonics in power distribution systems, which are using increased nonlinear loads, have become a power quality problem for both customers and suppliers. The harmonic power losses not only cause an increase in operational costs but also create additional heating in power system components, which in turn will reduce their life expectancy. This happens especially in commercial buildings, where usage of nonlinear loads is very high. In general the cost of power quality and in particular the aging costs due to harmonic losses in transformers will increase since harmonics will affect all power system equipment. This study examines the effect of harmonic distortion on power transformers when supplying nonsinusoidal load currents. The Malaysian standards are used in the findings for comparison. For this research, the harmonic problem can be analysed with simulations, real measurements and assessments. The results show that an increase in the current harmonic distortion can increase transformer losses and decrease its life expectancy.
Phototrophic pigment diversity and picophytoplankton in permafrost thaw lakes

Abstract. Permafrost thaw lakes (thermokarst lakes) are widely distributed across the northern landscape, and are known to be biogeochemically active sites that emit large amounts of carbon to the atmosphere as CH4 and CO2. However, the abundance and composition of the photosynthetic communities that fix CO2 have been little explored in this ecosystem type. In order to identify the major groups of phototrophic organisms and their controlling variables, we sampled 12 permafrost thaw lakes along a permafrost degradation gradient in northern Quebec, Canada. Additional samples were taken from five rock-basin reference lakes in the region to determine if the thaw lakes differed in limnological properties and phototrophs. Phytoplankton community structure was determined by high-performance liquid chromatography analysis of their photoprotective and photosynthetic pigments, and autotrophic picoplankton concentrations were assessed by flow cytometry. One of the black-colored lakes located in a landscape of rapidly degrading palsas (permafrost mounds) was selected for high-throughput 18S rRNA sequencing to complement conclusions based on the pigment and cytometry analyses. The results showed that the limnological properties of the thaw lakes differed significantly from the reference lakes, and were more highly stratified. However, both waterbody types contained similarly diverse phytoplankton groups, with dominance of the pigment assemblages by fucoxanthin-containing taxa, as well as chlorophytes, cryptophytes and cyanobacteria. Chlorophyll a concentrations (Chl a) were correlated with total phosphorus (TP), and both were significantly higher in the thaw lakes (overall means of 3.3 µg Chl a L−1 and 34 µg TP L−1) relative to the reference lakes (2.0 µg Chl a L−1 and 8.2 µg TP L−1). Stepwise multiple regression of Chl a against the other algal pigments showed that it was largely a function of alloxanthin, fucoxanthin and Chl b (R2 = 0.85). The bottom waters of two of the thaw lakes also contained high concentrations of bacteriochlorophyll d, showing the presence of green photosynthetic sulphur bacteria. The molecular analyses indicated a relatively minor contribution of diatoms, while chrysophytes, dinoflagellates and chlorophytes were well represented; the heterotrophic eukaryote fraction was dominated by numerous ciliate taxa, and also included Heliozoa, Rhizaria, chytrids and flagellates. Autotrophic picoplankton occurred in biovolume concentrations up to 3.1 × 105 µm3 picocyanobacteria mL−1 and 1.9 × 106 µm3 picoeukaryotes mL−1, with large variations among lakes. Both groups of picophytoplankton were positively correlated with total phytoplankton abundance, as measured by Chl a; picocyanobacteria were inversely correlated with dissolved organic carbon, while picoeukaryotes were inversely correlated with conductivity. Despite their net heterotrophic character, subarctic thaw lakes are rich habitats for diverse phototrophic communities.
Project Touchport: A system consisting of a portable touchscreen to convert any computer screen to a touch sensitive screen and a wearable wireless device to remotely control your computer

Project Touchport is a complete system that makes the human-computer interface convenient, simple and wireless. The system consists of two modules, the touchscreen module and the remote module. The touchscreen module can be used to convert any regular computer screen to a touch sensitive screen, eliminating the need for a new touch sensitive device. The remote module is a wearable device that can be used to control the computer from a distance by means of gestures. The system employs the technique of Sweep Frequency Capacitive Sensing (SFCS) in which a range of frequencies is applied to an object and its capacitive response is measured.
Preliminary evaluation of the analgesic and anti-inflammatory effects of Tacca integrifolia in rodents

Summary. This is a preliminary investigation of the ethyl acetate extract of the leaf of Tacca integrifolia (TIE) for the analgesic activity using writhing response in mice, tail flick test in rats and for anti-inflammatory activity using ethyl phenyl propiolate (EPP)-induced ear edema, carrageenan- and arachidonic acid-induced hind paw edema, as well as cotton pellet-induced granuloma formation in rats. The results showed that TIE (200 mg/kg, PO) significantly inhibited pain caused by acetic acid injection (65.9%) but did not exhibit effect in tail flick test in rats. These findings suggest that analgesic mechanism of TIE may act via peripherally pathway. The study of anti-inflammatory effect showed that TIE significantly inhibited ear edema induced by EPP. TIE (200 mg/kg, PO) inhibited paw edema induced by carrageenan (55.5%) and arachidonic acid (48.6%) but had no effect on cotton-induced granuloma formation in rats. In conclusion, the ethyl acetate extract of leaf of T. integrifolia possessed anti-inflammatory activity in acute inflammation and analgesic activity. Industrial relevant. Plants of the genus Tacca have been reported to possess many activities such as analgesic, anti-inflammatory and, antipyretic activities. Many species have been used to treat high blood pressure, burn, gastric ulcer, and hepatitis. The scientific studies supporting the traditional uses of Tacca integrifolia for some of the alleged activities are still lacking. The screening test for analgesic and anti-inflammatory effect of the ethyl acetate extract of the leaf of Tacca integrifolia provides scientific data to confirm the potentials of T. integrifolia as an analgesic and anti-inflammatory medicinal plant. In addition, the outcomes may be useful to develop a new analgesic and anti-inflammatory drug in the future. Key words. Tacca integrifolia ; Taccaceae; ethyl acetate extract; analgesic activity; anti-inflammatory activity
Model predictive control with two-step horizon for three-level neutral-point clamped inverter

This paper presents a detailed description of Finite Control Set Model Predictive Control (FCS-MPC) applied to three-level neutral point clamped inverter (3L-NPC). The controller uses a model of the converter, DC link and load to calculate predictions of the future values of the load currents and DC-link capacitor voltages for all possible voltage vectors. The cost function is defined to minimize the error between the reference currents and predicted load currents, balance the DC-link capacitor voltage and reduce the switching frequency. The optimal switching state that minimizes the cost function is selected and applied to the converter. Furthermore, the quality of the current and voltage are improved by using a two prediction steps procedure. Simulation results for the one and two prediction step are presented and compared with linear current controller and space-vector modulation (PI-SVM). The obtained results show the better performances of the proposed control method.
Electron Ionization Cross Sections of PF 3 Molecule

Partial single and double differential cross sections with their sums through direct and dissociative ionization of PF3 have been evaluated at fixed electron energies 100 and 200 eV, by using modified Jain-Khare semi-empirical approach. To the best of my knowledge no other data of differential cross sections are available for the comparison. I have also calculated integral ionization cross sections with their ionization rate coefficients by using M-B distribution. No other data of partial ionization cross section are available till now. The sum/or total of evaluated partial cross sections reveal good agreement with available theoretical data.
Hough-based robust lane boundary detection for the omni-directional camera

An omni-directional sensor can obtain a 360 field of view via a single lens camera without utilizing a dead angle of view. This feature can be useful for autonomous vehicles especially in regard to lane detection. In this paper, we propose a robust lane detection algorithm which is based on segmented images produced by the Hough transform for an omni-directional camera.