Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis and Optimization of Ambiguity Function in Radar-Communication Integrated Systems Using MPSK-DSSS

With increasingly sophisticated electromagnetic environment of combat platforms, radar communication integration has attracted wide interests. In this letter, instead of designing a new integrated signal, we employ multiple-phase shift keying direct sequence spread spectrum (MPSK-DSSS) signal as radar communication integrated signal due to its advantage of outstanding correlation. On the one hand, the closed form expression of average ambiguity function is obtained, by which we can analyze the relationship between parameters of integrated signal and radar range resolution. On the other hand, to improve radar peak sidelobe level (PSL) influenced by random communication signals, we propose a joint optimization method based on sequence mapping at the transmitter and sidelobe suppression at the radar receiver. Simulation results show that the sidelobe levels of the optimized integrated signal is effectively suppressed at the cost of slight communication rate loss.
Dynamics of a Well-Diversified Equity Index

The paper derives a parsimonious model for the long-term dynamics of a well-diversified stock index, the S&P500. The index is modeled as growth optimal portfolio. Its normalized value evolves, in some market time, as a square root process. The derivative of market time is a linear function of the squared derivative of a smoothed proxy of the single driving Brownian motion. The model explains the feedback effects from index moves typically observed for monthly and daily S&P500 values. It is highly tractable, permits almost exact simulation and leads beyond classical assumptions in finance.
Research on identification of irrational fractional-order systems in frequency domain based on optimization algorithm

Fractional-order calculus can obtain better results than the integer-order in control theory, so it has become a research hotspot in recent years. However, the structure of the irrational fractional-order system is complex, so its theoretical analysis and controller design are more difficult. In this paper, a method based on convolution integral is proposed to obtain the frequency domain response of the irrational model. Combined with the optimization algorithm, the model parameters are identified. Moreover, the rationalization of the irrational model is realized, which facilitates the analysis and application design of this kind models. Finally, two examples are given to illustrate the effectiveness and feasibility of the method by identifying parameters and rationalization.
Pattern synthesis of the multimode orbital angular momentum beams based on the fruit fly optimization algorithm

The multimode orbital angular momentum (OAM) radio waves can be used to multiplex multiple transmission channels to increase the capacity of communication system without adding additional bandwidth. However, the divergence of the OAM beams and beam inconsistency escalate by increasing OAM mode number. Moreover, the worse sidelobe level (SLL) always appears along with a better convergent beam. In this article, the fruit fly optimization algorithm (FOA) is proposed to suppress the SLL in multimode OAM scenario. Based on the concentric circular array antenna (CCAA), the feeding amplitudes and the radii of the array are synthesized simultaneously to realize less than −30 dB SLL of the multimode OAM patterns. When the main lobes with different OAM modes steered to a uniform azimuth of θ = 0°, the SLLs of these OAM modes are also suppressed to less than −21 dB. The advantages of FOA used in the OAM pattern synthesis are verified by comparing it with the genetic algorithm (GA). The FOA‐based synthesis has a simpler implementation flow diagram which reduces the time of synthesis to 39.5% of GA.
Optimal two-stage designs in phase-II clinical trials.

BANERJEE, ANINDITA. Optimal Two-stage designs in Phase-II Clinical Trials. (Under the direction of Dr. Anastasios A. Tsiatis.) Two-stage designs have been widely used in phase II clinical trials. Such designs are desirable because they allow a decision to be made on whether a treatment is effective or not after the accumulation of the data at the end of each stage. Optimal fixed two-stage designs, where the sample size at each stage is fixed in advance, were proposed by Simon when the primary outcome is a binary response. We propose an adaptive two-stage design which allows the sample size at the second stage to depend on the results at the first stage. Using a Bayesian decision theoretic construct, we derive optimal adaptive two-stage designs. The optimality criterion is to minimize the expected sample size under the null hypothesis value. We further explore optimal adaptive designs that minimize the expected sample size at the alternative hypothesis, at a probability mid-point between the null and alternative hypotheses and a weighted combination of the null, alternative and mid-point value. We also construct an envelope function that gives the lowest expected sample size for any possible value of the response probability. The different designs are compared to Simon’s design as well as the envelope function. The designs that minimize the expected sample size at the mid-point between the null and alternative hypotheses and the design that minimizes a weighted average of the response probabilities are closer to the envelope function. Results show that these designs perform better across a range of the response probability values, and generally surpass Simon’s design. OPTIMAL TWO-STAGE DESIGNS IN PHASE-II CLINICAL TRIALS
IMAGE RETRIEVAL AND FACE RECOGNITION TECHNIQUES: LITERATURE SURVEY

Now days the process of image retrieval is widely used in may real life applications from large datasets. This process of retrieving the images from the big images dataset is called as content based image retrieval (CBIR). These CBIR techniques are adopted recently in many image based applications like fingerprint matching image retrieval, face based image retrieval, and attribute based image retrieval. The area of interest during this review paper is face based image retrieval. We have studied many methods presented recently for the face based image retrieval in which different face recognition algorithms were used. The goal of face based image retrieval is to display the face results those are exactly related to the query image of person. In this paper, first we present the review of CBIR methods, after that different face recognition methods discussed with their advantages and disadvantages.
Analysis of a rectangular supersonic multi-stream jet by LES and experiments

This paper focuses on the analysis of a rectangular supersonic multi-stream jet with aft deck using large eddy simulation (LES) and experimental data. Proper orthogonal decomposition (POD) and Dynamic mode decomposition (DMD) are applied to timeresolved schlieren, stereo particle image velocimetry (PIV), and LES data. The spatial eigenfunctions of the two datasets reveal similar trends in the flow field, where structures with high mean squared value propagate from the nozzle lip and mixing layer. In the schlieren, acoustic waves can also be seen radiating from the nozzle lip and edge of the aft deck. By combining the spatial eigenfunctions from the schlieren experiment and the time-dependent snapshots of the LES, low-dimensional time characteristics for the flow are reconstructed. Additionally, we compare the spatial modes from the PIV and LES to determine how well the coherent structures are being captured in the simulation. EXPERIMENTAL SETUP The experiments presented herein were conducted in a 7.9m × 6.1m× 4.3m anechoic chamber, acoustically treated with fiberglass wedges to achieve a cut-off frequency of∼150 Hz, seen in Figure 1. The facility houses an idealized three-stream nozzle with aft deck based on a variable-geometry engine cycle by Simmons (2009). The engine design assumes a fully mixed fan flow far upstream of the nozzle’s exit. In the context of this study, we view this as an idealized representation consisting of two canonical flows; a supersonic convergent-divergent (CD) jet and a sonic wall jet (representing the 3rd stream). The cross-sectional view of the nozzle can be seen in Figure 2. The main stream consists of a single expansion ramp nozzle (SERN), referred to as the bulk flow and containing the core and fan flow. The wall jet (3rd stream) is a convergent only variable bypass that enters the bulk flow in the CD nozzle’s divergent section. The designed operating condition of the main jet is an x y
Estimation of Hedging Effectiveness Using Variance Reduction and Risk-return Approaches:Evidence From National Stock Exchange of India

Present study estimates the hedging effectiveness by applying variance-reduction framework and risk-return framework using near month contracts of three benchmark indices (NIFTY50, NIFTYIT, and BANKNIFTY) traded at National Stock Exchange of India (NSE) for the sample period from June 2000 to March 31, 2017 by using nine optimal hedge ratio models. Out of these nine models, six are constant hedging models and three are time-varying hedging models. The study finds that using variance-reduction framework, highest hedging effectiveness is achieved using Ordinary Least Square model; whereas, 1:1 naive hedge ratio gives lowest hedging effectiveness. On the other hand, when hedging effectiveness is estimated in a risk-return framework, naive hedge ratio gives highest hedging effectiveness; whereas, OLS gives the least estimate. Secondly, the coefficients of both optimal hedge ratio as well as hedging effectiveness have increased during post-crisis period implying an increase in the cost of hedging. These findings suggests that conventional hedging models are more efficient than highly complicated time-varying hedging models for estimating optimal hedge ratio, these findings are consistent with the findings of Lien (2005), Bhaduri and Durai (2007), Bhargava (2007), Mandal (2011), Wang et al. (2015).
Optimal Control Design of Active Suspension System Based on Quarter Car Model

The optimal control design of the ground-vehicle active suspension system is presented. The active suspension system is to improve the vehicle ride comfort by isolating vibrations induced by the road profile and vehicle velocity. The vehicle suspension system is approached by a quarter car model. Dynamic equations of the system are derived by applying Newton’s second law. The control law of the active suspension system is designed using linear quadratic regulator (LQR) method. Performance evaluation is done by benchmarking the active suspension system to a passive suspension system. Both suspension systems are simulated in computer. The simulation results show that the active suspension system significantly improves the vehicle ride comfort of the passive suspension system by reducing 50.37% RMS of vertical displacement, 45.29% RMS of vertical velocity, and 1.77% RMS of vertical acceleration.
Relationship of Mindfulness and Cognitive Defusion to Burnout, Openness to Change and Adaptive Performance with Mediating role of Psychological Flexibility: A Case Study of Iran South Railway Company

The purpose of this study was to design and test a model of the relationship of mindfulness and cognitive defusion to burnout, openness to change, and adaptive performance, considering the role of psychological flexibility. Participants consisted of 220 employees (186 men and 34 women) from Iran South Railway Company who was selected by stratified random sampling method. The instruments were acceptance and action questionnaire (Hayes et al., 2004), Mindful attention and awareness scale (Brown and Ryan, 2003), Openness to change questionnaire (Metselaar, 1997; Rossel, 2010), Adaptive Performance Questionnaire (Charbonnierâ€“Voirin et al., 2010), Burnout Questionnaire (Maslach, 1981), and Cognitive Fusion Questionnaire (Gillanders et al., 2014). The proposed model was tested through structural equation modeling. Findings showed that the proposed model was fitted to the data. Better fitness was found through the removal of two non-significant paths and making correlation between two errors. The results indicated that psychological flexibility had a meditating role between mindfulness and cognitive defusion with adaptive performance, openness to change and burnout. Therefore, mindfulness training and acceptance and commitment training programs can be a good way to increase adaptive adaptation and greater acceptance of employees against organizational changes and, as well as reducing job burnout in the workplace. Finally, research findings were discussed based on acceptance and commitment therapy.
Plant Leaf Image Reconstruction Based on Point Cloud Characteristics

We present a method of leaf image reconstruction for plants whose midribs are close to straight. First, tangerine leaves are used as an example to illustrate the geometric and leaf-shape features of such leaves and suggest an extraction method using principal component analysis. Hence, this method was used to extract the geometric features, and additional methods such as coordinate conversion, mathematical morphology, and scan line analysis were applied to extract the leaf shape features. Then, based on these leaf shape features, a Bezier deformation function of the tangerine leaf edges and their curved Bezier deformation function in the normal vector direction were employed to obtain a parametric equation of the leaves according to their rectangular deformation. Finally, a simple illumination model for the leaves is presented. The reconstruction results show that the method is highly efficient and geometrically realistic. These results will be useful for the further study of plant leaf image reconstruction.
Detecting Covariate Shift with Black Box Predictors

Many Machine Learning algorithms aiming at classifying signals/images $X$ among a number of discrete labels $Y$ involve training instances, from which the predictor $P_{Y\vert X}$ is extracted according to the data distribution $P_{X\vert Y}$. This predictor is later used to predict the appropriate label for other instances of $X$ that are hence assumed to be drawn from the same distribution. This is a fundamental requirement for many realworld applications, therefore it is of great importance to monitor the reliability of the classification provided by the algorithm based on the learned distributions, when the test set statistics differ from the training set ones. This paper makes a step in that direction by proposing a Black Box Shift Detector of the data evolution (covariate shift). ‘Black Box’ here means that it does not require any knowledge of the predictor's architecture. Experiments demonstrate accurate detection on different high-dimensional datasets of natural images.
Vowel-Plosive of English Word Recognition using HMM

this paper discusses a speech recognition based on spoken English words formed by vowel, diphthong and plosive and it has been developed and experimented for single speaker. The success rate of recognition of individually uttered words in experiments is excellent and has reached about 98.86 %. The miss rate of about 1.14% was almost only because of false acceptance. In phonemes classification on an average we have reached 85% and miss classification rate was 15%. We have successfully tested all the words formed by vowel followed by vowel-plosive or plosive-vowels or diphthong- plosive and reached high success rate in recognition of the words. All computations are performed in MATLAB and PRAAT software.
Scheduling Harvard SEAS Courses with Simulated Annealing

The timetabling problem, or the task of generating a working schedule, is a multidimensional combinatorial optimization problem and is therefore very difficult to solve via heuristics or IP for large problems of interest, such as scheduling the courses at a university. In this work, our primary objective is to create a feasible schedule for a full semester of course at the School of Engineering and Applied Sciences (SEAS) at Harvard University. Though this is a medium-to-small sized problem within the larger task of scheduling an entire semester of courses for the whole university, it is a good training and reconnaissance for what a really large problem will require. Using real data of courses to be scheduled, professors attributed to those courses, rooms available, time slots, and room capacities as fixed hard facts, we solved the problem using a simulated annealing (SA) approach under various parameter conditions. Namely, we were interested in comparing various cooling schemes and compare with results obtained in [1].
Mobile Edge Computing: A Taxonomy

Mobile Edge Computing proposes co-locating computing and storage resources at base stations of cellular networks. It is seen as a promising technique to alleviate utilization of the mobile core and to reduce latency for mobile end users. Due to the fact that Mobile Edge Computing is a novel approach not yet deployed in real-life networks, recent work discusses merely general and non-technical ideas and concepts. This paper introduces a taxonomy for Mobile Edge Computing applications and analyzes chances and limitations from a technical point of view. Application types which profit from edge deployment are identified and discussed. Furthermore, these applications are systematically classified based on technical metrics.
An Efficient Lossless Medical Image Compression Method Based on Adaptive Prediction

With the rapid increase of digitized medical image and wide application of PACS, efficient lossless medical image compression method has been highly desired.In this paper,a lossless compression method ,based on adaptive prediction,is presented.This method uses neural network model to modify the prediction weight.As a result,the algorithm can remove the redundancy of X ray medical images adaptively.In addition,it can simultaneously exploit the spatial and spectral correlation of colored medical images.Experimental results have proven the effectiveness and efficiency of this algorithm.
Wideband High-Gain Circularly Polarized Antenna Using Artificial Anisotropic Polarizer

A novel wideband high-gain circularly polarized (CP) antenna is proposed and investigated for the 60 GHz high-throughput communication and the 77 GHz automobile radar system. The design consists of a rectangular horn, a hyperbolic lens, and an artificial anisotropic polarizer. To minimize the thickness of the polarizer, the properties of the artificial anisotropic material (AAM) for generating CP wave are discussed analytically. Minimal polarizer thickness and the corresponding component ratio are provided mathematically. In comparison with other approaches, the proposed design achieves a relatively high-gain and wideband performance with a minimal thickness. The antenna exhibits a wide impedance bandwidth of more than 39% (VSWR < 2) from 55 to 82 GHz and a wide axial ratio (AR) bandwidth of more than 32% (AR < 3 dB) from 56 to 77 GHz. The average gain is 17 dBic. Good unidirectional radiation characteristics are achieved with low fabrication cost. In addition, the off-body lens and the polarizer could be directly migrated to other radiating sources with the concrete analytical guidance for polarizer design.
Reliability Estimation from Left-Truncated and Right-Censored Data Using Splines

: Reliability data are often left truncated and right censored, because the data-collection process usually starts much later than the installation of the ﬁrst product unit, and some units are still in service at the end of the data collection. The truncation introduces a sampling bias, making analyses of the lifetime data complicated. This study develops a nonparametric likelihood-based estimation procedure for left-truncated and right-censored data using B -splines. In terms of small-sample performance and large-sample eﬃciencies, the proposed spline-based estimators for the reliability function are shown to be more eﬃcient than the ex-isting nonparametric estimators. We further consider nonparametric two-sample tests for left-truncated and right-censored data. The new class of tests is useful for comparing the reliability of similar products. The test statistics are based on the cumulative weighted diﬀerences between the two estimated failure rates. Asymptotic distributions of the proposed statistics are derived and their ﬁnite-sample properties are evaluated using Monte Carlo simulations. The performance of the proposed test statistic is compared with that of the weighted Kaplan–Meier statistic. Lastly, a real-life example of high-voltage power transformers is used to illustrate the proposed method.
The Hyperspectral Operational Support Tool (HOST) User Interface Evaluation: Preliminary Heuristic Analysis Results

Abstract : This document presents a preliminary heuristic evaluation of the Hyperspectral Operational Support Tool (HOST) v3.0a user interface, which was designed for hyperspectral imagery analysts. Results of the interface evaluation recommend two main problem areas to address: first, enforcing a more structured file and image management convention; and second, creating a tighter mapping between objects in the control window and visualization window. A solution would be to utilize a layered image file or project file to address these problems, although either of these solutions may require developers to move away from the Environment for Visualizing Images (ENVI) platform upon which the HOST is currently based. The design of the user interface could benefit from additional independent evaluations, a large scale usability test and a formal task analysis with Subject Matter Experts.
The Firefly Algorithm and Application in Cryptanalysis of Monoalphabetic Substitution Ciphers

The firefly algorithm (FA) is Nature Inspired Algorithm; this algorithm is based on flashing behavior of fireflies. The Monoalphabetic substitution cipher creates cipher text by replacing each alphabet with another alphabet. The cryptanalysis of substitution cipher involves statistical data of language. In this paper we proposed new Firefly Algorithm for cryptanalysis of the Monoalphabetic substitution cipher and then compared result with random algorithm on the basis of convergence time and corrected percentage of decrypted text.
Pushing further:alternative ball-handling by intercepting and pushing with an omni-directional soccer robot

Tech United Eindhoven has been participating in the RoboCup mid-size soccer league since 2005 using its omni-directional soccer robots called Turtles. The team has been searching for a method to increase the speed at which the Turtles can receive the ball and subsequently score or pass the ball. Currently only a ball handling mechanism is used for this purpose. However, it requires the Turtle to be oriented towards the ball to intercept it, after which it has to turn before it can drive or shoot to the preferred target. To increase the speed of play, a new type of ball handling is developed in the form of the push action. During the push a Turtle will intercept and control the ball using its housing. An impact model, which describes the trajectories of the ball before and after impact has been implemented. In order to intercept the ball at the impact location, having the correct velocity and orientation, a trajectory planner has also been developed and implemented. The push action has been integrated into the general strategy of the Turtles such that the push can be used at corner situations. During the RoboCup World Championship 2013 a goal has been scored using the push. Future work includes the development of a more sophisticated trajectory planner and using the push action for passing.