Miracle-dz/UniFAR-FTUs huggingface dataset:
RAPIDLY EVOLVING AND LUMINOUS TRANSIENTS FROM PAN-STARRS1

In the past decade, several rapidly evolving transients have been discovered whose timescales and luminosities are not easily explained by traditional supernovae (SNe) models. The sample size of these objects has remained small due, at least in part, to the challenges of detecting short timescale transients with traditional survey cadences. Here we present the results from a search within the Pan-STARRS1 Medium Deep Survey (PS1-MDS) for rapidly evolving and luminous transients. We identify 10 new transients with a time above half-maximum (t1/2) of less than 12 days and −16.5 > M > −20 mag. This increases the number of known events in this region of SN phase space by roughly a factor of three. The median redshift of the PS1-MDS sample is z = 0.275 and they all exploded in star-forming galaxies. In general, the transients possess faster rise than decline timescale and blue colors at maximum light (gP1 − rP1 ≲ −0.2). Best-fit blackbodies reveal photospheric temperatures/radii that expand/cool with time and explosion spectra taken near maximum light are dominated by a blue continuum, consistent with a hot, optically thick, ejecta. We find it difficult to reconcile the short timescale, high peak luminosity (L > 1043 erg s−1), and lack of UV line blanketing observed in many of these transients with an explosion powered mainly by the radioactive decay of 56Ni. Rather, we find that many are consistent with either (1) cooling envelope emission from the explosion of a star with a low-mass extended envelope that ejected very little (<0.03 M☉) radioactive material, or (2) a shock breakout within a dense, optically thick, wind surrounding the progenitor star. After calculating the detection efficiency for objects with rapid timescales in the PS1-MDS we find a volumetric rate of 4800–8000 events yr−1 Gpc−3 (4%–7% of the core-collapse SN rate at z = 0.2).
An improved DFA for fast regular expression matching

Modern network devices need to perform deep packet inspection at high speed for security and application-specific services. Finite Automata (FAs) are used to implement regular expressions matching, but they require a large amount of memory. Many recent works have proposed improvements to address this issue. This paper presents a new representation for deterministic finite automata (orthogonal to previous solutions), called Delta Finite Automata (δFA), which considerably reduces states and transitions and requires a transition per character only, thus allowing fast matching. Moreover, a new state encoding scheme is proposed and the comprehensive algorithm is tested for use in the packet classification area.
Email Analytics for Support Center Performance Analysis

Despite the growth of social networks, emails still continue to be the building blocks of formal communication within any business organization. For many organizations, email-based information exchange provides the backbone for customer support centers. Analyzing these conversations can provide insights into domain process related lacunae and loopholes in that division and identify actionable methods to improve them. In this paper we present a framework along with several methods and metrics that provide insights about its current performance measures as well as identify the bottlenecks and their causes. We have also presented a new method for grouping emails according to the similarity of their content to derive problem-specific performance statistics.
An eye-opening approach to developing and communicating integrated environmental assessments

Communication among managers, the public, and scientists is the key to successful ecosystem management; however, the varied perspectives and interests of these groups can make such communication difficult. One way to achieve effective communication is to develop a common knowledge base by combining syntheses of key scientific results with information-rich visual elements. Within a management landscape, integrated environmental assessments provide a useful framework for evaluating resources and directing management efforts. The integrated assessment process involves (1) initial investigation, (2) development of a conceptual framework, (3) data navigation, (4) environmental report cards, and (5) science communication. Each step requires the synthesis and visualization of information on the status and trends connected with multiple natural resources. We provide a case study, using examples from selected National Park Service sites in the mid-Atlantic region of the United States. Visual elements (conceptual d.
Patterns of co-morbidity with anxiety disorders in Chinese women with recurrent major depression

Background Studies conducted in Europe and the USA have shown that co-morbidity between major depressive disorder (MDD) and anxiety disorders is associated with various MDD-related features, including clinical symptoms, degree of familial aggregation and socio-economic status. However, few studies have investigated whether these patterns of association vary across different co-morbid anxiety disorders. Here, using a large cohort of Chinese women with recurrent MDD, we examine the prevalence and associated clinical features of co-morbid anxiety disorders. Method A total of 1970 female Chinese MDD patients with or without seven co-morbid anxiety disorders [including generalized anxiety disorder (GAD), panic disorder, and five phobia subtypes] were ascertained in the CONVERGE study. Generalized linear models were used to model association between co-morbid anxiety disorders and various MDD features. Results The lifetime prevalence rate for any type of co-morbid anxiety disorder is 60.2%. Panic and social phobia significantly predict an increased family history of MDD. GAD and animal phobia predict an earlier onset of MDD and a higher number of MDD episodes, respectively. Panic and GAD predict a higher number of DSM-IV diagnostic criteria. GAD and blood-injury phobia are both significantly associated with suicidal attempt with opposite effects. All seven co-morbid anxiety disorders predict higher neuroticism. Conclusions Patterns of co-morbidity between MDD and anxiety are consistent with findings from the US and European studies; the seven co-morbid anxiety disorders are heterogeneous when tested for association with various MDD features.
A new quadripartite public-key cryptosystem

The paper introduces a new paradigm for public key cryptography, which is called quadripartite public-key (QPK) based on quaternion presentation. We considered a private key as a unit quaternion which has an arbitrary quadruple of real numbers. The public key has three different components which are constructed using a quaternion rotation matrix (QRM) to generate a secure key, which significantly eliminates the risk of eavesdropping. Furthermore, the quaternion has the capability to provide a meditative encryption system for wireless image or voice transmissions. A computer-based simulation, conducted to scrutinize carefully the capability of QPK to ensure the highest level of security, is reported.
Application of an ANFIS algorithm to narrowband active noise control system

This paper proposes a new narrowband active noise control (ANC) system where an ANFIS (adaptive network-based fuzzy inference system) is utilized as an adaptive controller. The ANFIS is a combination of a neural network and a fuzzy inference system. For the purpose of computational cost reduction, the nonlinear premise parameters in the ANFIS are fixed and only its linear consequent parameters are adjusted based on a gradient descent method rather than the hybrid learning rule. The proposed system may looks somewhat more complicated than the conventional FXLMS-based ANC system, but it does not require reference signal filtering at all. Simulation results reveal that the proposed ANC system enjoys sufficient effectiveness in suppressing noise signals of sinusoidal nature.
Cluster Analysis of Neural Network Weights for Discrimination of Eeg Signals

Category: Applications. No part of this work has been submitted or appeared in other scientiic conferences. Abstract Neural networks are trained to classify half-second segments of six-channel, EEG data into one of ve classes corresponding to ve cog-nitive tasks performed by one subject. Two and three-layer feed-forward neural networks are trained using 10-fold cross-validation and early stopping to control over-tting. Two representations of the EEG signals, based on autoregressive (AR) models and Fourier Transforms, are compared. Using the AR representation, an average of 71% of test segments are correctly classiied; for some test sets 100% are correctly classiied. Cluster analysis of the resulting neural networks' hidden-unit weight vectors shows that frequencies higher than those commonly believed to be associated with cogni-tive activity play a signiicant role in the classiication. These high frequencies may be the result of neck and head movements.
Scintigraphic Imaging of Inflammatory Processes

Nuclear medicine offers ideal techniques to visualize inflammatory processes using noninvasive methods of whole-body scanning, enabling the determination of both the localization and the number of inflammatory foci. In nuclear medicine, a radiolabeled compound is injected (mostly) intravenously and accumulates in the inflammatory lesion due to the locally changed physiological condition. These changes are enhanced blood flow, enhanced vascular permeability and enhanced influx of leukocytes. Radiopharmaceuticals can be primarily divided into two classes: those accumulating in the inflammatory lesion based on non-specific processes and those accumulating in connection to leukocytes. Nonspecific tracers like Ga-citrate, radiolabeled non-specific immunoglobulins and radiolabeled liposomes are discussed in detail. Studies using specific tracers mainly focus on radiolabeling leukocytes, either directly or indirectly. Direct labeling of isolated leukocytes and reinjecting them is considered the “gold standard” nuclear medicine technique for imaging inflammation. Labeling leukocytes in vivo (the indirect approach) can be achieved by the use of radiolabeled antibodies or by compounds binding to leukocyte receptors with high affinity. At least three anti-granulocyte antibodies have been tested for infection imaging: anti-NCA-95 IgG (BW250/183), anti-NCA-90 Fab' (Immu-MN3, leukoscan®: anti-CD66), and anti-SSEA-1 IgM (LeuTech: anti-CD15). In addition, a w ide var iety of pe ptide s binding to le ukocyte re ceptors ha s be en inve stiga ted, e.g. chemota ctic pe ptide formylMe t-L eu-Phe, cytokines such as inte rleukin-1, inte rleukin-2, inte rleukin-8 and pla te let f actor 4 (deriva tives) a nd complement f ac tor s suc h as C5a. Furthermore, positron emission tomography with Ffluorodeoxyglucose takes advantage of the enhanced glucose requirements of leukocytes and macrophages in inflammatory foci. A totally different approach is to target directly micro-organisms, without intervention of leukocytes. This strategy is adopted in radiopharmaceuticals such as Infecton and antimicrobial peptides. The discussed radiopharmaceuticals enable accurate diagnosis of the inflammatory condition and with these agents the effectiveness of anti-inflammatory therapies can be monitored.
A Practical Approach of Complex Dual Tree DWT for Image Quality Improvement and De-noising

It is pragmatic that for many natural signals and images, the wavelet transform is a more effective and powerful signal processing tool that provide an alternative to conventional signal transforms such as the Fourier transform. The wavelet transform provides a multi resolution representation using a set of analyzing functions that are dilation and translations of a few functions. Although the standard DWT is powerful tool, it has three major limitations (Shift Sensitivity, Poor Directionality, and Absence of Phase information) that undermines its application for certain signal and image processing tasks. The initial motivation behind the work to use Dual-tree complex-valued DWT which will overcome the limitations of standard DWT. This paper, proposes a new simple non Gaussian bivariate probability distribution function to model statistics of wavelet coefficients of images. The model captures the dependence between a wavelet coefficient and its parent. The new bivariate shrinkage function outperforms the method proposed by the previous authors for image de-noising and also give significant improvement in the value of PSNR over RMSE as given by the other classical methods.
Design and Development of Robot Hand System

Research on robot hand design is being carried out to accommodate a variety of tasks such as grasping and manipulation of objects in the field of industrial applications, service robots and rehabilitation robots. Problem statement: To design and develop a microcontroller-based four fingered robotic hand with a simple and minimal control strategy to pick and place application with object detection by simple IR sensor logic. Approach: The methodology is based on anthropomorphic design with three fingers and an opposing thumb. Each finger has three links and three double revolute joints. Each finger is actuated by a single opposing pair of tendons. The robot hand system is interfaced to microcontroller with software control by means of 14 independent commands for the motion of joints: close and open for fore finger, middle finger, ring finger and thumb finger and wrist up and down, base clockwise and counter clockwise, pick and place and home position. The tendoning system and wireless feedback logic provide the hand with the ability to confirm to object topology and therefore providing the advantage of using a simple control structure. Results: Reliable grasping and releasing is achieved with simple control mechanisms and IR sensors/push-button switches. The hand can pick a variety of objects with different surface characteristics and shapes without having to reconstruct its surface description. Picking of the object is successfully completed as long as the object is within the workspace of the hand and placed the object at the desired position within the workspace by relevant software control using keyboard commands. Conclusion: Hardware and software development of microcontroller-based four-fingered robotic hand is addressed. Details of hand control software for mainly pick and place applications are presented. Results of the experimental work for pick and place application of different objects is enumerated.
Analysis and Synthesis of Binaural Parameters for Efficient 3D Audio Rendering in MPEG Surround

This paper describes a novel method to simulate an multichannel audio experience using stereo headphones. In contrast to conventional, convolution-based methods, the current approach is based on parametric representations of spatial audio. An audio scene with multiple virtual sound sources is represented by a mono down-mix signal of all sound source signals, accompanied by certain statistical (spatial) properties. These statistical properties of the sound sources are combined with statistical properties of head-related transfer functions to estimate "binaural parameters" that represent the perceptually-relevant aspects of the auditory scene. Subsequently, a binaural rendering stage re-instates the estimated binaural parameters on the down mix. The advantage of this approach is that the computational complexity of the rendering process is virtually independent of the number of simultaneous sound sources. If combined with parametric multichannel audio coders such as MPEG Surround, the proposed method is advantageous over conventional methods in terms of perceived quality and computational complexity.
A New A New A New A New Checkpoint Approach for Fault Checkpoint Approach for Fault Checkpoint Approach for Fault Checkpoint Approach for Fault TTTTolerance in Grid olerance in Grid olerance in Grid olerance in Grid

Computational and Service grid are used to solve large-scale scientific application using grid resources. The main focus is on fault identification, fault rectification (fault tolerance) using checkpoint approaches. In order to achieve the fault tolerance, checkpoint approach can be used. Job check pointing is one of the most common utilized techniques for providing fault tolerance in computational grids. The effectiveness of check pointing depends on the choice of the checkpoint interval. A common technique for fault tolerance is dynamically adapting the checkpoint, in which all the failure information are maintained in the Grid Information Server. This requires a separate server for storage purpose in order to increase the execution time. The main goal of checkpoint approach is to minimize the overall execution time in grid system. In this work fault tolerant scheduling is achieved using kernel-level checkpoint. In case of resource failure, the Fault Index Based Rescheduling (FIBR) algorithm is used to reschedule the jobs to some other available resources. This ensures that the job is executed with minimized execution time.
Automatic Detection of Electrocardiogram ST Segment: Application in Ischemic Disease Diagnosis

The analysis of electrocardiograph (ECG) signal provides important clinical information for heart disease diagnosis. The ECG signal consists of the P, QRS complex, and T-wave. These waves correspond to the fields induced by specific electric phenomenon on the cardiac surface. Among them, the detection of ischemia can be achieved by analysis the ST segment. Ischemia is one of the most serious and prevalent heart diseases. In this paper, the European database was used for evaluation of automatic detection of the ST segment. The method comprises several steps; ECG signal loading from database, signal preprocessing, detection of QRS complex and R-peak, ST segment, and other relation parameter measurement. The developed application displays the results of the analysis. Keywords-Electrocardiogram (ECG); Ischemia; European ST- T database; QRS complex ; ST segment. I. INTRODUCTION Electrocardiographic (ECG) signals information is derived from analysis of the information indirectly reflected on the surface ECG. The ECG signal is able to make of basic information for heart disease, indisposed of the autonomic nervous system and stress. The world Health Organization estimates that 17.5 million people died of cardiovascular disease. It is representing 30% of all global deaths. Out of these, 7.6 million were due to coronary artery disease (CAD)(1). During the last few years, a lot of research has provided the solution of analysis and diagnosis in ECG by adopting new technologies and algorithms. Among them, ischemic heart disease constitutes one of the most common fatal diseases in the world. Myocardial ischemia is caused by a lack of sufficient blood flow to the contractile cells and many lead to myocardial information with its severe sequel of heart failure, arrhythmias and death (2). The ischemic disease is usually identified in the standard ECG by changes in values of measured amplitudes, times and durations on the ST-T complex. The ST-T complex of the ECG reflects the time period from the end of active ventricular depolarization to the end of depolarization in the heart cycle (3-4). Therefore, ST- segment changes are common ECG signal markers of important Myocardial ischemia (5). The several methods for ischemia parameter detection (T wave and ST complex) have been proposed. In generally, all of them are based on the spectral estimation (6) and signal point from the ST segment better characterizes ischemic patterns (3, 7). The various methods have been applied to the ECG for ischemia analysis and detection: used the First Fourier Transform (FFT) to analyze the frequency component (8), fuzzy-logic, neural network, genetic algorithm, support vector machines (SVM), wavelet transform and many more (9). However, most of the algorithms have sensitivity above the 80%. In this study we consider two applications of the ST segment detection and display program: Detection of ischemia episodes and monitoring PC programming. The modifications in the shape parameters have been used for ST segment measurement. II. METHOD AND MATERIAL A. European ST-T Database
A single-phase grid connected inverter with a power pulsation decoupling circuit on the AC output

In the single-phase grid connected inverter, a power pulsation with twice the grid frequency is contained in the input power. In the conventional inverter, electrolytic capacitor with large capacitance has been used in order to decouple the pulsation. But, the electrolytic capacitor has a drastically shortened lifespan when used in high-temperature environment. This paper presents a single-phase grid connected inverter with a power decoupling circuit on the AC output. A most distinctive feature of the proposed system is that the ripple energy appeared on the input DC capacitor is transferred into the energy in an inductance on the additional decoupling circuit. Hence, the large electrolytic capacitor can be replaced by the small film capacitor. This paper presents the proposed topology and its control requirement. Finally, the new topology is verified through MATLAB simulation.
Depth data filtering for real-time head pose estimation with Kinect

In order to analyze the head motion of pilots in real time and improve tracking performance, we propose a method based on the random regression forest framework to address head pose estimation from depth data captured by Kinect sensors. We present the novel Trinary Annulus Filter and implement Bilateral Filtering using CUDA to process depth data of Kinect, with the purpose of image quality improvement and minimized performance impact. We have evaluated our system on a public database, and it is proved to be more effective after depth data processing and capable of handling large and rapid head rotations, temporary and partial occlusions in performance evaluation. After head pose data are filtered by presented multiple pose estimation method, they are successfully used in flight simulation to drive the rotation of viewpoint.
1 Mobile Context Recommendations from Social Media through Geotopical Clustering

Mobile recommender systems can improve the speed at which information is passed to a user by taking advantage of the user’s context to provide relevant data. In addition, social media can often provide relevant information to a user about what is happening in their environment. However, to obtain this knowledge, a user may be required to wade through a large amount of irrelevant data. In this paper, we describe our system, GeoContext, for providing relevant contextual information to a user based on his or her location by mining social media. We implemented GeoContext with a geotopical clustering system, a keyword query system, and a location query system. We evaluate GeoContext against a common topic modeling algorithm often used in geotopical clustering, Latent Dirichlet Allocation.
A Method of Multiple Encryption and Sectional Encryption Protocol Reverse Engineering

Research on unknown network protocol reverse engineering is of great significance in many network security applications. Currently most of methods are limited in analyzing plain-text protocols, and a few of method can partly analyze the encryption protocol which is powerless for multiple encryption protocol or sectional encryption protocol. This paper proposes a method of encrypted protocol reverse engineering based on dynamic taint analysis. The method uses Pin to record executed instructions, and then conducts off-line analysis of the data dependencies to build two taint propagation graphs on instruction and function level, then recover the decryption process. The decrypted plaintext can be located due to the decryption process feature. And then, the format of protocol can be parsed. Experiments show that the method can accurately locate the decrypted protocol data of the multiple encryption and sectional encryption protocol, and restore the original format.