Miracle-dz/UniFAR-FTUs huggingface dataset:
The Fast Fourier Transform Digital Signal Processing: a Computer Science Perspective

It is difficult to overstate the importance of the FFT algorithm for DSP. We have often seen the essential duality of signals in our studies so far; we know that exploiting both the time and the frequency aspects is critical for signal processing. We may safely say that were there not a fast algorithm for going back and forth between time and frequency domains, the field of DSP as we know it would never have developed. The discovery of the first FFT algorithm predated the availability of hardware capable of actually exploiting it. The discovery dates from a period when the terms calculator and computer referred to people, particularly adept at arithmetic, who would perform long and involved rote calculations for scientists, engineers, and accountants. These computers would often exploit symmetries in order to save time and effort, much as a contemporary programmer exploits them to reduce electronic computer run-time and memory. The basic principle of the FFT ensues from the search for such time-saving mechanisms, but its discovery also encouraged the development of DSP hardware. Today's DSP chips and special-purpose FFT processors are children of both the microprocessor age and of the DSP revolution that the FFT instigated. In this chapter we will discuss various algorithms for calculating the DFT, all of which are known as the FFT. Without a doubt the most popular algorithms are radix-2 DIT and DIF, and we will cover these in depth. These algorithms are directly applicable only for signals of length N = 2m, but with a little ingenuity other lengths can be accommodated. Radix-4, split radix, and FFT842 are even faster than basic radix-2, while mixed-radix and prime factor algorithms directly apply to N that are not powers of two. There are special cases where the fast Fourier transform can be made even faster. Finally we present alternative algorithms that in specific circumstances may be faster than the FFT.
IHS-RD-Belarus at SemEval-2016 Task 5: Detecting Sentiment Polarity Using the Heatmap of Sentence

This paper describes the system submitted by IHS-RD-Belarus team for the sentiment detection polarity subtask on Aspect Based Sentiment Analysis task at the SemEval 2016 workshop on semantic evaluation. We developed a system based on artificial neural network to detect the sentiment polarity of opinions. Evaluation on the test data set showed that our system achieved the F-score of 0.83 for restaurants domain (rank 4 out of 28 sub-missions) and F-score of 0.78 for laptops domain (rank 4 out of 21 submissions).
Design of Compact RF Filters with Narrow Band-Pass and Wide StopBand by Open-Stub & T-shaped Microstrip Resonators and Defected Ground Structure ( DGS )

This paper presents the design of a narrow band-pass filter with wide stopband for WLAN and WiMAX applications. First, open-stub and T-shaped resonators were used to design a filter (F1) with the center frequency of 2.4 GHz. In order to verify the architectures of the proposed resonators, their frequency responses were compared to the response of an LC model. Next, DGS was utilized to achieve a wide stopband within the frequency response of F1. The design of other narrow-band filters (F2 and F3) with their center frequencies of 3.7 GHz and 5.1 GHz respectively is derived only by modifying the dimensions of the resonators in the structure of F1.Advantages of these filters include simplicity, architectural symmetry, tuning for applications at other frequencies and proper bandwidth. These filters have optimal return loss and insertion loss.
Application of the UCT Algorithm for Noisy Optimization Problems

This paper introduces the upper confidence bound (UCB) applied to the tree (UCT) algorithm for noisy optimization problems. Although there are many studies and effective algorithms regarding optimization problems like PSO and DE, the UCB value enables us to balance exploration and exploitation in the search process and to detect the most probable area containing the optimum solution. Thus, UCB applied to tree can search the area more precisely by dividing the area, and is well known for the bandit problem and computation igo. Under the noisy condition, optimization problems are not so much deterministic problems as probabilistic ones like the bandit problem. Therefore, we propose a novel approach to the situation based on the bandit algorithm as typified by UCT. We performed comparative experiments in continuous optimization problems with additive noise to confirm its convergence speed and ability for best area identification.
High Frequency Peakers

Abstract There is quite a clear anticorrelation between the intrinsic peak frequency and the overall radio source size in compact steep spectrum (CSS) and gigahertz peaked spectrum (GPS) radio sources. This feature is interpreted in terms of synchrotron self-absorption (although free–free absorption may play a role as well) of the radiation emitted by a small radio source which is growing within the inner region of the host galaxy. This leads to the hypothesis that these objects are young and that the radio source is still developing/expanding within the host galaxy itself. Very young radio sources must have the peak in their radio spectra occurring above a few tens of gigahertz, and for this reason they are termed high frequency peakers (HFPs). These newly born radio sources must be very rare given that they spend very little time in this stage. H o = 100 km s−1 Mpc−1 and q o = 0.5 are used throughout this paper.
A Finite Element Study of the Transport Phenomena in MHD Micropolar Flow in a Darcy-Forchheimer Porous Medium

analyze the free convection magnetohydrodynamic micropolar flow, heat and species diffusion between vertical plates enclosing a non-Darcian porous medium with variable thermal conductivity and internal heat generation/absorption effects. The non-linear coupled partial differential conservation equations are transformed and solved using the finite element method subjected to appropriate boundary conditions. Numerical results for the velocity, angular velocity, temperature and concentration profiles as well as for the heat transfer rate and skin friction are plotted graphically and tabulated for the controlling thermophysical and hydrodynamic parameters, namely hydromagnetic number buoyancy ratio parameter, vortex viscosity parameter, Darcy number, Forchheimer number, thermal conductivity parameter and heat absorption/generation parameter to demonstrate the flow and transport phenomena behaviour. It is also shown that the volume flow rate, the total heat rate and the total species rate added to the fluid are decreased with a rise in vortex viscosity parameter. The flow scenario finds applications in Chemical processing, metallurgical transport modeling, aerodynamic heating and many geophysical processes e.g. crude oil recovery. I. INTRODUCTION The study of convective flow, heat and mass transfer in porous media has been an active field of research as it play a crucial role in diverse applications, such as thermal insulation, extraction of crude oil and chemical catalytic reactors etc. Although considerable work has been reported on flow heat and mass transfer in porous media, a majority of porous studies have been on Darcy's law which states that the volume averaged velocity is proportional to the pressure gradient. Darcy's law however is valid only for slow flows through porous media with low permeability. At higher flow rates, there is a departure from the linear law and inertial effects
Improving semantic similarity measures for word pair comparison

The semantic web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. In order to achieve the goals of the semantic web, it have to be able to define and to describe the relations among data (i.e., resources) on the Web. Ontologies are one of the formal representation for organizing information in the semantic web and they are also used in artificial intelligence, systems engineering, software engineering, biomedical informatics, library science, enterprise bookmarking, and information architecture as a form of knowledge representation about the world or some part of it. In the semantic web context, since many actors provide their own ontologies, ontology matching or ontology alignment has taken a critical role for helping heterogeneous resources to inter-operate [23]. Ontology matching tools find classes of data that are “semantically equivalent”. This process determine correspondences between concepts which are called alignments [22]. Finding those correspondences imply a semantic similarity assessment between the involved concepts. Semantic similarity of words pairs is often represented by the similarity between the concepts associated with the words. Several methods have been developed to compute words similarity, most of them operating on taxonomic dictionaries like WordNet [24] or external corpus like the Brown Corpus. However the majority of them suffer from a serious limitation. They only focus on the semantic information shared by those words, or in the semantic differences, but they have been rarely combined in a broader perspective. In this thesis we developed and applied a model of semantic similarity computation for word pair comparison. This model consider the semantic commonalities and the semantic differences as the core of its approach. By applying the model five new WordNet-based semantic similarity measures for word pair comparison were created. Four of this semantic similarity measures obtained higher values of correlation with human judgment than their original expressions, while the fifth one remained as competitive as their original version. We also study WordNet taxonomic properties to extend a corpus-independent information content metric. The application of this new metric in one of the previously developed node-based semantic similarity allowed us to obtain the highest value of correlation with respect to human judgment. This thesis provides a general an extensible approach of semantic similarity computation for word pair comparison.
A continuous facility location problem and its application to a clustering problem

We consider a new problem, which we denote by Continuous Facility Location (ConFL), and its application to the k-Means Problem. Problem ConFL is a natural extension of the Uncapacitated Facility Location Problem where a facility can be any point in Rq. The proposed algorithms are based on a primal-dual technique for spaces with constant dimensions. For the ConFL Problem, we present algorithms with approximation factors 3 + ε and 1.861 + ε for euclidean distances and 9 + ε for squared euclidean distances. For the k-Means Problem (that is restricted to squared euclidean distance), we present an algorithm with approximation factor 54+ ε. All algorithms have good practical behaviour in small dimensions. Comparisons with known algorithms show that the proposed algorithms have good practical behaviour.
Sleep‐related eye symptoms and their potential for identifying driver sleepiness

The majority of individuals appear to have insight into their own sleepiness, but there is some evidence that this does not hold true for all, for example treated patients with obstructive sleep apnoea. Identification of sleep‐related symptoms may help drivers determine their sleepiness, eye symptoms in particular show promise. Sixteen participants completed four motorway drives on two separate occasions. Drives were completed during daytime and night‐time in both a driving simulator and on the real road. Ten eye symptoms were rated at the end of each drive, and compared with driving performance and subjective and objective sleep metrics recorded during driving. ‘Eye strain’, ‘difficulty focusing’, ‘heavy eyelids’ and ‘difficulty keeping the eyes open’ were identified as the four key sleep‐related eye symptoms. Drives resulting in these eye symptoms were more likely to have high subjective sleepiness and more line crossings than drives where similar eye discomfort was not reported. Furthermore, drivers having unintentional line crossings were likely to have ‘heavy eyelids’ and ‘difficulty keeping the eyes open’. Results suggest that drivers struggling to identify sleepiness could be assisted with the advice ‘stop driving if you feel sleepy and/or have heavy eyelids or difficulty keeping your eyes open’.
Nonlinear control for trajectory tracking of a quadrotor unmanned vehicle

This paper presents a new solution to the motion control problem for a rotary wing vehicle powered by four rotors. The proposed control structure is a parallel scheme consisting of a partial state saturated feedback to control the vehicle altitude and a partial feedback linearizing feedback to control the planar vehicle's position. It is shown that the resulting closed-loop dynamics has a local asymptotic stability property. Numerical simulations show the performance of the proposed controller.
Communication complexity of promise problems and their applications to finite automata

Equality and disjointness are two of the most studied problems in communication complexity. They have been studied for both classical and also quantum communication and for various models and modes of communication. Buhrman et al. [Buh98] proved that the exact quantum communication complexity for a promise version of the equality problem is ${\bf O}(\log {n})$ while the classical deterministic communication complexity is $n+1$ for two-way communication, which was the first impressively large (exponential) gap between quantum and classical (deterministic and probabilistic) communication complexity. If an error is tolerated, both quantum and probabilistic communication complexities for equality are ${\bf O}(\log {n})$. However, even if an error is tolerated, the gaps between quantum (probabilistic) and deterministic complexity are not larger than quadratic for the disjointness problem. It is therefore interesting to ask whether there are some promise versions of the disjointness problem for which bigger gaps can be shown. We give a positive answer to such a question. Namely, we prove that there exists an exponential gap between quantum (even probabilistic) communication complexity and classical deterministic communication complexity of some specific versions of the disjointness problem. Klauck [Kla00] proved, for any language, that the state complexity of exact quantum/classical finite automata, which is a general model of one-way quantum finite automata, is not less than the state complexity of an equivalent one-way deterministic finite automata (1DFA). In this paper we show, using a communication complexity result, that situation may be different for some promise problems. Namely, we show for certain promise problem that the gap between the state complexity of exact one-way quantum finite automata and 1DFA can be exponential.
Extracellular signals and receptor-like kinases regulating ROP GTPases in plants

Rho-like GTPase from plants (ROPs) function as signaling switches that control a wide variety of cellular functions and behaviors including cell morphogenesis, cell division and cell differentiation. The Arabidopsis thaliana genome encodes 11 ROPs that form a distinct single subfamily contrarily to animal or fungal counterparts where multiple subfamilies of Rho GTPases exist. Since Rho proteins bind to their downstream effector proteins only in their GTP-bound “active” state, the activation of ROPs by upstream factor(s) is a critical step in the regulation of ROP signaling. Therefore, it is critical to examine the input signals that lead to the activation of ROPs. Recent findings showed that the plant hormone auxin is an important signal for the activation of ROPs during pavement cell morphogenesis as well as for other developmental processes. In contrast to auxin, another plant hormone, abscisic acid, negatively regulates ROP signaling. Calcium is another emerging signal in the regulation of ROP signaling. Several lines of evidence indicate that plasma membrane localized-receptor like kinases play a critical role in the transmission of the extracellular signals to intracellular ROP signaling pathways. This review focuses on how these signals impinge upon various direct regulators of ROPs to modulate various plant processes.
A P2P Communication Model for IPv4/IPv6 Hybrid Network

We propose a P2P based communication model to resolve the inter-communication problem among the IPv4 and IPv6 terminals in large scale system. Our model well captures the traversing requirement of such hybrid network and achieves a balanced load through the networks. In addition, the model is highly adaptable to network topology changes and is able to support mobile terminals communication. We present the routing mechanism based on a route locality and searching algorithm built on Distributed Hash Table (DHT). The terminals form a flexible Overlay Network where each device has a unique Peer ID. They serve as a ¡ skeleton¡ of the network and distributedly store the route information and the mapping between IP addresses and Peer IDs. Our method provides both a seamless communication for the current hybrid network and a painless switching from IPv4 to IPv6.
Learning to bounce a ball with a robotic arm

Bouncing a ball is a fun and challenging task for humans. It requires fine and complex motor controls and thus is an interesting problem for robot learning. We investigate how to find a policy that is able to keep a ball in the air using a paddle. To solve the bounce ball task we use Relative Entropy Policy Search (REPS) to learn the parameters of Rhythmic Dynamical Movement Primitives (RDMP). We evaluate the policies learned for different configurations. The results show that REPS is successful at solving configurations in which the ball initialization is point-wise, but does not converge to a good optimum when the ball is initialized from a distribution.
Compliant-motion planning and execution for robotic assembly

This paper presents a method for the planning and execution of compliant motions within the scope of a two-phase fine-motion planner for the performance of planar assembly tasks with robots. Algorithms are provided to find a nominal solution path in both free and contact configuration space which is feasible in spite of the uncertainties affecting the task. Compliant-motion commands based on the generalized damping control mode are synthesized to follow this path, allowing to maintain a constant bounded force.
Sparsification of influence networks

We present Spine, an efficient algorithm for finding the "backbone" of an influence network. Given a social graph and a log of past propagations, we build an instance of the independent-cascade model that describes the propagations. We aim at reducing the complexity of that model, while preserving most of its accuracy in describing the data. We show that the problem is inapproximable and we present an optimal, dynamic-programming algorithm, whose search space, albeit exponential, is typically much smaller than that of the brute force, exhaustive-search approach. Seeking a practical, scalable approach to sparsification, we devise Spine, a greedy, efficient algorithm with practically little compromise in quality. We claim that sparsification is a fundamental data-reduction operation with many applications, ranging from visualization to exploratory and descriptive data analysis. As a proof of concept, we use Spine on real-world datasets, revealing the backbone of their influence-propagation networks. Moreover, we apply Spine as a pre-processing step for the influence-maximization problem, showing that computations on sparsified models give up little accuracy, but yield significant improvements in terms of scalability.
Query optimizer plan diagrams: Production, reduction and applications

The automated optimization of declarative SQL queries is a classical problem that has been diligently addressed by the database community over several decades. However, due to its inherent complexities and challenges, the topic has largely remained a “black art”, and the quality of the query optimizer continues to be a key differentiator between competing database products, with large technical teams involved in their design and implementation.
Effect Of Personality (Big Five Personality) To Multitasking

Humans perform daily activities, in resolving some activities, people can do multiple task in the same general time period by engaging in frequent switches between individual tasks that is called multitasking. The preference of a person to perform multitasking is called polychronicity. One of the factors that play a role in behavior is a personality, such as the Big Five Personality. The purpose of this study was to determine the effect of Five Personality Dimensions of the Big Five Personality to multitasking. The method used is quantitative research with the type of causal comparative research. The subjects of this study were 100 lecturers from UMM and sampling method using quota sampling. The instrument used was the Big Five Personality Inventory and Multitasking Questionnaire. Test data using Ordinal Regression Analysis. The results show that the contribution of personality based on the value is Nagelkerke coefficient amount of 14.4%, while 85.6% comes from other factors. The dimensions of Big Five Personality Factor such as extraversion, conscientiousness, openness and neuroticism are not significant effects on multitasking. Keynote: Big Five Personality, multitasking, agreeableness, lecturer
A New Memristor Based Hyperchaotic System

In this paper, based on improved Chua's chaotic oscillation circuit (MCK circuit), a four-dimensional autonomous hyper chaotic system with memristor is presented, in this system piecewise-linear function taken to describe the nonlinearity of the Chua diode has been replaced by a cubic polynomial. This circuit consists of just five linear components (two resistors, two capacitors and inductor), two nonlinear components (negative conductor and flux-controlled memristor). This has been investigated extensively using numerical analysis in this paper.
Timing and Congestion Driven Algorithms for FPGA Placement

Placement is one of the most important steps in physical design for VLSI circuits. For field programmable gate arrays (FPGAs), the placement step determines the location of each logic block. I present novel timing and congestion driven placement algorithms for FPGAs with minimal runtime overhead. By predicting the post-routing timing-critical edges and estimating congestion accurately, this algorithm is able to simultaneously reduce the critical path delay and the minimum number of routing tracks. The core of the algorithm consists of a criticality-history record of connection edges and a congestion map. This approach is applied to the 20 largest Microelectronics Center of North Carolina (MCNC) benchmark circuits. Experimental results show that compared with the state-of-the-art FPGA place and route package, the Versatile Place and Route (VPR) suite, this algorithm yields an average of 8.1% reduction (maximum 30.5%) in the critical path delay and 5% reduction in channel width. Meanwhile, the average runtime of the algorithm is only 2.3X as of VPR.
Antiport Is Essential for Yersinia pestis Virulence

Yusuke Minato, Amit Ghosh,* Wyatt J. Faulkner, Erin J. Lind, Sara Schesser Bartra, Gregory V. Plano, Clayton O. Jarrett, B. Joseph Hinnebusch, Judith Winogrodzki, Pavel Dibrov, Claudia C. Häse Department of Biomedical Sciences, College of Veterinary Medicine, and Department of Microbiology, College of Science, Oregon State University, Corvallis, Oregon, USA; Department of Microbiology and Immunology, University of Miami, Miller School of Medicine, Miami, Florida, USA; Laboratory of Zoonotic Pathogens, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, Montana, USA; Department of Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada