Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive JSPA in distributed colocated MIMO radar network for multiple targets tracking

In this study, the authors present a distributed resource-awareness colocated multiple-input-multiple-output radar network for multiple targets tracking. Specifically, taking posterior Cramer-Rao lower bound as the performance metric, they propose a joint scheduling and power allocation (JSPA) scheme as a sparse optimisation problem. The sparsity of the solution enables the JSPA scheme to jointly optimise the schedule and corresponding transmit power of radars by the non-zero entries with associated amplitudes. The JSPA scheme has the robustness of feasibility even if there is not enough resource to achieve the prescribed performance requirements of targets. In this case, the JSPA scheme will automatically relax the performance bounds for individual targets at the lowest price and decide the number of targets to be tracked according to the priorities. They also propose a global optimal fusion rule that builds the connection between resource allocation and distributed tracking. Simulation results demonstrate the effectiveness of the proposed methods. The JSPA scheme can dynamically adjust the resource utilisation of the tracking of individual targets according to the accuracy demands. The performance of important targets is favoured to be satisfied, whereas a target with low priority may be dropped by the JSPA scheme if necessary.
Mediating between causes and probabilities: the use of graphical models in econometrics

The development of macro-econometrics has been persistently fraught with a tension between “deductivist” and “inductivist” approaches to causal inference. The former conceives causes as something that economic theory must provide and that statistical methods must measure. The latter opens the possibility of inferring causes from statistical properties of the data alone. I argue that these conceptions can be interpreted as two opposite responses to the problem of under-determination of theoretical causal relations by statistical properties (the problem of identification). Econometrics offers a clear example as to how the general problem of causal inference can be solved only by delicately mediating between background knowledge and the statistical properties of the data. I show how graphical causal models, appropriately interpreted, can serve this purpose.
Studies of Chiral-Odd GPDs in Hard Exclusive Pseudoscalar Meson Production

Deeply virtual exclusive electroproduction of pseudoscalar mesons in hard scattering processes provides a unique avenue to access chiral-odd GPDs. The latter enter the soft matrix elements in transverse virtual photon-proton scattering. Transverse photon polarization dominates πo, η, and K production in the multi GeV region owing to the fact that t-channel meson pole contribution either does not occur (πo and η), or is predicted to be relatively small (K+,Ko). This is at variance with the longitudinal charged pion production channel which is enhanced by a large meson pole contribution. We propose a combination of measurements of cross sections, spin and azimuthal asymmetries with a longitudinally polarized beam and both an unpolarized and longitudinally polarized proton target for πo, η and K+,Ko electroproduction with the aim of: i) providing a detailed test of the mechanism for pseudoscalar meson electroproduction including strangeness, in the multi GeV region; ii) separating out the contributions from the different chiral-odd GPDs; iii) providing a flavor decomposition of underlying chiral-odd GPDs.
Examining the Impact of Self-Promotion on Job Interviews: A Case Study of Malaysian Fresh Graduate Teachers

The purpose of this study was to examine how a particular cohort of applicants, who were seeking teaching positions in an international school were working with students experiencing learning difficulties, responded to the job interview question "why should we hire you. " By analyzing their responses, the aim was to understand how these teachers engaged in self-promotion to create a favorable impression of the interviewer. A qualitative research approach was utilised to analyse the data collected, which consisted of interviews conducted with five successful candidates. The findings of this study indicated that these candidates encountered challenges in effectively demonstrating self-promotion during their job interviews, despite being ultimately successful in obtaining positions. Furthermore, the results revealed a lack of confidence among the candidates, potentially stemming from their limited proficiency in employing appropriate vocabulary to convey their goals and strategies effectively. Based on these findings, it is recommended that the teaching curriculum incorporate self-promotion techniques to better equip undergraduate students for job interviews and enable them to effectively respond to standard interview questions, thus allowing them to showcase their capabilities more confidently and successfully.
Coordinate frame free Dubins vehicle circumnavigation using only range‐based measurements

The paper presents a feedback control design that allows a Dubins vehicle to enter a circular trajectory using only range‐based measurements from the vehicle to the center of the trajectory. The controller is derived and analyzed based on a novel state space kinematic model, with the state that is composed of two continuous and one discrete state variables.The evolution of the discrete state variable is not completely defined by the model and the control design has to deal with the ambiguity of this value. Based on the conditions that need to be satisfied for the controller to work, the closed loop dynamics analysis can be performed based on 2D phase portraits, and it can be shown that the controller can work in the case of the bounded turning rate of the vehicle. The conditions define only bounds for the controller parameters and not their specific values. Therefore, the parameters can be selected based on the maximal working range of the controller and linear quadratic regulator design. The proposed control design is illustrated by 2D phase portraits and simulations describing the control implementation, which is based only on range measurements. Copyright © 2016 John Wiley & Sons, Ltd.
Numerical methods for finding characteristic roots and vectors of matrices

The present paper treats the problem of finding the characteristic roots and vectors of a matrix (having linear elementary divisors). The emphasis throughout is on methods of getting numerical results in practical cases rather than on theoretical questions. Symmetric matrices are taken up first, and methods are discussed for finding (a) the largest characteristic root and corresponding vector, and (b) the other roots and vectors. All these methods are variants of the iteration process. They are then extended to general matrices, with particular reference to the case of complex roots. The paper closes with a brief discussion of the solution of algebraic equations by means of matrices. Among earlier work on this subject, we may mention that of Hotelling1 and Aitken.2 Indeed, much of the material in the present paper is taken from Aitken's, through some modifications have been introduced, particularly with regard to the determination of roots other than the largest. A recent paper by Fry3 takes up matrices in connection with the solution of algebraic equations. The present paper, particularly the last section, is thus in a measure supplementary to Fry's. Wayland,4 on the other hand, gives methods for reducing the problem of finding the roots of a given matrix to that of solving an algebraic equation; this matter is touched upon Sec. II. Recent work along these lines has also been done by Morris6 and Head.6 At this point the author wishes to acknowledge his indebtedness to Prof. W. Feller for many helpful suggestions made during the preparation of the manuscript.
Understanding Rockburst-Generating Behaviors and Associated Seismicity by Using a Spatial Calculation Methodology with an Energy Density Index

Rockbursts have become one of the most severe risks in underground coal mining. A proper understanding of the relationship between the spatial activities of mining-induced tremors and the occurrence of rockbursts can provide effective insight into the evaluation of rockburst hazard as well as revealing their causes. A methodology for spatially calculating the seismicity involving the use of an energy density index was developed to identify the evolution of mining-induced tremors over time. The results showed that numerous tremors occurred during the excavation and mining periods, and those tremors were distributed in a spatially complicated fashion, and it was difficult to identify their evolution trends over time and assess the rockburst hazard. However, energy density clouds had obvious distinguishable trends that presented nucleation characteristics and followed obvious extension around the nucleuses until strong tremors took place nearby. Velocity tomograms indicated that evolution of energy density clouds was the response to the rising stress concentration in some local areas before the rockburst. Then the rockburst-generating journey was inferred; that is, the jump of stress in local areas of coal-rock masses results in the clustering and nucleation of microfractures firstly, and then as the microfractures developed, macrofractures appeared, bringing strong tremors which triggered the rockburst.
Significant shifts in inorganic carbon and ecosystem state in a temperate estuary (1985–2018)

Estuaries regulate carbon cycling along the land‐ocean continuum and thus influence carbon export to the ocean, and global carbon budgets. The Elbe Estuary in Germany has been altered by large anthropogenic perturbations, such as widespread heavy metal pollution, minimally treated wastewater before the 1980s, establishment of wastewater treatment plants after the 1990s, and an overall nutrient and pollutant load reduction in the last three decades. Based on an extensive evaluation of key ecosystem variables, and an analysis of the available inorganic and organic carbon records, this study has identified three ecosystem states in recent history: the polluted (1985–1990), transitional (1991–1996), and recovery (1997–2018) states. The polluted state was characterized by very high dissolved inorganic carbon (DIC) and ammonium concentrations, toxic heavy metal levels, dissolved oxygen undersaturation, and low pH. During the transitional state, heavy metal pollution decreased by > 50%, and primary production re‐established in spring to summer, with weak seasonality in DIC. Since 1997, during the recovery state, DIC seasonality was driven by primary production, and DIC significantly increased by 11 μmol L−1 yr−1, and > 23 μmol L−1 yr−1 in the recent decade (2008–2018), in the mid to lower estuary, indicating that, along with the improvement in water quality the ecosystem state is still changing. Large anthropogenic perturbations can therefore alter estuarine ecosystems (on the order of decades), as well as induce large and complex biogeochemical shifts and significant changes to carbon cycling.
Scrutinize Study on Face Recognition by Pose Invariant Methodology

Three-dimensional (3D) face models can handle large pose face recognition problem. In this paper, we propose survey on pose-invariant face recognition method. By scrutinizing study depth, here we only analysis on pose invariant technique in face recognition method is able to handle self-occlusion and deformation, both of which are challenging problems in two-dimensional (2D) face recognition. Texture images of the face in the database can be the same view as the probe during surveillance. In this survey of face detection technology has been presented in this work feature based approach with low level analysis has been done. Information, color, shape, model etc. has been considered for investigation. The technique considered here also explained in other papers. Depth information has improved the performance of face recognition with large pose variations up to the mark able angle and under even more challenging conditions.
Unraveling the Enigma: how can ChatGPT perform so well with language understanding, reasoning, and knowledge processing without having real knowledge or logic?

Artificial Intelligence (AI) has made significant progress in various domains, but the quest for machines to truly understand natural language has been challenging. Traditional mainstream approaches to AI, while valuable, often struggled to achieve human-level language comprehension. However, the emergence of neural networks and the subsequent adoption of the downstream approach have revolutionized the field, as demonstrated by the powerful and successful language model, ChatGPT. The deep learning algorithms utilized in large language models (LLMs) differ significantly from those employed in traditional neural networks. This article endeavors to provide a valuable and insightful exploration of the functionality and performance of generative AI. It aims to accomplish this by offering a comprehensive, yet simplified, analysis of the underlying mathematical models used by systems such as ChatGPT. The primary objective is to explore the diverse performance capabilities of these systems across some important domains such as clinical practice. The article also sheds light on the existing gaps and limitations that impact the quality and reliability of generated answers. Furthermore, it delves into potential strategies aimed at improving the reliability and cognitive aspects of generative AI systems.
Preparation and Characterization of Silver Nanospheroids: Theoretical and Experimental Approaches

We synthesized silver nanoparticles of different sizes and forms as function of the molar masses of AgNO 3 , in two different solvent mediums (ethanol, methanol). We carried out the synthesis according to standard chemical route with major modifications. The spectroscopic characterization showed the presence of two distinct absorption bands; the first band at 300 nm and the second shifted to 440 nm. We found a multipolar phenomenon depending on the temperature. The shape and size predicted by the numerical model are conform to the experimental results. The study demonstrated that the nanoparticles have a spheroidal shape. Full Text: PDF References Cecilia Noguez, "Surface Plasmons on Metal Nanoparticles: The Influence of Shape and Physical Environment", J. Phys. Chem. C 111(10), 3806 (2007). CrossRef M. Amraoui , C. Daoudi and M. Remram, Int.Sc. Sci and Tech. Conf. 2015 Ayd? n,Turkey , 11-13 May , 2015 (ISSTC 2015). M. I Gonzalez-Sanchez et al, "Silver nanoparticle based antibacterial methacrylate hydrogels potential for bone graft applications", Mater. Sci. Eng C. Mater. Biol. Appl 50, 332 (2015). CrossRef Xinyi Dong et al, "Shape Control of Silver Nanoparticles by Stepwise Citrate Reduction", J. Phys. Chem. C 113(16), 6573 (2009). CrossRef A. Wolak, M. Grabiec, O. Veron, J. ? P. Blondeau and K. Dzierzega, "Nanosecond infrared laser-induced precipitation of silver nanoparticles in glass", Phot. Lett. Poland 5(2), 54 (2013). CrossRef A. Zielinska, E. Skwarek, A. Zaleska, M. Gazda and J. Hupka, "Preparation of silver nanoparticles with controlled particle size", Procedia Chemistry 1, 1560 (2009). CrossRef K-S.Chou, Y.Chang and L. Hua, "Studies on the Continuous Precipitation of Silver Nanoparticles", Ind.Eng.Chem.Res 51(13) 4905 (2012). CrossRef A. M. Atta, H. A. Al-Lohedan, A. O. Ezzat, "Synthesis of Silver Nanoparticles by Green Method Stabilized to Synthetic Human Stomach Fluid", Molecules 19(5) 6737 (2014). CrossRef Botasini, S, Mendez, E. "Silver nanoparticle aggregation not triggered by an ionic strength mechanism", J Nanopart Res 15, 1526 (2013). CrossRef V. Amendola, O.M. Bakr, F. Stellacci, "A Study of the Surface Plasmon Resonance of Silver Nanoparticles by the Discrete Dipole Approximation Method: Effect of Shape, Size, Structure, and Assembly", Plasmonics 5(1) 85 (2010). CrossRef L. Jeong, W. Ho Park "Preparation and Characterization of Gelatin Nanofibers Containing Silver Nanoparticles", Int. J. Mol. Sci 15, 6857 (2014). CrossRef Peter Monk, Finite element method for Maxwell's equations, (Oxford, Clarendon Press 2003). DirectLink M.D. Abramoff, P.J. Magalhaes, S.J. Ram, "Image processing with ImageJ", Biophotonics International 11(7), 36 (2004). DirectLink Edward D.Palik, Handbook of optical constants of solids (California, Academic Press Inc, 1985). DirectLink
Leadership styles and employee creativity: the interactive impact of online knowledge sharing and organizational innovation

Purpose This study aims to examine the differences in the impact of three leadership styles (transactional, transformational and creative) on intraorganizational online knowledge-sharing and employee creativity. Specifically, we use self-determination theory (SDT) to examine the impact of these three leadership styles on four aspects of online knowledge sharing (knowledge donating, knowledge collecting, lurking and active lurking) and the moderating role of organizational innovation on these relationships. Design/methodology/approach Data were collected from 361 employees of business-to-business organizations in Vietnam to support all our hypotheses. Structural equation modelling was used for data analysis. Findings Transformational, transactional and creative leadership were found to affect online knowledge sharing, wherein creative leadership had the most potent effect. Online knowledge sharing was found to mediate the impact of three types of leadership on employee creativity. The results also showed that organizational innovation moderates the influence of leadership on online knowledge sharing. Originality/value This paper extends the current knowledge management research on online knowledge sharing by studying two new behaviors (lurking and active lurking), linking diverse leadership styles to these behaviors and employee creativity, and exploring the moderating role of organizational innovation. Our findings shed light on the complexity of the relationship between leadership and online knowledge sharing. This study also provides valuable implications for practitioners to help them choose the most appropriate leadership style for their digitalization process to ensure optimal outcomes.
The Optimum Communication Spanning Tree Problem : properties, models and algorithms

For a given cost matrix and a given communication requirement matrix, the OCSTP is defined as finding a spanning tree that minimizes the operational cost of the network. OCST can be used to design of more efficient communication and transportation networks, but appear also, as a subproblem, in hub location and sequence alignment problems. This thesis studies several mixed integer linear optimization formulations of the OCSTP and proposes a new one. Then, an efficient Branch & Cut algorithm derived from the Benders decomposition of one of such formulations is used to successfully solve medium-sized instances of the OCSTP. Additionally, two new combinatorial lower bounds, two new heuristic algorithms and a new family of spanning tree neighborhoods based on the Dandelion Code are presented and tested.
The Traveling Wave Solutions of Space-Time Fractional Differential Equation Using Fractional Riccati Expansion Method

In this paper, we firstly give a counterexample to indicate that the chain rule is lack of accuracy. After that, we put forward the fractional Riccati expansion method. No need to use the chain rule, we apply this method to fractional KdV-type and fractional Telegraph equations and obtain the tangent and cotangent functions solutions of these fractional equations for the first time.
CHEMICAL EVOLUTION LIBRARY FOR GALAXY FORMATION SIMULATION

We have developed a software library for chemical evolution simulations of galaxy formation under the simple stellar population (SSP) approximation. In this library, all of the necessary components concerning chemical evolution, such as initial mass functions, stellar lifetimes, yields from Type II and Type Ia supernovae, asymptotic giant branch stars, and neutron star mergers, are compiled from the literature. Various models are pre-implemented in this library so that users can choose their favorite combination of models. Subroutines of this library return released energy and masses of individual elements depending on a given event type. Since the redistribution manner of these quantities depends on the implementation of users’ simulation codes, this library leaves it up to the simulation code. As demonstrations, we carry out both one-zone, closed-box simulations and 3D simulations of a collapsing gas and dark matter system using this library. In these simulations, we can easily compare the impact of individual models on the chemical evolution of galaxies, just by changing the control flags and parameters of the library. Since this library only deals with the part of chemical evolution under the SSP approximation, any simulation codes that use the SSP approximation—namely, particle-base and mesh codes, as well as semianalytical models—can use it. This library is named “CELib” after the term “Chemical Evolution Library” and is made available to the community.
Venture Capital Contracting with Double-Sided Moral Hazard and Fairness Concerns

The development of new venture enterprise is the result of joint efforts of entrepreneurs and venture capitalists who collaborate based on complementary resources. In this paper, we analyze a venture capital incentive contracting model in which a venture capitalist interacts with an entrepreneur who is risk neutral and fairness concerned, offering him an equity contract. We solve the venture capitalist’s maximization problem in the presence of double-sided moral hazard. Our results show that fairness concerns change the structure of the optimal contract. More importantly, we show that the solution to the contract regarding the optimal share given to the entrepreneur is nonlinear and is a fixed point between 0 and 1. Further, we simulate the model under the assumption that venture project’s revenue is a Constant Elasticity of Substitution (CES) function and obtain the following results. (1) When the two efforts are complementary, the venture capitalist’s effort does not monotonically decrease in the share allocated to the entrepreneur, while the entrepreneur’s effort does not monotonically increase in his share. (2) Relative to the benchmark case where the entrepreneur is fairness neutral, the optimal equity share allocated to the fair-minded entrepreneur is larger than 1/2, and as the degree of efforts complementarity increases, the optimal equity share tends to 60%. In this scenario, for a given efforts substitution parameter, the fair-minded entrepreneur provides a higher effort level than the venture capitalist.
Gridless DOA Estimation Using Complex-Valued Convolutional Neural Network With Phasor Normalization

We propose a complex LeDIM-net (C-LeDIM-net) convolutional neural network (CNN) that employs a newly-formulated complex phasor normalization for gridless direction-of-arrival (DOA) estimation. Unlike existing deep learning (DL) approaches, C-LeDIM-net extracts explicit phase information in its intermediate complex-valued feature maps to estimate unknown source DOAs. Given its explicit phase representation, the proposed complex phasor normalization leverages the phase-to-sensor relationship of the feature maps which, as a consequence, improves the robustness of C-LeDIM-net to array imperfections when operating with limited number of snapshots. Simulation results show that the proposed method outperforms the existing methods, including the subspace-based and DL-based methods.