Miracle-dz/UniFAR-FTUs huggingface dataset:
OPTIMIZATION ON SHORTEST PATH FINDING FOR UNDERGROUND CABLE TRANSMISSION LINES ROUTING USING GIS

In cable trench construction, one of the tasks for engineers is to select a suitable route to minimize construction cost and obstructions. This paper discusses the development of a Geographic Information Systems (GIS)-based Customized system to automate the process of optimum shortest path finding for routing of underground power supply cable between any two substations. It combines the spatial analysis capabilities of GIS with the sophistication of one of the Artificial Intelligence technique “Simple Ant Colony Optimization” to deal with the complexity inherent in optimum shortest path finding. The results of this project are validated and compared with an inbuilt tool Network analyst of GIS software ArcGIS and explained in the Result and discussion of this paper. In this project only optimum shortest path finding is aimed and this will be one of the main input data in my future work of improving distribution efficiency using GIS.
Model based estimation of ego-motion and road plane using vehicle-mounted camera

This paper presents a new image feature based method to estimate ego-motion and relative pose to the road plane for a road vehicle-mounted camera. We introduce a restrictive motion model exploiting several constraints arising from the construction of road vehicles, thus significantly reducing parameter space and increasing overall estimation robustness. The model enables estimation of relative camera pose by optimization of four parameters. By adding a fifth parameter additional estimation of the road plane normal in a joint optimization process is possible. The proposed algorithm has been tested in authentic traffic environments and its superiority is shown in comparison to existing methods.
Optical Light Curves of the Black Hole Binaries GRS 1124–68 and A0620–00 in Outburst: The Importance of Irradiation

We test whether the model proposed by Esin et al. to explain X-ray observations of the black hole soft X-ray transient GRS 1124-68 in outburst can also explain the optical light curves of a similar object, A0620-00. We show that to reproduce the observed X-ray to optical flux ratio in A0620-00, we need to assume X-ray irradiation of the outer disk that is significantly in excess of what is expected for a standard planar disk. With enhanced irradiation, the Esin et al. model can reproduce the optical evolution of A0620-00 in outburst very well. Though we find that optical observations of GRS 1124-68 also imply enhanced X-ray heating of the outer disk, the irradiation appears to be a factor of ~3 weaker in this system than in A0620-00. This is surprising, since GRS 1124-68 has a larger disk. We speculate that enhanced irradiation may be due to disk warping, and that the degree of warping differs between the two binaries.
Interactions-Based Models

This paper describes a range of methods which have been proposed to study interactions in economic and social contexts. By interactions, we refer to interdependences between individual decisions which are not mediated by markets. These types of models have been employed to understand phenomena ranging from the effect of neighborhoods on the life prospects of children to the evolution of political party platforms. We provide a general choice-based framework for modeling such interactions which subsumes a number of specific models which have been studied. This framework illustrates the relationship between interactions-based models and models in statistical mechanics. Our analysis is then extended to the econometrics of these models, with an emphasis on the identification of group-level influences on individual behavior. Finally, we review some of the empirical work on interactions which has appeared in the social science literature.
Analysis of boundary representation model rectification

Defects in boundary representation models often lead to system errors in modeling software and associated applications. This paper analyzes the model rectification problem of manifold boundary models, and argues that a rectify-by-reconstruction approach is needed in order to reach the global optimal solution. The restricted face boundary reconstruction problem is shown to be NP-hard. Based on this, the solid boundary reconstruction problem is also shown to be NP-hard.
Ozone Depletion from Nearby Supernovae

Estimates made in the 1970s indicated that a supernova occurring within tens of parsecs of Earth could have significant effects on the ozone layer. Since that time, improved tools for detailed modeling of atmospheric chemistry have been developed to calculate ozone depletion, and advances have been made also in theoretical modeling of supernovae and of the resultant gamma-ray spectra. In addition, we now have better knowledge of the occurrence rate of supernovae in the Galaxy and of the spatial distribution of progenitors to core-collapse supernovae. We report here the results of two-dimensional atmospheric model calculations that take as input the spectral energy distribution of a supernova, adopting various distances from Earth and various latitude impact angles. In separate simulations we calculate the ozone depletion due to both gamma rays and cosmic rays. We find that for the combined ozone depletion from these effects roughly to double the "biologically active" UV flux received at the surface of the Earth, the supernova must occur at ≲8 pc. Based on the latest data, the time-averaged Galactic rate of core-collapse supernovae occurring within 8 pc is ~1.5 Gyr-1. In comparing our calculated ozone depletions with those of previous studies, we find them to be significantly less severe than found by Ruderman and consistent with Whitten et al. In summary, given the amplitude of the effect, the rate of nearby supernovae, and the ~0.5 Gyr timescale for multicellular organisms on Earth, this particular pathway for mass extinctions may be less important than previously thought.
Noise model for car-embedded speech acquisition system design

Intelligent vehicles provide several speech-based advanced features, which success rely on the robustness of the speech acquired by the vehicle microphone system. This speech can be enhanced with a microphone array by means of spatial filtering, which design needs a reliable noise model to guarantee good filtering performance. Traditionally, it has been assumed that this noise is diffuse, but different measurements in real scenarios revel that the coherence of the noise is high to consider that is completely diffuse. In this paper, we suggest that the major contribution of the noise in a car can be reduced to a finite number of uncorrelated noise sources. We propose a searching algorithm to identify the position of the most uncorrelated sources, obtaining also their relative energy. This model allows to generate reliable synthetic noise based on real measurements, which can be very useful in the design of spatial filters.
Women Rule: Gendered Leadership and State Supreme Court Chief Justice Selection

ABSTRACT While women are underrepresented in many political institutions and leadership positions, nearly half of state supreme court chief justices are women. Is there something about the role of state supreme court justice that facilitates the recruitment of women to this important political position? We examine whether the selection of a woman chief is driven by the court’s institutional need for women’s leadership style or simply the supply of qualified justices. We find that ideological diversity drives demand for a woman chief. A supply of experienced women justices also has a significant impact on likelihood of selection.
Probability-one Homotopy Maps for Constrained Clustering Problems

Many algorithms for constrained clustering have been developed in the literature that aim to balance vector quantization requirements of cluster prototypes against the discrete satisfaction requirements of constraint (must-link or cannot-link) sets. A significant amount of research has been devoted to designing new algorithms for constrained clustering and understanding when constraints help clustering. However, no method exists to systematically characterize solution sets as constraints are gently introduced and how to assist practitioners in choosing a sweet spot between vector quantization and constraint satisfaction. A homotopy method is presented that can smoothly track solutions from unconstrained to constrained formulations of clustering. Beginning the homotopy zero curve tracking where the solution is (fairly) well-understood, the curve can then be tracked into regions where there is only a qualitative understanding of the solution set, finding multiple local solutions along the way. Experiments demonstrate how the new homotopy method helps identify better tradeoffs and reveals insight into the structure of solution sets not obtainable using pointwise exploration of parameters.
Reasoning about Situation Similarity

Conceptual modeling is viewed as a promising means to represent contextual knowledge, which may be enriched with semantics. Such modeling is capable of describing situations context, as well as, reasoning about it. Moreover, situational reasoning is attained taking into consideration similarity-based approaches. This paper proposes approximate reasoning about situations similarity using ontological modeling, description logics representation, and fuzzy logic inference rules
Nested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit Likelihood

We consider probabilistic multinomial probit classification using Gaussian process (GP) priors. The challenges with the multiclass GP classification are the integration over the non-Gaussian posterior distribution, and the increase of the number of unknown latent variables as the number of target classes grows. Expectation propagation (EP) has proven to be a very accurate method for approximate inference but the existing EP approaches for the multinomial probit GP classification rely on numerical quadratures or independence assumptions between the latent values from different classes to facilitate the computations. In this paper, we propose a novel nested EP approach which does not require numerical quadratures, and approximates accurately all between-class posterior dependencies of the latent values, but still scales linearly in the number of classes. The predictive accuracy of the nested EP approach is compared to Laplace, variational Bayes, and Markov chain Monte Carlo (MCMC) approximations with various benchmark data sets. In the experiments nested EP was the most consistent method with respect to MCMC sampling, but the differences between the compared methods were small if only the classification accuracy is concerned.
Are Analysts’ Loss Functions Asymmetric?

Despite displaying a statistically significant optimism bias, analysts' earnings forecasts are an important input to investors’ valuation models. Understanding the possible reasons for any bias is important if information is to be extracted from earnings forecasts and used optimally by investors. Extant research into the shape of analysts' loss functions explains optimism bias as resulting from analysts minimizing the mean absolute forecast error under symmetric, linear loss functions. When the distribution of earnings outcomes is skewed, optimalforecasts can appear biased. In contrast, research into analysts' economic incentives suggests that positive and negative earnings forecast errors made by analysts are not penalized or rewarded symmetrically, suggesting that asymmetric loss functions are an appropriate characterization. To reconcile these findings, we exploit results from economic theory relating to the Linex loss function to discriminate between the symmetric linear loss and the asymmetric loss explanations of analyst forecast bias. Under asymmetric loss functions optimal forecasts will appear biased even if earnings outcomes are symmetric. Our empirical results support the asymmetric loss function explanation. Further analysis also reveals that forecast bias varies systematically across firm characteristics that capture systematic variation in the earnings forecast error distribution.
DEVELOPING A PROTOCOL FOR THE CONVERSION OF RANK-BASED TAXON NAMES TO PHYLOGENETICALLY DEFINED CLADE NAMES, AS EXEMPLIFIED BY TURTLES

Abstract We present a rank-free phylogenetic nomenclature for 25 well-established ancient clades of living turtles. This is the first attempt to document fully the nomenclatural history of a clade with the intent of proposing a coherent nomenclatural system to replace the traditional rank-based nomenclature. Because of the imperative to retain connectivity to the literature for information retrieval, due consideration is given to balancing the desire to develop a consistent system against the desire to conserve traditional associations between names, taxa (i.e., clades), and characters. Novel issues and problems that emerged during this review include: the unclear name/clade association of traditional names; the creation of synonymy lists from which to choose a name; difficulties associated with selecting a single criterion for choosing among multiple ‘subjectively synonymous’ names; identifying authorship for a converted traditional name; and the potential loss of nomenclatural information due to ‘functional homonyms. ’ This work may provide a useful road map to those intent on converting their traditional rank-based nomenclatures to explicitly phylogenetic nomenclatures under the precepts of the PhyloCode.
The Interactive Dining Table, or Pass the Weather Widget, Please

Large-scale interactive surfaces are nearly ubiquitous in research labs and showrooms around the world today. However, unlike other recent interactive technologies such as smartphones, they have not yet found their way into people's everyday lives. Possible reasons include high cost as well as a lack of suitable applications. In this paper, we present our prototypical implementation of a low-cost, unobtrusive interactive surface, integrated with the dining table in a real-world living room. To motivate our approach, we explore three scenarios highlighting potential applications for our system and present their prototypical implementations. In the first scenario, we extend regular board games with interactive components without sacrificing their unique haptic experience. In the second scenario, we investigate ambient notifications which provide a method for delivering information to the users subconsciously. Finally, we explore the concept of augmented dining in which the appearance of food placed on the table is augmented or modified by the system.
Broadband Dual Polarized Space-Fed Antenna Arrays with High Isolation

This paper presents a novel design of dual polarized space-fed antenna arrays with broad bandwidth and high isolation between two orthogonal ports. The dual polarized space-fed antenna arrays are designed with bottom radiating element electromagnetically coupled to two orthogonal open microstrip lines and top parasitic elements excited by the radiation from bottom radiating element, without any feed network for array elements excitation. Two space-fed antenna arrays with 7 and 19 parasitic elements, respectively, have been designed for 5.8 GHz frequency band and their performances are analyzed. The dual polarized space-fed array with 19 parasitic elements has been fabricated, and its performance is measured. The measured impedance bandwidth is 10.7%, isolation ≥ 32 dB between two orthogonal ports over entire bandwidth, maximum gain of 17.8 dBi and cross-polar levels ≤− 29 dB.
An LSB Data Hiding Technique Using Prime Numbers

In this paper, a novel data hiding technique is proposed, as an improvement over the Fibonacci LSB data-hiding technique proposed by Battisti et al. (2006), First we mathematically model and generalize our approach. Then we propose our novel technique, based on decomposition of a number (pixel-value) in sum of prime numbers. The particular representation generates a different set of (virtual) bit-planes altogether, suitable for embedding purposes. They not only allow one to embed secret message in higher bit-planes but also do it without much distortion, with a much better stego-image quality, and in a reliable and secured manner, guaranteeing efficient retrieval of secret message. A comparative performance study between the classical least significant bit (LSB) method, the Fibonacci LSB data-hiding technique and our proposed schemes has been done. Analysis indicates that image quality of the stego-image hidden by the technique using Fibonacci decomposition improves against that using simple LSB substitution method, while the same using the prime decomposition method improves drastically against that using Fibonacci decomposition technique. Experimental results show that, the stego-image is visually indistinguishable from the original cover-image.
X-Ray Insights into Interpreting C IV Blueshifts and Optical/Ultraviolet Continua

We present 0.5–8.0 keV Chandra observations of six bright quasars that represent extrema in quasar emission-line properties—three quasars each with small and large blueshifts of the C IV emission line with respect to the systemic redshift of the quasars. Supplemented with seven archival Chandra observations of quasars that met our selection criteria, we investigate the origin of this emission-line phenomenon in the general context of the structure of quasars. We find that the quasars with the largest C IV blueshifts show evidence, from joint spectral fitting, for intrinsic X-ray absorption (NH ∼ 1022 cm-2). Given the lack of accompanying C IV absorption, this gas is likely to be highly ionized and may be identified with the shielding gas in the disk-wind paradigm. Furthermore, we find evidence for a correlation of αUV, the ultraviolet spectral index, with the hardness of the X-ray continuum; an analysis of independent Bright Quasar Survey data from the literature supports this conclusion. This result points to intrinsically red quasars having systematically flatter hard X-ray continua without evidence for X-ray absorption. We speculate on the origins of these correlations of X-ray properties with both C IV blueshift and αUV and discuss the implications for models of quasar structure.
GAMMA-RAY STUDIES OF BLAZARS: SYNCHRO-COMPTON ANALYSIS OF FLAT SPECTRUM RADIO QUASARS

We extend a method for modeling synchrotron and synchrotron self-Compton radiations in blazar jets to include external Compton (EC) processes. The basic model assumption is that the blazar radio through soft X-ray flux is nonthermal synchrotron radiation emitted by isotropically distributed electrons in the randomly directed magnetic field of outflowing relativistic blazar jet plasma. Thus, the electron distribution is given by the synchrotron spectrum, depending only on the Doppler factor δD and the mean magnetic field B, given that the comoving emission region size scale R′b ≲ cδDtv/(1 + z), where tv is the variability time and z is the source redshift. Generalizing the approach of Georganopoulos, Kirk, & Mastichiadis to arbitrary anisotropic target radiation fields, we use the electron spectrum implied by the synchrotron component to derive accurate Compton-scattered γ-ray spectra throughout the Thomson and Klein–Nishina regimes for EC scattering processes. We derive and calculate accurate γ-ray spectra produced by relativistic electrons that Compton-scatter (1) a point source of radiation located radially behind the jet, (2) photons from a thermal Shakura–Sunyaev accretion disk, and (3) target photons from the central source scattered by a spherically symmetric shell of broad-line region gas. The calculations of broadband spectral energy distributions from the radio through γ-ray regimes are presented, which include self-consistent γγ absorption on the same radiation fields that provide target photons for Compton scattering. The application of this baseline flat spectrum radio/γ-ray quasar model is considered in view of data from γ-ray telescopes and contemporaneous multiwavelength campaigns.
Improving Recommendation Accuracy by Considering Electronic Word-of-Mouth and the Effects of Its Propagation Using Collective Matrix Factorization

In recent years, recommender systems have become an important tool for increasing sales and revenues for many online retailers, such as Amazon and eBay. Many of these recommender systems predict a user's interest in the items or the products by using the browsing/shopping history or item rating records of the user. However, many research studies show that, before making a purchase, people often read on-line reviews and exchange their opinion with friends in their social circles. The resulting electronic word-of-mouth (eWOM) has huge impact on customer's final purchase or decision. Nonetheless, most of the recommender systems in the current literature do not consider eWOM, let alone the effect of its propagation. Therefore, we propose a new recommendation model based on the collective matrix factorization technique for predicting customer's preferences in this paper. Our model not only considers customers' personal taste, their trust relationships, but also the effect of eWOM propagation in their social networks. We conduct a series of experiments using real-life data crawled from Epinions and Amazon. Experimental results show that our model significantly outperforms other closely related models that do not consider eWOM propagation effects by 5%-13% in terms of both RMSE and MAE.
Integrating Computational Biology and Forward Genetics in Drosophila

Genetic screens are powerful methods for the discovery of gene–phenotype associations. However, a systems biology approach to genetics must leverage the massive amount of “omics” data to enhance the power and speed of functional gene discovery in vivo. Thus far, few computational methods for gene function prediction have been rigorously tested for their performance on a genome-wide scale in vivo. In this work, we demonstrate that integrating genome-wide computational gene prioritization with large-scale genetic screening is a powerful tool for functional gene discovery. To discover genes involved in neural development in Drosophila, we extend our strategy for the prioritization of human candidate disease genes to functional prioritization in Drosophila. We then integrate this prioritization strategy with a large-scale genetic screen for interactors of the proneural transcription factor Atonal using genomic deficiencies and mutant and RNAi collections. Using the prioritized genes validated in our genetic screen, we describe a novel genetic interaction network for Atonal. Lastly, we prioritize the whole Drosophila genome and identify candidate gene associations for ten receptor-signaling pathways. This novel database of prioritized pathway candidates, as well as a web application for functional prioritization in Drosophila, called Endeavour-HighFly, and the Atonal network, are publicly available resources. A systems genetics approach that combines the power of computational predictions with in vivo genetic screens strongly enhances the process of gene function and gene–gene association discovery.
Benchmarking Servers using Virtual Machines

Virtualization soware is oen used in enterprise on server machines to run virtual machines (VMs), each running a distinct server. is has many bene ts including exibility and lower hardware cost. is paper presents the results from conducting a performance evaluation of two comparable dual quad-core server machines, one from HP and another from Dell, both running VMWare ESX V3. e performance is measured using a series of independent benchmarks testing the performance of a le server, database server, web server, java server and email server. is multi-workload benchmark is used to evaluate the two server machines and how the di erent server workloads interact to better utilize the hardware resources.