Miracle-dz/UniFAR-FTUs huggingface dataset:
Electromagnetic Radiation Field from a Flanged Rectangular Waveguide

In this paper, the radiation of an electromagnetic wave from a canged rectangular waveguide is exactly formulated by using the KP method when the waveguide is excited by TE- and TM-mode waves. The process of analysis is similar to [4]. The aelds in the waveguide and half-space are expanded in terms of the normal modes of the waveguide and the Weber-Schafheitlin (WS) discontinuous integrals, respectively. Imposing the continuity of the tangential components of the aelds on the aperture, we obtain a matrix equation to determine the expansion coeecients of the diaracted wave. The matrix elements are given by double inanite integrals and double inanite series which contain Bessel functions, and an eaective method for computing the double inanite series is proposed. Using the derived formula for the far diaracted aeld, the radiation patterns are computed for various kinds of parameters. 2. Statement of the problem Fig. 1 shows an open-ended canged rectangular waveguide and the related coordinate systems. We study the aeld E d radiated from the aperture to the half-space z> 0, when an electromagnetic wave E i in the waveguide are propagating in the positive z direction. The cange and waveguide are assumed to be perfectly conducting and the permittivity and permeability of the half-space（region I）are e1 and n1, respectively. The inside of the waveguide（region II） is alled with a homogeneous isotropic medium with parameters e2, n2, and the dimension of the guide is 2aC2b. The aperture and cange are located in the z = 0 plane. Because of the discontinuity of the geometry at z = 0, the recected wave of the incident wave and the higher-order mode waves are excited at the open end. In this analysis, the harmonic time dependence exp(j! t) is assumed and omitted throughout.
Three millennia of tonewood knowledge in Chinese guqin tradition: science, culture, value, and relevance for Western lutherie

The qin, also called guqin, is the most highly valued musical instrument in the culture of Chinese literati. Chinese people have been making guqin for over three thousand years, accumulating much lutherie knowledge under this uninterrupted tradition. In addition to being rare antiques and symbolic cultural objects, it is also widely believed that the sound of Chinese guqin improves gradually with age, maturing over hundreds of years. As such, the status and value of antique guqin in Chinese culture are comparable to those of antique Italian violins in Western culture. For guqin, the supposed acoustic improvement is generally attributed to the effects of wood aging. Ancient Chinese scholars have long discussed how and why aging improves the tone. When aged tonewood was not available, they resorted to various artificial means to accelerate wood aging, including chemical treatments. The cumulative experience of Chinese guqin makers represent a valuable source of tonewood knowledge, because they give us important clues on how to investigate long-term wood changes using modern research tools. In this review, we translated and annotated tonewood knowledge in ancient Chinese books, comparing them with conventional tonewood knowledge in Europe and recent scientific research. This retrospective analysis hopes to highlight the practical value of Chinese lutherie knowledge for 21st-century instrument makers.
Stability of Offshore Pipelines in Close Proximity to the Seabed

In traditional offshore pipeline design, the on-bottom stability of submarine pipelines is governed by the Morrison’s equations. According to this set of equations, offshore pipelines are designed to satisfy two stability conditions: the submerged weight of the pipe has to be greater than the lift force, and the horizontal frictional force should exceed the combined drag and inertia forces. It is common practice to used fixed hydrodynamic coefficients (drag, lift and inertia) to calculate the pipe stability, based on the assumption that the pipeline is either trenched or in contact with the seabed. However, due to uneven seabed topology and/or scouring, a gap may exist between the pipe and the seafloor. In such a case, the force coefficients not only depend on the relative gap between the pipe and the seabed. Moreover, in unsteady oscillatory flow (induced by waves), the timedependent laminar or turbulent characteristics of the boundary layer become important. In this paper, a computational fluid dynamics (CFD) model is presented to study onbottom stability of offshore pipelines in close proximity to the seabed. Numerical simulations of fluid flow are performed to evaluate the lift, drag and inertia forces exerted on a subsea pipeline when subjected to both steady current (tides) and oscillatory flow (waves). The evolution of the hydrodynamic coefficients with the relative gap between the pipe and the seafloor is investigated, and the effect of boundary proximity on the stability is revealed.
Evidence Fusion for Malicious Bot Detection in IoT

Billions of devices in the Internet of Things (IoT) are inter-connected over the internet and communicate with each other or end users. IoT devices communicate through messaging bots. These bots are important in IoT systems to automate and better manage the work flows. IoT devices are usually spread across many applications and are able to capture or generate substantial influx of big data. The integration of IoT with cloud computing to handle and manage big data, requires considerable security measures in order to prevent cyber attackers from adversarial use of such large amount of data. An attacker can simply utilize the messaging bots to perform malicious activities on a number of devices and thus bots pose serious cybersecurity hazards for IoT devices. Hence, it is important to detect the presence of malicious bots in the network. In this paper we propose an evidence theory-based approach for malicious bot detection. Evidence Theory, a.k. a. Dempster Shafer Theory (DST) is a probabilistic reasoning tool and has the unique ability to handle uncertainty, i.e. in the absence of evidence. It can be applied efficiently to identify a bot, especially when the bots have dynamic or polymorphic behavior. The key characteristic of DST is that the detection system may not need any prior information about the malicious signatures and profiles. In this work, we propose to analyze the network flow characteristics to extract key evidence for bot traces. We then quantify these pieces of evidence using apriori algorithm and apply DST to detect the presence of the bots.
Developments in Data Storage: Materials Perspective

Preface. Acknowledgments. 1. Introduction. 2.Fundamentals of Magnetism. 3. Longitudinal Recording Media. 4. Perpendicular Recording Medium. 5. Writer heads Fundamentals. 6. Magneto-resistive Read Heads: Fundamentals and Functionality. 7. Read sensors for over 1 Terabits per square inch. 8. Thin film media Lubricants: Structure, Characterization and Performance. 9. Overcoat Materials for Magnetic Recording Media. 10. Heat Assisted Magnetic Recording. 11. L lo FePt for Magnetic Recording Media Applications. 12. Patterned Magnetic Recording Media: Progress and Prospects. 13. Phase Change Random Access Memory. 14. Non-volatile Solid State Magnetic Memory.
Denotational Semantics: The Scott-Strachey Approach to Programming Language Theory

From the Publisher: "First book-length exposition of the denotational (or `mathematical' or `functional') approach to the formal semantics of programming languages (in contrast to `operational' and `axiomatic' approaches). Treats various kinds of languages, beginning with the pure-lambda-calculus and progressing through languages with states, commands, jumps, and assignments. This somewhat discursive account is a valuable compilation of results not otherwise available in a single source. " -- American Mathematical Monthly
Le modèle "monomaniaque" un modèle statistique simple pour l'analyse exploratoire d'un corpus de textes

Regrouper les elements d'un corpus de textes en segments thematiquement apparentes est un probleme d'analyse exploratoire complexe. On explore dans cette communication les performances d'un modele statistique simple, le modele "monomaniaque". On decrit le modele et sa procedure d'ajustement puis on illustre sa performance sur un probleme de segmentation d'un corpus de textes anglais relatifs au CKM ("Customer Knowledge Management").
Markerless 3D reconstruction of temporally deforming surfaces from multiple cameras

3D content generation is a major challenge in computer graphics, and generating realistic objects with timevarying shape and motion is a big part of creating realistic virtual environments. An attractive approach for generating content is to acquire the shape of real objects using computer vision techniques. Capturing the real world avoids the complexity of mathematical simulation as well as the time-consuming and difficult process of creating content manually. Traditional acquisition methods, such as range scanning, work well for static objects. However, temporally deformable objects like garments and human faces pose greater challenges. Here, the capture process must reconstruct both the time-varying shape as well as the motion of the object. Additionally, per-frame texture maps should be acquired for realistic rendering. Previous methods contain various limitations, such as the use of structured illumination patterns, or hand-placed markers on the surface in order to guide the reconstruction. Placing markers on garments limits the types of garments that can be captured. Both markers and structured light on human faces limit the ability to capture high-quality per-frame texture maps, which are essential for reconstructing performance-specific details such as sweating, wrinkles and blood flow. In this thesis we propose new, entirely passive techniques for advancing the state-of-the-art in 3D reconstruction of temporally deformable surfaces. We reconstruct high-resolution, temporally compatible geometry using multiple video cameras, without the need for either markers or structured light patterns. This thesis contains several contributions, both in computer graphics as well as computer vision. We start with new methods for multi-camera calibration and synchronization, which allow us to employ inexpensive consumer video cameras for reconstruction. We also present a novel technique for multi-view stereo reconstruction, capable of building high-resolution geometric meshes from a number of images. Finally, we combine these ideas and provide two inexpensive solutions for high-resolution 3D reconstruction of temporally deforming surfaces without the need for markers. The first is an application for capturing the shape and motion of garments, and the second is a new method for acquiring facial performances of actors. These new techniques have the potential for high impact in the film and video game industries.
Computational Prediction of Gene Function From High-throughput Data Sources

Computational Prediction of Gene Function from High-throughput Data Sources Sara Mostafavi Doctor of Philosophy Graduate Department of Computer Science University of Toronto 2011 A large number and variety of genome-wide genomics and proteomics datasets are now available for model organisms. Each dataset on its own presents a distinct but noisy view of cellular state. However, collectively, these datasets embody a more comprehensive view of cell function. This motivates the prediction of function for uncharacterized genes by combining multiple datasets, in order to exploit the associations between such genes and genes of known function–all in a query-specific fashion. Commonly, heterogeneous datasets are represented as networks in order to facilitate their combination. Here, I show that it is possible to accurately predict gene function in seconds by combining multiple large-scale networks. This facilitates function prediction on-demand, allowing users to take advantage of the persistent improvement and proliferation of genomics and proteomics datasets and continuously make up-to-date predictions for large genomes such as humans. Our algorithm, GeneMANIA, uses constrained linear regression to combine multiple association networks and uses label propagation to make predictions from the combined network. I introduce extensions that result in improved predictions when the number of labeled examples for training is limited, or when an ontological structure describing a hierarchy of gene function categorization scheme is available. Further, motivated by our empirical observations on predicting node labels for general networks, I propose a new label propagation algorithm that exploits common properties of real-world networks to
Reducing uncertainty in nitrogen budgets for African livestock systems

Livestock is poorly represented in N budgets for the African continent although some studies have examined livestock-related N flows at different levels. Livestock plays an important role in N cycling and therefore on N budgets including livestock-related flows. This study reviews the literature on N budgets for Africa to identify factors contributing to uncertainties. Livestock densities are usually modelled because of the lack of observational spatial data. Even though feed availability and quality varies across seasons, most studies use constant livestock excretion rates, and excreta are usually assumed to be uniformly distributed onto the land. Major uncertainties originate in the fraction of manure managed, and emission factors which may not reflect the situation of Africa. N budgets use coarse assumptions on production, availability, and use of crop residues as livestock feed. No flows between croplands–livestock and rangelands reflect the lack of data. Joint efforts are needed for spatial data collection of livestock data, crowdsourcing appears to be a promising option. The focus of the assessment of N budgets must go beyond croplands to include livestock and crop–livestock flows. We propose a nested systems definition of livestock systems to link local, regional level, and continental level and to increase the usefulness of point measurements of N losses. Scientists working at all levels should generate data to calibrate process-based models. Measurements in the field should not only concentrate on greenhouse gas emissions, but need to include crop and livestock production measurements, soil stock changes and other N loss pathways such as leaching, run-off and volatilization to assess management practices and trade-offs. Compared to the research done in other continents on N flows in livestock systems, there are few data for Africa, and therefore concerted effort will be needed to generate sufficient data for modelling.
Model Based Inference in the Life Sciences: A Primer on Evidence by ANDERSON, D. A.

Successful mathematical modeling requires the ability to formulate a mathematical description of the phenomenon of interest as well as to apply appropriate tools to glean results from the model. An effective modeling text must give attention to developing both of these abilities. The intriguing, wellwritten book by van Groesen and Molenaar is successful in both respects. Authors of modeling texts must decide whether to present mathematical concepts through a series of case studies, or whether to present mathematical principles in and of themselves and then apply them in examples. Van Groesen and Molenaar make the latter choice. Their philosophy (described in the preface) is that the case study approach “could disappoint the student, since having digested many particular models does not guarantee that one knows how to proceed when confronted with a new situation. ” Thus, they have written a text that highlights mathematical concepts relevant to the formulation and analysis of models. In contrast to modeling texts such as Fowler (1997) and Howison (2005), case studies do not play a central role. The exposition of general principles is peppered with examples; only at the conclusion of the book do the authors present full modeling case studies. The book is based on material originally developed for advanced undergraduates at the University of Twente, and is published by SIAM. Excluding a few minor editing issues (for instance, I noticed that the notation in some figures and figure captions was not consistent with that used in the body of the text) the book lives up to the high production standard
Practical small animal MRI.

Preface. 1. Physics. Section 1. Comparative Imaging ( Patrick R. Gavin ) Section 2. Basic Physics ( Patrick R. Gavin ). Section 3. Sequence Selection ( Patrick R. Gavin ). Section 4. Artifacts ( Patrick R. Gavin ). Section 5. Equipment Consideration and Selection ( Patrick R. Gavin ). 2. Veterinary Clinical Magnetic Resonance Imagin. Section 1. Diagnosis of Intracranial Disease ( Rodney S. Bagley, Patrick R. Gavin, and Shannon P. Holmes ). Section 2. Diagnosis of Spinal Disease ( Rodney S. Bagley, Patrick R. Gavin, and Shannon P. Holmes ). Section 3. Magnetic Resonance Imaging of Peripheral Nerve Disease ( Rodney S. Bagley, Patrick R. Gavin, and Shannon P. Holmes ). 3. Orthopedic ( Patrick R. Gavin and Shannon P. Holmes ). 4. Magnetic Resonance Imaging of Abdominal Disease ( Patrick R. Gavin and Shannon P. Holmes ). 5. Thorax ( Patrick R. Gavin and Shannon P. Holmes ). 6. Head-Non-CNS ( Patrick R. Gavin and Shannon P. Holmes ). 7. Cancer Imaging ( Susan L. Kraft ). Index.
Finite Element Breast Simulation for Sonography Image Registration

In case of female breast cancer, a breast conserving excision is often necessary. For this purpose, information from multiple medical imaging techniques have to be combined. Sonography imaging is essential for dense breast tissue and the only medical imaging technique available during surgery. During sonography of the outer breast quadrants the woman is usually in contralateral posterior oblique position, being in supine orientation while holding her ipsilateral arm over the head. Thus, these images cannot be directly registered with MRI or mammography images because these imaging technologies are performed in other patient positions with hands on the side of the body. Thus, we present a novel Finite Element approach how to enable a sonography image registration by showing the first time how to transfer the supine position with the arm straight on side into a supine position with the ipsilateral arm over the head which can be used to include information from MRI or mammography images. This approach is shown and validated with 3D scanner breast surface data as proof of concept. When comparing the simulation result with a 3D surface scan in supine orientation with the arm over the head, a mean surface distance error of 1.57 mm is achieved.
Modeling protein families using probabilistic suffix trees

proteins which await analysis. We present a method for modeling protein families by means of probabilistic suffix trees (PSTs). The method is based on identifying significant patterns in a set of related protein sequences. The input sequences do not need to be aligned, nor is delineation of domain boundaries required. The method is automatic, and can be applied, without assuming any preliminary biological information, with surprising success. Incorporating basic biological considerations such as amino acid background probabilities, and amino acids substitution probabilities can improve the performance in some cases. The PST can serve as a predictive tool for protein sequence classification, and for detecting conserved patterns (possibly functionally or structurally important) within protein sequences. The method was tested on one of the state of the art databases of protein families, namely, the Pfam database of HMMs, with satisfactory performance. Generally, the existing approaches can be divided into those based on short conserved motifs (e.g. [Bairoch et al. 1997, Attwood et al. 1998, Henikoff & Henikoff 19911) and those which are based on whole domains (e.g. [Sonnhammer & Kahn 1994, Sonnhammer et al. 19981). The manually defined patterns in PROSITE have served as an excellent seed for several such works. The methods used to represent these motifs and domains vary, and among the most popular forms are the consensus patterns [Bairoch et al. 1997, Attwood et al. 19981, the position-specific scoring matrices (profiles) [Gribskov et al. 1987, Henikoff & Henikoff 19911 and the HMMs [Krogh et al. 19961. These forms differ in their mathematical complexity, as well as in their sensitivity/selectivity.
A Multimodal Target-Source Classifier With Attention Branches to Understand Ambiguous Instructions for Fetching Daily Objects

In this study, we focus on multimodal language understanding for fetching instructions in the domestic service robots context. This task consists of predicting a target object, as instructed by the user, given an image and an unstructured sentence, such as “Bring me the yellow box (from the wooden cabinet). ” This is challenging because of the ambiguity of natural language, i.e., the relevant information may be missing or there might be several candidates. To solve such a task, we propose the multimodal target-source classifier model with attention branches (MTCM-AB), which is an extension of the MTCM. Our methodology uses the attention branch network (ABN) to develop a multimodal attention mechanism based on linguistic and visual inputs. Experimental validation using a standard dataset showed that the MTCM-AB outperformed both state-of-the-art methods and the MTCM. In particular, the MTCM-AB accuracy was 90.1% on average while human performance was 90.3% on the PFN-PIC dataset.
Examining Overreaction in BSE using Event Study Approach for Stock Split Announcements

If stock market shows abnormal price movement because of any news or event followed by a correction in reverse direction can be evidenced as market overreaction. The question of whether or not Indian stock prices market say BSE (Bombay Stock Exchange) is overreacted during any stock-specific news is best answered by a comprehensive and concurrent analysis of the various tests and data available while using the event study, like stock and market-specific data. The present study would deviate from the previous findings in various ways. Earlier studies document that prediction capability is more in the case of larger firms (Lev and Penman, 1990). The question nurtured by this study is based on the opinion that small firms (being less experimental) may have a better chance of attracting reaction of the rare event of stock split announcement than a large firm which is always monitored any type of market condition. We find how the smaller firms and larger firm’s overreaction vary with market condition or market uncertainty or volatility to firm-specific news. Finally, we want to address the impact of size, volatility and asymmetry in the terms of investors’ overreaction to the firm-specific news not only individually but also jointly of size and volatility, size and news and news and volatility. The outcome of this study helps to solve the problem concerning the extent to which stock split announcements have informational content, and whether the investors are affected by the signals. It may so happen that market-players act differently to stock split announcements during different market volatility conditions of various firms of various sizes in different firmspecific newsgood, bad or no news. It also answers the way of reaction for the case of small vs. large firms in the most advantageous manner. The present study substantiates the policy recommendation for the market players as well as for the analysts in estimating stock split announcement events under different market condition and different market capitalization value of the firm. Field of Research: Finance (Asset Pricing) JEL Code: G12