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The task of image-based virtual try-on aims to transfer a target clothing item onto the corresponding region of a person, which is commonly tackled by fitting the item to the desired body part and fusing the warped item with the person. While an increasing number of studies have been conducted, the resolution of synthesized images is still limited to low (e.g., 256x192), which acts as the critical limitation against satisfying online consumers. We argue that the limitation stems from several challenges: as the resolution increases, the artifacts in the misaligned areas between the warped clothes and the desired clothing regions become noticeable in the final results; the architectures used in existing methods have low performance in generating high-quality body parts and maintaining the texture sharpness of the clothes. To address the challenges, we propose a novel virtual try-on method called VITON-HD that successfully synthesizes 1024x768 virtual try-on images. Specifically, we first prepare the segmentation map to guide our virtual try-on synthesis, and then roughly fit the target clothing item to a given person's body. Next, we propose ALIgnment-Aware Segment (ALIAS) normalization and ALIAS generator to handle the misaligned areas and preserve the details of 1024x768 inputs. Through rigorous comparison with existing methods, we demonstrate that VITON-HD highly surpasses the baselines in terms of synthesized image quality both qualitatively and quantitatively. Code is available at https://github.com/shadow2496/VITON-HD., Comment: 21 pages; project page: https://psh01087.github.io/VITON-HD; accepted to CVPR 2021; code URL added, references formatted

Promoting the integration of modern high-tech and automobile design and manufacturing is an important development direction of China’s automobile design. Based on digital technology and additive manufacturing technology, this paper analyzes and studies the digital modeling and 3D printing application of all terrain vehicle. On the basis of market research and questionnaire quantitative analysis, the design direction and concept of bh1500uu all terrain vehicle are determined. Based on the modeling analysis of bh1500uu, this paper studies the digital modeling method and process of all terrain vehicle. By analyzing the modeling characteristics and advantages of rhino, alias and CATIA, this paper proposes a digital modeling solution for all terrain vehicle based on rhino, alias and CATIA. On this basis, it further proposes to apply additive manufacturing technology and 3D model printing to the design stage of all terrain vehicle to complete the design inspection and design optimization.

Most users have several Internet names. On Face-book or LinkedIn, for example, people usually appear with the real one. On other standard websites, like forums, people often use aliases to protect their real identities with respect to the other users, with no real privacy against the web site and the authorities. Aliases in the Dark Web are different: users expect strong identity protection.In this paper, we show that using both "open" aliases (aliases used in the standard Web) and Dark Web aliases can be dangerous per se. Indeed, we develop tools to link Dark Web to open aliases. For the first time, we perform a massive scale experiment on real scenarios. First between two Dark Web forums, then between the Dark Web forums and the standard forums. Due to a large number of possible pairs, we first reduce the search space cutting down the number of potential matches to a small set of candidates, and then on the selection of the correct alias among these candidates. We show that our methodology has excellent precision, from 87% to 94%, and recall around 80%.

This paper proposes a method for system realisation, where the realised system is described by a continuous-time, finite-duration impulse response. The proposed discrete-time implementation deploys Digital Alias-free Signal Processing. It means that despite the use of digital signal processing, the produced results do not suffer from aliasing. However, owing to the use of random sampling, the approach relies on constructing a suitable estimator of the system output. This paper shows that the proposed estimator is unbiased. It is also consistent, i.e. its variance goes to zero when the density of signal samples increasing. It is proven that under moderately restrictive assumptions, the estimator goes to zero proportionally to the fifth power of the average distance between the samples.

This chapter analyzes the narrative dimension of the interrogatories and testimonies included in the trial of Jupiter alias Gamelle, a twenty-five-year-old slave of the Cerer/Sereer nation who belonged to Jean-Charles de Pradel and was accused of running away and of theft by breaking and entering in French New Orleans in 1744. After having introduced the Superior Council of Louisiana and the judicial procedure, the chapter, probing Jupiter’s case, shows how court records can be exploited fruitfully in various ways despite their biases. Historians can piece together multiple layers of microevidence unintentionally scattered in the interrogatories and testimonies, and reconstruct the narratives of slaves’ life stories through their own experience. They can also analyze the narratives intentionally developed by enslaved defendants to defend themselves in front of judges.

Computed tomography (CT) screening is essential for early lung cancer detection. With the development of artificial intelligence techniques, it is particularly desirable to explore the ability of current state-of-the-art methods and to analyze nodule features in terms of a large population. In this paper, we present an artificial-intelligence lung image analysis system (ALIAS) for nodule detection and segmentation. And after segmenting the nodules, the locations, sizes, as well as imaging features are computed at the population level for studying the differences between benign and malignant nodules. The results provide better understanding of the underlying imaging features and their ability for early lung cancer diagnosis.

This paper introduces a non-uniform sub-sampling (NUSS) technique to relax the analog anti-aliasing filter design for mm-Wave receiver applications. By applying pre-designed periodic perturbation to the sub-sampling time instants, the unwanted spectral aliases, i.e., the integer multiples of the sampling frequency other than the carrier frequency, are spread out; hence undesired blocker aliasing at specific bands is significantly reduced. The NUSS technique effectively creates frequency notches during the sampling process that can be reconfigured simply by changing the NU perturbation sequence. A proof-of-concept NUSS receiver front-end is implemented in 28nm CMOS with 26.88GHz carrier frequency. Through spectral alias spreading, NUSS technique achieves 33dB alias rejection with 29mW power dissipation, which effectively creates notch filtering during sampling. The measured EVM is -25dB using a 200MHz 64QAM modulated signal in the presence of a 0dBc blocker.

Introducing a notion of the weighted mean sigma-r curvature and using the weighted Newton transformations we derive in this paper some integral formulae on weighted manifolds. These formulae generalize the flux formula and some of its examples of applications obtained by Alias, de Lira and Malacarne [3]., 15 pages

Hybrid particle-field molecular dynamics combines standard molecular potentials with density-field models into a computationally efficient methodology that is well-adapted for the study of mesoscale soft matter systems. Here, we introduce a new formulation based on filtered densities and a particle-mesh formalism that allows for Hamiltonian dynamics and alias-free force computation. This is achieved by introducing a length scale for the particle-field interactions independent of the numerical grid used to represent the density fields, enabling systematic convergence of the forces upon grid refinement. Our scheme generalizes the original particle-field molecular dynamics implementations presented in the literature, finding them as limit conditions. The accuracy of this new formulation is benchmarked by considering simple monoatomic systems described by the standard hybrid particle-field potentials. We find that by controlling the time step and grid size, conservation of energy and momenta, as well as disappearance of alias, is obtained. Increasing the particle-field interaction length scale permits the use of larger time steps and coarser grids. This promotes the use of multiple time step strategies over the quasi-instantaneous approximation, which is found to not conserve energy and momenta equally well. Finally, our investigations of the structural and dynamic properties of simple monoatomic systems show a consistent behavior between the present formulation and Gaussian core models.

The data collected from open source projects provide means to model large software ecosystems, but often suffer from data quality issues, specifically, multiple author identification strings in code commits might actually be associated with one developer. While many methods have been proposed for addressing this problem, they are either heuristics requiring manual tweaking, or require too much calculation time to do pairwise comparisons for 38M author IDs in, for example, the World of Code collection. In this paper, we propose a method that finds all author IDs belonging to a single developer in this entire dataset, and share the list of all author IDs that were found to have aliases. To do this, we first create blocks of potentially connected author IDs and then use a machine learning model to predict which of these potentially related IDs belong to the same developer. We processed around 38 million author IDs and found around 14.8 million IDs to have an alias, which belong to 5.4 million different developers, with the median number of aliases being 2 per developer. This dataset can be used to create more accurate models of developer behaviour at the entire OSS ecosystem level and can be used to provide a service to rapidly resolve new author IDs.

“He and She” (Он и Она) was published for the first time on 23 July 1882 by the magazine “Mirskoi Tolk”(Мирской толк). Two years later, in 1884, after undergoing some changes, it was published in the anthology “The Tales of Melpomene” (Сказки Мельпомены). Chekhov signed this work under the alias A. Chekhonte, which was derived from his surname. In the present short story we follow the conflictual relationship between a famous singer and her husband amidst the frantic pace of the the feasts and characters of the theatrical sphere. “Ele e Ela” (Он и Она) foi publicado pela primeira vez pela revista “Mirskói Tólk” (Мирской толк), em 23 de Julho de 1882. Dois anos mais tarde, em 1884 , foi publicado na coletânea “Contos de Melpômene” (Сказки Мельпомены) após sofrer algumas alterações. Tchékhov assinou essa obra utilizando um de seus pseudônimos, A. Tchekhonté, derivado de seu sobrenome. No presente conto acompanhamos o relacionamento conflituoso entre uma cantora famosa e seu marido em meio ao ritmo agitado dos banquetes e dos personagens da esfera teatral.

Second-order random walk is an important technique for graph analysis. Many applications use it to capture higher-order patterns in the graph, thus improving the model accuracy. However, the memory explosion problem of this technique hinders it from analyzing large graphs. When processing a billion-edge graph like Twitter, existing solutions (e.g., alias method) of the second-order random walk may take up 1796TB memory. Such high memory overhead comes from the memory-unaware strategies for node sampling across the graph. In this paper, to clearly study the efficiency of various node sampling methods in the context of second-order random walk, we design a cost model, and then propose a new node sampling method following the acceptance-rejection paradigm to achieve a better balance between memory and time cost. Further, to guarantee the efficiency of the second-order random walk within arbitrary memory budgets, we propose a memory-aware framework on the basis of the cost model. The framework applies a cost-based optimizer to assign desirable node sampling method for each node in the graph within a memory budget while minimizing the time cost. Finally, we provide general programming interfaces for users to benefit from the memory-aware framework easily. The empirical studies demonstrate that our memory-aware framework is robust with respect to memory and is able to achieve considerable efficiency by reducing 90% of the memory cost.

Data races occur when two threads fail to use proper synchronization when accessing shared data. In kernel file systems, which are highly concurrent by design, data races are common mistakes and often wreak havoc on the users, causing inconsistent states or data losses. Prior fuzzing practices on file systems have been effective in uncovering hundreds of bugs, but they mostly focus on the sequential aspect of file system execution and do not comprehensively explore the concurrency dimension and hence, forgo the opportunity to catch data races.In this paper, we bring coverage-guided fuzzing to the concurrency dimension with three new constructs: 1) a new coverage tracking metric, alias coverage, specially designed to capture the exploration progress in the concurrency dimension; 2) an evolution algorithm for generating, mutating, and merging multi-threaded syscall sequences as inputs for concurrency fuzzing; and 3) a comprehensive lockset and happens-before modeling for kernel synchronization primitives for precise data race detection. These components are integrated into Krace, an end-to-end fuzzing framework that has discovered 23 data races in ext4, btrfs, and the VFS layer so far, and 9 are confirmed to be harmful.

Malware is a prominent security threat and exposing malware behavior is a critical challenge. Recent malware often has payload that is only released when certain conditions are satisfied. It is hence difficult to fully disclose the payload by simply executing the malware. In addition, malware samples may be equipped with cloaking techniques such as VM detectors that stop execution once detecting that the malware is being monitored. Forced execution is a highly effective method to penetrate malware self-protection and expose hidden behavior, by forcefully setting certain branch outcomes. However, an existing state-of-the-art forced execution technique X-Force is very heavyweight, requiring tracing individual instructions, reasoning about pointer alias relations on-the-fly, and repairing invalid pointers by on-demand memory allocation. We develop a light-weight and practical forced execution technique. Without losing analysis precision, it avoids tracking individual instructions and on-demand allocation. Under our scheme, a forced execution is very similar to a native one. It features a novel memory pre-planning phase that pre-allocates a large memory buffer, and then initializes the buffer, and variables in the subject binary, with carefully crafted values in a random fashion before the real execution. The pre-planning is designed in such a way that dereferencing an invalid pointer has a very large chance to fall into the pre-allocated region and hence does not cause any exception, and semantically unrelated invalid pointer dereferences highly likely access disjoint (pre-allocated) memory regions, avoiding state corruptions with probabilistic guarantees. Our experiments show that our technique is 84 times faster than X-Force, has 6.5X and 10% fewer false positives and negatives for program dependence detection, respectively, and can expose 98% more malicious behaviors in 400 recent malware samples.

Alias resolution techniques (e.g., Midar) associate, mostly through active measurement, a set of IP addresses as belonging to a common router. These techniques rely on distinct router features that can serve as a signature. Their applicability is affected by router support of the features and the robustness of the signature. This paper presents a new alias resolution tool called Limited Ltd. that exploits ICMP rate limiting, a feature that is increasingly supported by modern routers that has not previously been used for alias resolution. It sends ICMP probes toward target interfaces in order to trigger rate limiting, extracting features from the probe reply loss traces. It uses a machine learning classifier to designate pairs of interfaces as aliases. We describe the details of the algorithm used by Limited Ltd. and illustrate its feasibility and accuracy. Limited Ltd. not only is the first tool that can perform alias resolution on IPv6 routers that do not generate monotonically increasing fragmentation IDs (e.g., Juniper routers) but it also complements the state-of-the-art techniques for IPv4 alias resolution. All of our code and the collected dataset are publicly available., Comment: Preprint to appear in Proceedings of Passive and Active Measurement (PAM 2020) Conference, Eugene, OR, March 2020

HD99458 was recently discovered to be a first object of its kind: a short-period eclipsing binary hosts a spotted, chemically peculiar A-type primary star that is a delta Scuti pulsator, and an M-dwarf secondary. These phenomena should not co-exist at the same time. Based on new photometric data we find that the previously published period of the main pulsation mode is a Nyquist alias of the true period (0.036 d, and not 0.052 d) given by the Kepler sampling.

Physical Unclonable Functions (PUFs) are modern solutions for cheap and secure key storage. The security level strongly depends on a PUF's unpredictability, which is impaired if certain bits of the PUF response tend towards the same value on all devices. The expectation for the probability of 1 at some position in the response, the Bit-Alias, is a state-of-the-art metric in this regard. However, the confidence interval of the Bit-Alias is never considered, which can lead to an overestimation of a PUF's unpredictability. Moreover, no tool is available to verify if the Bit-Alias is within given limits. This work adapts a method for the calculation of confidence intervals to Bit-Alias. It further proposes a statistical hypothesis test to verify if a PUF design meets given specifications on Bit-Alias or bit-wise entropy. Application to several published PUF designs demonstrates the methods' capabilities. The results prove the need for a high number of samples when the unpredictability of PUFs is tested. The proposed methods are publicly available and should improve the design and evaluation of PUFs in the future., Original publication at 2019 17th IEEE International New Circuits and Systems Conference (NEWCAS)

A multicarrier enabled subsampling baseband multiple-input-multiple-output system (MBS-MIMO) was proposed, which provides several advantages over the state-of-the-art solution using timing interleaved ADCs (TI-ADC) for high data-rate applications and allows massive parallelization in digital signal processing. This approach combines the known hybrid filter-bank architecture with discrete-multi-tone as a modulation scheme in an advantageous way. As a result, it was shown that multi-path propagation and alias introduced by subsampling can be seen as decoupled MIMO channels. To predict the system performance of MIMO systems, statistical models are widely used. The aim of the research is to accurately predict the system performance of the novel MBS-MIMO idea by means of statistical models. Since alias and multi-path propagation behave equally, known statistical models are extended regarding alias in this paper. A comparison of the signal-to-interference-and-noise-ratio (SINR) of both time domain and frequency domain models including alias subchannels is presented and demonstrates high consistency. Frequency domain calculations are many orders of magnitude faster and therefore suitable for system optimizations. It can be concluded, that extending the state of the art statistical models by means of alias is a valid approach.

In this paper, we present a novel method named RECON, that automatically identifies relations in a sentence (sentential relation extraction) and aligns to a knowledge graph (KG). RECON uses a graph neural network to learn representations of both the sentence as well as facts stored in a KG, improving the overall extraction quality. These facts, including entity attributes (label, alias, description, instance-of) and factual triples, have not been collectively used in the state of the art methods. We evaluate the effect of various forms of representing the KG context on the performance of RECON. The empirical evaluation on two standard relation extraction datasets shows that RECON significantly outperforms all state of the art methods on NYT Freebase and Wikidata datasets. RECON reports 87.23 F1 score (Vs 82.29 baseline) on Wikidata dataset whereas on NYT Freebase, reported values are 87.5(P@10) and 74.1(P@30) compared to the previous baseline scores of 81.3(P@10) and 63.1(P@30)., Comment: The Web Conference 2021 (WWW'21) full paper

Named Entity Disambiguation (NED) is a crucial task in many Natural Language Processing applications such as entity linking, record linkage, knowledge base construction, or relation extraction, to name a few. The task in NED is to map textual variations of a named entity to its formal name. It has been shown that parameter-less models for NED do not generalize to other domains very well. On the other hand, parametric learning models do not scale well when the number of formal names expands above the order of thousands or more. To tackle this problem, we propose a deep architecture with superior performance on NED and introduce a strategy to scale it to hundreds of thousands of formal names. Our experiments on several datasets for alias detection demonstrate that our system is capable of obtaining superior results with a large margin compared to other state-of-the-art systems.

The technology growth nowadays has made its way into the world of transportation by establishing smart vehicles and smarter vehicular transportation named Vehicular Ad-hoc networks (VANET). VANET gains its fame day by day by the way how it facilitates the efficient and safe transportation to the voyagers. However, the prime requirement of VANET is authentication. The main aim of the proposed work is to develop a practical and efficient pseudonymous authentication protocol which augments the conditional privacy preservation. Two-Way authentication is provided using local alias and global alias name. The alias name has offered to all the vehicles who register with the certification authority. The simulation result shows that the Two-Way protocol provides authentication with optimal packet delivery ratio (PDR), end-to-end delay and propagation delay.

Margaret Atwood’s Alias Grace (1997), a neo-Victorian classic biofictional novel about a nineteenth-century murderess, is interpreted in this chapter as a narrative of a madwoman, that is, a narrative which undercuts a possibility of a coherent representation of the self. Her “inability to speak”—fragmentation, instability and incompleteness of her narrative—is what makes it queer; its queerness is based in its refusal to be within the doctor-listener’s/reader’s grasp. Grace’s (mad) story, via its narrative “failure” to offer a linear, coherent account, becomes the epitome of queer subversiveness. The chapter also discusses the television adaptation of Atwood’s novel to examine alternative techniques used in the adaptive medium to express the instabilities and the incoherence of the self, and to diagnose Grace Marks of the television show as a (queer) madwoman.

As hordes of data-hungry devices challenge its current capabilities, Wi-Fi strikes back with 802.11be, alias Wi-Fi 7. This brand-new amendment promises a (r)evolution of unlicensed wireless connectivity as we know it. With its standardisation process being consolidated, we provide an updated digest of 802.11be essential features, vouching for multi-AP coordination as a must-have for critical and latency-sensitive applications. We then get down to the nitty-gritty of one of its most enticing implementations-coordinated beamforming-, for which our standard-compliant simulations confirm near-tenfold reductions in worst-case delays., Comment: 7 pages

Uncovering the Internet’s router graph is vital to accurate measurement and analysis. In this paper, we present a new technique for resolving router IP aliases that complements existing techniques. Our approach, Alias Pruning by Path Length Estimation (apple), avoids relying on router manufacturer and operating system specific implementations of IP. Instead, it filters potential router aliases seen in traceroute by comparing the reply path length from each address to a distributed set of vantage points.

This paper presents a simple method to design comb-based decimation filter. The goal is to get a low power design, while improving the comb alias rejection. The proposed structure has two stages. In the first stage is a comb filter in a nonrecursive form, and presented with its polyphase components. In the second stage is a comb filter cascaded with the modified combs. The cascade is also presented with the polyphase components. In that way the filters in the first stage are moved to the rate which is lesser than the high input rate, and which is determined by the decimation factor of the first stage. Similarly, the filters at second stage are moved to the rate which is M times time lesser than the high input rate, where M is a decimation factor. As a consequence, the proposed structure is a low power structure. The proposed method is compared with some methods from literature.

Zhu Xi 朱熹 (1130–1200) was a great philosopher, thinker, and educator in the Southern Song dynasty. His style name (zi 字) was Yuanhui 元晦, and his alias (hao 號) was Huian 晦庵. Zhu’s ancestral home was in Wu’yuan 婺源 County, Hui’zhou 徽州, while he was born in You’xi 尤溪 County.

The privacy policies, terms, and conditions of use in any Learning Management System (LMS) are one-way contracts. The institution imposes clauses that the student can accept or decline. Students, once they accept conditions, should be able to exercise the rights granted by the General Data Protection Regulation (GDPR). However, students cannot object to data processing and public profiling because it would be conceived as an impediment to teachers to execute their work with normality. Nonetheless, regarding GDPR and consulted legal advisors, a student could claim identity anonymization in the LMS, if adequate personal justifications are provided. Per contra, the current LMSs do not have any functionality that enables identity anonymization. This is a big problem that generates undesired situations which urgently requires a definitive solution. In this work, we surveyed students and teachers to validate the feasibility and acceptance of using aliases to anonymize their identity in LMSs as a sustainable solution to the problem. Considering the positive results, we developed a user-friendly plugin for Moodle that enables students’ identity anonymization by the use of aliases. This plugin, presented in this work and named Protected users, is publicly available online at GitHub and published under GNU General Public License. This work is carried out in the Doctorate Programme Formación en la Sociedad del Conocimiento de la Universidad de Salamanca [26–28]. The program is regulated by the Real Decreto 99/2011 [29].

The five-component Manakov system (alias 5-Manakov system) appears in many fields such as nonlinear optics, Bose–Einstein condensates (alias the spin-2 Gross–Pitaevskii equation), and ocean. In this Letter, we investigate the semi-rational vector rogon–soliton and soliton of the 5-Manakov system with mixed zero and non-zero backgrounds by using the modified Darboux transform. The key point is to explicitly solve the multiple roots of a sixth degree characteristic polynomial equation. In particular, we exhibit the wave structures of the fundamental semi-rational vector rogon with grey solitons and soliton solutions, and their higher-degree forms. Moreover, the semi-rational vector rogon with grey solitons corresponding to the components with non-zero backgrounds are P T -symmetric. These semi-rational wave structures will be useful to further understand some related physical phenomena and to design the relative experiments.

A maximal geodesic in a graph is a geodesic (alias shortest path) which is not a subpath of a longer geodesic. The geodesic-transversal problem in a graph G is introduced as the task to find a smallest set S of vertices of G such that each maximal geodesic has at least one vertex in S . The minimum cardinality of such a set is the geodesic-transversal number gt ( G ) of G . It is proved that gt ( G ) = 1 if and only if G is a subdivided star and that the geodesic-transversal problem is NP-complete. Fast algorithms to determine the geodesic-transversal number of trees and of spread cactus graphs are designed, respectively.

We establish here a method to partially recover the missing frequencies in data acquired through sub-sampling in the Fourier domain. Non-linear open and close operations are applied recursively to the raw spatial image estimated from its sparse Fourier samples. The mean of the open and closed images updates the estimated image after applying each structuring element (SE). The updated Fourier spectra are required at each stage to remain consistent with the known sample values. The SE size is incremented until the values estimated for the missing Fourier coefficients converge. The average image obtained from applying multiple sets of randomly selected SEs forms the final result. A denoising scheme is finally used to supplement the interpolated result. The denoising estimates the alias artefacts that arise from the initial sub-sampling by assuming that a narrow region around the borders of the reconstructed image has constant grey level. Convergence occurs in around 30 iterations that usually requires, in total a little less than one minute on a 64GB RAM, i7 machine. Since the computational complexity of the method is low, it can serve as a reliable initialization for more sophisticated iterative reconstruction schemes. Results for several simulated and real sub-sampled image data show an improvement of about 0.1 in Structural SIMilarity index (SSIM, whose maximum possible value is 1) in comparison to the raw inverse FFT image estimate. This method is more likely to underestimate the missing frequency values.

Implicit anti-aliasing is a remarkable property of continuous-time delta–sigma modulators employing a time-invariant loop filter. It turns out that weak nonlinearity of the operational transconductance amplifier (OTA) used in the input integrator, in conjunction with the DAC pulse shape and OTA parasitics can greatly degrade the alias rejection of the modulator. The authors report and analyze this hitherto undiscovered mechanism. The theory is borne out by measurement results from a fourth-order single-bit filtering delta–sigma modulator designed in a 65-nm CMOS process. The alias-rejection of the modulator, which is expected to be about 160dB, is degraded to around 70dB by weak OTA nonlinearity and OTA parasitics.

Nonregular fractional factorial designs such as Plackett-Burman designs and other orthogonal arrays are widely used in various screening experiments for their run size economy and flexibility. In this paper, we study matrix image theory and present a new method for distinguishing and assessing nonregular designs with complex alias structure, which works for all symmetrical and asymmetrical, regular and nonregular orthogonal arrays. Based on the matrix image theory, our proposed method captures orthogonality and projection properties. Empirical studies show that the proposed method has a more precise differentiation capacity when comparing with some other criteria.

Products of time-series signals have found wide-spread application in many fields of signal processing. For example, they are often used in modeling and compensating distortions generated by analog and mixed-signal components. Without excess bandwidth, the products of time-series signals will produce aliased artifacts that do not represent the physical phenomenology of the components being modeled. To ameliorate the effects of these potentially unwanted, aliased distortion products, we compare two multidimensional filters: the first is a simple one-dimensional (1-D) polyphase filter that is used to generate excess bandwidth; the second is a multidimensional (M-D) filter that is convolved with the time-series product. We demonstrate that the 1-D polyphase filter, although computationally simple, still produces unwanted aliasing when applied to signals near Nyquist rate, which can adversely affect modeling and/or compensation performance. By contrast, the M-D filter is computationally expensive, but is capable of most closely matching the ideal antialias filter response.

Salvet Lufti Tozan was a Turkish subject of Bosnian origin, bi-lingual in Serbian and Turkish, speaking French fluently. He has a dynamic character. All his life he appears to have been attracted by revolution and intrigue. Prior to and after the outbreak of the Second World War, several members of the British Embassy in Ankara, frequently were guests at the Tozan property, among them Commander Wolfson who enlisted Tozan’s support in the provision of naval and other intelligence. During the Second World War, Tozan was one of the most important Special Operation Executive’s agents in the Balkans. Our paper aim is to present his activity and especially his contacts with Iuliu Maniu. Keywords: Tozan, SOE, Intelligence, Istanbul, Chastelain.

Truman Capote’s self-proclaimed “nonfiction novel” In Cold Blood: A True Account of a Multiple Murder and Its Consequences (1965) and Margaret Atwood’s Alias Grace (1996), a fictional retelling of ...

The alias length pattern (ALP) was proposed to characterize the aliasing among two-factor interactions for regular two-level fractional factorial designs of resolution I V . Experimenters often pay more attention to joint estimation of main effects and some two-factor interactions. Hence, resolution I I I and I V designs are commonly used in practice. In this article, we first extend the ALP for regular two-level fractional factorial designs of resolution I I I and I V by modeling justification. Then we study the properties of the ALP and provide the relationships between the ALP and other popular criteria.

Historical fiction writers can be drawn to the true stories of women who have committed violent or criminal acts, as are readers. Margaret Atwood's Alias Grace and Hannah Kent's Burial Rites are po...

We know from the outset that Roscoe Hudson is a pen name, an alias for an academic who also authors pornography. Writing pornography, and writing about pornography, in fact both require the constru...