Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance evaluation of handoff detection schemes

For successful handoff operation in cellular mobile telecommunication, the first and foremost concern is to detect the handoff requirement without significant delay. Various handoff procedures have been implemented over the years to minimize the delay in handoff detection in order to minimize interruptions in communication. It is known that each detection algorithm has its own characteristics and features to overcome specific problems for which it is designed. A new detection algorithm has been devised which can overcome the problem of handoffs to wrong cells. The performance of the proposed algorithm is evaluated and compared with a hysteresis based algorithm.
Applied Production Analysis

This book contains a modern treatment of production economics from a dual perspective, with special emphasis on recent developments. Results that were scattered throughout professional journals and monographs are now gathered into an integrated approach using a common notation. The book prepares the reader to apply the tools of the dual approach to real world problems and data sets. Particular care has been devoted to choosing topics for discussion that achieve this goal. Throughout the book there are worked examples and exercises, which are geared toward developing the reader's facility in using modern developments in production economics. Separate chapters are devoted to production, cost, and profit functions. Other topics include flexible functional forms, aggregation across inputs and outputs using the theory of separable structures, aggregation over economic optimizing firms, the representation of multioutput technologies, and the analysis and measurement of technical change from both a primal and a dual perspective.
Image segmentation by iterative parallel region growing with applications to data compression and image analysis

An iterative parallel segmentation algorithm, which avoids the problem of dependency on the order in which portions of the image are processed by performing the globally best merges first, is presented. The segmentation approach and two implementations of the approach on a massively parallel processor (MPP) are discussed. Application of the segmentation approach to data compression and image analysis is described, and results of the application are given for a Landsat thematic mapper image. <<ETX>>
Native and Non‐Native Teachers of English

Language teaching is a complex task that requires knowledge beyond language proficiency. It is obvious that one needs to know a language in order to teach it, but it is no less true that one needs to have pedagogical skills and metalinguistic awareness in order to take the adequate methodological decisions involved in language education. Keywords: Educational Linguistics; Identity; Language Teaching; Lingua Francas; Multilingualism; World Englishes
The Effects of Graphing Calculator use on High-School Students' Reasoning in Integral Calculus

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Low-power bit-serial Viterbi decoder for 3rd generation W-CDMA systems

This paper presents a low-power bit-serial Viterbi decoder chip with the coding rate r=1/3 and the constraint length K= 9 (256 states). This chip is targeted for high speed convolutional decoding for next generation wireless applications. The Add-Compare-Select (ACS) units have been designed using bit-serial arithmetic and a power efficient trace-back scheme and an application-specific memory have been developed for the trace-back operation. The chip was implemented using 0.5 /spl mu/m CMOS technology and is operative at 20 Mbps under 3.3 V and at 2 Mbps under 1.8 V. The power dissipation is only 9.8 mW at 2 Mbps operation under 1.8 V.
Topological Electronic Structure and Intrinsic Magnetization in 
MnBi4Te7
: A 
Bi2Te3
 Derivative with a Periodic Mn Sublattice

Combinations of non-trivial band topology and long-range magnetic order hold promise for realizations of novel spintronic phenomena, such as the quantum anomalous Hall effect and the topological magnetoelectric effect. Following theoretical advances material candidates are emerging. Yet, a compound with a band-inverted electronic structure and an intrinsic net magnetization remains unrealized. MnBi$_2$Te$_4$ is a candidate for the first antiferromagnetic topological insulator and the progenitor of a modular (Bi$_2$Te$_3$)$_n$(MnBi$_2$Te$_4$) series. For $n$ = 1, we confirm a non-stoichiometric composition proximate to MnBi$_4$Te$_7$ and establish an antiferromagnetic state below 13 K followed by a state with net magnetization and ferromagnetic-like hysteresis below 5 K. Angle-resolved photoemission experiments and density-functional calculations reveal a topological surface state on the MnBi$_4$Te$_7$(0001) surface, analogous to the non-magnetic parent compound Bi$_2$Te$_3$. Our results render MnBi$_4$Te$_7$ as a band-inverted material with an intrinsic net magnetization and a complex magnetic phase diagram providing a versatile platform for the realization of different topological phases.
Number interference in sentence processing

This thesis presents six eye-tracking experiments that investigate the time-course of similarity based interference caused by number congruency of two noun phrases. In addition, effects of number congruency were dissociated from effects of number attraction. Experiments 1 and 2 contrasted effects of number congruency in object-relative with subject relative clauses. Models of interference in sentence processing (Lewis & Vasishth, 2005; Van Dyke & Lewis, 2003; Van Dyke 2007) claim that object relatives clauses (1) are harder to understand than subject-relatives (2). According to these models, an interference effect arises at the verb (counted) for object relatives because there are two noun phrases (banker, accountant) in memory that have to be retrieved at the verb in contrast to only one for subject relatives (banker). In a cue-based retrieval account, the two noun phrases in object relatives should cause even more interference when they share the same retrieval cues. Thus, object relatives should be more difficult when the preceding noun phrases have the same number (either both singular like in (1a, 2a) or both plural) than when they have a different number (one singular and the other plural like in (1b)). Because both the relative clause effect and the number congruency effect are due to interference of the noun phrases when they are integrated with the verb (counted), both effects should occur at the same time. 1. (a) The banker that | the accountant helps | counted | the money | several times. (b) The bankers that | the accountant helps | counted | the money | several times. 2. (a) The banker that | helps the accountant | counted | the money | several
UAV-Enabled Covert Wireless Data Collection

This work considers unmanned aerial vehicle (UAV) networks for collecting data covertly from ground users. The full-duplex (FD) UAV intends to gather critical information from a scheduled user (SU) through wireless communication and generate artificial noise (AN) with random transmit power in order to ensure a negligible probability of the SU’s transmission being detected by the unscheduled users (USUs). To enhance the system performance, we jointly design the UAV’s trajectory and its maximum AN transmit power together with the user scheduling strategy subject to practical constraints, e.g., a covertness constraint, which is explicitly determined by analyzing each USU’s detection performance, and a binary constraint induced by user scheduling. The formulated design problem is a mixed-integer non-convex optimization problem, which is challenging to solve directly, but tackled by our developed penalty successive convex approximation (P-SCA) scheme. An efficient UAV trajectory initialization is also presented based on the successive hover-and-fly (SHAF) trajectory, which also serves as a benchmark scheme. Our examination shows the developed P-SCA scheme significantly outperforms the benchmark scheme in terms of achieving a higher max-min average transmission rate (ATR) from all the SUs to the UAV.
ENCORE: Ensemble Learning using Convolution Neural Machine Translation for Automatic Program Repair

Automated generate-and-validate (G&V) program repair techniques typically rely on hard-coded rules, only fix bugs following specific patterns, and are hard to adapt to different programming languages. We propose ENCORE, a new G&V technique, which uses ensemble learning on convolutional neural machine translation (NMT) models to automatically fix bugs in multiple programming languages. We take advantage of the randomness in hyper-parameter tuning to build multiple models that fix different bugs and combine them using ensemble learning. This new convolutional NMT approach outperforms the standard long short-term memory (LSTM) approach used in previous work, as it better captures both local and long-distance connections between tokens. Our evaluation on two popular benchmarks, Defects4J and QuixBugs, shows that ENCORE fixed 42 bugs, including 16 that have not been fixed by existing techniques. In addition, ENCORE is the first G&V repair technique to be applied to four popular programming languages (Java, C++, Python, and JavaScript), fixing a total of 67 bugs across five benchmarks.
Knotted proteins: Tie etiquette in structural
 biology

A small fraction of all protein structures characterized so far are entangled. The challenge of understanding the properties of these knotted proteins, and the why and the how of their natural folding process, has been taken up in the past decade with different approaches, such as structural characterization, in vitro experiments, and simulations of protein models with varying levels of complexity. The simplest among these are the lattice Gō models, which belong to the class of structure-based models, i.e., models that are biased to the native structure by explicitly including structural data. In this review we highlight the contributions to the field made in the scope of lattice Gō models, putting them into perspective in the context of the main experimental and theoretical results and of other, more realistic, computational approaches.
Two-dimensional plasmonic waveguides for nanolasing and four-wave mixing

Plasmonic waveguides are an essential element of nanoscale coherent sources, including nanolasers and four-wave mixing (FWM) devices. Here we report how the design of the plasmonic waveguide needs to be guided by the ultimate application. This contrasts with traditional approaches in which the waveguide is considered in isolation. We find that hybrid plasmonic waveguides, with a nonlinear material sandwiched between the metal substrate and a high-index layer, are best suited for FWM applications, whereas metallic wedges are preferred in nanolasers. We also find that in plasmonic nanolasers high-index buffer layers perform better than more traditional low-index buffers.
The trade-off between long-term memory and smoothness for recurrent networks

Training recurrent neural networks (RNNs) that possess long-term memory is challenging. We provide insight into the trade-off between the smoothness of the cost function and the memory retention capabilities of the network. We express both aspects in terms of the Lipschitz constant of the dynamics modeled by the network. This allows us to make a distinction between three types of regions in the parameter space. In the first region, the network experiences problems in retaining long-term information, while at the same time the cost function is smooth and easy for gradient descent to navigate in. In the second region, the amount of stored information increases with time and the cost function is intricate and full of local minima. The third region is in between the two other regions and here the RNN is able to retain long-term information. Based on these theoretical findings we present the hypothesis that good parameter choices for the RNN are located in between the well-behaved and the ill-behaved cost function regions. The concepts presented in the paper are illustrated by artificially generated and real examples.
On Deep Domain Adaptation: Some Theoretical Understandings

Compared with shallow domain adaptation, recent progress in deep domain adaptation has shown that it can achieve higher predictive performance and stronger capacity to tackle structural data (e.g., image and sequential data). The underlying idea of deep domain adaptation is to bridge the gap between source and target domains in a joint space so that a supervised classifier trained on labeled source data can be nicely transferred to the target domain. This idea is certainly intuitive and powerful, however, limited theoretical understandings have been developed to support its underpinning principle. In this paper, we have provided a rigorous framework to explain why it is possible to close the gap of the target and source domains in the joint space. More specifically, we first study the loss incurred when performing transfer learning from the source to the target domain. This provides a theory that explains and generalizes existing work in deep domain adaptation which was mainly empirical. This enables us to further explain why closing the gap in the joint space can directly minimize the loss incurred for transfer learning between the two domains. To our knowledge, this offers the first theoretical result that characterizes a direct bound on the joint space and the gain of transfer learning via deep domain adaptation
Microbiomes and Pathogen Survival in Crop Residues, an Ecotone Between Plant and Soil

The negative contribution of crop residues as a source of inoculum for plant diseases is well established. However, microbial ecologists have long reported positive effects of residues on the stability of agrosystems and conservation tillage practices have become increasingly widespread. Most studies have suggested that large microbial communities should be taken into account in plant disease management, but we know little about their ecological interaction with pathogens in the crop residue compartment. This review focuses on microbiomes associated with residues within the context of other microbial habitats in cereal-producing agroecosystems such as phyllosphere or rhizosphere. We connected residue microbiome with the survival of residue-borne fungal plant pathogens, thus combining knowledge in microbial ecology and epidemiology, two disciplines still not sufficiently connected. We provide an overview of the impact of residues on cereal disease epidemics and how dynamic interactions between microbial communities of nonburied residues during their degradation, along with soil and multitude of abiotic factors, can contribute to innovative disease management strategies, including next-generation microbiome-based biocontrol strategies. Starting from the classical but still relevant view of crop residues as a source of pathogen inoculum, we first consider possibilities for limiting the amount of residues on the soil surface to reduce the pathogen pressure. We then describe residues as a transient half-plant/half-soil compartment constituting a key fully fledged microbial ecosystem: in other words, an ecotone which deserves special attention. We focus on microbial communities, the changes in these communities over time and the factors influencing them. Finally, we discuss how the interactions between the microbial communities and the pathogens present on residues could be used: identification of keystone taxa and beneficial assemblages, then preservation of these taxa by adapted agronomic practices or development of synthetic communities, rather than the introduction of a single exogenous biocontrol species designed as a treatment product. [Formula: see text] Copyright © 2019 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
The FRB 121102 Host Is Atypical among Nearby Fast Radio Bursts

We search for host galaxy candidates of nearby fast radio bursts (FRBs), FRB 180729.J1316+55, FRB 171020, FRB 171213, FRB 180810.J1159+83, and FRB 180814.J0422+73 (the second repeating FRB). We compare the absolute magnitudes and the expected host dispersion measure DMhost of these candidates with that of the first repeating FRB, FRB 121102, as well as those of long gamma-ray bursts (LGRBs) and superluminous supernovae (SLSNe), the proposed progenitor systems of FRB 121102. We find that while the FRB 121102 host is consistent with those of LGRBs and SLSNe, the nearby FRB host candidates, at least for FRB 180729.J1316+55, FRB 171020, and FRB 180814.J0422+73, either have a smaller DMhost or are fainter than FRB 121102 host, as well as the hosts of LGRBs and SLSNe. In order to avoid the uncertainty in estimating DMhost due to the line-of-sight effect, we propose a galaxy-group-based method to estimate the electron density in the intergalactic regions, and hence, DMIGM. The result strengthens our conclusion. We conclude that the host galaxy of FRB 121102 is atypical, and LGRBs and SLSNe are likely not the progenitor systems of at least most nearby FRB sources. The recently reported two FRB hosts differ from the host of FRB 121102 and also the host candidates suggested in this paper. This is consistent with the conclusion of our paper and suggests that the FRB hosts are very diverse.
Classical proof of the classical soft graviton theorem in 
D>4

The classical soft graviton theorem gives an expression for the spectrum of low frequency gravitational radiation, emitted during a classical scattering process, in terms of the trajectories and spin angular momenta of ingoing and outgoing objects, including hard radiation. This has been proved to subleading order in the expansion in powers of the soft frequency by taking the classical limit of the quantum soft graviton theorem. In this paper we give a direct proof of this result by analyzing the classical equations of motion of a generic theory of gravity coupled to interacting matter in space-time dimensions larger than four.
Global Nash–Kuiper theorem for compact manifolds

We obtain global extensions of the celebrated Nash-Kuiper theorem for $C^{1,\theta}$ isometric immersions of compact manifolds with optimal Holder exponent. In particular for the Weyl problem of isometrically embedding a convex compact surface in 3-space, we show that the Nash-Kuiper non-rigidity prevails upto exponent $\theta<1/5$. This extends previous results on embedding 2-discs as well as higher dimensional analogues.
Effective theory for ultracold strongly interacting fermionic atoms in two dimensions

We propose a minimal theoretical model for the description of a two-dimensional (2D) strongly interacting Fermi gas confined transversely in a tight harmonic potential, and present accurate predictions for its equation of state and breathing mode frequency. We show that the minimal model Hamiltonian needs at least two independent interaction parameters, the 2D scattering length and effective range of interactions, in order to quantitatively explain recent experimental measurements at nonzero filling factor $N/N_{2D}$, where $N$ is the total number of atoms and $N_{2D}$ is the threshold number to reach the 2D limit. We therefore resolve in a satisfactory way the puzzling experimental observations of reduced equations of state and reduced quantum anomaly in breathing mode frequency, due to small yet non-negligible $N/N_{2D}$. We argue that a conclusive demonstration of the much-anticipated quantum anomaly is possible at a filling factor of a few percent. Our establishment of the minimal model for 2D ultracold atoms could be crucial to understanding the fermionic Berezinskii-Kosterlitz-Thouless transition in the strongly correlated regime.
Ab initiotheory of polarons: Formalism and applications

We develop a theoretical and computational framework to study polarons in semiconductors and insulators from first principles. Our approach provides the formation energy, excitation energy, and wavefunction of both electron and hole polarons, and takes into account the coupling of the electron or hole to all phonons. An important feature of the present method is that it does not require supercell calculations, and relies exclusively on electron band structures, phonon dispersions, and electron-phonon matrix elements obtained from calculations in the crystal unit cell. Starting from the Kohn-Sham (KS) equations of density-functional theory, we formulate the polaron problem as a variational minimization, and we obtain a nonlinear eigenvalue problem in the basis of KS states and phonon eigenmodes. In our formalism the electronic component of the polaron is expressed as a coherent superposition of KS states, in close analogy with the solution of the Bethe-Salpeter equation for the calculation of excitons. We demonstrate the power of the methodology by studying polarons in LiF and Li2O2. We show that our method describes both small and large polarons, and seamlessly captures Frohlich-type polar electron-phonon coupling and non-Frohlich coupling to acoustic and optical phonons. To analyze in quantitative terms the electron-phonon coupling mechanisms leading to the formation of polarons, we introduce spectral decompositions similar to the Eliashberg spectral function. We validate our theory using both analytical results and direct calculations on large supercells. This study constitutes a first step toward complete ab initio many-body calculations of polarons in real materials.
Agile modeling: effective practices for extreme programming and the unified process

In this innovative book, Scott Ambler reviews how to: 1. Model on an XP project without detracting from its fast-moving and agile software development approach. 2. Simplify the modeling disciplines/workflows of the UP without losing any of the true benefits of those disciplines. 3. Use modeling to explore an issue or to facilitate communication. 4. Effectively apply the UML, and extend it with other methodologies, to meet your real-world development needs. 5. Reduce the documentation burden on your project by writing agile documents. 6. Use simple modeling tools, such as index cards and whiteboards, and know when to use complex CASE tools. 7. Rethink your approach to work areas, modeling teams, and modeling sessions.
Semi-supervised acoustic model training for five-lingual code-switched ASR

This paper presents recent progress in the acoustic modelling of under-resourced code-switched (CS) speech in multiple South African languages. We consider two approaches. The first constructs separate bilingual acoustic models corresponding to language pairs (English-isiZulu, English-isiXhosa, English-Setswana and English-Sesotho). The second constructs a single unified five-lingual acoustic model representing all the languages (English, isiZulu, isiXhosa, Setswana and Sesotho). For these two approaches we consider the effectiveness of semi-supervised training to increase the size of the very sparse acoustic training sets. Using approximately 11 hours of untranscribed speech, we show that both approaches benefit from semi-supervised training. The bilingual TDNN-F acoustic models also benefit from the addition of CNN layers (CNN-TDNN-F), while the five-lingual system does not show any significant improvement. Furthermore, because English is common to all language pairs in our data, it dominates when training a unified language model, leading to improved English ASR performance at the expense of the other languages. Nevertheless, the five-lingual model offers flexibility because it can process more than two languages simultaneously, and is therefore an attractive option as an automatic transcription system in a semi-supervised training pipeline.