Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance of TCP/IP Using ATM ABR and UBR Services over Satellite Networks

We study the buffering requirements for zero cell loss for TCP/IP over satellite links using the available bit rate (ABR) and unspecified bit rate (UBR) services of asynchronous transfer mode (ATM) networks. For the ABR service, we explore the effect of feedback delay (a factor which depends upon the position of the bottleneck), the switch scheme used, and background variable bit rate (VBR) traffic. It is shown that the buffer requirement for TCP over ABR is independent of the number of TCP sources, but depends on the aforementioned factors. For the UBR service, we show that the buffer requirement is the sum of the TCP receiver window sizes. We substantiate our arguments with simulation results.
Pseudocodeword weights for non-binary LDPC codes

Pseudocodewords of q-ary LDPC codes are examined and the weight of a pseudocodeword on the q-ary symmetric channel is defined. The weight definition of a pseudocodeword on the AWGN channel is also extended to two-dimensional q-ary modulation such as q-PAM and q-PSK. The tree-based lower bounds on the minimum pseudocodeword weight are shown to also hold for q-ary LDPC codes on these channels
Pricing Virtual Paths with Quality-of-Service Guarantees as Bundle Derivatives

We describe a model of a communication network that allows us to price complex network services as financial derivative contracts based on the spot price of the capacity in individual routers. We prove a theorem of a Girsanov transform that is useful for pricing linear derivatives on underlying assets, which can be used to price many complex network services, and it is used to price an option that gives access to one of several virtual channels between two network nodes, during a specified future time interval. We give the continuous time hedging strategy, for which the option price is independent of the service providers attitude towards risk. The option price contains the density function of a sum of lognormal variables, which has to be evaluated numerically.
Anusaaraka: Machine Translation in Stages

Fully-automatic general-purpose high-quality machine translation systems (FGH-MT) are extremely difficult to build. In fact, there is no system in the world for any pair of languages which qualifies to be called FGH-MT. The reasons are not far to seek. Translation is a creative process which involves interpretation of the given text by the translator. Translation would also vary depending on the audience and the purpose for which it is meant. This would explain the difficulty of building a machine translation system. Since, the machine is not capable of interpreting a general text with sufficient accuracy automatically at present - let alone re-expressing it for a given audience, it fails to perform as FGH-MT. FOOTNOTE{The major difficulty that the machine faces in interpreting a given text is the lack of general world knowledge or common sense knowledge. }
Soundness, idempotence and commutativity of set-sharing

It is important that practical data-flow analyzers are backed by reliably proven theoretical results. Abstract interpretation provides a sound mathematical framework and necessary generic properties for an abstract domain to be well-defined and sound with respect to the concrete semantics. In logic programming, the abstract domain Sharing is a standard choice for sharing analysis for both practical work and further theoretical study. In spite of this, we found that there were no satisfactory proofs for the key properties of commutativity and idempotence that are essential for Sharing to be well-defined and that published statements of the soundness of Sharing assume the occurs-check. This paper provides a generalization of the abstraction function for Sharing that can be applied to any language, with or without the occurs-check. Results for soundness, idempotence and commutativity for abstract unification using this abstraction function are proven.
Using Wireless Sensor Networks to Narrow the Gap Between Low-Level Information and Context-Awareness

Wireless sensor networks are finally becoming a reality. In this paper, we present a scalable architecture for using wireless sensor networks in combination with wireless Ethernet networks to provide a complete end-to-end solution to narrow the gap between the low-level information and context awareness. We developed and implemented a complete proximity detector in order to give a wearable computer, such as a PDA, location context. Since location is only one element of contextawareness, we pursued utilizing photo sensors and temperature sensors in learning as much as possible about the environment. We used the TinyOS RF Motes as our test bed WSN (Wireless Sensor Network), 802.11 compatible hardware as our wireless Ethernet network, and conventional PCs and wired 802.3 networks to build the upper levels of the architecture.
Text Segmentation Based on Similarity between Words

This paper proposes a new indicator of text structure, called the lexical cohesion profile (LCP), which locates segment boundaries in a text. A text segment is a coherent scene; the words in a segment are linked together via lexical cohesion relations. LCP records mutual similarity of words in a sequence of text. The similarity of words, which represents their cohesiveness, is computed using a semantic network. Comparison with the text segments marked by a number of subjects shows that LCP closely correlates with the human judgments. LCP may provide valuable information for resolving anaphora and ellipsis.
Scheduling for Stable and Reliable Communication over Multiaccess Channels and Degraded Broadcast Channels

Information-theoretic arguments focus on modeling the reliability of information transmission, assuming availability of infinite data at sources, thus ignoring randomness in message generation times at the respective sources. However, in information transport networks, not only is reliable transmission important, but also stability, i.e., finiteness of mean delay incurred by messages from the time of generation to the time of successful reception. Usually, delay analysis is done separately using queueing-theoretic arguments, whereas reliable information transmission is studied using information theory. In this thesis, we investigate these two important aspects of data communication jointly by suitably combining models from these two fields. In particular, we model scheduled communication of messages, that arrive in a random process, (i) over multiaccess channels, with either independent decoding or joint decoding, and (ii) over degraded broadcast channels. The scheduling policies proposed permit up to a certain maximum number of messages for simultaneous transmission. In the first part of the thesis, we develop a multi-class discrete-time processor-sharing queueing model, and then investigate the stability of this queue. In particular, we model the queue by a discrete-time Markov chain defined on a countable state space, and then establish (i) a sufficient condition for $c$-regularity of the chain, and hence positive recurrence and finiteness of stationary mean of the function $c$ of the state, and (ii) a sufficient condition for transience of the chain. These stability results form the basis for the conclusions drawn in the thesis.
Obesity Model in White Male Wistar Rats: The Impact of Moringa (Moringa Oleifera) Flower Extract on Pancreatic Function as Deduced from Serum Amylase and Lipase Levels and the Histopathological Image of the Pancreas

Diabetes and obesity go hand in hand. Antidiabetic drugs are effective in treating diabetes. However, currently available antidiabetic drugs are too expensive, do not work, and cause major side effects. A significant therapeutic option for Diabetes Mellitus and obesity is using bioactive chemicals produced by plants. This compound is efficacious, easily accessible, safe, and affordable. The main aim of this study was to determine whether pancreatic extract from Moringa oleifera flowers affected blood amylase and lipase levels, as well as the histological appearance, of obese male Wistar white rats (Rattus norvegicus). This is a True experimental study, with the research design used as a test control Group Design. The research data was then analyzed with the help of SPSS using ANOVA and Post Hoc Test with LSD technique. This researcher used 24 male rats. Treatment with Moringa oleifera flower extract improves pancreatic function in obese Wistar white rats by reducing serum lipase and amylase levels. The results of research on serum lipase and amylase levels showed that a dose of 600mg/Kg BW improved pancreatic function in white rats of the Wistar strain that were obese.
On Quantum Cellular Automata

In recent work [quant-ph/0405174] by Schumacher and Werner was discussed an abstract algebraic approach to a model of reversible quantum cellular automata (CA) on a lattice. It was used special model of CA based on partitioning scheme and so there is a question about quantum CA derived from more general, standard model of classical CA. In present work is considered an approach to definition of a scheme with "history", valid for quantization both irreversible and reversible classical CA directly using local transition rules. It is used language of vectors in Hilbert spaces instead of C*-algebras, but results may be compared in some cases. Finally, the quantum lattice gases, quantum walk and "bots" are also discussed briefly.
Gowers uniformity, influence of variables, and PCPs

We return to the study of the relation of query complexity and soundness in probabilistically checkable proofs.We present a PCP verifier for languages that are Unique-Games-Hard and such that the verifier makes q queries, has almost perfect completeness, and has soundness error at most 2q/2q+ε, for arbitrarily small ε>0. For values of q of the form 2t-1, the soundness error is (q+1)/2q+ε. Charikar et al. show that there is a constant c such that for every language that has a verifier of query complexity q, and a ratio of soundness error to completeness smaller than cq/2q is decidable in polynomial time. Up to the value of the multiplicative constant and to the validity of the Unique Games Conjecture, our result is therefore tight.As a corollary, we show that approximating the Maximum Independent Set problem in graphs of degree Δ within a factor better than Δ/(log Δ)c is Unique-Games-Hard for a certain constant c>0.Our main technical results are (i) a connection between the Gowers uniformity of a Boolean function and the influence of its variables and (ii) the proof that "Gowers uniform" functions pass the "hypergraph linearity test" approximately with the same probability of a random function. The connection between Gowers uniformity and influence might have other applications.
Acquiring lexical paraphrases from a single corpus

This paper studies the potential of identifying lexical paraphrases within a single corpus, focusing on the extraction of verb paraphrases. Most previous approaches detect individual paraphrase instances within a pair (or set) of comparable corpora, each of them containing roughly the same information, and rely on the substantial level of correspondence of such corpora. We present a novel method that successfully detects isolated paraphrase instances within a single corpus without relying on any a-priori structure and information. A comparison suggests that an instance-based approach may be combined with a vector based approach in order to assess better the paraphrase likelihood for many verb pairs.
Dynamic 3-Coloring of Claw-free Graphs

A {\it dynamic $k$-coloring} of a graph $G$ is a proper $k$-coloring of the vertices of $G$ such that every vertex of degree at least 2 in $G$ will be adjacent to vertices with at least 2 different colors. The smallest number $k$ for which a graph $G$ can have a dynamic $k$-coloring is the {\it dynamic chromatic number}, denoted by $\chi_d(G)$. In this paper, we investigate the dynamic 3-colorings of claw-free graphs. First, we prove that it is $NP$-complete to determine if a claw-free graph with maximum degree 3 is dynamically 3-colorable. Second, by forbidding a kind of subgraphs, we find a reasonable subclass of claw-free graphs with maximum degree 3, for which the dynamically 3-colorable problem can be solved in linear time. Third, we give a linear time algorithm to recognize this subclass of graphs, and a linear time algorithm to determine whether it is dynamically 3-colorable. We also give a linear time algorithm to color the graphs in the subclass by 3 colors.
Multivariate Regression Depth

The regression depth of a hyperplane with respect to a set of n points in \Reald is the minimum number of points the hyperplane must pass through in a rotation to vertical. We generalize hyperplane regression depth to k -flats for any k between 0 and d-1 . The k=0 case gives the classical notion of center points. We prove that for any k and d , deep k -flats exist, that is, for any set of n points there always exists a k -flat with depth at least a constant fraction of n . As a consequence, we derive a linear-time (1+ɛ) -approximation algorithm for the deepest flat. We also show how to compute the regression depth in time O(nd-2+nlog n) when 1≤ k≤ d-2.
Assessing Agreement on Classification Tasks: The Kappa Statistic

Currently, computational linguists and cognitive scientists working in the area of discourse and dialogue argue that their subjective judgments are reliable using several different statistics, none of which are easily interpretable or comparable to each other. Meanwhile, researchers in content analysis have already experienced the same difficulties and come up with a solution in the kappa statistic. We discuss what is wrong with reliability measures as they are currently used for discourse and dialogue work in computational linguistics and cognitive science, and argue that we would be better off as a field adopting techniques from content analysis.
Customizable Segmentation of Morphologically Derived Words in Chinese

The output of Chinese word segmentation can vary according to different linguistic definitions of words and different engineering requirements, and no single standard can satisfy all linguists and all computer applications. Most of the disagreements in language processing come from the segmentation of morphologically derived words (MDWs). This paper presents a system that can be conveniently customized to meet various user-defined standards in the segmentation of MDWs. In this system, all MDWs contain word trees where the root nodes correspond to maximal words and leaf nodes to minimal words. Each non-terminal node in the tree is associated with a resolution parameter which determines whether its daughters are to be displayed as a single word or separate words. Different outputs of segmentation can then be obtained from the different cuts of the tree, which are specified by the user through the different value combinations of those resolution parameters. We thus have a single system that can be customized to meet different segmentation specifications.
Morphological Cues for Lexical Semantics

Most natural language processing tasks require lexical semantic information. Automated acquisition of this information would thus increase the robustness and portability of NLP systems. This paper describes an acquisition method which makes use of fixed correspondences between derivational affixes and lexical semantic information. One advantage of this method, and of other methods that rely only on surface characteristics of language, is that the necessary input is currently available.
Observer-Based Adaptive Neural Network Control for Nonlinear Stochastic Systems With Time Delay

This paper considers the problem of observer-based adaptive neural network (NN) control for a class of single-input single-output strict-feedback nonlinear stochastic systems with unknown time delays. Dynamic surface control is used to avoid the so-called explosion of complexity in the backstepping design process. Radial basis function NNs are directly utilized to approximate the unknown and desired control input signals instead of the unknown nonlinear functions. The proposed adaptive NN output feedback controller can guarantee all the signals in the closed-loop system to be mean square semi-globally uniformly ultimately bounded. Simulation results are provided to demonstrate the effectiveness of the proposed methods.
Canonical time-frequency, time-scale, and frequency-scale representations of time-varying channels

U § Abstract. Mobile communication channels are often modeled as linear time-varying filters or, equivalently, as time-frequency integral operators with finite support in time and frequency. Such a characterization inherently assumes the signals are narrowband and may not be appropriate for wide- band signals. In this paper time-scale characterizations are examined that are useful in wideband time-varying channels, for which a time-scale integral operator is physically justifiable. A review of these time-frequency and time-scale characterizations is presented. Both the time-frequency and time-scale integral operators have a two-dimensional discrete characterization which motivates the design of time-frequency or time-scale rake receivers. These receivers have taps for both time and frequency (or time and scale) shifts of the transmitted signal. A general theory of these charac- terizations which generates, as specific cases, the discrete time-frequency and time-scale models is presented here. The interpretation of these models, namely, that they can be seen to arise from processing assumptions on the transmit and receive waveforms is discussed. Out of this discus- sion a third model arises: a frequency-scale continuous channel model with an associated discrete frequency-scale characterization.
Maintaining information in fully dynamic trees with top trees

We design top trees as a new simpler interface for data structures maintaining information in a fully dynamic forest. We demonstrate how easy and versatile they are to use on a host of different applications. For example, we show how to maintain the diameter, center, and median of each tree in the forest. The forest can be updated by insertion and deletion of edges and by changes to vertex and edge weights. Each update is supported in O(log n) time, where n is the size of the tree(s) involved in the update. Also, we show how to support nearest common ancestor queries and level ancestor queries with respect to arbitrary roots in O(log n) time. Finally, with marked and unmarked vertices, we show how to compute distances to a nearest marked vertex. The latter has applications to approximate nearest marked vertex in general graphs, and thereby to static optimization problems over shortest path metrics.Technically speaking, top trees are easily implemented either with Frederickson's [1997a] topology trees or with Sleator and Tarjan's [1983] dynamic trees. However, we claim that the interface is simpler for many applications, and indeed our new bounds are quadratic improvements over previous bounds where they exist.
Outage-Efficient Downlink Transmission Without Transmit Channel State Information

This paper investigates downlink transmission over a quasi-static fading Gaussian broadcast channel (BC), to model delay-sensitive applications over slowly time-varying fading channels. System performance is characterized by outage achievable rate regions. In contrast to most previous work, here the problem is studied under the key assumption that the transmitter only knows the probability distributions of the fading coefficients, but not their realizations. For scalar-input channels, two coding schemes are proposed. The first scheme is called blind dirty paper coding (B-DPC), which utilizes a robustness property of dirty paper coding to perform precoding at the transmitter. The second scheme is called statistical superposition coding (S-SC), in which each receiver adaptively performs successive decoding with the process statistically governed by the realized fading. Both B-DPC and S-SC schemes lead to the same outage achievable rate region, which always dominates that of time-sharing, irrespective of the particular fading distributions. The S-SC scheme can be extended to BCs with multiple transmit antennas.
A Bi-GRU-attention neural network to identify motor units from high-density surface electromyographic signals in real time

To utilize surface electromyographics (sEMG) for control purposes, it is necessary to perform real-time estimation of the neural drive to the muscles, which involves real-time decomposition of the EMG signals. In this paper, we propose a Bidirectional Gate Recurrent Unit (Bi-GRU) network with attention to perform online decomposition of high-density sEMG signals. The model can give different levels of attention to different parts of the sEMG signal according to their importance using the attention mechanism. The output of gradient convolutional kernel compensation (gCKC) algorithm was used as the training label, and simulated and experimental sEMG data were divided into windows with 120 sample points for model training, the sampling rate of sEMG signal is 2048 Hz. We test different attention mechanisms and find out the ones that could bring the highest F1-score of the model. The simulated sEMG signal is synthesized from Fuglevand method (J. Neurophysiol., 1993). For the decomposition of 10 Motor Units (MUs), the network trained on simulated data achieved an average F1-score of 0.974 (range from 0.96 to 0.98), and the network trained on experimental data achieved an average F1-score of 0.876 (range from 0.82 to 0.97). The average decomposition time for each window was 28 ms (range from 25.6 ms to 30.5 ms), which falls within the lower bound of the human electromechanical delay. The experimental results show the feasibility of using Bi-GRU-Attention network for the real-time decomposition of Motor Units. Compared to the gCKC algorithm, which is considered the gold standard in the medical field, this model sacrifices a small amount of accuracy but significantly improves computational speed by eliminating the need for calculating the cross-correlation matrix and performing iterative computations.
Differential sharing and distinct co‐occurrence networks among spatially close bacterial microbiota of bark, mosses and lichens‬‬

Knowledge of bacterial community host‐specificity has increased greatly in recent years. However, the intermicrobiome relationships of unrelated but spatially close organisms remain little understood. Trunks of trees covered by epiphytes represent complex habitats with a mosaic of ecological niches. In this context, we investigated the structure, diversity and interactions of microbiota associated with lichens, mosses and the bare tree bark. Comparative analysis revealed significant differences in the habitat‐associated community structures. Corresponding co‐occurrence analysis indicated that the lichen microbial network is less complex and less densely interconnected than the moss‐ and bark‐associated networks. Several potential generalists and specialists were identified for the selected habitats. Generalists belonged mainly to Proteobacteria, with Sphingomonas as the most abundant genus. The generalists comprise microorganisms with generally beneficial features, such as nitrogen fixation or other supporting functions, according to a metagenomic analysis. We argue that beneficial strains shared among hosts contribute to ecological stability of the host biocoenoses.