Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-flow Attacks Against Network Flow Watermarking Schemes

We analyze several recent schemes for watermarking network flows based on splitting the flow into intervals. We show that this approach creates time dependent correlations that enable an attack that combines multiple watermarked flows. Such an attack can easily be mounted in nearly all applications of network flow watermarking, both in anonymous communication and stepping stone detection. The attack can be used to detect the presence of a watermark, recover the secret parameters, and remove the watermark from a flow. The attack can be effective even if different the watermarks in different flows carry different messages. We analyze the efficacy of our attack using a probabilistic model and a Markov-modulated Poisson process (MMPP) model of interactive traffic. We also implement our attack and test it using both synthetic and real-world traces, showing that our attack is effective with as few as 10 watermarked flows. Finally, we propose a countermeasure that defeats the attack by using multiple watermark positions.
Detection of microscopic melanoma metastases in sentinel lymph nodes

Sentinel lymph node biopsy following radioisotope labeling is a recently developed, minimally invasive surgical staging procedure used in the management of primary cutaneous malignant melanoma. If histologic analysis reveals melanoma metastasis in the sentinel lymph node, completion lymphadenectomy is performed and adjuvant therapy considered. The routine pathologic assessment of the sentinel lymph node consists of bisecting the lymph node along its long axis and histologic examination of one hematoxylin and eosin–stained section of each cut surface.
Increasing organizational citizenship behaviors of Turkish academicians

Purpose – The purpose of this paper is to explore the role of organizational justice and trust in supervisor in enhancing organizational citizenship behaviors (OCBs) of Turkish academicians.Design/methodology/approach – Data were collected via a web‐based questionnaire. A total of 1,018 academicians from public universities in Turkey participated in the study. The basic postulate of this study is that trust in supervisor will surpass the effects of employee perceptions of managerial fairness (i.e. distributive justice, procedural justice and interactional justice) as they jointly influence both OCBs directed to the organization (OCBO) and OCBs directed to the individuals (OCBI). Findings – The findings in this paper indicate that trust in supervisor fully mediates the relationship between organizational justice and OCBO, however it partially mediated the relationship between organizational justice and OCBI of Turkish academicians.Originality/value – This paper has contributed to the literature by investiga.
Natural and Social System Metaphors for Distributed Problem Solving: Introduction to the Issue

Naturally occurring information systems provide a number of useful metaphors for distributed problem solving. An introduction to some aspects of these metaphors is given which simultaneously serves as a guest editorial for a special issue devoted to the topic. The ubiquity of a distributed mode of computation in information processing in natural phenomena in general and in human societies in particular is observed and related to the evolutionary and complexity-reducing advantages of this mode. The forms of communication media available to coordinate the problem solving activities of the individual processors are examined. Some general remarks are made on how problem solving is distributed and coordinated in some human organizations, and the potential usefulness of the " society of specialists" notion in explicating cognitive activity is pointed out. Along the way, the contents of the papers in the special issue are considered in relation to various points raised in the discussion.
Differential Gating and Recruitment of P/Q-, N-, and R-Type Ca2+ Channels in Hippocampal Mossy Fiber Boutons

Voltage-gated Ca2+ channels in presynaptic terminals initiate the Ca2+ inflow necessary for transmitter release. At a variety of synapses, multiple Ca2+ channel subtypes are involved in synaptic transmission and plasticity. However, it is unknown whether presynaptic Ca2+ channels differ in gating properties and whether they are differentially activated by action potentials or subthreshold voltage signals. We examined Ca2+ channels in hippocampal mossy fiber boutons (MFBs) by presynaptic recording, using the selective blockers ω-agatoxin IVa, ω-conotoxin GVIa, and SNX-482 to separate P/Q-, N-, and R-type components. Nonstationary fluctuation analysis combined with blocker application revealed a single MFB contained on average ∼2000 channels, with 66% P/Q-, 26% N-, and 8% R-type channels. Whereas both P/Q-type and N-type Ca2+ channels showed high activation threshold and rapid activation and deactivation, R-type Ca2+ channels had a lower activation threshold and slower gating kinetics. To determine the efficacy of activation of different Ca2+ channel subtypes by physiologically relevant voltage waveforms, a six-state gating model reproducing the experimental observations was developed. Action potentials activated P/Q-type Ca2+ channels with high efficacy, whereas N- and R-type channels were activated less efficiently. Action potential broadening selectively recruited N- and R-type channels, leading to an equalization of the efficacy of channel activation. In contrast, subthreshold presynaptic events activated R-type channels more efficiently than P/Q- or N-type channels. In conclusion, single MFBs coexpress multiple types of Ca2+ channels, which are activated differentially by subthreshold and suprathreshold presynaptic voltage signals.
Towards a knowledge-based intelligent handover in heterogeneous wireless networks

This work presents a knowledge-based handover anticipation scheme. We propose to construct a knowledge plane using intelligent agents. Agents are delegated to information collection for nourishing the knowledge plane and also, handover decision and a proper network selection. We use the parameters of RSS, bandwidth, cost, user preferences, and mobility pattern of the mobile user. We estimate the future attachment point for the mobile user and anticipate the handover. Finally, we analyze the performance of our approach for (1) assuring the quality of service for different types of ongoing sessions during the handover, (2) reducing handover latency, (3) reducing the ping-pong effect and (4) signaling overhead.
Online Learning for Offroad Robots: Spatial Label Propagation to Learn Long-Range Traversability

We present a solution to the problem of long-range obstacle/path recognition in autonomous robots. The system uses sparse traversability information from a stereo module to train a classifier online. The trained classifier can then predict the traversability of the entire scene. A distance-normalized image pyramid makes it possible to efficiently train on each frame seen by the robot, using large windows that contain contextual information as well as shape, color, and texture. Traversability labels are initially obtained for each target using a stereo module, then propagated to other views of the same target using temporal and spatial concurrences, thus training the classifier to be viewinvariant. A ring buffer simulates short-term memory and ensures that the discriminative learning is balanced and consistent. This long-range obstacle detection system sees obstacles and paths at 30-40 meters, far beyond the maximum stereo range of 12 meters, and adapts very quickly to new environments. Experiments were run on the LAGR robot platform.
Causal reversibility in Bayesian networks

Causal manipulation theorems proposed by Spirtes et al. and Pearl in the context of directed probabilistic graphs, such as Bayesian networks, offer a simple and theoretically sound formalism for predicting the effect of manipulation of a system from its causal model. While the theorems are applicable to a wide variety of equilibrium causal models, they do not address the issue of reversible causal mechanisms, i.e. mechanisms that are capable of working in several directions, depending on which of their variables are manipulated exogenously. An example involving reversible causal mechanisms is the power train of a car: normally the engine moves the transmission which, in turn, moves the wheels; when the car goes down the hill, however, the driver may want to use the power train to slow down the car, i.e. let the wheels move the transmission, which then moves the engine. Some probabilistic systems can also be symmetric and reversible. For example, the noise introduced by a noisy communication channel does not usually depend on the direction of data transmission. In this paper, we investigate whether Bayesian networks are capable of representing reversible causal mechanisms. Building on the result of Druzdzel and Simon (1993), which shows that conditional probability tables in Bayesian networks can be viewed as descriptions of causal mechanisms, we study the conditions under which a conditional probability table can represent a reversible causal mechanism. Our analysis shows that conditional probability tables are capable of modelling reversible causal mechanisms but only when they fulfill the condition of soundness, which is equivalent to injectivity in equations. While this is a rather strong condition, there exist systems where our finding and the resulting framework are directly applicable.
From Philosophy to Psychotherapy: A Phenomenological Model for Psychology, Psychiatry, and Psychoanalysis

Presenting a highly innovative exploration of the relationship between philosophical and psychological issues, Edwin L. Hersch argues that psychological theories and practices inescapably rest upon a series of philosophical positions - whether they are acknowledged and reflected upon or not. To examine this proposition Hersch develops his Hierarchy of Levels of Theoretical or Philosophical Inquiry Method, which involves the systematic consideration of a series of philosophical questions pertaining to the ontological, general epistemological, field-specific epistemological, and psychological stances adopted (either explicitly or implicitly) by any particular psychological theory. By using this hierarchical framework the book then attempts to develop a new approach to psychological theory and psychotherapeutic practice based largely on the premises of phenomenological philosophy. The scope of the book cuts across a variety of theoretical and professional disciplinary approaches within the broad psychological field in demonstrating the relevance of certain philosophical issues for all of them. Clinicians, theorists and students in the psychological field are presented with a palatable introduction to the importance and inevitability of dealing with philosophy in pursuing their own work. Furthermore, his philosophical explications of a variety of psychological theories provides a new tool with which to better understand, compare, or assess any internal inconsistencies.
H-SPREAD: a hybrid multipath scheme for secure and reliable data collection in wireless sensor networks

Communication security and reliability are two important issues in any network. A typical communication task in a wireless sensor network is for every sensor node to sense its local environment, and upon request, send data of interest back to a base station (BS). In this paper, a hybrid multipath scheme (H-SPREAD) to improve both the security and reliability of this task in a potentially hostile and unreliable wireless sensor network is proposed. The new scheme is based on a distributed N-to-1 multipath discovery protocol, which is able to find multiple node-disjoint paths from every sensor node to the BS simultaneously in one route discovery process. Then, a hybrid multipath data collection scheme is proposed. On the one hand, end-to-end multipath data dispersion, combined with secret sharing, enhances the security of the end-to-end data delivery in the sense that the compromise of a small number of paths will not result in the compromise of a data message in the face of adversarial nodes. On the other hand, in the face of unreliable wireless links and/or sensor nodes, alternate path routing available at each sensor node improves the reliability of each packet transmission significantly. The extensive simulation results show that the hybrid multipath scheme is very efficient in improving both the security and reliability of the data collection service seamlessly
The Effect of Field of View on Social Interaction in Mobile Robotic Telepresence Systems

One goal of mobile robotic telepresence for social interaction is to design robotic units that are easy to operate for novice users and promote good interaction between people.This paper presents an exploratory study on the effect of camera orientation and field of view on the interaction between a remote and local user.Our findings suggest that limiting the width of the field of view can lead to better interaction quality as it encourages remote users to orient the robot towards local users. Categories and Subject Descriptors I.2. 9 [Robotics]: Commercial robots and applications; H.5. 2 [User interfaces]: Graphical user interfaces (GUI)
On the role of MHC class II molecules in the survival and lymphopenia-induced proliferation of peripheral CD4+ T cells

CD4+ T cells expand after transfer into lymphopenic H-2b Aβ−/− mice (I-Aβ-, I-Eα-deficient mice) but not after transfer into lymphopenic MHC IIΔ/Δ mice (I-Aα-, I-Aβ-, I-Eα-, and I-Eβ-deficient mice), implying that in H-2b Aβ−/− mice, Aα chain and Eβ chain associate to form a hybrid AαEβ MHC class II molecule. In light of this unexpected result, we reexamined the MHC class II requirement in the survival and lymphopenia-induced proliferation of CD4+ T cells. Here we show that expansion, but not short-term survival, of CD4+ T cells depends on interactions with MHC class II molecules in lymphopenic mice. Nevertheless, interactions with classical MHC class II molecules are required for CD4+ T cells to survive in CD8+ T-cell-containing mice.
Distributed under Creative Commons Cc-by 4.0 Region-of-interest Analyses of One- Dimensional Biomechanical Trajectories: Bridging 0d and 1d Theory, Augmenting Statistical Power

One-dimensional (1D) kinematic, force, and EMG trajectories are often analyzed using zero-dimensional (0D) metrics like local extrema. Recently whole-trajectory 1D methods have emerged in the literature as alternatives. Since 0D and 1D methods can yield qualitatively different results, the two approaches may appear to be theoretically distinct. The purposes of this paper were (a) to clarify that 0D and 1D approaches are actually just special cases of a more general region-of-interest (ROI) analysis framework, and (b) to demonstrate how ROIs can augment statistical power. We first simulated millions of smooth, random 1D datasets to validate theoretical predictions of the 0D, 1D and ROI approaches and to emphasize how ROIs provide a continuous bridge between 0D and 1D results. We then analyzed a variety of public datasets to demonstrate potential effects of ROIs on biomechanical conclusions. Results showed, first, that a priori ROI particulars can qualitatively affect the biomechanical conclusions that emerge from analyses and, second, that ROIs derived from exploratory/pilot analyses can detect smaller biomechanical effects than are detectable using full 1D methods. We recommend regarding ROIs, like data filtering particulars and Type I error rate, as parameters which can affect hypothesis testing results, and thus as sensitivity analysis tools to ensure arbitrary decisions do not influence scientific interpretations. Last, we describe open-source Python and MATLAB implementations of 1D ROI analysis for arbitrary experimental designs ranging from one-sample t tests to MANOVA.
A fingerprint spoof detection based on MLP and SVM

We introduce a fingerprint spoof detection technique based on MLP and SVM that combines several features. The proposed technique is evaluated on two scenarios: (i) when an impostor can perform consecutive attempts to be considered authentic; and, (ii) when the system deals with fingerprints from elderly people. In order to analyze these scenarios, a database was developed. The results show that the proposed combination of features increases the system performance in at least 33.56% and that the average error increases as more attempts for acceptance are allowed. The SVM classifier presents better performance in almost all the tested configurations. However, MLP is more accurate with biometrics from elderly people.
Convex Sparse Coding, Subspace Learning, and Semi-Supervised Extensions

Automated feature discovery is a fundamental problem in machine learning. Although classical feature discovery methods do not guarantee optimal solutions in general, it has been recently noted that certain subspace learning and sparse coding problems can be solved efficiently, provided the number of features is not restricted a priori. We provide an extended characterization of this optimality result and describe the nature of the solutions under an expanded set of practical contexts. In particular, we apply the framework to a semi-supervised learning problem, and demonstrate that feature discovery can co-occur with input reconstruction and supervised training while still admitting globally optimal solutions. A comparison to existing semi-supervised feature discovery methods shows improved generalization and efficiency.
The design and use of simplePower: a cycle-accurate energy estimation tool

In this paper, we presen t the design and use of a comprehensiv e framework, SimplePower, for ev aluating the effect of high-level algorithmic, architectural, and compilation trade-offs on energy. An execution-driven, cycle-accurate RT lev el energy estimation tool that uses transition sensitive energy models forms the cornerstone of this framework. SimplePower also pro vides the energy consumed in the memory system and on-chip buses using analytical energy models. We presen t the use of SimplePower to evaluate the impact of a new selective gated pipeline register optimization, a high-level data transformation and a pow er-conscious post compilation optimization (register relabeling) on the datapath, memory and on-chip bus energy, respectively. We find that these three optimizations reduce the energy by 18-36% in the datapath, 62% in the memory system and 12% in the instruction cache data bus, respectively.
Perpetuating the global division of labour: defensive free trade and development in the third world

This article contains an examination of whether free trade coupled with the neoliberal principles of the Washington Consensus has been turned into a defensive strategy used by developed countries in order to maintain and perpetuate the division of labour in the global market between developed and developing countries. The question is raised of whether developed countries are worried that some highly populated emerging economies may follow the path of the newly industrialized economies. As a pre-emptive measure, developed countries adopt free trade as a defensive mechanism that would create a level playing field or “fair trade” in the global market and would deliberately stifle infant, high value added industries from thriving within emerging economies. On a level playing field, infant industries cannot compete against the wellestablished corporations of developed countries. Finally, free trade also leads to another indirect outcome: it intensifies competition among developing economies in low value added goods and consequently lessens a rise in the income of unskilled labour in these economies.
Simulation of Spread of African Swine Fever, Including the Effects of Residues from Dead Animals

To study the spread of African swine fever (ASF) within a pig unit and the impact of unit size on ASF spread, a simulation model was created. In the model, an animal can be in one of the following stages: susceptible, latent, subclinical, clinical, or recovered. Animals can be infectious during the subclinical stage and are fully infectious during the clinical stage. ASF virus (ASFV) infection through residues of dead animals in the slurries was also modeled in an exponentially fading-out pattern. Low and high transmission rates for ASFV were tested in the model. Robustness analysis was carried out in order to study the impact of uncertain parameters on model predictions. The results showed that the disease may fade out within the pig unit without a major outbreak. Furthermore, they showed that spread of ASFV is dependent on the infectiousness of subclinical animals and the residues of dead animals, the transmission rate of the virus, and importantly the unit size. Moreover, increasing the duration of the latent or the subclinical stages resulted in longer time to disease fade out. The proposed model is a simple and robust tool simulating the spread of ASFV within a pig house taking into account dynamics of ASFV spread and the unit size. The tool can be implemented in simulation models of ASFV spread between herds.
Multilingual speech recognition: a unified approach

Abstract In this paper, we present a uniﬁed approach for hidden markovmodel based multilingual speech recognition. The proposedapproach could be used across acoustically similar as well asdiverse languages. We use an automatic phone mapping algo-rithm to map phones across languages and reduce the effectivenumber of phones in the multililingual acoustic model. Weexperimentally verify the effectiveness of the approach usingtwo acoustically similar languages, Tamil and Hindi and alsoAmerican English which is very different from the other twolanguages acoustically. The experimental results are very en-couraging and demonstrate the effectiveness of the approach inbuilding a universal multilingual speech recognition system. 1. Introduction A practical approach to multilingual speech recognition forcountries like India where more than 30 languages are spokenacrossthecountrywouldbetohaveatrulymultilingualacousticmodel. This multilingual model should then be adapted to thetarget language with the help of a language identiﬁcation sys-tem. This is more important in the case of telephony applica-tions where the conversations can be of short durations and thelanguage could change from one conversation to another.IndianlanguagesingeneralbelongtoeitherDravidianfam-ily or Aryan family or both. For example, a south Indian lan-guage Malayalam is derived from another south Indian lan-guage Tamil, a Dravidian language. But, its vocabulary is richwith words derived from sanskrit, an Aryan language, makingit resemble the Dravidian and Aryan languages. The acousticcharacteristics of some of the Malayalam phones are similar toTamil, whilesomeareclosertoSanskrit. Therefore, whiledeal-ing with Indian languages, there are acoustic similarities acrosslanguages that could be shared to our advantage to reduce theoverall size of the acoustic model.Dealing with many languages at the same time, the easi-est and effective approach would be to identify the languagewith the help of a language identiﬁcation system and choosethe appropriate monolingual acoustic model for decoding. Thisapproach however suffers from mainly two drawbacks: