Miracle-dz/UniFAR-FTUs huggingface dataset:
Network Log Anonymization: Application of Crypto-PAn to Cisco Netflows

Logs are one of the most fundamental resources to any security professional. It is widely recognized by the government and private industry that it is both beneficial and desirable to share logs for the purpose of security research and network measurements. Rapid growth of the Internet and its applications, especially financial and security related services, require a secure and efficient way to share network logs among security engineers and network operators. However, due to the risk of exposing sensitive information to potential attackers, the sharing is either not happening or not happening to the degree or magnitude that is desired. To eliminate the hurdle of sharing logs, strong and efficient anonymization techniques are needed. Crypto-PAn is a new anonymization tool which is gaining recognition. In this paper, we extend Crypto-PAn by designing and integrating it with an efficient passphrasebased key generation algorithm that requires no new libraries and little extra code. We also evaluate the performance of the extended Crypto-PAn on binary Cisco NetFlow log files.
A New Design Method for Linear Control Systems Possessing Integrity

The paper is concerned with fault-tolerant control (FTC) problem of state feedback control system with parameter uncertainty. A new simple design method is given. By means of Lyapunov theorem, the paper derives three sufficient conditions for the controller to maintain closed-loop systems asymptotically stable against arbitrary sensor failures, actuator failures, both sensor and actuator failures, respectively. Be distinguished from other literatures' method about FTC, the paper utilizes some concepts such as spectral radius and minimum eigenvalue of matrix to construct constrain inequalities in order to represent the sufficient conditions. Furthermore, controller design procedure is presented. A numerical example is provided to demonstrate the effectiveness and simplicity of the method proposed
LEARNING EMERGENT STYLE USING AN EVOLUTIONARY APPROACH

This paper presents an evolutionary approach to learning emergent style in architectural designs. Emergence is the process of making features explicit which were previously only implicit. Style is considered as a set of common characteristics of a group of designs. A syntax-semantics model to interpret style is proposed and is represented at a genetic level. A genetic engineering technique is used to find the mapping between emergent style and the gene structures which produce that style. Preliminary results are presented.
Distributed Space-Time Block Codes for Two-Hop Wireless Relay Networks (Invited Paper)

Recently, the idea of space-time coding has been applied to wireless relay networks wherein a set of geographically separated relay nodes cooperate to process the received signal from the source and forward them to the destination such that the signal received at the destination appears like a Space-Time Block Code (STBC). Such STBCs (referred to as Distributed Space- Time Block Codes (DSTBCs)) when appropriately designed are known to offer spatial diversity. It is known that different classes of DSTBCs can be designed primarily depending on (i) whether the Amplify and Forward (AF) protocol or the Decode and Forward (DF) protocol is employed at the relays and (ii) whether the relay nodes are synchronized or not. In this paper, we present a survey on the problems and results associated with the design of DSTBCs for the following classes of two-hop wireless relay networks: (i) synchronous relay networks with AF protocols, (ii) asynchronous relay networks with AF protocols (iii) synchronous relay networks with DF protocols and (iv) asynchronous relay networks with DF protocols.
Firm growth and R&D expenditure

We apply a panel vector autoregression model to a firm-level longitudinal database to observe the co-evolution of sales growth, employment growth, profits growth and the growth of research and development (R&D) expenditure. Contrary to expectations, profit growth seems to have little detectable association with subsequent R&D investment. Instead, firms appear to increase their total R&D expenditure following growth in sales and employment. In a sense, firms behave ‘as if’ they aim for a roughly constant ratio of R&D to employment (or sales). We observe heterogeneous effects for growing or shrinking firms, however, suggesting that firms are less willing to reduce their R&D levels following a negative growth shock than they are willing to increase R&D after a positive shock.
Medication Adherence Measures: An Overview

WHO reported that adherence among patients with chronic diseases averages only 50% in developed countries. This is recognized as a significant public health issue, since medication nonadherence leads to poor health outcomes and increased healthcare costs. Improving medication adherence is, therefore, crucial and revealed on many studies, suggesting interventions can improve medication adherence. One significant aspect of the strategies to improve medication adherence is to understand its magnitude. However, there is a lack of general guidance for researchers and healthcare professionals to choose the appropriate tools that can explore the extent of medication adherence and the reasons behind this problem in order to orchestrate subsequent interventions. This paper reviews both subjective and objective medication adherence measures, including direct measures, those involving secondary database analysis, electronic medication packaging (EMP) devices, pill count, and clinician assessments and self-report. Subjective measures generally provide explanations for patient's nonadherence whereas objective measures contribute to a more precise record of patient's medication-taking behavior. While choosing a suitable approach, researchers and healthcare professionals should balance the reliability and practicality, especially cost effectiveness, for their purpose. Meanwhile, because a perfect measure does not exist, a multimeasure approach seems to be the best solution currently.
Adaptive Function-Link Fuzzy CMAC Control System Design for MIMO Nonlinear Chaotic Systems

A novel function-link fuzzy cerebelarmodel-articulation-controller (CMAC) is developed in this study. It is a generalization of a fuzzy neural network and of a conventional CMAC. Then, a control system comprising a function-link fuzzy CMAC and a fuzzy compensator is proposed for multi-input multi-output (MIMO) nonlinear chaotic systems. The function-link fuzzy CAMC is used to mimic an ideal controller and the fuzzy compensator is designed to suppress the approximation error between the function-link fuzzy CMAC and the ideal controller. The on-line learning algorithm of the controller's parameters is derived to improve the control performance. Moreover, the design of the fuzzy compensator can guarantee the system's stability. Finally, synchronization of the unified chaotic system has been examined to illustrate the effectiveness of the proposed design method.
In Search of What We Experimentally Know about Unit Testing

Gathering evidence in any discipline is a lengthy procedure, requiring experimentation and empirical confirmation to transform information from mere opinion to undisputed fact. Software engineering is a relatively young field and experimental SE is even younger, so undisputed facts are few and far between. Nevertheless, ESE's relevance is growing because experimental results can help practitioners make better decisions. We have aggregated results from unit-testing experiments with the aim of identifying information with some experimental basis that might help practitioners make decisions. Most of the experiments focus on two important characteristics of testing techniques: effectiveness and efficiency. Some other experiments study the quality of test-case sets according to different criteria
Modeling and Prediction of Great Salt Lake Elevation Time Series Based on ARFIMA

The elevation of Great Salt Lake (GSL) has a great impact on the people of Utah. The flood of GSL in 1982 has caused a loss of millions of dollars. Therefore, it is very important to predict the GSL levels as precisely as possible. This paper points out the reason why conventional methods failed to describe adequately the rise and fall of the GSL levels — the long-range dependence (LRD) property. The LRD of GSL elevation time series is characterized by some most commonly used Hurst parameter estimation methods in this paper. Then, according to the revealed LRD, the autoregressive fractional integrated moving average (ARFIMA) model is applied to analyze the data and predict the future levels. We have shown that the prediction results has a better performance compared to the conventional ARMA models.Copyright © 2007 by ASME
Mobile TV Extension to WiFi Networks for Location Dependent Services

This paper proposes an end-to-end system solution of mobile TV extension to WiFi networks. We integrate WiFi network components into mobile TV system, which intends to extend the mobile TV content to the WiFi networks with the additional local dependent content. Recognizing the high end-user demand for location dependent services, we provide the dynamic and hybrid ESG (electronic service guide) transmission solution rather than fixed broadcasting transmission in traditional mobile TV system. The complexity of the solution is analyzed and scalability can be guaranteed through the common web application servers. Part of this work is under the EU FP6 project Mobiserve which aims to enrich value-added services for mobile TV broadcasting through mobile and TV service convergence.
Phenolic Extracts from Acacia mangium Bark and Their Antioxidant Activities

Phenolic compounds are present at very high concentrations in the bark of Acacia mangium. These compounds are known to have strong antioxidant activity and thus different beneficial effects on human health. Phenolic compounds in bark of A. mangium were extracted and their antioxidant activities were investigated using the 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical-scavenging and ferric-reducing antioxidant power (FRAP) assays. A central composite design has been employed to optimize the experimental conditions for a high total phenolic content and antioxidant activity. The desirability function approach has been employed to simultaneously optimize the three responses: total phenols, antiradical activity and FRAP. An extraction time of 90 min, liquid-solid ratio of 5, and temperature of 50 °C was predicted for the optimum experimental conditions using the desirability function. A significant linear relationship between antioxidant potency, antiradical activity and the content of phenolic compounds of bark extracts was observed. The structures of condensed tannins isolated from A. mangium were characterized by MALDI-TOF MS analyses. Condensed tannin oligomers from A. mangium were shown to be heterogeneous mixtures consisting of procyanidin and prodelphinidin structural units with polymerization degrees up to 9.
Web page segmentation based on the hough transform and vision cues

Web page segmentation has extensive value in web applications. As the traditional method which only based on Document Object Model (Dom) tree poorly reflects the actual semantic structure of a page, the vision-based measures which attempt to understand the perception of user have attracted great concern in recently. Moreover, the visual page layout structuring is more suitable to suggest a semantic partitioning of a page. Vision-based Page Segmentation (VIPS) algorithm is a notable technique which improves the situation that the visual effect is not consistent with the corresponding DOM tree of web pages. However, due to the increasing complicated structure of web pages and ever-changing of web design, the rules in VIPS become numerous and are no longer fully applicable. To alleviate the shortcoming of VIPS, this paper introduces Hough transform in image processing and takes advantage from DOM trees and visual cues. Our proposed method first extracts the visual separator in web pages according to the perceptive of web designers, then adjusts the segmented information blocks by Hough transformation in the hope of enhancing the VIPS algorithm compatibility and improving the performance of information extraction in applications. The quality of our proposed method is evaluated by subjective and objective measurements, and the experiment results show that this method has come to an anticipant result which even better than the classical one.
Novel organelle-targeting signals in viral proteins

Peroxisomes are vital cellular organelles controllingimportant metabolic functions like hydrogen peroxidedegradation, fatty acid metabolism, gluconeogenesis,toxin degradation, etc. (Flatmark et al., 1988; van denBosch et al., 1992; Masters, 1997; Lopez-Huertas etal., 2000). Certain human metabolic disorders such asZellweger syndrome, neonatal adrenoleukodystrophy,infantile Refsum disease and rhizomelic chondrodysplasiapunctata are associated with the peroxisomal defect inprotein import and/or biogenesis (Gould and Valle, 2000). Intracellular transport of proteins into peroxisomes de-pends on either type 1 peroxisomal targeting signal (PTS1)or, type 2 (PTS 2). Type 1 signal sequence is a tripeptidemotif present in the carboxy terminal of the protein(consensus sequence [STAGQCN]-[KRH]-[LIVMAFY];Gould et al., 1987, 1989; Swinkels et al., 1991; Olivieret al., 2000). Whereas, PTS2 constitutes a combina-tion of nine amino acid bipartite sequences (consensus[RKS]-[ILVH]-x(5)-[QH]-[LAE]) in the N-terminal halfof the protein (Gould et al., 1989; Swinkels et al., 1991;Terlecky et al., 1996). Receptors for PTS1 and PTS2 havebeen identiﬁed as PEX5 and PEX7 respectively (Terleckyet al., 1996; Lametschwandtner et al., 1998; Subramani,1998). The ﬁrst report of PTS was in the ﬁreﬂy luciferasegene more than a decade ago (Gould et al., 1987, 1989). Following its discovery, except for viruses, virtually alleukaryotes, parasites and fungi have been identiﬁed tohave PTS-containing proteins and demonstrated to targetsuch proteins to the organelle (Fung and Clayton, 1991;Aitchison et al., 1992; Subramani, 1998). Recently weidentiﬁed the presence of a functional and conserved PTS1in one of the rotaviral proteins (VP4) which prompted usto look into other viral protein sequences available in thedatabase for potential PTS1 and PTS2 motifs.
AnCF, the CCAAT Binding Complex ofAspergillus nidulans, Is Essential for the Formation of a DNase I-Hypersensitive Site in the 5′ Region of theamdS Gene

ABSTRACT The CCAAT sequence in the amdS promoter ofAspergillus nidulans is recognized by AnCF, a complex consisting of the three evolutionary conserved subunits HapB, HapC, and HapE. In this study we have investigated the effect of AnCF on the chromatin structure of the amdS gene. The AnCF complex and the CCAAT sequence were found to be necessary for the formation of a nucleosome-free, DNase I-hypersensitive region in the 5′ region of theamdS gene. Deletion of the hapE gene results in loss of the DNase I-hypersensitive site, and the positioning of nucleosomes over the transcriptional start point is lost. Likewise, a point mutation in the CCAAT motif, as well as a 530-bp deletion which removes the CCAAT box, results in the loss of the DNase I-hypersensitive region. The DNase I-hypersensitive region and the nucleosome positioning can be restored by insertion of a 35-bp oligonucleotide carrying the CCAAT motif. A DNase I-hypersensitive region has been found in the CCAAT-containing fmdS gene and was also hapE dependent. These data indicate a critical role for the AnCF complex in establishing an open chromatin structure in A. nidulans.
The importance of percent-done progress indicators for computer-human interfaces

A “percent-done progress indicator” is a graphical technique which allows the user to monitor the progress through the processing of a task. Progress indicators can be displayed on almost all types of output devices, and can be used with many different kinds of programs. Practical experience and formal experiments show that prograss indicators are an important and useful user-interface tool, and that they enhance the attractiveness and effectiveness of programs that incorporate them. This paper discusses why progress indicators are important. It includes the results of a formal experiment with progress indicators. One part of the experiment demonstrates that people prefer to have progress indicators. Another part attempted to replicate earlier findings to show that people prefer constant to variable response time in general, and then to show that this effect is reversed with progress indicators, but the results were not statistically significant. In fact, no significant preference for constant response time was shown, contrary to previously published results.
Target Representation on an Autonomous Vehicle with Low-Level Sensors

How can low-level autonomous robots with only very simple sensor systems be endowed with cognitive capabilities? Specifically, we consider a system that uses seven infrared sensors and five microphones to avoid obstacles and acquire sound targets. The cognitive abilities of the vehicle consist of representing the direction in which a sound source lies. This representation supports target detection, estimation of target direction, selection of one out of multiple-detected targets, storage of target direction in short-term memory, continuous updating of memory, and deletion of memorized target information after a characteristic delay. We show that the dynamic approach (attractor dynamics) employed to control the motion of the robot can be extended to the level of representation by using dynamic neural fields to interpolate sensory information. We show how the system stabilizes decisions in the presence of multivalue sensorial information and activates and deactivates memory. Smooth integration of this target representation with target acquisition, in the form of phonotaxis, and obstacle avoidance is demonstrated.
Survey Propagation beyond Constraint Satisfaction Problems

Survey propagation (SP) is a message passing procedure that attempts to model all the fixed points of Belief Propagation (BP), thereby improving BP’s approximation in loopy graphs where BP’s assumptions do not hold. For this, SP messages represent distributions over BP messages. Unfortunately this requirement makes SP intractable beyond constraint satisfaction problems because, to perform general SP updates, one has to operate on distributions over a continuous domain. We propose an approximation scheme to efficiently extend the application of SP to marginalization in binary pairwise graphical models. Our approximate SP has O(DK log(DK)τ) complexity per iteration, where τ is the complexity of BP per iteration, D is the maximum node degree and K is a resolution constant controlling the approximation’s fidelity. Our experiments show that this method can track many BP fixed points, achieving a high marginalization accuracy within a few iterations, in difficult settings where BP is often non-convergent and inaccurate.
MNCM: A Critical Node Matching Approach to Scheduling for Input Buffered Switches With No Speedup

In this paper, we use fluid model techniques to establish new results for the throughput of input-buffered switches. Dai and Prabhakar have shown that any maximal size matching algorithm with speedup of 2 achieves 100% throughput. We introduce the maximum node containing matching (MNCM), which is a new class of matching algorithms that achieve 100% throughput with no speedup. The only assumption on the arrival processes is they satisfy the strong law of large numbers (SLLN). The MNCM policies only need to include ports whose weight (backlog) are above a threshold in the matching rather than finding a matching with maximum total weight. This simplified requirement enables us to introduce a new matching algorithm, maximum first matching (MFM), with O(N2.5) complexity. We show that MFM is a low-complexity algorithm with good delay performance. We also provide a deterministic upper bound for the buffering requirement of a switch with an MNCM scheduler, when the ports incoming traffic are admissible and (sigma, rho) regulated.
A Three-Dimensional Computational Model of Collagen Network Mechanics

Extracellular matrix (ECM) strongly influences cellular behaviors, including cell proliferation, adhesion, and particularly migration. In cancer, the rigidity of the stromal collagen environment is thought to control tumor aggressiveness, and collagen alignment has been linked to tumor cell invasion. While the mechanical properties of collagen at both the single fiber scale and the bulk gel scale are quite well studied, how the fiber network responds to local stress or deformation, both structurally and mechanically, is poorly understood. This intermediate scale knowledge is important to understanding cell-ECM interactions and is the focus of this study. We have developed a three-dimensional elastic collagen fiber network model (bead-and-spring model) and studied fiber network behaviors for various biophysical conditions: collagen density, crosslinker strength, crosslinker density, and fiber orientation (random vs. prealigned). We found the best-fit crosslinker parameter values using shear simulation tests in a small strain region. Using this calibrated collagen model, we simulated both shear and tensile tests in a large linear strain region for different network geometry conditions. The results suggest that network geometry is a key determinant of the mechanical properties of the fiber network. We further demonstrated how the fiber network structure and mechanics evolves with a local formation, mimicking the effect of pulling by a pseudopod during cell migration. Our computational fiber network model is a step toward a full biomechanical model of cellular behaviors in various ECM conditions.
A commentary on the mathematical model of the heterogeneous gypsy moth larva population by G. Dwyer and his co-authors

In this commentary I utilize the general methods of the mathematical theory of heterogeneous populations in order to point out an omission in the analysis of the mathematical model in [Dwyer et al (2000), Am Nat, 156(2):105–120], which led to the conclusion in [Elderd et al (2008) Am Nat, 172(6):829–842] that the original model must be replaced with an alternative one because of the new data. I show that more thorough understanding of the underlying model allows twitching the model parameters to account for the observed data.
UNCONVENTIONAL COMPUTING: A SHORT

Physics imposes some limits to the computations that we can perform. Because of these limits we cannot solve problems in almost no time and with almost zero energy consumption. The main problem is that we are asking too much from a single device: we want computers that play chess, solve equations, navigate on the internet etc. Because of this great generality we are paying some big prices (in time and energy consumption). Some problems can be e-ciently solved by using other concepts. Some materials have intrinsic properties which makes them very suitable for solving some kind of problems. In this paper we provide a short survey to the fleld of Unconventional Computing. We review and compare the most popular problems and methods belonging to this fleld.
MicroRNA Precursors Are Not Structurally Robust but Plastic

Robustness is considered a ubiquitous property of living systems at all levels of organization, and small noncoding RNA (sncRNA) is a genuine model for its study at the molecular level. In this communication, we question whether microRNA precursors (pre-miRNAs) are actually structurally robust, as previously suggested. We found that natural pre-miRNAs are not more robust than expected under an appropriate null model. On the contrary, we found that eukaryotic pre-miRNAs show a significant enrichment in conformational flexibility at the thermal equilibrium of the molecule, that is, in their plasticity. Our results further support the selection for functional diversification and evolvability in sncRNAs.