Miracle-dz/UniFAR-FTUs huggingface dataset:
Decentralized Stochastic Control of Delay Tolerant Networks

We study in this paper optimal stochastic control issues in delay tolerant networks. We first derive the structure of optimal 2-hop forwarding policies. In order to be implemented, such policies require the knowledge of some system parameters such as the number of mobiles or the rate of contacts between mobiles, but these could be unknown at system design time or may change over time. To address this problem, we design adaptive policies combining estimation and control that achieve optimal performance in spite of the lack of information. We then study interactions that may occur in the presence of several competing classes of mobiles and formulate this as a cost-coupled stochastic game. We show that this game has a unique Nash equilibrium such that each class adopts the optimal forwarding policy determined for the single class problem.
Minimizing the Condition Number for Small Rank Modifications

We consider the problem of minimizing the condition number of a low rank modification of a matrix. Analytical results show that the minimum, which is not necessarily unique, can be obtained and expressed by a small number of eigenpairs or singular pairs. The symmetric and the nonsymmetric cases are analyzed, and numerical experiments illustrate the analytical observations.
Bubble hierarchies

We introduce bubble hierarchies as an approach to generating algorithmic art from random hierarchies. The technique is based on repeatedly drawing color-coded circles to illustrate parent--child relationships. The algorithm is simple and produces densely packed structures similar to the concept of Apollonian gaskets. We demonstrate the influence of different parameters on the visual outcome, such as the number of created circles or the color encoding. Our algorithm also supports multiple seeding points and obstacles that can be used to influence the layout of the hierarchy.
An achievable rate region of a three-receiver BC with degraded message sets and side information

In this paper, a three-receiver (named as one-receiver two-eavesdropper) discrete memoryless broadcast channel (DM-BC) with three degraded message sets and side information is studied. The main objective of this paper is to present a theorem so as to give an achievable secrecy region for this one-receiver two-eavesdropper DM-BC with the side information available at the transmitter. In the achievability proof scheme, we use the superposition coding scheme to divide the available randomness into different levels for misleading the eavesdroppers. We establish the achievable secrecy region by using a combination of Gelfand-Pinsker binning scheme and rate splitting technique. Achievability in this case also follows from the new idea of Nair-El Gamal indirect decoding. The achievable secrecy region of this paper subsumes the steinberg rate region for two-receiver degraded BC with the side information as well as the secrecy capacity region for one-receiver two-eavesdropper DM-BC with no side information as its special cases.
Stimulant use transitions and harm mitigation responses: Analysis of a qualitative data set

INTRODUCTION This project aims to develop effective harm-reduction messages and strategies for young adult illicit stimulant users. It focuses on identifying threshold moments in the lives of users of amphetamine-type stimulant (ATS) such as ecstasy [MDMA] and methamphetamine. Data for this project comes from a broader study, the Natural History Study of Drug Use—a longitudinal study that followed a population-based cohort of young adult ATS users for four and a half years. In-depth qualitative interviews were conducted at the start of the study with these users. They were asked about the most recent occasion of ecstasy or methamphetamine use—in particular the social context and setting of use, subjective effects of use, using other drugs (including alcohol) in conjunction with ecstasy or methamphetamine, and recovering from the drug experience. This project analysed the baseline interview data, as well as that from four follow-up waves over the study’s four and a half years. It looks at the natural history of ATS use, in particular: - initiation of ATS use; - patterns of ATS use; - simultaneous and concurrent use of licit and illicit substances with ATS; and - motivating factors and predictors of desistance from ATS use. This document compares patterns of ATS and other substance use between well-managed and at-risk ATS users. It also explores harm-reduction practices among ATS users and discusses proposals for effective harm-reduction messages and strategies for young adult ATS users.
PROVING THE DECIDABILITY OF THE PDL × PDL PRODUCT LOGIC

The propositional dynamic logic (PDL) is an adequate tool to write down programs. In a previous article we used PDL to formulate cryptographic protocols as parallel programs. In these protocols at least two agents/individuals exchange messages, so we needed to use product logic to formulate the parallel actions. ´Agnes Kurucz proved that S5 × S5 × S5 — which is the simplest triple product logic — is undecidable, hence it follows that PDL × PDL × PDL is undecidable, too. It is easy to show that the PDL logic (without the star operator) is decidable, so it is an interesting problem, that the PDL × PDL product logic is decidable or not.
DOPPLER IMAGING OF STELLAR SURFACE STRUCTURE. IX. A HIGH-RESOLUTION IMAGE OF THE WEAK-LINED T TAURI STAR HDE 283572 = V987 TAURI

We present a Doppler image of the T Tauri star HDE 283572 from a set of high-quality spectroscopic line profiles and simultaneous multicolor photometry from October 1997. Additional photometry throughout the entire observing season was obtained with a robotic telescope and is used to determine the precise photometric period of 1.5495±0.0002 days that we interpret to be the stellar rotation period. Further relevant astrophysical parameters like mass, luminosity, radius, effective temperature, gravity, and elemental abundances are obtained and discussed. HDE 283572 shows one of the largest and coolest polar spots ever observed and confirms an earlier map by Joncour et al. from Pic-du-Midi data. We also compare our map with predicted magnetic flux-tube distributions from MHD simulations and suggest that the polar spot on HDE 283572 was possibly created by a strong poleward meridional flow.
Preemptive Oral Clonidine Provides Better Sedation Than Intravenous Midazolam in Brachial Plexus Nerve Blocks

Background Preemptive analgesia is the blocking of pain perception afferent pathways before noxious painful stimuli. Clonidine is an alpha agonist drug that is partially selective for α-2 adrenoreceptors. Clonidine is used as anti-anxiety medication and an, analgesic, and it prolongs the duration of the block in the brachial plexus block. Objectives To compare the effect of preemptive clonidine with midazolam on intraoperative sedation, duration of block, and postoperative pain scores. Patients and Methods In a randomized clinical trial, 80 patients with orthopedic fractures of an upper extremity who underwent supraclavicular nerve block were randomly assigned to receive 0.2 mg oral clonidine or 2 mg oral midazolam. Intraoperative sedation was measured at one hour after the start of urgery and again in the PACU (Post-Anesthesia Care Unit) using the Ramsay scale. The duration of sensory blockade was measured. Postoperative pain scores were measured using the VAS (Visual Analogue Scale) after entrance to recovery up to 2 hours. Results The percentages of patients in the calm and sedated scale were significantly higher in clonidine group (35 and 42.5%, respectively), compared to the midazolam group (17.5 and 17.5%, respectively) (P = 0.042, 0.029; respectively). Those administered fentanyl in the clonidine group 105 ± 30.8 was significantly lower than that for the midazolam group 165 ± 34.5 (P = 0.0018). The percentages of patients in the calm scale were significantly higher in the clonidine group (52.5), compared to the midazolam group (17.5) (P = 0.001) in the post-operative period. VAS scores were significantly lower at one (P = 0.01) and two hours (P = 0.001) after operation in the clonidine group, compared to the midazolam group. Conclusions Preemptive clonidine has many marvelous advantages over midazolam, including better sedation inside the operating room and then in the post-operative care unit, lower fentanyl doses are required during surgery, more stable heart rate and blood pressure are observed during the procedure, and patients report lower post-operative pain scores.
Selection and Peer-review under Responsibility of the Organizing Committee of the International Conference on Timing and Time Perception. Unifying Prospective and Retrospective Interval-time Estimation: a Fading-gaussian Activation-based Model of Interval-timing

Hass and Hermann (2012) have shown that only variance-based processes will lead to the scalar growth of error that is characteristic of human time judgments. Secondly, a major meta-review of over one hundred studies (Block et al., 2010) reveals a striking interaction between the way in which temporal judgments are queried and cognitive load on participants' judgments of interval duration. For retrospective time judgments, estimates under high cognitive load are longer than under low cognitive load. For prospective judgments, the reverse pattern holds, with increased cognitive load leading to shorter estimates. We describe GAMIT, a Gaussian spreading-activation model, in which the sampling rate of an activation trace is differentially affected by cognitive load. The model unifies prospective and retrospective time estimation, normally considered separately, by relating them to the same underlying process. The scalar property of time estimation arises naturally from the model dynamics and the model shows the appropriate interaction between mode of query and cognitive load. Selection and peer-review under responsibility of the Organizing Committee of the International Conference on Timing and Time Perception.
Intrusion Detection Using Text Processing Techniques: A Recent Survey

Intrusion Detection is one of the major threats for any organization of any size. The approach of intrusion detection using text processing has been one of the research interests among researchers working in the area of the network and information security. In this approach for intrusion detection, the system calls serve as the source for mining and predicting any chance of intrusion. When an application runs, there might be several system calls which are initiated in the background. These system calls form the basis and the deciding factor for intrusion detection. We perform an extensive survey on Intrusion detection using text mining techniques and validate the suitability of various kernel measures published in the literature. We finally come out with the research directions for intrusion detection which have not been discussed in detail in the literature. We hope this survey will be useful for researchers working in the direction of intrusion detection using text mining techniques.
Head Gesture Recognition Based on SAE

First, combine depth information with 2D gray image information to obtain samples, while adjusting their contribution for the samples. Use SAE to get head gesture recognition model. Finally, test the accuracy of recognition model. The proposed method unlike the some traditional methods–use CNN to cope with RGB-D image requiring GPU support, PC can fulfill all experimental procedures. The best result in this experiment can achieve gesture recognition error around 12° on average. The data of this study is based on Biwi Kinect Head Pose Database.
Diversity in populations of free‐living Symbiodinium from a Caribbean and Pacific reef

The presence and diversity of free‐living dinoflagellates belonging to the endosymbiotic genus Symbiodinium were explored in seawater samples collected above coral reefs in KaneÂ'ohe Bay, OÂ'ahu, HawaiÂ'i, and Puerto Morelos, Quintana Roo, Mexico. Two genetic markers were used to assess Symbiodinium diversity in the water column: the internal transcribed spacer 2 region of the nuclear ribosomal array (ITS2), and a hypervariable region in domain V of the large subunit (23S) of the chloroplast ribosomal array (cp23S‐HVR). Sequencing of cloned gene fragments reveals that clades B, C, D, and H Symbiodinium are detectable in the seawater samples. In addition to the previously described types B1, C3, C15, C21, and D1, novel Symbiodinium sequences belonging to clades B and C were also retrieved. The majority of Symbiodinium sequences recovered from KaneÂ'ohe Bay belonged to clade C and those from Puerto Morelos to clade B, a pattern that reflects the dominant types of Symbiodinium found in endosymbiosis with scleractinian corals in these two areas. This study represents the first direct assessment of Symbiodinium diversity in waters adjacent to coral reefs located in the Caribbean and the Pacific and confirms the presence of Symbiodinium in this compartment of the ecosystem. These data provide context for future studies examining spatial and temporal patterns in the availability of Symbiodinium in the water column, work that will ultimately promote a greater understanding of the interactions between symbiotic dinoflagellates and their environmentally sensitive benthic hosts.
MGeT: Malware Gene-Based Malware Dynamic Analyses

Malware, as a malicious software, or applications or execution codes, has become the centerpiece of most security threats in such a unceasing open Internet environment. The essential technology of malware analysis is to extract the characteristics of malware, intended to supply signatures to detection systems and provide evidence for recovery and cleanup. The focal point in the malware analysis is how to detect malicious behaviors versus how to hide a malware analyzer from malware during runtime. In this paper, we propose an approach called Malware Gene Topology Model (MGeT) inspired by Biotechnological Genomics that can quickly detect potential malware from a large amount of software or execution codes including metamorphic or new variants of malware. Instead of extracting the signatures from the malware in the execution file level or operating system level, we identify the key malicious behaviors of malware by the underlying instructions, named malware Gene. We evaluate our method based on real-world datasets and the results demonstrate the advantages of our method over the previous studies, validating the contribution of our method.
Intuition, deduction, and the art of picking up the pieces: reciprocal gains of computational modeling and fMRI

Given recent technological and methodological developments, a liaison between neuroimaging and computational neuroscience becomes increasingly promising. Drawing on these developments, two approaches to conduct interdisciplinary research were illustrated. This integration proved fruitful for testing existing theories of brain function as well as developing new theories. The first part of the thesis presents research embedded within the neuroscience of vision. Specifically, it is concerned with developing a framework suited for evaluating the detailed spatial activation profile predicted by a computational model of how the brain processes surfaces against neuroimaging data. The second part of the thesis presents research aimed at understanding structure-function relationships in the brain. Specifically, it is concerned with elucidating the role of the cortical rich club, a set of brain regions exhibiting very rich connectivity, in the globally coordinated integration of segregated brain regions into temporal functional networks.
A Survey & Current Research Challenges in Meta Learning Approaches based on Dataset Characteristics

Classification is a process that predicts class of objects whose class label is unknown. According to No Free Lunch (NFL) theorem, there is no single classifier that performs better on all datasets. Meta learning is one of the approaches that acquired knowledge based on the past experience. The knowledge in Meta-Learning is acquired from a set of meta-examples which stores the features of the problem and the performance obtained by executing a set of candidate algorithms on Meta Features. Based on the experience acquired by the system during training phase, ranking of the classifiers is provided based on considering various measures of classifiers.
Effects of Preheating on X-Ray Scaling Relations in Galaxy Clusters

The failure of purely gravitational and gasdynamical models of X-ray cluster formation to reproduce basic observed properties of the local cluster population suggests the need for one or more additional physical processes operating on the intracluster medium (ICM). We present results from 84 moderate-resolution gasdynamic simulations designed to investigate systematically the effects of preheating (an early elevated ICM adiabat) on the resultant, local X-ray size-temperature, luminosity-temperature, and ICM mass-temperature relations. Seven sets of 12 simulations are performed for a ΛCDM cosmology, each set characterized by a different initial entropy level Si. The slopes of the observable relations steepen monotonically as Si is increased. Observed slopes for all three relations are reproduced by models with Si ∈ 55-150 keV cm2, levels that compare favorably to empirical determinations of core ICM entropy by Lloyd-Davies, Ponman, & Cannon. The redshift evolution for the case of a locally successful model with Si = 106 keV cm2 is presented. At temperatures kT ≳ 3 keV, little or no evolution in physical isophotal sizes or bolometric luminosities is expected to z ≲ 1. The ICM and total masses at fixed T are lower at higher z, as expected from the virial theorem. ICM mass fractions show a mild T dependence. Clusters with kT ≲ 3 keV contain ICM mass fractions depressed by modest amounts (≲25%) below the cosmic mean baryon fraction Ωb/Ωm; hot clusters subject to preheating remain good tracers of the cosmic mix of clustered mass components at redshifts z ≲ 1.
A Multilevel Test of the Racial Threat Hypothesis in One State’s Juvenile Court

Noting the paucity of research on the racial threat hypothesis in the juvenile courts, this study examined the interplay of defendant characteristics and country-level characteristics on dispositions. Data were retrieved from the Department of Juvenile Justice files in South Carolina and were analyzed using multinomial logistic hierarchical linear modeling. Results revealed support for the racial threat hypothesis, as racial inequity operated in a different manner (more punitively) for Black defendants. Larger Black populations in counties also led to an increased use of punitive sanctions. In addition, concentrated disadvantage effects were found, and heightened levels of teenage population led to higher incarceration rates for Black defendants. Limitations of this study, implications for stakeholders/practitioners, and directions for future research are discussed.
An extended OTIS-Cube interconnection network

This paper proposes a new extended OTIS-Cube Interconnection network of the well known class of network, OTIS-Cube. This paper presents attractive topological properties for the new network which carry a way the weakness of some topological properties of the OTIS-Cube found in the degree and the diameter. The new network has a regular degree, a small diameter, and a semantic structure. An efficient routing algorithm is proposed. In this new algorithm, an optimal path is selected based on the two locations of the source node and the destination node. The paper presents also a comparative analysis proving the superiority of the proposed interconnection network over the OTIS-Cube. The comparison is obtained in terms of topological properties measures and routing distances.
Inductive reasoning about effectful data types

We present a pair of reasoning principles, definition and proof by rigid induction, which can be seen as proper generalizations of lazy-datatype induction to monadic effects other than partiality. We further show how these principles can be integrated into logical-relations arguments, and obtain as a particular instance a general and principled proof that the success-stream and failure-continuation models of backtracking are equivalent. As another application, we present a monadic model of general search trees, not necessarily traversed depth-first. The results are applicable to both lazy and eager languages, and we emphasize this by presenting most examples in both Haskell and SML.
A real-time knowledge processing executive for Army rotorcraft applications

The authors describe research in the development of a real-time knowledge-based system execution environment suitable for use in next-generation Army helicopters. They first describe the unique problems which must be solved in real-time knowledge processing applications. They then describe an overall processing architecture for achieving the requisite real-time performance. The execution environment is being specifically designed for embedded applications such as the mission equipment package of the RAH-66 Comanche helicopter. The environment will provide the requisite software execution facilities which heretofore have not been available in an integrated embedded execution environment. This execution environment will provide the control features required to manage real-time problem solving. <<ETX>>
Creating new functions in a P2P network using a source routing based method and a genetic algorithm

In this paper we first assume a peer-to-peer (P2P) network composing nodes with a variety of functions and then propose a method for each node to create new functions by combining others' functions in a P2P network. In the proposed method, a node (user) that desires a new function first creates a candidate of new function combining others' functions by using a source routing based method that determines a next hop node based on numerical operations. Next, the node evaluates the created new function candidate and then genetic operators of a genetic algorithm adjusts parameter values used by the source routing based method based on the user's evaluation value. Thus, new functions desired by a node are created by repeating the source routing for creating a candidate of new function, evaluation of the new function candidate by a node, and adjustment of the routing parameters by genetic operators. We show basic effectiveness of the proposed method through simulations.
Scaling and modeling of call center arrivals

The Poisson process has been an integral part of many models for the arrival process to a telephone call centers. However, several publications in recent years suggest the presence of a significant “overdisperson” relative to the Poisson process in real-life call center arrival data. In this paper, we study the overdispersion in the context of “heavy traffic” and identify a critical factor that characterizes the stochastic variability of the arrivals to their averages. We refer to such a factor as the scaling parameter and it potentially has a profound impact on the design of staffing rules. We propose an new model to capture the scaling parameter in this paper.
Cyclical Budgetary Policy and Economic Growth: What Do We Learn from OECD Panel Data?

This paper uses yearly panel data on OECD countries to analyze the relationship between growth and the cyclicality of government debt. We develop new time-varying estimates of the cyclicality of public debt. Our main findings can be summarized as follows: (i) less procyclical public debt growth can have significantly positive effects on productivity growth, in particular when financial development is lower; (ii) public debt growth has become increasingly countercyclical in most OECD countries over the past twenty years, but this trend has been less pronounced in the EMU; (iii) less financially developed or more open economies display less countercyclical public debt growth.