Miracle-dz/UniFAR-FTUs huggingface dataset:
Extended analysis with reduced pessimism for systems with limited parallelism

Under limited parallelism, processes competing for a single processor may issue at any time operations on remote co-processors, during which the processor is not idled but granted to other ready processes instead. We reduce the pessimism in existing worst-case response time (WCRT) analysis for such systems by examining temporal patterns of local/remote execution. We extend to multi-CPU variants of the model and offer a WCRT-based feasibility test for symmetric multiprocessor (SMP) systems.
Optimized artificial neural network using differential evolution for prediction of RF power in VHF/UHF TV and GSM 900 bands for cognitive radio networks

Cognitive radio (CR) technology has emerged as a promising solution to many wireless communication problems including spectrum scarcity and underutilization. The knowledge of Radio Frequency (RF) power (primary signals and/or interfering signals plus noise) in the channels to be exploited by CR is of paramount importance, not just the existence or absence of primary users. If a channel is known to be noisy, even in the absence of primary users, using such channels will demand large quantities of radio resources (transmission power, bandwidth, etc) in order to deliver an acceptable quality of service to users. Computational Intelligence (CI) techniques can be applied to these scenarios to predict the required RF power in the available channels to achieve optimum Quality of Service (QoS). While most of the prediction schemes are based on the determination of spectrum holes, those designed for power prediction use known radio parameters such as signal to noise ratio (SNR), bandwidth, and bit error rate. Some of these parameters may not be available or known to cognitive users. In this paper, we developed a time domain based optimized Artificial Neural Network (ANN) model for the prediction of real world RF power within the GSM 900, Very High Frequency (VHF) and Ultra High Frequency (UHF) TV bands. The application of the models produced was found to increase the robustness of CR applications, specifically where the CR had no prior knowledge of the RF power related parameters. The models used implemented a novel and innovative initial weight optimization of the ANN's through the use of differential evolutionary algorithms. This was found to enhance the accuracy and generalization of the approach.
The Three U.S.-Mexico Border Wars: Drugs, Immigration, and Homeland Security

As the United States' response to the attacks of September 11, 2001, begins to take its final shape, perhaps the most affected area of the country is the U.S. borderlands with Mexico. The optimistic talk of the 1990s regarding trade, investment, and economic integration in North America has given way to a rhetoric focused on security, particularly securing and controlling all points of entry to and exit from the United States. Cities and towns across the Southwestern border have experienced firsthand the consequences of the new, security-oriented national ethos and practices embodied in the Homeland Security Act of 2002. The comprehensive security strategy now in place permeates the three border wars examined in this insightful work-the war on drugs, the war over the enforcement of immigration laws, and the war on terror. As Payan demonstrates, the effects of these three wars have been significant. They include a loss of local autonomy and a disconnect between the priorities of Washington, D.C., and the local populations. Perhaps more important, they have created a rigid international line that represents a barrier to economic, social, and cultural integration-and a source of fear and suspicion between neighbors. Payan traces the history of these policies on the border to discern and understand the evolutionary patterns and common threads that join all three policies together today. He argues that historically the border has experienced a gradual tightening and increasing militarization, culminating in today's restrictive environment. This book illuminates the ways in which border residents are coping with the stricter border security environment, and how they navigate their daily lives in the face of an increasing number of federal bureaucrats and programs designed to close the border. It examines the significant conflict between the government's efforts to close the border and the border communities' efforts to open it.
Real-Time Motion Simulation of Artificial Fish for Virtual Marine World

In interactive 3D cyber space systems including computer games and virtual reality applications, we have increased need for real-time interactive control of articulated body motions for more realistic expression of characters. Animation methods that based on articulated body motions are used for produce real-time control of artificial life's motion. But these methods are not adequate to complex systems, like virtual marine world, that lead to many interactive actions. In this paper, we present the real-time animation method that can be applied to control of artificial fish for constructing the virtual marine world.
On the Effects of Detailed Mobility Models in Vehicular Network Simulations

While it is crucial to test and evaluate protocol implementations in a real world environment, simulations are still commonly used as a first step in the protocol development for VANET research. One of the most important parameters in simulating ad-hoc networks is the node mobility. It is important to use a realistic mobility model so that results from the simulation correctly reflect the real-world performance of a VANET. A realistic mobility model should consist of a realistic topological map which reflects different densities of roads and different categories of streets with various speed limits. Another important parameter should be modeled is the obstacles. In addition, each vehicle needs to decide a turning directions at the intersection (e.g. turn left, turn right or go straight). Such a turning model could have an effect on the congestion of the road as well as on the clustering of the vehicles. Furthermore, a smooth deceleration and acceleration model should be considered since vehicles do not abruptly break and move. Many prior studies [7, 2] have shown that a realistic model with sufficient level of details is critical for accurate network simulation results.
QBEES: query by entity examples

Structured knowledge bases are an increasingly important way for storing and retrieving information. Within such knowledge bases, an important search task is finding similar entities based on one or more example entities. We present QBEES, a novel framework for defining entity similarity based only on structural features, so-called aspects, of the entities, that includes query-dependent and query-independent entity ranking components. We present evaluation results with a number of existing entity list completion benchmarks, comparing to several state-of-the-art baselines.
Interlaced Knowledge in the Emergence of a New Architecture at ATLAS, CERN

We report on a longitudinal study of the emergence of the ATLAS detector, a complex technological system developed at CERN, Geneva. Our data show that justification is an important mechanism for coordination, and that it results in the creation of interlaced knowledge, i.e., a partial overlapping of knowledge across actors and groups. Neither ? modular? nor ? common,? such interlaced knowledge confers generative properties on the enterprise by enabling actors with diverse backgrounds to make informed choices on technological alternatives, anticipate and address latent interdependencies, and harmonize their contributions leading to the emergence of a system architecture over time. ABSTRACT We report on a longitudinal study of the emergence of the ATLAS detector, a complex technological system developed at CERN, Geneva. Our data show that justification is an important mechanism for coordination, and that it results in the creation of interlaced knowledge, i.e., a partial overlapping of knowledge across actors and groups. Neither " modular " nor " common, " such interlaced knowledge confers generative properties on the enterprise by enabling actors with diverse backgrounds to make informed choices on technological alternatives, anticipate and address latent interdependencies, and harmonize their contributions leading to the emergence of a system architecture over time.
Design and implementation of position controller for electro hydraulic drives in turbine control system

Turbine control system uses electro hydraulic servo sub-system which is widely used in numerous automation and process industries. One of the major problems in designing an electro hydraulic system is, quantifying the dynamic behaviour of servomechanisms as per the requirements. In existing position controller main problem is non-linearity which affects the stability of the system. The basic position controller feedback from actuator generates non linear error, which is difficult to control. This paper is focused on position control of electro hydraulic servo valve for exponential input in turbine control systems. A novel design has been proposed to overcome the nonlinearity problems in electro hydraulic servo valve. Printed Circuit Board (PCB) has been developed using Computer Aided Design (CAD) STAR tool and GERBER file has been generated for PCB manufacturing. Digital position controller has been developed and implementation has been targeted on Virtex II FPGA. Analog and digital position controller has been realized in MATLAB. FPGA implementation for the developed RTL architecture has been carried out. The design speed has been improved to 80% and it utilizes 174 slices and needs 2 clock cycles per action with the maximum clock frequency of 100MHz. SI analysis has been carried out and maximum EMI emission at 24MHz is found to be 40. 1351dBμV/m.
Edelweiss: Automatic Storage Reclamation for Distributed Programming

Event Log Exchange (ELE) is a common programming pattern based on immutable state and messaging. ELE sidesteps traditional challenges in distributed consistency, at the expense of introducing new challenges in designing space reclamation protocols to avoid consuming unbounded storage. We introduce Edelweiss, a sublanguage of Bloom that provides an ELE programming model, yet automatically reclaims space without programmer assistance. We describe techniques to analyze Edelweiss programs and automatically generate application-specific distributed space reclamation logic. We show how Edelweiss can be used to elegantly implement a variety of communication and distributed storage protocols; the storage reclamation code generated by Edelweiss effectively garbage-collects state and often matches hand-written protocols from the literature.
Generalised Quasi-Cyclic LDPC codes based on Progressive Edge Growth Techniques for block fading channels

Generalised Quasi-Cyclic Root-Check LDPC codes based on Progressive Edge Growth (PEG) techniques for block-fading channels are proposed. The proposed Root-Check LDPC codes are suitable for channels under F= 3, 4 independent fadings per codeword which is a scenario that has not been previously considered. A generalised Quasi-Cyclic Root-Check structure is devised for F= 3, 4 independent fadings. The proposed PEG-based algorithm for generalised Quasi-Cyclic Root-Check LDPC codes takes into account the specific structure, and designs a parity-check matrix with a reduced number of cycles. The performance of the new codes is investigated in terms of the Frame Error Rate (FER). Numerical results show that the codes constructed by the proposed algorithm perform about 0.5dB from the theoretical limit.
Post Deployment Encryption Key Generation for a Fully Connected and Secure Wireless Sensor Network

In Wireless Senor Networks the use of multiple encryption keys is adopted to provide resilience against compromised encryption keys. The keys are either pre distributed or generated post deployment. Key pre distribution causes redundancy and limits scalability and link establishment. Key generation via computation requires processor intensive operations and the network might still be prone to serious consequences after a node is captured or compromised. This paper presents a key generation technique that can eliminate redundancy and key reuse, ensure link establishment, and subsequent scalability. The proposed technique provides resilience in the event of compromised nodes by localizing the impact on the network and inherently thwarts some attacks.
Feature based SLAM using laser sensor data with maximized information usage

This paper formulates the SLAM problem using 2D laser data as an optimization problem. The environment is modeled as a set of curves and the variables of the optimization problem are the robot poses as well as the parameters describing the curves. There are two key differences between this SLAM formulation and existing SLAM methods. First, the environment is represented by continuous curves instead of point clouds or occupancy grids. Second, all the laser readings, including laser beams which returns its maximum range value, have been included in the objective function. As the objective function to be optimized contains discontinuities, it can not be solved by standard gradient based approaches and thus a Genetic Algorithm (GA) based method is applied. Matching of laser scans acquired from relatively far apart robot poses is achieved by applying GA on top of the Iterative closest point (ICP) algorithm. The new SLAM formulation and the use of a global optimization algorithm successfully avoid the convergence to local minimum for both the scan matching and the SLAM problem. Both simulated and experimental data are used to demonstrate the effectiveness of the proposed techniques.
Testing for Purchasing Power Parity and Efficiency in the Taiwan Foreign Exchange Market - Financial and Economic Forecasting (Chapter 13)

In this chapter, the hypotheses of purchasing power parity (PPP) and market efficiency are tested for the bilateral exchange rate between the New Taiwan (N.T.) and the US dollar. Different test results lead to the conclusion that, a PPP relationship over the long term cannot be rejected confidently. Furthermore, an error correction analysis indicates that this long-term relationship may be helpful in explaining short-term movements in the exchange rate. For testing the efficiency of Taiwan's foreign exchange market, the relationship between the spot rate and forward rates is examined for 10-, 30- and 90-day contracts was examined using daily observations. The forward premium is spilt into two components, one due to risk and the other due to a forecasting error. Over the two consecutive sample periods examined (1 May 1992 to 15 February 1993, and 16 February to 31 December 1993) the results are suggestive of a time-varying risk premium in the former period. However, efficiency was found to be acceptable for the 30- and 90-day contracts during the latter sample period.
Optimization, validation and efficacy of the phytohaemagglutinin inflammation assay for use in ecoimmunological studies of amphibians

Amphibians are in the midst of an extinction crisis, yet there are few tools available to study amphibian immunocompetence under conditions of changing environments, disease and stress. We developed, validated and optimised a practical assay for studying amphibian immunocompetence and tested its efficacy in a real-world scenario of varying environmental conditions.
Chained Path Evaluation for Hierarchical Multi-Label Classification

In this paper we propose a novel hierarchical multi-label clas- sification approach for tree and directed acyclic graph (DAG) hierarchies. The method predicts a single path (from the root to a leaf node) for tree hierarchies, and multiple paths for DAG hierarchies, by combining the predictions of every node in each possible path. In contrast with previous approaches, we evaluate all the paths, training local classifiers for each non-leaf node. The approach incorporates two contributions; (i) a cost is assigned to each node depending on the level it has in the hierarchy, giving more weight to correct predic- tions at the top levels; (ii) the relations between the nodes in the hierarchy are considered, by incorporating the parent label as in chained classifiers. The proposed approach was experimentally evaluated with 10 tree and 8 DAG hierarchi- cal datasets in the domain of protein function prediction. It was contrasted with various state-of-the-art hierarchical clas- sifiers using four common evaluation measures. The results show that our method is superior in almost all measures, and this difference is more significant in the case of DAG struc- tures.
Effects of human traffic on the movement patterns of Hawaiian spinner dolphins (Stenella longirostris) in Kealakekua bay, Hawaii

Kealakekua Bay is an important resting site for Hawaiian spinner dolphins (Stenella longirostris) and is popular with both local residents and tourists. Human activities occurring here include swimming, snorkeling, kayaking, and motor-boating. The objectives of this study were to document movement patterns of dolphin groups in Kealakekua Bay, to determine if different types and levels of human activity within the bay result in quantifiable changes in dolphin group movement patterns, and to provide baseline data for future studies. Theodolite tracking was used to assess responses of dolphin groups to human traffic. Variables examined included group mean leg speed (leg speed: the distance between two consecutive theodolite fixes of a dolphin group divided by time; mean leg speed: the average of all leg speeds comprising a track) and group reorientation rate. Swimmers and/or vessels were present within 100 m of all dolphin groups tracked during all surveys. Regression analyses were used to examine potential relationships between dolphin group related variables (e.g., reorientation rate, mean leg speed) and variables related to human activities (e.g., swimming, kayaking, motor-boating). Increasing levels of human activity had a limited but measurable effect on the movement patterns of Hawaiian spinner dolphin groups at this site.
Diffusion bases dimensionality reduction

The overflow of data is a critical contemporary challenge in many areas such as hyper-spectral sensing, information retrieval, biotechnology, social media mining, classification etc. It is usually manifested by a high dimensional representation of data observations. In most cases, the information that is inherent in high-dimensional datasets is conveyed by a small number of parameters that correspond to the actual degrees of freedom of the dataset. In order to efficiently process the dataset, one needs to derive these parameters by embedding the dataset into a low-dimensional space. This process is commonly referred to as dimensionality reduction or feature extraction. We present a novel algorithm for dimensionality reduction - diffusion bases - which explores the connectivity among the coordinates of the data and is dual to the diffusion maps algorithm. The algorithm reduces the dimensionality of the data while maintaining the coherency of the information that is conveyed by the data.
Macrophages Homing to Metastatic Lymph Nodes Can Be Monitored with Ultrasensitive Ferromagnetic Iron-Oxide Nanocubes and a 1.5T Clinical MR Scanner

Background Due to the ability of macrophages to specifically home to tumors, their potential use as a delivery vehicle for cancer therapeutics has been suggested. Tracking the delivery and engraftment of macrophages into human tumors with a 1.5T clinical MR scanner requires the development of sensitive contrast agents for cell labeling. Therefore, this study aimed to determine whether intravenously injected macrophages could target a primary tumor as well as metastatic LNs, and whether these cells could be detected in vivo by MRI. Methodology Peritoneal macrophages were obtained from BALB/c nude mice. The viability, phagocytotic capacity and migratory activity of the macrophages were assessed. MR imaging was performed using a clinical 1.5 T MR scanner and we estimated the T2* of the labeled macrophages. Metastatic lymph nodes were produced in BALB/c nude mice. We administrated 2×106 macrophages labeled with 50 µg Fe/mL FIONs intravenously into the mice. In the 3D T2* GRE MR images obtained one day after the injection of the labeled macrophages or FION solution, the percentages of pixels in the tumors or LNs below the minimum normalized SI (signal intensity) threshold were summated and reported as the black pixel count (%) for the FION hypointensity. Tumors in the main tumor model as well as the brachial, axillary and inguinal lymph nodes in the metastatic LN models were removed and stained. For all statistical analyses, single-group data were assessed using t test or the Mann-Whitney test. Repeated measurements analysis of variance (ANOVA) with Tukey–Kramer post hoc comparisons were performed for multiple comparisons. Conclusions The FION-labeled macrophages, which could be non-invasively monitored using a 1.5 T clinical MR scanner, targeted both the main tumors and LN metastases. Overall, the results of this study suggest that the use of macrophages may have many future applications in the clinic for vectorizing therapeutic agents toward main tumors as well as LN metastases.
Power model validation through thermal measurements

Simulation environments are an indispensable tool in the design, prototyping, performance evaluation, and analysis of computer systems. Simulator must beable to faithfully reflect the behavior of the system being analyzed. To ensure the accuracy of the simulator, it must be verified and determined to closely match empirical data. Modern processors provide enough performance counters to validate the majority of the performance models; nevertheless, the information provided is not enough to validate power and thermal models. In order to address some of the difficulties associated with the validation of power andthermal models, this paper proposes an infrared measurement setup to capture run-time power consumption and thermal characteristics of modern chips. We use infrared cameras with high spatial resolution (10x10μm) and high frame rate (125fps) to capture thermal maps. To generate a detailed power breakdown (leakage and dynamic) for each processor floorplan unit, we employ genetic algorithms. The genetic algorithm finds a power equation for each floorplan block that produces the measured temperature for a given thermal package. The difference between the predicted power and the externally measured power consumption for an AMD Athlon analyzed in this paper has less than 1% discrepancy. As an example of applicability, we compare the obtained measurements with CACTI power models, and propose extensions to existing thermal models to increase accuracy.
Creating Exploratory Tasks for a Faceted Search Interface

In this paper we describe a process for creating and evaluating exploratory tasks for a faceted search interface. We used the tasks in an eye tracking study of a faceted library catalog search interface. We report on user perceptions of the tasks. The method is intended to be extensible to generate exploratory tasks for other types of interfaces and domains.