Miracle-dz/UniFAR-FTUs huggingface dataset:
Rendezvous for Cognitive Radios

Cognitive radios have been touted as a solution to communicating in a Dynamic Spectrum Access environment. This paper examines how cognitive radios initially find one another among the expanse of ever-changing open spectrum, termed the rendezvous problem. Specifically, it addresses the problem of rendezvous under varying levels of system capabilities, spectrum policies, and environmental conditions. The focus is on rendezvous when there are are no control channels or centralized controllers, which we term the blind rendezvous problem. Under these conditions, a sequence-based and modular clock blind rendezvous algorithms are proposed, and it is shown that the performance of these algorithms compares favorably to that of a random blind rendezvous algorithm. Specifically, the sequence-based algorithm provides a bounded Time To Rendezvous (TTR) and the ability to prioritize channels where rendezvous is more likely to occur; the modular clock algorithm reduces the expected TTR, requires little precoordination among radios attempting to rendezvous, and is robust to radios sensing different sets of available channels.
Neuromodulation: present and emerging methods

Neuromodulation has wide ranging potential applications in replacing impaired neural function (prosthetics), as a novel form of medical treatment (therapy), and as a tool for investigating neurons and neural function (research). Voltage and current controlled electrical neural stimulation (ENS) are methods that have already been widely applied in both neuroscience and clinical practice for neuroprosthetics. However, there are numerous alternative methods of stimulating or inhibiting neurons. This paper reviews the state-of-the-art in ENS as well as alternative neuromodulation techniques—presenting the operational concepts, technical implementation and limitations—in order to inform system design choices.
Energy Aware Cloud Computing A Review

Over the previous couple of years, cloud computing services became more and more fashionable as a result of the evolving information centers and parallel computing paradigms. The notion of a cloud is often outlined as a pool of laptop resources organized to supply a computing perform as a utility. The most important IT corporations, like Microsoft, Google, Amazon, and IBM, pioneered the sphere of cloud computing and keep increasing their offerings in information distribution and machine hosting. The operation of enormous geographically distributed information centers needs right smart quantity of energy that accounts for an oversized slice of the full operational prices for cloud information centers. Within the last years cloud computing has become a lot of and a lot of fashionable. This increase in quality of cloud services ends up in higher resource demands on the suppliers finish. a lot of resources means that a lot of energy consumption and therefore higher electricity bills. there\'s a desire to create a cloud service a lot of profitable by reducing energy usage whereas at identical time keeping the service level for the client. During this paper we\'ve got mentioned many simulators found in scientific literature to realize this goal.
Oil Price Shocks, Rigidities and the Conduct of Monetary Policy: Some Lessons from a New Keynesian Perspective

The strong and sustained rise in oil prices observed in recent years poses a challenge to monetary policy and its ability to simultaneously achieve low inflation and stable output. Against this background, the paper studies monetary policy in a small open economy New Keynesian DSGE model including oil as a production input and a component of final demand. It investigates the performance of alternative price level definitions, notably headline and core CPI, in standard interest rate rules with respect to output and inflation stabilisation. The analysis puts special emphasis on the impact of price and real wage rigidity and their interaction on the policy trade-off induced by the oil price shock. While the degree of price rigidity alone is found to have little impact on the shock transmission and generates only small differences between alternative monetary strategies, the simulations suggest a more important role for real wage stickiness. Real wage stickiness triggers second round effects and complicates stabilisation whatever the policy rule. A focus on core inflation tends to limit the contraction of output in this context. The results also point to some interaction between nominal price and real wage rigidities. In the presence of real wage rigidity, greater price flexibility is found to be destabilising, as it amplifies the initial inflation effect of shocks, thereby triggering a stronger monetary policy response and a larger output effect.
Self-Adaptive Optimized Link Prediction Based on Weak Ties Theory in Unweighted Network

Recently, link prediction becomes the focus of researchers from various fields of science, and considerable achievements have been obtained. Algorithms based on similarities constitute the research mainstream. This paper proposes an optimization to the classical algorithms: Adamic-Adar (AA) and Resource Allocation (RA) with the same foundation in local similarity. Herein, weak ties theory will be introduced to improve accuracy of AA and RA. Although Lü et al. discussed the functions of weak ties in AA and RA, only weighted network was considered. Then this paper will pay more attention to unweighted and undirected simple network. Theoretical analysis will be processed in advance, and at the end, experiments will be performed in five real networks to compare classical algorithms with the optimized index in the network through numerical analysis.
A Multiple Migration and Stacking Algorithm Designed for Land Mine Detection

This paper describes a modification to a standard migration algorithm for land mine detection with a ground-penetrating radar (GPR) system. High directivity from the antenna requires a significantly large aperture in relation to the operating wavelength, but at the frequencies of operation of GPR, this would result in a large and impractical antenna. For operator convenience, most GPR antennas are small and exhibit low directivity and a wide beamwidth. This causes the GPR image to bear little resemblance to the actual target scattering centers. Migration algorithms attempt to reduce this effect by focusing the scattered energy from the source reflector and consequentially improve the target detection rate. However, problems occur due to the varying operational conditions, which result in the migration algorithm requiring vastly different calibration parameters. In order to combat this effect, this migration scheme stacks multiple versions of the same migrated data with different velocity values, whereas some other migration schemes only use a single velocity value.
FOR DAC NONLINEARITIES IN LOWPASS AND BANDPASS DELTA-SIGMA MODULATORS-THEORY AND IMPLEMENTATION

In this paper we review a background digital DAC linearization technique for Delta-Sigma analog-to-digital converters (∆Σ ADCs). A description of the theory behind this technique, details on a modulator implementation, measurement results, and finally an outlook for enhancing this technique for bandpass ∆Σ ADCs is provided. The technique has been successfully implemented in hardware and we here give a review on our work from early system level ideas for the background error estimation to measurements on real hardware.
Integration of clock skew and register delays into a retiming algorithm

The clock frequency of a synchronous circuit can be increased by retiming, an operation of temporally and physically relocating the registers. A new approach to the retiming process is presented which enables one to consider the effects on optimal retiming of electrical issues such as variable clock distribution delays and different register delays due to variable loads and cell instances. The algorithm provides increased accuracy in determining the maximum clock frequency and also eliminates any race conditions. Depending on the nature of the synchronous circuit, retiming using this algorithms may also provide an increase in system operating clock frequency. <<ETX>>
A Survey of Some Implementation Techniques for Security Membranes ?

The notion of security membrane appears as an emerging concept in the design of secure languages for global computing. Membranes separate the computational behavior of a site from the security code controlling access to sitelocated resources. We provide a survey of some of the challenges which arise when trying to implement security membranes in an execution platform such as an operating system. We identify four main design issues: the choice of a security model; the type of architecture for the execution environment; the layer at which to place security mechanisms; and the assurance level of the platform. In each case, we discuss possible trade-offs between security, flexibility, simplicity, and trustworthiness. We then show how applying a component-based approach to design and implement the execution environment can help to reach an acceptable compromise between such properties.
Indoor positioning algorithm using light-emitting diode visible light communications

This paper proposes a novel indoor positioning algorithm using visible light communications (VLC). The algorithm is implemented by preinstalled light-emitting diode illumination systems. It recovers the VLC channel features from illuminating visible light and estimates receiver locations by analytically solving the Lambertian transmission equation group. According to our research, the algorithm is able to provide position- ing resolution higher than 0.5 mm, in a practical indoor environment. The performance significantly exceeds conventional indoor positioning approaches using microwaves. © 2012 Society of Photo-Optical Instrumentation
eam leader experience in improvement teams : A social networks erspective

In this research, we disentangle the relationship between several key aspects of a team leader’s experience and the likelihood of improvement project success. Using the lens of socio-technical systems, we argue that the effect of team leader experience derives from the social system as well as the technical system. The aspects of team leader experience we examine include team leader social capital (a part of the social system) and team leader experience leading projects of the same type (a part of the technical system). We examine four different, yet related, dimensions of a team leader’s social capital, which we motivate based on the social networks literature. One dimension, team leader familiarity, suggests that social capital is created when team leaders have experience working with current team members on prior improvement projects, and that such social capital increases the likelihood of improvement project success. We develop three additional dimensions, using social network analysis (SNA), to capture the idea that the improvement team leader’s social capital extends beyond the current team to include everyone the leader has previously worked with on improvement projects. Contrasting our SNA-based dimensions with team leader familiarity enables us to better understand the impact of a team leader’s social capital both inside and beyond the team. We also examine the effect of a team leader’s experience leading prior projects of the same type, and consider the extent to which organizational experience may moderate the impact of both team leader social capital and same-type project experience. Based on analysis of archival data of six sigma projects spanning six years from a Fortune 500 consumer products manufacturer, we find that two of our SNA-based dimensions of team leader social capital, as well as experience leading projects of the same type, increase the likelihood of project success. In addition, we show that organizational experience moderates the relationship between team leader same-type project experience and project success. However, this is not the case for the relationship between the dimensions of team leader social capital and project success. These results provide insights regarding how dimensions of team leader experience and organizational experience collectively impact the operational performance of improvement teams.
Asymmetries and cooperation in the Free Trade Area of the Americas

Abstract The prospective Free Trade Agreement of the Americas seeks to link the countries of Latin America and the Caribbean (with the exception of Cuba); with Canada and the United States, thereby forming the largest free trade area in the world. Given the huge asymmetries in the size and level of development of participating countries, the major challenge in this ambitious and complex process will be to ensure that all countries, especially the smallest and least developed ones, benefit from trade liberalization within the hemisphere. This study argues that whether FTAA translates into benefits for its members will depend largely on how these asymmetries are addressed. In particular, countries will need to conserve margins of flexibility in fostering productive development in order to increase their competitiveness and manage their capital accounts as instruments of macroeconomic regulation. According to the study, new and ambitious initiatives, such as the creation of cohesion or integration funds, and an increase in the international mobility of labour will also be necessary in order to achieve convergence in the levels of development of participating countries.
VLA H I Observations of Gas Stripping in the Virgo Cluster Spiral NGC 4522

We present VLA H I observations at ∼20″ ≃ 1.5 kpc resolution of the highly inclined, H I–deficient Virgo Cluster spiral galaxy NGC 4522, which is one of the clearest and nearest cases of ongoing intracluster medium–interstellar medium (ICM-ISM) stripping. H I is abundant and spatially coincident with the stellar disk in the center, but beyond R = 3 kpc the H I distribution in the disk is sharply truncated, and the only H I is extraplanar and all on the northwest side. Forty percent of the total H I, corresponding to 1.5 × 108 M⊙, is extraplanar and has likely been removed from the galaxy disk by an ICM-ISM interaction. The kinematics and the morphology of the H I appear more consistent with ongoing stripping and less consistent with gas fall-back, which may occur long after peak pressure. Some of the extraplanar gas has line widths (FWZI) of 150 km s-1, including a blueshifted tail of weaker emission, and much of the extraplanar gas exhibits a modest net blueshift with respect to the galaxy's disk rotational velocities, consistent with gas accelerated toward the mean cluster velocity. The southwest side of the galaxy has less H I in the disk but more H I in the halo, suggesting more effective gas removal on the side of the galaxy that is rotating into the ICM wind. In recent simulations of ICM-ISM interactions large surface densities of extraplanar gas like that in NGC 4522 are seen at relatively early stages of active stripping and not during later gas fall-back stages. The galaxy is 3. °3 ≃ 800 kpc from M87, somewhat outside the region of strongest cluster X-ray emission. The ram pressure at this location, assuming a static smooth ICM and standard values for ICM density and galaxy velocity, appears inadequate to cause the observed stripping. We consider the possibility that the ram pressure is significantly stronger than standard values, because of large bulk motions and local density enhancements of the ICM gas, which may occur in a dynamic, shock-filled ICM experiencing subcluster merging. The H I and Hα distributions are similar, with both truncated in the disk at the same radius and H II regions located throughout much of the extraplanar H I. This implies that the star-forming molecular ISM has been effectively stripped from the outer disk of the galaxy along with the H I. The inferred peak stripping rate of ∼10 M⊙ yr-1 is much larger than the galaxy's total star formation rate of ∼0.1 M⊙ yr-1, implying that the rate of triggered star formation due to ICM pressure is presently minor compared with the rate of gas lost as a result of stripping.
Extending Traditional Learning by Enforcing Collaboration and Self-Assessment

The paper presents a way to overcome the shortcomings of traditional learning by enforcing collaboration between students and introducing self-assessment as part of the process of final grade formation. Treating collaboration and self assessment as two elements of a modern learning process that are very closely bounded together, the authors argue that these elements should by no means replace the traditional (ex-cathedra) way of learning but rather extend it. A specifically designed computer science course is presented as an illustration of how the introduction of self-assessment combined with teacher evaluation can encourage collaboration between students. The benefits and drawbacks of this method are discussed.
LockSTM: Mixing Locks and Transactional Memory

Atomic sections are a technique used to simplify the writing of parallel programs. Actions performed during the execution of an atomic section should not be visible to other components in the program until after the section completes. Usually the atomicity requirement is enforced through optimistic transactional memory. However, transactional memories have the drawback that not every action is allowed to occur inside of an atomic section. In particular, I/O actions cannot be rolled back on most systems, and so they may not appear within transactions. This paper examines supporting atomic sections that can contain arbitrary actions, using a combination of locks and transactions. We present a system that infers a locking strategy, identifies problematic atomic sections and creates a hybrid solution. This paper presents the algorithm, argues the process is sound and reports experimental results.
Analysis of Spatio-Temporal Preferences and Encounter Statistics for DTN Performance

Spatio-temporal preferences and encounter statistics provide realistic measures to understand mobile user's behavioral preferences and transfer opportunities in Delay Tolerant Networks (DTNs). The time dependent behavior and periodic reappearances at specific locations can approximate future online presence while encounter statistics can aid to forward the routing decisions. It is theoretically shown that such characteristics heavily affect the performance of routing protocols. Therefore, mobility models demonstrating such characteristics are also expected to show identical routing performance. However, we argue models despite capturing these properties deviate from their expected routing performance. We use realistic traces to validate this observation on two mobility models. Our empirical results for epidemic routing show those models' largely differ (delay 67% & reachability 79%) from the observed values. This in-turn call for two important activities: (i) Analogous to routing, explore structural properties on a Global scale (ii) Design new mobility models that capture them.
A Semantic Recommender for Micro-blog Users

In this paper we propose a Twitter recommender based on a semantic description of users' interests. To express interests we use friendship information, which is readily available in users' profiles, not only in Twitter but in the majority of Social Networks, thus presenting substantial advantage in terms of computational complexity with respect to methods based on content mining. To obtain a synthetic representation of interests, we first identify, for each user, his/her topical friends, i.e. Those friends for which there is at least one associated page in Wikipedia. Then, category vectors at different levels of generality are created for each user, exploiting WiBi, the Wikipedia Bitaxonomy. The recommendation task is accomplished in three steps: First, we classify users as belonging to a target community, which is again inferred from highly popular topical friends, such as Democrat Party, Starbucks, etc. Then, for each community, we identify the relevant item sets (efficiently computed using a minimum, rather than maximum, support count). Our items are either topical friends or higher level Wikipedia categories, and the generality level is a tunable parameter. Finally, we fine-tune recommendations for each community, using semantic association rules.
Error-robust Scalable Extension of H.264/AVC Ubiquitous Streaming Using the Adaptive Packet Interleaving Mechanism

In this article, we realize error-robust scalable extension of H.264/AVC video streaming using an adaptive packet interleaving mechanism among heterogeneous networks and devices. The state-of-the-art SVC was used to provide combined scalability to adjust spatiotemporal resolutions and SNR quality. In an error-prone channel, a method of bandwidth estimation and a three-state network transition chain are proposed to adjust the transmission bit-rate and the interleaving window size, respectively. Unlike past packet interleaving methods, the interleaving window size can be adjusted dynamically to compromise pre-processing delay, e.g., packet rearrangement time for interleaving, and quality improvement. Additionally, with the understanding of the global SVC bitstream structure, an SVC coder was designed to increase the decoding efficiency and extract in real time the proper SVC-quality bitstream based on the network condition. In our experiments, performances of the adaptive packet interleaving mechanism w.r. t. distinct interleaving window sizes and network conditions are demonstrated for distinct kinds of videos.
Comment on social preferences, beliefs, and the dynamics of free riding in public good experiments

Fischbacher and Gaechter (AER, 2010) find that contributions decline in repeatedly played public good games because people are imperfect conditional cooperators who match others' contributions only partly. We re-examine the data using dynamic panel data methods and find that contributions also decline because people only partially match their own contributions from previous periods. We discuss possible interpretations.
Learning Natural Selection from the Site Frequency Spectrum

Genetic adaptation to external stimuli occurs through the combined action of mutation and selection. A central problem in genetics is to identify loci responsive to specific selective constraints. Many tests have been proposed to identify the genomic signatures of natural selection by quantifying the skew in the site frequency spectrum (SFS) under selection relative to neutrality. We build upon recent work that connects many of these tests under a common framework, by describing how selective sweeps affect the scaled SFS. We show that the specific skew depends on many attributes of the sweep, including the selection coefficient and the time under selection. Using supervised learning on extensive simulated data, we characterize the features of the scaled SFS that best separate different types of selective sweeps from neutrality. We develop a test, SFselect, that consistently outperforms many existing tests over a wide range of selective sweeps. We apply SFselect to polymorphism data from a laboratory evolution experiment of Drosophila melanogaster adapted to hypoxia and identify loci that strengthen the role of the Notch pathway in hypoxia tolerance, but were missed by previous approaches. We further apply our test to human data and identify regions that are in agreement with earlier studies, as well as many novel regions.