Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Base Station Sleep Control and RF Chain Activation for Energy-Efficient Millimeter-Wave Cellular Systems

In a millimeter-wave base station (BS) with hybrid precoding, the radio frequency (RF) chain is the main contributor to the energy consumption. As the traffic pattern varies over time, part of the RF chains in a BS or the entire BS can be turned off to prevent overheating and save energy. However, to guarantee the multiplexing gain of a hybrid precoding system, a certain number of RF chains needs to be activated. In addition, as BSs are turned off, the quality of service of users would be degraded. Thus, the number of active RF chains and the set of operating BSs should be carefully designed to achieve a tradeoff between data rate and energy consumption. We consider dynamic BS sleep control and RF chain activation to maximize the energy efficiency (EE) of a multicell millimeter-wave cellular systems. We formulate such a problem as an integer programming problem with two sets of variables. We first develop a centralized scheme, and then apply a primal decomposition to derive the optimal solution of the convex problem. Based on such solution, we derive the near optimal BS sleep control strategy with a greedy algorithm. With given BS on–off states, the optimal user association and RF chain activation are obtained by solving a linear programming problem. We then propose a distributed scheme based on a matching between users and BSs, and show that the matching process converges. The proposed schemes are evaluated with simulations, showing that near optimal performance can be achieved. Compared with baseline schemes, the system EE can be significantly improved while the data rate loss due to BS sleep control and dynamic RF chain activation is relatively small.
Tourism in Kingdom of Saudi Arabia: facts and challenges for a promising sector.

This paper explores a number of tourism variables such as visitor exports services, travel and tourism consumption and demand, tourism gross domestic product (GDP) throughout the period 1988-2011. In addition to, tourism arrivals, tourism expenditure and percentage of Saudi employment in the tourism sector throughout the period 2012-2017 in KSA. Moreover, services related to tourism sector such as numbers of transport and rent a car companies, recreations, restaurants, travel agencies, furnished apartment units and hotels, in addition to, their value added are analyzed as well throughout the period 2007-2011. The pattern of the earlier mentioned variables is investigated by employing data in levels and first differences. It then predicts their future values throughout the next decade (2012-2023) via employing the Double Exponential Smoothing technique. The results suggest that, tourism variables such as visitor exports services, travel and tourism consumption and demand and tourism gross domestic product are estimated throughout the period 2012-2023 at about (US $ billion) 7.1, 18.8, 58.1 and 13.3 (on average) respectively. Whereas, for tourism arrivals (8.5 million arrivals), tourism expenditure (30 US $ billion) and percentage of Saudi employment (29%) throughout the period 2012-2017. In addition, the prediction for services related to tourism sector (during the period 2012-2017) such as numbers of hotels, furnished apartment units, travel agencies, restaurants, rent a car and transport companies and recreations estimated at 1050, 938, 1917, 28284, 533, 2010 and 12983 respectively. Whereas, total value added for accommodation, food services, recreation, travel agencies and transportation estimated at about (US $ billion) 2.9, 5.2, 0.8, 0.2, and 5.6 respectively(during the same period). Moreover, it investigates the main difficulties facing this important industry and the suggested ways to overcome them. [Ahmed El-Kholei and Dirar Al-Otaibi. Tourism in Kingdom of Saudi Arabia: Facts and Challenges for a Promising Sector. J Am Sci 2013;9(12):810-823]. (ISSN: 1545-1003). http://www.jofamericanscience. org. 104
Model Checking and Model Finding with USE

This contribution demonstrates central options available in the tool USE (Uml-based Specification Environment) for exploring UML models within software development. It particularly uses so-called classifying OCL terms for building validation and verification scenarios. The contribution demonstrates the tool’s options with an example: statecharts together with a simple syntax model and a model for capturing finite fractions of the statechart semantics.
Making Judgments Based on Similarity and Proximity

In this study, we investigate the conceptual structure of the metaphor “SIMILARITY IS PROXIMITY. ” The results of four experiments suggest a tight mental link between similarity and proximity. Two experiments revealed that people judge entities to be more similar to each other when they are placed closely in space, while two other experiments showed that entities are judged to be closer to each other when they are thought to be more similar. We discuss this bidirectional metaphor transfer effect in light of approaches to metaphor understanding, including the long-standing view that metaphorical mappings are assumed to be asymmetrical. We also consider the implications of this bi-directional mapping for high level cognition.
Remote sensing of sun‐induced fluorescence to improve modeling of diurnal courses of gross primary production (GPP)

Terrestrial gross primary production (GPP) is an important parameter to explore and quantify carbon fixation by plant ecosystems at various scales. Remote sensing (RS) offers a unique possibility to investigate GPP in a spatially explicit fashion; however, budgeting of terrestrial carbon cycles based on this approach still remains uncertain. To improve calculations, spatio‐temporal variability of GPP must be investigated in more detail on local and regional scales. The overarching goal of this study is to enhance our knowledge on how environmentally induced changes of photosynthetic light‐use efficiency (LUE) are linked with optical RS parameters. Diurnal courses of sun‐induced fluorescence yield (FSyield) and the photochemical reflectance index of corn were derived from high‐resolution spectrometric measurements and their potential as proxies for LUE was investigated. GPP was modeled using Monteith's LUE‐concept and optical‐based GPP and LUE values were compared with synoptically acquired eddy covariance data. It is shown that the diurnal response of complex physiological regulation of photosynthesis can be tracked reliably with the sun‐induced fluorescence. Considering structural and physiological effects, this research shows for the first time that including sun‐induced fluorescence into modeling approaches improves their results in predicting diurnal courses of GPP. Our results support the hypothesis that air‐ or spaceborne quantification of sun‐induced fluorescence yield may become a powerful tool to better understand spatio‐temporal variations of fluorescence yield, photosynthetic efficiency and plant stress on a global scale.
Pricing of European-and American-style Asian Options using the Finite Element Method June 2018 Supervisors

An option is a contract between two parties where the holder has the option to buy or sell some underlying asset after a predefined exercise time. Options where the holder only has the right to buy or sell at the exercise time is said to be of European-style, while options that can be exercised any time before the exercise time is said to be of American-style. Asian options are options where the payoff is determined by some average value of the underlying asset, e.g., the arithmetic or the geometric average. For arithmetic Asian options, there are no closed-form pricing formulas, and one must apply numerical methods. Several methods have been proposed and tested for Asian options. For example, the Monte Carlo method is slow for European-style Asian options and not applicable for American-style Asian options. In contrast, the finite difference method have successfully been applied to price both Europeanand American-style Asian options. But from a financial point of view, one is also interested in different measures of sensitivity, called the Greeks, which are hard approximate with the finite difference method. For more accurate approximations of the Greeks, researchers have turned to the finite element method with promising results for European-style Asian options. However, the finite element method has never been applied to American-style Asian options, which still lack accurate approximations of the Greeks. Here we present a study of pricing Europeanand American-style Asian options using the finite element method. For European-style options, we consider two different pricing PDEs. The first equation we consider is a convection-dominated problem, which we solve by applying the so-called streamline-diffusion method. The second equation comes from modelling Asian options as options on a traded account, which we solve by using the so-called cG(1)cG(1) method. For American-style options, the model based on options on a traded account is not applicable. Therefore, we must consider the first convection-dominated problem. To handle American-style options, we study two different methods, a penalty method and the projected successive overrelaxation method. For European-style Asian options, both approaches give good results, but the model based on options on a traded account show more accurate results. For American-style Asian options, the penalty method give accurate results. Meanwhile, the projected successive over-relaxation method does not converge properly for the tested parameters. Our result is a first step towards an accurate and fast method to calculate the price and the Greeks of both Europeanand American-style Asian options. Because good estimations of the Greeks are crucial when hedging and trading of options, we anticipate that the ideas presented in this work can lead to new ways of trading with Asian options.
Quantum limit for nuclear spin polarization in semiconductor quantum dots

A recent experiment [E. A. Chekhovich et al., Phys. Rev. Lett. 104, 066804 (2010)] has demonstrated that high nuclear spin polarization can be achieved in self-assembled quantum dots by exploiting an optically forbidden transition between a heavy hole and a trion state. However, a fully polarized state is not achieved as expected from a classical rate equation. Here, we theoretically investigate this problem with the help of a quantum master equation and we demonstrate that a fully polarized state cannot be achieved due to formation of a nuclear dark state. Moreover, we show that the maximal degree of polarization depends on structural properties of the quantum dot.
A NOTE ON THRESHOLDS AND CONNECTIVITY IN RANDOM DIRECTED GRAPHS

Thresholds and phase transitions have been well studied for several properties of random undirected graphs. In this article we adapt a result of Pal asti to the context of directed graphs, thereby allowing thresholds for the uniform random directed graph model D(n;M) to be used in determining thresholds for the binomial random directed graph model D(n;p). We then determine the threshold for strong connectivity in D(n;p).
Discrete‐time control for switched positive systems with application to mitigating viral escape

This paper has been motivated by the problem of viral mutation in HIV infection. Under simplifying assumptions, viral mutation treatment dynamics can be viewed as a positive switched linear system. Using linear co‐positive Lyapunov functions, results for the synthesis of stabilizing, guaranteed performance and optimal control laws for switched linear systems are presented. These results are then applied to a simplified human immunodeficiency viral mutation model. The optimal switching control law is compared with the law obtained through an easily computable guaranteed cost function. Simulation results show the effectiveness of these methods. Copyright © 2010 John Wiley & Sons, Ltd.
The Relationship of DBSCAN to Matrix Factorization and Spectral Clustering

DBSCAN is a popular approach for density-based clustering. In this short “work in progress” paper, we want to present an interpretation of DBSCAN as a matrix factorization problem, which introduces a theoretical connection (but not an equivalence) between DBSCAN and Spectral Clustering (SC). While this does not yield a faster algorithm for DBSCAN, establishing this relationship is a step towards a more uniﬁed view of clustering, by identifying further relationships between some of the most popular clustering algorithms.
The Importance of Understanding Culture When Improving Education: Learning from Cambodia

Following Education for All, initiatives like child-friendly schools initiative is rolled out in many countries, including Cambodia. The child-friendly schools initiative is addressing general and local needs of children in schools, like a safe environment, well-trained teachers and the provision of teaching and materials. But there is also a component that is more cultural in nature and might not resonate well with the country’s culture. As Hofstede’s (1980, 1986) research concerning cultural differences indicated, a country’s culture can be described following five dimensions (individualism/collectivism, power distance, uncertainty avoidance, masculinity/femininity, and long-term/short-term orientation). Not taking a country’s culture into account while intervening with important services like education, might lead to low intervention outcomes, teachers who feel uncomfortable with the proposed contents and ways of teaching, and students who are not prepared well towards the society they live in. A cultural profile of Cambodia was missing when the ministry of education started to roll out the Education for All and Child Friendly School approaches in 2006/2007 (Schaeffer & Heng, 2016). The original research has since been enriched with additional data sets. The data sets are by no means large enough to be representative, but through triangulation a careful attempt is made to at least inform educationalists of the importance of taking culture into account when designing and implementing educational interventions to improve learning in Cambodia, and likely elsewhere. With the onset of the Sustainable Development Goals (UN Sustainable Development Knowledge Platform, 2015), such cultural understanding is a necessity in order to achieve cultural appropriate project outcomes.
Combining Linear Logic and Size Types for Implicit Complexity

Several type systems have been proposed to statically control the time complexity of lambda-calculus programs and characterize complexity classes such as FPTIME or FEXPTIME. A first line of research stems from linear logic and defines type systems based on restricted versions of the " ! " modality controlling duplication. An instance of this is light linear logic for polynomial time computation [Girard98]. A second perspective relies on the idea of tracking the size increase between input and output, and together with a restricted use of recursion, to deduce from that time complexity bounds. This second approach is illustrated for instance by non-size-increasing types [Hofmann99]. However both approaches suffer from limitations. The first one, that of linear logic, has a limited in-tensional expressivity, that is to say some natural polynomial time programs are not typable. As to the second approach it is essentially linear, more precisely it does not allow for a non-linear use of functional arguments. In the present work we adress the problem of incorporating both approaches into a common type system. The source language we consider is a lambda-calculus with data-types and iteration, that is to say a variant of Godel's system T. Our goal is to design a system for this language allowing both to handle non-linear functional arguments and to keep a good intensional expressivity. We illustrate our methodology by choosing the system of elementary linear logic (ELL) and combining it with a system of linear size types. We discuss the expressivity of this new type system and prove that it gives a characterization of the complexity classes FPTIME and 2k-FEXPTIME, for k >= 0.
A surveillance video compression algorithm based on regional dictionary

Surveillance video system as an effective means of public safety widely appeared in people’s life in recent years. Traditional video coding technology, the encoding process is complex, computation, and conflicts with hardware limitations of the monitoring system. This paper presents a kind method used to design and train redundant dictionary based on image region. Each frame is divided into same-sized area with equal blocks, then the image areas of the same position are put together as the training sample library of regional redundant dictionary. In this way, redundant dictionary compression results in the occupied volume can be reduce. On top of this dictionary, surveillance video compression coding algorithm based on the regional dictionary is designed and implemented. Experimental results show that the proposed algorithm can effectively improve the compression ratio of the algorithm.
Methods and Theories for Large-scale Structured Prediction in Natural Language Processing

This is a draft of a survey for large-scale structured prediction in natural language processing. Large-scale structured prediction is a important problem in language processing. In this paper, we introduce the significant theories and technologies for large-scale structured learning in recent years. Some important traditional models are Conditional Random Field, Structured Perceptron and Probabilistic Perceptron. These models have their own advantages in speed and performance. to reduce the labeling work of traditional models in large-scale leaning, latent variable models are used to replace the accurate labeled data. Recently, neural networks are widely used. They reduce the feature extraction work and improve the performance of large-scale structured learning. Finally, regularized models, especially structure regularization, can greatly reduce the overfitting risk of models.
Inferior tilt fixation of the glenoid component in reverse total shoulder arthroplasty: A biomechanical study

Background: Glenoid component fixation with an inferior tilt has been suggested to decrease scapular notching, but this remains controversial. We aimed here to evaluate the effect of glenoid component inferior tilt in reverse total shoulder arthroplasty (RSA) on micromotion and loss of fixation of the glenoid component by biomechanical testing. Hypothesis: Increased inferior reaming of the glenoid for inferiorly tilted implantation of the glenoid component will decrease glenoid bone stock and compromise the fixation of RSA. Materials and methods: The micromotions of the glenoid components attached to 14 scapulae from fresh frozen cadavers were measured and compared between neutral and 10◦ inferior tilts in 0.7and 1-body weight cyclic loading tests using digital-image analysis. The incidence of bone breakage or loss of fixation was assessed in the 1-body weight fatigue-loading test. Results: Micromotion was higher with a 10◦ inferior tilt than with a neutral tilt during both the 0.7-body weight (36 ± 11 m vs. 22 ± 5 m; P = 0.028) and 1-body weight (44 ± 16 m vs. 28 ± 9 m; P = 0.045) cyclic loading. The incidence of bone breakage or loss of fixation was 17% and 60% with a neutral and 10◦ inferior tilt, respectively. Discussion: Glenoid component inferior tilt fixation in RSA may reduce primary stability and increase mechanical failure of the glenoid component, thereby reducing longevity of the prosthesis. Accordingly, we recommend careful placement of the glenoid component when an inferior tilt is used. Level of evidence: Level III, Basic Science Study. © 2015 Elsevier Masson SAS. All rights reserved.
Asynchronous Proactive Cryptosystems Without Agreement ( Extended

In this paper, we present efficient asynchronous protocols that allow to build proactive cryptosystems secure against a mobile fail-stop adversary. Such systems distribute the power of a public-key cryptosystem among a set of servers, so that the security and functionality of the overall system is preserved against an adversary that crashes and/or eavesdrops every server repeatedly and transiently, but no more than a certain fraction of the servers at a given time. The building blocks of proactive cryptosystems — to which we present novel solutions — are protocols for joint random secret sharing and for proactive secret sharing. The first protocol provides every server with a share of a random value unpredictable by the adversary, and the second allows to change the shared representation of a secret value. Synchronous protocols for these tasks are well-known, but the standard method for adapting them to the asynchronous model requires an asynchronous agreement sub-protocol. Our solutions are more efficient as they go without such an agreement sub-protocol. Moreover, they are the first solutions for such protocols having a bounded worst-case complexity, as opposed to only a bounded average-case complexity.
Infinite volume extrapolation in the one-dimensional bond diluted Levy spin-glass model near its lower critical dimension

We revisited, by means of numerical simulations, the one dimensional bond diluted Levy Ising spin glasses outside the limit of validity of mean field theories. In these models the probability that two spins at distance $r$ interact (via a disordered interactions, $J_{ij}=\pm 1$) decays as $r^{-\rho}$. We have estimated, using finite size scaling techniques, the infinite volume correlation length and spin glass susceptibility for $\rho=5/3$ and $\rho=9/5$. We have obtained strong evidence for divergences of the previous observables at a non zero critical temperature. We discuss the behavior of the critical exponents, especially when approaching the value $\rho=2$, corresponding to a critical threshold beyond which the model has no phase transition. Finally, we numerically study the model right at the threshold value $\rho=2$.
Glacier mapping and monitoring based on spectral data

Spectral, and not least multi-spectral satellite data represent the backbone of spaceborne glacier mapping and monitoring, and have allowed for substantial progress of global glacier observations in recent years. In this chapter we give an overview of the information contained in, for the most part, ASTER or Landsat type spectral data, and of methods to qualitatively and quantitatively analyze this information for glacier studies. Besides multispectral techniques based on the visible, and near- and short-wave infrared sections of the spectrum, we also shortly discuss methods based on thermal and radar data, with special emphasis on the mapping of debris-covered glacier ice. A further focus is on spectral change detection techniques applied to multitemporal data over glaciers, with special attention to a novel image differencing technique. Finally, we give an overview of satellite-image based measurement of glacier flow, a group of methods that we view as a category of spectrally-based change detection.
Evaluation of UMTS RLC Parameters for MPEG-4 Video Streaming

Universal Mobile Telecommunication Systems (UMTS) known as Third Generation (3G) mobile phone systems using Wideband Code Division Multiple Access (WCDMA) standard aim to provide a high bit rate of services to enable a high quality of multimedia communications. The 3G specification entity, 3GPP, has defined a reliable link layer protocol, Radio Link Control (RLC), for hiding transmission errors from upper layers. Due to the complexity of the protocol and the a number of parameter configurations available, there are many ways that can degrade a system performance, such as incorrect parameters configuration, buffer missmanagement, protocol stalling, etc. MPEG-4 is widely used for video stream services due to its good video quality at low bit rate. In this paper, we have studied on the impacts of RLC parameters, especially RLC timer and polling mechanism, for MPEG-4 video stream transmission by using a computer simulation. Our simulation results provide some suggestions value to optimize such parameters, e.g. RLC time and polling.