Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk Evaluation of Project Option Based on Probabilistic Influence Diagram

The option evaluation method of investment project influenced by numerous risk factors, in this paper, these risk factors are subdivided into fourteen risk indexes, then use the probabilistic influence diagram method, through model simplifying and probability reasoning, and eventually to identify the key factors that affect the evaluation of project option, it is of important significance in theory and practice to the perfection and promotion of investment projects' option evaluation method.
Modeling the Structural Basis of Human CCR5 Chemokine Receptor Function: From Homology Model Building and Molecular Dynamics Validation to Agonist and Antagonist Docking

This article describes the construction and validation of a three-dimensional model of the human CCR5 receptor using a homology-based approach starting from the X-ray structure of the bovine rhodopsin receptor. The reliability of the model is assessed through molecular dynamics and docking simulations using both natural agonists and a synthetic antagonist. Some important structural and functional features of the receptor cavity and the extracellular loops are identified, in agreement with data available from site-directed mutagenesis. The results of this study help to explain the structural basis for the recognition, activation, and inhibition processes of CCR5 and may provide fresh insights for the design of HIV-1 entry blockers.
A miniaturized electrokinetic bioparticle microseparator based on travelling wave dielectrophoresis for lab on a chip applications

In order to offer the ability of smaller volumes and high throughput in Lab-On-a-Chip devices more miniaturized components are needed. In this paper a microchannel technique based on surface micromachining method is modified to a miniaturized microseparator. Any downscaling of channels which is used microfluidic components in such systems intensified the phenomena. The proposed device is a 4-phase travelling wave microseparator with fishbone-like and sorting electrodes. Due to fabrication process the electrodes made of highly boron-doped poly-silicon are covered by a thin insulating (silicon-nitride) layer. Additional advantage of the silicon-nitride layer on electrode arrays is the reduction of high electric field gradient. The effect of this layer on functionality of the microseparator is discussed. The simulation results show that a good focusing and separation occurs in the frequency range of 5MHz and 150kHz respectively, when electrical conductivity of buffer fluid is near 10μs/m. The fabrication steps are presented and influence of buffer fluid conductivity on the functionality of separator is presented.
Colouration in Atlantic puffins and blacklegged kittiwakes: monochromatism and links to body condition in both sexes

Sexual dimorphism is widely used as an indirect measure of the intensity of sexual selection. It is also a way to evaluate whether different selective pressures act on males and females. Dichromatism, defined as a difference in colouration between males and females, may for instance result from selection for crypsis in females and selection for conspicuousness in males. Here, we conducted a study to investigate whether differential sexual selective pressures might act on the colour traits of two colonial seabird species, the Atlantic puffin Fratercula artica and the black-legged kittiwake Rissa tricactyla. First, we used spectrophotometry and visual modelling to determine whether these presumed monomorphic birds are really monochromatic from an avian perspective (birds and humans have a different vision). Second, we estimated whether some of their colourations have the potential to be sexually or socially selected by determining whether these colourations were related to body condition in males and females, and whether the yellow, orange and red colourations may contain carotenoid pigments. Our results indicated that both species were fully monochromatic from an avian perspective. Moreover, our preliminary analyses suggested that the yellow, orange and red colours of these birds contained carotenoids. Lastly, some indices of colouration were positively linked to estimates of condition. Birds in better condition had redder gape (both species) and bill (puffins). In puffins, the relation between condition and gape colouration was significantly stronger in females than males. By contrast, the size of the gape rosette was larger in males than females. The positive links we found between colour indices and condition, together with the absence of sexual dichromatism, suggest that mutual sexual selection may act in these two species.
Identifying the Cost of Security

Organizations know that investing in security measures is an important requirement for doing business. But how much should they invest and how should those investments be directed? Many organizations have turned to a risk management approach to identify the largest threats and the control measures that could help mitigate those threats. This thesis presents a framework to support analysis of the costs and benefits of those control measures. This analysis can be performed by using either quantification methods or by using a qualitative approach. Based on a study of five distinct security areas–Identity Management, Network Access Control, Intrusion Detection Systems, Business Continuity Management and Data Loss Prevention–nine cost factors are identified for IT security, and for only five of those nine a quantitative approach is feasible for the cost factor. This study finds that even though quantification methods are useful, organizations that wish to use those should do this together with more qualitative approaches in the decision-making process for security measures.
Design and implementation of a MIMO MAC protocol for ad hoc networking

Multiple Input Multiple Output (MIMO) provides the potential for significant gains in channel capacity and spectral efficiency through its use of multiple element antenna systems and space-time coding. There are numerous published accounts of experimental MIMO communications links with high numbers of transmit and receive antennas, as well as commercial products exploiting MIMO with smaller antenna configurations. However, the use of MIMO as a modulation scheme for mobile ad hoc networking has so far only been explored as part of a theoretic or simulation exercise. In this paper we describe the design and implementation of a MAC protocol for a MIMO system which is designed to exploit the capability of 8x10 MIMO for ad hoc networks. This work is unique in that from the start our design considered the specific capabilities and parameters of an existing 8x10 MIMO physical layer, including nonnegligible decoding delays, variable array size and coding schemes, as well as fixed frame sizes. Furthermore, given the bandwidths and antenna array sizes available, the physical layer design could achieve hundreds of megabits in link capacity, and our MAC protocol therefore needed to be designed and implemented in such a way as to maximize this capacity, particularly in a network multi-hop environment. Our MIMO-MAC protocol provides this capability while supporting multi-hop ad hoc networks through novel schemes for channel access, segmentation/reassembly, ARQ and link adaptation. This paper discusses the challenges and tradeoffs involved in developing a MAC for real MIMO hardware, and briefly describes a subset of our solutions to them.
Agile Bottom-Up Development of Domain-Specific IDEs for Model-Driven Development

Diminishing time-to-market and rapidly evolving technology stacks stretch traditional software development methods to their limits. In this paper, we propose a novel process for bottom-up development of domain-specific IDEs based on agile principles. It aims to enable a fine-grained co-evolution of domain-specific modeling languages (DSMLs) and their model editors and code generators. We illustrate our approach by iteratively developing an IDE for model-driven development of mobile applications. As a key success factor for continuous DSML development, we determine the automated deduction of migration scripts for all dependent artifacts of a DSML evolution step.
The Chameleon framework : practical solutions for memory behavior analysis

Though the performance of many applications is dominated by memory behavior, our ability to describe, capture, compare, and recreate that behavior is quite limited. This inability underlies much of the complexity in the field of performance analysis: it is fundamentally difficult to relate benchmarks and applications or use realistic workloads to guide system design and procurement. A concise, observable, and machine-independent characterization of memory behavior is needed. This dissertation presents the Chameleon framework, an integrated solution to three classic problems in the field of memory performance analysis: reference locality modeling, accurate synthetic address trace generation, and the creation of synthetic benchmark proxies for applications. The framework includes software tools to capture a concise, machine-independent memory signature from any application and produce synthetic memory address traces that mimic that signature. It also includes the Chameleon benchmark, a fully tunable synthetic executable whose memory behavior can be dictated by these signatures. By simultaneously modeling both spatial and temporal locality, Chameleon produces uniquely accurate, general-purpose synthetic traces. Results demonstrate that the cache hit rates generated by each synthetic trace are nearly identical to those of the application it targets on dozens of memory hierarchies representing many of today's commercial offerings. This work focuses on the unique challenges of high-performance computing (HPC) where workload selection, benchmarking, system procurement, performance prediction, and application analysis present important challenges. The Chameleon framework can aid in each scenario by providing a concise representation of the memory requirements of full-scale applications that can be tractably captured and accurately mimicked.
An energy and delay aware data collection for mobile sink Wireless Sensor Networks based on clusters

In Wireless Sensor Networks, recent studies reveal using mobile sink as a solution for collecting the data has been shown to be an effective way of improving sensor network performances. In this paper, Firstly, we analyze the data collection algorithms based on hierarchical or cluster and the Mobile Element Scheduling(MES) algorithms. Subsequently, a new energy and delay aware hybrid data collection algorithm(HDCA) is presented, which computes the path of mobile sink based on cluster head, not based on every sensor directly. Lastly, a simulation to analyze and evaluate its performances is implemented. The result shows that the proposed algorithm not only can enhance Quality of Service(QoS) performances such as delay and data loss rate, but also has excellence flexibility to networks topology and size.
Stochastic Gradient Descent Training for L1-regularized Log-linear Models with Cumulative Penalty

Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework is attractive because it often requires much less training time in practice than batch training algorithms. However, L1-regularization, which is becoming popular in natural language processing because of its ability to produce compact models, cannot be efficiently applied in SGD training, due to the large dimensions of feature vectors and the fluctuations of approximate gradients. We present a simple method to solve these problems by penalizing the weights according to cumulative values for L1 penalty. We evaluate the effectiveness of our method in three applications: text chunking, named entity recognition, and part-of-speech tagging. Experimental results demonstrate that our method can produce compact and accurate models much more quickly than a state-of-the-art quasi-Newton method for L1-regularized loglinear models.
LETTER TO THE EDITOR: Derivation of Boltzmann equation in closed-time-path formalism

A systematic derivation of the Boltzmann equation is presented in the framework of closed-time-path formalism. Introducing a new type of probe, the expectation value of number operator is calculated as a functional of source. Then solving for the source by inverting the relation, the equation of motion for number is obtained when the source is removed, and it turns out to be the Boltzmann equation. The inversion formula is used in the course of derivation.
Delving Deeper into MOOC Student Dropout Prediction

In order to obtain reliable accuracy estimates for automatic MOOC dropout predictors, it is important to train and test them in a manner consistent with how they will be used in practice. Yet most prior research on MOOC dropout prediction has measured test accuracy on the same course used for training the classifier, which can lead to overly optimistic accuracy estimates. In order to understand better how accuracy is affected by the training+testing regime, we compared the accuracy of a standard dropout prediction architecture (clickstream features + logistic regression) across 4 different training paradigms. Results suggest that (1) training and testing on the same course ("post-hoc") can overestimate accuracy by several percentage points; (2) dropout classifiers trained on proxy labels based on students' persistence are surprisingly competitive with post-hoc training (87.33% versus 90.20% AUC averaged over 8 weeks of 40 HarvardX MOOCs); and (3) classifier performance does not vary significantly with the academic discipline. Finally, we also research new dropout prediction architectures based on deep, fully-connected, feed-forward neural networks and find that (4) networks with as many as 5 hidden layers can statistically significantly increase test accuracy over that of logistic regression.
Improving Data Transmission for Collaborative Work Using Forwarding Nodes in Mobile Ad Hoc Environments

Mobile users are often involved in team activities and exhibit collaborative mobility in realistic ad hoc network application scenarios. Due to diverse group mobility patterns, the network may remain partitioned for extended durations. This paper describes an approach to reduce the communication disruptions by deploying forwarding nodes. The forwarding nodes explore the field periodically in orderto gather network information for countering the influence from mobility and sparseness of node deployment. By selecting the rendezvous grid pair, the forwarding nodes can move to appropriate locations to recover communication between disconnected groups. The mechanism has been implemented in the network simulator ns-2. The simulation results show that the mechanism can efficiently improve information availability and also achieve the required communication quality.
Scaling to Build the Consolidated Audit Trail : A Financial Services Application of Google Cloud Bigtable

Google Cloud Bigtable is a fully managed, high-performance, extremely scalable NoSQL database service offered through the industry-standard, open-source Apache HBase API, powered by Bigtable. The Consolidated Audit Trail (CAT) is a massive, government-mandated database that will track every equities and options market event in the US financial industry over a six-year period. We consider Google Cloud Bigtable in the context of CAT, and perform a series of experiments measuring the speed and scalability of Cloud Bigtable. We find that Google Cloud Bigtable scales well and will be able to meet the requirements of CAT. Additionally, we discuss how Google Cloud Bigtable fits into the larger full technology stack of the CAT platform.
On Rank Functions of Graphs

We study rank functions (also known as graph homomorphisms onto Z), ways of imposing graded poset structures on graphs. We first look at a variation on rank functions called discrete Lipschitz functions. We relate the number of Lipschitz functions of a graph G to the number of rank functions of both G and G× E . We then find generating functions that enable us to compute the number of rank or Lipschitz functions of a given graph. We look at a subset of graphs called squarely generated graphs, which are graphs whose cycle space has a basis consisting only of 4-cycles. We show that the number of rank functions of such a graph is proportional to the number of 3-colorings of the same graph, thereby connecting rank functions to the Potts model of statistical mechanics. Lastly, we look at some asymptotics of rank and Lipschitz functions for various types of graphs.
Streamline-Based Topological Graph Construction with Application to Self-Animated Images

Vector field analysis and visualization is a fundamental tool in science and engineering applications, raising the need for robust methods to capture and represent the global vector field behavior. One such representation, the topological graph, partitions the domain into regions where the flow of the vector field is homogeneous. This work introduces a topological graph construction based on streamlines. It is guaranteed to produce a coherent result even when some singularities are not detected. This work also details an application of topological graphs to improve the generation of self-animated images. In this application, the streamline-based approach carries almost no overhead, since self-animated images already rely on streamlines, but leads to a threefold speed-up of the core processing.
Double Directional Channel Measurements in an Arched Tunnel and Interpretation Using Ray Tracing in a Rectangular Tunnel

The objective of this paper is to study the wideband characteristics of the radio channel in a tunnel environment, not only the delay spread, but also the angle of departure/arrival of the rays, their relative weights and their delays, which are important values for Multiple-Input Multiple-Output applications. In order to achieve this goal, a measurement campaign has been carried out in a straight arched tunnel over a frequency band extending from 2.8 to 5.0GHz and distance varying from 50m up to 500m. First, the variations of the channel impulse response and of the delay spread versus the distance between the transmitter and the receiver are analyzed. Then, the bidirectional channel characteristics have been extracted from the measured channel matrices using a high resolution estimation algorithm. The main contribution of this paper is to clearly show the quantitative variation of the delay spread and the angle of departure/arrival of the rays along a real tunnel and to investigate the possibility of using the ray theory in a rectangular tunnel to interpret experimental results obtained in an arched tunnel.
Traceability as input for model transformations

Some model transformations require more information than can be derived from its source model(s) in order to generate a meaningful target model. For example, a transformation with two source models needs to know how their respective model elements relate; these relations often only exist implicitly as part of the transformations developer’s knowledge. In this paper we show that traceability models, who can be automatically generated as part of any model transformation, contain explicit interand intra-model relations that are valuable to subsequent transformations. We explain how to extract this information and propose a number of additions to current transformation techniques that are needed to completely open up traceability information to transformation developers.
3D non-linear invisible boundary detection filters

The human vision system can discriminate regions which differ up to the second order statistics only. A lot of malignant tumours have boundaries which are not visible to the human eye. We present an algorithm designed to reveal "hidden" boundaries in grey level images, by computing gradients in higher order statistics of the data. We demonstrate it by applying it to the identification of possible "hidden" boundaries of gliomas as manifest themselves in MRI 3D scans.
A Constructive Learning Algorithm for Discriminant Tangent Models

To reduce the computational complexity of classification systems using tangent distance, Hastie et al. (HSS) developed an algorithm to devise rich models for representing large subsets of the data which computes automatically the "best" associated tangent subspace. Schwenk & Milgram proposed a discriminant modular classification system (Diabolo) based on several autoassociative multilayer perceptrons which use tangent distance as error reconstruction measure. We propose a gradient based constructive learning algorithm for building a tangent subspace model with discriminant capabilities which combines several of the the advantages of both HSS and Diabolo: devised tangent models hold discriminant capabilities, space requirements are improved with respect to HSS since our algorithm is discriminant and thus it needs fewer prototype models, dimension of the tangent subspace is determined automatically by the constructive algorithm, and our algorithm is able to learn new transformations.
Ownership structure, corporate governance and firm performance: Evidence from an African emerging market

Purpose - In spite of an abundance of corporate governance literature across the world, the Botswana corporate sector is lacking. The purpose of this study is to investigate the relationship among the ownership structure, board characteristics and financial performance to determine the role of corporate governance in the performance behavior of companies listed in such an emerging market in Africa as Botswana. Design/methodology/approach - Ordinary least square (OLS) models are applied to Botswana Stock Exchange listed firms over the period 2000-2007 to determine the role of corporate governance in the performance behavior of companies listed in an emerging market. Findings - The empirical evidence shows distinct nature of corporate governance behavior among alternative performance measures used, in particular, between accounting-based/hybrid and market-based measures. Practical implications - Such diversified findings provide the policy-makers with insights to take appropriate measures on corporate governance and stock market development in order to ensure their efficiency. Originality/value - The approach of this study is different from the other available literature as it captures all types of shareholdings together in addition to other corporate governance and firm-specific predictable variables.
Dimensions of the Concept of Professionalism in State Legislatures: A Research Note

* Abstract Over the last quarter century, American state legislatures have experienced great pressures to professionalize. Recently, political scientists have redeveloped an interest in studying the causes and the consequences of state legislative professionalism. In this note we demonstrate that the concept of professionalism has several different components. While these components are related, they are different enough that they may not be tapping the same dimension. It is possible for a state legislature to be professional in one dimension and amateur in another. Moreover, different components of professionalism seem to be associated with different socioeconomic factors in the state.