Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution of The Yield Curve and the Business Cycle : An Econometric Model

We propose a framework to model the evolution of the entire yield curve over time, maintaining consistency with the cross sectional fit across maturities. Using a parsimonious representation of the business cycle, namely the loop representation, as the key driver of the yield curve, the model combines the cross sectional properties like the curve shape with its dynamic evolution, depending on the business cycle. In doing so the model accounts for the spatio-temporal correlation structure of the yields.The model establishes a mapping between the stylised phases of the business cycle and stylised yield curve shapes in those phases. We provide empirical evidence using data from the U.S.A.
From physical security to cybersecurity

Security is a critical concern around the world. In many domains from cybersecurity to sustainability, limited security resources prevent complete security coverage at all times. Instead, these limited resources must be scheduled (or allocated or deployed), while simultaneously taking into account the importance of different targets, the responses of the adversaries to the security posture, and the potential uncertainties in adversary payoffs and observations, etc. Computational game theory can help generate such security schedules. Indeed, casting the problem as a Stackelberg game, we have developed new algorithms that are now deployed over multiple years in multiple applications for scheduling of security resources. These applications are leading to real-world use-inspired research in the emerging research area of “security games. ” The research challenges posed by these applications include scaling up security games to real-world-sized problems, handling multiple types of uncertainty, and dealing with bounded rationality of human adversaries. In cybersecurity domain, the interaction between the defender and adversary is quite complicated with high degree of incomplete information and uncertainty. While solutions have been proposed for parts of the problem space in cybersecurity, the need of the hour is a comprehensive understanding of the whole space including the interaction with the adversary. We highlight the innovations in security games that could be used to tackle the game problem in cybersecurity.
An advanced security-aware Cloud architecture

Nowadays, Cloud offers many interesting features such as on-demand and pay-as-you-go resources, but induces new security problems in case a company wants to outsource its critical services. But since Clouds are shared between multiple tenants, both applications and execution environments need to be secured consistently in order to avoid possible attacks from malicious tenants. Moreover, if a large range of security mechanisms can improve the Cloud security, the configuration of those mechanisms to guarantee a global security property remains an open problem. Nowadays Clouds solutions lack two key features in order to realize it: an easy expression of security requirements and an actual enforcement of those requirements. This paper describes an overall architecture providing those features and an experiment run in order to demonstrate its validity. Our solution includes a language, a distribution engine and a security enforcement agent. The language eases the definition of the security properties required to plug an application into a Cloud. The distribution engine computes the sub-properties related to the different resources that must be deployed into the Cloud and coordinates the different enforcement agents associated to the provisioned resources. Our use-case addresses private hosting of customer data into the Cloud. The implementation and experiments show that the global security requirements (authentication and confidentiality) are satisfied when the application is scheduled within virtual machines and shared resources.
Turing's Imitation Game has been Improved

Using the recently introduced universal computing model, called orchestrated machine, that represents computations in a dissipative environment, we consider a new kind of interpretation of Turing's Imitation Game. In addition we raise the question whether the intelligence may show fractal properties. Then we sketch a vision of what robotic cars are going to do in the future. Finally we give the specification of an artificial life game based on the concept of orchestrated machines. The purpose of this paper is to start the search for possible relationships between these different topics.
Pedestrian detection with image segmentation and virtual mask

Pedestrian detection is one of the most popular research areas in video processing and it is vital for video surveillance systems. In this paper, we present a real-time pedestrian detection system based on Dalal and Triggs's human detection framework with the use of image segmentation and virtual mask. Image segmentation enables the system to focus only on the region of interest whereas the virtual mask reduces noise and unnecessary processing. The system has high computational speed while it retains the discriminative power of Histogram of Oriented Gradient (HOG) features for pedestrian detection. It is tested with videos captured in a single task environment and in various lengths. The experimental results showed that most of the pedestrians in the videos are correctly detected, achieving an overall accuracy of 83.29% with low amount of computational time, which implies the effectiveness in detecting pedestrians and the real-time property of the proposed system.
Urban Safety Prediction Using Context and Object Information via Double-Column Convolutional Neural Network

Recently, various studies are performed on theanalysis of urban environment (e.g. safety, hygiene, economyand population). Particularly, the prediction of urban safetyhas received a lot of attention in society. In this paper, wepropose safety prediction of urban place using ConvolutionalNeural Network. To predict more accurate safety score, we usethe fusion of context and object information. To do this, weadopt Double-columns Convolutional Neural Network whichconsist of one column is context information extraction column, the other object information extraction column. Contextinformation is extracted from re-sized whole image and objectinformation is extracted from highest saliency score patchof object saliency map. We trained our prediction modelusing Place Pulse 1.0 dataset. To evaluate the performanceof our prediction model, we compared with SVR model andAlexnet model using RMSE. Also, we analyze correlationground truth safety scores and predicted safety scores. Fromour experimental results, our prediction model showed thebest performance (RMSE of 0.7403 and pearson/spearmancorrelation coefficient of 0.903/0.900).
Translation-based verification of Web services composition via ZING

BPEL4WS (BPEL for short) is a standard business process execution language for Web services composition. To formally verify the correctness and reliability of Web services compositions, we propose an Input/Output Labelled Transition System (I/OLTS) as the intermediate formal model, which is well adapted to model BPEL constructs and handle faults, events, terminations, message correlation and activities. To be able to automatically verify Web services compositions via a model checker, we first develop a translation procedure to translate BPEL language into I/OLTS, and then develop another translation procedure to translate the I/OLTS model into the input language of ZING, a software model checker developed by Microsoft. The translation-based verification process for Web services composition is illustrated by a case study.
Robust protein–protein interactions in crowded cellular environments

The capacity of proteins to interact specifically with one another underlies our conceptual understanding of how living systems function. Systems-level study of specificity in protein–protein interactions is complicated by the fact that the cellular environment is crowded and heterogeneous; interaction pairs may exist at low relative concentrations and thus be presented with many more opportunities for promiscuous interactions compared with specific interaction possibilities. Here we address these questions by using a simple computational model that includes specifically designed interacting model proteins immersed in a mixture containing hundreds of different unrelated ones; all of them undergo simulated diffusion and interaction. We find that specific complexes are quite robust to interference from promiscuous interaction partners only in the range of temperatures Tdesign > T > Trand. At T > Tdesign, specific complexes become unstable, whereas at T < Trand, formation of specific complexes is suppressed by promiscuous interactions. Specific interactions can form only if Tdesign > Trand. This condition requires an energy gap between binding energy in a specific complex and set of binding energies between randomly associating proteins, providing a general physical constraint on evolutionary selection or design of specific interacting protein interfaces. This work has implications for our understanding of how the protein repertoire functions and evolves within the context of cellular systems.
Illegal Information Flow Detection in Electronic Institution

Due to the lack of information flow control mechanism, the authorization model of an electronic institution (EI) may bring illegal information propagation threatening the confidentiality of sensitive data. By analyzing information flows among roles, algorithms for detecting and controlling potential illegal information flows in EIs are designed. The algorithms are applied to simulating classic cases. The experiments show the proposed algorithms can prevent unauthorized information leakage and enhance securities of EI based systems.
Strategic Information Systems Planning: A Case from Public Organization

Strategic information system planning (SISP) is one of the important steps in information system (IS) development. This proposed empirical study investigates factors leading to SISP success in a public organization. The research model and hypotheses were derived from two possible theories, agency theory and the political conflict model. The research methodology proposed uses the case study approach. The expected findings and a brief conclusion are also discussed.
Robust location algorithm based on weighted least- squares support vector machine (WLS-SVM) for non- line-of-sight environments

One of the main problems facing accurate location in wireless communication systems is non-line-ofsight (NLOS) propagation. Though learning location methods perform well in NLOS environments, learning location methods may be improved further since these methods do not consider outliers in the training data set. In this paper, we extend weighted least squares support vector machine (WLS-SVM) algorithm to mobile location problem. The proposed method can effectively suppress outliers with different weights. In simulation, we analyze the effects of the number of training points, the percentage of outliers in training data set, the standard deviation and mean of outliers, and the standard deviation of measurement error. Simulation results show that the proposed algorithm clearly outperforms three other algorithms (LS method, kernel method and LS-SVM based method).
A Modified Response Surface Methodology for Knowledge Discovery with Simulations

The response surface methodology (RSM) provides an iterative process for learning that involves the sequential use of experimental design, empirical model building, and analysis of the developed models. This work provides a modified response surface methodology (MRSM) that can be applied to more complex simulation studies. These problems involve a larger number of input variables, multiple measures of performance, and complex systems relationships. Furthermore, the MRSM considers simulation analyses that have multiple objectives. These may include: 1) determining near optimal solutions; 2) understanding tradeoffs; and 3) translating the findings into generalizations. In many applications, one may begin the analysis with relatively little understanding of the variable relationships in the systems under study. The MRSM capitalizes on the underlying learning philosophy of the traditional RSM while benefiting from other knowledge discovery concepts and data mining techniques. We describe the general concepts behind the MRSM and a sequential procedure for analysis of a broad range of simulation applications. To show the steps of the MRSM, we provide examples based on an application involving combat agent-based simulation models.
A Prototype Gaze-Controlled Speller for Text Entry

Eye typing provides a means of communication that is useful for people with disabilities which prevent using their hands for text entry. In this paper, we describe the development of the prototype gaze-controlled speller and discuss its experimental evaluation. Using scrollable virtual keyboard interface, the text input speed of 1.2 wpm was achieved. Keywords—gaze tracking; gaze writing; eye typing; hands-free text entry; speller; assistive technology.
Visual 3D self localization with 8 gram circuit board for very compact and fully autonomous unmanned aerial vehicles

We describe an algorithm and hardware system of a 3D self-localization method for very cost effective hovering robots. The hardware system consists of very compact calculation and sensor units, instead of using a high performance calculation unit like a laptop PC. In the experiment, the comparison with the ground truth sensor is discussed and implementation of the system on a palm-sized quad-copter is studied to realize a very compact, on-board, fully autonomous quad-copter.
Bayesian VARs with Large Panels

This paper assesses the performance of Bayesian Vector Autoregression (BVAR) for models of different size. We consider standard specifications in the macroeconomic literature based on, respectively, three and eight variables and compare results with those obtained by larger models containing twenty or over one hundred conjunctural indicators. We first study forecasting accuracy and then perform a structural exercise focused on the effect of a monetary policy shock on the macroeconomy. Results show that BVARs estimated on the basis of hundred variables perform well in forecasting and are suitable for structural analysis.
Surface abundances of light elements for a large sample of early B-type stars – IV. The magnesium abundance in 52 stars – a test of metallicity

From high-resolution spectra a non-local thermodynamic equilibrium analysis of the Mg II 4481.2-A feature is implemented for 52 early and medium local B stars on the main sequence (MS). The influence of the neighbouring line Al III 4479.9-A is considered. The magnesium abundance is determined; it is found that log e(Mg) = 7.67 ± 0.21 on average. It is shown that uncertainties in the microturbulent parameter V t are the main source of errors in log e(Mg). When using 36 stars with the most reliable V t values derived from On II and N II lines, we obtain the mean abundance log e(Mg) = 7.59 ± 0.15. The latter value is precisely confirmed for several hot B stars from an analysis of the Mg II 7877-A weak line. The derived abundance log e(Mg) = 7.59 ± 0.15 is in excellent agreement with the solar magnesium abundance log e ○. (Mg) = 7.55 ± 0.02, as well as with the proto-Sun abundance log e ps (Mg) = 7.62 ± 0.02. Thus, it is confirmed that the Sun and the B-type MS stars in our neighbourhood have the same metallicity.
Assessment of Flow Structures in Bubble Columns by X-ray Based Particle Tracking Velocimetry

For the investigation of flow structures in bubble columns it is necessary to measure the local liquid velocity. Common optical methods fail in a bubble flow with a large void fraction. The cause is the different refraction index of liquid phase and gaseous phase, which leads to reflection and dispersion. The new X-ray based Particle Tracking Velocimetry (PTV) called “XPTV” presented here permits to obtain the liquid velocity threedimensionally, touch-free and for any large void fraction. The problem of light reflection and light refraction on phase boundaries is solved by the use of X-rays instead of light. X-rays penetrate a gas/liquid flow in straight lines. The method can also be applied to opaque liquids, where optical methods fail.
An Auto-Navigation System for Virtual Factories

Interactive 3D graphics is an effective front end for a virtual factory to provide virtual tours, tracking, training, and simulation. With the recent advances in graphics acceleration hardware and in the development of web 3D standards such as VRML, networked virtual reality is becoming a viable and promising man-machine interface. However, it is still a great challenge for a novice user equipped with a regular desktop PC to navigate in most virtual worlds of moderate complexity. We think the main problem is due to the facts that the level of control that a user needs to provide is too low and the display frame rate is not high enough for this servo loop. In this paper, we consider an alternative metaphor of allowing a user to specify locations of interests on a 2D-layout map and let the system automatically generate the animation of guided tours in a virtual factory. Specifically, we aim to generate animations of customizable tour paths and its associated human/camera motions in an on-line manner according to high-level user inputs. We describe an auto-navigation system, in which several efficient pathplanning algorithms adapted from robotics are used. The core planning modules in this system are implemented in Java, and common VRML browsers are adopted for 3D visualization of virtual factories.
Natural language text classification and filtering with trigrams and evolutionary nearest neighbour classifiers

Ngrams offer fast language independent multi-class text categorization. Text is reduced in a single pass to ngram vectors. These are assigned to one of several classes by a) nearest neighbour (KNN) and b) genetic algorithm operating on weights in a nearest neighbour classifier. 91 percent accuracy is found on binary classification on short multi-author technical English documents. This falls if more categories are used but 69 percent is obtained with 8 classes. Zipf law is found not to apply to trigrams.
A Multilinear Approach to the Unsupervised Learning of Morphology

We present a novel approach to the un-supervised learning of morphology. In particular, we use a Multiple Cause Mixture Model (MCMM), a type of autoen-coder network consisting of two node layers—hidden and surface—and a matrix of weights connecting hidden nodes to surface nodes. We show that an MCMM shares crucial graphical properties with autosegmental morphology. We argue on the basis of this graphical similarity that our approach is theoretically sound. Experiment results on Hebrew data show that this theoretical soundness bears out in practice.
Audiovisual speech decreases the number of cognate translations in simultaneous interpreting

A large body of research suggests that audiovisual speech facilitates listening comprehension, especially in adverse conditions like noisy environments or hearing impairment, but previous studies on simultaneous interpreting focusing on the interpreting performance failed to demonstrate the benefit of visual input. One explanation might be that conference interpreters increase their cognitive effort to maintain the quality of their rendering. Hence, the impact of visual input might not directly be visible in the interpretation. In order to elucidate this question, I concentrated on self-monitoring in simultaneous interpreting and analyzed the number of cognate translations in a 2×2 factorial design with presence/absence of lip movements and presence/absence of white noise as levels. The results showed an increase of cognate translations when the interpreters worked without visible lipmovements, indicating a less effectivemonitoring in this condition. The findings of this study point out the importance of visual input in simultaneous interpreting and its integration in models of simultaneous interpreting.
Copper Electrodeposition for 3 D Integration

Two dimensional (2D) integration has been the traditional approach for IC integration. Increasing demands for providing electronic devices with superior performance and functionality in more efficient and compact packages has driven the semiconductor industry to develop more advanced packaging technologies. Three-dimensional (3D) approaches address both miniaturization and integration required for advanced and portable electronic products. Vertical integration proved to be essential in achieving a greater integration flexibility of disparate technologies, resulting in a general trend of transition from 2D to 3D integration in the industry. 3D chip integration using through silicon via (TSV) copper is considered one of the most advanced technologies among all different types of 3D packaging technologies. Copper electrodeposition is one of technologies that enable the formation of TSV structures. Because of its well-known application for copper damascene interconnects, it was believed that its transfer to filling TSV vias would be easily adopted. However, as any new technology at its beginning, there are several challenges that need to be addressed and resolved before becoming a fully mature technology. This paper will address the TSV fill processes using copper electrodeposition, the advantages as well as difficulties associated with this technology and approaches taken to overcome them. The effect of wafer design on process, including necessary process optimization that is required for achieving void-free filling will be discussed.
Impact Of Feedback And Revision On Student Team Solutions To Model Eliciting Activities

Helping first-year engineering students to embrace the iterative and open-ended nature of engineering problem solving is a challenge when their prior learning experiences have focused heavily on achieving a correct answer in a single attempt. In this paper, the authors will present a case study of student work from the Fall 2007 implementation of Model-Eliciting Activities (MEAs) to demonstrate the impact of the iterative process of feedback and revision on the quality of student products. They will also discuss some of the future research questions resulting from the iterative process used with MEAs.