Miracle-dz/UniFAR-FTUs huggingface dataset:
ThemeRiver: Visualizing Thematic Changes in Large Document Collections

The ThemeRiver visualization depicts thematic variations over time within a large collection of documents. The thematic changes are shown in the context of a time-line and corresponding external events. The focus on temporal thematic change within a context framework allows a user to discern patterns that suggest relationships or trends. For example, the sudden change of thematic strength following an external event may indicate a causal relationship. Such patterns are not readily accessible in other visualizations of the data. We use a river metaphor to convey several key notions. The document collection's time-line, selected thematic content and thematic strength are indicated by the river's directed flow, composition and changing width, respectively. The directed flow from left to right is interpreted as movement through time and the horizontal distance between two points on the river defines a time interval. At any point in time, the vertical distance, or width, of the river indicates the collective strength of the selected themes. Colored "currents" flowing within the river represent individual themes. A current's vertical width narrows or broadens to indicate decreases or increases in the strength of the individual theme.
Cognitive Control and the Salience Network: An Investigation of Error Processing and Effective Connectivity

The Salience Network (SN) consists of the dorsal anterior cingulate cortex (dACC) and bilateral insulae. The network responds to behaviorally salient events, and an important question is how its nodes interact. One theory is that the dACC provides the earliest cortical signal of behaviorally salient events, such as errors. Alternatively, the anterior right insula (aRI) has been proposed to provide an early cognitive control signal. As these regions frequently coactivate, it has been difficult to disentangle their roles using conventional methods. Here we use dynamic causal modeling and a Bayesian model evidence technique to investigate the causal relationships between nodes in the SN after errors. Thirty-five human subjects performed the Simon task. The task has two conditions (congruent and incongruent) producing two distinct error types. Neural activity associated with errors was investigated using fMRI. Subjects made a total of 1319 congruent and 1617 incongruent errors. Errors resulted in robust activation of the SN. Dynamic causal modeling analyses demonstrated that input into the SN was most likely via the aRI for both error types and that the aRI was the only region intrinsically connected to both other nodes. Only incongruent errors produced behavioral adaptation, and the strength of the connection between the dACC and the left insulae correlated with the extent of this behavioral change. We conclude that the aRI, not the dACC, drives the SN after errors on an attentionally demanding task, and that a change in the effective connectivity of the dACC is associated with behavioral adaptation after errors.
A scheme for fast network traffic anomaly detection

Fast network traffic anomaly detection is an important issue in network security. At present, the Internet environment becomes more and more complex than ever before. The unexpected anomaly occurs constantly, which brings great loss to Internet services. This makes people put forward higher requirements for the speed and real-time of network traffic anomaly detection. How to quickly perceive the traffic anomaly is a new demand in the network anomaly detection. Due to the shortage of the conventional detection methods in terms of speed, a fast anomaly detection scheme is proposed in this paper, which is based on the iterative estimation of Hurst parameter. The anomaly can be determined through the value of estimation. Meanwhile, by on-line we can estimate continuously and refresh the value of Hurst according to the latest network traffic, and then we can get the latest traffic data and speed up the process of anomaly detection. Analyses show that this scheme is effective in fast anomaly detection.
Does better education cause higher income

While the positive influence of higher education on income has been repeatedly confirmed, the linking channel can be ambiguous. Within the framework of estimating the effect of income on life satisfaction, various sources of endogeneity caused by joint determination are addressed and the earnings equation is reconsidered, too: We cast doubt on the hypothesis of the direct influence of educational achievement on income, using two separate cross-section datasets for full-time employed, male white- or blue-collar workers from German SOEP data. Our data rather suggest that the socio-economic rank of an occupation serves as a factor which links educational achievement and income. One explanation relates to the signaling theory by Spence, another possible explanation is yielded by the existence of a regime of regulations in Germany that require certain formal quali cations to obtain highly-prestigious jobs which are, in general, also better paid.
A Run-Time System for Programming Out-of-Core Matrix Algorithms-by-Tiles on Multithreaded Architectures FLAME Working Note # 43

Out-of-core implementations of algorithms for dense matrix computations have traditionally focused on optimal use of memory so as to minimize I/O, often trading programmability for performance. In this paper we show how the current state of hardware and software allows the programmability problem to be solved without sacrificing performance. This comes from the realizations that memory is cheap and large, making it less necessary to optimally orchestrate I/O, and that new algorithms view matrices are collections of submatrices and computation as operations with those submatrices. This enables libraries to be coded at a high level of abstraction, leaving the tasks of scheduling the computations and data movement in the hands of a run-time system. Remarkable performance is demonstrated for this approach on multi-core architectures as well as platforms equipped with hardware accelerators.
Political Legitimacy and Democracy*

The term ‘political legitimacy’ is unfortunately ambiguous. One serious source of confusion is the failure to distinguish clearly between political legitimacy and political authority and to conflate political authority with authoritativeness. I will distinguish between (1) political legitimacy, (2) political authority, and (3) authoritativeness. I will also articulate two importantly different variants of the notion of political authority. Having drawn these distinctions, I will argue first that political legitimacy, rather than political authority, is the more central notion for a theory of the morality of political power. My second main conclusion will be that where democratic authorization of the exercise of political power is possible, only a democratic government can be legitimate. Another ambiguity is also a source of confusion. Sometimes it is unclear whether ‘legitimacy’ is being used in a descriptive or a normative sense. In this article I am concerned exclusively with legitimacy in the normative sense, not with the conditions under which an entity is believed to be legitimate. However, a normative account of legitimacy is essential for a descriptive account. Unless one distinguishes carefully between political legitimacy, political authority, and authoritativeness, one will not be clear about what beliefs in legitimacy are beliefs about.
Irregular Convolution and Unity-Rate Coded Network-Coding for Cooperative Multi-User Communications

Near-Capacity Multi-user Network-coding (NCMN) based systems operating in multiple modes and relying on an amalgamated Irregular Convolutional Code, a Unity-Rate Code and M-ary Phase-Shift Keying are proposed. We consider a multiuser network in which the users cooperatively transmit their independent information to a common base station (BS). Extrinsic Information Transfer (EXIT) charts were used for designing the proposed NCMN scheme for the sake of approaching the Discrete-input Continuous-output Memoryless Channel's (DCMC) capacity. The NCMN systems are capable of simultaneously exploiting the advantages of all the new modes we designed for our system and those of the conventional mode. The design principles presented in this contribution can be extended to a vast range of NCMN based systems using arbitrary channel coding schemes.
A Study of Mineral Impurities within the Georgia Kaolins

The mining industry located along the fall line region of central Georgia has been and remains as one of the largest global exporters of the clay mineral kaolinite. Among the kaolin deposits in that region, the Cretaceous Buffalo Creek formation and the Eocene Jeffersonville member contain the most commercially viable kaolin to extract and process for resale. The minerals of the sand and silt fractions of these kaolin units were separated via dense liquid separation and analyzed for comparison by X-ray diffraction, scanning electron microscopy, and elemental analysis. The dense fractions are enriched in select heavy minerals (zircon and rutile) and trace elements (rare earth). These elemental enrichments and the differences in the mineral maturity of these gangue (grit) fractions suggest differences in the provenance of the gangue minerals between these two different kaolins. INDEX WORDS: Kaolinite, Gangue, Grit, Buffalo Creek, Jeffersonville, A STUDY OF MINERAL IMPURITIES WITHIN THE GEORGIA KAOLINS
Texture Mapping Range Images

We are concerned with capturing a real scene with both cameras and laser range scanners, and combining them to produce convincing rendersings. In this paper, we focus on the texture mapping component of this pipeline. Our automatic algorithms register texture from radiance images with the geometry and synthesize compact high-quality texture maps. Our image registration technique performs a very efficient search to automatically find the camera poses for arbitrary position and orientation relative to the geometry. Thus we can take photographs from any location without precalibration between the scanner and the camera. All the photographs are commbined to form one texture map for the whole scene, which is rendered on top of our reconstructed geometric mesh. These algorithms have been applied to large-scale real data. Additionally, we demonstrate our ability to edit this captured scene by moving, inserting, and deleting objects.
From Bosnia To Kosovo And East Timor: The Changing Role Of The United Nations In The Administration Of Territory

In recent years there has been a resurgence in projects where territorial units are administered by international organizations. In Bosnia and Hercegovina ('Bosnia'), Kosovo and East Timor, international organizations have been given wide powers of administration, covering a broad range of activities. I am currently undertaking a study of this phenomenon, what I term 'International Territorial Administration' (ITA). Today, I would like to make some observations on the role of the United Nations in creating and carrying out the administration projects in these three territories. With respect to Bosnia, the starting point is the General Framework Agreement of 1995, collectively known as the Dayton Agreement. ' Annex 10 of the Dayton Agreement established the Office of the High Representative (OHR), with responsibility for the implementation of civil administration in Bosnia.2 The civilian role of OHR is complemented by the military role of the NATO-led body, called at first the Implementation Force (IFOR), and later the Stabilization Force (SFOR). Annex 1-A of Dayton invites the Security Council to establish IFOR, effectively granting the force total military control in Bosnia. ' The Dayton Agreement also allocates further aspects of Bosnia's administration to other international actors, from the Organization for Security and Co-operation in Europe (OSCE) being requested to set up and run the electoral system, 4 to three members of the Constitutional Court being appointed by the President of the European Court of Human Rights.5
A pluggable service-to-service communication mechanism for home multimedia networks

This paper proposes a pluggable service-to-service (S2S) communication mechanism in a middleware for home networks, called Virtual Networked Appliance (VNA) architecture. In the architecture, service description method and the plug-gable S2S communication mechanism are separated in an orthogonal way. Through the separation, VNA architecture solved problems of home networks on which users have to operate multiple heterogeneous middleware technologies simultaneously: middleware fragmentation problem, due to complexity of realizing heterogeneous services on one middle-ware technology: aspect realization violation problem. The pluggable S2S communication mechanism provides service programmers with a simple aspect representation method to define a service-specific protocol concern apart from the service's implementation. It also provides off-the-shelf protocol modules of such well-known communication protocols as RTP, RTSP, HTTP, and SMTP for an inter-service communication, and dynamically loads them based on the aspects defined by the programmer. This reduces the complexity of implementing heterogeneous services on the VNA architecture, thereby addressing the problems. In this paper, we first clarify the two problems. Then, we describe the proposed mechanism with an overview of the middleware architecture referring to a composite service: "Follow-You-and-Me Video. "
Neural network fusion strategies for identifying breast masses

In this work, we introduce the perceptron average neural network fusion strategy and implemented a number of other fusion strategies to identify breast masses in mammograms as malignant or benign with both balanced and imbalanced input features. We numerically compare various fixed and trained fusion rules, i.e., the majority vote, simple average, weighted average, and perceptron average, when applying them to a binary statistical pattern recognition problem. To judge from the experimental results, the weighted average approach outperforms the other fusion strategies with balanced input features, while the perceptron average is superior and achieves the goals with lowest standard deviation with imbalanced ensembles. We concretely analyze the results of above fusion strategies, state the advantages of fusing the component networks, and provide our particular broad sense perspective about information fusion in neural networks.
Eigenstructure Assignment Based Controllers Applied to Flexible Spacecraft

The objective of this paper is to evaluate the behaviour of a controller designed using a parametric Eigenstructure Assignment method and to evaluate its suitability for use in flexible spacecraft. The challenge of this objective lies in obtaining a suitable controller that is specifically designated to alleviate the deflections and vibrations suffered by external appendages in flexible spacecraft while performing attitude manoeuvres. One of the main problems in these vehicles is the mechanical cross-coupling that exists between the rigid and flexible parts of the spacecraft. Spacecraft with fine attitude pointing requirements need precise control of the mechanical coupling to avoid undesired attitude misalignment. In designing an attitude controller, it is necessary to consider the possible vibration of the solar panels and how it may influence the performance of the rest of the vehicle. The nonlinear mathematical model of a flexible spacecraft is considered a close approximation to the real system. During the process of controller evaluation, the design process has also been taken into account as a factor in assessing the robustness of the system.
Sequential Convex Programming Methods for A Class of Structured Nonlinear Programming

In this paper we study a broad class of structured nonlinear programming (SNLP) problems. In particular, we first establish the first-order optimality conditions for them. Then we propose sequential convex programming (SCP) methods for solving them in which each iteration is obtained by solving a convex programming problem exactly or inexactly. Under some suitable assumptions, we establish that any accumulation point of the sequence generated by the methods is a KKT point of the SNLP problems. In addition, we propose a variant of the exact SCP method for SNLP in which nonmonotone scheme and “local” Lipschitz constants of the associated functions are used. And a similar convergence result as mentioned above is established.
Recovery of Myocardial Kinematic Function without the Time History of External Loads

A time-domain filtering algorithm is proposed to recover myocardial kinematic function using output-only measurements without the time history of external loads. The main contribution of this work is that the overall effect of all the external loads on the myocardium is treated as a random variable disturbed by the Gaussian white noise because the external loads of the myocardium are usually unknown in practical exercises. The kernel of our proposed algorithm is an iterative, multiframe, and sequential filtering procedure consisting of a Kalman filter and a least-squares filter. In our proposed implementation, the initial guess of myocardial kinematic function and residual innovation of all the state variables are first computed using a Kalman filter via state space equations only driven by the Gaussian white noise, and then the residual innovation is fed into a least-squares filter to estimate the total external loads of the myocardium. In the end, the initial guess of myocardial kinematic function is corrected using external loads provided by the least-squares filter. After the introduction of the whole structure of our algorithm, we demonstrate the ability of the framework on synthetic data and MR image sequences.
Labor Market Status and Transitions During the Pre-Retirement Years: Learning from International Differences

Many western industrialized countries face strong budgetary pressures due to the aging of the baby boom generations and the general trends toward earlier ages of retirement. We use the American PSID and the European Community Household Panel (ECHP) to explain differences in prevalence and dynamics of self-reported work disability and labor force status. To that end we specify a two-equation dynamic panel data model describing the dynamics of labor force status and self-reported work disability. When we apply the U.S. parameters to the equations for the thirteen European countries we consider, the result is generally that work disability is lower and employment is higher. Furthermore, measures of employment protection across the different countries suggest that increased employment protection reduces reentry into the labor force and hence is a major factor explaining employment differences in the pre-retirement years.
Predicting Player Moves in an Educational Game: A Hybrid Approach

Open-ended educational tools can encourage creativity and active engagement, and may be used beyond the classroom. Being able to model and predict learner performance in such tools is a critical component to assist the student, and enable tool refinement. However, open-ended educational domains typically allow an extremely broad range of learner input. As such, building the same kind of cognitive models often used to track and predict student behavior in existing systems is challenging. In addition, the resulting large spaces of user input coupled with comparatively sparse observed data, limits the applicability of straightforward classification methods. We address these difficulties with a new algorithm that combines Markov models, state aggregation, and player heuristic search, dynamically selecting between these methods based on the amount of available data. Applied to a popular educational game, our hybrid model achieved greater predictive accuracy than any of the methods alone, and performed significantly better than a random baseline. We demonstrate how our model can learn player heuristics on data from one task that accurately predict performance on future tasks, and explain how our model retains parameters that are interpretable to non-expert users.
Can filesharers be triggered by economic incentives? Results of an experiment

Illegal filesharing on the internet leads to considerable financial losses for artists and copyright owners as well as producers and sellers of music. Thus far, measures to contain this phenomenon have been rather restrictive. However, there are still a considerable number of illegal systems, and users are able to decide quite freely between legal and illegal downloads because the latter are still difficult to sanction. Recent economic approaches account for the improved bargaining position of users. They are based on the idea of revenue-splitting between professional sellers and peers. In order to test such an innovative business model, the study reported in this article carried out an experiment with 100 undergraduate students, forming five small peer-to-peer networks. The networks were confronted with different economic conditions. The results indicate that even experienced filesharers hold favourable attitudes towards revenue-splitting. They seem to be willing to adjust their behaviour to different economic conditions.
Screen printed electrochemical detector combine with digital microfluidic microchip

In this work, a screen-printed electrochemical detector with electrowetting on dielectric (EWOD) digital microfluidics lab on a chip was designed, fabricated, and experimental studied for biological, biomedical, and chemical analysis. For the design, the electrochemical EWOD digital microfluidics system consists of T-junction EWOD microchip for merging buffer reagent and analyte droplets and three screen-printed electrochemical detectors at the end of T-junction. The detectors consist of three electrodes: carbon working electrode, carbon counter electrode and silver/silver chloride reference electrode with minimal reagent consumption and rapid analysis. The systems has been successfully fabricated and tested for rapid analysis. In experiment, the electrochemical detector with EWOD microchip was fabricated and tested to control moving (merging and transporting) droplet on the microchip to analyte at three electrochemical detector. For analysis, the electrochemical detectors was demonstrated for minimal reagent consumption which were potassium ferricyanide and L-ascorbic. The concentration of the reagent were varied from 1, 2, 3, 5, 7 and 10 mM for analysis. Microdroplets of buffer reagent and analyte droplet solution was mixed and detected by cyclic voltammetry. The total analysis time including droplet mixing and measurement was less than 20 seconds.
Channel-aware routing for underwater wireless networks

This paper presents a new cross layer routing protocol for underwater wireless sensor networks. The solution, termed CARP for Channel-aware Routing Protocol, exploits link quality information for cross layer relay determination. Nodes are selected as relays if they have a (recent) history of successful transmissions to their neighbors. CARP combines link quality with simple topology information (hop count), thus being able to route around connectivity voids and shadow zones. The protocol is also designed to take advantage of power control for selecting robust links. The performance of CARP has been evaluated through ns2-based simulations, and compared to the performance of two previously proposed routing protocols, namely, FBR and DBR. Our results show that CARP robust relay selection mechanism enables it to achieve throughput efficiency that is up to twice the throughput of FBR and almost three times that of DBR. CARP also obtains remarkable performance improvements over FBR and DBR with respect to end-to-end packet latency and energy consumption.