Miracle-dz/UniFAR-FTUs huggingface dataset:
Line outage vulnerabilities of power systems : models and indicators

La vulnerabilite des systemes electriques est l'un des problemes lies a leur complexite. Il a fait l’objet d’une attention croissante des chercheurs au cours des dernieres decennies. Malgre cela, les phenomenes fondamentaux qui regissent la vulnerabilite du systeme ne sont pas encore bien compris.Comprendre comment la vulnerabilite des reseaux electriques emerge de leur topologie est la motivation principale du present travail. Pour cela, le present travail de recherche propose une nouvelle methode pour evaluer la vulnerabilite des systemes electriques et identifier leurs elements les plus critiques. La methode permet d’avoir une bonne comprehension des liens entre la topologie d’un reseau et sa vulnerabilite a des pertes d’ouvrages (lignes ou transformateurs). La premiere partie de ce travail consiste en une analyse critique des approches rencontrees dans la litterature, s’appuyant sur la theorie des graphes, pour analyser la vulnerabilite des reseaux electriques. Les resultats fournis par ces approches pour quatre reseaux IEEE sont compares a ceux fournis par une analyse de contingence de reference, basee sur une resolution d’un load-flow AC. Des avantages et inconvenients de chaque approche est tiree une methode amelioree pour l'evaluation de la vulnerabilite des reseaux electriques aux pertes d’ouvrage. Cette methode est basee sur une approximation courant continue du load flow.La deuxieme partie propose une nouvelle approche basee sur la theorie spectrale des graphes et son utilisation pour la resolution d’un load flow DC. Elle permet de mieux comprendre comment la vulnerabilite des reseaux electriques et leurs composants critiques emergent de la topologie du graphe sous-jacent au reseau.
Novel approach for vehicle detection in dynamic environment based on monocular vision

This paper describes a vehicle detection system in dynamic environment based on monocular vision. Vehicles are separated from forward scenes by the proposed system. Hypotheses extracted using Haar-like feature and Adaboost classifier include several non-vehicle regions. In order to remove false positive detections, we apply the SVM-based classifier with HOG feature and HOG symmetry feature to predicate whether the hypotheses are vehicles in the hypothesis verification process. By this method, false detection rate resulted from only using Haar-like feature is reduced. The vehicle detection system has been evaluated in dynamic environment, and shown a strong and accurate performance.
Developing Interaction 3D Models for E-Learning Applications

Some issues concerning the development of interactive 3D models for e-learning applications are considered. Given that 3D data sets are normally large and interactive display demands high performance computation, a natural solution would be placing the computational burden on the client machine rather than on the server. Mozilla and Google opted for a combination of client-side languages, JavaScript and OpenGL, to handle 3D graphics in a web browser (Mozilla 3D and O3D respectively). Based on the O3D model, core web technologies are considered and an example of the full process involving the generation of a 3D model and their interactive visualization in a web browser is described. The challenging issue of creating realistic 3D models of objects in the real world is discussed and a method based on line projection for fast 3D reconstruction is presented. The generated model is then visualized in a web browser. The experiments demonstrate that visualization of 3D data in a web browser can provide quality user experience. Moreover, the development of web applications are facilitated by O3D JavaScript extension allowing web designers to focus on 3D contents generation.
A gp41 MPER-specific Llama VHH Requires a Hydrophobic CDR3 for Neutralization but not for Antigen Recognition

The membrane proximal external region (MPER) of the HIV-1 glycoprotein gp41 is targeted by the broadly neutralizing antibodies 2F5 and 4E10. To date, no immunization regimen in animals or humans has produced HIV-1 neutralizing MPER-specific antibodies. We immunized llamas with gp41-MPER proteoliposomes and selected a MPER-specific single chain antibody (VHH), 2H10, whose epitope overlaps with that of mAb 2F5. Bi-2H10, a bivalent form of 2H10, which displayed an approximately 20-fold increased affinity compared to the monovalent 2H10, neutralized various sensitive and resistant HIV-1 strains, as well as SHIV strains in TZM-bl cells. X-ray and NMR analyses combined with mutagenesis and modeling revealed that 2H10 recognizes its gp41 epitope in a helical conformation. Notably, tryptophan 100 at the tip of the long CDR3 is not required for gp41 interaction but essential for neutralization. Thus bi-2H10 is an anti-MPER antibody generated by immunization that requires hydrophobic CDR3 determinants in addition to epitope recognition for neutralization similar to the mode of neutralization employed by mAbs 2F5 and 4E10.
Multi-Commodity Network Flow for Tracking Multiple People

In this paper, we show that tracking multiple people whose paths may intersect can be formulated as a multi-commodity network flow problem. Our proposed framework is designed to exploit image appearance cues to prevent identity switches. Our method is effective even when such cues are only available at distant time intervals. This is unlike many current approaches that depend on appearance being exploitable from frame-to-frame. Furthermore, our algorithm lends itself to a real-time implementation. We validate our approach on three publicly available datasets that contain long and complex sequences, the APIDIS basketball dataset, the ISSIA soccer dataset, and the PETS'09 pedestrian dataset. We also demonstrate its performance on a newer basketball dataset that features complete world championship basketball matches. In all cases, our approach preserves identity better than state-of-the-art tracking algorithms.
An Intelligent Online Presswork Defect Detection Method and System

With the improvement of printing precise and printing speed, manual quality checking is unable to satisfy the demand of high speed printing quality checking. This paper presents a real-time presswork defect detection method and system based on machine vision. It designs an image fusion-basing fiducially image dynamic updating method, uses multi-channel image subtraction to segment defects, and presents a fake defects removing method based on image contour. The real application shows that this inspection method and system is efficient and valid.
A new tension controller for continuous strip processing line

The strip tension as well as the line speed should be controlled tightly for the quality of products and productivity of the continuous strip processing line. In this paper, a new tension control algorithm with tension observer is proposed using observed tension as a regulator feedback. The tension observer is based on the torque balance of a roller stand including the acceleration torque. Using this estimated tension, a new tension controller can be constructed with faster dynamic response in case of line speed acceleration or deceleration. The proposed scheme needs no additional hardware because the inputs of observer, current and speed, are already being monitored by the motor drive system. As this scheme directly controls torque current of the motor, better control performance can be obtained even without the tension transducer. Through the simulations and experiments with laboratory set up, performances of conventional schemes and the proposed one are compared. The results show the effectiveness of the proposed tension controller.
Towards Adaptive Spoken Dialogue

Although it is now possible to build real-time spoken dialogue systems for a wide variety of applications, designing the dialogue strategy of such systems involves a number of nontrivial design choices. These choices can seriously impact system performance, and include choosing appropriate strategies for initiative (whether to accept relatively open-ended versus constrained user utterances) and connrmation (when to connrm a user's previous utterance). Typically, dialogue strategy design has been done in an ad-hoc manner. This paper summarizes how my recent research has addressed the design, implementation, and experimental evaluation of methods for dynamically adapting and optimizing a system's dialogue strategy, in order to improve system performance. Although users diier with respect to their knowledge of system limitations, and although diierent dialogue strategies make system limitations more apparent to users, most spoken dialogue systems do not try to improve performance by adapting dialogue behavior to individual users. We have evaluated the utility of allowing users to dynamically adapt (at any point(s) in a dialogue) the initial set of initiative and connrmation dialogue strategies used by TOOT, a spoken dialogue system for retrieving train schedules on the web. (The initiative strategy speciies who controls the dialogue, while the connrmation strategy speciies how TOOT lets the user know what it just understood.) We conducted an experiment in which 20 novice users carried out 4 tasks with adaptable and non-adaptable versions of TOOT, resulting in a corpus of 80 dialogues. Our results showed that adaptable TOOT outperformed non-adaptable TOOT for task success and a subjective measure of user satisfaction, and that the utility of adaptation for other evaluation measures depended on the initial connguration of dialogue strategies (Litman & Pan 1999). We have explored the utility of automatically adapting the behavior of TOOT, in response to inferred poor speech recognition performance. Our evaluations of TOOT and other spoken dialogue systems suggest that speech recognition accuracy is among the most signiicant predictors of dialogue system performance, e.g. First, we demonstrated that it is possible to recognize when dialogues are going poorly with respect to speech recognition. Our training and testing data consisted of 544 dialogues, obtained from TOOT and two other dialogue systems. Each dialogue was assigned a classiication of either \good" or \bad", by thresholding on the percentage of user utterances that were misrecognized. Each dialogue was also represented in terms of 23 features that were automatically computed from system logs. The features were …
The Production of Sodium and Aluminum in Globular Cluster Red Giant Stars

We study the production of Na and Al around the hydrogen shell of two red giant sequences of different metallicity in order to explain the abundance variations seen in globular cluster stars in a mixing scenario. Using detailed stellar models, together with an extensive nuclear reaction network, we have calculated the distribution of the various isotopic abundances around the hydrogen shell at numerous points along the red giant branch. These calculations allow for the variation in both temperature and density in the shell region as well as the timescale of the nuclear processing, as governed by the outward movement of the hydrogen shell. The reaction network uses updated rates over those of Caughlan & Fowler. We find evidence for the production of Na and Al occurring in the NeNa and MgAl cycles. In particular, Na is significantly enhanced throughout the region above the hydrogen shell. The use of the newer reaction rates causes a substantial increase in the production of 27Al above the hydrogen shell through heavy leakage from the NeNa cycle and should have an important effect on the predicted surface abundances. We also find that the nuclear processing is considerably more extensive at lower metallicities.
The Asynchronous Partitioned Global Address Space Model

The central question in front of us is the design of a programming model that can address this diversity of architectures. By a programming model, we mean the central mental constructs around which every activity around the programming enterprise – specification, design, implementation, testing, debugging – is organized. That is, a programming model gives us a coherent set of principles around which to organize our thinking about the computation. While it is relatively easy for the industry to come up with new architectures, it is far more difficult for the industry to adopt new programming models. Indeed, it took about twenty years since the first introduction of objectoriented (OO) programming for the industry to finally accept it. It took about ten years for the US National Labs to move to the MPI programming model. While declarative (functional, logic) programming ideas have been around for several decades — and flourish in certain niche areas — they have not yet established themselves in the main-stream. Application lifetime, number of programmers and users, testing, verification, and maintenance are all factors that contribute to the slow acceptanace. We believe that each computing era is characterized by a dominant programming model – programming models tend to exhibit a “winner take all” effect. The era of concurrency we now have embarked on essentially requires that a programming model that expects to be dominant must fundamentally account for concurrency, distribution, and composition, and must be able to address heterogeneous architectures. Further, much as the OO revolution did not completely eliminate the previous programming model – procedural programming – rather improved on it in a fundamental way (by providing much better control on structure and extensibility), the new concurrent programming model must improve on the current dominant programming model (OO, procedural programming). In this note we put forward the APGAS programming model as such a candidate. APGAS is currently being realized through a new programming language (X10), language extension proposals for existing concurrent languages, such as UPC and CoArray Fortran, and through a runtime library which can be invoked from C/C++.
A novel voltage sag generator for low voltage ride-through testing of grid-connected PV system

The capability of Low Voltage Ride-Through (LVRT) is required in China's standards as more and more photovoltaic (PV) generation system in large scale are connected to the grid. Voltage sag generator (VSG) is the device for LVRT testing. A novel design of VSG for LVRT testing of PV system is proposed in this paper, by which the grid voltage sags to 90%~0% (10% per degree) can be simulated with good performance. With the SVG, an entire model for LVRT test of PV system is built on real-time digital simulator (RTDS). The results of simulation verify the correction of LVRT platform and the feasibility of VSG design. This paper helps for the research of PV system' LVRT and the production of real VSG device for LVRT testing.
Anonymous Stabilizing Leader Election using a Network Sequencer

In this paper, we present an anonymous, stable, communication efficient, stabilizing leader election algorithm that works using anonymous communication primitives. The algorithm offers properties similar to that of the Omega failure detector, with the added property of totally ordering the sequence of proposed leaders. The algorithm does not need to know beforehand the identity or the number of processes in the system, and operates using a constant amount of memory. We present the algorithm, discuss performance issues and optimizations and present experimental results of a prototype implementation.
Epigenetic modification and preliminary investigation of the mechanism of the immune evasion of HL-60 cells

The aim of the present study was to explore the effect of epigenetic modification of class II transactivator (CIITA) methylation on histocompatibility complex (MHC) class II expression and the immune evasion of leukemia HL-60 cells. HL-60 cells were treated with various concentrations of 5-aza-2′deoxycytidine (5-Aza-CdR) and 0.5 μmol/l suberoyl-anilide hydroxamic acid (SAHA) for 24 h and then stimulated by interferon γ (IFN-γ) for 48 h. The mRNA levels of MHC class I, II and co-stimulatory molecules were quantified by reverse transcription polymerase chain reaction (RT-PCR). The levels of CIITA protein were determined by western blot analysis, and the CpG island methylation ratios in the CIITA promoter IV (CIITApIV) were analyzed by bisulfite-sequencing PCR (BSP). MHC I as well as the co-stimulatory molecules CD40 and CD80 were significantly increased following treatment with 5-Aza-CdR + SAHA + IFN-γ (epigenetic groups) compared with those in the control group and IFN-γ group (P<0.05). The expression of MHC class II and CIITA was restored and increased in an 5-Aza-CdR concentration-dependent manner in the three epigenetic groups. The results of the BSP assay showed that the methylation rate of CIITApIV CpG sites decreased with the treatment of epigenetic modification and negatively correlated to the 5-Aza-CdR concentration. This demonstrated that the negative expression of CIITA protein was the key reason for the loss of MHC II expression in HL-60 cells. The results of the present study may help to illustrate the mechanism of immune evasion in HL-60 cells.
Upper Bounds on the Capacity of Deletion Channels Using Channel Fragmentation

We study memoryless channels with synchronization errors as defined by a stochastic channel matrix allowing for symbol drop-outs or symbol insertions with particular emphasis on the binary and non-binary deletion channels. We offer a different look at these channels by considering equivalent models by fragmenting the input sequence where different subsequences travel through different channels. The resulting output symbols are combined appropriately to come up with an equivalent input-output representation of the original channel which allows for derivation of new upper bounds on the channel capacity. We consider both random and deterministic types of fragmentation processes applied to binary and nonbinary deletion channels. With two specific applications of this idea, a random fragmentation applied to a binary deletion channel and a deterministic fragmentation process applied to a nonbinary deletion channel, we prove certain inequality relations among the capacities of the original channels and those of the introduced subchannels. The resulting inequalities prove useful in deriving tighter capacity upper bounds for: 1) independent identically distributed (i.i.d.) deletion channels when the deletion probability exceeds 0.65 and 2) nonbinary deletion channels. Some extensions of these results, for instance, to the case of deletion/substitution channels are also explored.
A block-by-block blind post-fft beamforming algorithm for multiuser OFDM systems based on subcarrier averaging

This paper considers blind beamforming of multiuser orthogonal frequency division multiplexing (OFDM) systems. Assuming that the channel is static within one OFDM block, a blind post-FFT multi-stage beamforming algorithm (MSBFA) based on subcarrier averaging over one OFDM block is proposed, which basically comprises: i) source (path) extraction using a hybrid beamforming algorithm composed of a Fourier beamformer and a kurtosis maximization beam- former, ii) time delay estimation and compensation, iii) classification (path-to-user association) and blind maximum ratio combining (of paths). The designed beamformer effectively utilizes multipath diversity for performance gain, and is robust against the effects of correlated sources. Some simulation results are presented to demonstrate the effectiveness of the proposed MSBFA.
Evaluating Multi-label Classification of Incident-related Tweet

Microblogs are an important source of information in emergency management as lots of situational information is shared, both by citizens and ocial sources. It has been shown that incident-related information can be identified in the huge amount of available information using machine learning. Nevertheless, the currently used classification techniques only assign a single label to a micropost, resulting in a loss of important information that would be valuable for crisis management. With this paper we contribute the first in-depth analysis of multi-label classification of incident-related tweets. We present an approach assigning multiple labels to these messages, providing additional information about the situation at-hand. An evaluation shows that multi-label classification is applicable for detecting multiple labels with an exact match of 84.35%. Thus, it is a valuable means for classifying incident-related tweets. Furthermore, we show that correlation between labels can be taken into account for these kinds of classification tasks.
A novel trust-based secure data aggregation for Internet of Things

Data aggregation is an efficient technique widely used in Internet of Things (IOT) to collect statistics about data of interest. However, the resource-limited and the inherent unreliability of wireless transmission makes the sensors in the IOT are vulnerable to many attacks. Hence, how to design an efficient and secure data aggregation mechanism becomes critical. In this paper, we present TBSDA-a trust-based secure data aggregation scheme. In TBSDA, secure data aggregation is achieved by behavior-detected trust evaluation and data assembling technique. The trust evaluation and data aggregation work synergistically. We analyze the performance of TBSDA in term of communication overhead and the sensitivity of malicious nodes that behavior abnormally, and compare with other clustering scheme.
Acculturative Stress and Disengagement: Learning from the Adjustment Challenges faced by East Asian International Graduate Students

International graduate students meet TOEFL, GPA, and other admissions criteria to gain entry into US colleges and universities. During their stay in the USA, they provide educational and economic contributions for their host country. In contrast to their educational and economic potential, international students often demonstrate poor academic and social integration at their host institutions. Grounded theory methodology was used to investigate what accounts for the academic, cultural, and social adjustment problems faced by East Asian graduate students pursuing studies at an elite private not-for-profit university in the USA. Findings revealed that students experienced lowered self-confidence and acculturative stress as a result of challenges encountered during their first year, language barriers, different teaching styles and teaching environments, and their interactions with professors. Raising faculty sensitivity to cultural differences among international students, early adjustment counseling and obtaining regular feedback are recommended. Keywords: college student experience, student engagement, international students, adjustment, acculturative stress
OPTIMIZATION OF URBAN MULTI-INTERSECTION TRAFFIC FLOW VIA Q-LEARNING

Congestions of the traffic flow within the urban traffic network have been a challenging task for all the urban developers. Many approaches have been introduced into the current system to solve the traffic congestion problems. Reconfiguration of the traffic signal timing plan has been carried out through implementation of different techniques. However, dynamic characteristics of the traffic flow increase the difficulties towards the ultimate solutions. Thus, traffic congestions still remain as unsolvable problems to the current traffic control system. In this study, artificial intelligence method has been introduced in the traffic light system to alter the traffic signal timing plan to optimize the traffic flows. Q-learning algorithm in this study has enhanced the traffic light system with learning ability. The learning mechanism of Q-learning enables traffic light intersections to release itself from traffic congestions situation. Adjacent traffic light intersections will work independently and yet cooperate with each others to a common goal of ensuring the fluency of the traffic flows within the traffic network. The simulated results show that the Q-Learning algorithm is able to learn from the dynamic traffic flow and optimize the traffic flow accordingly.