Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature Based Image Stitching with Seam Blending

Image stitching is a way of using multiple partial images to create high resolution image. The partial images must have overlapping features with each other in order to render photo stitching feasible, the overlapping areas of the composite image are blended to remove the seams and discontinuities. The main goal of this work is using feature points extraction approach to extract corner from images to initiate the process of stitching images. This paper adopts the Harris feature based algorithm to detect feature point in image then matching these points by the correlation methods, and eliminate the error correlated points in images by RANSAC algorithm, after that the blended method is applied to get stitched image. The presented algorithms have succeeded in proving stitching images for input images. Several images are used to demonstrate the validity of the presented algorithms. The testing results show that the presented algorithms provide an efficient approach for image stitching . The stitching quality is measured by the similarity of the stitched image to each of the input images and by the visibility of the seam between the stitched images. KeywordsImage stitching, Correlation, Harris feature, RANSAC algorithm, Feature based stitching, Image blending
Using Next Generation Sequencing for Multiplexed Trait-Linked Markers in Wheat

With the advent of next generation sequencing (NGS) technologies, single nucleotide polymorphisms (SNPs) have become the major type of marker for genotyping in many crops. However, the availability of SNP markers for important traits of bread wheat ( Triticum aestivum L.) that can be effectively used in marker-assisted selection (MAS) is still limited and SNP assays for MAS are usually uniplex. A shift from uniplex to multiplex assays will allow the simultaneous analysis of multiple markers and increase MAS efficiency. We designed 33 locus-specific markers from SNP or indel-based marker sequences that linked to 20 different quantitative trait loci (QTL) or genes of agronomic importance in wheat and analyzed the amplicon sequences using an Ion Torrent Proton Sequencer and a custom allele detection pipeline to determine the genotypes of 24 selected germplasm accessions. Among the 33 markers, 27 were successfully multiplexed and 23 had 100% SNP call rates. Results from analysis of "kompetitive allele-specific PCR" (KASP) and sequence tagged site (STS) markers developed from the same loci fully verified the genotype calls of 23 markers. The NGS-based multiplexed assay developed in this study is suitable for rapid and high-throughput screening of SNPs and some indel-based markers in wheat.
Automatic Validation and Correction of Formalized, Textual Requirements

Nowadays requirements are mostly specified in unrestricted natural language so that each stakeholder understands them. To ensure high quality and to avoid misunderstandings, the requirements have to be validated. Because of the ambiguity of natural language and the resulting absence of an automatic mechanism, this has to be done manually. Such manual validation techniques are time-consuming, error-prone, and repetitive because hundreds or thousands of requirements must be checked. With an automatic validation the requirements engineering process can be faster and can produce requirements of higher quality. To realize an automatism, we propose a controlled natural language (CNL) for the documentation of requirements. On basis of the CNL, a concept for an automatic requirements validation is developed for the identification of inconsistencies and incomplete requirements. Additionally, automated correction operations for such defective requirements are presented. The approach improves the quality of the requirements and therefore the quality of the whole development process.
Extending the Jadex Framework with Coherence-Driven Adaptive Agent Decision-Making Model

Decision making involves selection of a choice among alternatives. Making the right decision can be interpreted as choosing the more coherent alternative. In the context of adaptive decision making, Thagard's deliberative coherence model provides a computational model for which one is more coherent. This article presents the implementation and the integration of coherence-driven adaptive decision making architecture into a concrete BDI architecture. The decision-making architecture is illustrated using a scenario involving Unmanned Surface Vehicles engaged in a patrol mission.
Contribution of Chondroitin Sulfate A to the Binding of Complement Proteins to Activated Platelets

Background Exposure of chondroitin sulfate A (CS-A) on the surface of activated platelets is well established. The aim of the present study was to investigate to what extent CS-A contributes to the binding of the complement recognition molecule C1q and the complement regulators C1 inhibitor (C1INH), C4b-binding protein (C4BP), and factor H to platelets. Principal Findings Human blood serum was passed over Sepharose conjugated with CS-A, and CS-A-specific binding proteins were identified by Western blotting and mass spectrometric analysis. C1q was shown to be the main protein that specifically bound to CS-A, but C4BP and factor H were also shown to interact. Binding of C1INH was dependent of the presence of C1q and then not bound to CS-A from C1q-depleted serum. The specific interactions observed of these proteins with CS-A were subsequently confirmed by surface plasmon resonance analysis using purified proteins. Importantly, C1q, C4BP, and factor H were also shown to bind to activated platelets and this interaction was inhibited by a CS-A-specific monoclonal antibody, thereby linking the binding of C1q, C4BP, and factor H to exposure of CS-A on activated platelets. CS-A-bound C1q was also shown to amplify the binding of model immune complexes to both microtiter plate-bound CS-A and to activated platelets. Conclusions This study supports the concept that CS-A contributes to the binding of C1q, C4BP, and factor H to platelets, thereby adding CS-A to the previously reported binding sites for these proteins on the platelet surface. CS-A-bound C1q also seems to amplify the binding of immune complexes to activated platelets, suggesting a role for this molecule in immune complex diseases.
2 7 A pr 2 00 5 Online Medians via Online Bribery ( Extended Abstract )

Following Mettu and Plaxton [15, 16], we study online algorithms for the k-medians problem. Such an algorithm must produce an incremental sequence F1 ⊆ F2 ⊆ · · · ⊆ Fn ⊆ F of sets of facilities. Mettu and Plaxton show that online metric medians has a (roughly) 40-competitive deterministic polynomial-time algorithm. We give improved algorithms, including a (24 + ǫ)competitive deterministic polynomial-time algorithm and a 2e ≈ 5.44-competitive, randomized, non-polynomial-time algorithm. We also consider the competitive ratio with respect to size. An algorithm is s-size-competitive if, for each k, the cost of Fk is at most the minimum cost of any set of k facilities, while the size of Fk is at most sk. We present optimally competitive algorithms for this problem. Our proofs reduce online medians to the following online bribery problem: faced with some unknown threshold T ∈ R, an algorithm must submit “bids” b ∈ R until it submits a bid as large as T . The algorithm pays the sum of its bids. We describe optimally competitive algorithms for online bribery. Our results on cost-competitive online medians extend to approximately metric distance functions, online fractional medians, and online bicriteria approximation. Department of Computer Science, University of California, Riverside, CA 92521. Email: marek@cs.ucr. edu. Research supported by NSF Grant CCR-0208856. Computer Science Department, Brown University, Providence, RI 02912. Department of Computer Science, California State University, Northridge, CA 91330. Email: jnoga@csun.edu. Department of Computer Science, University of California, Riverside, CA 92521. Email: neal@cs.ucr. edu.
Image Segmentation with Multiple Hypergraph Fusion and Superpixels

- This paper presents a new method of image segmentation based on superpixels and multiple hypergraph fusion. In this paper, the original image is oversegmented by the ultra-pixel segmentation algorithm SLIC, and the super-pixel blocks are extracted from the two aspects of color information and gradient information. A hypergraph model is constructed for each channel of the features. From the respect of random walk, the information of multiple hypergraphs is fused to construct the multi-hypergraph laplacian matrix. After obtaining the multi-hypergarph laplacian matrix, we construct the optimization model and solve the model by crossing the iterations. Then we can get the results of the superpixel blocks and the image segmentation results. With the superpixels and multiple hypergarph fusion, our method can reduce the loss of information effectively and make the segmentation more precise. Our method was evaluated in Berkeley Segmentation Database. The comparative experiments result with some state-of-the-art segmentation algorithms show that our method can give better segmentations for the natural images.
Resource Allocation in Continuous Production using Market-Based Multi-Agent Systems

Distributed resource allocation is a promising field for the application of multi-agent systems also in technical or industrial environments. The design of the multi-agent system then mainly comprises the definition of the agents' local knowledge and behavior as well as the definition of an interaction protocol for overall coordination. Most solutions of agent-based resource allocation however exist in static or discrete-event systems while the allocation of resources to continuous dynamic systems is hardly addressed. In order to derive the local and the interaction behavior of the agents, we refer to a mathematical formulation of the resource allocation problem as an optimization problem. Based on a marketlike coordination scheme, a new agent-based solution for the allocation of resources to continuous production processes is developed and applied to an industrial examples. The novelty hereby is the suitable combination of resource allocation and process control in continuous production.
Geometry of the ends of the moduli space of anti-self-dual connections

Let $X$ be a closed, four-dimensional, oriented, smooth manifold with a Riemannian metric, $g$, let $G$ be a compact Lie group, and $P$ be a principal $G$ bundle over $X$. D. Groisser and T. Parker (1987, 1989) and S. K. Donaldson (1990) conjectured that the moduli space of $g$-anti-self-dual connections on $P$, endowed with the $L^2$ metric, has finite volume and diameter. The purpose of this article is to prove this conjecture under the following additional hypotheses. Suppose that $g$ is generic and $X$ is simply-connected. If (i) $G=SU(2)$ or $SO(3)$ and $b^+(X)=0$ or (ii) $G=SO(3)$ and $w_2(P)\neq 0$, where $w_2(P)$ is the second Stiefel-Whitney class of $P$, then we prove that the moduli space of $g$-anti-self-dual connections on $P$ has finite volume and diameter with respect to the $L^2$ metric. Our development of the bubble-tree compactification of the moduli space of $g$-anti-self-dual connections --- based on ideas of Sacks and Uhlenbeck for sequences of harmonic maps from the two-sphere (1981), Taubes (1988) for sequences of Yang-Mills connections, and Parker and Wolfson (1993, 1996) for sequences of pseudo-holomorphic maps --- provides one of the key technical tools used in the proof.
10-Gigabit Throughput and Low Area for a Hardware Implementation of the Advanced Encryption Standard

Current secure applications often need encrypted channels with high throughput, of the order of several gigabits per second. This level of performance is usually obtained with a considerable cost in terms of silicon area. In this paper, we present an implementation of the Advanced Encryption Standard based on heavy pipelining and partial unrolling, which is capable of a 10-Gbps throughput when encrypting with 128-bit keys.
Sift-flow registration for facial expression analysis using Gabor wavelets

Within the affective computing research field, researchers are still facing a big challenge to establish techniques to recognize human emotions from video sequences, since human affective behavior is subtle and multimodal. Automated systems try to build a mapping between the continuous emotion space and a set of discrete expression categories (e.g. happiness, sadness). Since facial expression may vary differently across humans, designing a general expression model is the most challenging problem.
Exploiting dynamic reconfiguration techniques: the 2D-VLIW approach

Fast reconfiguration is a mandatory feature for re-configurable computing architectures. Research in this area has been increasingly focusing on new reconfiguration techniques that can sustain the architecture performance and to allow the simultaneous execution, at the same stage, of configuration and computation tasks. In this context, this paper presents a new dynamic reconfiguration technique, based on a configuration cache, that tackles this challenge by configuring and executing operations on functional units during the execution stage. This approach is implemented in a pipelined reconfigurable multiple-issue architecture called 2D-VLIW. Our dynamic reconfiguration technique takes advantage of the 2D-VLIW pipelined execution by starting reconfiguration concurrently to activities like reading operand registers and executing operations.
Fuzzy vault based automatic secret sharing in body sensor networks

Automatic secret sharing is prefered in body sensor network (BSN) where sensor nodes normally have no user interfaces and may be shared by a group of users, such as family users. The automatic user identification at each sensor node for the purpose of communication security is different from traditional biometrics with static or stable characteristics. It should be dynamic and time varying, and the bio-channel that connects the wearable or implantable sensors in an inherent secure way makes it possible. Physiological Signals based Secret Sharing scheme (PSSS) aiming to automatically deploy identical secrets among network nodes is potentially considered to be an important add-on security mechanism for BSN. In this paper, taking the advantages of randomness and similarity of physiological characteristics, a fuzzy vault based automatic secret sharing scheme is proposed. Results of simulation and experimental analysis show that the proposed scheme has an improved performance in node recognition over the existing schemes.
Contrast echocardiography for myocardial perfusion imaging using intravenous agents: progress and promises.

AIMS This article is a convenient overview to assist the interested echocardiographist towards acquiring his own experience in the field of myocardial perfusion imaging using intravenous contrast agents. This goal is now pursued in many centres, since contrast echo holds the advantages of cardiac ultrasound (non-invasiveness, high spatial and temporal resolution, wide availability, use of non-ionizing radiation), and because a variety of transpulmonary agents-together with a spectrum of imaging modalities-are becoming available. METHODS AND RESULTS Many technical considerations need to be addressed for optimal myocardial perfusion imaging: characteristics of the contrast medium (air-filled or perfluorocarbon filled and/or encapsulated agents), modality of administration (bolus injection or continuous infusion) and interaction between microbubbles and ultrasound (dependency on power output). Moreover, intermittent harmonic imaging, intermittent harmonic power Doppler, pulse inversion and amplitude modulation imaging have all been developed to enhance microbubble detection over myocardial tissue. These new acquisition modalities also yield specific artifacts impacting on myocardial perfusion assessment. Finally, acute myocardial infarction and chronic ischaemic heart disease (at baseline and during stress) are the most studied clinical models for perfusion imaging with contrast echo, and are reviewed in this article. CONCLUSION Perfusion imaging with intravenous contrast agents has never been as close to widespread clinical use as it is today, but many methodological issues remain unsettled before the wish of the contrast echocardiographist comes true: that is, a cheap, user-friendly and widely available technology that would disclose new information in echocardiography.
Depth resampling for mixed resolution multiview 3D videos

The depth information in multiview 3D video sequences are mainly utilized to synthesize new video sequences at virtual view points. Decoded depth maps, however, have typical coding artifacts such as blocking noise according to the compression ratio. Furthermore, depth maps are even resized to reduce the size of compressed bitstreams. Defects in depth maps degrade the quality of synthesized view. This paper proposes a depth resampling method as post processing for encoding/decoding of mixed resolution multiview 3D videos. Different filtering approaches are applied according to the type of depth map. Gray scale dilation filter is applied to graphics depth data to directly remove artifact in synthesized view, and segmentation based filter is applied to estimated or measured depth data to enhance edge and to reduce the compression noise. Experimental result using MPEG reference software shows that the BD bitrate gain in terms of synthesized PSNR is -5.69% for 7 test sequences.
Acid Resistance in Francisella tularensis

Francisella tularensis, the etiologic agent of tularemia, can survive under acidic conditions. Tularemia can be acquired by several routes, including by ingestion of contaminated food or water. While acid resistance is usually associated with a low oral infective dose (ID), the ID for gastrointestinal illness is quite high. In this study, four strains of F. tularensis ssp. tularensis (type A) and four strains of F. tularensis ssp. holarctica (type B) were examined for innate acid resistance and the ability to survive in synthetic gastric fluid (SGF) under in vitro conditions similar to passage through the human stomach. Survival for all strains was significantly less in pH 2.5 SGF than in pH 2.5 phosphate‐buffered saline and pH 4.0 SGF. Attenuated strains were consistently less resistant. Type B strains are most often associated with waterborne outbreaks and were examined after storage in natural water. Low‐nutrient preadaptation resulted in increased resistance. Although F. tularensis can persist under certain acidic conditions, it is sensitive to conditions replicating the fasting human stomach. This may help explain the high ID required for gastrointestinal infections.
Degree-correlation, robustness, and vulnerability in finite scale-free networks

Many naturally occurring networks have a power-law degree distribution as well as a non-zero degree correlation. Despite this, most studies analyzing the robustness to random node-deletion and vulnerability to targeted node-deletion have concentrated only on power-law degree distribution and ignored degree correlation. This study looks specifically at the effect degree-correlation has on robustness and vulnerability in scale-free networks. Our results confirm Newman's finding that positive degree-correlation increases robustness and decreases vulnerability. However, we found that networks with positive degree-correlation are more vulnerable to random node-deletion than to targeted deletion methods that utilize knowledge of initial node-degree only. Targeted deletion sufficiently alters the topology of the network to render this method less effective than uniform random methods unless changes in topology are accounted for. This result indicates the importance of degree correlation in certain network applications.
FUTURE PSYCHOLOGISTS EXPERIENCING THE CRISIS OF PROFESSIONAL SELF-DETERMINATION: FEATURES OF MOTIVATIONAL SPHERE

The paper is aimed at identifying the features of the future psychologists’ professional learning motivation under the conditions of experiencing the crisis of professional self-determination on the border of the 3 rd and 4 th year of study. The research was held at the Faculty of Psychology and Pedagogy of Volodymyr Vynnychenko Central Ukrainian State Pedagogical University during the years 2017-2018 and involved 47 3 rd year and 63 4 th year psychology students. The following methods were used: psychodiagnostic techniques “Motivation to study at a higher education institution” by Ilyina and “Personality orientation” by Bas. The data was compared to similar research conducted in the years 2003-2004. The study showed that the psychology students of recent years show more acute signs of experiencing the crisis of professional self-determination and the features of their motivational sphere could be characterised as mostly negative. The characteristic feature of the 3 rd year students is high indicators of external motivation: egoistic “self-orientation” combined with dominating motives to obtain a diploma. For the 4 th year students, the general decrease in motivation is combined with a trend of cognitive motivation decline. This tendency is mainly typical for the group of students who show an unwillingness to change the decision once made in relation to their choice of profession in spite of having negative attitude thereto. The accumulation of negative trends was interpreted in terms of the eco-facilitation approach as a forthcoming adaptive reaction of the eco-system.
Research of Noun Phrase Coreference Resolution

Coreference resolution is an important subtask in natural language processing systems. The process of it is to find whether two expressions in natural language refer to the same entity in the world. Machine learning approaches to this problem have been reasonably successful, operating primarily by recasting the problem as a classification task. A great deal of research has been done on this task in English, using approaches ranging from those based on linguistics to those based on machine learning. In Chinese, however, much less work has been done in this area. The lack of public resources is a big problem in the research of Chinese NLP. The other problem is that some features are more difficult to get than those features of English. In this paper, We present a noun phrase coreference system that refers to the work of Soon et al. (2001). We also explore the impact of various features on our system's performance. Experiments on the Chinese portion of OntoNotes 3.0 show that the platform achieves a good performance.
A Constructive Representation of Univariate Skewed Distributions

We introduce a general perspective on the introduction of skewness into symmetric distributions. Through inverse probability integral transformations we provide a constructive representation of skewed distributions, where the skewing mechanism and the original symmetric distributions are specified separately. We study the effects of the skewing mechanism on, e.g., modality, tail behavior and the amount of skewness generated. The representation is used to introduce novel classes of skewed distributions, where we induce certain prespecified characteristics through particular choices of the skewing mechanism. Finally, we use a Bayesian linear regression framework to compare the new classes with some existing distributions in the context of two empirical examples.