Miracle-dz/UniFAR-FTUs huggingface dataset:
Positive Semidefinite Metric Learning with Boosting

The learning of appropriate distance metrics is a critical problem in image classification and retrieval. In this work, we propose a boosting-based technique, termed BOOSTMETRIC, for learning a Mahalanobis distance metric. One of the primary difficulties in learning such a metric is to ensure that the Mahalanobis matrix remains positive semidefinite. Semidefinite programming is sometimes used to enforce this constraint, but does not scale well. BOOSTMETRIC is instead based on a key observation that any positive semidefinite matrix can be decomposed into a linear positive combination of trace-one rank-one matrices. BOOSTMETRIC thus uses rank-one positive semidefinite matrices as weak learners within an efficient and scalable boosting-based learning process. The resulting method is easy to implement, does not require tuning, and can accommodate various types of constraints. Experiments on various datasets show that the proposed algorithm compares favorably to those state-of-the-art methods in terms of classification accuracy and running time.
A Static Hand Gesture Recognition Method Based on the Depth Information

For static gestures image classification problems, this paper proposed a kind of image recognition method based on the unsupervised feature learning, mainly using the sparse auto-encoding neural network model to extract image edge feature which is belong to unsupervised feature learning, then let the edge feature as the input of the classifier, finally sort and identify the gesture image which having depth information by the trained classifier.
International Conference on Intelligent and Advanced Systems 2007 Optimistic Replication in Mobile Traffic Control Environment

Data Management in mobile computing poses great challenges to the database researchers. One of the important challenges is to provide a data replication solution, suitable for various applications in the mobile environment. Because of this difficulty, this paper interested to address a solution customized to one of most important areas in our live that is traffic control area, because this area strongly demand solutions for managing and maintaining data distributed between multiple sites. Our solution is based on the use of optimistic replication, which is the best technique for sharing data efficiently in mobile environment. The solution is applied by using Microsoft SQLSERVER replication types: Snapshot replication, Merge replication, and Transactional replication, and adaptation of some activities of these techniques to ensure availability and consistency of data.
A Scalable, Non-Hierarchical Resource Discovery Mechanism Based on Probabilistic Protocols†

Computer network interconnection provides access to a bewildering array of resources, including databases, network services, and people in various capacities. We consider the problem of allowing users to discover the existence of such resources in a large scale, administratively decentralized environment. While hierarchically organized resource registries have good scalability properties, they provide poor support for resource discovery, because users must understand how the nested components are arranged. In this paper we present a probabilistic approach that supports non-hierarchical, attribute based "yellow pages" searches. The protocols support locating a small number of instances of moderately large classes of objects. The resource graph evolves over time in accordance with what resources exist and the types of searches that users make. Simulation results indicate that the approach can support scalable and flexible resource discovery for an environment roughly the size of a large country, with several thousand administrative domains participating in resource registration and searches. Moreover, the probabilistic search strategy naturally supports fair access among competing information providers.
The weak-type (1,1) of Fourier integral operators of order –(n–1)/2

Abstract Let T be a Fourier integral operator on Rn of order–(n–1)/2. Seeger, Sogge, and Stein showed (among other things) that T maps the Hardy space H1 to L1. In this note we show that T is also of weak-type (1, 1). The main ideas are a decomposition of T into non-degenerate and degenerate components, and a factorization of the non-degenerate portion.
Apparent relief: a shape descriptor for stylized shading

Shape depiction in non-photorealistic rendering of 3D objects has mainly been concerned with the extraction of contour lines, which are generally detected by tracking the discontinuities of a given set of shape features varying on the surface and/or the picture plane. In this paper, we investigate another approach: the depiction of shape through shading. This technique is often used in scientific illustration, comics, cartoon animation and various other artwork. A common method consists in indirectly adapting light positions to reveal shape features; but it quickly becomes impractical when the complexity of the object augments. In contrast, our approach is to directly extract a set of shape cues that are easily manipulated by a user and re-introduced during shading. The main problem raised by such an approach is that shape cues must be identified in a continuous way in image space, as opposed to line-based techniques. Our solution is a novel view-dependent shape descriptor called Apparent Relief, which carries pertinent continuous shape cues for every pixel of an image. It consists of a combination of object- and imagespace attributes. Such an approach provides appealing properties: it is simple to manipulate by a user, may be applied to a vast range of styles, and naturally brings levels-of-detail functionalities. It is also simple to implement, and works in real-time on modern graphics hardware.
Semi-supervised discriminative preference elicitation for cold-start recommendation

Recommendation for cold users is fairly challenging because no prior rating can be used in preference prediction. To tackle this cold-start scenario, rating elicitation is usually employed through an initial interview in which users are queried by some carefully selected items. In this paper, we propose a novel framework to mine the most valuable items to construct query set using a semi-supervised discriminative selection (SSDS) model. To learn a low dimensional representation for users in item space which can reflect their tastes to a large extent, the model incorporates category labels as discriminative information. To ensure the used labels reliable as well as all users considered, the model utilizes a semi-supervised scheme leveraging expert guidance with graph regularization. Experimental results on real-world dataset MovieLens demonstrate that the proposed SSDS model outperforms traditional preference elicitation methods on top-N measures for cold-start recommendation.
The Image torque operator for mid-Level Vision: Theory and Experiment

A problem central to visual scene understanding and computer vision is to extract semantically meaningful parts of images. A visual scene consists of objects, and the objects and parts of objects are delineated from their surrounding by closed contours. In this thesis a new bottom-up visual operator, called the Torque operator, which captures the concept of closed contours is introduced. Its computation is inspired by the mechanical definition of torque or moment of force, and applied to image edges. It takes as input edges and computes over regions of different size a measure of how well the edges are aligned to form a closed, convex contour. The torque operator is by definition scale independent, and can be seen as an operator of mid-level vision that captures the organizational concept of 'closure' and grouping mechanism of edges. In this thesis, fundamental properties of the torque measure are studied, and experiments are performed to demonstrate and verify that it can be made a useful tool for a variety of applications, including visual attention, segmentation, and boundary edge detection.
On complexity of decoding Reed-Muller codes within their code distance

Recently Gopalan, Klivans, and Zuckerman proved that any binary Reed-Muller (RM) code RM(s, m) can be list-decoded up to its minimum distance d with a polynomial complexity of order n in blocklength n. The GKZ algorithm employs a new upper bound that is substantially tighter for RM codes of fixed order s than the universal Johnson bound, and yields a constant number of codewords in a sphere of radius less than d. In this note, we modify the GKZ algorithm and show that full list decoding up to the code distance d can be performed with a lower complexity order of at most n lns−1 n. We also show that our former algorithm yields the same complexity order n lns−1 n if combined with the new GKZ bound on the list size.
5G wareforms design for aeronautical communications

With the incoming of the new era of 5G mobile communications and Internet of Things (IoT), the aeronautical communications for aircraft, Air-to-Ground (A/G) communications and Air-to-Air (A/A) communications, confronts with new challenges of high safety, large transmission capacity, low latency, high elasticity, and synthetic service providing etc. In this paper, the new requirement and challenges of future aeronautical communications are reviewed. Moreover, the future aeronautical communications architecture is envisioned and the typical wareforms recommended for 5G are deeply analyzed. Finally, the transition from the current aeronautical datalinks is prospectively discussed.
The design and implementation of background Pass-Go scheme towards security threats

Currently, access to computer systems is often based on the use of alpha-numeric. The textual passwords or alpha-numeric passwords have been the basis of authentication systems for centuries. Similarly, it had also been the major attraction for crackers and attackers. However, users tend to face difficulty in remembering a password that is considered as secured password because this type of secured password usually has long string of characters and they appear randomly [14]. Hence, most users tend to create simple, short and insecure passwords. As a consequence, most of the time, the usability level of passwords has not achieved an optimum for a secured password [14]. In order to solve this problem, a new password scheme had been invented, known as Graphical Password System (GPS). Graphical password is an alternative mean of authentication for login intended to be used in place of conventional password; it utilizes images instead of text. In this paper, we discuss the design and intention of our proposed scheme, called Background Pass-Go (BPG). BPG is an improved version of Pass-Go, as it keeps most of the advantages of Pass-Go and achieves better usability. We had analyzed the BPG scheme in terms of 1) how BPG is able to improve other schemes of GPS especially in Pass-Go, 2) how BPG acts as a solution to different types of threats to networked computer systems. We had verified that BPG manages to overcome the shortage of other GPS schemes. Moreover, the BPG also manages to address most of the security threats for the network security system.
Controlled Dissemination Filter (CDF) for Integrated Link Selection Agents

To perform optimizations as the network changes dynamically, distributed network agents rely on information that is dispersed in the network. A data dissemination service for the agents can benefit from data filtering at selected nodes in a data distribution tree. Controlled dissemination filter (CDF) offers an efficient filtering functionality such as sifting, collection, aggregation, and scoping. We defined a number of new objective functions for the data-flow channelization algorithms, and created both centralized and distributed algorithms to optimize filter placement in polynomial time. We also designed an application of the CDF to information flows relevant to the unicast routing control agent (URCA) and showed how the CDF reduces the bandwidth consumed by data dissemination without impairing the URCA decision-making functionalities.
A Small Survey on Preference Languages and Preference Mining Techniques

The research literature on preference modeling, reasoning and eliciting is extensive. Different specification approaches have been proposed to model user preferences such as graphs, logical formalisms and SQL-like constructors. The approach of CP-Nets [2] uses a very simple graphical model which captures users qualitative conditional preference over tuples, under a ceteris paribus semantics. The approach of TCP-Nets [3] generalizes the CP-Nets by introducing the ability of expressing absolute and relative importance of object attributes in the graphical model. In [19] a simple logical framework is introduced for expressing conditional preference statements (cp-rules). It generalizes both the CP-Net and TCP-Net approaches, by relaxing the ceteris paribus semantics and allowing more expressiveness. This formalism is used in [7] in order to extend the SQL query language with preference support. In [5] a simple logical framework is proposed for expressing preferences by means of preference formulae. These formulae are incorporated into the Relational Algebra and into SQL through the operator winnow parameterized by a preference formula. This approach is very expressive and generalizes the CP-Nets, TCP-Nets and the cp-rules of [19]. From a more operational standpoint, [14] proposes to inductively construct complex preferences by means of various basic and intuitive preference construc-tors. These preference constructors are used to extend the SQL query language with preference support [15]. Unlike the previous approaches, the formalism of [14] does not allow to express contextual preferences. In the present paper, we follow the approach of [1] for expressing contextual preference rules. In this work, the formalism i + ≻ i − | X for specifying contextual preference rules has been introduced and a method for incorporating the preference rules into the query-answering mechanism of a database system has been proposed. The preference rules are supposed to be available and the problem of how the rules are obtained is out of the scope of that paper. For a comprehensive survey on preference modeling and query languages with preference support see [18]. In what follows we focus on the literature related to the topic of preference elicitation. Preference learning can be divided into two distinct problems: label ranking and object ranking. Label ranking aims at predicting an order over a set of labels for a given object [8, 11]. One can view the objects as tuples containing information about users: age, education, economic status, city, profession, etc. And the labels represents objects to rank. The problem of label ranking …
A BiCMOS W-Band 2×2 Focal-Plane Array With On-Chip Antenna

This paper presents a W-band 2 × 2 focal-plane array (FPA) for passive millimeter-wave imaging in a standard 0.18 μm SiGe BiCMOS process (fT/fmax = 200/180 GHz). The FPA incorporates four Dicke-type receivers representing four imaging pixels. Each receiver employs the direct-conversion architecture consisting of an on-chip slot folded dipole antenna, an SPDT switch, a low noise amplifier, a single-balanced mixer, an injection-locked frequency tripler (ILFT), an IF variable gain amplifier, a power detector, an active bandpass filter and a synchronous demodulator. The LO signal is generated by a shared Ka-band PLL and distributed symmetrically to four local ILFTs. The measured LO phase noise is -93 dBc/Hz at 1 MHz offset from the 96 GHz carrier. This imaging receiver (without antenna) achieves a measured average responsivity and noise equivalent power of 285 MV/W and 8.1 fW/Hz1/2, respectively, across the 86-106 GHz bandwidth, which results a calculated NETD of 0.48 K with a 30 ms integration time. The system NETD increases to 3 K with on-chip antenna due to its low efficiency at W-band. MMW images have been generated in transmission mode. This work demonstrates the highest integration level of any silicon-based systems in the 94 GHz imaging band.
Translocus Is Independent of the Heavy Chain Intron myc Chromosome-based Immunoglobulin Heavy/c- B-Cell Tumorigenesis in Mice Carrying a Yeast Artificial

We have used YAC (yeast artificial chromosome) technology to create large translocation regions where the cmyc proto-oncogene is coupled to the core region of the human immunoglobulin heavy chain ( IgH) locus (from VH2–5 through to Cd). Chimeric mice were obtained from embryonic stem cells carrying a single copy of the 240-kb IgH/cmyc translocation region. B-cell tumorigenesis occurs in the translocus mice, even when the entire Em intron enhancer region between the joining segments and switch m is deleted. This demonstrates that as yet unidentified regulatory elements in theIgH locus, independent from the known enhancers, are sufficient to cause B-cell specific activation of cmyc after translocation. The phenotype of tumors from IgH/c-myc YAC transgenic mice with or without Em (B220, IgM /IgD) is reminiscent of Burkitt’s lymphoma. A rapidly expanding abnormal B-cell population is present at birth and accumulates in bone marrow, periphery, and spleen, well before discrete tumor establishment. Molecular analysis identified a clonal origin, with rearrangement of one mouse heavy chain allele retained in tumor cells from different sites, whereas subsequent rearrangements of heavy or light chain loci can be diverse. These mice routinely develop mature B-cell tumors early in life and may provide an invaluable resource of a B-cell lymphoma model.
Sertad1 Plays an Essential Role in Developmentaland Pathological Neuron Death

Developmental and pathological death of neurons requires activation of a defined pathway of cell cycle proteins. However, it is unclear how this pathway is regulated and whether it is relevant in vivo. A screen for transcripts robustly induced in cultured neurons by DNA damage identified Sertad1, a Cdk4 (cyclin-dependent kinase 4) activator. Sertad1 is also induced in neurons by nerve growth factor (NGF) deprivation and Aβ (β-amyloid). RNA interference-mediated downregulation of Sertad1 protects neurons in all three death models. Studies of NGF withdrawal indicate that Sertad1 is required to initiate the apoptotic cell cycle pathway since its knockdown blocks subsequent pathway events. Finally, we find that Sertad1 expression is required for developmental neuronal death in the cerebral cortex. Sertad1 thus appears to be essential for neuron death in trophic support deprivation in vitro and in vivo and in models of DNA damage and Alzheimer's disease. It may therefore be a suitable target for therapeutic intervention.
Isolation and characterization of oligomerization domain I and II coding regions of doublesex genes in agricultural fruit flies (Diptera: Tephritidae).

Bactrocera fruit flies are ranked among the most destructive pests of the worldwide fruit and vegetable trades. Coding regions of two oligomerization domains within doublesex (dsx) genes were determined in Bactrocera dorsalis (oriental fruit fly) and B. correcta (guava fruit fly). Resulting sequences revealed a high degree of similarity at both nucleotide and putative amino acid levels in the genus Bactrocera. Conservation of the DNA-binding DM motif and several known molecular features within the domains suggest a presence of strong purifying selection on the DSX proteins. Topology of the phylogenetic gene trees and deduced amino acid substitution patterns suggest that the coding region sequences of the two domains are diversified in concert parallel with the species differentiation.
An Adaptive Metaheuristic for Vehicle Routing Problems with Time Windows and Multiple Service Workers

Distribution planning in urban areas faces a lack of available parking space at customer sites. One approach to mitigate the issue is to cluster nearby customers around known parking locations. Deliveries from each parking location to its assigned customers occur by a second mode of transport (for example by foot). These lead to long service times at each of the clusters. However, long service times in conjunction with time windows can lead to inefficient routes as nearby customer clusters with overlapping service times may not be connected. As a consequence, assigning additional service workers to each vehicle is a strategy to reduce service times. The additional workers can do the last mile deliveries in parallel to reduce the service time of a cluster and hence permit more efficient routing. The trade-off between paying additional workers to reduce costs for vehicles and driving creates a new decision problem called the vehicle routing problem with time windows and multiple service workers (VRPTWMS). The present work introduces a stochastic cluster first, route second algorithm. The clus- tering takes care of assigning and scheduling customers to parking locations. Its goal is to allow the routing algorithm to obtain high quality results. These two stages are linked together with a feedback loop based on the well established ant colony optimiza- tion metaheuristic. This allows learning from prior results and leads to vastly improved solution quality. For each of the used benchmark instances new best known solutions were generated. Furthermore, it is shown that applying the concept of bi-modal trans- portation potentially reduces both cost and environmental impact in regular vehicle routing problems with time windows.
The refocusing distance of a standard plenoptic photograph

In the past years, the plenoptic camera aroused an increasing interest in the field of computer vision. Its capability of capturing three-dimensional image data is achieved by an array of micro lenses placed in front of a traditional image sensor. The acquired light field data allows for the reconstruction of photographs focused at different depths. Given the plenoptic camera parameters, the metric distance of refocused objects may be retrieved with the aid of geometric ray tracing. Until now there was a lack of experimental results using real image data to prove this conceptual solution. With this paper, the very first experimental work is presented on the basis of a new ray tracing model approach, which considers more accurate micro image centre positions. To evaluate the developed method, the blur metric of objects in a refocused image stack is measured and compared with proposed predictions. The results suggest quite an accurate approximation for distant objects and deviations for objects closer to the camera device.