Miracle-dz/UniFAR-FTUs huggingface dataset:
A J2ME-Based Wireless Intelligent Video Surveillance System Using Moving Object Recognition Technology

A low-cost intelligent mobile phone-based wireless video surveillance solution using moving object recognition technology is proposed in this paper. The proposed solution can be applied not only to various security systems, but also to environmental surveillance. Firstly, the basic principle of moving object detecting is given. Limited by the memory consuming and computing capacity of a mobile phone, a background subtraction algorithm is presented for adaptation. Then, a self-adaptive background model that can update automatically and timely to adapt to the slow and slight changes of natural environment is detailed. When the subtraction of the current captured image and the background reaches a certain threshold, a moving object is considered to be in the current view, and the mobile phone will automatically notify the central control unit or the user through phone call, SMS (Short Message System) or other means. The proposed algorithm can be implemented in an embedded system with little memory consumption and storage space, so it’s feasible for mobile phones and other embedded platforms, and the proposed solution can be used in constructing mobile security monitoring system with low-cost hardware and equipments. Based on J2ME (Java2 Micro Edition) technology, a prototype system was developed using JSR135 (Java Specification Requests 135: Mobile Media API) and JSR120 (Java Specification Requests 120: Wireless Messaging API) and the test results show the effectiveness of proposed solution.
A blind robust watermarking scheme based on CT and SVD

In this paper, we present an image watermarking scheme based on contourlet transform (CT) and singular value decomposition (SVD). Unlike usual CT algorithm where the watermarking is embedded directly into the coefficients, we segment the lowpass coefficients into blocks. The blocks are decomposed using SVD, and the watermarking image after Arnold scrambling is embedded into the biggest singular value by using Euclidean norm and combining with human visual system (HVS) adaptively. Experimental results show that the proposed scheme guarantees high peak signal to noise ratio (PSNR), and is very robust against scaling, JPEG compression, cropping etc.
ACM SIGACT news distributed computing column 13

The Distributed Computing Column covers the theory of systems that are composed of a number of interacting computing elements. These include problems of communication and networking, databases, distributed shared memory, multiprocessor architectures, operating systems, verification, Internet, and the Web.This issue describes the PODC 20th anniversary Special Issue published by Distributed Computing journal.
Concordance of hepatitis C virus typing methods based on restriction fragment length polymorphism analysis in 5' noncoding region and NS4 serotyping, but not in core PCR or a line probe assay

Data from sequence analysis, genotyping by restriction fragment length polymorphism in the 5' noncoding region, and NS4 serotyping of the sera of 20 patients with chronic hepatitis C virus infection have shown 100% concordance, while core-based methods and a line probe assay have shown several missing or wrong results.
Interactive image deformation using cage coordinates on GPU

Cage-based deformation is widely used in various applications of image and geometry processing. In this paper, we show how to deform a 2D image by using Cage Coordinates (CC), which naturally unifies the existing coordinates, such as Mean Value Coordinates (MVC), Harmonic Coordinates (HC) and Green Coordinates (GC) into the same formulation. The cage is generated interactively for the region-of-interest (ROI), and the warping effect is obtained by simply changing the positions of the cage vertices. An intuitive method is designed to keep the image shape during the process of deformation. Meanwhile, a new GPU-based framework of using CC for real time image deformation is developed. Such real-time rendering and the intuitive user interaction in our cage-based image deformation make it easy to conduct the image animation by enabling the cage vertices' 2D motions, as demonstrated in the experimental results of the proposed technique.
A candidate precursor to serous carcinoma that originates in the distal fallopian tube (J Pathol 2007; 211: 26–35)

The tubal fimbria is a common site of origin for early (tubal intraepithelial carcinoma or TIC) serous carcinomas in women with familial BRCA1 or 2 mutations (BRCA+). Somatic p53 tumour suppressor gene mutations in these tumours suggest a pathogenesis involving DNA damage, p53 mutation, and progressive loss of cell cycle control. We recently identified foci of strong p53 immunostaining-termed 'p53 signatures'-in benign tubal mucosa from BRCA+ women. To examine the relationship between p53 signatures and TIC, we compared location (fimbria vs ampulla), cell type (ciliated vs secretory), evidence of DNA damage, and p53 mutation status between the two entities. p53 signatures were equally common in non-neoplastic tubes from BRCA+ women and controls, but more frequently present (53%) and multifocal (67%) in fallopian tubes also containing TIC. Like prior studies of TIC, p53 signatures predominated in the fimbriae (80-100%) and targeted secretory cells (HMFG2 + /p73-), with evidence of DNA damage by co-localization of gamma-H2AX. Laser-capture microdissected and polymerase chain reaction-amplified DNA revealed reproducible p53 mutations in eight of 14 fully-analysed p53 signatures and all of the 12 TICs; TICs and their associated ovarian carcinomas shared identical mutations. In one case, a contiguous p53 signature and TIC shared the same mutation. Morphological intermediates between the two, with p53 mutations and moderate proliferative activity, were also seen. This is the first report of an early and distinct alteration in non-neoplastic upper genital tract mucosa that fulfils many requirements for a precursor to pelvic serous cancer. The p53 signature and its malignant counterpart (TIC) underline the significance of the fimbria, both as a candidate site for serous carcinogenesis and as a target for future research on the early detection and prevention of this disease.
Word concept extraction using HOSVD for automatic text summarization

Computers understand little about the meaning of human language. Vector space models of semantics are beginning to overcome these limits. In this regard, one of the modern issues is using high dimensional data, which is formulated as tensors. Also, due to the increased information and texts, automatic text summarization has become one of the most important issues in information retrieval and natural language processing. In this paper, we propose a new method, using higher-order singular value decomposition (HOSVD) for extracting the concept of the words from word-document-time three-dimensional tensor and then select important sentences with more cosine similarity to this concept. In the following, we measure WordNet-based semantic similarity between sentences and remove redundancy sentences with less importance. The evaluation of the proposed method is done using the ROUGE evaluation on the DUC 2007 standard data set that the obtained results indicate the predominance of our method over many dominant systems.
A new active contour model-based segmentation approach for accurate extraction of the lesion from breast DCE-MRI

Breast lesion segmentation is an essential step in developing Computer-aided Diagnostic (CAD) system for the early detection of breast cancer. However, accurate lesion segmentation is challenging, since the lesions may have complicated topological structures and different intensity distributions. This paper describes a novel approach for breast lesion segmentation from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using a level set-based active contour model. Its evolution is controlled by specially designed signed pressure function that only accounts for distribution of image background intensity, so solving the weak-edge-passed problem and improving the robustness to segment different lesions. To confirm the proposed approach, it is compared with different methods based on level set. Experiment results show that the proposed method leads to better results. On a total of 38 breast DCE-MRI studies, our method yields a mean difference (MAD) of 7.2561±12.4537 pixels and Jaccard index of 0.8564±0.0493 compared to manual ground truth segmentation.
Current issues and challenges of MIMO antenna designs

The demand for high data rate and channel bandwidth is always the primary area of concern in modern wireless communication systems. All the modern wireless communication system applications are rapidly shifting towards multiple input multiple output (MIMO) from single input and single output (SISO) and single input multiple output (SIMO) systems, increasing the demand for the integration of multiple antennas in the users equipment. The development of MIMO antennas and its performance evaluation for the portable wireless communication terminals have attracted many researchers to improve channel capacity, bandwidth, gain, polarization diversity and reduce coupling between inter elements. Further these systems also demands that the multiple element antenna (MEA) should be minimized so that they can fit in the compact and robust user equipment, and support multiband operation for the equipment reusability in the different regions of the world. Antenna designers have ample vacuum in the development of novel antenna systems for the new generation networks by enhancing the impedance bandwidth and multiband resonance. In addition improving radiation pattern diversity reduces the correlation coefficient and increases MIMO antenna performance. This review paper is focused on the related work in the field of MIMO antenna designs. Researchers have proposed various different techniques to design antennas at a range of microwave bands of interest, where the key concern of the research is to enhance the channel capacity by reducing the correlation coefficient and increasing the isolation between multi element antennas.
Autotuning dense linear algebra libraries on GPUs

As GPUs are quickly evolving in complexity, tuning numerical libraries for them is becoming more challenging. We present an autotuning approach in the area of dense linear algebra (DLA) libraries for GPUs. The MAGMA library is used to demonstrate the techniques and their effect on performance and portability across hardware systems. We show that, figuratively speaking, our autotuning approach for GPUs can be regarded as both the beauty and the beast behind hybrid DLA libraries as it is an elegant and very practical solution for easy maintenance and performance portability, while often being a brute force, empirically based exhaustive search that would find and set automatically the best performing algorithms/kernels for a specific hardware configuration. The exhaustive search is often relaxed by applying various performance models.
An Investigation into Reactive Planning in Complex Domains

A model of purely reactive planning is proposed based on the concept of reactive action packages. A reactive action package, or RAP, can be thought of as an independent entity pursuing some goal in competition with many others at execution time. The RAP processing algorithm addresses the problems of execution monitoring and replanning in uncertain domains with a single, uniform representation and control structure. Use of the RAP model as a basis for adaptive strategic planning is also discussed.
A Reward Design Pattern in BCSS

Although constructs have been developed for designing the features of Behavior Change Support Systems (BCSSs), detailed descriptions and gui- delines for their software level implementation are lacking. Through develo- ping software design patterns one is able to examine BCSSs at a more intricate technical level instead of merely a black-box approach to them. In this paper, we present a software design pattern for rewarding users as a way of enhan- cing persuasive human-computer dialogue in BCSS. The resulting pattern contributes to both research on software design of persuasive system features, and for assisting the practical development of such systems.
Fourth order conservative twist systems: simple closed characteristics

On the energy manifolds of fourth order conservative systems closed characteristics can be found in many cases via analogues of Twist-maps. The ‘Twist property’ implies the existence of a generating function which leads to second order recurrence relations. We study these recurrence relations to find simple closed characteristics and we give conditions when fourth order systems satisfy the ‘Twist property’.
Shareholder Influence on Joint Venture Exploration

In this study, we theorize about how different types of institutional investors influence firms’ choice of exploration versus exploitation for their joint ventures (JVs). Exploratory JVs engender risk, uncertain outcomes, and ex post contractual updating, whereas exploitative JVs allow for ex ante contracts. We argue that dedicated institutional investors (DIIs), who maintain concentrated holdings over time regardless of current earnings, offer tolerance for failure and reward for long-term success that encourages managerial choice of exploratory JVs. Transient institutional investors (TIIs), who trade frequently based on near-term performance metrics, prefer ex ante contracts and use exit to discipline managers who do not meet their short-term performance objectives. This suggests that TIIs may influence managers to reduce the extent to which they choose exploratory (as opposed to exploitative) JVs. Furthermore, we argue that the transactional governance of TIIs gives way to the relational monitoring of DIIs when both types of shareholders are present. As a result, the likelihood of choosing exploration, versus exploitation, as a JV formation strategy is greatest in the presence of high DII and TII ownership. We examine JVs among S&P 500 firms over the years 2000 to 2010, and results largely support our theory.
Projection structures of three photosynthetic complexes from Rhodobacter sphaeroides: LH2 at 6 A, LH1 and RC-LH1 at 25 A.

Three photosynthetic complexes, light-harvesting complex 2 (LH2), light-harvesting complex 1 (LH1), and the reaction centre-light-harvesting complex 1 photounit (RC-LH1), were purified from a single species of a purple bacterium, Rhodobacter sphaeroides, and reconstituted into two-dimensional (2-D) crystals. Vesicular 2-D crystals of LH1 and RC-LH1 were imaged in negative stain and projection maps at 25 A resolution were produced. The rings formed by LH1 have approximately the same mean diameter as the LH1 rings from Rhodospirillum rubrum ( approximately 90 A) and therefore are likely to be composed of 15 to 17 alphabeta subunits. In the projection map calculated from the RC-LH1 2-D crystals, the reaction centre is represented by an additional density in the centre of the ring formed by the LH1 subunits. The marked improvement of shape and fine structure after a rotational pre-alignment of the RC-LH1 unit cells before averaging strongly suggests that the RC is not in a unique orientation within the LH1 rings. Tubular crystals of LH2 showed a high degree of order and allowed calculation of a projection map at 6 A resolution from glucose-embedded specimens. The projection structure shows a ring of nine alphabeta subunits. Variation of the alpha-helical projection densities suggests that the 9-fold symmetry axis is tilted with respect to the membrane normal.
Challenging SMT solvers to verify neural networks

In recent years, Satisfiability Modulo Theory (SMT) solvers are becoming increasingly popular in the Computer Aided Verification and Reasoning community. Used natively or as back-engines, they are accumulating a record of success stories and, as witnessed by the annual SMT competition, their performances and capacity are also increasing steadily. Introduced in previous contributions of ours, a new application domain providing an outstanding challenge for SMT solvers is represented by verification of Multi-Layer Perceptrons (MLPs) a widely-adopted kind of artificial neural network. In this paper we present an extensive evaluation of the current state-of-the-art SMT solvers and assess their potential in the promising domain of MLP verification.
Growth‐compensating phenomena in continuous cultures of Dunaliella tertiolecta limited simultaneously by light and nitrate

Two nitrogen‐limited continuous cultures of Dunaliella tertiolecta were grown on light/dark cycles. One was submitted to limiting photon flux density (PFD) and the other to nonlimiting PFD. The growth rate was identical in the two cultures despite the difference in the PFD conditions. Once equilibria were reached both cultures, the PFD were reversed to simulate a decrease and an increase in light conditions. A large suite of variables was measured to characterize the response of the cells, mainly through the interactions of carbon and nitrogen assimilation pathways. A decrease in irradiance led to a rapid decrease in algal biovolume; the biovolume‐based growth rate (µ) descended to levels lower than those estimated for cells of the light‐limited culture. An increase in irradiance rapidly led to an increase in µ, which attained values greater than those observed in high‐light cells of the other culture before the shift. For the two cultures before and after the shift, cell carbon and cell volume were strongly correlated, showing the same pattern of diel variations.
Chapter 7 Parallelism in Sound and Music Applications

This paper is about the role of the operating system (OS) within computer nodes of network audio systems. While many efforts in the network-audio community focus on low-latency network protocols, here we highlight the importance of the OS for network audio applications. We present Tessellation, an experimental OS tailored to multi-core processors. We show how specific OS features, such as guaranteed resource allocation and customizable user-level runtimes, can help ensure quality-of-service (QoS) guarantees for data transmission and audio signal processing, especially in scenarios where network bandwidth and processing resources are shared between applications. To demonstrate performance isolation and service guarantees, we benchmark Tessellation under different conditions using a resource-demanding network audio application. Our results show that Tessellation can be used to create low-latency network audio systems.
Computing bounded-width tree and branch decompositions of k-outerplanar graphs

By a well known result the treewidth of k-outerplanar graphs is at most 3k-1. This paper gives, besides a rigorous proof of this fact, an algorithmic implementation of the proof, i.e. it is shown that, given a k-outerplanar graph G, a tree decomposition of G of width at most 3k-1 can be found in O(kn) time and space. Similarly, a branch decomposition of a k-outerplanar graph of width at most 2k+1 can be also obtained in O(kn) time, the algorithm for which is also analyzed.
Sexual Dimorphism in Glucose and Lipid Metabolism during Fasting, Hypoglycemia, and Exercise

Sexually dimorphic physiologic responses occur during fasting, hypoglycemia, and exercise. The areas covered in this mini review include studies that have used isotopic tracer methods and/or euglycemic clamp studies to investigate substrate metabolism during the above common physiologic stress. Women have greater reliance on lipid metabolism during fasting, hypoglycemia, and exercise while men exhibit preference of carbohydrate utilization. Plasma glucose concentrations were shown to be lower, while free fatty acids (FFA) and lipolysis higher in women compared to men after fasting. Hypoglycemia resulted in significantly reduced epinephrine, norepinephrine, glucagon, growth hormone, pancreatic polypeptide, and hepatic glucose production responses in females as compared to males. Sexual dimorphism during exercise was demonstrated by higher glycerol and FFA responses in women compared to men and higher carbohydrate oxidation rate in men. Mechanisms that can increase lipolytic rates in women include higher total fat mass, enhanced lipolytic sensitivity to epinephrine, and increased activation of β adrenergic receptors.
Examining Heuristics for the K-Centers Problem

In this paper, we discuss and analyze the heuristics existing to solve the K-Center problem. The K-Center problem is used in various practical scenarios such as facility location, load-balancing, ATM mapping, Cloud Server Selection, or even data clustering and image classification. Specifically, we examine a standard Greedy algorithm with an approximation factor of 2, the clustering algorithm introduced by Gonzales in 1985, and the Dominating Set Algorithm(commonly referred to as the elimination heuristic) devised by Jurij Mihelič and Borut Robič. We also propose a new heuristic to solve the specified problem using Tree-Independent Dual-Trees devised by Ryan R. Curtin.
Linkage Analysis of a Model Quantitative Trait in Humans: Finger Ridge Count Shows Significant Multivariate Linkage to 5q14.1

The finger ridge count (a measure of pattern size) is one of the most heritable complex traits studied in humans and has been considered a model human polygenic trait in quantitative genetic analysis. Here, we report the results of the first genome-wide linkage scan for finger ridge count in a sample of 2,114 offspring from 922 nuclear families. Both univariate linkage to the absolute ridge count (a sum of all the ridge counts on all ten fingers), and multivariate linkage analyses of the counts on individual fingers, were conducted. The multivariate analyses yielded significant linkage to 5q14.1 (Logarithm of odds [LOD] = 3.34, pointwise-empirical p-value = 0.00025) that was predominantly driven by linkage to the ring, index, and middle fingers. The strongest univariate linkage was to 1q42.2 (LOD = 2.04, point-wise p-value = 0.002, genome-wide p-value = 0.29). In summary, the combination of univariate and multivariate results was more informative than simple univariate analyses alone. Patterns of quantitative trait loci factor loadings consistent with developmental fields were observed, and the simple pleiotropic model underlying the absolute ridge count was not sufficient to characterize the interrelationships between the ridge counts of individual fingers.
Cross-domain traffic scene understanding by motion model transfer

This paper proposes a novel framework for cross-domain traffic scene understanding. Existing learning-based outdoor wide-area scene interpretation models suffer from requiring long term data collection in order to acquire statistically sufficient model training samples for every new scene. This makes installation costly, prevents models from being easily relocated, and from being used in UAVs with continuously changing scenes. In contrast, our method adopts a geometrical matching approach to relate motion models learned from a database of source scenes (source domains) with a handful sparsely observed data in a new target scene (target domain). This framework is capable of online ''sparse-shot'' anomaly detection and motion event classification in the unseen target domain, without the need for extensive data collection, labelling and offline model training for each new target domain. That is, trained models in different source domains can be deployed to a new target domain with only a few unlabelled observations and without any training in the new target domain. Crucially, to provide cross-domain interpretation without risk of dramatic negative transfer, we introduce and formulate a scene association criterion to quantify transferability of motion models from one scene to another. Extensive experiments show the effectiveness of the proposed framework for cross-domain motion event classification, anomaly detection and scene association.