Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic classification of mammographic parenchymal patterns: a statistical approach

Breast parenchymal density has been found to be a strong indicator for breast cancer risk, however, to date, measures of breast density are qualitative and require the judgement of the radiologist. Objective, quantitative measures of breast density are crucial tools for assessing the association between the risk of breast cancer and mammographic density as well as for quantification of density changes to the breast. Various schemes have been proposed for classifying breast density patterns, though again each requires the judgement of the clinician to assign a particular region of tissue to its class and so it is time-consuming and prone to inter- and intra-radiologist disagreement. Motivated by recent results in texture classification, we present a new approach to breast parenchymal pattern classification. The proposed scheme uses texture models to capture the mammographic appearance within the breast area: parenchymal density patterns are modelled as a statistical distribution of clustered, rotationally invariant filter responses in a low dimensional space. This robust representation can accommodate large variations in intra-class mammogram appearance and can be trained in a straight-forward manner. Key to the approach is that parenchymal patterns can occupy disconnected regions in feature space. Objective descriptors of breast density based on the digital mammogram, are developed and validated.
PFKA: A physiological feature based key agreement for wireless body area network

In recent years, Wireless Body Area Network (WBAN) has emerged as a new technology which allows human body monitoring. Because of their enormous benefits, the use of this type of wireless networks is surprisingly increasing day by day and it has a strong presence in several domains. However, WBAN has many challenges yet to be resolved. Security is the most crucial issue. In this paper, we propose a novel key agreement scheme termed Physiological-Feature-based Key Agreement (PFKA) as a biometric based security system. The proposed scheme allows sensors belonging the same WBAN to agree on a symmetric cryptographic key generated from overlapping physiological signal features. On one hand, security analysis shows that our protocol can guarantee data confidentiality, authenticity and integrity. In the other hand, performance analysis show that our scheme reduces communication overhead in comparison with the other proposal protocol termed Secure and Efficient Ordered-Physiological-Feature-based Key Agreement for Wireless Body Area Networks (OPFKA).
Planck and re-ionization history: a model selection view

We use Bayesian model selection tools to forecast the Planck satellite's ability to distinguish between different models for the re-ionization history of the Universe, using the large angular scale signal in the cosmic microwave background polarization spectrum. We find that Planck is not expected to be able to distinguish between an instantaneous re-ionization model and a two-parameter smooth re-ionization model, except for extreme values of the additional re-ionization parameter. If it cannot, then it will be unable to distinguish between different two-parameter models either. However, Bayesian model averaging will be needed to obtain unbiased estimates of the optical depth to re-ionization. We also generalize our results to a hypothetical future cosmic variance limited microwave anisotropy survey, where the outlook is more optimistic.
Detecting the instant of emotion change from speech using a martingale framework

Towards a better understanding of emotion in speech, it is important to understand how emotion changes and when it changes. Recognizing emotions using pre-segmented speech utterances results in a loss in continuity of emotions and does not provide insights into emotion changes. In this paper, we propose an investigation into emotion change detection from the perspective of exchangeability of data points observed sequentially using a martingale framework. Within the framework, a per-frame GMM likelihood based approach is proposed as a measure of strangeness from a particular emotion class. Experimental results on the IEMOCAP database demonstrate that the proposed martingale framework offers significant improvements over the baseline GLR method for detecting emotion changes not only between neutral and emotional speech, but also between positive and negative classes along the arousal and valence emotion dimensions.
Sub-Subgiants in the Old Open Cluster M67?

We report the discovery of two spectroscopic binaries in the field of the old open cluster M67—S1063 and S1113—whose positions in the color-magnitude diagram place them ≈1 mag below the subgiant branch. A ROSAT study of M67 independently discovered these stars to be X-ray sources. Both have proper-motion membership probabilities greater than 97%; precise center-of-mass velocities are consistent with the cluster mean radial velocity. S1063 is also projected within one core radius of the cluster center. It is a single-lined binary with a period of 18.396 days and an orbital eccentricity of 0.206. S1113 is a double-lined system with a circular orbit having a period of 2.823094 days. The primary stars of both binaries are subgiants. The secondary of S1113 is likely a 0.9 M⊙ main-sequence star, which implies a 1.3 M⊙ primary star. We have been unable to explain securely the low apparent luminosities of the primary stars. The colors of S1063 suggest 0.15 mag higher reddening than found for either M67 or through the entire Galaxy in the direction of M67. S1063 could be explained as an extincted M67 subgiant, although the origin of such enhanced extinction is unknown. The photometric properties of S1113 are well modeled by a cluster binary with a 0.9 M⊙ main-sequence secondary star. However, the low composite luminosity requires a small (2.0 R⊙) primary star that would be supersynchronously rotating, in contrast to the short synchronization timescales, the circular orbit, and the periodic photometric variability with the orbital period. Geometric arguments based on a tidally relaxed system suggest a larger (4.0 R⊙) primary star in a background binary, but such a large star violates the observed flux ratio. Thus, we have not been able to find a compelling solution for the S1113 system. We speculate that S1063 and S1113 may be the products of close stellar encounters involving binaries in the cluster environment and may define alternative stellar evolutionary tracks associated with mass transfer episodes, mergers, and/or dynamical stellar exchanges.
An end-to-end QoS framework with on-demand bandwidth reconfiguration

This paper proposes a new QoS framework, called the on-demand QoS path framework (ODP). ODP provides end-to-end QoS guarantees to individual flows with minimal overhead, while keeping the scalability characteristic of Diff-Serv. ODP exercises per-flow admission control and end-to-end bandwidth reservation at the edge of the network and only differentiates traffic classes in the core of the network. In addition, to adapt to dynamically changing traffic load, ODP monitors the bandwidth utilization of the network and performs dynamic bandwidth reconfiguration in the network core. Through extensive simulations, the performance of ODP is investigated and compared with that of IntServ and DiffServ frameworks. The simulation results clearly show that ODP provides end-to-end QoS guarantees to individual flows, which DiffServ can not provide, with much less overhead than IntServ
Development of Techniques for the Computational Modelling of Harmony

This research is concerned with the development of representational and modelling techniques employed in the onstruction of statistical models of four-part harmony. Multiple viewpoint systems have been chosen to represent both surface and underlying musical structure, and it is this framework, along with Prediction by Partial Match (PPM), which will be developed during this work. Two versions of the framework are described, starting with the strictest possible application of multiple viewpoints and PPM, and then extending and generalising a little. Some implementation details are reported, as are some preliminary results.
CESSM: collaborative evaluation of semantic similarity measures

The application of semantic similarity measures to proteins annotated with Gene Ontology terms has become a common method in bioinformatics. However, the evaluation of these measures is still challenging, since no common standard of evaluation exists. We present an online tool for the automated evaluation of GO-based semantic similarity measures, CESSM, that enables the comparison of new measures against previously published ones considering their relation to sequence, Pfam and EC similarity. The tool also has a collaborative component, by which the authors of published measures can contribute to the enrichment of the evaluation by providing their own results. CESSM is freely available at http://xldb.di. fc.ul. pt/tools/cessm/ BACKGROUND The creation of the Gene Ontology (GO) [1], a controlled vocabulary for the description of gene product functions, triggered the development of computational methods that take advantage of its structured information. One such method is the application of semantic similarity measures to GO terms, whereby the similarity between two terms is calculated according to their relationship in the ontology. Likewise, semantic similarity measures can also be used to calculate the similarity between gene products, provided they are annotated with GO terms. Several semantic similarity measures based on GO have been proposed in recent years [2-12], but the evaluation of their performance has been identified as a relevant problem in the field [13]. Various evaluation strategies have been proposed, including the investigation of the relation between the semantic similarity measure and other gene product or protein similarities (such as sequence[2-7], family [12,7] or expression similarity [8,14,15]); and of the feasibility to use semantic similarity measures in such distinct scenarios as the prediction of subnuclear location [16], the ability to characterize human regulatory pathways [17], or the performance in gene clustering [9,10]. This multiplicity of evaluation strategies arises from the lack of a gold standard suitable to this scenario, driving researchers to use diverse data sets, to which they apply distinct evaluation strategies, thus rendering comparison among different works unfeasible. We present an online tool CESSM (Collaborative Evaluation of Semantic Similarity Measures) for the collaborative and automated evaluation of semantic similarity measures in the context of GO. CESSM allows researchers to compare the performance of their novel semantic similarity measures against several existing ones, using the same protein and annotation dataset and according to three distinct aspects: relation with sequence, EC class and Pfam family similarities.
Improved 3D Reconstruction using Combined Weighting Strategies

Due to the availability of cheap consumer depth sensors and recent advances in graphics hardware, scenes can be reconstructed in real time allowing a wide range of new applications. Current state-of-the-art approaches use a volumetric data structure and integrate recorded scans incrementally to provide complete and accurate reconstructions. However, scans usually contain noise and may be incomplete. Thus, using a simple update procedure becomes impracticable. To overcome these issues, we introduce a new weighting technique which combines different existing strategies. Typical strategies try to model such limitations, like varying visibility and depth-dependent noise, in order to estimate reasonable weights. Since the complexity of modeling grows extremely fast with respect to the number of considered limitations, development becomes complicated and prone to errors. Instead, we consider each limitation separately and construct easy-to-understand solutions for each one. Combining these small strategies leads to a more complex one and results in much higher quality reconstructions.
Adaptive formation transition among a mobile robot group based on phase gradient

We propose an algorithm for adaptive formation transitions of a robot group composing autonomous, nonlabeled robots. In the proposed system, one leader robot that knows the target position guides the other robots; the other robots do not have any global information. Each individual robot is equipped with a nonlinear oscillator and a simple communication system realized by LED flashlights and photodetectors. In order to control these robots, we have used phase gradients and phase waves in a manner similar to that of a slime mold (amoeba). By controlling only the leader robot, we can generate and erase a phase gradient. We propose an algorithm to control the heading directions of the follower robots according to the phase gradients. By using this algorithm, a robot group can change its formation adaptively in an obstacle region. The algorithm enables the robots to move in a tight formation in free space and dissolve this formation in obstacle regions in order to avoid deadlocks. We have not only formulated the algorithm but also developed real hardware and analyzed the system design. We have verified the proposed system by simulations and by real implementations of 12 autonomous mobile robots.
Explicating Opinion Leadership: Nonpolitical Dispositions, Information Consumption, and Civic Participation

What are the sources of opinion leadership? Do opinion leaders seek informational media, and if so, how do they consume it? Are opinion leaders active in civic life, or is it that those who are active think of themselves as opinion leaders? Is opinion leadership a cause or a consequence of political efficacy? To answer these questions, we use data from two large national surveys: a cross-sectional study conducted in 1998 and a panel study conducted in 1999 and 2000. Our cross-sectional analysis shows that opinion leadership is largely explained by nonpolitical dispositions such as self-assuredness, innovativeness, and sophistication. These opinion leaders, spurred by an interest in politics, tend to seek out informational content on television, newspapers, and the Internet, likely as a way to maintain their environmental surveillance and structural influence. All of this helps explain why opinion leadership is linked to civic participation, both directly and indirectly. Further analysis of panel data indicates that opinion leadership is a consequence rather than a cause of civic participation, lending support to the causal structure advanced in our model. These data also reveal a reciprocal relationship between opinion leadership and political efficacy, indicative of a mutually reinforcing cycle of relational dispositions and political competence. Implication for political communication, civic participation, and democratic theory are discussed.
On Distance Preserving and Sequentially Distance Preserving Graphs

A graph $H$ is an \emph{isometric} subgraph of $G$ if $d_H(u,v)= d_G(u,v)$, for every pair~$u,v\in V(H)$. A graph is \emph{distance preserving} if it has an isometric subgraph of every possible order. A graph is \emph{sequentially distance preserving} if its vertices can be ordered such that deleting the first $i$ vertices results in an isometric subgraph, for all $i\ge1$. We give an equivalent condition to sequentially distance preserving based upon simplicial orderings. Using this condition, we prove that if a graph does not contain any induced cycles of length~$5$ or greater, then it is sequentially distance preserving and thus distance preserving. Next we consider the distance preserving property on graphs with a cut vertex. Finally, we define a family of non-distance preserving graphs constructed from cycles.
Hybridizing Teaching Personal Social Responsibility (TPSR) and Problem Based Learning (PBL) in Physical Education

The aim of this research was to test the effectiveness of TPSR and PBL in physical education to increase student’s personal and social responsibility. This is quasi experimental research with pretest posttest control group design, Sample of this research were senior high school as many as 122 student’s. The instrument used was an adaptation of Tool for Assessing Responsibility-Based Education (TARE) Observation, while the data analysis using paired sample t-test and independent sample t-test. The results showed there was significant effect of hybridizing TPSR and PBL in enhancing student’s personal and social responsibility. Hybridizing TPSR and PBL is effective to increase student’s personal and social responsibility in physical education. Next, more in-depth research is required by involving a random sampling with larger sample size or by using another scientific learning approach such as inquiry or project based learning.  Alamat korespondensi : Jl. Dr. Setiabui No.229 Bandung, Indonesia E-mail : nurindrirahayu1910@upi.edu ISSN 2580-071X (online) ISSN 2085-6180 (print) DOI : 10.17509/jpjo.v3i2. 12395
PktAnon – A Generic Framework for Profile-based Traffic Anonymization

ABSTRACT Computer network researchers, system engineers and network operators have an increasing need for network traces. These are necessary to build and evaluate communication systems. This ranges from developing intrusion detection systems over evaluating network protocols or system design decisions, up to education in network security. Unfortunately, availability of real-world traces is very scarce, mainly due to privacy and security concerns. Making recorded data anonymous helps to mitigate this problem. Available anonymization systems, however, do not provide sufficient flexibility, extensibility or ease of use. Therefore, we developed a generic framework for traffic anonymization that can easily be configured by anonymization profiles. Such profiles ensure an easy adaptation of the information actually being made anonymous to different environments or local legislation. Furthermore, our framework supports flexible application of arbitrary anonymization primitives to every protocol field. Due to its extensibility our framework provides an easy incorporation of new anonymity-enhancing techniques, too. Additionally, it prevents accidental disclosure of private data by applying a technique called defensive transformation. Finally, it can be used for online as well as offline anonymization of network traffic.
Monocular camera based object recognition and 3D-localization for robotic grasping

Visual Servoing for a robotic hand is still a difficult problem to solve and is the topic of current research. To recognize an object of interest and calculating its orientation and location without extensive training is another far-fetched problem faced by researchers in this field. In this paper, object recognition based on scale-invariant feature based transform (SIFT) is done, which is used to calculate the location in image plane, scaling factor and orientation of the object in the testing image with respect to the training image of the object. Here the system is trained using single image instead of many images at different orientations. Further, the object location from 2D image coordinated is mapped to real world 3D coordinates where the third dimension is calculated using relative scaling obtained from SIF T. The i mages are obtained u sing a stationary monocular camera system. For this, we have used NAO which is autonomous, programmable humanoid robot developed by Aldebaran Robotics, France.
Development of roGFP2-derived redox probes for measurement of the glutathione redox potential in the cytosol of severely glutathione-deficient rml1 seedlings

Glutathione is important for detoxification, as a cofactor in biochemical reactions and as a thiol-redox buffer. The cytosolic glutathione buffer is normally highly reduced with glutathione redox potentials (EGSH) of more negative than −310 mV. Maintenance of such negative redox potential is achieved through continuous reduction of glutathione disulfide by glutathione reductase (GR). Deviations from steady state glutathione redox homeostasis have been discussed as a possible mean to alter the activity of redox-sensitive proteins through switching of critical thiol residues. To better understand such signaling mechanisms it is essential to be able to measure EGSH over a wide range from highly negative redox potentials down to potentials found in mutants that show already severe phenotypes. With the advent of redox-sensitive GFPs (roGFPs), understanding the in vivo dynamics of the thiol-based redox buffer system became within reach. The original roGFP versions, roGFP1 and roGFP2, however, have midpoint potentials between −280 and −290 mV rendering them fully oxidized in the ER and almost fully reduced in the cytosol, plastids, mitochondria, and peroxisomes. To extend the range of suitable probes we have engineered a roGFP2 derivative, roGFP2-iL, with a midpoint potential of about −238 mV. This value is within the range of redox potentials reported for homologous roGFP1-iX probes, albeit with different excitation properties. To allow rapid and specific equilibration with the glutathione pool, fusion constructs with human glutaredoxin 1 (GRX1) were generated and characterized in vitro. GRX1-roGFP2-iL proved to be suitable for in vivo redox potential measurements and extends the range of EGSH values that can be measured in vivo with roGFP2-based probes from about −320 mV for GRX1-roGFP2 down to about −210 mV for GRX1-roGFP2-iL. Using both probes in the cytosol of severely glutathione-deficient rml1 seedlings revealed an EGSH of about −260 mV in this mutant.
Computing a nonnegative matrix factorization -- provably

The Nonnegative Matrix Factorization (NMF) problem has a rich history spanning quantum mechanics, probability theory, data analysis, polyhedral combinatorics, communication complexity, demography, chemometrics, etc. In the past decade NMF has become enormously popular in machine learning, where the factorization is computed using a variety of local search heuristics. Vavasis recently proved that this problem is NP-complete. We initiate a study of when this problem is solvable in polynomial time. Consider a nonnegative m x n matrix $M$ and a target inner-dimension r. Our results are the following: - We give a polynomial-time algorithm for exact and approximate NMF for every constant r. Indeed NMF is most interesting in applications precisely when r is small. We complement this with a hardness result, that if exact NMF can be solved in time (nm)o(r), 3-SAT has a sub-exponential time algorithm. Hence, substantial improvements to the above algorithm are unlikely. - We give an algorithm that runs in time polynomial in n, m and r under the separablity condition identified by Donoho and Stodden in 2003. The algorithm may be practical since it is simple and noise tolerant (under benign assumptions). Separability is believed to hold in many practical settings. To the best of our knowledge, this last result is the first polynomial-time algorithm that provably works under a non-trivial condition on the input matrix and we believe that this will be an interesting and important direction for future work.