Miracle-dz/UniFAR-FTUs huggingface dataset:
Finding and Visualizing Subspace Clusters of High Dimensional Dataset Using Advanced Star Coordinates

— Analysis of high dimensional data is a research area since many years. Analysts can detect similarity of data points within a cluster. Subspace clustering detects useful dimensions in clustering high dimensional dataset. Visualization allows a better insight of subspace clusters. However, displaying such high dimensional database clusters on the 2-dimensional display is a challenging task. We proposed an ISC-ASC approach which first identifies subspace clusters in a high dimensional dataset and then display these clusters on a 2-dimensional display device. Algorithm ISC detects the subspace clusters using a density notion of clustering. Algorithm ASC visualizes these subspace clusters. In ASC instead of considering all the dimensions, the dimensions which are taking part in subspace clustering are considered to find the projection points. ISC-ASC is beneficial for users to identify subspace clusters. Visualizing these subspace clusters using ASC have efficient knowledge discovery which helps to take decision about the quality of subspace clusters.
Conformal Invariance

At the beginning of the semester we motivated our investigation of symmetries by illustrating that, given differential equations which were symmetric , the solutions had to transform into each other under the symmetries as a representation of the symmetry. The first illustrations considered Schrödinger equations with symmetric potentials, such as the electrons in the spherically symmetric potential of an atom, having wavefunctions transforming under the rotation group. The Laplacian is invariant under both rotations and translations, but the source of the potential may be taken as invariant rotationally but not translationally. Under translations, we might make a connection of the wave function at x for an atom with a nucleus at y with the wave function at x + a for an atom with a nucleus at y + a, as the physics is translationally invariant if we translate both the point of evaluation and the boundary conditions, or sources. Thus the way symmetries act on solutions depend on both the differential operator having the symmetry and the boundary conditions or sources having the symmetry. The electric field of a point charge at the center of a conducting cube would not have a full rotational symmetry, but would behave as a representation of the symmetry group of the cube. It is obvious that the differential operator ∇ 2 = ∂ 2 ∂x 2 + ∂ 2 ∂y 2 + ∂ 2 ∂z 2 is symmetric under x ↔ −x, under x ↔ y, and under x ↔ z, which generate the group. For a spherical conductor with a charge at the center, we should have O(3) symmetry , but how do we know ∇ 2 is rotationally invariant, when it seems to depend on a choice of three axes? One way is to perform a change of variables (x, y, z) −→ R (u, v, w) where R is an orthogonal matrix. Then the chain rule shows that ∇ 2 = ∂ 2 ∂u 2 + ∂ 2 ∂v 2 + ∂ 2 ∂w 2 , of the same form as in terms of (x, y, z). Of course it might be even better to make a change of variables to spherical coordinates, where we would see that the r dependence factors out, and actually gives us the differential equations in θ and φ which would in general provide the decomposition of Φ into spherical harmonics, and for a conducting …
Experience of Supervision Scale: The Development of an Instrument to Measure Child Welfare Workers' Experience of Supervisory Behaviors

x Chapter 1: Introduction . 1 Child Welfare Supervision as an Intervention . 2 Improving the Quality of Child Welfare Supervision . 8 Limits to What is Known . 9 Rationale and Purpose of Study . 10 Chapter 2: Literature Review . 13 The Child Welfare System . 13 Child Welfare Workforce . 14 Social Work Supervision . 18 Supervisory functions . 18 Stages of the supervisory process . 19 History of social work supervision . 19 Defining social work supervision . 22 Child Welfare Supervision . 23 Clinical supervision in child welfare . 23 Provision of child welfare supervision . 24 Conceptual Models of Social Work Supervision . 26 Interactional supervision . 27
ERG Transcriptional Networks in Primary Acute Leukemia Cells Implicate a Role for ERG in Deregulated Kinase Signaling

High expression of the E26 transforming sequence related gene (ERG) is associated with poor prognosis in a subgroup of leukemia patients with acute myeloid (AML) and acute T-lymphoblastic leukemia (T-ALL). In a previous study we proposed that ERG overexpression may deregulate several signaling cascades in acute leukemia. Herein, we further expand those studies by identifying a consensus of biological targets in primary blasts of newly diagnosed acute leukemia patients. Our findings of chromatin immunoprecipitation-on-chip of primary samples revealed 48 significantly enriched single genes including DAAM1 and NUMB. Significantly enriched signaling pathways included WNT/β-catenin, p53, and PI3K/AKT with ERG overexpression inducing dephosphorylation of AKT(Ser473) relative to non ERG expressing K562 cells. Cell based ERG overexpression studies also revealed drug resistance to multi-kinase inhibitor, BAY 43-9006 (Sorafenib) and to the tyrosine kinase inhibitor TKI258. Thus in primary leukemic cells, ERG may contribute to the dysregulation of kinase signaling, which results in resistance to kinase inhibitors.
Assessing Routing Behavior on On-Chip-Network

Network-on-chip (NoC) is being proposed as a scalable and reusable communication platform for future SoC applications. An important problem in NoC design is deciding the type of routing which is one of the most crucial key factors that greatly affects the NoC architecture based systems performance. Currently, most of the proposals for routing in NoC are based upon deterministic routing mechanism because it gives better latency at low packet injection and requires less resources while guaranteeing an orderly packet arrival. However, the disadvantage of deterministic routing is that it cannot respond to dynamic network condition such as congestion. When the network becomes congested, adaptive routing provides better throughput and lower latency by allowing alternate paths. In this paper, using simulation, we evaluate the performance of adaptive routing algorithm to deterministic routing strategy respected to throughput, power consumption and latency. The simulation environment is 2D-mesh based NoC topology including different kinds of mapping video object plane decoder (VOPD) application onto this architecture. The experiment results prove the adaptive routing performance under network congestion occurrence
2 Hopf algebras as symmetries

We present the review of noncommutative symmetries applied to Connes’ formulation of spectral triples. We introduce the notion of equivariant spectral triples with Hopf algebras as isometries of noncommutative manifolds, relate it to other elements of theory (equivariant K-theory, homology, equivariant differential algebras) and provide several examples of spectral triples with their isometries: noncommutative torus, isospectral (twisted) deformations and finite spectral triples.
Power quality analysis of a static synchronous compensator (STATCOM) connected to a high voltage transmission network

This paper analyses the voltage harmonic content at the Point of Common Coupling (PCC) and at the Voltage Source Converter (VSC) output in a STATCOM application by using a calculation tool, also discussed in the paper. Subsequently, a parameter sensitivity analysis is carried out taking into account the variation of key parameters such as the line length, the shunt transformer impedance, the capacitor bank connection and the effect of a given filter, for instance a LC type filter. The harmonic content at the (PCC) obtained when 24 and quasi 48 pulse modulation techniques are used, is calculated and subsequently compared against the stringent Spanish power quality legislation.
Quality-Aware Estimation of Facial Landmarks in Video Sequences

Face alignment in video is a primitive step for facial image analysis. The accuracy of the alignment greatly depends on the quality of the face image in the video frames and low quality faces are proven to cause erroneous alignment. Thus, this paper proposes a system for quality aware face alignment by using a Supervised Decent Method (SDM) along with a motion based forward extrapolation method. The proposed system first extracts faces from video frames. Then, it employs a face quality assessment technique to measure the face quality. If the face quality is high, the proposed system uses SDM for facial landmark detection. If the face quality is low the proposed system corrects the facial landmarks that are detected by SDM. Depending upon the face velocity in consecutive video frames and face quality measure, two algorithms are proposed for correction of landmarks in low quality faces by using an extrapolation polynomial. Experimental results illustrate the competency of the proposed method while comparing with the state-of-the art methods including an SDM-based method (from CVPR-2013) and a very recent method (from CVPR-2014) that uses parallel cascade of linear regression (Par-CLR).
Cooperative distributed scheduling for ATS-based broadband networks

A proactive distributed cooperative control algorithm for resource scheduling of broadband networks based on asynchronous time sharing is presented. The problem setting for distributed, cooperative proactive scheduling is described. An overview of the distributed cooperative algorithm is presented. The general control principles underlying the effectiveness of the cooperative algorithm are discussed. The formal details of the distributed cooperative algorithm and its underlying single noise scheduling algorithm are considered. Simulation results comparing the distributed cooperative algorithm with other networkwide scheduling algorithms are reported. <<ETX>>
Can School League Tables Help Parents Choose Schools

Information on schools' performance is central to the school choice process in England. This paper evaluates school performance tables against criteria of functionality, relevance and comprehensibility. We estimate a model to judge functionality by setting up the following question: ‘In which feasible school will my child achieve the highest exam score? ’. We show that neither of the current leading performance measures scores very well. We propose an alternative measure which performs better on relevance and comprehensibility and not significantly worse on functionality. We demonstrate how the measure could be best delivered to parents. We also describe the trade-offs between the criteria of functionality and relevance and between comprehensibility and relevance.
Rethinking Muslim Women and the Veil: Challenging Historical & Modern Stereotypes

notion that the veil is a symbol of Muslim women’s oppression. In postulating a positive theory of the ^ij¥b the author challenges with great sophistication both the pop culture view of Muslim women as being utterly subjugated by men, as well as the more complex arguments put forward by liberal feminists such as Mernissi, Macleod and others who have sought to criticize women’s choices to cover as ultimately unliberating. Examining and questioning the validity and accuracy of some of the latter’s assumptions, the author puts forward the case that the judgment of the veil as being an oppressive feature of Islam is based on liberal understandings of ‘equality’ and ‘liberty’ that preclude other ways of thinking about ‘equality’ and ‘liberty’ that offer a positive approach for contemplating the wearing of the veil. The author argues that in a consumer capitalist culture, the ^ij¥b can be experienced as liberation from the tyranny of the beauty myth and the thin ‘ideal’ woman.
Array signal processing based on interference model with incomplete correlation matrix

Based on the model of interference with incomplete rank correlation matrix, a new method of signal processing in antenna arrays is proposed. Numerical simulation shows that the proposed method as applied to estimate the directions of arrival of a plane wave has the variance which is close to the Cramer-Rao lower bound. In the case when the distance and the direction of arrival are unknown, the proposed method has been shown to be more effective than known techniques such as Capon techniques of types I and II, the MUSIC technique. It has also been shown that the proposed technique can be used for effective estimation of the time waveform of the desired signal.
Polyalanine Repeat Polymorphism in RUNX2 Is Associated with Site-Specific Fracture in Post-Menopausal Females

Runt related transcription factor 2 (RUNX2) is a key regulator of osteoblast differentiation. Several variations within the RUNX2 gene have been found to be associated with significant changes in BMD, which is a major risk factor for fracture. In this study we report that an 18 bp deletion within the polyalanine tract (17A>11A) of RUNX2 is significantly associated with fracture. Carriers of the 11A allele were found to be nearly twice as likely to have sustained fracture. Within the fracture category, there was a significant tendency of 11A carriers to present with fractures of distal radius and bones of intramembranous origin compared to bones of endochondral origin (p = 0.0001). In a population of random subjects, the 11A allele was associated with decreased levels of serum collagen cross links (CTx, p = 0.01), suggesting decreased bone turnover. The transactivation function of the 11A allele showed a minor quantitative decrease. Interestingly, we found no effect of the 11A allele on BMD at multiple skeletal sites. These findings suggest that the 11A allele is a biologically relevant polymorphism that influences serum CTx and confers enhanced fracture risk in a site-selective manner related to intramembranous bone ossification.
Central Role of Hemocytes in Autographa californica M Nucleopolyhedrovirus Pathogenesis in Heliothis virescens and Helicoverpa zea

ABSTRACT Autographa californica M nucleopolyhedrovirus (AcMNPV) can infect and kill a wide range of larval lepidopteran hosts, but the dosage required to achieve mortal infection varies greatly. Using a reporter gene construct, we identified key differences between AcMNPV pathogenesis in Heliothis virescens and Helicoverpa zea, a fully permissive and a semipermissive host, respectively. Even though there was more than a 1,000-fold difference in the susceptibilities of these two species to mortal infection, there was no significant difference in their susceptibilities to primary infections in the midgut or secondary infections in the tracheal epidermis. Foci of infection within the tracheal epidermis of H. zea, however, were melanized and encapsulated by 48 h after oral inoculation, a host response not observed in H. virescens. Further, H. zeahemocytes, unlike those of H. virescens, were highly resistant to AcMNPV infection; reporter gene expression was observed only rarely even though virus was taken up readily, and nucleocapsids were transported to the nucleus. Collectively, these results demonstrated that hemocytes—by removing virus from the hemolymph instead of amplifying it and by participating in the encapsulation of infection foci—together with the host's melanization response, formed the basis of H. zea's resistance to fatal infection by AcMNPV.
Monetary Policy Forecasting In A Dsge Model With Data That Is Uncertain, Unbalanced And About The Future

If theory-consistent models can ever hope to forecast well and to be useful for policy, theyhave to relate to data which though rich in information is uncertain, unbalanced and sometimes forecastsfrom external sources about the future path of other variables. One example from many is financial marketdata, which can help but only after smoothing out irrelevant short-term volatility. In this paper we proposecombining different types of useful but awkward data set with a linearised forward-looking DSGE modelthrough a Kalman Filter fixed-interval smoother to improve the utility of these models as policy tools. Weapply this scheme to a model for Colombia.
The new similarity measure based on user preference models for collaborative filtering

The recommender system is widely used in many areas in the age of information overload. Collaborative filtering (CF), as one of the most successful methods used for recommendation, recommends items based on the nearest neighbors of the target user. Thus, the performance of the recommender system depends largely on the similarity measure used for selecting neighbors. Most of the traditional similarity measures are based on the rating data that users give to the items, such as Pearson's correlation and cosine, and suffer from low performances. In order to improve the performance of CF recommender system, this paper proposes a new kind of similarity measure based on user preference models and applies it to a movie recommender system. In this paper, two user preference models are build, one is focused on percentages of different movie genres a user has watched, the other is on the average ratings a user has given to different genres of movies. Based on the two user preference models, two new similarity measures are designed. The experiments compare the performance of the two new similarity measures with the Pearson's correlation which is widely used in the traditional CF, and are carried out on the MovieLens data set. The results show that the new similarity measure based on the watched genre ratio model outperforms that of traditional CF in all aspects. While the new similarity measure based on the average genre rating model has almost the same performance with the traditional one, but has much less computing complexity for no need in finding the co-rated items.
Coordination in P2P management overlays to improve decentralized detection of SLA violations

Critical networked services enable significant revenue for network operators and, in turn, are regulated by Service Level Agreements (SLAs). In order to ensure SLAs are being met, service levels need to be monitored. One technique for this involves active measurement mechanisms which employ measurement probes along the network to inject synthetic traffic and compute the network performance. However, these mechanisms are expensive in terms of resources consumption. Thus, active measurement mechanisms usually can cover only a fraction of what could be measured, which can lead to SLA violations being missed. Besides that, the definition of this fraction is a practice done by human administrators, which does not scale well and does not adapt to highly dynamic networking patterns. The contribution of the present work is the proposal of a solution to increase the potential number of detected SLA violations in which network devices autonomously and dynamically share service level measurement results. The sharing of these measurement results is based on the utilization of a Peer-to-Peer (P2P) management overlay built using past service level measurement results and a coordination strategy characterized by a high degree of decentralized decision making. The solution is evaluated using simulation and the results show its feasibility and interesting features.
Prescribing ex-ercise regimens for cardiac and pulmonary disease patients with cbr

This paper describes a prototypical system that employs case based reasoning to help sports medicine students learn to prescribe exercise regimens for cardiac and pulmonary disease patients Tradition ally students have been taught a manual rule based approach to se lecting workouts for these patients The training system produces two recommendations for each patient one based on the traditional rules and one based on experience with past patients In preliminary tests the case based recommendations more closely matched the exercise regimens prescribed for actual patients by experienced sports medicine profession als than the rule based recommendations
On defining sets of directed designs

The concept of defining set has been studied in block designs and, under the name critical sets, in Latin squares and Room squares. Here we study defining sets for directed designs. A t-(v, k, λ) directed design (DD) is a pair (V, B), where V is a v-set and B is a collection of ordered blocks (or k-tuples of V), for which each t-tuple of V appears in precisely λ blocks. A set of blocks which is a subset of a unique t-(v, k, λ)DD is said to be a defining set of the directed design. As in the case of block designs, finding defining sets seems to be a difficult problem. In this note we introduce some lower bounds for the number of blocks in smallest defining sets in directed designs, determine the precise number of blocks in smallest defining sets for some directed designs with small parameters and point out an open problem relating to the number of blocks needed to define a directed design as compared with the number needed to define its underlying undirected design.
SMARTbot: A Behavioral Analysis Framework Augmented with Machine Learning to Identify Mobile Botnet Applications

Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS), disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks’ back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps’ detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies.
Templated Synthesis of Magnetic Nanoparticles through the Self-Assembly of Polymers and Surfactants

The synthesis of superparamagnetic nanoparticles (NPs) for various technological applications continues to be an interesting research topic. The successful application of superparamagnetic NPs to each specific area typically depends on the achievement of high magnetization for the nanocrystals obtained, which is determined by their average size and size distribution. The size dispersity of magnetic NPs (MNPs) is markedly improved when, during the synthesis, the nucleation and growth steps of the reaction are well-separated. Tuning the nucleation process with the assistance of a hosting medium that encapsulates the precursors (such as self-assembled micelles), dispersing them in discrete compartments, improves control over particle formation. These inorganic-organic hybrids inherit properties from both the organic and the inorganic materials, while the organic component can also bring a specific functionality to the particles or prevent their aggregation in water. The general concept of interest in this review is that the shape and size of the synthesized MNPs can be controlled to some extent by the geometry and the size of the organic templates used, which thus can be considered as molds at the nanometer scale, for both porous continuous matrices and suspensions.