Miracle-dz/UniFAR-FTUs huggingface dataset:
Mining Complex Data Streams: Discretization, Attribute Selection and Classification

Due to the large volume of data set as well as complex and dynamic properties of data instances, several data mining algorithms have been applied for mining complex data streams in the last decades. Now a day, knowledge extraction from data streams is getting more complex because the structure of the data instance does not match the attribute values when considering the tabulated data, texts, web, images or videos etc. In this paper, we address some difficulties of mining complex data streams such as dealing with continuous attributes, input attribute selection, and classifier construction. The proposed discretization algorithm finds the possible cut points in continuous attributes using information gain heuristic and naive Bayesian classifier that can separate the class distributions. We evaluate the proposed algorithms on several benchmark data sets from UCI machine learning repository. The experimental results demonstrate that the proposed method improves the quality of discretization of continuous attributes and scales up the classification accuracy for different types of classification problem.
Relationship of Perceived Adequacy of Services, Family–Professional Partnerships, and Family Quality of Life in Early Childhood Service Programmes

This study applied three family measures (ratings of service adequacy or implementation, satisfaction with the family–professional partnership, and family quality of life) to a sample of families of young children in one Midwestern U.S. state. The results suggest that: (a) families more often believe they are receiving adequate amounts of services for their child, but tend to believe they are not receiving adequate amounts of services for their family; (b) respondents tend to be satisfied with their partnerships with their primary service provider, with lower satisfaction ratings for the provider's ability to meet their child's individual needs and to provide information about services; and (c) respondents tended to be more satisfied with their family's material well‐being and less so with their family's emotional well‐being. Finally, we found that service adequacy ratings were a significant predictor of family quality of life, and that partnerships partially mediated this effect. We discuss the research, service, and policy implications of these findings.
Shadow detection via Rayleigh scattering and Mie theory

In this paper, we present a method to detect shadows in outdoor scenes. Here, we note that the shadow areas correspond to the diffuse skylight which arises from the scattering of the sunlight by particles in the atmosphere. This yields a treatment in which shadows in the image can be viewed as a linear combination of scattered light obeying Rayleigh scattering and Mie theory. This treatment allows for the computation of a ratio which permits casting the problem of recovering the shadowed areas in the image into a clustering setting making use of active contours. We illustrate the utility of the method for purposes of detecting shadows in real-world imagery and compare our results against a number of alternatives elsewhere in the literature.
A unifying view on template protection schemes

We show that there is a direct relation between the maximum length keys extracted from biometric data and the error rates of the biometric system. This information can be used a-priori to evaluate the potential of the biometric data in the context of a specific cryptographic application. We model the biometric data more naturally as a continuous distribution and we give a new definition for the fuzzy extractor that works better for this type of data. We give three examples in this sense.
Stress Resistance, Adaptability, and Emotional Stability of Medical Students Obtaining Categories 4 and 5 on the Psychometric Test and Related Factors

Background: In its effort to produce high quality graduates, the Faculty of Medicine University of Indonesia administered psychological tests to assess first year medical students’ logical thinking skills and personality. The results of those tests are divided into 5 categories of recommendation, 1 to 5, based on the capability of the students to complete their studies. Fifty six point forty five percent of the students receiving recommendation categories 4 and 5, were considered as at-risk students who were predicted to have difficulties in completing their education. In addition, there were many non-academic factors that affect the learning process to achieve the clinical competence required by the Competence Standard for Indonesian Doctors. Research Objectives: to study the psychological profile of students in the at-risk category and related factors, in which could affect the learning process. Results: Using multivariable analysis, it was found that gender has a significant correlation to stress resistance and adaptability; motivation is significantly correlated to stress resistance and perseverance; whereas birth position has a significant correlation to stress resistance. Conclusion: the psychological profile of medical students including their work attitude and personality as well as other related factors can be used as predictors of success in completing their education. Thus, support and guidance for students should be made available as early as possible in their medical education, particularly for those students in the at-risk category, to help them achieve clinical competence.
Clinical Records Malignant otitis externa with optic neuritis

Malignant otitis externa is a serious condition that presents difficulties in treatment, and also in monitoring its progress. A case of malignant otitis externa with optic neuritis is presented that remained refractory to standard treatment but was cured by adjuvant hyperbaric oxygen therapy. This is the only reported case that has survived this disease with optic neuritis. The usefulness of imaging techniques in this condition is discussed, as well as the ESR, in evaluating the effectiveness of treatment.
Estimates of Marine Debris Accumulation on Beaches Are Strongly Affected by the Temporal Scale of Sampling

Marine debris is a global issue with impacts on marine organisms, ecological processes, aesthetics and economies. Consequently, there is increasing interest in quantifying the scale of the problem. Accumulation rates of debris on beaches have been advocated as a useful proxy for at-sea debris loads. However, here we show that past studies may have vastly underestimated the quantity of available debris because sampling was too infrequent. Our study of debris on a small beach in eastern Australia indicates that estimated daily accumulation rates decrease rapidly with increasing intervals between surveys, and the quantity of available debris is underestimated by 50% after only 3 days and by an order of magnitude after 1 month. As few past studies report sampling frequencies of less than a month, estimates of the scale of the marine debris problem need to be critically re-examined and scaled-up accordingly. These results reinforce similar, recent work advocating daily sampling as a standard approach for accurate quantification of available debris in coastal habitats. We outline an alternative approach whereby site-specific accumulation models are generated to correct bias when daily sampling is impractical.
Latin American Struggles| Student Online Video Activism and the Education Movement in Chile

In this article, we introduce and analyze two important cases of online video activism led by secondary and undergraduate students during the 2011 education movement in Chile. These video activism projects are analyzed using a methodology that combines interviews with several key informants and a review of their audiovisual production. Using a theoretical-conceptual approach to social appropriation of technologies and video activism, our research aims are to: (1) describe the experiences of online video activism by Chilean young people participating in the movement for a better public education and (2) characterize their appropriation of the audiovisual language within the technology and narrative of the Internet. We conclude that, in the Chilean context analyzed, online video activism takes place in two models according to the combination and use of different video formats.
Blockade of NMDA receptors decreased spinal microglia activation in bee venom induced acute inflammatory pain in rats

Abstract Objectives: Microglial cells in spinal dorsal horn can be activated by nociceptive stimuli and the activated microglial cells release various cytokines enhancing the nociceptive transmission. However, the mechanisms underlying the activation of spinal microglia during nociceptive stimuli have not been well understood. In order to define the role of NMDA receptors in the activation of spinal microglia during nociceptive stimuli, the present study was undertaken to investigate the effect of blockade of NMDA receptors on the spinal microglial activation induced by acute peripheral inflammatory pain in rats. Methods: The acute inflammatory pain was induced by subcutaneous bee venom injection to the plantar surface of hind paw of rats. Spontaneous pain behavior, thermal withdrawal latency and mechanical withdrawal threshold were rated. The expression of specific microglia marker CD11b/c was assayed by immunohistochemistry and western blot. Results: After bee venom treatment, it was found that rats produced a monophasic nociception characterized by constantly lifting and licking the injected hind paws, decreased thermal withdrawal latency and mechanical withdrawal threshold; immunohistochemistry displayed microglia with enlarged cell bodies, thickened, extended cellular processes with few ramifications, small spines, and intensive immunostaining; western blot showed upregulated expression level of CD11b/c within the period of hyperalgesia. Prior intrathecal injection of MK-801, a selective antagonist of NMDA receptors, attenuated the pain behaviors and suppressed up-regulation of CD11b/c induced by bee venom. Conclusion: It can be concluded that NMDA receptors take part in the mediation of spinal microglia activation in bee venom induced peripheral inflammatory pain and hyperalgesia in rats.
Modeling Uncertainties in EEG Microstates: Analysis of Real and Imagined Motor Movements Using Probabilistic Clustering-Driven Training of Probabilistic Neural Networks

Part of the process of EEG microstate estimation involves clustering EEG channel data at the global field power (GFP) maxima, very commonly using a modified K-means approach. Clustering has also been done deterministically, despite there being uncertainties in multiple stages of the microstate analysis, including the GFP peak definition, the clustering itself and in the post-clustering assignment of microstates back onto the EEG timecourse of interest. We perform a fully probabilistic microstate clustering and labeling, to account for these sources of uncertainty using the closest probabilistic analog to KM called Fuzzy C-means (FCM). We train softmax multi-layer perceptrons (MLPs) using the KM and FCM-inferred cluster assignments as target labels, to then allow for probabilistic labeling of the full EEG data instead of the usual correlation-based deterministic microstate label assignment typically used. We assess the merits of the probabilistic analysis vs. the deterministic approaches in EEG data recorded while participants perform real or imagined motor movements from a publicly available data set of 109 subjects. Though FCM group template maps that are almost topographically identical to KM were found, there is considerable uncertainty in the subsequent assignment of microstate labels. In general, imagined motor movements are less predictable on a time point-by-time point basis, possibly reflecting the more exploratory nature of the brain state during imagined, compared to during real motor movements. We find that some relationships may be more evident using FCM than using KM and propose that future microstate analysis should preferably be performed probabilistically rather than deterministically, especially in situations such as with brain computer interfaces, where both training and applying models of microstates need to account for uncertainty. Probabilistic neural network-driven microstate assignment has a number of advantages that we have discussed, which are likely to be further developed and exploited in future studies. In conclusion, probabilistic clustering and a probabilistic neural network-driven approach to microstate analysis is likely to better model and reveal details and the variability hidden in current deterministic and binarized microstate assignment and analyses.
IMPLEMENTATION OF P 2 P REPUTATION MANAGEMENT SCHEME BASED ON DISTRIBUTED IDENTITIES AND DECENTRALIZED RECOMMENDATION CHAINS BAJI SHAHEED

The motivation behind basing applications on peer-to-peer architectures derives to a large extent from their ability to function, scale and self-organize in the presence of a highly transient population of nodes, network and computer failures, without the need of a central server and the overhead of its administration. P2P networks are vulnerable to peers, who cheat, propagate malicious codes, or peers who do not cooperate. Traditional client-server security models are not sufficient to P2P networks because of their centralized nature. To full fill this ,in this paper we present a cryptographic protocol for ensuring secure and timely availability of the reputation data of a peer extremely at low cost and develop a queuing model to evaluate the time required at each peer to serve its replication requests.
Resilience of mutual exclusion algorithms to transient memory faults

We study the behavior of mutual exclusion algorithms in the presence of unreliable shared memory subject to transient memory faults. It is well-known that classical 2-process mutual exclusion algorithms, such as Dekker and Peterson's algorithms, are not fault-tolerant; in this paper we ask what degree of fault tolerance can be achieved using the same restricted resources as Dekker and Peterson's algorithms, namely, three binary read/write registers. We show that if one memory fault can occur, it is not possible to guarantee both mutual exclusion and deadlock-freedom using three binary registers; this holds in general when fewer than 2f+1 binary registers are used and f may be faulty. Hence we focus on algorithms that guarantee (a) mutual exclusion and starvation-freedom in fault-free executions, and (b) only mutual exclusion in faulty executions. We show that using only three binary registers it is possible to design an 2-process mutual exclusion algorithm which tolerates a single memory fault in this manner. Further, by replacing one read/write register with a test&set register, we can guarantee mutual exclusion in executions where one variable experiences unboundedly many faults. In the more general setting where up to f registers may be faulty, we show that it is not possible to guarantee mutual exclusion using 2f + 1 binary read/write registers if each faulty register can exhibit unboundedly many faults. On the positive side, we show that an n-variable single-fault tolerant algorithm satisfying certain conditions can be transformed into an ((n-1)f + 1)-variable f-fault tolerant algorithm with the same progress guarantee as the original. In combination with our three-variable algorithm, this implies that there is a (2f+1)-variable mutual exclusion algorithm tolerating a single fault in up to f variables without violating mutual exclusion.
The Armada framework for parallel I/O on computational grids

An exciting trend in high-performance distributed computing is the development of widely-distributed networks of heterogeneous systems and devices, known as computational grids. Grid applications use high-speed networks to logically assemble collections of resources such as scientific instruments, supercomputers, databases, and so forth. One important challenge facing grid computing is efficient parallel I/O for data-intensive grid applications. Data-intensive grid applications are particularly challenging because they require access to large (terabyte-petabyte) remote data sets and often have computational requirements that can only be met by high-performance supercomputers. In addition, data is often stored in “raw” formats and requires significant preprocessing or filtering before the computation can take place. Such applications exist in seismic processing, climate modeling, physics, astronomy, biology, chemistry, and visualization. In this report, we present the Armada framework [OK01] for building I/O-access paths for data-intensive grid applications. We designed Armada to allow grid applications to efficiently access data sets distributed across a computational grid, and in particular to allow the application programmer and the dataset provider to design and deploy a flexible network of application-specific and dataset-specific functionality across the grid. Using the Armada framework, grid applications access remote data sets by sending data requests through a graph of distributed application objects. The graph is called an “armada” and the objects are called “ships”. Figure 1 shows a simple armada for an application accessing applying a preprocessing operator to a distributed data set. We expect most applications to access data through existing armadas constructed by a data set provider; however, it is also possible for the application to extend existing armadas with applicationspecific functionality or to construct entire armadas from scratch. The armada encodes the programmer’s interface, data layout, caching and prefetching policies, interfaces to heterogeneous data servers, and most other functionality provided by an I/O system. The application sees an armada as an object providing access to a specific type of data through a high-level interface. One use of Armada, for example, is to construct complicated data sets on top of legacy files and databases. API storage
Scoliosis screening.

The term "scoliosis" orginates from the Greek word meaning crooked, and involves lateral curvature and rotation of the spine. Although it can span all age groups, the deformity is most frequently seen in normal, rapidly growing, preadolescent or adolescent children. Because most of the serious consequences of scoliosis can be prevented, it is a deformity particularly amenable to early diangosis and proper treatment. It is therefore important that the health care community and general public be knowledgeable about the deformity; that screening programs be promoted in every locality; and that pediatricians focus particular attention on the spine during the adolescent growth spurt.
A multi-scale learning approach for landmark recognition using mobile devices

The growing usage of mobile camera phones has led to proliferation of many mobile applications. Landmark recognition is one of the mobile applications that are gaining more attention in recent years. The main idea of the application is that a user will use a camera phone to capture the image of a landmark or building and then the system will analyze, identify, and inform the user the name of the captured landmark together with its related information. A new mobile landmark recognition method is proposed in this paper: first, a set of multi-scale patches are extracted from the landmark images. Discriminative patches of the images are then selected based on a Gaussian mixture model (GMM). A combination of color, texture and scale-invariant feature transform (SIFT) descriptors are then extracted from the selected patches. They are used to train support vector machine (SVM) classifiers for each category of landmark. Experimental results using a database of 4000 landmark images illustrate the effectiveness of the proposed method.
Firm performance through social Customer Relationship Management: Evidence from small and medium enterprises

The objective of this study is to investigate the effect of social customer relationship management (CRM) adoption on firm performance in small and medium enterprises (SMEs) context. Accordingly, we develop a new adoption-performance model for social CRM strategy at the organization level. The proposed model of this study links technological, organizational, environmental and process factors to social CRM adoption and performance. The proposed hypotheses were verified by using structural equation modeling on a dataset of 240 SMEs across Kuala Lumper, the capital city of Malaysia. The results revealed that top management support, IT/IS knowledge of employee, cost, relative advantage, compatibility, customer pressure and competitive pressure are important drivers for social CRM adoption. Finally, this study confirms that there is a significant relationship between social CRM adoption and SMEs performance.
On fixed-database universal data compression with limited memory

The amount of fixed side information required for lossless data compression is discussed. Nonasymptotic coding and converse theorems are derived for data-compression algorithms with fixed statistical side information ("training sequence") that is not large enough so as to yield the ultimate compression, namely, the entropy of the source.
Large chiro-optical effect in stacked chiral metamaterials

Plasmonic nanostructures in chiral geometries are suitable candidates for various device applications pertaining to optical polarization. These devices can show large chiro-optical effects, implying a strongly differential response to right and left circularly polarized light. In general, three-dimensional plasmonic structures show larger optical activity, but are typically not suitable for wafer-scale fabrication. As an alternate strategy, we have considered the optical response of stacked planar chiral geometries, which were found to exhibit very large chiro-optical response. Further, the plasmonic chirality of such stacked metamaterials can be tuned in the visible, by simply varying the thickness of the stack. This novel design of layered achiral metamaterials will be easier to fabricate than standard three dimensional geometries, and is suitable for various photonic device applications requiring polarization control.