Miracle-dz/UniFAR-FTUs huggingface dataset:
Data Mining Using Genetic Algorithm ( DMUGA )

In this paper the Genetic Algorithm has been used to mine the real world dataset in medical domain. The growth of information has proceeded at an explosive rate in recent years. The size of data available now is beyond the capability of our mind to analyze. Due to the size of the data, it is extremely difficult to draw meaningful conclusions about the data. To overcome the above scenario, data mining technology is introduced. In fact we are busy with data in most fields and not concerned about hidden patterns. To a certain extent, there are not enough qualified human analysts available who are expert at translating all of this data into knowledge and find the interesting patterns. Data Mining is a process that starts with data and ends with previously unknown patterns and knowledge. The Knowledge Discovery in Databases (KDD) process will be used and on the data mining stage the GA is applied in this paper. This series of activities is divided into five steps. The raw data is selected and analysed during the steps to reveal patterns and create new knowledge. The KDD will include several steps including Selection, Pre-processing, Transformation, Data Mining and Interpretation of pattern.
Improving Sentiment Classification Using Feature Highlighting and Feature Bagging

Sentiment classification is an important data mining task. Previous researches tried various machine learning techniques while didn't make fully use of the difference among features. This paper proposes a novel method for improving sentiment classification by fully exploring the different contribution of features. The method consists of two parts. First, we highlight sentimental features by increasing their weight. Second, we use bagging to construct multiple classifiers on different feature spaces and combine them into an aggregating classifier. Extensive experiments show that the method can evidently improve the performance of sentiment classification.
Evaluating image segmentation algorithms using monotonic hulls in fitness/cost space

Image segmentation is the first stage of processing in many practical computer vision systems. While development of particular segmentation algorithms has attracted considerable research interest, relatively little work has been published on the subject of their evaluation. In this paper we propose a framework for quantitative evaluation of segmentation algorithms which we believe addresses shortcomings of previous approaches, and use this framework to compare several state-of-the-art algorithms.
A selective checkpointing mechanism for query plans in a parallel database system

Most existing parallel database systems achieve fault tolerance by aborting unfinished queries upon a failure and restart the entire from the beginning. This is inefficient for long running queries of OLAP workloads. To solve this problem, this paper presents a selective checkpointing mechanism which materializes the outputs of some necessary operators, enabling to resume queries from middle of the execution upon failures. Each query is represented by a DAG of relational operators in which data are typically pipelined between operators. The goal of the mechanism is to find a set of operators whose outputs are worth being checkpointed to minimize the expected runtime of the whole query. It firstly provides a cost model to estimate the expected runtime of a whole query plan under a given failure probability for each operator. Then a divide-and-conquer algorithm is proposed to find a close-to-optimal solution to the problem. The algorithm divides the query plan into subplans with smaller search spaces. For a given query plan with n operators, the algorithm runs in O(n) time. The mechanism is implemented in a shared-nothing parallel database system called ParaLite which provides a coordination layer to glue many SQLite instances together, and parallelizes SQL queries across them. The experimental results indicate that different fault-tolerant strategies affect the overall runtimes of queries. Our selective checkpointing mechanism can choose reasonable operators to be checkpointed and outperforms other fault-tolerant strategies. In addition, the divide-and-conquer algorithm taken by our mechanism has a smaller overhead than brute-force approach while keeping a similar effectiveness.
Three-dimensional modeling of tongue during speech using MRI data

1. ABSTRACT The t ongue is the most important and dynamic articulator for speech formation, because of its anatomic aspects (particularly, the large volume of this muscular organ comparatively to the surrounding organs of the vocal tract) and also due to the wide range of movements and flexibility that are involved. In speech communication research, a variety of techniques have been used for measuring the three-dimensional vocal tract shapes. More recently, magnetic resonance imaging (MRI) becomes common; mainly, because this technique allows the collection of a set of static and dynamic images that can represent the entire vocal tract along any orientation. Over the years, different anatomical organs of the vocal tract have been modelled; namely, 2D and 3D tongue models, using parametric or statistical modelling procedures. Our aims are to present and describe some 3D reconstructed models from MRI data, for one subject uttering sustained articulations of some typical Portuguese sounds. Thus, we present a 3D database of the tongue obtained by stack combinations with the subject articulating Portuguese vowels. This 3D knowledge of the speech organs could be very important; especially, for clinical purposes (for example, for the assessment of articulatory impairments followed by tongue surgery in speech rehabilitation), and also for a better understanding of acoustic theory in speech formation.
A Query-Reply System Based on a Modular Bayesian Neural Network

This Masters project treats a query-reply system based on a modularized version of the Bayesian confidence propagation network (BCPNN). The theoretical basis for the BCPNN is reviewed, as well as the fundamentals of query-reply systems. A query-reply system is developed on top of an already existing Java code for the BCPNN, and the implemented system is tested on several data sets. The modular version of the BCPNN improves performance of the query-reply system considerably, and the use of a hidden layer of merged features can enhance performance even more. It appears particularly favorable to merge all features into a grandmother cell or, if only two features are to be merged, to merge independent ones. On the other hand merging features with high mutual information, i.e. high dependency, worsens performance of the system. When erroneous or uncertain answers are provided the hit rates fall and the number of questions needed for a classification increase as expected.ten minskar.
Iterative Helical CT Reconstruction in the Cloud for Ten Dollars in Five Minutes

Iterative statistical X-ray CT reconstruction algorithms can improve image quality for low dose scans. Unfortunately, their clinical utility has been hampered by their enormous computational requirements; typical low-dose reconstructions require about an hour on commercial systems. Most existing parallel implementations use a shared memory programming model, limiting available parallelism. We investigate using a large compute cluster for a penalized weighted least-squares algorithm using ordered subsets (PWLS-OS), scaled to hundreds of cores to accelerate a single helical CT reconstruction problem. Using Amazon’s Elastic Cloud Compute (EC2) service, our experimental results show that a typical helical chest scan can be reconstructed in under five minutes at a cost under $10.
Galileon Cosmology

We study the cosmology of a galileon scalar-tensor theory, obtained by covariantizing the decoupling lagrangian of the Dvali-Gabadadze-Poratti (DGP) model. Despite being local in 3+1 dimensions, the resulting cosmological evolution is remarkably similar to that of the full 4+1-dimensional DGP framework, both for the expansion history and the evolution of density perturbations. As in the DGP model, the covariant galileon theory yields two branches of solutions, depending on the sign of the galileon velocity. Perturbations are stable on one branch and ghost-like on the other. An interesting effect uncovered in our analysis is a cosmological version of the Vainshtein screening mechanism: at early times, the galileon dynamics are dominated by self-interaction terms, resulting in its energy density being suppressed compared to matter or radiation; once the matter density has redshifted sufficiently, the galileon becomes an important component of the energy density and contributes to dark energy. We estimate conservatively that the resulting expansion history is consistent with the observed late-time cosmology, provided that the scale of modification satisfies rc ∼> 15 Gpc. lchow@sas.upenn. edu jkhoury@sas.upenn. edu ar X iv :0 90 5. 13 25 v4 [ he pth ] 2 2 Ju l 2 00 9
Converting a tetrahedral mesh to a prism-tetrahedral hybrid mesh for FEM accuracy and efficiency

This paper presents a computational method for converting a tetrahedral mesh to a prism-tetrahedral hybrid mesh for improved solution accuracy and computational efficiency of finite element analysis. The proposed method inserts layers of prism elements and deletes tetrahedral elements in sweepable sub-domains, in which cross-sections remain topologically identical and geometrically similar along a certain sweeping path. The total number of finite elements is reduced because roughly three tetrahedral elements are converted to one prism element. The solution accuracy of the finite element analysis improves since a prism element yields a more accurate solution than a tetrahedral element. Only previously known method for creating such a prism-tetrahedral mesh was to manually decompose a target volume into sweepable and non-sweepable sub-volumes and mesh each sub-volume separately. The proposed method starts from a cross-section of a tetrahedral mesh and replaces the tetrahedral elements with layers of prism elements until prescribed quality criteria can no longer be satisfied. The method applies a sequence of edge-collapse, local-transformation, and smoothing operations to remove or displace nodes located within the volume to be replaced with a layer of prism elements. Series of computational fluid dynamics simulations and structural analyses have been conducted, and the results verified a better performance of prismtetrahedral hybrid mesh in finite element simulations.
Law Students’ Judgments of a Rape Victim’s Statement: The Role of Displays of Emotion and Acceptance of Sexual Aggression Myths

Female rape victims who display “appropriate” emotions (versus “inappropriate” or no emotions) are often judged to be more credible. The authors studied the interplay of different emotion displays with perceivers’ acceptance of modern myths about sexual aggression (AMMSA) in predicting judgments of credibility and blame. Law students (N = 120) completed a 16-item AMMSA scale and watched a video showing a simulated interview with a rape victim (played by an actress). The emotion displayed by the victim (sad, angry, or neutral) was experimentally manipulated; her statement’s verbal content was held constant. Main dependent variables were perceived victim credibility, victim blame, severity of the injury, and likelihood of recovery. Results showed that AMMSA strongly predicted all dependent variables across conditions. Effects of displayed emotions were less pervasive and depended on participants’ gender and AMMSA: At higher (vs. lower) levels of AMMSA, women – but not men – judged the sad victim’s statement to be most credible, and the angry victim’s statement to be least credible, with the neutral statement falling in between. The findings suggest that perceivers may be better at keeping their judgements free from unwanted external influences (the emotional displays) than unwanted internal influences (their own AMMSA). The authors discuss future directions regarding the mechanisms involved and practical implications for the legal context.
HarvOS: Efficient Code Instrumentation for Transiently-Powered Embedded Sensing

We present code instrumentation strategies to allow transiently-powered embedded sensing devices efficiently checkpoint the system’s state before energy is exhausted. Our solution, called HarvOS, operates at compile-time with limited developer intervention based on the control-flow graph of a program, while adapting to varying levels of remaining energy and possible program executions at run-time. In addition, the underlying design rationale allows the system to spare the energy-intensive probing of the energy buffer whenever possible. Compared to existing approaches, our evaluation indicates that HarvOS allows transiently-powered devices to complete a given workload with 68% fewer checkpoints, on average. Moreover, our performance in the number of required checkpoints rests only 19% far from that of an “oracle” that represents an ideal solution, yet unfeasible in practice, that knows exactly the last point in time when to checkpoint.
Two new intermediate polars with a soft X-ray component

Aims. We analyze the first X-ray observations with XMM-Newton of 1RXS J070407.9+262501 and 1RXS 180340.0+401214, in order to characterize their broad-band temporal and spectral properties, also in the UV/optical domain, and to confirm them as intermediate polars. Methods. For both objects, we performed a timing analysis of the X-ray and UV/optical light curves to detect the white dwarf spin pulsations and study their energy dependence. For 1RXS 180340.0+401214 we also analyzed optical spectroscopic data to determine the orbital period. X-ray spectra were analyzed in the 0.2–10.0 keV range to characterize the emission properties of both sources. Results. We find that the X-ray light curves of both systems are energy dependent and are dominated, below 3–5 keV, by strong pulsations at the white dwarf rotational periods (480 s for 1RXS J070407.9+262501 and 1520.5 s for 1RXS 180340.0+401214). In 1RXS 180340.0+401214 we also detect an X-ray beat variability at 1697 s which, together with our new optical spectroscopy, favours an orbital period of 4.4 h that is longer than previously estimated. Both systems show complex spectra with a hard (temperature up to 40 keV) optically thin and a soft (kT ∼ 85–100 eV) optically thick components heavily absorbed by material partially covering the X-ray sources. Conclusions. Our observations confirm the two systems as intermediate polars and also add them as new members of the growing group of “soft” systems which show the presence of a soft X-ray blackbody component. Differences in the temperatures of the blackbodies are qualitatively explained in terms of reprocessing over different sizes of the white dwarf spot. We suggest that systems showing cooler soft X-ray blackbody components also possess white dwarfs irradiated by cyclotron radiation.
Neural Networks Elitist Evolution

This paper presents an elitist evolving strategy, which allows obtaining a controller, based on a neural network capable of commanding an autonomous robot. In order to reduce the detrimental crossover effect, we propose to use a strategy to create several children for each parent pair, selecting properly the way of making the replacement. The results obtained show that, though the number of children is high, the quantity of fitness tests carried out is actually lower than that of a conventional evolving algorithm. In this way, we propose an alternative that reduces the computational cost of the process, reaching at a suitable response for the problem resolution.
Explore and Model Better I-Frames for Video Coding

In video coding, an intra (I)-frame is used as an anchor frame for referencing the subsequence frames, as well as error propagation prevention, indexing, and so on. To get better rate-distortion performance, a frame should have the following quality to be an ideal I-frame: the best similarity with the frames in a group of picture (GOP), so that when it is used as a reference frame for a frame in the GOP we need the least bits to achieve the desired image quality, minimize the temporal fluctuation of quality, and also maintain a more consistent bit count per frame. In this paper we use a most common frame of a scene in a video sequence with dynamic background modeling and then encode it to replace the conventional I-frame. The extensive experimental results confirm the superiority of our proposed scheme in comparison with the existing state-of-art methods by significant image quality improvement and computational time reduction.
Improving Chinese Chunking with Enriched Statistical and Morphological Knowledge

In this paper, we address the issue of improving a Chinese chunking system with rich lexicalized information. A method that incorporates statistical information based on distributional similarity between words obtained from large unlabeled corpus and morphological knowledge into a state-of-the-art CRF-based chunking model is proposed to tackle the data sparseness problem given limited amount of labeled training data. Evaluations are performed on the latest release of Chinese Treebank, and experimental results show that our method outperforms the chunking models based on features over word and automatically assigned POS tags when using the same amount of training data.
Emergence, a Universal Phenomenon which Connects Reality to Consciousness, Natural Sciences to Humanities

Abstract Progress in neuroscience has left a central question of psychism unanswered: what is consciousness? Modeling the psyche from a computational perspective has helped to develop cognitive neurosciences, but it has also shown their limits, of which the definition, description and functioning of consciousness remain essential. From Rene Descartes, who tackled the issue of psychism as the brain-mind dualism, to Chambers, who defined qualia as the tough, difficult problem of research in neuroscience, many hypotheses and theories have been issued to encompass the phenomenon of consciousness. Neuroscience specialists, such as Giulio Tononi or David Eagleman, consider consciousness as a phenomenon of emergence of all processes that take place in the brain. This hypothesis has the advantage of being supported by progress made in the study of complex systems in which the issue of emergence can be mathematically formalized and analyzed by physical-mathematical models. The current tendency to associate neural networks within the broad scope of network science also allows for a physical-mathematical formalization of phenomenology in neural networks and the construction of information-symbolic models. The extrapolation of emergence at the level of physical systems, biological systems and psychic systems can bring new models that can also be applied to the concept of consciousness. The meaning and significance that seem to structure the nature of consciousness is found as direction of evolution and teleological finality, of integration in the whole system and in any complex system at all scales. Starting from the wave-corpuscle duality in quantum physics, we can propose a model for structuring reality, based on the emergence of systems that contribute to the integration and coherence of the entire reality. Physical-mathematical models based mainly on (mereo)topology can provide a mathematical formalization path, and the paradigm of information could allow the development of a pattern of emergence, that is common to all systems, including the psychic system, the difference being given only by the degree of information complexity. Thus, the mind-brain duality, which has been dominating the representation on psychism for a few centuries, could be solved by an informational approach, describing the connection between object and subject, reality and human consciousness, between mind and brain, thus unifying the perspective on natural sciences and humanities.
Repeated Episodes of Hypoglycemia as a Potential Aggravating Factor for Preclinical Atherosclerosis in Subjects With Type 1 Diabetes

OBJECTIVE To evaluate through early preclinical atherosclerosis assessment whether repeated episodes of hypoglycemia represent an aggravating factor for macrovascular disease in type 1 diabetes. RESEARCH DESIGN AND METHODS After sample-size calculation, a case-control study of 25 patients with type 1 diabetes and repeated severe/nonsevere hypoglycemia (H-group) compared with 20 age- and sex-matched type 1 diabetes control subjects (C-group) was designed. Assessment of preclinical atherosclerosis consisted of flow-mediated brachial dilatation (FMD) and carotid and femoral intima-media thickness (IMT) studies. To consider hypoglycemia awareness, two different questionnaires and symptomatic response to an acute induction to hypoglycemia were used. Evaluation of the glycemic profile was obtained from continuous glucose monitoring. Endothelial function/inflammation markers were measured in euglycemia/hypoglycemia. A multivariate linear regression analysis was performed to test whether repeated hypoglycemia was independently associated with atherosclerosis. RESULTS H-group subjects displayed hypoglycemia unawareness and presented a higher percentage of continuous glucose values and area under the curve <70 mg/dl compared with the C-group (14.2 ± 8.9 vs. 6.3 ± 7.1%, P < 0.02 and 2.4 ± 1.8 vs. 0.6 ± 1.0 mg/dl/day, P < 0.01). The percentage of maximal FMD was lower in the H-group than in the C-group (6.52 ± 2.92 vs. 8.62 ± 3.13%, P < 0.05). A significantly higher IMT was observed at both carotid and femoral sites in the H-group (carotid 0.53 ± 0.09 vs. 0.47 ± 0.08 mm, P < 0.05 and femoral 0.51 ± 0.17 vs. 0.39 ± 0.09 mm, P < 0.05). Baseline inflammation and endothelial function markers were higher in the H-group (leukocytes 7.0 ± 1.8 vs. 5.6 ± 1.4 × 103/ml, von Willebrand factor 119 ± 29 vs. 93 ± 26%, fibrinogen 2.82 ± 0.64 vs. 2.29 ± 0.44g/l, and soluble intercellular adhesion molecule-1 408 ± 224 vs. 296 ± 95 ng/ml; P < 0.05 for all). CONCLUSIONS In addition to the induction of hypoglycemia unawareness and an increased risk for severe hypoglycemia, repeated hypoglycemia could be related to and considered an aggravating factor for preclinical atherosclerosis in type 1 diabetes. The precise mechanisms explaining this association remain to be clarified.
The impact of early bilingualism on controlling a language learned late: an ERP study

This study asks whether early bilingual speakers who have already developed a language control mechanism to handle two languages control a dominant and a late acquired language in the same way as late bilingual speakers. We therefore, compared event-related potentials in a language switching task in two groups of participants switching between a dominant (L1) and a weak late acquired language (L3). Early bilingual late learners of an L3 showed a different ERP pattern (larger N2 mean amplitude) as late bilingual late learners of an L3. Even though the relative strength of languages was similar in both groups (a dominant and a weak late acquired language), they controlled their language output in a different manner. Moreover, the N2 was similar in two groups of early bilinguals tested in languages of different strength. We conclude that early bilingual learners of an L3 do not control languages in the same way as late bilingual L3 learners –who have not achieved native-like proficiency in their L2– do. This difference might explain some of the advantages early bilinguals have when learning new languages.