Miracle-dz/UniFAR-FTUs huggingface dataset:
Image Mosaicing using Harris, SIFT Feature Detection Algorithm

Image Mosaicing has wide applications in the field of 3D image reconstruction, medical imaging, military automatic target recognition, video conferencing, and data from satellites. An Image Mosaicing is a method of assembling multiple overlapping images of the same scene into a larger image. The input images are stitched together using image mosaicing algorithms i.e. Harris and SIFT (Scale Invariant Feature Transform). In this paper, a comparative study is done among the common stitching algorithms: Harris corner detection algorithm, SIFT algorithm. The principles of these algorithms are described in terms of computing time and stitching precision. Harris algorithm detects more features and is only rotationally invariant. SIFT is both rotationally and scale invariant, although it is slow. Harris corner detection algorithm (5) was proposed by Harris C and Stephens MJ in the year 1988. Harris algorithm is a point feature extracting algorithm based on Moravec algorithm. It is an algorithm based on still image used for combined corner and edge detector. Reasonable amount of corner features are extracted which gives a better quantitative measurement by using a stable operator. A local detecting window in image is designed. The average variation in intensity is determined by shifting the window by a small amount in different direction. The centre point of the window is extracted as corner point. The point can be recognized easily by looking at the intensity values within a small window. Shifting the window in any direction gives a large change in appearance. Harris corner detector is used for detecting corners. On shifting the window if it's a flat region than it will show no change of intensity in all direction. If an edge region is found than it will show no change of intensity along the edge direction. But if a corner is found than there will be a significant change of intensity in all directions. Harris corner detector gives a mathematical approach for determining the region is flat, edge or corner. Harris corner technique detects more features and it is rotational invariant and scale variant. Harris gave a formula that can be calculated out the change of the pixel values in any direction, rather than fixed in the 8 directions.
Correcting Interaction Mismatches for Business Processes

Discovering and correcting interaction mismatches in inter-organizational business processes are important for service choreography. Automatic discovery mismatches and providing correcting plans will alleviate burdens on business modelers, however, three major challenges are: 1) by what cost model to evaluate multiple correcting plans; 2) how to avoid generating new mismatches when correcting processses;3) how to effectively reduce the search space size. In this paper, we first extend our previous approach to discover interaction mismatches, and present a cost model for evaluating correcting plans; secondly, we propose an independent modifying region-based method to obtain multiple correcting plans which can avoid generating new mismatches, and reduce the search space for finding out correcting plans. A running example is given to illustrate the validity.
Automobile driver's stress index provision system that utilizes electrocardiogram

This research intends to develop devices that make drivers rest and to verify in the early stage by effectively detecting the electrocardiogram (ECG) signal, one of the signals of living body, in the vehicle during the operation and providing ANS information and degree of stress. Recording the regular activity of heart clinically, ECG reflects the health state of subject as well as checks the degree of operation of autonomic nervous system through analysis of Heart Rate Variability (HRV). As this alteration of autonomic nervous system predicts the stress level of drivers during operation and provides the possibility of warning by continuous detection, it may lead to the recognition and safe driving of driver by detecting the stress during driving altered by diverse factors such as changing mood, bio rhythm, condition, fatigue, boredom or disease and preventing the driver from reaching the inappropriate state for driving. Thus, the reliability and utilization level of system was confirmed to be satisfactory by providing new ECG measuring method familiar to drivers and comparing it with the result of judging drivers' emotion through this research.
Knowledge Sharing Behavior in Organization: An Empirical Investigation

Effective knowledge sharing cannot be forced or mandated. Organizations desiring to institutionalize knowledge sharing behaviors must foster facilitative work context. The aim of this paper is to develop a deeper understanding of the factors inhibiting individuals' knowledge sharing intentions, and suggest a method to shape appropriate work context. To reach this goal, this paper focus on the inner knowledge externalization process, and formulate a research model which integrate self-concept-based model and theory of reasoned action to explain how contextual forces can transform into the triggers of inner motivations. Using the Structural Equation Modeling (SEM) method, data analysis showed that most of the research hypotheses were supported. The research findings show that the firm should (1) make the employees regard knowledge sharing as an enjoyment; (2) enforce their sense of belonging ; (3) induce employees' focus on long term return rather than shore term wins; (4) leverage centrality and promote individual reputations may also be helpful.
Randomized Algorithmic Approach for Biclustering of Gene Expression Data

Microarray data processing revolves around the pivotal issue of locating genes altering their expression in response to pathogens, other organisms or other multiple environmental conditions resulted out of a comparison between infected and uninfected cells or tissues. To have a comprehensive analysis of the corollaries of certain treatments, deseases and developmental stages embodied as a data matrix on gene expression data is possible through simultaneous observation and monitoring of the expression levels of multiple genes. Clustering is the mechanism of grouping genes into clusters based on different parameters. Clustering is the process of grouping genes into clusters either considering row at a time(row clustering) or considering column at a time(column clustering). The application of clustering approach is crippled by conditions which are unrelated to genes. To get better of these problems a unique form of clustering technique has evolved which offers simultaneous clustering (both rows and columns) which is known as biclustering. A bicluster is deemed to be a sub matrix consisting data values. A bicluster is resulted out of the removal of some of the rows as well as some of the columns of given data matrix in such a fashion that each row of what is left reads the same string. A fast, simple and efficient randomized algorithm is explored in this paper, which discovers the largest bicluster by random projections.
Economic Harmony: An Epistemic Theory of Economic Interactions

We propose an epistemic theory of micro-economic interactions, termed Economic Harmony. In the theory, we modify the standard utility, by changing its argument from the player’s actual payoff, to the ratio between the player’s actual payoff and his or her aspired payoff. We show that the aforementioned minor epistemic modification of the concept of utility is quite powerful in generating plausible and successful predictions of experimental results, obtained in the standard ultimatum game, and the sequential common pool resource dilemma (CPR) game. Notably, the cooperation and fairness observed in the studied games are accounted for without adding an other-regarding component in the players’ utility functions. For the standard ultimatum game, the theory predicts a division of φ and 1 − φ, for the proposer and responder, respectively, where φ is the famous Golden Ratio (≈0.618), most known for its aesthetically pleasing properties. We discuss possible extensions of the proposed theory to repeated and evolutionary ultimatum games.
Entry Criteria and Baseline Characteristics Predict Outcome in Acute Stroke Trials

Background and Purpose— We sought to study the range of entry criteria and baseline characteristics in acute stroke trials and to understand their effects on patient outcomes. Methods— Randomized, placebo-controlled therapeutic trials in patients with acute ischemic stroke were identified. Entry criteria, baseline clinical characteristics, and outcome were extracted for the placebo group of each trial. The relationship between key variables was then determined. Results— Across 90 placebo groups identified, there was great variation in entry criteria and outcome measures. This was associated with divergent outcomes; for example, in some studies most placebo group patients died, while in other studies nearly all had no disability. Entry criteria were significantly correlated with outcome; for example, higher age cutoff for study entry correlated with 3-month mortality. Entry criteria also predicted baseline clinical characteristics; for example, wider time window for study entry correlated directly with time to treatment and inversely with stroke severity (initial National Institutes of Health Stroke Scale score). Baseline characteristics predicted outcome. Greater stroke severity predicted higher 3-month mortality rate; despite this, successful thrombolytic trials have enrolled more severe strokes than most trials. The mean age of enrollees also predicted 3-month mortality and was inversely related to percentage of patients with 3-month Barthel Index score ≥95. The strongest predictors of 3-month mortality were obtained with multivariate models. Conclusions— Acute stroke studies vary widely in entry criteria and outcome measures. Across multiple studies, differences in entry criteria, and the baseline clinical characteristics they predict, influence patient outcomes along a continuum. In some studies, enrolling a specific subset of patients may have improved the chances of identifying a treatment-related effect, while in others, such chances may have been reduced. These findings may be useful in the design of future stroke therapeutic trials.
Implanted Ventricular Shunts in the United States: The Billion-dollar-a-year Cost of Hydrocephalus Treatment

OBJECTIVE:To characterize admissions related to ventricular shunts in the year 2000 in terms of diagnoses, procedures, socioeconomic status, and other related data. METHODS:The Nationwide Inpatient Sample database (year 2000) was analyzed retrospectively. We reviewed 7.45 million patient admissions for primary International Classification of Diseases, 9th Revision, procedure codes 023 to 0243 (ventricular shunts to peritoneal, atrial, pleural, and urinary systems for initial placement, revision, and removal); admissions listing ventriculostomy placement (code 022) were excluded from analysis. RESULTS:Five thousand five hundred seventy-four admissions were identified. Admission sources primarily were routine (58.8%) and the emergency department (32.4%). Admission types primarily were elective (43.3%), emergent (33.2%), and urgent (21.9%). The top three primary diagnoses treated were shunt malfunction (40.7%), noncommunicating hydrocephalus (16.6%), and communicating hydrocephalus (13.2%). Shunt infection was the primary diagnosis in 7.2% of admissions. Age frequency of admissions was nonparametric, being highest for infants; the average stay was 8.4 ± 0.2 days (standard error range, 0–243 d). The most common procedures were ventriculoperitoneal shunt placement (43.4%) and ventricular shunt replacement (42.8%); ventricular shunt removal occurred in 7.3% of admissions, whereas ventricle-to-thorax (0.6%), ventricle-to-circulatory system (0.5%), and ventricle-to-urinary system (0.05%) shunts were rare. Average cost was $35,816 ± $810 (standard error range, $137–$814,748). Primary payers primarily were private insurers (43.8%), Medicare (26.0%), and Medicaid (24.5%). Disposition mainly was routine (78.4%, with home health care in 6.5%), and inpatient mortality was 2.7%. There was no socioeconomic disproportion in treatment with respect to average household income. CONCLUSION:Ventricular shunts as primary procedures constitute a significant medical and economic problem.
Scene Recognition Acceleration Using CUDA and OpenMP

Scene recognition has become a remarkable field in image processing area, and many methods have been proposed in recent years, in which the idea of extracting the scene gist from global features has been proved to have higher retrieval accuracy compared with many other methods. However, the process of extracting gist is heavily time-consuming and not suitable for real-time application. In this paper, the CUDA architecture is deployed to accelerate this process. The influences of data transfer and memory access pattern on performance have also been investigated. Furthermore, when all the gist descriptors are got, parallel image feature similarity comparison is implemented with the OpenMP architecture. Experiments illustrate obvious speedup compared with implementation using only CPU.
Advanced Imaging Techniques in the Diagnosis of Nonlesional Epilepsy: MRI, MRS, PET, and SPECT

Once patients have a diagnosis of localization related epilepsy (LRE), it is critical to further classify those patients into lesional or nonlesional for treatment and prognostic reasons. An individual with LRE may be classified as nonlesional for two reasons: 1) a lesion may not exist; that is, the structural abnormality that gives rise to seizures may be at the channel level or be spatially distributed in such a way that it would not be accurately termed a lesion, or 2) a lesion exists but is so subtle that standard clinical imaging is not sensitive enough to discriminate between the lesion and surrounding healthy brain tissue. As with any technology and disease process, this definition is dynamic, as we know that future imaging techniques will be developed and new disease mechanisms will be discovered, making detection of the epileptogenic underlying abnormality an ever-changing target.
Consciousness and the Invention of Morel

A scientific study of consciousness should take into consideration both objective and subjective measures of conscious experiences. To this date, very few studies have tried to integrate third-person data, or data about the neurophysiological correlates of conscious states, with first-person data, or data about subjective experience. Inspired by Morel's invention (Casares, 1940), a literary machine capable of reproducing sensory-dependent external reality, this article suggests that combination of virtual reality techniques and brain reading technologies, that is, decoding of conscious states by brain activity alone, can offer this integration. It is also proposed that the multimodal, simulating, and integrative capacities of the dreaming brain render it an “endogenous” Morel's machine, which can potentially be used in studying consciousness, but not always in a reliable way. Both the literary machine and dreaming could contribute to a better understanding of conscious states.
Estilos interepersonales del entrenador, frustración de las necesidades psicológicas básicas y el burnout: un análisis longitudinal en futbolistas (Coach interpersonal styles, frustration of basic psychological needs and burnout: a longitudinal analysis

Basado en la Teoria de las Necesidades Psicologicas Basicas se puso a prueba un modelo con la siguiente secuencia: Estilo interpersonal de apoyo a la autonomia y estilo controlador del entrenador eFrustracion de las necesidades psicologicas basicas eel Burnout (BO). Participaron 177 futbolistas, con edades que entre 15 a 24 anos ( M = 17.81; DT = 1.98), quienes completaron los instrumentos que evaluaban las variables del estudio (CCBS, CBS, PNTS y ABQ). La fiabilidad de los instrumentos fue satisfactoria excepto la sub-escala de frustracion de la autonomia del tiempo 1. Los jugadores percibieron mas el estilo de AA que el EC de su entrenador, una baja FNPB y BO en el tiempo 1 (T1) y 2 (T2). Solo se encontraron diferencias significativas entre el T1 versus T2 en la percepcion del estilo de AA del entrenador siendo mas baja en el T2. El AA del T1 estuvo significativamente relacionado de manera negativa con el EC, con la FNPB, la frustracion de la autonomia (FA), frustracion de la competencia (FC) y frustracion de las relaciones (FR) y el BO en el T1 y T2, sin embargo, esto no fue asi con el AA del T2. Los resultados del Modelo A revelaron que AA del T1 fue un predictor negativo y el EC fue un predictor positivo de la FNPB del T2, y la FNPB del T2 actuo como un predictor positivo del BO. Por su parte el Modelo B revelo que el AA del T1 fue un predictor negativo y el EC del T1 fue un predictor positivo de la FA, FC y FR. Finalmente, la FA y FR actuaron como predictores positivos del BO. Abstract. A model based on the Basic Needs Theory was tested in accordance with the following sequence: Coach’s Autonomy Support and Authoritarian styles eBasic psychological need frustration eBurnout (BO). A total of 177 football players aged 15 to 24 years old ( M = 17.81; DT = 1.98) took part in the study. The athletes filled questionnaires related with the research variables (CCBS, CBS, PNTS, and ABQ). Instruments’ reliability was satisfactory, except for Autonomy frustration subscale at first measurement session (T1). Players perceived that their coaches used more AA than EC style. In addition, they showed low FNPB and BO at T1 and at the second measurement session (T2). Significant lower scores for perceived AA style were found at T2 compared to T1. AA at T1 was significantly and negatively related with EC, FNPB, Autonomy Frustration (FA), Competence Frustration (FC), and Relatedness Frustration (FR), whereas it was negatively related with BO at both T1 and T2. Nonetheless, this did not happen for AA at T2. Results of Model A showed that AA at T1 was a negative predictor of FNBP at T2 whereas EC at T1 was a positive predictor of FNBP at T2. In addition, FNPB at T2 positively predicted BO. Modelo B outcomes revealed that AA at T1 was a negative predictor of FA, FC, and FR, whereas EC at T1 was a positive predictor of those variables. Finally, FA and FR positively predicted BO.
Fast neighbor cells finding method for multiple octree representation

A cell occupancy map has been used widely for efficiently representing obstacles in robotic navigation. Such a map can often be formed based on the multi-resolution octree representation (MOR) of 3D point clouds captured from objects and workspace. This elevated cell-based approach may offer the capability of understanding the geometric context of workspace, expanding its applicability to robotic manipulation in a cluttered workspace. Under this context, the main issue of MOR becomes how to represent and generate cell addresses in such a way as to find neighboring cells efficiently. This paper presents a novel method for efficiently searching for neighboring cells with the fast generation of all the neighboring cell addresses. The original contribution of this paper is that not only the direct neighbors defined by those cells the edges or corners of which are directly connected to the given cell, but also the indirect neighbors of distance r, defined by those cells being separated from the given cell by the distance r, are included. The proposed method have been implemented and applied to obstacle representation in the 3D workspace modeling.
Upward Extension of the Jacobi Matrix for Orthogonal Polynomials

Orthogonal polynomials on the real line always satisfy a three-term recurrence relation. The recurrence coefficients determine a tridiagonal semi-infinite matrix (Jacobi matrix) which uniquely characterizes the orthogonal polynomials. We investigate new orthogonal polynomials by adding to the Jacobi matrixrnew rows and columns, so that the original Jacobi matrix is shifted downward. Thernew rows and columns contain 2rnew parameters and the newly obtained orthogonal polynomials thus correspond to an upward extension of the Jacobi matrix. We give an explicit expression of the new orthogonal polynomials in terms of the original orthogonal polynomials, their associated polynomials, and the 2rnew parameters, and we give a fourth order differential equation for these new polynomials when the original orthogonal polynomials are classical. Furthermore we show how the 1? orthogonalizing measure for these new orthogonal polynomials can be obtained and work out the details for a one-parameter family of Jacobi polynomials for which the associated polynomials are again Jacobi polynomials.
Labelled Propositional Modal Logics: Theory and Practice

We show how labelled deductive systems can be combined with a logical framework to provide a natural deduction implementation of a large and well-known class of propositional modal logics (including K, D, T, B, S4, S4:2, KD45, S5). Our approach is modular and based on a separation between a base logic and a labelling algebra, which interact through a xed interface. While the base logic stays xed, diierent modal logics are generated by plugging in appropriate algebras. This leads to a hierarchical structuring of modal logics with inheritance of theorems. Moreover, it allows modular correctness proofs, both with respect to soundness and completeness for semantics, and faithfulness and adequacy of the implementation. We also investigate the tradeoos in possible labelled presentations: we show that a narrow interface between the base logic and the labelling algebra supports modularity and provides an attractive proof-theory but limits the degree to which we can make use of extensions to the labelling algebra.
Research on Buffer Overflow Test Based on Invariant

Buffer overflow (BOF) is one of the major vulnerabilities that lead to non-secure software. Testing an implementation for BOF vulnerabilities is challeng-ing as the underlying reasons of buffer overflow vary widely. This paper presents a novel method for BOF test for ANSI C language, which uses program instrumenta-tion and mutation test technology to test the BOF vul-nerabilities, on the basis of analyzing the invariants for BOF vulnerabilities. The implementation shows that it can check the attack of BOF vulnerabilities adequately and accurately, in the circumstances of no large losses in performance.
Principled dictionary pruning for low-memory corpus compression

Compression of collections, such as text databases, can both reduce space consumption and increase retrieval efficiency, through better caching and better exploitation of the memory hierarchy. A promising technique is relative Lempel-Ziv coding, in which a sample of material from the collection serves as a static dictionary; in previous work, this method demonstrated extremely fast decoding and good compression ratios, while allowing random access to individual items. However, there is a trade-off between dictionary size and compression ratio, motivating the search for a compact, yet similarly effective, dictionary. In previous work it was observed that, since the dictionary is generated by sampling, some of it (selected substrings) may be discarded with little loss in compression. Unfortunately, simple dictionary pruning approaches are ineffective. We develop a formal model of our approach, based on generating an optimal dictionary for a given collection within a memory bound. We generate measures for identification of low-value substrings in the dictionary, and show on a variety of sizes of text collection that halving the dictionary size leads to only marginal loss in compression ratio. This is a dramatic improvement on previous approaches.