Miracle-dz/UniFAR-FTUs huggingface dataset:
The BRIGHTEN program: implementation and evaluation of a program to bridge resources of an interdisciplinary geriatric health team via electronic networking.

PURPOSE To demonstrate the feasibility of the BRIGHTEN Program (Bridging Resources of an Interdisciplinary Geriatric Health Team via Electronic Networking), an interdisciplinary team intervention for assessing and treating older adults for depression in outpatient primary and specialty medical clinics. The BRIGHTEN team collaborates "virtually" to review patient assessment results, develop a treatment plan, and refer to appropriate team members for follow-up care. DESIGN AND METHODS Older adults in 9 academic medical center clinics and 2 community-based clinics completed screening forms for symptoms of depression and anxiety. Those with positive screens engaged in comprehensive assessment with the BRIGHTEN Program Coordinator; the BRIGHTEN virtual team provided treatment recommendations based on the results of assessment. A collaborative treatment plan was developed with each participant, who was then connected to appropriate services. RESULTS Two thousand four hundred twenty-two older adults were screened in participating clinics over a 40-month period. Eight hundred fifty-nine older adults screened positive, and 150 elected to enroll in BRIGHTEN. From baseline to 6 months, significant improvements were found in depression symptoms (Geriatric Depression Scale, p < .01) and general mental health (SF-12 Mental Component, p < .01). IMPLICATIONS The BRIGHTEN Program demonstrated that an interdisciplinary virtual team linked with outpatient medical clinics can be an effective, nonthreatening, and seamless approach to enable older adults to access treatment for depression.
Eliminating Cover Image Requirement in Discrete Wavelet Transform based Digital Image Steganography

steganography is the art and science of hiding secret image into digital media such that no one apart from the intended recipient is able to detect the existence of the information. There are many different carriers that can be used to hide the information such as digital images, videos, sound files and other computer files but digital images are the most popular. In this paper, a method has been proposed using which a large size secret image can be hidden into small size cover image securely. The main aim here is the absolute invisibility of the large size secret image. The secret image is first scrambled by using Arnold transformation. Haar Discrete Wavelet Transformation (DWT) is then applied on cover image and Arnold transformed secret image, followed by Alpha Blending operation. Then the Haar Inverse Discrete Wavelet Transformation (IDWT) is applied to obtain the stego image. At the receiver side, first the cover image is obtained from the stego image. Then Haar DWT is applied on the cover image and the stego image followed by the alpha blending operation. Haar IDWT is applied on the resulting image. Then by applying Arnold transformation, the secret image is obtained. The proposed method does not require the sender to send the cover image to the receiver for obtaining the secret image. The performance of the proposed method is investigated by comparing the cover image and the stego image in terms of Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Normalized Cross Correlation (NCC). Experimental results demonstrate the effectiveness and accuracy of the proposed method.
Open-Sphere Designs for Spherical Microphone Arrays

Spherical microphone arrays have been studied for a wide range of applications, one of which is acoustic measurement and analysis. Since a minimal interaction between the array and the measured sound field is an advantage in this case, open-sphere arrays are preferable compared to rigid-sphere arrays. However, it has been shown that open-sphere arrays suffer from numerical ill-conditioning at frequencies which correspond to the nodal values of the spatial spherical modes with the result of excessive noise at these frequencies. A method for overcoming this problem using an open dual-sphere array is proposed in this correspondence and then investigated and compared to an array configured around a rigid sphere and an array composed of cardioid microphones. An optimal value for the ratio of the two spheres is derived, and simulation examples illustrating the advantage of the dual-sphere array are finally presented
Autoregressive and Iterative Hidden Markov Models for Periodicity Detection and Solenoid Structure Recognition in Protein Sequences

Traditional signal processing methods cannot detect interspersed repeats and generally cannot handle nonstationary signals. In this paper, we propose a new method for periodicity detection in protein sequences to locate interspersed repeats. We first apply the autoregressive model with a sliding window to find possible repeating subsequences within a protein sequence. Then, we utilize an iterative hidden Markov model (HMM) to count the number of subsequences similar to each of the possible repeating subsequences. An iterative HMM search of the potential repeating subsequences can help identify interspersed repeats. Finally, the numbers of repeating subsequences are aggregated together as a feature and used in the classification process. Experiment results show that our method improves the performance of solenoid protein recognition substantially.
CSR: Cooperative source routing using virtual MISO in wireless ad hoc networks

Cooperative transmissions combat various fading effects in wireless communications by employing multiple antennas from different nodes to achieve spatial diversity. Virtual Multiple-Input Single-Output (MISO) is one instance of cooperative transmissions capable of achieving higher receiving SNR, which can either extend the transmission range or increase the transmission rate. While the physical layer performance of Virtual MISO has been well studied, this paper describes the Cooperative Source Routing (CSR) protocol to convert physical layer gain into network level performance improvement. With both route request and route reply control packets being transmitted cooperatively, CSR can explore routes with high cooperative diversity. We demonstrate CSR's performance through simulation and compare CSR with other protocols.
The Object-Relation-Kin Model Toward Relational Analysis and Design in General Object Oriented Languages

The relational model is in use by many database systems. Object oriented technology is also widely used in database application development. But “object-relational impedance mismatch” was found between the two approaches. However, in the study behind this paper, the REAL mismatch is reevaluated, and the Object-Relational Mapping approach is found being actually mapping between the Network Model and the SQL interface. A new data model — the Object-Relation-Kin model is then derived from the entity-relationship model regarding the relational model, to better consolidate object technology and the relational model without defective mappings. AbleverseTM TheObjectBase as the DBMS and WebOfWeb as the blueprint project are showing a feasible solution in the JavaTM programming language as realworld practices, on the basis of this new data model.
Intrusion Patterns Recognition in Computer Networks

One of the hottest research areas in recent years is detecting network intrusion patterns in computer networks. Because of dynamic nature of intrusion patterns in networks, intelligently inspecting the behavior of networks and detecting anomalies are mostly desirable. KDD-Cup99 pattern database are used as a standard source of network packets in our research. K-mean, Bayesian method and Support Network Machine (SVM) are used as anomaly detectors. Results show the superiority of SVM over other two methods regarding the accuracy of classifying patterns into normal packets and suspicious ones. It can be concluded that using high dimensional pattern recognition methods have reasonable competence in detecting attack patterns in computer networks.
Networks on Chip (NOC): Design Challenges

With the growth of the number of SOC components it is necessary to revalue the de-sign technology and architecture. This work overviews the field of Networks on Chip (NOC), and addresses the distinguishing features of the several architectural designs of a NOC (Octa-gon and Eclipse). The limitations of the interconnect technology are discussed as well as how his technology has been scaled down to meet systems requirements.
Characterization and prognostic value of persistent hyponatremia in patients with severe heart failure in the ESCAPE Trial.

BACKGROUND Mild hyponatremia is relatively common in patients hospitalized with heart failure (HF). To our knowledge, the association of hyponatremia with outcomes has not been evaluated in the context of in-hospital clinical course including central hemodynamics and changes in serum sodium level. METHODS The ESCAPE trial (Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness) was a randomized, controlled study designed to evaluate the utility of a pulmonary artery catheter plus clinical assessment vs clinical assessment alone in guiding therapy in patients hospitalized with New York Heart Association class IV HF due to systolic dysfunction (left ventricular ejection fraction <30%). A Cox proportional hazards model with baseline serum sodium level as a continuous variable was used to examine the association of serum sodium level with 6-month postdischarge mortality, HF rehospitalization, and death or rehospitalization. A categorical analysis was also performed comparing persistent and corrected hyponatremia. RESULTS A total of 433 hospitalized patients with HF were enrolled in ESCAPE. Hyponatremia (serum sodium level < or = 134 mEq/L) was present in 103 patients (23.8%). (To convert serum sodium to millimoles per liter, multiply by 1.0.) Of these, 71 had persistent hyponatremia (68.9%). Hyponatremia was associated with higher 6-month mortality after covariate adjustment (hazard ratio [HR] for each 3-mEq/L decrease in sodium level, 1.23; 95% confidence interval [CI], 1.05-1.43) (P = .01). After controlling for baseline variables and clinical response, we found that patients with persistent hyponatremia had an increased risk of all-cause mortality (31% vs 16%; HR, 1.82) (P = .04), HF rehospitalization (62% vs 43%; HR, 1.52) (P = .03), and death or rehospitalization (73% vs 50%; HR, 1.54) (P = .01) compared with normonatremic patients. CONCLUSION Persistent hyponatremia was an independent predictor of mortality, HF hospitalization, and death or rehospitalization despite clinical and hemodynamic improvements that were similar to those in patients without hyponatremia.
A fuzzy logic system for home elderly people monitoring (EMUTEM)

The purpose of this paper is to present a view of a telemonitoring system based on fuzzy logic for distress situations detection of elderly people living alone in the home environment. This system includes three different sensors: physiological sensors (cardiac frequency, activity or agitation, posture and fall detection sensor), microphones and infrared sensors. Taking into account the difficulty of the statistical modeling of abnormal situation and considering that the Fuzzy Logic has been actually used with success in the development of classifier and analysis of control systems, its use in the decision fusion module of our home elderly people monitoring system is presented and evaluated in this paper.
How Do European Pharmacy Students Rank Competences for Practice?

European students (n = 370), academics (n = 241) and community pharmacists (n = 258) ranked 13 clusters of 68 personal and patient care competences for pharmacy practice. The results show that ranking profiles for all three groups as a rule were similar. This was especially true of the comparison between students and community pharmacists concerning patient care competences suggesting that students have a good idea of their future profession. A comparison of first and fifth (final) year students shows more awareness of patient care competences in the final year students. Differences do exist, however, between students and community pharmacists. Students—like academics—ranked competences concerned with industrial pharmacy and the quality aspects of preparing drugs, as well as scientific fundamentals of pharmacy practice, well above the rankings of community pharmacists. There were no substantial differences amongst rankings of students from different countries although some countries have more “medicinal” courses than others. This is to our knowledge the first paper to look at how, within a healthcare sectoral profession such as pharmacy, the views on the relative importance of different competences for practice of those educating the future professionals and their students, are compared to the views of working professionals.
Stochastic Logic Programs

One way to represent a machine learning algorithm's bias over the hypothesis and instance space is as a pair of probability distributions. This approach has been taken both within Bayesian learning schemes and the framework of U-learnability. However, it is not obvious how an Induc-tive Logic Programming (ILP) system should best be provided with a probability distribution. This paper extends the results of a previous paper by the author which introduced stochastic logic programs as a means of providing a structured deenition of such a probability distribution. Stochastic logic programs are a generalisation of stochastic grammars. A stochastic logic program consists of a set of labelled clauses p : C where p is from the interval 0; 1] and C is a range-restricted deenite clause. A stochastic logic program P has a distributional semantics, that is one which assigns a probability distribution to the atoms of each predicate in the Herbrand base of the clauses in P. These probabilities are assigned to atoms according to an SLD-resolution strategy which employs a stochastic selection rule. It is shown that the probabilities can be computed directly for fail-free logic programs and by normalisation for arbitrary logic programs. The stochastic proof strategy can be used to provide three distinct functions: 1) a method of sampling from the Herbrand base which can be used to provide selected targets or example sets for ILP experiments, 2) a measure of the information content of examples or hypotheses; this can be used to guide the search in an ILP system and 3) a simple method for conditioning a given stochastic logic program on samples of data. Functions 1) and 3) are used to measure the generality of hypotheses in the ILP system Progol4.2. This supports an implementation of a Bayesian technique for learning from positive examples only. This paper is an extension of a paper with the same title which appeared in 12]
Spectrum of a Feinberg-Zee random hopping matrix

This paper provides a new proof of a theorem of Chandler-Wilde, Chonchaiya, and Lindner that the spectra of a certain class of infinite, random, tridiagonal matrices contain the unit disc almost surely. It also obtains an analogous result for a more general class of random matrices whose spectra contain a hole around the origin. The presence of the hole forces substantial changes to the analysis.
PCantorSim

Computer architects rely heavily on microarchitecture simulation to evaluate design alternatives. Unfortunately, cycle-accurate simulation is extremely slow, being at least 4 to 6 orders of magnitude slower than real hardware. This longstanding problem is further exacerbated in the multi-/many-core era, because single-threaded simulation performance has not improved much, while the design space has expanded substantially. Parallel simulation is a promising approach, yet does not completely solve the simulation challenge. Furthermore, existing sampling techniques, which are widely used for single-threaded applications, do not readily apply to multithreaded applications as thread interaction and synchronization must now be taken into account. This work presents PCantorSim, a novel Cantor set (a classic fractal)--based sampling scheme to accelerate parallel simulation of multithreaded applications. Through the use of the proposed methodology, only less than 5% of an application's execution time is simulated in detail. We have implemented our approach in Sniper (a parallel multicore simulator) and evaluated it by running the PARSEC benchmarks on a simulated 8-core system. The results show that PCantorSim increases simulation speed over detailed parallel simulation by a factor of 20×, on average, with an average absolute execution time prediction error of 5.3%.
Tight performance bounds for space-time coded systems with antenna selection

In this paper we use Renyi representation of order statistics to provide a tight lower bound on the outage probability and a tight upper bound on the average signal-to-noise ratio of orthogonal space-time coded systems with antenna selection. Using these bounds we propose a chi-square approximation to the outage probability. We show through simulations that the bounds and also the chi-square approximation are quite tight for a variety of antenna configurations. The method presented here is quite general and not restricted to the Rayleigh distribution.
Algorithms for discovering repeated patterns in multidimensional representations of polyphonic music

In previous approaches to repetition discovery in music, the music to be analysed has been represented using strings. However, there are certain types of interesting musical repetitions that cannot be discovered using string algorithms. We propose a geometric approach to repetition discovery in which the music is represented as a multidimensional dataset. Certain types of interesting musical repetition that cannot be found using string algorithms can efficiently be found using algorithms that process multidimensional datasets. Our approach allows polyphonic music to be analysed as efficiently as monophonic music and it can be used to discover polyphonic repeated patterns “with gaps” in the timbre, dynamic and rhythmic structure of a passage as well as its pitch structure. We present two new algorithms: SIA and SIATEC. SIA computes all the maximal repeated patterns in a multidimensional dataset and SIATEC computes all the occurrences of all the maximal repeated patterns in a dataset. For a k -dimensional dataset of size n, the worstcase running time of SIA is O (kn 2 log 2 n) and the worst-case running time of SIATEC is O (kn 3).
TestUml: user-metrics driven web applications testing

Web applications have become very complex and crucial, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering), the scientific community has focused attention to Web application design, development, analysis, and testing, by studying and proposing methodologies and tools. This paper describes techniques for semi-automatic test case definition and for user1-driven testing (based on statistical testing or coverage analysis) from Web applications reverse engineered UML models. These techniques are implemented as tools in the WAAT project. WebUml is a reverse engineering tool that generates class and state diagrams through static and dynamic Web application analysis. TestUml is a testing suite that uses generated models to define test cases, coverage testing criteria and also reliability analysis.
1 Instruction Set Architecture for Multimedia Signal Processing

Multimedia signal processing, or media processing [1], is the processing of digital multimedia information in a programmable processor. Digital multimedia information includes visual information like images, video, graphics and animation, audio information like voice and music, and textual information like keyboard text and handwriting. With general-purpose computers processing more multimedia information, multimedia instructions for efficient media processing have been defined for the Instruction Set Architectures (ISAs) of microprocessors. Meanwhile, digital processing of video and audio data in consumer products has also resulted in more sophisticated multimedia processors. Traditional digital signal processors (DSPs) in music players and recorders and mobile telephones are becoming increasingly sophisticated as they process multiple forms of multimedia data, rather than just audio signals. Video processors for televisions and video recorders have become more versatile as they have to take into account high-fidelity audio processing and real-time three-dimensional (3-D) graphics animations. This has led to the design of more versatile media processors, which combine the capabilities of DSPs for efficient audio and signal processing, video processors for efficient video processing, graphics processors for efficient 2-D and 3-D graphics processing, and general-purpose processors for efficient and flexible programming. The functions performed by microprocessors and media processors may eventually converge. In this chapter, we describe some of the key innovations in multimedia instructions added to microprocessor ISAs, which have allowed high-fidelity multimedia to be processed in real-time on ubiquitous desktop and notebook computers. Many of these features have also been adopted in modern media processors and digital signal processors.
Generating Edge-disjoint Sets of Quadruples in Parallel for the Molecular Conformation Problem

Tightening interatomic distance bounds, obtained from NMR experiments, is a critical step in solving the molecular conformation problem. Tetrangle inequality (resulting from the Cayley-Menger determinant for the 3D embedding) is applied to quadruples of atoms in order to tighten the distance bounds. Complete graph Kn is used to model an n-atom molecule, where the nodes represent the atoms. Only edge-disjoint sets of quadruples can be processed in parallel. In this paper we propose a coarse-grain parallelization for generating edge-disjoint sets of quadruples in parallel. Previous methods for generating edge-disjoint quadruples relied on difference sets. Our approach partitions the nodes into disjoint sets (partitions). Quadruples are then generated based on their node distribution among these sets.
Co-Integration, Error Correction, and the Econometric Analysis of Non-Stationary Data

This book provides a wide-ranging account of the literature on co-integration and the modelling of integrated processes (those which accumulate the effects of past shocks). Data series which display integrated behaviour are common in economics, although techniques appropriate to analysing such data are of recent origin and there are few existing expositions of the literature. This book focuses on the exploration of relationships among integrated data series and the exploitation of these relationships in dynamic econometric modelling. The concepts of co-integration and error-correction models are fundamental components of the modelling strategy. This area of time-series econometrics has grown in importance over the past decade and is of interest to econometric theorists and applied econometricians alike. By explaining the important concepts informally, but also presenting them formally, the book bridges the gap between purely descriptive and purely theoretical accounts of the literature. The asymptotic theory of integrated processes is described and the tools provided by this theory are used to develop the distributions of estimators and test statistics. Practical modelling advice, and the use of techniques for systems estimation, are also emphasized. A knowledge of econometrics, statistics, and matrix algebra at the level of a final-year undergraduate or first-year undergraduate course in econometrics is sufficient for most of the book. Other mathematical tools are described as they occur.