Miracle-dz/UniFAR-FTUs huggingface dataset:
[Clearance dose in acute kidney injury].

Correspondencia: Francisco Javier Gainza de los Rios Servicio de Nefrologia. Hospital de Cruces. Universidad del Pais Vasco. fco.javier. gainzadelosrios@osakidetza.net E n la ultima decada se han concentrado esfuerzos para definir el umbral de dosis de tratamiento renal sustitutivo en la insuficiencia renal aguda (IRA) que permitiera reducir la elevada mortalidad de esta frecuente complicacion en el ambito hospitalario.
Spirometrie für die klinische Praxis

Nach den internationalen Richtlinien der COPD (GOLD) und denen des Asthmas (GINA) ist fur die Diagnose und Therapie beider Krankheitsbilder die Durchfuhrung einer Spirometrie unverzichtbar. Obwohl praktisch jeder Allgemeininternist uber ein EKG verfugt, ist nicht in jeder Praxis bzw. jeder Spitalambulanz ein Spirometer vorhanden bzw. konnen die Messwerte korrekt interpretiert werden. Die nachfolgende Arbeit will einen einfachen Zugang zur Messung und Interpretation der Spirometrie ermoglichen.
Repeated-Game Modeling of Cooperation Enforcement in Wireless Ad Hoc Network: Repeated-Game Modeling of Cooperation Enforcement in Wireless Ad Hoc Network

Due to the absence of centralized authority, the service reliability of wireless ad hoc network is seriously affected by selfish actions of the rational nodes during the packet forwarding. In this paper, we propose a repeated-game model of node behavior that takes account of the selfish nodes' future payoff expectations and their long-term desires for profit. An incentive-compatible condition under which the selfish one will be deterred from cheating by the subsequent punishments and then turn to cooperate is shown analytically. The impacts on the selfish nodes’ behaviors, which are induced by their willingness for future collaboration, the parameter settings of punishment mechanism and the efficiency of misbehavior detection, are also discussed. Simulation results show that, the increase of network scale, the deterioration of node's collaborative patience and the low misbehavior detection efficiency will motivate entities toward self-interested action, but this tendency can be neutralized by carefully configuration of the punishment mechanism in our model.
Research on IPv6 intrusion detection system Snort-based

This paper introduces the common intrusion detection technologies, discusses the work flow of Snort intrusion detection system, and analyzes IPv6 data packet encapsulation and protocol decoding technology. We propose the expanding Snort architecture to support IPv6 intrusion detection in accordance with CIDF standard combined with protocol analysis technology and pattern matching technology, and present its composition. The research indicates that the expanding Snort system can effectively detect various intrusion attacks; it is high in detection efficiency and detection accuracy and reduces false alarm and omission report, which effectively solves the problem of IPv6 intrusion detection.
Analysis, Feature Extraction, Modeling and Testing Techniques for Speaker Recognition

Abstract Speaker recognition system may be viewed as working in four stages, namely, analysis, feature extraction, modeling and testing. This paper gives an overview of the major techniques developed in each of these stages. Such a review helps in understanding the developments that have taken place in each stage and also the available choices of techniques, along with their relative merits and demerits. A comparative study of different techniques is done at the end of each section to justify the choice of techniques available in the state-of-the-art speaker recognition systems. The paper is concluded with a discussion on the possible future direction for the development of techniques in each stage.
Standby/active mode logic for sub-1-V operating ULSI memory

New gate logics, standby/active mode logic I and II, for future 1 Gb/4 Gb DRAMs and battery operated memories are proposed. The circuits realize sub-l-V supply voltage operation with a small 1-/spl mu/A standby subthreshold leakage current, by allowing 1 mA leakage in the active cycle. Logic I is composed of logic gates using dual threshold voltage (Vt) transistors, and it can achieve low standby leakage by adopting high Vt transistors only to transistors which cause a standby leakage current. Logic II uses dual supply voltage lines, and reduces the standby leakage by controlling the supply voltage of transistors dissipating a standby leakage current. The gate delay of logic I is reduced by 30-37% at the supply voltage of 1.5-1.0 V, and the gate delay of logic II is reduced by 40-85% at the supply voltage of 1.5-0.8 V, as compared to that of the conventional CMOS logic. >
Three‐Dimensional Region‐Based Segmentation for Breast Tumors on Sonography

Because malignant and benign breast tumors show different shapes and sizes on sonography, information about tumor shapes and sizes is important for clinical diagnosis. Since sonograms include noise and tissue texture, accurate clinical diagnosis is highly dependent on clinical experience and expertise. However, manually sketching a 3‐dimensional (3D) breast tumor contour is a time‐consuming and complicated task. Automatic contouring, which provides a contour similar to that of manual sketching of a breast tumor on sonography, may improve diagnostic accuracy. This study presents an efficient method for automatically detecting 3D contours of breast tumors on 3D sonography. The proposed method applies a voxel nearest neighbor filter, a Wiener filter, and an unsharp filter to enhance contrast and reduce noise. After a 3D region‐growing algorithm is used to obtain the contour of the breast tumor, postprocessing of the extracted contour is performed to diminish the shadow region of the tumor. This study evaluated 20 tumor cases comprising 10 benign and 10 malignant cases. The results of computer simulation reveal that the proposed 3D segmentation method provides robust contouring for breast sonograms. This approach consistently obtains contours similar to those obtained by manual contouring of a breast tumor and can reduce the time needed to sketch precise contours.
A Self-Managing Framework for Health Monitoring

Existing medical devices and equipment monitor abnormal physiological conditions and trigger audiovisual alarms. However, these devices require high levels of interaction by a doctor since they do not have any selfmanaging capabilities to reduce user intervention or to autonomically handle alerts. Recent advances in low-power wireless communication technologies have led to the development of small formfactor, wireless, body-wearable biomedical devices for health monitoring [1]. This enables patient mobility and comfort and enables continuity of care from hospital to home. In this paper we propose a self-managing framework for health monitoring using body-wearable bio-devices [2] that can reduce the doctor’s intervention for patient management. This will enable doctors to effectively manage a greater number of patients and reduce the number of errors inherent in paper-based processes. We illustrate three usage models where this self-managing framework can be applied: remotely monitoring patients at home, monitoring fetal well-being in a maternity ward, and monitoring critical patients in an Intensive Care Unit (ICU).
Keys, Nominals, and Concrete Domains

Many description logics (DLs) combine knowledge representation on an abstract, logical level with an interface to 'concrete' domains such as numbers and strings with built-in predicates such as <, +, and prefix-of. These hybrid DLs have turned out to be quite useful for reasoning about conceptual models of information systems, and as the basis for expressive ontology languages. We propose to further extend such DLs with key constraints that allow the expression of statements like 'US citizens are uniquely identified by their social security number'. Based on this idea, we introduce a number of natural description logics and perform a detailed analysis of their decidability and computational complexity. It turns out that naive extensions with key constraints easily lead to undecidability, whereas more careful extensions yield NEXPTIME-complete DLs for a variety of useful concrete domains.
Influence of crosstalk on the scalability of WDM cross-connect networks

Intraband crosstalk contributions in three types of WDM cross-connect topologies based on the Benes architectures are identified. The crosstalk behaviours of the WDM networks are compared and discussed. It is demonstrated that the first-order crosstalk contributions are dominated by the crosstalk from the switching elements. The network scalability is analysed in terms of fibres, wavelengths and nodes. The results show that routing different wavelengths in each switching architecture in WDM cross-connect networks is a reasonable approach to achieve perfect performance in the presence of component crosstalk.
Nested neural networks for image compression

Data compression occurs naturally in the human brain. The brain detects features and the context to any input signal and associates with it a name and form. The use of artificial neural networks for compressing data has been used in the past with some degree of success. The difficulty with this technique is that even though it may achieve a high compression ratio, it provides only the 'approximate' information and loses the 'detail'. In this paper, a new concept has been developed-nested neural networks. These networks are built with a set of networks 'nested' inside the larger network. This scheme has been implemented for data compression of images and the results are promising.
Altered expression of HLA class I antigens in breast cancer: Association with prognosis

Loss of surface expression of class I major histocompatibility antigens is commonly observed in malignant tumors and has been considered one of the mechanisms for escape from cytotoxic T cells. However, natural killer cells kill cells lacking HLA class I antigens. In the present study, we characterized by immunohistochemistry the HLA class I expression of breast carcinomas from 187 patients with TNM stages I and II, diagnosed 1981–1984, using β2‐microglobulin as a marker and evaluated the effect on survival with a follow‐up of up to 14 years. The largest group (48%) consisted of HLA class I–negative tumors (≤10% of cells stained), mixed expression (>10% and <80% of cells stained) was seen in 36% and only 15% were classified as HLA class I–positive (≥80% cells stained). No associations could be established with various clinicopathological parameters, such as tumor size, presence of lymph node metastases, histological grade, expression of hormone receptors, S phase and p53 mutations. There was no effect on recurrence‐free survival in the whole group; but among node‐negative patients (n = 86), those who had tumors with mixed HLA class I expression had a significantly higher probability of disease recurrence (OR = 3.42, p = 0.014) than patients with either HLA class I–positive or –negative tumors, particularly after more than 5 years. In node‐positive patients who received adjuvant therapy, this phenotype was not associated with disease recurrence. Int. J. Cancer 89:500–505, 2000. © 2000 Wiley‐Liss, Inc.
Process-based measures of quality: the need for detailed clinical data in large health care databases.

The Institute of Medicine defines health care quality as increasing "the likelihood of desired health outcomes" using "services . consistent with current professional knowledge. " This definition implies that quality measures can be based on either achieving health care outcomes or completing processes that experts agree have been shown by scientific evidence to improve outcomes. Process-based measures are especially suitable when the user needs to know how to improve quality, when provider comparisons show equivalent outcomes but all providers should improve processes, when measures are needed to evaluate health care that is intended to improve long-term outcomes, or when the contribution of individual providers (especially providers who have a small number of cases) needs to be defined. However, many different process-based measures are needed to comprehensively assess quality, and many process-based measures require detailed clinical data currently found only in medical records. Therefore, the expense of abstracting records is a barrier to process-based measurement. Fortunately, large-scale process-based measures are becoming more feasible because the required clinical data are being included in large databases. The merging of existing inpatient and outpatient databases with pharmacy and laboratory databases is an important step toward obtaining data that link all patient admissions, appointments, diagnostic procedures, and prescriptions with diagnoses and test results. Other data that are valuable for process-based measures must still be obtained by abstracting data from records, including clinical findings, patient preferences, and medical and family history. In the future, such data may be added to large databases to create computerized medical records.
WAKE UP! The effectiveness of a student response system in large packaging classes

Large classes present many challenges in higher education. New digital technologies, such as interactive student response systems (SRSs), are promising tools for large classes. SRSs facilitate interaction between faculty members and students on an on‐going basis by allowing instructors to ask multiple‐choice, true/false and numerical questions during class and then analyse and display the student responses in real time. In general, SRSs consist of three basic components: a student input device (clicker), operating system software loaded onto the classroom computer, and an overhead projection system to display the questions asked and the distribution of student responses. SRSs have already been used in classrooms in a variety of fields; however, to our knowledge, they have not been used previously in packaging education. This article describes the introduction of an SRS in two packaging classes at the School of Packaging at Michigan State University. The SRS implementation is discussed and faculty and student comments and responses regarding the SRS are reported. The system motivated student participation and attendance for both classes: 75% of student respondents stated that the SRS motivated them to attend class; 57% of student respondents reported that the SRS enhanced their classroom experience; and 56% of the student respondents indicated that the system helped them to comprehend the material better. These numbers are supported by the vast majority of research studies, which indicate improved attendance, participation and comprehension when using SRSs for large classrooms. Copyright © 2006 John Wiley & Sons, Ltd.
Theory and practice of systems methodology in ERP implementation

The application and evolution of MRP II/ERP can be roughly divided into three stages: the introduction stage, the growth stage, and the maturity stage. A successful ERP implementation requires knowledge on both ERP systems and business management. In implementing ERP, the business processes of those enterprises adopted ERP systems need to be examined. It is important to understand the ERP system itself and the business processes involved with the ERP systems and the enterprises-adopted ERP systems. In order to resolve issues that may appear in the process of implementing ERP system, this paper proposes that a systematic analysis of those significant factors involved with implementing ERP systems is a necessity, especially if such analysis is conducted in the framework of systems science. Copyright © 2006 John Wiley & Sons, Ltd.
Neural-network techniques for software-quality evaluation

Software quality modeling involves identifying fault-prone modules and predicting the number of errors in the early stages of the software development life cycle. This paper investigates the viability of several neural network techniques for software quality evaluation (SQE). We have implemented a principal component analysis technique (used in SQE) with two different neural network training rules, and have classified software modules as fault-prone or nonfault-prone using software complexity metric data. Our results reveal that neural network techniques provide a good management tool in a software engineering environment.
A life-like control algorithm for the natural movement of a 3 dof finger

This paper describes the dynamic control of a 3 dof finger emulating a human medium finger for reaching a desired configuration in space. The controller imitates the physiological control and the motion planning strategy in human beings. A Multi Layers Perceptron (MLP) architecture has been setup, which receives as input the desired position and velocity of the fingertip (sensorial input) and the actual position and velocity (proprioceptive input). The output produces the necessary torques to reach the desired position. The MLP is fed back by the plant with the actual positions and velocities by closing the loop with a direct dynamics block: the movement due to the applied torques is sent back to update the proprioceptive input. Assuming a 'cognitive' approach well established in the literature, the controller performs a smooth 'natural' speed profile of the fingertip motion by adopting an arranged extension of the minimum jerk theory. The generalization capabilities of the NN is checked. The results are discussed by considering the closed loop configuration with respect to the open loop one (that is the MLP without the feedback). We suggest this approach for dynamical control of multi-finger prosthetic/robotic hand.
Improvement of information filtering by independent components selection

We propose an improvement of an information filtering process with independent components selection. The independent components are obtained by Independent Components Analysis and considered as topics. Selection of independent components is an efficient method of improving the accuracy of the information filtering for the purpose of extraction of similar topics by focusing on their meanings. To achieve this, we select the topics by Maximum Distance Algorithm with Jensen‐Shannon divergence. In addition, document vectors are represented by the selected topics. We create a user profile from transformed data with a relevance feedback. Finally, we sort documents by the user profile and evaluate the accuracy by imputation precision. We carried out an evaluation experiment to confirm the validity of the proposed method considering meanings of components used in this experiment. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 163(2): 49–56, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20519
Embedding and detection of side information for peak-to-average power ratio reduction of an OFDM signal using partial transmit sequences

The peak-to-average power ratio (PAPR) problem of OFDM systems can be efficiently resolved using the partial transmit sequences (PTS) method, for which data recovery requires side information (SI) about the phase rotation factors used at the transmitter. With no loss of spectrum efficiency, two embedded SI transmission schemes (I and II), including frequency-domain marking algorithms and decision statistics, are proposed for PSK data and one (III) for QAM data. A time-domain implementation of the proposed marking algorithms is presented for reducing complexity. Simulation results demonstrate the good performance of the proposed schemes, especially for scheme III.
Assessment of hearing in children with type 1 diabetes mellitus

Abstract Objective: To evaluate auditory function in a group of Egyptian type 1 diabetic children. Methods: This was a cross sectional observational study, which included 40 patients with type 1 diabetes and 40 controls. HbA1, urinary albumin/creatinine ratio, and auditory assessments (including dizziness questionnaire, pure tone audiometry, speech audiometry, tympanometry, and auto-acoustic cochlear emission) were completed for all patients and controls. Mann-Whitney U-test, χ2-test and Spearman’s correlation were used for statistical analyses. Results: Assessment of pure tone audiometry revealed that the diabetics had a significantly higher reading in high frequency at 8000 Hz, 16,000 Hz, 17,000 Hz, and 18,000 Hz on the right side and at 4000 Hz, 8000 Hz, 16,000 Hz, 17,000 Hz, and 18,000 Hz on the left side. There was a significantly lower level in speech reception threshold, repetition of words, and masking level of diabetics on the left side. Evaluation of transient otoacoustic emission revealed that diabetics recorded significantly lower signal to noise ratio at 4000 Hz on the right side and at 1000, 1500, 4000, and all Hz on left side. There was significant lower emission amplitude in the right side of the diabetics group at 1500 and 4000 Hz and at 1000, 1500, and 4000 Hz on the left side. Patients with failed otoacoustic emission were significantly higher in disease duration >10 years. Conclusion: Type 1 diabetes is associated with high/extended high frequency hearing loss, more prominent on the left side and with longer disease duration.
Enhanced visual secret sharing for graphical password authentication

Password is a very common and widely used authentication method to provide security to valuable data. It is desirable to make password more memorable and easier for people to use. Traditionally passwords are alphanumeric, numbers & symbols. Some problems of normal password appear like stolen the password, forgetting the password, week password. Study shows that text-based passwords suffer with both security and authentication problems. To overcome these problems, Graphical passwords have been developed. Visual secret sharing (VSS) scheme is a secret sharing scheme in which an image is converted into shares. No information can be revealed by observing any share (Dotted image). The information about the original image will be revealed only after stacking sufficient number of shares (Dotted images). In this paper, we have used XNOR operation instead of OR operation and contrast of the decrypted image is clearer than existing Enhanced Visual Secret Sharing (EVSS) scheme. Also, we are presenting new approach to authenticate graphical password image using 2-out-of-2 EVSS scheme. Which can be used to protect machines with additional security.
A noise‐robust speech input interface for information kiosk terminals

In social amenity apparatus such as information terminals or on-line shopping terminals and ticket vending machines, more natural and smoother communication between machines and humans is made possible by incorporating speech recognition, thus rapidly enhancing operation and convenience. In this paper, we will describe the trial production of an information kiosk terminal equipped with speech recognition and the noise reduction technique adopted as a speech input interface. In general, the aforementioned system equipment is installed in public spaces such as stations. Therefore, robust speech recognition performance is required even in the worst noise environments. For the realization of this antinoise capability, we have used noise reduction based on both a microphone array and spectral subtraction (SS). Experiments with evaluation data recorded in real environments indicate that a recognition performance of over 90% in isolated-word recognition of 216 words uttered by an unspecified speaker is achieved by the combined use of a 32-channel microphone array and SS. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 87(12): 51–61, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjb.20135