Miracle-dz/UniFAR-FTUs huggingface dataset:
Minimale Flussmoden als theoretisches Konzept für die funktionelle Analyse und modulare Beschreibung zellulärer Stoffwechselnetzwerke

The metabolism of a cell consists of chemical transformations and transport processes. Their rates (fluxes) are the result of genetic, translational and metabolic control and therefore carry valuable information about the internal state of a cell. However, metabolic fluxes are hard to determine by experiment and are therefore subject of mathematical prediction methods. In this work, a conceptually new method for the prediction of fluxes in large scale metabolic networks is developed. The method is based on the assumption of optimally evolved synthesis pathways that are regulated independently of each other. This enables organisms: (i) to quickly adapt to a varying and complex environment and (ii) to modularly organize its metabolism in order to restrict internal disturbances and damage to smaller subsystems. The core of this method is the prediction of optimal “synthesis-modules”: stationary flux modes, each of which synthesizes a single metabolite while minimizing or maximizing a so-called objective function. These so-called minimal flux modes (MinModes) are rapidly calculable without knowledge of enzyme kinetics. As such they are suited for the determination of the synthesis capacity and the set of blocked reactions of large networks. Linearly combined, they allow for the representation of complex metabolic tasks. In contrast to previous approaches that optimize for the concerted accomplishment of complex metabolic tasks (e.g. biomass formation), optimizing single syntheses results in a rather suboptimal total network flux. However, with respect to available experimental data the prediction quality is comparable to previous (FBA) approaches. As major benefit, the method relies on a flexible structure that allows for the integration of diverse experimentally observed data. Here, incorporating free Gibbs-energy and metabolite concentration values enabled the prediction of thermodynamically feasible flux modes without prior restriction of flux directions.
An object-based video watermarking

This paper deals with the watermarking problem for irregular shaped objects in video. Extracting the meaningful objects from video, we have implemented the watermarking using the SA-DCT (shape adaptive discrete cosine transform) and conventional rectangular based watermarking using various padding methods. The experimental results show that the SA-DCT method is superior to all other padding methods in terms of the robustness against the image deformations such as lossy compression, additive noise, filtering, and clipping.
Fault tree analysis: 10/sup 20/ prime implicants and beyond

The performances of almost all available fault tree analysis tools are limited by the performance of the prime implicant computation procedure used. All these products manipulate the prime implicants of the fault trees explicitly, so that their complexities are directly related to the number of prime implicants to be generated. The authors present a novel analysis method of coherent as well as noncoherent fault trees that overcomes this limitation because its computational cost is not related to the number of variables, gates, or prime implicants of these trees. The interactive fault tree analyzer MetaPrime based on this new method has been shown by experience to be able to perform in seconds the complete analysis of noncoherent fault trees with more than 10/sup 20/ prime implicants. <<ETX>>
Text-independent speaker recognition by trajectory space comparison

The principle of trajectory space comparison for text-independent speaker recognition and some solutions to the space comparison problem based on vector quantization are presented. The comparison of the recognition rates of different solutions is reported. The experimental system achieves a 99.5% text-independent speaker recognition rate for 23 speakers, using five phrases for training and five for test. A speaker-independent continuous speech recognition system is built in which this principle is used for speaker adaptation. <<ETX>>
Cepstral methods in computational vision

Many computational vision routines can be regarded as recognition and retrieval of echoes in space or time. Cepstral analysis is a powerful nonlinear adaptive signal processing methodology widely used in many areas such as: echo retrieval and removal, speech processing and phoneme chunking, radar and sonar processing, seismology, medicine, image deblurring and restoration, and signal recovery. The aim of this paper is: (1) To provide a brief mathematical and historical review of cepstral techniques. (2) To introduce computational and performance improvements to power and differential cepstrum for use in detection of echoes; and to provide a comparison between these methods and the traditional cepstral techniques. (3) To apply cepstrum to visual tasks such as motion analysis and trinocular vision. And (4) to draw a brief comparison between cepstrum and other matching techniques. The computational and performance improvements introduced in this paper can e applied in other areas that frequently utilize cepstrum.
Human Eye Iris Recognition Using Discrete 2d Reverse Biorthogonal Wavelet 6.8

Based on unique features possessed by an individual, the biometric system provides automatic identification of the person. There have been various implementations using biometric especially for identification and verification cases. In general, typical iris recognition follows the approach of image processing and computer vision. This approach contains various stages-image segmentation, image normalization, feature extraction and image recognition. Iris Biometry has been proposed as sound measure. In this paper, an iris recognition system is presented with four steps. First, image segmentation is performed using Canny Edge Detector followed by iris Circular Hough transformation (CHT) ,and is able to localize the iris and pupil regions. The segmented iris is further normalized. Then features are extracted using discrete 2D reverse biorthogonal wavelet 6.8. Finally, the iris codes are compared. The proposed system gives a high recognition rate of 99.82% whereas the FAR and FRR values are calculated the lowest as compared to existing systems. The proposed method is simple and effective. The system is implemented in MATLAB.
An emerging global knowledge management platform: The case of iBridge

Purpose – This paper seeks to serve as an introduction to a networking platform called iBridge, recently launched by the administrative office of Zhongguancun Haidian Science Park (HSP) in Beijing, China. With the goal of enabling knowledge sharing and collaboration between members and businesses across the world, iBridge has evolved to include features such as communities, blogs, search, recommendation and content customization. The emergence of iBridge is viewed in the context of China's national innovation policy, paying specific attention to the role that collaboration plays as a means of fostering the exchange of ideas and innovation. The paper also aims to discuss the challenges involved in adopting this approach.Design/methodology/approach – The information for this paper was gathered through visits by the author to HSP in 2006 and 2008, as well as through secondary written and web‐based sources.Findings – The paper finds that, since its inception in 2006, the iBridge platform has incorporated many.
A Family History Intervention

This article describes the effect of individualized counseling using family history data and objective cardiovascular risk factors on intent to change and actual exercise behavior in a diverse sample of working adults. Using a longitudinal, quasi-Bxperimental, crossover design, objective data (blood lipids, glucose, blood pressure, and body mass index) and subjective data (awareness of heart disease risk, depression, spirituality, and knowledge of family history) were collected from 91 (mostly female and with a mean age of 45 years) primary and secondary teachers in a southwestern city. The Transtheoretical Model of Change guided the study and measured intent to exercise. Objective risks in this sample mirrored national indices of risk for obesity and abnormal lipids. Although some participants increased their exercise, no significant differences were found between the groups in exercise behavior at 6 and 12 months. Using knowledge of family history to raise awareness and encourage lifestyle changes related to cardiovascular risk warrants further study.
Adenoid and Tonsil Hypertrophy in Children and Facial Malformations

The controversy over the effect of nasal breathing in musculoskeletal facial development has continued over the decades. Although today it is better understood how facial bones grow and the hormonal effect on them, further well-controlled studies with larger populations are still needed to establish a direct relationship between obstruction of the upper airway and poor facial development.
Enriching language learning through a multimedia corpus

Abstract Until recently, use has been made almost exclusively of text-based concordancers in the analysis of spoken corpora. This article discusses research being carried out on Padua University's Multimedia English Corpus (Padova MEC) using the multimodal concordancer MCA (Multimodal Corpus Authoring System, Baldry, 2005). This highly innovative concordancer enables the retrieval of parts of video and audio from a tagged corpus and access to examples of language in context, thereby providing non-verbal information about the environment, the participants and their moods, details that can be gleaned from a combination of word, sound, image and movement. This is of use to language learners of all levels because if “communication is to be successful, a relevant context has to be constructed by the discourse participants” (Braun, 2005: 52). In other words, transcripts alone are not sufficient if learners are to have anything like participant knowledge and comprehend spoken language. In the article it will be demonstrated how language functions expressed in the multimedia corpus of spoken English are retrieved using MCA. Online learning materials based on the multimodal concordances take into consideration not only language, but also the way in which it co-patterns with other semiotic resources, thereby raising the issue of the importance of learner awareness of the multimodal nature of communication.
A Practical Scheme for Induction Motor Modelling and Speed Control

A practical scheme for induction motor modelling and speed control based on field oriented control is presented in this paper. Simplified model of the induction motor is constructed for simulations, which is time-saving and very suitable for controller design in Matlab/Simulink. Actual rotor speed signal is measured to modify the original rotor flux observer, which cannot perform well at low speeds, and conventional proportional-integral controllers are used in both speed and current loops for a desired speed. Comparative simulations and experimental results demonstrate the effectiveness of the proposed scheme, and the induction motor performs well at both high and low speeds.
Semisupervised Learning Using the AdaBoost Algorithm with SVM-KNN

In this paper, we focus on solving the classification problem by using semisupervised learning strategy. Traditional classifiers are constructed based on labeled data in supervised learning. Labeled data, however, are often difficult, expensive or time consuming to obtain, as they require the efforts of experienced human annotators. Unlabeled data are significantly easier to obtain without human efforts. Thus, we use AdaBoost algorithm with SVM-KNN classifier to apply semisupervised learning problem and improve the classifier performance. Experimental results on both artificial and UCI data sets show that the proposed methodology can reduce the error rate.
Scheduling algorithm for fairness improvement among subscribers in multihop wireless networks

Recently, attention has focused on multihop wireless networks capable of expanding the communication area by employing wireless relays between nodes and access points. However, the problem in a multihop wireless network is differences arise in the throughput caused by the number of hops from the base station connected to wired networks. In this paper, we propose a scheduling algorithm which solves this problem. In this proposal, the uplink packets and downlink packets are queued separately, and the uplink packets are classified into packets originated within the node and forwarded packets from adjacent wireless nodes and queued. When the node transmits a packet, the fairness among the nodes is improved by scheduling based on the source identifiers of the queued packets. The results of a performance evaluation using a network simulator verified a maximum tenfold improvement in the fairness among the subscribers compared to typical schemes. © 2006 Wiley Periodicals, Inc. Electron Comm Jpn Pt 1, 90(4): 11–22, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecja.20364
Some tools for attacking secure communication systems employing chaotic carriers

We present a review of methods which can be used to uncover the information signal hidden using one of so-called chaos communication methodologies. All of the known secure communication methods employing chaotic carriers are shown to be of very low security. Hidden messages can be found using extremely simple reasoning and straightforward computational methods. We point out also that none of the methodologies proposed so far uses the properties of the chaotic signal. The only property exploited is the sensitivity (instability) of the transmitter/receiver pair to parameter and initial condition changes.
Design and implementation of spatial knowledge grid for integrated spatial analysis

Supported by spatial information grid(SIG), the spatial knowledge grid (SKG) for integrated spatial analysis utilizes the middleware technology in constructing the spatial information grid computation environment and spatial information service system, develops spatial entity oriented spatial data organization technology, carries out the profound computation of the spatial structure and spatial process pattern on the basis of Grid GIS infrastructure, spatial data grid and spatial information grid (specialized definition). At the same time, it realizes the complex spatial pattern expression and the spatial function process simulation by taking the spatial intelligent agent as the core to establish space initiative computation. Moreover through the establishment of virtual geographical environment with man-machine interactivity and blending, complex spatial modeling, network cooperation work and spatial community decision knowledge driven are achieved. The framework of SKG is discussed systematically in this paper. Its implement flow and the key technology with examples of overlay analysis are proposed as well.
PROCESSING, CATALOGUING AND DISTRIBUTION OF UAS IMAGES IN NEAR REAL TIME

Abstract. Why are UAS such a hype? UAS make the data capture flexible, fast and easy. For many applications this is more important than a perfect photogrammetric aerial image block. To ensure, that the advantage of a fast data capturing will be valid up to the end of the processing chain, all intermediate steps like data processing and data dissemination to the customer need to be flexible and fast as well. GEOSYSTEMS has established the whole processing workflow as server/client solution. This is the focus of the presentation. Depending on the image acquisition system the image data can be down linked during the flight to the data processing computer or it is stored on a mobile device and hooked up to the data processing computer after the flight campaign. The image project manager reads the data from the device and georeferences the images according to the position data. The meta data is converted into an ISO conform format and subsequently all georeferenced images are catalogued in the raster data management System ERDAS APOLLO. APOLLO provides the data, respectively the images as an OGC-conform services to the customer. Within seconds the UAV-images are ready to use for GIS application, image processing or direct interpretation via web applications – where ever you want. The whole processing chain is built in a generic manner. It can be adapted to a magnitude of applications. The UAV imageries can be processed and catalogued as single ortho imges or as image mosaic. Furthermore, image data of various cameras can be fusioned. By using WPS (web processing services) image enhancement, image analysis workflows like change detection layers can be calculated and provided to the image analysts. The processing of the WPS runs direct on the raster data management server. The image analyst has no data and no software on his local computer. This workflow is proven to be fast, stable and accurate. It is designed to support time critical applications for security demands – the images can be checked and interpreted in near real-time. For sensible areas it gives you the possibility to inform remote decision makers or interpretation experts in order to provide them situations awareness, wherever they are. For monitoring and inspection tasks it speeds up the process of data capture and data interpretation. The fully automated workflow of data pre-processing, data georeferencing, data cataloguing and data dissemination in near real time was developed based on the Intergraph products ERDAS IMAGINE, ERDAS APOLLO and GEOSYSTEMS METAmorph! IT. It is offered as adaptable solution by GEOSYSTEMS GmbH.
A Method to Extract Sentences with Protein Functional Information from Literature by Iterative Learning of the Corpus

We are developing PROFESS, a system to assist with the extraction of protein functional site information from the literature related to protein structural analysis. In this system, the sentences with functional information are first extracted. This paper proposes the complementary use of the protein structure data, keywords and patterns to extract the target sentences. In the proposed method, the sentences in the literature are expressed in vector using these three features, which are learnt by the SVM. As the accuracy of the SVM depends on the number of effective vector elements, we propose a method to automatically extract patterns to add as new vector elements and obtain a higher value in accuracy. There is a problem of matching of the patterns to the sentences when any proper noun tag is expressed adjacent to residue tag. We defined two rules to eliminate these unnecessary tags so that the patterns can match to the sentences. The proposed method was applied to five documents related to structural analysis of protein for extracting sentences with protein functional information, where eight literatures were used for the feedback for each of the experiment literatures. The average recall value and F value were 0.96 and 0.69, respectively. It was confirmed that the increase of the number of the vector elements lead to a higher performance in the sentence extraction.
Performance Overhead Evaluation of Multi-cloud Computing with Secret Sharing approach Based Model

Data security is one of the most critical aspects in a cloud computing environment due to the sensitivity and importance of the information stored in the cloud, as is the trustworthiness of the cloud service provider. The risk of malicious insiders in the cloud and the failure of cloud services have received intense attention by cloud users. The aim of this work is to analyse and evaluate an existing model called Multi-clouds Databases (MCDB) which uses multi-clouds instead of single cloud service provider, such as in Amazon cloud service, and compare it with other cryptographic based model. Our MCDB model incorporated Shamir’s secret sharing approach. In addition, it adopted a triple modular redundancy (TMR) technique with sequential method to improve data trustworthiness of cloud computing system and then enhance the data security aspect. The evaluation is done through simulation using cloud computing simulator. It shows a significant improvement in performance for data storage and data retrieval compared to a cloud cryptographic based model. This improvement in performance in MCDB model is due to the computational complexity of data encryption/decryption during a query execution in the cryptographic based model.
THE STRUCTURAL QUADRANTS METHOD: A NEW APPROACH TO THE ASSESSMENT OF CONSTRUCT SYSTEM COMPLEXITY VIA THE REPERTORY GRID

This article presents a new mathematical method (the Structural Quadrants Method) for the assessment of construct system complexity via the repertory grid. The Structural Quadrants Method (SQM) is presented step by step, and its sensitivity to grid structure is illustrated by applying it to five case studies. A validational study demonstrating the discriminative power of the SQM and comparing it to traditional measures is included. Results indicate that the SQM discriminates between a group of 11 experts and one of 11 novices in terms of grid complexity as expected (i.e., detecting high degrees of differentiation and integration in the experts' grids and low degrees of differentiation and integration in the novices' grids). The discriminative power of the SQM is unparalleled by the traditional measures of grid structure compared in this article. The article ends with a section on the distinctive advantages of the SQM and some suggestions for future research.
An algorithm for reverse traffic channel rate control for cdma2000 high rate packet data systems

cdma2000 high rate packet data standard is a third generation wireless standard that provides higher download speeds for wireless data users. This paper describes an algorithm to control the data rate at which access terminals transmit data on the reverse traffic channel on this system. The paper also presents results on the reverse traffic channel throughput and outage probability of the system obtained from numerical simulations.
A spread spectrum PRMA protocol with randomized arrival time for microcelluar networks

A spread spectrum PRMA (SSPRMA) protocol with randomized arrival time is proposed in this paper. We analyze its channel utilization, and the probability of voice packet being dropped (Pdrop) by Markov chain analysis. We study the effect of delay capture phenomenon on the performance of this protocol. Packet transmission errors are taken into account in the simulation and the Markov chain analysis. Numerical results prove that delay capture improves the performance of this protocol.
Introducing Preparatory Operations into Concurrency Control in Parallel B-trees

Parallel and distributed B-tree structures and their concurrency control protocols for shared-nothing parallel database systems have been proposed and are being developed in connection with the related technological advancements such as clustered computers. We focus specially on the performance of the concurrency control protocols for parallel B-trees and consider the possibility and suitability of introduction of preemptive split or merge method to them. We propose a protocol, called PO-P, in which preparatory operations are used during traversals of updater processes, and we expect this protocol can serve as a good alternative to the present protocols for parallel B-trees. Keyword parallel shared nothing computers, B-tree, concurrency control protocol, parallel and distributed database systems.