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Tytuł:
Sender-equivocable encryption schemes secure against chosen-ciphertext attacks revisited
Autorzy:
Huang, Z.
Liu, S.
Qin, B.
Chen, K.
Powiązania:
https://bibliotekanauki.pl/articles/330140.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
sender equivocable encryption
chosen ciphertext attack
cross authentication code
Opis:
Fehr et al. (2010) proposed the first sender-equivocable encryption scheme secure against chosen-ciphertext attacks (NCCCA) and proved that NC-CCA security implies security against selective opening chosen-ciphertext attacks (SO-CCA). The NC-CCA security proof of the scheme relies on security against substitution attacks of a new primitive, the “cross-authentication code”. However, the security of the cross-authentication code cannot be guaranteed when all the keys used in the code are exposed. Our key observation is that, in the NC-CCA security game, the randomness used in the generation of the challenge ciphertext is exposed to the adversary. Based on this observation, we provide a security analysis of Fehr et al.'s scheme, showing that its NC-CCA security proof is flawed. We also point out that the scheme of Fehr et al. encrypting a single-bit plaintext can be refined to achieve NC-CCA security, free of the cross-authentication code. Furthermore, we propose the notion of “strong cross-authentication code”, apply it to Fehr et al. 's scheme, and show that the new version of the latter achieves NC-CCA security for multi-bit plaintexts.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2015, 25, 2; 415-430
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Delay-dependent Asymptotic Stabilitzation for Uncertain Time-delay Systems with Saturating Actuators
Autorzy:
Liu, P. L.
Powiązania:
https://bibliotekanauki.pl/articles/908496.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
stabilność
system opóźniania
równanie Riccatiego
stability
delay-dependency
time delay system
Riccati equation
Opis:
This paper concerns the issue of robust asymptotic stabilization for uncertain time-delay systems with saturating actuators. Delay-dependent criteria for robust stabilization via linear memoryless state feedback have been obtained. The resulting upper bound on the delay time is given in terms of the solution to a Riccati equation subject to model transformation. Finally, examples are presented to show the effectiveness of our result.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2005, 15, 1; 45-51
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multiple-instance learning with pairwise instance similarity
Autorzy:
Yuan, L.
Liu, J.
Tang, X.
Powiązania:
https://bibliotekanauki.pl/articles/330821.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
multiple instance learning
instance selection
similarity
support vector machine (SVM)
uczenie maszynowe
podobieństwo
metoda wektorów wspomagających
Opis:
Multiple-Instance Learning (MIL) has attracted much attention of the machine learning community in recent years and many real-world applications have been successfully formulated as MIL problems. Over the past few years, several Instance Selection-based MIL (ISMIL) algorithms have been presented by using the concept of the embedding space. Although they delivered very promising performance, they often require long computation times for instance selection, leading to a low efficiency of the whole learning process. In this paper, we propose a simple and efficient ISMIL algorithm based on the similarity of pairwise instances within a bag. The basic idea is selecting from every training bag a pair of the most similar instances as instance prototypes and then mapping training bags into the embedding space that is constructed from all the instance prototypes. Thus, the MIL problem can be solved with the standard supervised learning techniques, such as support vector machines. Experiments show that the proposed algorithm is more efficient than its competitors and highly comparable with them in terms of classification accuracy. Moreover, the testing of noise sensitivity demonstrates that our MIL algorithm is very robust to labeling noise.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2014, 24, 3; 567-577
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hospitalization patient forecasting based on multi-task deep learning
Autorzy:
Zhou, Min
Huang, Xiaoxiao
Liu, Haipeng
Zheng, Dingchang
Powiązania:
https://bibliotekanauki.pl/articles/2201025.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
hospitalization patient
neural network
multitask learning
pacjent hospitalizowany
sieć neuronowa
nauka wielozadaniowa
Opis:
Forecasting the number of hospitalization patients is important for hospital management. The number of hospitalization patients depends on three types of patients, namely, admission patients, discharged patients, and inpatients. However, previous works focused on one type of patients rather than the three types of patients together. In this paper, we propose a multi-task forecasting model to forecast the three types of patients simultaneously. We integrate three neural network modules into a unified model for forecasting. Besides, we extract date features of admission and discharged patient flows to improve forecasting accuracy. The algorithm is trained and evaluated on a real-world data set of a one-year daily observation of patient numbers in a hospital. We compare the performance of our model with eight baselines over two real-word data sets. The experimental results show that our approach outperforms other baseline algorithms significantly.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2023, 33, 1; 151--162
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On The Stability of Neutral-type Uncertain Systems With Multiple Time Delays
Autorzy:
Liu, P. L.
Powiązania:
https://bibliotekanauki.pl/articles/911133.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
twierdzenie Razumikhina
opóźnienie czasowe
układ niepewny
Razumikhin-type theorem,
time delay
neutral type uncertain systems
Opis:
The problems of both single and multiple delays for neutral-type uncertain systems are considered. First, for single neutral time delay systems, based on a Razumikhin-type theorem, some delay-dependent stability criteria are derived in terms of the Lyapunov equation for various classes of model transformation and decomposition techniques. Second, robust control for neutral systems with multiple time delays is considered. Finally, we demonstrate numerical examples to illustrate the effectiveness of the proposed approaches. Compared with results existing in the literature, our methods are shown to be superior to them.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2005, 15, 2; 221-229
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Curve skeleton extraction via k-nearest-neighbors based contraction
Autorzy:
Zhou, Jianling
Liu, Ji
Zhang, Min
Powiązania:
https://bibliotekanauki.pl/articles/331332.pdf
Data publikacji:
2020
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
curve skeleton
points contraction
point cloud
k nearest neighbors
szkieletyzacja
chmura punktów
metoda k najbliższych sąsiadów
Opis:
We propose a skeletonization algorithm that is based on an iterative points contraction. We make an observation that the local center that is obtained via optimizing the sum of the distance to k nearest neighbors possesses good properties of robustness to noise and incomplete data. Based on such an observation, we devise a skeletonization algorithm that mainly consists of two stages: points contraction and skeleton nodes connection. Extensive experiments show that our method can work on raw scans of real-world objects and exhibits better robustness than the previous results in terms of extracting topology-preserving curve skeletons.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2020, 30, 1; 123-132
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Synthesis and Evaluation Analysis of the Indicator Information in Nuclear Safeguards Applications by Computing With Words
Autorzy:
Liu, J.
Ruan, D.
Carchon, R.
Powiązania:
https://bibliotekanauki.pl/articles/908042.pdf
Data publikacji:
2002
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
fizyka
safeguards
computing with words
decision-making
physical model
Opis:
This paper aims at the handling and treatment of nuclear safeguard relevant information by using a linguistic assessment approach. This is based on a hierarchical analysis of a State's nuclear activities in a multi-layer structure of the evaluation model. After a hierarchical analysis of the State's nuclear activities on the basis of the IAEA Physical Model, the addressed objective is divided into several less complex levels. The overall evaluation can be obtained step by step from those lower levels. Special emphasis is put on the synthesis and evaluation analysis of the Physical Model indicator information. Accordingly, the aggregation process with the consideration of the different kinds of qualitative criteria is in focus. Especially, the symbolic approach is considered by the direct computation on linguistic values instead of the approximation approach using the associated membership function. In this framework, several kinds of ordinal linguistic aggregation operators are presented and analyzed. The application of these linguistic aggregation operators to the combination of the Physical Model indicator information is provided. An example is given to support and clarify the mathematical formalism.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2002, 12, 3; 449-462
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Variable structure observer design for a class of uncertain systems with a time-varying delay
Autorzy:
Liu W., J.
Powiązania:
https://bibliotekanauki.pl/articles/330119.pdf
Data publikacji:
2012
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
obserwator
niezmienniczość
uogólniona odwrotność macierzy
variable structure observer
invariance property
generalized matrix inverse approach
Opis:
Design of a state observer is an important issue in control systems and signal processing. It is well known that it is difficult to obtain the desired properties of state feedback control if some or all of the system states cannot be directly measured. Moreover, the existence of a lumped perturbation and/or a time delay usually reduces the system performance or even produces an instability in the closed-loop system. Therefore, in this paper, a new Variable Structure Observer (VSO) is proposed for a class of uncertain systems subjected to a time varying delay and a lumped perturbation. Based on the strictly positive real concept, the stability of the equivalent error system is verified. Based on the generalized matrix inverse approach, the global reaching condition of the sliding mode of the error system is guaranteed. Also, the proposed variable structure observer will be shown to possess the invariance property in relation to the lumped perturbation, as the traditional variable structure controller does. Furthermore, two illustrative examples with a series of computer simulation studies are given to demonstrate the effectiveness of the proposed design method.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2012, 22, 3; 575-583
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Simultaneous disturbance compensation and Hi/H optimization in fault detection of UAVs
Autorzy:
Liu, H.
Zhong, M.
Yang, R.
Powiązania:
https://bibliotekanauki.pl/articles/331045.pdf
Data publikacji:
2018
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
fault detection
disturbance compensation
unmanned aerial vehicle
detekcja uszkodzeń
kompensacja zakłóceń
bezzałogowy statek powietrzny
Opis:
This paper deals with the problem of robust fault detection (FD) for an unmanned aerial vehicle (UAV) flight control system (FCS). A nonlinear model to describe the UAV longitudinal motions is introduced, in which multiple sources of disturbances include wind effects, modeling errors and sensor noises are classified into groups. Then the FD problem is formulated as fault detection filter (FDF) design for a kind of nonlinear discrete time varying systems subject to multiple disturbances. In order to achieve robust FD performance against multiple disturbances, simultaneous disturbance compensation and Hi/H optimization are carried out in designing the FDF. The optimality of the proposed FDF is shown in detail. Finally, both simulations and real flight data are applied to validate the proposed method. An improvement of FD performance is achieved compared with the conventional Hi/H-FDF.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2018, 28, 2; 349-362
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An active exploration method for data efficient reinforcement learning
Autorzy:
Zhao, Dongfang
Liu, Jiafeng
Wu, Rui
Cheng, Dansong
Tang, Xianglong
Powiązania:
https://bibliotekanauki.pl/articles/331205.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
reinforcement learning
information entropy
PILCO
data efficiency
uczenie ze wzmocnieniem
entropia informacji
wydajność danych
Opis:
Reinforcement learning (RL) constitutes an effective method of controlling dynamic systems without prior knowledge. One of the most important and difficult problems in RL is the improvement of data efficiency. Probabilistic inference for learning control (PILCO) is a state-of-the-art data-efficient framework that uses a Gaussian process to model dynamic systems. However, it only focuses on optimizing cumulative rewards and does not consider the accuracy of a dynamic model, which is an important factor for controller learning. To further improve the data efficiency of PILCO, we propose its active exploration version (AEPILCO) that utilizes information entropy to describe samples. In the policy evaluation stage, we incorporate an information entropy criterion into long-term sample prediction. Through the informative policy evaluation function, our algorithm obtains informative policy parameters in the policy improvement stage. Using the policy parameters in the actual execution produces an informative sample set; this is helpful in learning an accurate dynamic model. Thus, the AEPILCOalgorithm improves data efficiency by learning an accurate dynamic model by actively selecting informative samples based on the information entropy criterion. We demonstrate the validity and efficiency of the proposed algorithm for several challenging controller problems involving a cart pole, a pendubot, a double pendulum, and a cart double pendulum. The AEPILCO algorithm can learn a controller using fewer trials compared to PILCO. This is verified through theoretical analysis and experimental results.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2019, 29, 2; 351-362
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systems
Autorzy:
Tong, S.
Liu, C.
Li, Y.
Powiązania:
https://bibliotekanauki.pl/articles/908148.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system nieliniowy
sterowanie rozmyte
sprzężenie zwrotne
nonlinear system
adaptive fuzzy control
backstepping
small-gain approach
K-filters
Opis:
In this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly parameterized, and no prior knowledge of their bounds is available. In recursive design, fuzzy logic systems are used to approximate unstructured uncertainties, and K-filters are designed to estimate unmeasured states. By combining backstepping design and a small-gain theorem, a stable adaptive fuzzy output feedback control scheme is developed. It is proven that the proposed adaptive fuzzy control approach can guarantee the all the signals in the closed-loop system are uniformly ultimately bounded, and the output of the controlled system converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by a simulation example and some comparisons.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2010, 20, 4; 637-653
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Using a vision cognitive algorithm to schedule virtual machines
Autorzy:
Zhao, J.
Mhedheb, Y.
Tao, J.
Jrad, F.
Liu, Q.
Streit, A.
Powiązania:
https://bibliotekanauki.pl/articles/330838.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
cloud computing
vision cognitive algorithm
VM scheduling
simulation
chmura obliczeniowa
algorytm poznawczy
szeregowanie
symulacja
Opis:
Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality of services. A large cloud center is normally equipped with several hundred thousand physical machines. The mission of the scheduler is to select the best one to host a virtual machine. This is an NP-hard global optimization problem with grand challenges for researchers. This work studies the Virtual Machine (VM) scheduling problem on the cloud. Our primary concern with VM scheduling is the energy consumption, because the largest part of a cloud center operation cost goes to the kilowatts used. We designed a scheduling algorithm that allocates an incoming virtual machine instance on the host machine, which results in the lowest energy consumption of the entire system. More specifically, we developed a new algorithm, called vision cognition, to solve the global optimization problem. This algorithm is inspired by the observation of how human eyes see directly the smallest/largest item without comparing them pairwisely. We theoretically proved that the algorithm works correctly and converges fast. Practically, we validated the novel algorithm, together with the scheduling concept, using a simulation approach. The adopted cloud simulator models different cloud infrastructures with various properties and detailed runtime information that can usually not be acquired from real clouds. The experimental results demonstrate the benefit of our approach in terms of reducing the cloud center energy consumption.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2014, 24, 3; 535-550
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fast leak detection and location of gas pipelines based on an adaptive particle filter
Autorzy:
Liu, M.
Zang, S.
Zhou, D.
Powiązania:
https://bibliotekanauki.pl/articles/908443.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
rurociąg gazowy
diagnozowanie wycieku
lokalizowanie wycieku
filtr cząsteczkowy
gas pipeline
leak detection and location
particle filter
Opis:
Leak detection and location play an important role in the management of a pipeline system. Some model-based methods, such as those based on the extended Kalman filter (EKF) or based on the strong tracking filter (STF), have been presented to solve this problem. But these methods need the nonlinear pipeline model to be linearized. Unfortunately, linearized transformations are only reliable if error propagation can be well approximated by a linear function, and this condition does not hold for a gas pipeline model. This will deteriorate the speed and accuracy of the detection and location. Particle filters are sequential Monte Carlo methods based on point mass (or “particle”) representations of probability densities, which can be applied to estimate states in nonlinear and non-Gaussian systems without linearization. Parameter estimation methods are widely used in fault detection and diagnosis (FDD), and have been applied to pipeline leak detection and location. However, the standard particle filter algorithm is not applicable to time-varying parameter estimation. To solve this problem, artificial noise has to be added to the parameters, but its variance is difficult to determine. In this paper, we propose an adaptive particle filter algorithm, in which the variance of the artificial noise can be adjusted adaptively. This method is applied to leak detection and location of gas pipelines. Simulation results show that fast and accurate leak detection and location can be achieved using this improved particle filter.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2005, 15, 4; 541-550
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Finite-time adaptive modified function projective multi-lag generalized compound synchronization for multiple uncertain chaotic systems
Autorzy:
Li, Q.
Liu, S.
Chen, Y.
Powiązania:
https://bibliotekanauki.pl/articles/331032.pdf
Data publikacji:
2018
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
finite-time adaptive control
unknown parameter
chaotic system
sterowanie adaptacyjne
parametr nieznany
układ chaotyczny
Opis:
In this paper, for multiple different chaotic systems with fully unknown parameters, a novel synchronization scheme called ‘modified function projective multi-lag generalized compound synchronization’ is put forward. As an advantage of the new method, not only the addition and subtraction, but also the multiplication of multiple chaotic systems are taken into consideration. This makes the signal hidden channels more abundant and the signal hidden methods more flexible. By virtue of finite-time stability theory and an adaptive control technique, a finite-time adaptive control scheme is established to realize the finite-time synchronization and to properly evaluate the unknown parameters. A detailed theoretical derivation and a specific numerical simulation demonstrate the feasibility and validity of the advanced scheme.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2018, 28, 4; 613-624
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Finding robust transfer features for unsupervised domain adaptation
Autorzy:
Gao, Depeng
Wu, Rui
Liu, Jiafeng
Fan, Xiaopeng
Tang, Xianglong
Powiązania:
https://bibliotekanauki.pl/articles/331356.pdf
Data publikacji:
2020
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
unsupervised domain adaptation
feature reduction
generalized eigenvalue decomposition
object recognition
adaptacja domeny
redukcja cech
rozkład wartości własnych
rozpoznawanie obiektu
Opis:
An insufficient number or lack of training samples is a bottleneck in traditional machine learning and object recognition. Recently, unsupervised domain adaptation has been proposed and then widely applied for cross-domain object recognition, which can utilize the labeled samples from a source domain to improve the classification performance in a target domain where no labeled sample is available. The two domains have the same feature and label spaces but different distributions. Most existing approaches aim to learn new representations of samples in source and target domains by reducing the distribution discrepancy between domains while maximizing the covariance of all samples. However, they ignore subspace discrimination, which is essential for classification. Recently, some approaches have incorporated discriminative information of source samples, but the learned space tends to be overfitted on these samples, because they do not consider the structure information of target samples. Therefore, we propose a feature reduction approach to learn robust transfer features for reducing the distribution discrepancy between domains and preserving discriminative information of the source domain and the local structure of the target domain. Experimental results on several well-known cross-domain datasets show that the proposed method outperforms state-of-the-art techniques in most cases.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2020, 30, 1; 99-112
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł

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