• Journal of KIISE:Computer Systems and Theory
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• v.33 no.7
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• pp.448-453
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• 2006

We extend a parallel depth-first search (DFS) algorithm for planar graphs to deal with (non-planar) solid grid graphs, a subclass of non-planar grid graphs. The proposed algorithm takes time O(log n) with $O(n/sqrt{log\;n})$ processors in Priority PRAM model. In our knowledge, this is the first deterministic NC algorithm for a non-planar graph class.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.377-382
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• 2005

This paper presents a new method for the attitude control of planar space robots. In order to control highly constrained non-linear system such as a 3D space robot, the analytical formulation for the system with complex dynamics and effective control methodology based on the formulation, are not always obtainable. In the proposed method, correspondingly, a non-analytical but effective self-organizing modeling method for controlling a highly constrained system is proposed based on a polynomial data mining algorithm. In order to control the attitude of a planar space robot, it is well known to require inputs characterized by a special pattern in time series with a non-deterministic length. In order to correspond to this type of control paradigm, we adopt the Model Predictive Control (MPC) scheme where the length of the non-deterministic horizon is determined based on implementation cost and control performance. The optimal solution to finding the size of the input pattern is found by a solving two-stage programming problem.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.637-648
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• 2007

This paper presents a sensor fusion method based on indirect Kalman filter(IKF) for error compensation of low-cost inertial sensors and its application to the determination of attitude and position of small flying robots. First, the analysis of the measurement error characteristics to zero input is performed, focusing on the bias due to the temperature variation, to derive a simple nonlinear bias model of low-cost inertial sensors. Moreover, from the experimental results that the coefficients of this bias model possess non-deterministic (stochastic) uncertainties, the bias of low-cost inertial sensors is characterized as consisting of both deterministic and stochastic bias terms. Then, IKF is derived to improve long term stability dominated by the stochastic bias error, fusing low-cost inertial sensor measurements compensated by the deterministic bias model with non-inertial sensor measurement. In addition, in case of using intermittent non-inertial sensor measurements due to the unreliable data link, the upper and lower bounds of the state estimation error covariance matrix of discrete-time IKF are analyzed by solving stochastic algebraic Riccati equation and it is shown that they are dependant on the throughput of the data link and sampling period. To evaluate the performance of proposed method, experimental results of IKF for the attitude determination of a small flying robot are presented in comparison with that of extended Kaman filter which compensates only deterministic bias error model.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.153-154
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• 2022

본 논문에서는 블록체인 기반의 투명성/신뢰성을 제공하는 조작 불가능한 확률 제어 시스템을 제안한다. 해당 시스템은 클라이언트에 의해 질의 된 확률값을 블록체인상에서 산출해냄으로써, Legacy 시스템 아키텍처의 한계인 조작 가능성을 원천적으로 배제할 수 있다. 이는 블록체인 참여 노드 간의 데이터를 동일하게 공유하여 투명성을 확보하고, 이를 기반으로 데이터에 대한 신뢰성을 확보한 확률 제공 기능이다. 특히 해당 시스템은 Private/Permissioned 구조 기반의 블록체인 네트워크를 기반으로 운영 노드에 의해서 유지/관리되어 별도의 트랜잭션 수수료가 블록체인상에서 발생하지 않는다. 또한 Public Blockchain 메인 네트워크상의 미래 블록에 대한 정보를 확률값 산출 Seed에 활용함으로써, Non-deterministic 한 환경을 제공한다. 이는 클라이언트가 확률 질의에 대한 검증 과정을 직접 수행하거나 Third-party 검증을 통해 확률값에 대한 조작 여부를 확인할 수 있다.

• The KIPS Transactions:PartA
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• v.17A no.1
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• pp.9-18
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• 2010

Races that occur in shared-memory parallel programs such as OpenMP programs must be detected for debugging because of causing unintended non-deterministic results. Previous works which verify the existence of these races on-the-fly are limited to the programs without internal non-determinism. But in the programs with internal non-determinism, such works need at least N! execution instances for each critical section to verify the existence of races, where N is the degree of maximum parallelism. This paper presents a preprocessor that statically analyzes the locations of non-deterministic accesses using program slicing and can detect apparent races as well as potential races through single execution using the analyzed information. The suggested tool can deterministically monitor non-deterministic accesses to occur in OpenMP programs so that this tool can verify the existence of races even if it is used any race detection protocol which can apply to programs with critical section. To prove empirically this tool, we have experimented using a set of benchmark programs such as synthetic programs that involve non-deterministic accesses, OpenMP Microbenchmark, NAS Parallel Benchmark, and OpenMP application programs.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.737-744
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• 2018

The RSA cryptosystem is a one of the first public-key cryptosystems and is widely used for secure data transmission and electric signature. The security of the RSA cryptosystem is based on the difficulty of factoring large numbers.. Though many studies on finding methods for factoring large numbers are going on, the results of that are all experimental or probabilistic. We, in this paper, construct an algorithm for finding large prime factors of integers without factoring integers using properties of the structure of semigroup of imaginary quadratic order and non-invertible ideal, then propose our methods foe deterministic attack against RSA cryptosystem.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.49-60
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• 2023

The amount of data generated by electronic systems through e-commerce, social networks, and data computation has risen. However, the security of data has always been a challenge. The problem is not with the quantity of data but how to secure the data by ensuring its confidentiality and privacy. Though there are several research on cloud data security, this study proposes a security scheme with the lowest execution time. The approach employs a non-linear time complexity to achieve data confidentiality and privacy. A symmetric algorithm dubbed the Non-Deterministic Cryptographic Scheme (NCS) is proposed to address the increased execution time of existing cryptographic schemes. NCS has linear time complexity with a low and unpredicted trend of execution times. It achieves confidentiality and privacy of data on the cloud by converting the plaintext into Ciphertext with a small number of iterations thereby decreasing the execution time but with high security. The algorithm is based on Good Prime Numbers, Linear Congruential Generator (LGC), Sliding Window Algorithm (SWA), and XOR gate. For the implementation in C, thirty different execution times were performed and their average was taken. A comparative analysis of the NCS was performed against AES, DES, and RSA algorithms based on key sizes of 128kb, 256kb, and 512kb using the dataset from Kaggle. The results showed the proposed NCS execution times were lower in comparison to AES, which had better execution time than DES with RSA having the longest. Contrary, to existing knowledge that execution time is relative to data size, the results obtained from the experiment indicated otherwise for the proposed NCS algorithm. With data sizes of 128kb, 256kb, and 512kb, the execution times in milliseconds were 38, 711, and 378 respectively. This validates the NCS as a Non-Deterministic Cryptographic Algorithm. The study findings hence are in support of the argument that data size does not determine the execution.

• Communications for Statistical Applications and Methods
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• v.26 no.1
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• pp.27-34
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• 2019

We study the effect of detrending on the coherency between two time series processes. Many economic and financial time series variables include nonstationary components; however, we analyze the two most popular cases of stochastic and deterministic trends. We analyze the asymptotic behavior of coherency under incorrect detrending, which includes the cases of first-differencing the deterministic trend process and, conversely, the time trend removal of the unit root process. A simulation study is performed to investigate the finite sample performance of the sample coherency due to incorrect detrending. Our work is expected to draw attention to the possible distortion of coherency when the series are incorrectly detrended. Further, our results can extend to various specification of trends in aggregate time series variables.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.12
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• pp.907-917
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• 2006

In this paper, we propose a strategy to improve fault-tolerance and scalability of replicated services in mobile agent systems by applying an appropriate passive replication protocol for each replicated service according to whether the service is deterministic or non-deterministic. For this purpose, two passive replication protocols, PRPNS and PRPDS, are designed for non-deterministic and deterministic services respectively. They both allow visiting mobile agents to be forwarded to and execute their tasks on any node performing a service agent, not necessarily the primary agent. Especially, in the protocol PRPDS, after a backup service agent has received each mobile agent request and obtained its delivery sequence number from the primary service agent, the backup is responsible for processing the request and coordinating with the other replica service agents. Therefore, our strategy using the two proposed protocols can promise high scalability of replicated services a large number of mobile agents attempt to access in mobile agent systems. Our simulation results show that the proposed strategy performs much better than the one using only the traditional passive replication protocol.

• Steel and Composite Structures
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• v.44 no.5
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• pp.651-676
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• 2022

Most of the experimental, theoretical, and numerical studies on the stability of functionally graded composites are deterministic, while there are full of complex interactions of variables with an inherently probabilistic nature, this paper presents a non-intrusive framework to investigate the stochastic nonlinear buckling behaviors of porous functionally graded cylindrical shells exposed to inevitable source-uncertainties. Euler-Lagrange equations are theoretically derived based on the three variable refined shear deformation theory. Closed-form solutions for the shell buckling loads are achieved by solving the deterministic eigenvalue problems. The analytical results are verified with numerical results obtained from finite element analyses that are conducted in the commercial software ABAQUS. The non-intrusive framework is completed by integrating the Monte Carlo simulation with the verified closed-form solutions. The convergence studies are performed to determine the effective pseudorandom draws of the simulation. The accuracy and efficiency of the framework are verified with statistical results that are obtained from the first and second-order perturbation techniques. Eleven cases of individual and compound uncertainties are investigated. Sensitivity analyses are conducted to figure out the five cases that have profound perturbative effects on the shell buckling loads. Complete probability distributions of the first three critical buckling loads are completely presented for each profound uncertainty case. The effects of the shell thickness, volume fraction index, and stochasticity degree on the shell buckling load under compound uncertainties are studied. There is a high probability that the shell has non-unique buckling modes in stochastic environments, which should be known for reliable analysis and design of engineering structures.