Let f be a Boolean function in n variables. The Möbius transform and its converse of f can describe the transformation behaviors between the truth table of f and the coefficients of the monomials in the algebraic normal form representation of f. In this letter, we develop the Möbius transform and its converse into a more generalized form, which also includes the known result given by Reed in 1954. We hope that our new result can be used in the design of decoding schemes for linear codes and the cryptanalysis for symmetric cryptography. We also apply our new result to verify the basic idea of the cube attack in a very simple way, in which the cube attack is a powerful technique on the cryptanalysis for symmetric cryptography.

In this paper, we present an algorithm that counts the number of empty quadrilaterals whose corners are chosen from a given set S of n points in general position. Our algorithm can separately count the number of convex or non-convex empty quadrilaterals in O(T) time, where T denotes the number of empty triangles in S. Note that T varies from Ω(n2) and O(n3) and the expected value of T is known to be Θ(n2) when the n points in S are chosen uniformly and independently at random from a convex and bounded body in the plane. We also show how to enumerate all convex and/or non-convex empty quadrilaterals in S in time proportional to the number of reported quadrilaterals, after O(T)-time preprocessing.

Multivariate public key cryptosystem (MPKC) is one of the major post quantum cryptosystems (PQC), and the National Institute of Standards and Technology (NIST) recently selected four MPKCs as candidates of their PQC. The security of MPKC depends on the hardness of solving systems of algebraic equations over finite fields. In particular, the multivariate quadratic (MQ) problem is that of solving such a system consisting of quadratic polynomials and is regarded as an important research subject in cryptography. In the Fukuoka MQ challenge project, the hardness of the MQ problem is discussed, and algorithms for solving the MQ problem and the computational results obtained by these algorithms are reported. Algorithms for computing Gröbner basis are used as the main tools for solving the MQ problem. For example, the F4 algorithm and M4GB algorithm have succeeded in solving many instances of the MQ problem provided by the project. In this paper, based on the F4-style algorithm, we present an efficient algorithm to solve the MQ problems with dense polynomials generated in the Fukuoka MQ challenge project. We experimentally show that our algorithm requires less computational time and memory for these MQ problems than the F4 algorithm and M4GB algorithm. We succeeded in solving Type II and III problems of Fukuoka MQ challenge using our algorithm when the number of variables was 37 in both problems.

In this letter, an efficient hybrid direction-of-arrival (DOA) estimation scheme is devised for massive uniform rectangular array. In this scheme, the DOA estimator based on a two-dimensional (2D) discrete Fourier transform is first applied to acquire coarse initial DOA estimates for single data snapshot. Then, the fine DOA is accurately estimated through using the iterative search estimator within a very small region. Meanwhile, a Nyström-based method is utilized to correctly compute the required noise-subspace projection matrix, avoiding the direct computation of full-dimensional sample correlation matrix and its eigenvalue decomposition. Therefore, the proposed scheme not only can estimate DOA, but also save computational cost, especially in massive antenna arrays scenarios. Simulation results are included to demonstrate the effectiveness of the proposed hybrid estimate scheme.

Conceptual data modeling is an important activity in database design. However, it is difficult for novice learners to master its skills. In the conceptual data modeling, learners are required to detect and correct errors of their artifacts by themselves because modeling tools do not assist these activities. We call such activities self checking, which is also an important process. However, the previous research did not focus on it and/or the data collection of self checks. The data collection of self checks is difficult because self checking is an internal activity and self checks are not usually expressed. Therefore, we developed a method to help learners express their self checks by reflecting on their artifact making processes. In addition, we developed a system, KIfU3, which implements this method. We conducted an evaluation experiment and showed the effectiveness of the method. From the experimental results, we found out that (1) the novice learners conduct self checks during their conceptual data modeling tasks; (2) it is difficult for them to detect errors in their artifacts; (3) they cannot necessarily correct the errors even if they could identify them; and (4) there is no relationship between the numbers of self checks by the learners and the quality of their artifacts.

This paper presents an approach to nonlinear impedance measurement exploiting an oscilloscope and Möbius transformation. Proposed system consists of a linear 4-port network and an oscilloscope. One of the port is excited by a high power source. The power is delivered to the second port, which is loaded with a DUT. Another set of two ports are used to observe a voltage set. This voltage set gives the impedance of the DUT through Möbius transformation. We formulated measurability M of the system, and derived the condition that M becomes constant for any DUT. To meet the condition, we propose a linear 4-port network consisting of a quarter-wavelength transmission line and resistors. We confirm the validity and utility of the proposed system by measuring the impedance of incandescent bulbs and an RF diode rectifier.

The copy-move or region duplication forgery technique is a very common type of image manipulation, where a region of the image is copied and then pasted in the same image in order to hide some details. In this paper, a keypoint-based method for copy-move forgery detection is proposed. Firstly, the feature points are detected from the image by using the Förstner Operator. Secondly, the algorithm extracts the features by using MROGH feature descriptor, and then matching the features. Finally, the affine transformation parameters can be estimated using the RANSAC algorithm. Experimental results are presented to confirm that the proposed method is effective to locate the altered region with geometric transformation (rotation and scaling).

We propose a multi-label feature selection method that considers feature dependencies. The proposed method circumvents the prohibitive computations by using a low-rank approximation method. The empirical results acquired by applying the proposed method to several multi-label datasets demonstrate that its performance is comparable to those of recent multi-label feature selection methods and that it reduces the computation time.

A projective Reed-Muller (PRM) code, obtained by modifying a Reed-Muller code with respect to a projective space, is a doubly extended Reed-Solomon code when the dimension of the related projective space is equal to 1. The minimum distance and the dual code of a PRM code are known, and some decoding examples have been presented for low-dimensional projective spaces. In this study, we construct a decoding algorithm for all PRM codes by dividing a projective space into a union of affine spaces. In addition, we determine the computational complexity and the number of correctable errors of our algorithm. Finally, we compare the codeword error rate of our algorithm with that of the minimum distance decoding.

Currently there is not any prospect of realizing quantum computers which can compute prime factorization, which RSA relies on, or discrete logarithms, which ElGamal relies on, of practical size. Additionally the rapid growth of Internet of Things (IoT) is requiring practical public key cryptosystems which do not use exponential operation. Therefore we constituted a cryptosystem relying on the difficulty of factoring the product of two large prime numbers, based on the Chinese Remainder Theorem, fully exploiting another strength of MPKC that exponential operation is not necessary. We evaluated its security by performing the Gröbner base attacks with workstations and consequently concluded that it requires computation complexity no less than entirely random quadratic polynomials. Additionally we showed that it is secure against rank attacks since the polynomials of central map are all full rank, assuming the environment of conventional computers.

Robust yet efficient techniques for detecting and tracking targets in infrared (IR) images are a significant component of automatic target recognition (ATR) systems. In our previous works, we have proposed infrared target detection and tracking systems based on sparse representation method. The proposed infrared target detection and tracking algorithms are based on sparse representation and Bayesian probabilistic techniques, respectively. In this paper, we adopt Naïve Bayes Nearest Neighbor (NBNN) that is an extremely simple, efficient algorithm that requires no training phase. State-of-the-art image classification techniques need a comprehensive learning and training step (e.g., using Boosting, SVM, etc.) In contrast, non-parametric Nearest Neighbor based image classifiers need no training time and they also have other more advantageous properties. Results of tracking in infrared sequences demonstrated that our algorithm is robust to illumination changes, and the tracking algorithm is found to be suitable for real-time tracking of a moving target in infrared sequences and its performance was quite good.

In this paper, a one-class Naïve Bayesian classifier (One-NB) for detecting toll frauds in a VoIP service is proposed. Since toll frauds occur irregularly and their patterns are too diverse to be generalized as one class, conventional binary-class classification is not effective for toll fraud detection. In addition, conventional novelty detection algorithms have struggled with optimizing their parameters to achieve a stable detection performance. In order to resolve the above limitations, the original Naïve Bayesian classifier is modified to handle the novelty detection problem. In addition, a genetic algorithm (GA) is employed to increase efficiency by selecting significant variables. In order to verify the performance of One-NB, comparative experiments using five well-known novelty detectors and three binary classifiers are conducted over real call data records (CDRs) provided by a Korean VoIP service company. The experimental results show that One-NB detects toll frauds more accurately than other novelty detectors and binary classifiers when the toll frauds rates are relatively low. In addition, The performance of One-NB is found to be more stable than the benchmark methods since no parameter optimization is required for One-NB.

We calculated propagation constants of supermodes for two-dimensional two-slab waveguides, with small core gap, using second-order perturbation expansion from gapless slab waveguide system, and compared our results with the existing works. In the perturbation calculation, we used trapezoidal method to calculate the integral over the transverse direction in space and obtained second-order expansion of (core gap)/(core width) for propagation constants. Our result can explain the qualitative relationship between the propagation constants and the gap distance in the neighbor of (core gap)/(core width) being zero.

During a software development phase where a product is progressively elaborated, it is difficult to guarantee that the refined product retains its original behaviors. In this paper, we propose a method to detect refinement errors in UML sequence diagrams using LTSA (Labeled Transition System Analyzer). The method integrates multiple sequence diagrams using hMSC (high-level Message Sequence Charts) into a sequence diagram. Then, the method translates the diagram into FSP representation, which is the input language of LTSA. The method also supports some combined fragment operators in the UML 2.0 specification. We applied the method to some examples of refined sequence diagrams and checked the correctness of refinement. As a result, we confirmed the method can detect refinement errors in practical time.

Accurate estimation of Software Code Size is important for developing cost-efficient embedded systems. The Code Size affects the amount of system resources needed, like ROM and RAM memory, and processing capacity. In our previous work, we have estimated the Code Size based on CFP (COSMIC Function Points) within 15% accuracy, with the purpose of deciding how much ROM memory to fit into products with high cost pressure. Our manual CFP measurement process would require 2.5 man years to estimate the ROM size required in a typical car. In this paper, we want to investigate how the manual effort involved in estimation of Code Size can be minimized. We define a UML Profile capturing all information needed for estimation of Code Size, and develop a tool for automated estimation of Code Size based on CFP. A case study will show how UML models save manual effort in a realistic case.

Design-complexity metrics, while measured from the code, have shown to be good predictors of fault-prone object-oriented programs. Some of the most often used metrics are the Chidamber and Kemerer metrics (CK). This paper discusses how to make early predictions of fault-prone object-oriented classes, using a UML approximation of three CK metrics. First, we present a simple approach to approximate Weighted Methods per Class (WMC), Response For Class (RFC) and Coupling Between Objects (CBO) CK metrics using UML collaboration diagrams. Then, we study the application of two data normalization techniques. Such study has a twofold purpose: to decrease the error approximation in measuring the mentioned CK metrics from UML diagrams, and to obtain a more similar data distribution of these metrics among software projects so that better prediction results are obtained when using the same prediction model across different software projects. Finally, we construct three prediction models with the source code of a package of an open source software project (Mylyn from Eclipse), and we test them with several other packages and three different small size software projects, using their UML and code metrics for comparison. The results of our empirical study lead us to conclude that the proposed UML RFC and UML CBO metrics can predict fault-proneness of code almost with the same accuracy as their respective code metrics do. The elimination of outliers and the normalization procedure used were of great utility, not only for enabling our UML metrics to predict fault-proneness of code using a code-based prediction model but also for improving the prediction results of our models across different software packages and projects.

3D graphics application is widely used in consumer electronics which is an inevitable tendency in the future. In general, the higher abstraction level is used to model a complex system like 3D graphics SoC. However, the concerned issue is that how to use efficient methods to traverse design space hierarchically, reduce simulation time, and refine the performance fast. This paper demonstrates a system-level design space exploration model for a tile-based 3D graphics SoC refinement. This model uses UML tools which can assist designers to traverse the whole system and reduces simulation time dramatically by adopting SystemC. As a result, the system performance is improved 198% at geometry function and 69% at rendering function, respectively.

Tailoring industrial standards is done to reduce costs and improve quality for a particular project. This paper proposes using Bayesian Belief Network (BBN) analysis to support tailoring decision-making under uncertainties. However, there are two major problems associated with the objectivity of BBNs; that is, the construction of the causal inference diagrams and the assignment of probabilities of their dependency relations. We have developed a method to solve the first problem. In general, the relations among different activities, resources, and products addressed in software standards can be expressed more directly in Unified Modeling Language (UML) diagrams than in BBN's. Such relations include association, aggregation, or inheritance relations. We have developed a schema to construct BBNs for process tailoring from given UML diagrams that model a particular standard. The proposed approach systematically constructing BBNs can also be used to assist decision-making in other software project management activities, such as planning and risk management.

Constraint-based software specifications enable run-time monitoring to detect probable risk events and ensure the desired system behavior. SpecTRM-RL is a well-developed constraint-based specification method for computer-controlled systems. However, it is desirable to express constraints in familiar visual models. To provide better visualization and popularity, we developed methods to represent all the SpecTRM-RL constraint types in UML. We have also extended SpecTRM's constraints by adding relational and global constraints, and then expressed them in OCL. Safety verification of these specifications is also proposed. We developed a systematic way to construct fault trees for safety analysis based on UML diagrams. Due to the generality of UML as well as the defensive manner of constraints and fault tree analysis, our approach can be adapted for both general applications and safety-critical applications.

In iterative software development methodology, a version control system is used in order to record and manage modification histories of products such as source codes and models described in diagrams. However, conventional version control systems cannot manage the models as a logical unit because the systems mainly handle source codes. In this paper, we propose a version control technique for handling diagrammatical models as logical units. Then we illustrate the feasibility of our approach with the implementation of version control functions of a meta-CASE tool that is able to generate a modeling tool in order to deal with various diagrams.