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This paper discusses about the crisis-management and the security in the Internet. The crime that not is so far occurs during widespread to the society of the Internet, and a big social trouble. Moreover, the problem of a new security such as a cyber war and cyber terrorism appeared, too. It is necessary to recognize such a situation, and to do both correspondences corresponding to the environmental transformation by government and the people.

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The current semiconductor industry has shifted from vertical integrated model to horizontal specialization model in term of integrated circuit manufacturing. In this circumstance, IP cores as solutions for System-on-Chip (SoC) have become increasingly important for semiconductor business. This paper examines to what extent IP cores of SoC effectively can be protected by current intellectual property system including integrated circuit layout design law, patent law, design law, copyright law and unfair competition prevention act.

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This article overviews the historical transition of legal protection of Computer software contracts in the Unite States and presents how it should function under Uniform Commercial Code and its amended Article 2B, Uniform Computer Information Transactions Act, and also recently-approved “Principles of the Law of Software Contracts”.

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Assuming that patent trolls would come up in the field of software and the like in Japan in the future, we have proposed countermeasures to apply compulsory license against their exercise of patent right. Specifically, in order to avoid injunctive relief of the patent trolls, we have proposed that the enforcement regulation for Japanese Patent Act Article 83 is overhauled in attempt to broadly construe the provision of “the grant of non-exclusive license where invention is not worked” as “the grant of non-exclusive license where invention will not be worked in the future”. Also, we have compared such countermeasures with other countermeasures to apply the principle of abuse of rights to the injunctive relief.

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A method is presented to extract the physical parameters of illuminated organic bulk-heterojunction solar cells based on genetic algorithms and Levenberg-Marquardt method. The solar cell model is the well known single diode equivalent circuit containing four components. The voltage dependence of the photocurrent in the organic solar cells due to electron and hole drift lengths is taken into account. The applicability of the present method is demonstrated by fitting current - voltage characteristics of poly-3-hexylthiophene (P3HT) and [6,6]- phenyl-C₆₁-butyric acid methyl ester (PCBM) bulk-heretojunction solar cells at different light intensities and annealing temperatures.

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The intervalence band absorption loss coefficient of active layer in semiconductor laser diodes operating at long wavelengths have been calculated for Al_0.012Ga_0.458In_0.53As and In_0.53Ga_0.47As_0.77P_0.23 material with various hole density by taking into account of intraband relaxation time of 0.1 ps and 0.2 ps at 300 K and 400 K as parameters. Calculated results show that the loss and its temperature dependence of InGaAsP are larger than those of AlGaInAs material. The calculated intervalence band loss for InGaAsP is compared with the calculated data reported. The dependence of threshold current and quantum efficiency for both materials on intraband relaxation time as well as on the temperature in the wavelength range of 1.29∼1.6 μm have been calculated by using the density matrix theory. It obtained that AlGaInAs devices are superior in temperature performance to InGaAsP because T₀ value for the former is higher (109 K) than that of the latter (85 K).

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In this paper, we propose a high accuracy current mirror circuit suitable for a low-voltage operation. The proposed circuit has a novel negative feedback that is composed of neuron MOSFETs and a transimpedance amplifier. As a result, the proposed circuit achieves a high accuracy current mirror circuit. At the same time, the proposed circuit monitors an error current by a low voltage because the negative feedback operates in a current-mode. The performance of the proposed circuit is evaluated using HSPICE simulation with On-Semiconductor 1.48μm CMOS device parameters. Simulation results show that the output resistance of the proposed circuit is 5.79[GΩ] and minimum operating range is 0.3[V].

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Traffic signal control is an effective method to solve the traffic jam. and forecasting traffic density has been known as an important part of the Intelligent Transportation System (ITS). The several methods of the traffic signal control are known such as random walk method, Neuron Network method, Bayesian Network method, and so on. In this paper, we propose a new method of a traffic signal control using a predicted distribution of traffic jam based on a Dynamic Bayesian Network model. First, a forecasting model to predict a probabilistic distribution of the traffic jam during each period of traffic lights is built. As the forecasting model, the Dynamic Bayesian Network is used to predict the probabilistic distribution of a density of the traffic jam. According to measurement of two crossing points for each cycle, the inflow and outflow of each direction and the number of standing vehicles at former cycle are obtained. The number of standing vehicle at k-th cycle will be calculated synchronously. Next, the probabilistic distribution of the density of standing vehicle in each cycle will be predicted using the Dynamic Bayesian Network constructed for the traffic jam. And then a control rule to adjust the split and the cycle to increase the probability between a lower limit and ceiling of the standing vehicles is deduced. As the results of the simulation using the actual traffic data of Kitakyushu city, the effectiveness of the method is shown.

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Using the characteristics of the optima is so effective to solve the traveling salesman problems. In our study, the edges on the optimal tours calculated completely have been analyzed to have the characteristics of their mutual relationship. The edge set based on the characteristics can construct the sub graph including all or almost the edges selected as optimal edges. If a sub graph has all or almost the edges of constructing the optimum, the investigation on this graph will lead to discover a good solution in reasonable time. Therefore, such sub graphs are the effective tools for existing methods to become improved methods. In this paper, Delaunay graph and two graphs, called Fragmented Nearest Neighbor graph, are proposed as the special sub graphs. And the experiments by the simulated annealing method that is executable on sub graph explain that Delaunay graph as a triangulated graph is the most effective graph among the three sub graphs to find optimum or sub optimum tour of the traveling salesman problems.

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Three-dimensional (3-D) image measurement is a technique that uses a digital camera to determine the shape and dimensions of the surface of an object. Although it has been studied for a long time, various problems still remain to be solved for practical applications. The goal of our research is to solve these problems and to develop a 3-D camera that can be used for practical 3-D image measurements. This paper analyzes the problems associated with the conventional technology and introduces development goals for the new 3-D camera. The key techniques of this 3-D camera are explained, including techniques for optimizing the intensity-modulation pattern projection, controlling the projection pattern intensity, determining the projection position, and controlling the stripe period. The system is evaluated and some examples of applications are given. The proposed 3-D camera can automatically adjust for variations in an object's size, form, surface color, and reflection characteristics and it can measure non-stationary objects. Consequently, it has the potential to be used in a wide range of applications including product quality control, human measurement, and face recognition.

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In this paper, the reconstruction error between the real system to be controlled and its T-S fuzzy model is considered, and fuzzy approximator is employed to cope with the reconstruction error. As a result, it reaches an adaptive controller that has two parts: one is obtained by solving certain linear matrix inequalities (LMIs) (fixed part) and another one is acquired by the fuzzy approximator in which the related parameters are tuned by adaptive law (variable part). The proposed controller can guarantee the control state to converge and uniformly bounded while maintaining all the signals involved stable. Also, the convergence in terms of relaxing the LMIs conservatism is discussed. An inverted pendulum is provided to demonstrate the effectiveness of the proposed adaptive fuzzy controller.

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PLL-MSC (Phase Locked Loop Motor Speed Control) systems can completely reject speed error and steady-state phase error for constant-speed input signals. However, it is not usually applied to systems with inputs including acceleration, because they have poor tracking speed and strange pull-in behavior.
In the field of radio communication, “dual-loop PLL” is very effective for such signals. It can not only enable high-speed tracking, but also cancel phase error.
In the digital implementation of the PLL-MSC, it can achive easily by inserting loop filters into both feed back paths, and employed a special adder in PWM to implement loop addition for the two phase detector outputs. The scheme was implemented by programming an FPGA, and satisfiable results were obtained.

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Carrier type dynamic strain amplifiers are frequently used for stress measurement with strain gages. That is because the carrier type dynamic strain amplifier can conduct high precision measurement since it is highly resistant against hum noise from the power supply frequency in principle and is free from the thermoelectomotive force even if a metal contact is used in wiring to a Wheatstone bridge for measuring.
A problem of the carrier type dynamic strain amplifier is generation of Capacitive component (hereinafter referred to as the C component) in an input cable connecting from the amplifier to the input sensor (Wheatstone bridge for measuring). The C component varies with cable length, cable materials, or ambient temperature change. The aforementioned changing adversely affects the stability of the amplifier. In this paper, we realize and analyze the method that increases the stability of amplifier by detecting, eliminating and self tracking the above C component constantly. Used carrier frequency at 12kHz and 28kHz.
We made amplifiers with noise resistant and wide band frequency of measurement range and verified the theory of the Capacitance Self Tracing with the above amplifiers.

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Traffic accidents caused by drowsy driving never disappear and easily result in fatal crash when heavy vehicle is involved. General methods to prevent drowsy driving are caution-advisory indicators and alarm sounds. However visual and auditory information are excessive enough to alert drivers. This study aims to focus on olfactory stimuli, which do not provoke interference with driving actions, and examine the effectiveness in combating drowsiness. Changing type of scent, we performed investigations on the effectiveness of each countermeasure to remain alert against drowsy driving.

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We propose a color-based weed detection method specifically designed for detecting lawn weeds in winter. The proposed method exploits fuzzy logic to make inference from color information. Genetic algorithm is adopted to search for the optimal combination of color information, fuzzy membership functions, as well as fuzzy rules used in the method. Experimental results show that the proposed color-based method outperforms the conventional texture-based methods when testing with a winter dataset. In addition, we propose a hybrid system that incorporates both texture-based and color-based weed detection methods. It can automatically select a better method to perform weed detection, depending on an input image. The results show that the use of the hybrid system can significantly improve weed control performances for the overall datasets.

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It is a general way that the industrial product is tested by individual inspector. If the product involves sound factors, each inspector will evaluate the test product to sort out a strange engine noise from the natural sound. However, it is hard to cover the consistency in evaluation criteria due to the personal equation referred to the idea that every individual had an inherent bias, plus a physical and mental conditions can be a negative effect on his/her evaluation criteria. It would be ideal if the criteria would not be affected by anyone, anywhere, circumstances; accordingly the quality of products must be equated. In this paper, we propose a noise detection method based on Cubic Higher-order Local Auto-Correlation (CHLAC) scheme and DP Matching provided by Cepstrum Analysis to extract the correct solution. This technique is practically used for detecting any human abnormal movements out of a monitored video clip and identifying individual persons by voice. The study results are shown to be highly effective in our proposed method.

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Male and female recognition is necessary to make security stronger and when various statistics on the visitor are taken in commercial facilities and so on. The conventional method of male and female recognition is currently determined by using the person's dress and in such cases, the way of walking, the foot pressure, the hair type. But, these characteristics can be intentionally changed by human intervention or design. The proposed method obtains a difference in the male's and female's characteristics by taking absorbance characteristics of the fat distribution of the person's cheek by near infrared ray scanning spectrophotometer. This is a male and female recognition based on the new concept idea which this is used for. Consequently, this can be used to recognize a male from a female even if a male turns himself into the female intentionally (and vice versa), because this method involves biometrics authentication. Therefore, the proposed method will be applied to the security system.

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Nowadays, children spend most of their time in kindergarten as well as nursery schools. This directly brings a requirement to the parents: they want to see how everyday goes with their kids. To meet this requirement, in this paper, we propose a method to automatically generate video digest that records kids' daily life in kindergarten. Our method involves two steps. The first is to efficiently narrow down the searching space by analyzing the noisy RFID tag log which records kids' temporal location, while the second is to use visual features and time constrains to recognize events and pick out video segments for each individual event. The accuracy of our method was evaluated with quantitative experiment and the superior of the digest that generated by our method was confirmed via questionnaire survey.

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This paper describes a method for estimating 3D motion. Some methods for detecting the 3D scene flow (=3D-Flow) of an arbitrary point on free-form surface by using video sequence have been already suggested. When the target object is a rigid body, motion parameters can be calculated analytically because all 3D-Flow vectors are based on same conversion matrix. On the other hand, when the target object is a non-rigid body, it is difficult to calculate overall motion involving local deformation. In this study, we define detected 3D-Flow vectors as “flow-field” (or “force-field”), and store the virtual buoy (float) into this field, and calculate motion of the virtual buoy by using simple physical simulation. Motion of the object in the real world is estimated through the motion of the virtual buoy.

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In this research, we have developed a sorting system for fishes, which is comprised of a conveyance part, a capturing image part, and a sorting part. In the conveyance part, we have developed an independent conveyance system in order to separate one fish from an intertwined group of fishes. After the image of the separated fish is captured in the capturing part, a rotation invariant feature is extracted using two-dimensional fast Fourier transform, which is the mean value of the power spectrum with the same distance from the origin in the spectrum field. After that, the fishes are classified by three-layered feed-forward neural networks. The experimental results show that the developed system classifies three kinds of fishes captured in various angles with the classification ratio of 98.95% for 1044 captured images of five fishes. The other experimental results show the classification ratio of 90.7% for 300 fishes by 10-fold cross validation method.

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A novel method that can be used to evaluate luminance uniform quality of Flat Panel Displays (FPDs) has been developed. This method is capable of evaluating the edge gradients of the non-uniform regions. This is accomplished by converting the original image into a visual sensitivity image using a contrast sensitivity function filter. The experiments were executed by using pseudo non-uniform samples and real LCD displays. It was shown that the average of the visual sensitivity values of the non-uniform regions correlated strongly to the grades obtained by human evaluation. The proposed method can be used to evaluate luminance uniform grades at any viewing distance, which is very important for uniformity evaluation.

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In this paper, we propose the new keyframe-based lip reading method which does not need the advanced registration of an utterance scene. To extract keyframe, we apply the frame subtraction method and extract frame which the difference value is the local minimum as the keyframe. We compute thirteen shape features from the five lip regions of the extracted keyframe. Then we apply a discriminant analysis to mouth shape recognition. We generate a code sequence based on a mouth shape recognition result. Moreover, in accordance with several rules, we generate candidate code sequences. Finally, we apply DP matching using two kinds of code sequence of based on keyframe and candidate, and select the similar code sequence as the result word. We set Japanese 19 words as the target. We took four speakers' utterance scene. We carried out three experiments of the keyframe extraction, the mouth shape recognition, and the word recognition. As a result, we obtained average recognition rate of 53.9%. Although there was individual difference, one speaker obtained 72.1% of the highest recognition rate.

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This paper proposes a method of detecting unusual human behavior from video images for automated visual surveillance. The method detects unusual human behavior by learning examples of usual behavior and then detecting behavior that is different from the usual. Histogram of oriented gradients of Motion History Image (MHI) is used for describing the features of human movements, and k nearest neighbors is used for the classifier. The performance of the method was evaluated by applying it to unusual pedestrian behavior detection on a street. As a result, true positive rate was 85% when false positive rate was 3%.

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Function optimizations are used in various fields. Solution spaces, however, varies according to the solving problems. Therefore we think that searching algorithms considering solution spaces are more efficient than algorithms without considering. Our proposed algorithm uses self-organizing maps (SOM) to realize the pseudo solution space. From this pseudo solution space in SOM map, we presume candidate optimum solutions. We obtain the “number feature” and the “soluiton feature” from these candidate optimum solutions. The “number feature” means how many candidate optimum solutions are in the SOM map. The “soluiton feature” means what kind of features the candidate optimum solutions have. We prepare six features as these “soluiton feature”s. Prepared features are “Dimension”, “Surround”, “Difference”, “Vector”, “Fourier” and “Wavelet”. We compare our proposed algorithm with particle swarm optimization, differential evolution and SPX. The problem we treat in experiments is the real-valued minimization problem with several benchmark functions. We show that our proposed algorithm searches the optimum solution effectively in terms of the number of function evaluations from experimental results.

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In real time analysis and forecasting of time series data, it is important to detect the structural change as immediately, correctly, and simply as possible. And it is necessary for rebuilding the next prediction model after the change point as soon as possible. For this kind of time series data analysis, in general, multiple linear regression models are used. In this paper, we present two methods, i.e., Sequential Probability Ratio Test (SPRT) and Chow Test that is well-known in economics, and describe those experimental evaluations of the effectiveness in the change detection using the multiple regression models. Moreover, we extend the definition of the detected change point in the SPRT method, and show the improvement of the change detection accuracy.

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A new prediction method of stock returns was constructed from a cross-sectional multivariable model where explanatory variables are current financial indexes and an explained variable is a future stock return. To achieve precise prediction, explanatory variables were appropriately selected over time based on various test statistics and optimization of a performance index of expected portfolio return. A long-short portfolio, in which stocks with high predicted return were bought and stocks with low predicted return were sold short, was constructed to evaluate the proposed method. The simulation test showed that the proposed prediction method was effective to achieve high portfolio performance.

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We propose a method for solving optimal price decision problems for simultaneous multi-article auctions. An auction problem, originally formulated as a combinatorial problem, determines both every seller's whether or not to sell his/her article and every buyer's which article(s) to buy, so that the total utility of buyers and sellers will be maximized. Due to the duality theory, we transform it equivalently into a dual problem in which Lagrange multipliers are interpreted as articles' transaction price. As the dual problem is a continuous optimization problem with respect to the multipliers (i.e., the transaction prices), we propose a numerical method to solve it by applying heuristic global search methods. In this paper, Particle Swarm Optimization (PSO) is used to solve the dual problem, and experimental results are presented to show the validity of the proposed method.

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A real-time kernel (henceforth RTK) is in the center place of embedded software technology, and the understanding of RTK is indispensable for the embedded system design. To implement RTK, it is necessary to understand languages that describe RTK software program code, system programming manners, software development tools, CPU on that RTK runs and the interface between software and hardware, etc. in addition to understanding of RTK itself. This means RTK implementation process largely covers embedded software implementation process. Therefore, it is thought that RTK implementation practice program is very effective as a means of the acquisition of common embedded software skill in addition to deeper acquisition of RTK itself. In this paper, we propose to apply RTK implementing practice program to embedded software engineers educational program. We newly developed very small and step-up type RTK named μK for educational use, and held a seminar that used μK as a teaching material for the students of information science and engineers of the software house. As a result, we confirmed that RTK implementation practice program is very effective for the acquisition of embedded software common skill.

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Ensemble Monte Carlo simulation based on analytic band model has been developed for electron transport in silicon. The present simulator includes L valley, in addition to X valley, impact ionization and donor ionization rate with the temperature dependence of some physical parameters. Nevertheless the simple model, this simulator works well within the practical ranges of temperatures, electric fields and donor concentrations. Furthermore, the simulation is executed on a personal computer.

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In this letter, we propose a color conversion method for realizing barrier free of color defective vision. Based on confusion loci theory, the proposed technique realizes the perceptible images for dichromats by changing the confusion colors through the low computational cost. Moreover, the conversion method preserves the naturalness of the image.

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