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This paper addresses an operation and energy purchase planning problem under the CO₂ emissions regulation for corporate entities. Considering energy trading, more efficient energy consumption may be possible. We have studied an agent-based planning system, called Distributed Energy Management Systems (DEMSs), which intends to reduce energy consumption. In the DEMSs, CO₂ emissions regulation is imposed on each corporate entity, and electrical and thermal energy trading among the entities are allowed. We have proposed an energy trading decision method based on the Market Oriented Programming (MOP). In this paper, we propose trading decision methods for the group composed of several customers and several suppliers. Experimental results show effectiveness of the proposed method.

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Heat pump water heaters (HPWHs) are one of the key technologies for reducing CO₂ emissions from the household sector and must be downsized to expand their use in high density urban areas. Though the reduction of tank capacity is vital for downsizing HPWH, this often increases operation costs because it means heat pumps must boil water with expensive electricity during the day in order to avoid running out of hot water. Consequently, the development of a heat pump water heater with a storage battery (HPWH-SB) was investigated. In this paper, we develop an optimizing unit configuration tool that finds the optimal combination of heat pump, storage tank, and storage battery and estimate battery break-even point.

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The system most widely employed in existing heat pump water heaters is based on three rules, the parameters of which used to calculate the amount of hot water required are fixed. A method exists to optimize parameters in the three rules; however, this parameter optimization method remains insufficient for many types of heaters since the method does not take demand patterns fully into account. Parameter optimization optimizes a control rule set simply assuming that a storage tank has sufficient capacity for a whole day demand. We propose a new method for generating an control rule set that minimizes running costs based on hot water demand patterns. Our method adopts a new rule format which can control the heaters more flexibly than parameter optimization. The control rule set is explored by Genetic Algorithm (GA) and a computer simulation of the heat pump water heater. To evaluate our method, we explored control rule sets for two types of storage tanks for three actual consumers. Our method generated efficient control rule sets that adapt to changes of hot water demand patterns. Consequently, over 20% of running costs were reduced compared to the control rule set optimized by parameter optimization.

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Distributed processing system for restoration of electric power distribution network using two-layered CNP is proposed. The goal of this study is to develop the restoration system which adjusts to the future power network with distributed generators. The state of the art of this study is that the two-layered CNP is applied for the distributed computing environment in practical use. The two-layered CNP has two classes of agents, named field agent and operating agent in the network. In order to avoid conflicts of tasks, operating agent controls privilege for managers to send the task announcement messages in CNP. This technique realizes the coordination between agents which work asynchronously in parallel with others. Moreover, this study implements the distributed processing system using a de-fact standard multi-agent framework, JADE(Java Agent DEvelopment framework). This study conducts the simulation experiments of power distribution network restoration and compares the proposed system with the previous system. We confirmed the results show effectiveness of the proposed system.

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This paper describes about a decision model for solar energy utilization and an investigation of optimal configuration of solar energy system considering electricity transportation between interprofessional consumers. Solar energy is effective energy source for CO₂ reduction. Available collectable area for solar energy is limited to consumer's condition. A photovoltaic can supply electricity which is flexible. However its efficiency is low compared to solar heat collector. A solar heat collector has high efficiency. But heat demand varies with consumer type. We investigate optimal ratio of photovoltaic and solar heat collector in several condition. The result shows that solar heat collector is effective energy supply system for consumers which require high hot water demand in daytime. On the other hand, electrical heat pump for hot water supply varies optimal configuration of solar energy system due to the shift of energy source from gas to electricity. To introduce electrical heat pump for hot water supply increases the ratio of photovoltaic due to the increase in electricity demand. However, there is no consumer without solar heat collector. Therefore, solar heat collector does not compare with electrification of consumer.

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Japanese government has declared that the amount of the Photovoltaic cells (PV) will be 53GW by 2030 in national area. It is about 40 times of the amount of PV in 2005. It means that 30 to 40 percent of detached residential houses will have PV systems. It results in many issues such as voltage fluctuation in distribution systems. Voltage in distribution network might rise because of the reverse power flow from many PV systems. PV generation outputs suppression method is being considered to avoid the voltage problem in case of high insolation. However, the output of PV generation should not be suppressed from the viewpoint of efficient energy utilization.
It is also probable that fuel cell cogeneration systems will be introduced in many residential houses. In this paper, the operating method of fuel cells for relieving PV generation outputs suppression under high penetration conditions is studied. It is shown that PV outputs can be increased by the operation of fuel cells.

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Design technology of stacked NAND type 1-transistor FeRAM has been described. With 39nm design rule feasibility study of 1Tbit memory focused on cell array structure and core circuit has been investigated. 64 layer 8k×8k stacked SGT memory cell array structure and the double ended row and column decoder with SGT have been newly introduced.
From the estimation of wordline and bitline delay time this structure enables to reduce the delay time of core circuit to 5ns. Stacked NAND type 1-transistor FeRAM is a promising candidate for realizing fast access time of 50ns.

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A new playback signal processing system capable of large-capacity optical disc playback of over 25GB in the same optical format as the Blu-ray Disc has been developed. Generally, as optical disc capacity increases, the read-out signal of minimum pits is markedly degraded due to inter-symbol interference (ISI) from adjacent pits, asymmetries caused by pit-form distortion, and the frequency characteristics of optical transfer function (OTF). Partial Response Maximum Likelihood (PRML) is known to effectively improve ISI and asymmetries by compensating for these factors electrically. However, in high-density optical discs greater than 25GB, bit errors frequently occur even when PRML is applied. This proposed system consists of a PRML circuit and Improved Waveform Correction circuit that control only read-out signals of minimum pits more surely. Bit error rate (BER) measurements of the playback of a 30GB optical disc showed better BER performance. The system can be realized without major changes to the current PRML system.

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We measured somatosensory evoked fields (SEFs) by applying on electric stimulus to the right finger (medium nerve and ulnar nerve) and the right ankle (posterior tibial nerve) with a 39-channel SQUID system, which can measure magnetic-field components perpendicular (B_r) and tangential to the scalp (B_θ, B_φ) simultaneously. To investigate the relationship between phase lag and stimulus repetition frequency (SRF), the delay time of a component synchronized with the SRFs was calculated by convoluting the reference signal and the measured SEF. The phase lag was linear to SRF for at least three different ranges of the SRFs in each SEF data. We simulated the SEF responses based on the results of phase-lag characteristics and determined the parameters for modeling. To quantitatively characterize the component of SEF, we proposed electric circuit model for the characteristics of phase-lag of the SEF with stimuli frequency.

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To investigate the possibility of a brain computer interface (BCI) constructed using activities of the prefrontal cortex (PFC), we analyzed PFC multiple unit activities (MUAs) during a delayed reinforcement (DRF) lever press task in rats. In the DRF task, each trial consisted of two lever press responses (R1, R2): R1 as the trial initiation, R2 as a pre-conditioned response to a stimulus (buzzer) for a reward. Between R1 and the buzzer, rats were required to inhibit the lever press (waiting phase). The trial was evaluated as incorrect if rats pressed the lever during the waiting phase. Results show that the mean firing rate (MFR) was significantly lower around the time of R1 compared with the pre-trial time in correct trials, although no significant changes were found in incorrect trials. From a neuroengineering perspective, the MFR of each single trial was calculated. Most correct trials showed decreasing MFR around the time of R1. The PFC MUA might be useful for BCI.

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We address an estimation method of isometric muscle tension of fingers, as fundamental research for a neural signal-based prosthesis of fingers. We utilize needle electromyogram (EMG) signals, which have approximately equivalent information to peripheral neural signals.
The estimating algorithm comprised two convolution operations. The first convolution is between normal distribution and a spike array, which is detected by needle EMG signals. The convolution estimates the probability density of spike-invoking time in the muscle. In this convolution, we hypothesize that each motor unit in a muscle activates spikes independently based on a same probability density function. The second convolution is between the result of the previous convolution and isometric twitch, viz., the impulse response of the motor unit. The result of the calculation is the sum of all estimated tensions of whole muscle fibers, i.e., muscle tension.
We confirmed that there is good correlation between the estimated tension of the muscle and the actual tension, with >0.9 correlation coefficients at 59%, and >0.8 at 89% of all trials.

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Blood Pressure (BP) is a very important factor for monitoring the cardiovascular condition. In general, non-invasive BP measurements need a cuff. However, such measurement techniques can hardly monitor BP continuously. Recently it has gotten easier to measure biological signals daily because sensor technologies have well-developed, and because of availability of many kinds of miniaturized measurement instruments consuming less power. This study suggests a method of estimating Systolic Blood Pressure (SBP) with a wearable sensor instead of a cuff. In particular, our study depends on only one pulse wave signal detected by a Photoplethysmograph (PPG) sensor since the PPG sensor is very small. Moreover, the human subject just wears the sensor on the surface of the body to measure the signal. Cardiovascular peculiarities keep changing as people get older. Additionally, the peculiarities vary among individuals according to the advanced rate of arteriosclerosis. Hence, it is necessary for estimating the SBP to divide the data into several classes, by parameters that relate to individual cardiovascular peculiarities. In this study, the regression equation of SBP was calculated from individual information and from features of the PPG signal in each class. As a result, the estimation accuracy was improved. This technique would make cuffless SBP monitoring become more convenient and helpful as only one device is required for monitoring, which is smaller than traditional measurements.

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Falling is one of the most serious problems for the elderly. It is thought that lower limb muscular strength greatly affects falls of the elderly. The aim of this study is to develop a safe, easy-to-use and quantitative device of knee-gap force measurement for evaluation of the lower limb muscular strength, and additionally, we examined it for efficiency. We examined from the three viewpoints. In the results, 1. the knee-gap force is clearly associated with the strength of muscle contraction estimated by electromyogram in each muscle for the hip joint adductors. Therefore, the proposed device for the measurement of knee-gap force correctly estimates the activity of the hip joint adductors, which is closely related with the activities of daily living. 2.The results of knee-gap force measured from 170 people aging from middle age to elderly, including some persons who are suffering from physical frailness on a clinical estimation. In the group of healthy elderly knee-gap force was decreased by 16%, while that of the physically frail elderly was decreased by 34% in comparison to middle age.3. Furthermore, the correlation coefficient between the knee-gap force and 10m obstacle walking time was found to be -0.57 (negative correlation). It means that the ambulatory ability is decreased along with the knee-gap force being decreased. This indicates a possibility easily to estimate risk of falling by the knee-gap force, because the decrease of lower limb muscular strength and ambulatory ability is a factor of increased falling risk.

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The railway crew scheduling problem is to determine the assignment of crews to each traveling task to minimize the number of crews satisfying set covering constraints. Column generation method is often applied to solve railway crew scheduling problems. In this paper, we propose dual inequalities for railway crew scheduling problems to reduce the number of iterations in the column generation method. Three types of dual inequalities are generated from railway timetable data and they are added to the restricted master problem. Computational results show the effectiveness of the proposed method compared with the conventional column generation method.

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In this paper, we propose a robust series-parallel adaptive filter for near-end noise. The compensating method of the bias error when the near-end noise can be assumed to a white signal is known well. The example of representative adaptive algorithm is that the weights are controlled under the unit norm condition. We considered the adaptive filter that was able to be applied when the near-end noise is a colored signal. The cost function is a square-sum of the cross-correlation coefficient of the input signal and the estimation error. The analytical results and the above mentioned feature are strictly verified by computer simulation.

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In this paper, an algorithm capable of finding important time related association rules is proposed where Genetic Network Programming (GNP) with Attribute Accumulation Mechanism (AAM) and Extraction Mechanism at Stages (EMS) is used. Then, the classification system based on extracted time related association rules is proposed to estimate to which class the current traffic data belong. Using this kind of classification mechanism, the traffic prediction is available since the rules extracted are based on time sequences. And, we also present the experimental results on the traffic prediction problem.

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Studies for video surveillance applications for preventing various crimes such as stealing and violence have become a hot topic. This paper proposes a new video surveillance system that can detect suspicious behaviors such as a car break-in and vandalization in an open space parking, and that is based on image processing. The proposed system has the following features: it 1)deals time series data flow, 2)recognizes “human elemental actions” using statistic features, and 3)detects suspicious behavior using Subspace method and AdaBoost. We conducted the experiments to test the performance of the proposed system using open space parking scenes. As a result, we obtained about 10.0% for false positive rate, and about 4.6% for false negative rate.

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To prevent a person from falling of a bed, we have developed an awakening behavior detection system using a neural network (abbreviated as NN). However, the detection ability of unknown persons is not sufficient compared to that of learned persons. In this research, to improve the detection ability of unknown persons, we apply an online tuning system using a continuous learning of the NN to the detection system. In the online tuning system, only a few additional data of a new target person are used for the continuous learning, where the weights of the NN converged in the initial learning are used as the initial weights for the continuous learning. In this paper, first, we verify that the individual differences among persons affect the detection ability. Second, we demonstrate that the detection ability is improved by executing the online tuning. Thus, we verify the effectiveness of the online tuning of the awakening behavior detection system.

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This paper describes a novel architecture to promote retail businesses using information recommendation systems. The main features of the architecture are 1) Dual-directed Recommendation system, 2) Portal site for three kinds of users: Producers, Retailers, and Consumers, which are considered to be Prosumers, and 3) Agent-based implementation. We have developed a web-based system DAIKOC (Dynamic Advisor for Information and Knowledge Oriented Communities) with the above architecture. In this paper, we focus on the recommendation functions to extract the items that will achieve the large sales in the future from the ID (IDentification)-POS (Point-Of-Sales) data.

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A diffusion model is proposed for two-sided service systems. ‘Two-sided’ refers to the existence of an economic network effect between two different and interrelated groups, e.g., card holders and merchants in an electronic money service. The service benefit for a member of one side depends on the number and quality of the members on the other side. A mathematical model by J. H. Rohlfs explains the network (or bandwagon) effect of communications services. In Rohlfs' model, only the users' group exists and the model is one-sided. This paper extends Rohlfs' model to a two-sided model. We propose, first, a micro model that explains individual behavior in regard to service subscription of both sides and a computational method that drives the proposed model. Second, we develop macro models with two diffusion-rate variables by simplifying the micro model. As a case study, we apply the models to an electronic money service and discuss the simulation results and actual statistics.

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Recently, train regulation is being complex because of congested train schedules and various kinds of cars/classes of trains. So it is necessary for decreasing operator's workload and raising his skill to help his work by computer systems. A research in automatic train rescheduling has been done by several approaches. But it is impossible to satisfy standards of train regulation about response time and accuracy. In this paper, we propose a concept of an automatic train regulation method using operator's knowledge and show an algorithm that is built by the constraint programming. Being evaluated on some test case, it is shown that the algorithm can find a feasible solution at practical speed.

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To judge the understanding level of students unfamiliar with programming on a sample code, we propose a specification change exercise. In a specification change exercise, a teacher indicates a tiny specification change on the sample code. He forces students to modify the given sample code to meet the new specification. To automate marking, the method conducts a specification change exercise, using a control structure graph. A control structure graph stratifies elements constructing the sample code in the order of abstraction level. Each node in the graph has one-on-one relation with a code fragment in the sample code. When students identify the code fragments to be modified, they select its nodes instead of code fragments. The comparison of nodes selected by students with the correct nodes designated by teachers enables the automatic calculation of the understanding level on the sample code. Using calculated level, the method provides students study time, and facilitates students to enhance understanding level gradually by themselves. As a result of experiment, the method greatly reduces human load to judge the understanding level assuring almost same understanding level as existing human based way.

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This paper presents a real-time method for generating various footprints in relation to state of walking. In addition, the method is expanded to cover both on hard floor and soft ground. Results of the previous method were not so realistic, because the method places same simple foot prints on the motion path. Our method runs filters on the original pattern of footprint on GPU. And then our method gradates intensity of the pattern to two directions, in order to create partially dark footprints. Here parameters of the filter and the gradation are changed by move speed and direction. The pattern is mapped on a polygon. If the walker is pigeon-toed or bandy-legged, the polygon is rotated inside or outside, respectively. Finally, it is placed on floor. Footprints on soft ground are concavity and convexity caused by walking. Thus an original pattern of footprints on ground is defined as a height map. The height map is modified using the filter and the gradation operation developed for floor footprints. The height map is converted to a bump map to fast display the concavity and convexity of footprints.

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A paper filtering system that supports the effective collection of related journal papers is becoming important as the technological progress has been rapid. However, previous systems realized insufficient filtering effectiveness, because of lack of available information in abstract part of journal papers that is available to the public. In this paper, we propose a paper filtering method using the profile which is revised from not only relevant papers but also relevant patent documents by pseudo relevance feedback. By the evaluation for 15 examinees using 4,875 journal papers, it became clear that for all examinees the effectiveness of proposed method exceeds the conventional method, when the counterparts in patent document components for the journal paper's abstract is used, which became closer to practical use.

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