The electric power is the modernized life cornerstone, is the economical development power. In recent years but as a result of the energy shortage, the fuel price anabatic wind rose, the peak load continued to grow, creates the electric power supply becoming serious. If the power supply cost is unable to respond in the electrovalence, how also creates the enterprise own to continue forever the management. This research main goal thoroughly is analyzing the Taiwan Telegraphic Transmission electrovalence structural model and the set price law, and the electrovalence difference¡£season electrovalence, the time electrovalence¡¤rationality, and on the external environment, faces the fuel price anabatic wind to rise and under the unreasonable low price electrovalence arduous situation, then discusses it in accordance to it road¡FFinally will attempt summarizes in accordance to the future transport business environment, the formulation electrovalence adjustment mechanism, will conform to present situation, will be full responded each kind of factor in the electrovalence, hoped for this research will be able to become the future to establish in the electrovalence model formulation process the reference. This study research for the document company, after the process material analysis, will establish "the most suitable electrovalence set price pattern" the factor induction to be as follows¡G (1) Brings into line with "the fuel cost". (2) To consider "the reserve capacity rate". (3) Enhancement breaks a contract the penal regulations. (4) To enhance the time electrovalence section several. (5) Change unreasonable electrovalence structure. (6) Reference various countries electrovalence model.

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This paper designs and implements a DSP based intelligent battery charger and residual capacity estimator for electric vehicle. This system uses the proposed new electric circuit structure and the intelligent fuzzy charge algorithm to charge batteries, and the improved coulometric measurement with accurate residual capacity estimation to estimate the residual capacity of batteries. From the experimental results, the charger can achieve the purpose of fast and uniform charge with charging time six (6) to eight (8) hours, and will not cause the damage of battery because of using the intelligent fuzzy charge algorithm can give different charging current depend on the difference of voltage, capacity and temperature of battery; the residual capacity estimator can accurate estimate the residual capacity of batteries due to calculating the increment current and considering the aging factor.

This paper Management and Diagnosis a DSP based intelligent battery charger and residual capacity estimator for electric vehicle. This system uses the proposed new electric circuit structure and the intelligent fuzzy charge algorithm to charge batteries, and the improved coulometric measurement with accurate residual capacity estimation to estimate the residual capacity of batteries. From the experimental results, the charger can achieve the purpose of fast and uniform charge with charging time six (6) to eight (8) hours, and will not cause the damage of battery because of using the intelligent fuzzy charge algorithm can give different charging current depend on the difference of voltage, capacity and temperature of battery; the residual capacity estimator can accurate estimate the residual capacity of batteries due to calculating the increment current and considering the aging factor.

The Kaoping River basin is the largest and the most intensively used river basin in Taiwan. It is 171-km long, drains a catchment of more than 3,250 km2. Based on the current water quality analysis, the Kaoping River is heavily polluted. Concern about the deteriorating condition of the river led the Government of Taiwan to amend the relevance legislations and strengthen the enforcement of the discharge regulations to effectively manage the river and control the pollution. Investigation results demonstrate that both point and non-point source pollutants are now the causes of biochemical oxygen demand (BOD), nutrients, and pathogens in the river. The main water pollution sources are livestock wastewater from hog farms, municipal wastewater, industrial wastewater, non-point source (NPS) pollutants from agricultural areas, and leachate from riverbank landfills. The current daily BOD, NH3-N, and TP loadings to Kaoping River are 74,700, 39,400, and 5,100 kg, respectively. However, the calculated BOD, NH3-N, and TP carrying capacities are 27,700, 4,200, and 600 kg per day. To protect public health and improve the river water quality, the comprehensive management and construction strategy is proposed. The proposed strategy includes the following measures to meet the calculated river carrying capacity: (1) hog ban in the entire Kaoping River basin, (2) sewer system construction to achieve 30% of connection in the basin within 10 years, (3) removal of 10 riverbank landfills, and (4) enforcement of the industrial wastewater discharge standards. After the implementation of the proposed measures, the water quality should be significantly improved and the BOD and nutrient loadings can be reduced to below the calculated carrying capacities.

This paper designs and implements a DSP based intelligent battery charger and residual capacity estimator. This system uses the proposed structure of the series circuit and battery equalizer with the intelligent fuzzy charge algorithm to charge batteries, and the improved coulometric measurement with accurate residual capacity estimation to estimate the residual capacity of batteries. Because of using the intelligent fuzzy charge algorithm can give different charging current depend on the difference of voltage, capacity and temperature of battery; And because of using the battery equalizer can adjust the voltage of battery. The charger can charge the battery safely without causing any damage. From the experimental results, the charger can achieve the purpose of fast and uniform charge with charging time six (6) to eight (8) hours, the residual capacity estimator can accurate estimate the residual capacity of batteries due to calculating the increment current and considering the aging factor.

This thesis is to design an intelligent battery charger and residual capacity estimator with DSP. This system uses the proposed structure of the series circuit and battery equalizer with the intelligent fuzzy charge algorithm to charge battery, The internal resistance measurement can accurately estimate the residual capacity of battery. Because of using the intelligent fuzzy charge algorithm, it can give different charging current depends on voltage, capacity and temperature of battery. Because of using battery equalizer, it can adjust the voltage of battery to guarantee the battery be charged safely. According to experimental results, the charger can achieve the goal of fast and uniform charge within 6 to 8 hours. On the residual capacity estimator, We measure internal resistance to accurately estimate residual capacity of battery, because internal resistance is affected by environmental temperature, battery corrosion, aging factor and output current .

We present a serially concatenated coding scheme for partial response channels. The encoder consists of an outer irregular LDPC code and an inner matched spectrum trellis code. These codes are shown to offer considerable improvement over the i.i.d. capacity (> 1 dB) of the channel for low rates (approximately 0.1 bits per channel use). We also present a qualitative argument on the optimality of these codes for low rates. We also formulate a performance index for such codes to predict their performance for low rates. The results have been verified via simulations for the (1-D)/sqrt(2) and the (1-D+0.8D^2)/sqrt(2.64) channels. The structure of the encoding/decoding scheme is considerably simpler than the existing scheme to maximize the information rate of encoders over partial response channels.

The use of multiple antennas at the transmitter and/or the receiver promises greatly increased capacity. This can be useful to meet the ever growing demand of wireless connectivity, provided we can find techniques to efficiently exploit the advantages of the Multiple-Input Multiple-Output (MIMO) system. This work explores the MIMO system in a flat quasi-static fading scenario. Such a channel occurs, for example, in packet data systems, where the channel fade is constant for the duration of a codeword and changes independently from one transmission to another. We first show why it is hard to compute the true constrained modulation outage capacity. As an alternative, we present achievable lower bounds to this capacity based on existing space-time codes. The bounds we compute are the fundamental limits to the performance of these space-time codes under maximum-likelihood decoding, optimal outer codes and asymptotically long lengths. These bounds also indicate that MIMO systems have different behavior under Gaussian signaling (unconstrained input) and under the finite alphabet setting. Our results naturally suggest the use of concatenated codes to approach near-capacity performance. However, we show that a system utilizing an iterative decoder has a fundamental limit – it cannot be universal and therefore it cannot perform arbitrarily close to its outage limit. Next, we propose two different transceiver structures that have good performance. The first structure is based on a novel BCJR-decision feedback decoder which results in performance within a dB of the outage limit. The second structure is based on recursive realizations of space-time trellis codes and uses iterative decoding at the receiver. This recursive structure has impressive performance even when the channel has time diversity. Thus, it forms the basis of a very flexible and robust MIMO transceiver structure.

Social research specifically aimed at evaluating the efficacy of coastal zone management programs at the parish (county) level in building local capacities has been meager in academic literatures and absent from Louisiana Department of Natural Resources evaluative reports. This study addresses this deficiency by examining the effectiveness of Louisiana's Local Coastal Program (LCP) in building local coastal zone management capacity. Using levels of LCP development as a proxy for capacity-building, the study examines the influence of: 1) aggregate level social and demographic characteristics, 2) structural differences, and 3) different types of issue framing (i.e. "regulator" framing versus "regulated" framing). A multiple case design, using survey, interview, observation, and archival methods of data collection, produces two multi-layered data sets - one at the parish level (nineteen Coastal Zone parishes) and the other at the individual level (a target population of parish officials, CZM administrators and advisory panel members). Patterns in findings from quantitative and qualitative analysis are matched to rival theories, namely, resource mobilization theory and social construction theory. The analyses show that parishes with LCPs have a much stronger presence of "regulator" framing than do parishes without LCPs. The "regulator" frame is particularly strong among LCP/CZM advisory panel members, while agreement with regulator frames is lowest among parish council or police jury members. Coastal hazards vulnerability is highly salient to parishes both with and without LCPs, but the translation of hazard impacts to economic vulnerabilities, such as infrastructure damage, property loss and business interruption, is far weaker for non-LCP parishes. Themes prevalent in the data include contentions over wetland mitigation issues, disjunctions between the restorative and regulatory arm of LADNR, and disparate perceptions between non-LCP parishes and LCP parishes concerning the benefits of a parish LCP over developmental and maintenance costs. Overall findings indicate that while resource mobilization is necessary to programmatic participation and the building of capacity, social construction theory can explain the differences between respondent agreement with the regulator frame, and thus the presence of institutional capacity.