Treadmill is a highly popular fitness equipments. One of the most important purposes of running is to consume redundant energy of the body. A well designed exercise intensity plan can achieve the benefits of exercise while avoiding sport injuries. Calculating the appropriate exercise intensity is therefore a valuable study issue. Current commercially available treadmills cannot provide sufficient physiological data. In particular, in order to measure the ground reaction force (GRF) of the runners, traditional approach is to design treadmill as a rigid body. Such treadmills are thus expensive and heavy. To estimate heart rate (HR), ECG measurement is typically required. However, sweat can cause the patch to loose and the quality of the signal transmission can also be degraded by environmental noises. Thus the aim of this work is to develop a simple and effective method to assess exercise intensity by estimating HR with GRF.. To achieve this goal, this work places load cells under the legs of the treadmill. By constructing the dynamic model of the treadmill via system identification technique, we can estimate the actual GRF from the measurements of the load cells. After computing the TVI (Total Vertical Impulse) index from the GRF, this work then investigates the linear relationship between TVI and running energy consumption by estimating HR from TVI. Based on the known relationship between HR and exercise intensity, we can observe the runner¡¦s condition from the speed of HR recovery and the HR time response during running. By means of linear regression method, it is found that the linear relations between TVI index and these HR measures are statistically significant. The p-value of such statically tests become even smaller when TVI index is normalized.

Issues related to global warming and weather changes have forced people start to pay attention to energy saving. We expect that Smart Home Energy Management (SHEM) would be an important development over the next decade. In some environments cost is important, in other environments living quality is important and in other environments a tradeoff between cost and living quality is important. SHEM means being able to manage electrical loads so as to meet different purposes in homes. In this thesis, we develop a SHEM to curtail some electrical loads at peak time to meet predefined circuit level demand limits while minimizing the effect on users¡¦ living quality. The core of our SHEM is an electrical control loop which is developed based on heuristic modifications through lots of case studies and trials. To this end, we study several utilization characteristics of household loads including air conditioning, water heaters clothes dryers, and electric vehicles and model their behaviors through computer simulations. Finally, we implement the whole ideal of our SHEM in LabVIEW (Laboratory Virtual Instrument Engineering Workbench). Several simulations are conducted to verify the robustness and efficiency of our SHEM. keyword : Quick Charge,Load Priority,Convience Preference,Severity Indices,Duration Indices.

Renewal process has been often employed as a mathematical model of the failure and repair cycle of components in power system reliability assessment. This implies that after repair, the component is assumed to be restored to be in as good as new condition in terms of reliability perspective. However, some of the components may enter an aging stage as the system grows older. This thesis describes how aging characteristics of a system may impact the calculation of commonly used quantitative reliability indices such as Loss of Load Expectation (LOLE), Loss of Load Duration (LOLD), and Expected Energy Not Supplied (EENS). To build the history of working and failure states of a system, Stochastic Point Process modeling based on Sequential Monte Carlo simulation is introduced. Power Law Process is modeled as the failure rate function of aging components. Power system reliability analysis can be made at the generation capacity level where transmission constraints may be included. The simulation technique is applied to the Single Area IEEE Reliability Test System (RTS) and the results are evaluated and compared. The results show that reliability indices become increased as the age of the system grows.

The simulation of seafloor-steel catenary interaction and prediction of riser fatigue life required an accurate characterization of seafloor stiffness as well as realistic description of riser load-deflection (P-y) response. This thesis presents two load-deflection (P-y) models (non-degradating and degradating models) to simulate seafloor-riser interaction. These two models considered the seafloor-riser system in terms of an elastic steel pipe supported on non-linear soil springs with vertical motions. These two models were formulated in terms of a backbone curve describing self-embedment of the riser, bounding curves describing P-y behavior under extremely large deflections, and a series of rules for describing P-y behavior within the bounding loop. The non-degradating P-y model was capable of simulating the riser behavior under very complex loading conditions, including unloading (uplift) and re-loading (downwards) cycles under conditions of partial and full separation of soils and riser. In the non-degradating model, there was a series of model parameters which included three riser properties, two trench geometry parameters and one trench roughness parameter, two backbone curve model parameters, and four bounding loop model parameters. To capture the seafloor stiffness degradation effect due to cyclic loading, a degradating P-y model was also developed. The degradating model proposes three degradation control parameters, which consider the effects of the number of cycles and cyclic unloading-reloading paths. Accumulated deflections serve as a measure of energy dissipation. The degradating model was also made up of three components. The first one was the backbone curve, same as the non-degradating model. The bounding loops define the P-y behavior of extreme loading deflections. The elastic rebound curve and partial separation stage were in the same formation as the non-degradating model. However, for the re-contact and re-loading curve, degradation effects were taken into the calculation. These two models were verified through comparisons with laboratory basin tests. Computer codes were also developed to implement these models for seafloor-riser interaction response.

Low Dropout Regulators (LDOs) are extensively used in portable applications like mobile phones, PDAs and notebooks. These portable applications demand high power efficiency and low output voltage ripple. In addition to these, the radio circuits in these applications demand high power supply rejection (PSR). The output voltage of a conventional DC/DC converter (generally switched mode) has considerable ripple which feeds as input to these LDOs. And the challenge is to suppress these ripples for wide range of frequencies (for radio units) to provide clean supply. Enhanced buffer based compensation is proposed for the fully on-chip CMOS LDO which stabilizes the loop for different load conditions as well as improve the power supply rejection (PSR) until frequencies closer to open loop‟s unity-gain frequency. The stability and PSR are totally valid even for load capacitor varying from 0 to 100 pF. The proposed capacitor-less LDO is fabricated in On-Semi 0.5 μm fully CMOS process. Experimental results confirm a PSR of -30 dB till 420 KHz for the maximum load current of 50mA. The load transients of the chip shows transient glitches less than 90 mV independent of output capacitance.

Mass Rapid Transit(MRT) plays a very important role for the city development,the investment cost is very expensive. It is necessary to derive the MRT system planning by considering the service reliability and performance index according to the forecast of annual ridership. With the less ridership as compared to Taipei MRT network, Kaohsiung MRT has to be developed to achieve the most cost effective investment of power supply and rolling stock planning. This thesis is to investigate the proper expansion planning of traction substations (TSS) for an electrified mass rapid transit system. The motion equation of train sets is used to solve the mechanical power consumption at each time snapshot according to the operation timetable, the passenger ridership and various types of operation resistance. The mathematical models of power converters in traction substations for different operation modes have been derived. With all train sets operated along the main line, the AC/DC load flow analysis is performed to find power demand of all traction substations for annual system peak operation over the study period. The objective function is formulated by considering both the voltage drop of train sets and investment cost of traction substations as the equivalent cost of all feasible states of each year. By performing the dynamic programming (DP) and immune algorithm (IA), the expansion planning of traction substations to achieve the minimum overall cost has been solved by identifying the optimal capacity and locations of new traction substations to be committed at each year.

An Integrated Chaos Search Genetic Algorithm (CGA) /Fuzzy System (FS), Tabu Search (TS) and Neural Fuzzy Network (NFN) method for load forecasting is presented in this paper. A Fuzzy Hyper-Rectangular Composite Neural Networks (FHRCNNs) was used for the initial load forecasting. Then we used CGAFS and TS to find the optimal solution of the parameters of the FHRCNNs, instead of Back-Propagation (BP). First the CGAFS generates a set of feasible solution parameters and then puts the solution into the TS. The CGAFS has good global optimal search capabilities, but poor local optimal search capabilities. The TS method on the other hand has good local optimal search capabilities. We combined both methods to try and obtain both advantages, and in doing so eliminate the drawback of the traditional ANN training by BP. This thesis presents a hybrid Chaos Search Immune Algorithm (IA)/Genetic Algorithm (GA) and Fuzzy System (FS) method (CIGAFS) for solving short-term thermal generating unit commitment problems (UC). The UC problem involves determining the start-up and shutdown schedules for generating units to meet the forecasted demand at the minimum cost. The commitment schedule must satisfy other constraints such as the generating limits per unit, reserve and individual units. We combined IA and GA, then added chaos search and fuzzy system approach in it. Then we used the hybrid system to solve UC. Numerical simulations were carried out using four cases; ten, twenty and thirty thermal units power systems over a 24-hour period.

In a P2P (Peer-to-Peer) system, every user node, i.e., the peer, may dynamically join and leave the system. In general, peers can exchange information and contribute portions of their resources to the community in a P2P system. They are treated functionally identical. Therefore, it is very important to efficiently locate the peer that stores a particular data item and make the system load balance in P2P systems. Chord is a structured P2P system which has a ring architecture, where a structured P2P system means that peers maintain information about what resources neighbor peers offer. It provides support for just one operation: to assign the data key to the peer by hashing. Therefore, we can efficiently locate the peer that stores a particular data key. However, in the Chord system, most of data keys may be assigned to the same peer by using the static hashing scheme, which results in the case that the load of the system not be balanced. Therefore, in this thesis, we propose a strategy which uses the dynamic hashing scheme to locate the data key based on the Chord architecture, and to maintain the load balance. A dynamic hashing allows the address space allocated to the file to be increased and reduced without reorganizing the whole file. The basic idea of a dynamic hashing approach is to split the current overflow bucket into two new buckets by using the next level hashing function without reorganizing the other buckets, and our proposed strategy uses such an approach. In our strategy, we use two data structures for a peer, one stores the data hashed to the current peer and the other one stores the data from its predecessor. When an overflow occurs in the bucket after insertion of a data key, we use the one hashing function to split data keys stored in the data bucket. If the capacity of the current peer is larger than that of its successor, we forward some data keys to the successor. Similarly, we also consider the case of an underflow occurs in the bucket after deletion of a data key. Therefore, the unbalanced condition of the load (even distribution of items to nodes) of the system can be improved based on our strategy. From our simulation results, we show that the load of the P2P system based on our strategy is much more balanced than that used in the Chord system, when there are few peers and a lot of data keys in the P2P system. We also show that the load based on our strategy is still more balanced than that used in the Chord system, when the data distribution becomes skew.

The rollers of run out table in Hot Strip Mill are operated with variable high rotational speed under a severe environment of high temperature and much cooling water around. And the table takes long space about 128 meters of length with over 330 rollers. The rollers of this area often break down, and it takes long to make urgent repair. So it costs about ten million NT dollars per year for mill shut-down. Although some improvements have been made before, the troubles still happens frequently. Then the temporary countermeasures of shortening the maintenance cycle and increasing the grease supply have been applied to prevent the break-down frequency from aggravation . But it wastes the cost and does not meet the environmental policy. This study analyzes many damage phenomena. Then it assumes that the 75% of roller running break-down is bearing damage resulting from bad lubrication condition and abnormal axial load. The cooling water which penetrates into bearing housing will result in grease emulsification and its consistency diluting. This certainly causes the bad lubrication condition and bearing rusting. In the meantime, if the floating function of roller bearing is inactive, the bearings will be operated under abnormal high axial load and without appropriate lubrication. Then the bearing will be damaged rapidly and must be repaired quickly. In order to improve bad lubrication and bearing rusting, this study modifies sealing arrangement and grease feeding circuit for bearing housing with the special functions of water obstruction, drainage and resistance to prevent water penetration. In addition, the overflow of grease will be collected to meet the environmental needs. Meanwhile, to look for better water resistance and mechanical stability for greasing, the study also discusses the relationship between consistency variation and thickening soap base after grease emulsification. During a three-month running of the new design , the water contents are stably under 1.5% which has greatly advanced. And the quantity of grease supply is under 10% of existing one. In order to improve the inactive floating function of roller bearings, this study not only analyzes the derivation of problems but also modifies the dimensional tolerance and adds cylindricity of geometric tolerance for the bore of bearing housing. This will ensure complete loose fit and shape accuracy to prevent the interference fit between the bore and bearing caused by manufacturing inaccuracy or other mistakes

A Peer-to-Peer system is a distributed system whose component nodes participate in similar roles. Every user node (the peer) can exchange and contribute its resources to another one in the system. Similar to the case that peers may dynamically join and leave the system, the data will also be inserted into and removed from the system dynamically. Given a certain range, a range query will find any data item whose value within the range. For example, a range query can find all the Beatle's works between 1961 and 1968 for us. However, once the range data is distributed over a P2P system through the hash function which has been used largely in many P2P systems, the continuity of the range data is not guaranteed to exist. Therefore, finding the scattered data whose value within a certain range costs much in a P2P system. The Distributed Segment Tree method (DST) preserves the local continuity of the range data at each node by using a segment tree and can break any given range into minimum number of node intervals whose union constitutes the whole requested range. The DST method works based on the Distributed Hash Table (DHT) logic; therefore, it can be applied in any DHT-based P2P system. However, data distribution of the DST method may cause overlapping. When searching a data range, the DST method sends more number of requests than what is really needed. Although the DST method designs the Downward Load Stripping Mechanism, the load on peers still may not be balanced. The main reason of these problems is that the DST method applies the DHT logic to the P2P systems. Therefore, in this thesis, we propose a method called Structured Segment Tree (SST) that does not use the DHT logic but embeds the structure of the segment tree into the P2P systems. In fact, the P2P network topology of an SST is the structure of a segment tree. Unlike a DST, an SST can fully reflect the properties of the original segment tree. Each peer in our proposed P2P system represents a node of a segment tree. Data intervals at the same level are continuous and will not overlap with each other. The union of data intervals at a level with full nodes is totally the whole data range which the P2P system can support. When searching a data range, the SST method sends as many number of requests as needed. In addition, we add sibling links to preserve the spatial locality and speed up the search efficiency. For the issue of load balance, our SST method also performs better than the DST method. From our simulation, we show that the SST method routes less number of peers to locate the requested range data than the DST method. We also show that the load based on our method is more balanced than that based on the DST method.