The accuracy of target location and the coverage range of sensor network are two factors that affect each other in target tracking. When the flocking sensor network has a larger coverage area, it can increase the range of detecting target and the scope of environmental information. The network can also pass the information to a query source or other sensors which do not belong to the flocking network. However, the accuracy of measurements at sensors may be affected by the distances between the target and the sensors. We use mobile sensors as agents in flocking algorithm for target tracking. Every mobile sensor exchanges information with its neighbors, and keeps an appropriate separation distance with neighbors to maintain flocking. Flocking algorithm is a distributed control method for mobile sensor which can catch up the target and maintain flocking formation. In the thesis, we derive the cost function based on the accuracy of target positioning and range coverage. The proposed adaptive flocking algorithm combines the amount of information and the distance changes between neighbors based on the cost function. Each mobile sensor adaptively adjusts distance separation with all its neighbors within communication range. Sensors closer to the target shortens the separation distance between neighbors, therefore they will move toward the target and obtain better measurement. Kalman-consensus information filter is used for target positioning. The accuracy of target position can therefore be improved in the overall network. On the other hand, the sensors located far from the target will widen the distance separation between neighbors to expand the overall network area. In the thesis, we use Kalman-consensus information filter to estimate the state of a target, and use adaptive flocking algorithm for maintaining the formation of mobile sensors. Simulations show that adaptive flocking algorithm effectively improves location accuracy while maintaining approximate generally same coverage area when compared with other methods.

This research was conducted to test the hypothesis that select nutrients including glucose, leucine, arginine and glutamine stimulate conceptus development by activating mTOR (mammalian target of rapamycin; HGNC approved gene name: FRAP1, FK506 binding protein 12-rapamycin associated protein 1) signaling pathway. First, temporal changes in quantities of select nutrients (glucose, amino acids, glutathione, calcium, sodium and potassium) in uterine lumenal fluid from cyclic (Days 3 to 16) and pregnant (Days 10 to 16) ewes were determined. Total recoverable glucose, Arg, Gln, Leu, Asp, Glu, Asn, His, beta-Ala, Tyr, Trp, Met, Val, Phe, Ile, Lys, Cys, Pro, glutathione, calcium and sodium was greater in uterine fluid of pregnant compared to cyclic ewes between Days 10 and 16 after onset of estrus. Of note were remarkable increases in glucose, Arg, Leu and Gln in uterine flushings of pregnant ewes between Days 10 and 16 of pregnancy. Second, effects of the estrous cycle, pregnancy, progesterone (P4) and interferon tau (IFNT) on expression of both facilitative (SLC2A1, SLC2A3 and SLC2A4) and sodium-dependent (SLC5A1 and SLC5A11) glucose transporters, cationic amino acid transporters (SLC7A1, SLC7A2 and SLC7A3), neutral amino acid transporters (SLC1A4, SLC1A5, SLC3A1, SLC6A14, SLC6A19, SLC7A5, SLC7A6, SLC7A8, SLC38A3, SLC38A6 and SLC43A2) and acidic amino acid transporters (SLC1A1, SLC1A2 and SLC1A3) in ovine uterine endometria from Days 10 to 16 of the estrous cycle and Days 10 to 20 of pregnancy as well as in conceptuses from Days 13 to 18 of pregnancy were determined. Among these genes, SLC2A3 and SLC7A6 were detectable only in trophectoderm and endoderm of conceptuses. The abundance of mRNAs for SLC2A1, SLC2A4, SLC5A1, SLC5A11, SLC7A1, SLC7A2, SLC1A4, SLC1A5, SLC43A2 and SLC1A3 changed dynamically in ovine uterine endometria according to day of the estrous cycle and early pregnancy. Expression of mRNAs for SLC2A1, SLC5A11 and SLC7A1 in endometria was induced by P4 and further stimulated by IFNT with shortterm treatment (12 days), while expression of SLC7A1 and SLC1A5 in endometria required long-term treatment (20 days) with P4 and IFNT. Third, effects of the estrous cycle, pregnancy, P4 and IFNT on expression of nitric oxide synthase (NOS1, NOS2 and NOS3), GTP cyclohydrolase (GCH1), ornithine decarboxylase 1(ODC1), insulin-like growth factor II (IGF2), FRAP1 complexes (FRAP1, LST8, MAPKAP1, RAPTOR, RICTOR), regulators (TSC1, TSC2, RHEB) and an effector (EIF4EBP1) of FRAP1 signaling in ovine uterine endometria from Days 10 to 16 of the estrous cycle and Days 10 to 20 of pregnancy as well as in conceptuses from Days 13 to 18 of pregnancy were determined. All of these genes were expressed in ovine uterine endometrium and conceptuses. Among these genes, expression of NOS1, IGF2, RHEB and EIF4EBP1 changed dynamically due to day of the estrous cycle and early pregnancy. Progesterone stimulated NOS1 and GCH1 expression while IFNT inhibited NOS1 expression in uterine endometria, and P4 and IFNT stimulated expression of RHEB and EIF4EBP1 in uterine endometria. Collectively, these results indicate that: 1) the availability of select nutrients in the ovine uterine lumen increases to support the rapid growth and elongation of the conceptus during the peri-implantation stage of pregnancy; 2) P4 and/or IFNT stimulate(s) glucose and amino acid transporters to facilitate their transport from maternal tissues and/or blood into the uterine lumen during early pregnancy; 3) the FRAP1 cell signaling pathway mediates interactions between the maternal uterus and peri-implantation conceptus and both P4 and IFNT affect this pathway by regulating expression of RHEB and EIF4EBP1. Expression of NOS, ODC1 and IGF2 appear to be linked to FRAP1 signaling in both uteri and peri-implantation conceptuses.

Disulfide bonds play important roles in establishing and stabilizing three-dimensional protein structure, and mass spectrometry (MS) has become the primary detection method to decipher their biological and pathological roles. Several experimental methods before or after MS detection have been developed to aid in disulfide bond assignment, such as tandem MS followed by database searching or modification of the disulfide bond via chemical reduction or oxidation. Despite these technological advancements, the detection and proper assignment of disulfide bonds have remained experimentally difficult. Therefore, we have developed an alternative method for disulfide bond elucidation using capillary electrophoresis-mass spectrometry (CE-MS) combined with an on-target performic acid oxidation method for matrix assisted laser desorption/ionization (MALDI) deposited samples. An information rich CE-MS method that results in distinct charge-state trends observed in two-dimensional plots of log(mu eff) versus log (MW) was developed to enhance the confidence of peptide and protein identifications. The charge-state trends provide information about the number of basic amino acid residues present within each peptide. This information can be used to develop methods to screen for posttranslationally modified peptides (e.g., phosphorylation, disulfide bonds, etc.). In the case of disulfide bonds, the highly charged peptides (i.e., 3, 4 or greater charge states) have a high probability of being disulfide-linked peptides, owing to charge contribution of both peptides forming the disulfide bridged peptide. However, intra-linked disulfide bridged peptides can also be present at lower charge states. Therefore, a chemically selective method to rapidly locate disulfide-linked peptides that have been separated by CE-MS must be developed. An on-target performic acid oxidation method was developed to provide the chemical selectivity towards disulfide bonds, i.e., converting the cystine bond to form two peptides modified with a cysteic acid (SO3H) side chain. The on-target oxidation method offers (i) no post-oxidation sample cleanup, (ii) improved throughput over solution-phase oxidation methods, and (iii) easily adapted to CE separations coupled offline with MALDI-MS. The evaluation of the on-target oxidation experimental parameters, the fragmentation behavior of cysteic acid-containing peptides and an alternative method for disulfide bond elucidation, using CE-MS combined with the ontarget oxidation method, are discussed within.

This thesis considers the Perspective-N-Point (PNP) problem with orthogonal target geometry, as seen in the problem of cubesat relative navigation. Cubesats are small spacecraft often developed for research purposes and to perform missions in space at low cost. Sensor systems for cubesats have been designed that, by providing vector (equivalently line-of-sight, angle, and image plane) measurements, equate relative navigation to a PNP problem. Much study has been done on this problem, but little of it has considered the case where target geometry is known in advance, as is the case with cooperating cubesats. A typical constraint for cubesats, as well as other PNP applications, is processing resources. Therefore, we considered the ability to reduce processing burden of the PNP solution by taking advantage of the known target geometry. We did this by considering a specific P3P solver and a specific point-cloud correspondence (PCC) solver for disambiguating/improving the estimate, and modifying them both to take into account a known orthogonal geometry. The P3P solver was the Kneip solver, and the point-cloud-correspondence solver was the Optimal Linear Attitude Estimator (OLAE). We were able to achieve over 40% reduction in the computational time of the P3P solver, and around 10% for the PCC solver, vs. the unmodified solvers acting on the same problems. It is possible that the Kneip P3P solver was particularly well suited to this approach. Nevertheless, these findings suggest similar investigation may be worthwhile for other PNP solvers, if (1) processing resources are scarce, and (2) target geometry can be known in advance.

The presented thesis has closely examined the discussion on policy assignments that are restricted on an open macroeconomic model; very little reference has focused on a closed macroeconomic model. As we know, Ramirez (1986) is the first person who has applied policy assignment to a closed macroeconomic model. But Chang and Lai have clearly proved that Ramirez's model is not appropriate for policy assignment, and a way to redeem the problem is to introduce policy instrument to aggregate supply side. Also, this thesis is going to focus on, instead of introduced the policy instrument to aggregate supply side, use system endogenous on aggregate supply function. Could this kind of correction redeem the flaws made by Ramirez? Hence, this thesis would apply the reality intertemporal substitution effect of labor to subsume an aggregate supply side, then discuss the relationship on policy assignment that is between policy instrument and policy target that would derive the conclusion as below: When a model does not include the intertemporal substitution effect of labor, it degrades to a Ramirez's model (1986) and cannot be used for policy assignment. On the other hand, a model including intertemporal substitution effect of labor remedies the flaws in Ramirez's model (1986) and can be used for appropriate policy assignment assuming that government spending is in complement with private spending.

There are much economic and financial data which are restricted by some bounds, such as expenditure shares, unemployment, norminal interest rate, or target zone exchange rate. How to interpret and analyze time series whose behaviors can be well approximated by means of integrated processes, I(1), but are ¡§limited¡¨ in the sense that their range is constrained by fixed bounded is what this thesis develops. One method to analyze bounded variable of this paper is ¡§The Bounded Unit Root¡¨ which provided by Cavaliere (2005), and the other is using Gibbs sampling simulation and trying to recover the part of hidden variables. We would examin some empirical problems that has often been tackled in the literature and we give three time series which include Danish kron/Deutshe mark, Belgium Franc/ Deutshe mark, and Japan 1 mouth interbank interest rate for examples. We conclude that these three time series data are I(0) in classical unit root test framework, but are all I(1) in The Bounded Unit Root test framework. And the results of Gibbs sampling simulation are that Danish kron/Deutshe mark and Belgium Franc/ Deutshe mark are I(0), but Japan 1 mouth interbank interest rate is I(1).

In the past time, I had opportunity to serve as Rear Admiral Executive Officer, Office of Deputy Chief of General Staff for Personnel, Ministry of National Defense ROC. To establish "The National Armed Forces Recruitment Center" was my duty during that time. Under my command and control,the Recruitment Center, Ministry of National Defense, was founded on Jan 1, 1999. Now this center has operated for 7 years. After attending the EMBA Class, marketing and business management are our core courses, I want to use this knowledge to analysis the recruiting situation, market segmentation, target market, marketing strategy and management of this center. I hope to get some useful conclusion to enhance the marketing strategy and management, and make youths obtain the military information of joining the ROC military academies in time, and therefore the National Armed Forces can enhance quality of cadres. The major research findings of this study are summarized as follows: 1. The achievement of Recruitment Center has been excellent for seven years. Especially, in 2000 and 2001, the center got the Excellent Award Of Executive Yuan for two times. 2. In Taiwan, there are 77.7% people to know the activity of Recruitment Center according the issue of Executive Yuan in 2001. 3. The number of female joining the National Armed Forces is adding. The major target market is in the South of Taiwan, the second one is in the North of Taiwan, the third is in the Central Taiwan. 4. Most of student, their family outcome is 20000 to 50000 New Taiwan Dollars and most of them are the middle-low outcome family. 5. Speaking the occupation of student parents, most of them are workers and merchants, and most of them graduated from the high school. 6. Most of student, their motivation of joining the National Armed Forces is to emphasize the requirement of high level, such as Love and Belongingness Needs; Esteem Needs;Self Actualization Needs. 7. People Communication plays a very important role and network marketing also plays a key role according the Metcalfe Law. 8. In 2003, over 25000 young people took part in the entrance examination.But only 5.4% examinee can be elected to go to military academies, this is the lowest record in the history. Their examination score is up to the level of national university. 9. In the near future, the master degree will be the major market requirement. The voluntary officer should get the master degree before promoting to major or lieutenant commander. All of these achievement will enhance the image of National Armed Forces and competitive strength. 10. This study provides marketing strategy and action items in the Chapter 6, Article 2.

This thesis examines the performance of some dim target detection algorithms in low-SNR imaging scenarios. In the past research, there have been numerous attempts for detection and tracking barely visible targets for military surveillance applications with infrared sensors. In this work, two of these algorithms are analyzed via extensive simulations. In one of these approaches, dynamic programming is exploited to coherently integrate the visible energy of dim targets over possible relative directions, whereas the other method is a Bayesian formulation for which the target likelihood is updated along time to be able to detect a target moving in any direction. Extensive experiments are conducted for these methods by using synthetic image sequences, as well as some real test data. The simulation results indicate that it is possible to detect dim targets in quite low-SNR conditions. Moreover, the performance might further increase, in case of incorporating any a priori information about the target trajectory.

In this thesis the radar target tracking problem in Bayesian estimation framework is studied. Traditionally, linear or linearized models, where the uncertainty in the system and measurement models is typically represented by Gaussian densities, are used in this area. Therefore, classical sub-optimal Bayesian methods based on linearized Kalman filters can be used. The sequential Monte Carlo methods, i.e. particle filters, make it possible to utilize the inherent non-linear state relations and non-Gaussian noise models. Given the sufficient computational power, the particle filter can provide better results than Kalman filter based methods in many cases. A survey over relevant radar tracking literature is presented including aspects as estimation and target modeling. In various target tracking related estimation applications, particle filtering algorithms are presented.

The Weapon-Target Assignment (WTA) problem is a fundamental problem arising in defense-related applications of operations research. Optimizing the WTA is about the selection of the most appropriate weapon for each target in the problem. Basically the aim is to have the maximum effect on targets. Different algorithms / branch and bound (B&amp / B), genetic algorithm (GA), variable neighborhood search (VNS), are used to solve this problem. In this thesis, a more complex version of this problem is defined and adapted to fire support automation (Command Control Communication Computer Intelligence, C4I) systems. For each target, a weapon with appropriate ammunition, fuel, timing, status, risk is moved to an appropriate ammunitions, economy of fuel, risk analysis and time scheduling are all integrated into the solution. B&amp / B, GA and VNS are used to solve static and dynamic WTA problem. Simulations have shown that GA and VNS are the best suited methods to solve the WTA problem.