This paper investigates what factors affect the destination choice for Jordanian to 8 countries (Oman, Saudi Arabia, Syria, Tunisia, Yemen, Egypt, Lebanon and Bahrain) using panel data analysis. Number of outbound tourists is represented as dependent variable, which is regressed over five explanatory variables using fixed effect model. The finding of this paper is that tourists from Jordan have weak demand for outbound tourism; Jordanian decision of traveling abroad is determined by the cost of traveling to different places and choosing the cheapest alternative.

Most studies of gustatory coding have been performed in either anesthetized or awake, passively stimulated rats. In this dissertation the influences of behavioral state on gustatory processing in awake rats are described. In the first set of experiments, the effects of non-contingent tastant delivery on the chemical tuning of single neurons were explored. Tastants were delivered non-contingently through intra-oral cannulas to restrained, non water-deprived rats while single unit responses were recorded from the gustatory cortex (GC). As the subjects' behavior progressed from acceptance to rejection of the tastants, the chemical tuning of the neurons changed as well. This suggests that the subjects' behavioral state powerfully influences gustatory processing. In the second set of experiments, rats were trained to lick for fluid reinforcement on an FR5 schedule while single unit activity was recorded from GC. In this case, the chemical tuning was much more stable. Under this paradigm, chemosensory responses were rapid (~ 150 ms) and broadly tuned. In the third study, it was found that ensembles of GC neurons could discriminate between tastants and their concentrations on a single trial basis, and such discrimination was accomplished with a combination of rate and temporal coding. Ensembles of GC neurons also anticipated the identity of the upcoming stimulus when the tastant delivery was predictable. Finally, it was found that ensembles of GC neurons could discriminate between the bitter stimuli nicotine and quinine. Nicotine is both a bitter tastant and a trigeminal stimulant, and when the acetylcholine receptors in the lingual epithelium were blocked with mecamylamine, the ensembles failed to discriminate nicotine from quinine.

The optimum configuration of rotor-to-generator size for wind turbines is dependent upon the wind resource and is the configuration that produces the most electrical energy at a fixed capital cost. This optimization study held the combined cost of the rotor plus generator constant, but varied the respective sizes of the rotor and generator within this constraint. Total annual electrical energy was computed for each configuration at a series of wind resources each defined by a different Weibull probability distribution. In each case the configuration that produced the most electrical energy was determined to be the optimum. The fixed capital cost was also varied to see the effect on the optimum at each wind resource. It was found that the optimal rotor-to-generator size decreased as the average wind speed at a resource increased, and increased as Weibull shape parameter k increased. The optimal rotor-to-generator size decreased at a constant wind resource as the fixed capital cost increased. In each case there was a corresponding optimal capacity factor which never exceeded 0.5. Capacity factors above this optimum resulted in less electrical energy being produced for the same capital cost. The final product of the study is a series of graphs showing the optimum rotor size for a given generator size at a series of wind resources.

We consider the problem of finding a common fixed point of an infinite family ${T_n}$ of nonlinear self-mappings of a closed convex subset $C$ of a real Hilbert space $H$. Namely, we want to find a point $x$ with the property (assuming such common fixed points exist): [ xin igcap_{n=1}^infty ext{Fix}(T_n). ] We will use the Krasnoselskii-Mann (KM) Type inertial iterative algorithms of the form $$ x_{n+1} = ((1-alpha_n)I+alpha_nT_n)y_n,quad y_n = x_n + eta_n(x_n-x_{n-1}).eqno(*)$$ We discuss the convergence properties of the sequence ${x_n}$ generated by this algorithm (*). In particular, we prove that ${x_n}$ converges weakly to a common fixed point of the family ${T_n}$ under certain conditions imposed on the sequences ${alpha_n}$ and ${eta_n}$.

This thesis presents a feedback design for an active noise cancellation (ANC) headphone. The designed ANC headphone consists of an analog controller, an audio power amplifier, a headphone speaker, a mini microphone, and a microphone amplifier, which constitute a feedback loop. The controller design follows the method of feedback sensitivity shaping with degree constraint introduced by R. Nagamune and A. Blomqvist in 2005. The advantage of this method is that it eliminates the needs for choosing an analytic weighting function and performing model reduction to yield a lower-order controller, as commonly required in conventional H2/H¡Û optimizations. A fifth-order analog controller for the ANC headphone is designed. The experimental result shows a maximum acoustic noise reduction of 19.7 dB near 200 Hz and an overall noise reduction of more than 10 dB in the control frequency band from 107 Hz to 523 Hz. Moreover, the out-of-band noise amplification is limited to a barely noticeable level of 4.26 dB.

Parameterized NP-hard problems are NP-hard problems that are associated with special variables called parameters. One example of the problem is to find simple paths of length k in a graph, where the integer k is the parameter. We call this problem the p-path problem. The p-path problem is the parameterized version of the well-known NP-complete problem - the longest simple path problem. There are two main reasons why we study parameterized NP-hard problems. First, many application problems are naturally associated with certain parameters. Hence we need to solve these parameterized NP-hard problems. Second, if parameters take only small values, we can take advantage of these parameters to design very effective algorithms. If a parameterized NP-hard problem can be solved by an algorithm of running time in form of f(k)nO(1), where k is the parameter, f(k) is independent of n, and n is the input size of the problem instance, we say that this parameterized NP-hard problem is fixed parameter tractable (FPT). If a problem is FPT and the parameter takes only small values, the problem can be solved efficiently (it can be solved almost in polynomial time). In this dissertation, first, we introduce several techniques that can be used to design efficient algorithms for parameterized NP-hard problems. These techniques include branch and bound, divide and conquer, color coding and dynamic programming, iterative compression, iterative expansion and kernelization. Then we present our results about how to use these techniques to solve parameterized NP-hard problems, such as the p-path problem and the pd-feedback vertex set problem. Especially, we designed the first algorithm of running time in form of f(k)nO(1) for the pd-feedback vertex set problem. Thus solved an outstanding open problem, i.e. if the pd-feedback vertex set problem is FPT. Finally, we will introduce how to use parameterized algorithm techniques to solve the signaling pathway problem and the motif finding problem from bioinformatics.

We consider the problem of scheduling a given set of tasks on multiple pro- cessors with predefined periods of unavailability, with the aim of minimizing the maximum completion time. Since this problem is strongly NP-hard, polynomial ap- proximation algorithms are being studied for its solution. Among these, the best known are LPT (largest processing time first) and Multifit with their variants. We give a Multifit-based algorithm, FFDL Multifit, which has an optimal worst- case performance in the class of polynomial algorithms for same-speed processors with at most two downtimes on each machine, and for uniform processors with at most one downtime on each machine, assuming that P 6= NP. Our algorithm finishes within 3/2 the maximum between the end of the last downtime and the end of the optimal schedule. This bound is asymptotically tight in the class of polynomial algorithms assuming that P 6= NP. For same-speed processors with at most k downtimes on each machine our algorithm finishes within ( 3 2 + 1 2k ) the end of the last downtime or the end of the optimal schedule. For problems where the optimal schedule ends after the last downtime, and when the downtimes represent fixed jobs, the maximum completion time of FFDL Multifit is within 3 2 or ( 3 2+ 1 2k ) of the optimal maximum completion time. We also give an LPT-based algorithm, LPTX, which matches the performance of FFDL Multifit for same-speed processors with at most one downtime on each machine, and is thus optimal in the class of polynomial algorithms for this case. LPTX differs from LPT in that it uses a specific order of processors to assign tasks if two processors become available at the same time. For a similar problem, when there is at most one downtime on each machine and no more than half of the machines are shut down at the same time, we show that a bound of 2 obtained in a previous work for LPT is asymptotically tight in the class of polynomial algorithms assuming that P 6= NP.

This paper aims on the study of developing the firmware program for the monitor chips designed inside the battery set of a Notebook power management system, with the function of monitoring safety during battery charge/discharge via the chips; meanwhile, to estimate the residual capacity of the battery. Owing to the chemistry properties of the battery, whose residual capacity will be affected by the current flow during charge/discharge, high/low of the ambient temperature, fatigue of the battery, as a result, variations of the residual capacity will be presented in non-linear. Therefore, in estimation of the battery residual capacity, using the curve learned from the practical experiment on the battery charge/discharge to be the basis for us to find out the appropriate parameters under the relevant influence factors for revision. It will be more accurate in estimation of the battery residual capacity. At the same time, the battery signal can be transmitted to the managing end of the Notebook power management system via the system management interface, which may enable the system to operate more efficiently.

This dissertation modifies the model of Yang and Ng (1995) to investigate the condition of the emergence of the firm from a specialized exchange economy. It is assumed in this dissertation that there are fixed costs involved in the operation of a firm. After taking into account of this factor, I re-examine its effects on the division of labor and the structure of firm following Yang and Ng¡¦s framework. The model adopts an inframarginal framework to analyze the subject, in which a firm demonstrates diminishing returns, while both the final labor input and the intermediate labor input demonstrates increasing returns defined upon individuals. However, it is assumed that only the final labor input has the economies of specialization. It is argued in this dissertation that the existence of fixed learning costs may stimulate the economy to undergo structural changes if suitable conditions are met, which are largely related to relative market efficiency between markets.

In this thesis, we consider the following delay boundary value problem egin{eqnarray*}(BVP)left{begin{array}{l}y'(t)+q(t)f(t,y(sigma(t)))=0, tin(0,1)/{ au}, y(t)=xi(t), tin[- au_{0},0], y(1)=0,end{array} right. end{eqnarray*}, where the functions f and q satisfy certain conditions; $sigma(t)leq t$ is a nonlinear real valued continuous function. We use two different methods to establish some existence criteria for the solution of problem (BVP). We generalize the delay term to a nonlinear function and obtain more general and supplementary results for the known ones about linear delay term due to Agarwal and O¡¦Regan [1] and Jiang and Xu [5].