A Box-Counting Method with Adaptable Box Height for Measuring the Fractal Feature of Images

Most of the existing box-counting methods for measuring fractal features are only applicable to square images or images with each dimension equal to the power of 2 and require that the box at the top of the box stack of each image block is of the same height as that of other boxes in the same stack, which gives rise to inaccurate estimation of fractal dimension. In this paper, we propose a more accurate box-counting method for images of arbitrary size, which allows the height of the box at the top of each grid block to be adaptable to the maximum and minimum gray-scales of that block so as to circumvent the common limitations of existing box-counting methods

Improved Localization Algorithms in Indoor Wireless Environment

Localization has been considered as an important precondition for the location-dependent applications such as mobile tracking and navigation.To obtain specific location information, we usually make use of Global Positioning System(GPS), which is the most common plat- form to acquire localization information in outdoor environments. When targets are in indoor environment, however, the GPS signal is usually blocked, so we also consider other assisted positioning techniques in order to obtain accurate position of targets. In this thesis, three different schemes in indoor environment are proposed to minimize localization error by placing refer- ence nodes in optimum locations, combining the localization information from accelerometer sensor in smartphone with Received Signal Strength (RSS) from reference nodes, and utilizing frequency diversity in Wireless Fidelity (WiFi) environment. Deployments of reference nodes are vital for locating nearby targets since they are used to estimate the distances from them to the targets. A reference nodes’ placement scheme based on minimizing the average mean square error of localization over a certain region is proposed in this thesis first and is applied in different localization regions which are circular, square and hexagonal for illustration of the flexibility of the proposed scheme. Equipped with accelerometer sensor, smartphone provides useful information which out- puts accelerations in three different directions. Combining acceleration information from smart- phones and signal strength information from reference nodes to prevent the accumulated error from accelerometer is studied in this thesis. The combined locating error is narrowed by as- signing different weights to localization information from accelerometer and reference nodes. In indoor environment, RSS technology based localization is the most common way to imply since it require less additional hardware compared to other localization technologies. However, RSS can be affected greatly by complex circumstance as well as carrier frequency. Utilization of diverse frequencies to improve localization performance is proposed in the end of this thesis along with some experiments applied on Software Defined Platform (SDR)

Digital image forensics

Digital image forensics is a relatively new research field that aims to expose the origin and composition of, and the history of processing applied to digital images. Hence, the digital image forensics is expected to be of significant importance to our modern society in which the digital media are getting more and more popular. In this thesis, image tampering detection and classification of double JPEG compression are the two major subjects studied. Since any manipulation applied to digital images changes image statistics, identifying statistical artifacts becomes critically important in image forensics. In this thesis, a few typical forensic techniques have been studied. Finally, it is foreseen that the investigations on endless confliction between forensics and anti-forensics are to deepen our understanding on image statistics and advance civilization of our society

Long-term versus Short-term Contracting in Salesforce Compensation

This dissertation investigates multi-period salesforce incentive contracting. The first chapter is an overview of the problems as well as the main findings. The second chapter continues with a review of the related literatures. The third and fourth chapters address a central question in salesforce contracting: how frequently should a firm compensate its sales agents over a long-term horizon? Agents can game the long-term contract by varying their effort levels dynamically over time, as discussed in Chapter 3, or by altering between a “bold" action and a “safe" action dynamically over time, as discussed in Chapter 4. Chapter 3 studies multi-period salesforce incentive provisions when agents are able to vary their demand-enhancing effort levels dynamically. I establish a stylized agency-theory model to analyze this central question. I consider salespeople's dynamic responses in exerting effort (often known as “gaming"). I find that long time horizon contracts weakly dominate short time horizon contracts, even though they enable gaming by the agent, because they allow compensation to be contingent on more extreme outcomes; this not only motivates the salesperson more, but also leads to lower expected payment to the salesperson. A counterintuitive observation that my analysis provides is that under the optimal long time horizon contract, the firm may find it optimal to induce the agent to not exert high effort in every period. This provides a rationale for effort exertion patterns that are often interpreted as suboptimal for the firm (e.g., exerting effort only in early periods, often called “giving up"; exerting effort only in later periods, often called “postponing effort"). I also discuss the implication of sales pull-in and push-out, and dependence of periods (through limited inventory) upon the structure of the optimal contracting. Chapter 4 examines multi-period salesforce incentive contracting, where sales agents can dynamically choose between a bold action with higher sales potential but also higher variance, and a safe action with limited sales potential but lower variance. I find that the contract format is determined by how much the firm wants later actions to depend on earlier outcomes. Making later actions independent of earlier demand outcomes reduces agents' gaming, but it also reduces an agent's incentive to take bold actions. When the two periods are independent, an extreme two-period contract with a hard-to-achieve quota, or a polarized two-period contract allowing agents to make up sales, can strictly dominate a period-by-period contract, because they induce more bold actions in earlier periods by making later actions dependent on earlier outcomes. However, when the two periods are dependent through a limited inventory to be sold across two periods, the period-by-period contract can strictly dominate the two-period contract, by allowing the principal more flexibility in adjusting the contract