Adaptive microfoundations for emergent macroeconomics

In this paper we present the basics of a research program aimed at providing microfoundations to macroeconomic theory on the basis of computational agentbased adaptive descriptions of individual behavior. To exemplify our proposal, a simple prototype model of decentralized multi-market transactions is offered. We show that a very simple agent-based computational laboratory can challenge more structured dynamic stochastic general equilibrium models in mimicking comovements over the business cycle.Microfoundations of macroeconomics, Agent-based economics, Adaptive behavior

Application of Multi-Sensor Fusion Technology in Target Detection and Recognition

Application of multi-sensor fusion technology has drawn a lot of industrial and academic interest in recent years. The multi-sensor fusion methods are widely used in many applications, such as autonomous systems, remote sensing, video surveillance, and the military. These methods can obtain the complementary properties of targets by considering multiple sensors. On the other hand, they can achieve a detailed environment description and accurate detection of interest targets based on the information from different sensors.This book collects novel developments in the field of multi-sensor, multi-source, and multi-process information fusion. Articles are expected to emphasize one or more of the three facets: architectures, algorithms, and applications. Published papers dealing with fundamental theoretical analyses, as well as those demonstrating their application to real-world problems

Spectral image utility for target detection applications

In a wide range of applications, images convey useful information about scenes. The “utility” of an image is defined with reference to the specific task that an observer seeks to accomplish, and differs from the “fidelity” of the image, which seeks to capture the ability of the image to represent the true nature of the scene. In remote sensing of the earth, various means of characterizing the utility of satellite and airborne imagery have evolved over the years. Recent advances in the imaging modality of spectral imaging have enabled synoptic views of the earth at many finely sampled wavelengths over a broad spectral band. These advances challenge the ability of traditional earth observation image utility metrics to describe the rich information content of spectral images. Traditional approaches to image utility that are based on overhead panchromatic image interpretability by a human observer are not applicable to spectral imagery, which requires automated processing. This research establishes the context for spectral image utility by reviewing traditional approaches and current methods for describing spectral image utility. It proposes a new approach to assessing and predicting spectral image utility for the specific application of target detection. We develop a novel approach to assessing the utility of any spectral image using the target-implant method. This method is not limited by the requirements of traditional target detection performance assessment, which need ground truth and an adequate number of target pixels in the scene. The flexibility of this approach is demonstrated by assessing the utility of a wide range of real and simulated spectral imagery over a variety ii of target detection scenarios. The assessed image utility may be summarized to any desired level of specificity based on the image analysis requirements. We also present an approach to predicting spectral image utility that derives statistical parameters directly from an image and uses them to model target detection algorithm output. The image-derived predicted utility is directly comparable to the assessed utility and the accuracy of prediction is shown to improve with statistical models that capture the non-Gaussian behavior of real spectral image target detection algorithm outputs. The sensitivity of the proposed spectral image utility metric to various image chain parameters is examined in detail, revealing characteristics, requirements, and limitations that provide insight into the relative importance of parameters in the image utility. The results of these investigations lead to a better understanding of spectral image information vis-à-vis target detection performance that will hopefully prove useful to the spectral imagery analysis community and represent a step towards quantifying the ability of a spectral image to satisfy information exploitation requirements

Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression

Personalized medicine—a modern approach for the diagnosis and management of hypertension

The main goal of treating hypertension is to reduce blood pressure to physiological levels and thereby prevent risk of cardiovascular disease and hypertension-associated target organ damage. Despite reductions in major risk factors and the availability of a plethora of effective antihypertensive drugs, the control of blood pressure to target values is still poor due to multiple factors including apparent drug resistance and lack of adherence. An explanation for this problem is related to the current reductionist and ‘trial-and-error’ approach in the management of hypertension, as we may oversimplify the complex nature of the disease and not pay enough attention to the heterogeneity of the pathophysiology and clinical presentation of the disorder. Taking into account specific risk factors, genetic phenotype, pharmacokinetic characteristics, and other particular features unique to each patient, would allow a personalized approach to managing the disease. Personalized medicine therefore represents the tailoring of medical approach and treatment to the individual characteristics of each patient and is expected to become the paradigm of future healthcare. The advancement of systems biology research and the rapid development of high-throughput technologies, as well as the characterization of different –omics, have contributed to a shift in modern biological and medical research from traditional hypothesis-driven designs toward data-driven studies and have facilitated the evolution of personalized or precision medicine for chronic diseases such as hypertension

System Support For Energy Efficient Mobile Computing

Mobile devices are developed rapidly and they have been an integrated part of our daily life. With the blooming of Internet of Things, mobile computing will become more and more important. However, the battery drain problem is a critical issue that hurts user experience. High performance devices require more power support, while the battery capacity only increases 5% per year on average. Researchers are working on kinds of energy saving approaches. For examples, hardware components provide different power state to save idle power; operating systems provide power management APIs to better control power dissipation. However, the system energy efficiency is still low that cannot reach users’ expectation. To improve energy efficiency, we studied how to provide system support for mobile computing in four different aspects. First, we focused on the influence of user behavior on system energy consumption. We monitored and analyzed users’ application usages information. From the results, we built battery prediction model to estimate the battery time based on user behavior and hardware components’ usage. By adjusting user behavior, we can at most double the battery time. To understand why different applications can cause such huge energy difference, we built a power profiler Bugu to figure out where does the power go. Bugu analyzes power and event information for applications, it has high accuracy and low overhead. We analyzed almost 100 mobile applications’ power behavior and several implications are derived to save energy of applications and systems. In addition, to understand the energy behavior of modern hardware architectures, we analyzed the energy consumption and performance of heterogeneous platforms and compared them with homogeneous platforms. The results show that heterogeneous platforms indeed have great potential for energy saving which mostly comes from idle and low workload situations. However, a wrong scheduling decision may cause up to 30% more energy consumption. Scheduling becomes the key point for energy efficient computing. At last, as the increased power density leads to high device temperature, we investigated the thermal management system and developed an ambient temperature aware thermal control policy Falcon. It can save 4.85% total system power and more adaptive in various environments compared with the default approach. Finally, we discussed several potential directions for future research in this field