Design of high fidelity building energy monitoring system

Building energy meter network, based on per-appliance monitoring system, willbe an important part of the Advanced Metering Infrastructure. Two key issues exist for designing such networks. One is the network structure to be used. The other is the implementation of the network structure on a large amount of small low power devices, and the maintenance of high quality communication when the devices have electric connection with high voltage AC line. The recent advancement of low-power wireless communication makes itself the right candidate for house and building energy network. Among all kinds of wireless solutions, the low speed but highly reliable 802.15.4 radio has been chosen in this design. While many network-layer solutions have been provided on top of 802.15.4, an IPv6 based method is used in this design. 6LOWPAN is the particular protocol which adapts IP on low power personal network radio. In order to extend the network into building area without, a specific network layer routing mechanism-RPL, is included in this design. The fundamental unit of the building energy monitoring system is a smart wall plug. It is consisted of an electricity energy meter, a RF communication module and a low power CPU. The real challenge for designing such a device is its network firmware. In this design, IPv6 is implemented through Contiki operation system. Customize hardware driver and meter application program have been developed on top of the Contiki OS. Some experiments have been done, in order to prove the network ability of this system.

MODELING AND PROTOCOL DESIGN FOR EMERGING WIRELESS SYSTEMS

Mobile Mesh Network based In-Transit Visibility (MMN-ITV) system facilitates global real-time tracking capability for the logistics system. In-transit containers form a multi-hop mesh network to forward the tracking information to the nearby sinks, which further deliver the information to the remote control center via satellite. The fundamental challenge to the MMN-ITV system is the energy constraint of the battery-operated containers. Coupled with the unique mobility pattern, cross-MMN behavior, and the large-spanned area, it is necessary to investigate the energy-efficient communication of the MMN-ITV system thoroughly. First of all, this dissertation models the energy-efficient routing under the unique pattern of the cross-MMN behavior. A new modeling approach, pseudo-dynamic modeling approach, is proposed to measure the energy-efficiency of the routing methods in the presence of the cross-MMN behavior. With this approach, it could be identified that the shortest-path routing and the load-balanced routing is energy-efficient in mobile networks and static networks respectively. For the MMN-ITV system with both mobile and static MMNs, an energy-efficient routing method, energy-threshold routing, is proposed to achieve the best tradeoff between them. Secondly, due to the cross-MMN behavior, neighbor discovery is executed frequently to help the new containers join the MMN, hence, consumes similar amount of energy as that of the data communication. By exploiting the unique pattern of the cross-MMN behavior, this dissertation proposes energy-efficient neighbor discovery wakeup schedules to save up to 60% of the energy for neighbor discovery. Vehicular Ad Hoc Networks (VANETs)-based inter-vehicle communications is by now growingly believed to enhance traffic safety and transportation management with low cost. The end-to-end delay is critical for the time-sensitive safety applications in VANETs, and can be a decisive performance metric for VANETs. This dissertation presents a complete analytical model to evaluate the end-to-end delay against the transmission range and the packet arrival rate. This model illustrates a significant end-to-end delay increase from non-saturated networks to saturated networks. It hence suggests that the distributed power control and admission control protocols for VANETs should aim at improving the real-time capacity (the maximum packet generation rate without causing saturation), instead of the delay itself. Based on the above model, it could be determined that adopting uniform transmission range for every vehicle may hinder the delay performance improvement, since it does not allow the coexistence of the short path length and the low interference. Clusters are proposed to configure non-uniform transmission range for the vehicles. Analysis and simulation confirm that such configuration can enhance the real-time capacity. In addition, it provides an improved trade off between the end-to-end delay and the network capacity. A distributed clustering protocol with minimum message overhead is proposed, which achieves low convergence time.

USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS

Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been conducted to solve the problems underlying the middleware services of sensor networks, such as self-deployment, self-localization, and synchronization. With the provided middleware services, sensor networks have grown into a mature technology to be used as a detection and surveillance paradigm for many real-world applications. The individual sensors are small in size. Thus, they can be deployed in areas with limited space to make unobstructed measurements in locations where the traditional centralized systems would have trouble to reach. However, there are a few physical limitations to sensor networks, which can prevent sensors from performing at their maximum potential. Individual sensors have limited power supply, the wireless band can get very cluttered when multiple sensors try to transmit at the same time. Furthermore, the individual sensors have limited communication range, so the network may not have a 1-hop communication topology and routing can be a problem in many cases. Carefully designed algorithms can alleviate the physical limitations of sensor networks, and allow them to be utilized to their full potential. Graphical models are an intuitive choice for designing sensor network algorithms. This thesis focuses on a classic application in sensor networks, detecting and tracking of targets. It develops feasible inference techniques for sensor networks using statistical graphical model inference, binary sensor detection, events isolation and dynamic clustering. The main strategy is to use only binary data for rough global inferences, and then dynamically form small scale clusters around the target for detailed computations. This framework is then extended to network topology manipulation, so that the framework developed can be applied to tracking in different network topology settings. Finally the system was tested in both simulation and real-world environments. The simulations were performed on various network topologies, from regularly distributed networks to randomly distributed networks. The results show that the algorithm performs well in randomly distributed networks, and hence requires minimum deployment effort. The experiments were carried out in both corridor and open space settings. A in-home falling detection system was simulated with real-world settings, it was setup with 30 bumblebee radars and 30 ultrasonic sensors driven by TI EZ430-RF2500 boards scanning a typical 800 sqft apartment. Bumblebee radars are calibrated to detect the falling of human body, and the two-tier tracking algorithm is used on the ultrasonic sensors to track the location of the elderly people.

PROOF OF CONCEPT PROTOTYPE FOR A RAILROAD PEDESTRIAN WARNING SYSTEM USING WIRELESS SENSOR NETWORKS

Wireless sensor network is an emerging research topic due to its vast and ever-growing applications. Wireless sensor networks are made up of small nodes whose main goal is to monitor, compute and transmit data. The nodes are basically made up of low powered microcontrollers, wireless transceiver chips, sensors to monitor their environment and a power source. The applications of wireless sensor networks range from basic household applications, such as health monitoring, appliance control and security to military application, such as intruder detection. The wide spread application of wireless sensor networks has brought to light many research issues such as battery efficiency, unreliable routing protocols due to node failures, localization issues and security vulnerabilities. This report will describe the hardware development of a fault tolerant routing protocol for railroad pedestrian warning system. The protocol implemented is a peer to peer multi-hop TDMA based protocol for nodes arranged in a linear zigzag chain arrangement. The basic working of the protocol was derived from Wireless Architecture for Hard Real-Time Embedded Networks (WAHREN).

Bothnia dystrophy is caused by domino-like rearrangements in cellular retinaldehyde-binding protein mutant R234W

Cellular retinaldehyde-binding protein (CRALBP) is essential for mammalian vision by routing 11-cis-retinoids for the conversion of photobleached opsin molecules into photosensitive visual pigments. The arginine-to-tryptophan missense mutation in position 234 (R234W) in the human gene RLBP1 encoding CRALBP compromises visual pigment regeneration and is associated with Bothnia dystrophy. Here we report the crystal structures of both wild-type human CRALBP and of its mutant R234W as binary complexes complemented with the endogenous ligand 11-cis-retinal, at 3.0 and 1.7 A resolution, respectively. Our structural model of wild-type CRALBP locates R234 to a positively charged cleft at a distance of 15 A from the hydrophobic core sequestering 11-cis-retinal. The R234W structural model reveals burial of W234 and loss of dianion-binding interactions within the cleft with physiological implications for membrane docking. The burial of W234 is accompanied by a cascade of side-chain flips that effect the intrusion of the side-chain of I238 into the ligand-binding cavity. As consequence of the intrusion, R234W displays 5-fold increased resistance to light-induced photoisomerization relative to wild-type CRALBP, indicating tighter binding to 11-cis-retinal. Overall, our results reveal an unanticipated domino-like structural transition causing Bothnia-type retinal dystrophy by the impaired release of 11-cis-retinal from R234W.

Query Technologies and Applications for Program Comprehension

Industrial software systems are large and complex, both in terms of the software entities and their relationships. Consequently, understanding how a software system works requires the ability to pose queries over the design-level entities of the system. Traditionally, this task has been supported by simple tools (e.g., grep) combined with the programmer's intuition and experience. Recently, however, specialized code query technologies have matured to the point where they can be used in industrial situations, providing more intelligent, timely, and efficient responses to developer queries. This working session aims to explore the state of the art in code query technologies, and discover new ways in which these technologies may be useful in program comprehension. The session brings together researchers and practitioners. We survey existing techniques and applications, trying to understand the strengths and weaknesses of the various approaches, and sketch out new frontiers that hold promise.

Querying Runtime Information in the IDE

Code queries focus mainly on the static structure of a system. To comprehend the dynamic behavior of a system however, a software engineer needs to be able to reason about the dynamics of this system, for instance by querying a database of dynamic information. Such a querying mechanism should be directly available in the IDE where the developers implements, navigates and reasons about the software system. We propose (i) concepts to gather dynamic information, (ii) the means to query this information, and (iii) tools and techniques to integrate querying of dynamic information in the IDE, including the presentation of results generated by queries.

Lower Benefits to the Refugees in Denmark: Missing Recognition?

This article is a study of the contrast between the Danish law concerning reduced economic benefits for newly arrived refugees and immigrants (known as Start Help or as introductory benefit) and the idea of recognition as the condition for individual self-realization and justice. Our assumption is that Start Help both implies economic discrimination against newly arrived persons in Denmark (especially refugees and their families under family reunification rules) and symbolizes a lack of recognition. We have chosen to adopt the theories of recognition (and redistribution) propounded by Axel Honneth and Nancy Fraser to explore our queries about Start Help and the discriminatory impact on its recipients. Empirically the article is based on in-depth qualitative interviews with six refugees who all receive Start Help.

QoE-aware Multiple Path Video Transmission for Wireless Multimedia Sensor Networks

Wireless Multimedia Sensor Networks (WMSNs) promise a wide scope of emerging potential applications in both civilian and military areas, which require visual and audio information to enhance the level of collected information. The transmission of multimedia content requires a minimal video quality level from the user’s perspective. However, links in WMSN communi- cations are typically unreliable, as they often experience fluctuations in quality and weak connectivity, and thus, the routing protocol must evaluate the routes by using end-to-end link quality information to increase the packet delivery ratio. Moreover, the use multiple paths together with key video metrics can enhance the video quality level. In this paper, we propose a video-aware multiple path hierarchical routing protocol for efficient multimedia transmission over WMSN, called video-aware MMtransmission. This protocol finds node-disjoint multiple paths, and implements an end-to-end link quality estimation with minimal over- head to score the paths. Thus, our protocol assures multimedia transmission with Quality of Experience (QoE) and energy-efficiency support. The simula- tion results show the benefits of video-aware MMtransmission for disseminating video content by means of energy-efficiency and QoE analysis.

Service-centric Networking Extensions

This paper discusses several issues of Service-Centric Networking (SCN) as an extension of the Information-Centric Networking (ICN) paradigm. SCN allows extended caching, where not exactly the same content as requested can be read from caches, but similar content can be used to produce the content requested, e.g., by filtering or transcoding. We discuss the issue of naming and routing for general dynamic services for both tightly coupled and decoupled ICN approaches. Challenges and solutions for service management are identified, in particular for composed services, which allow distributed in-network processing of service requests. We introduce the term Software-Defined Service-Centric Networking as an extension of Software-Defined Networking. A prototype implementation for SCN proofs its validity and feasibility and underlines its potential benefits.

Fuzzy Online Reputation Analysis Framework

The fuzzy online reputation analysis framework, or “foRa” (plural of forum, the Latin word for marketplace) framework, is a method for searching the Social Web to find meaningful information about reputation. Based on an automatic, fuzzy-built ontology, this framework queries the social marketplaces of the Web for reputation, combines the retrieved results, and generates navigable Topic Maps. Using these interactive maps, communications operatives can zero in on precisely what they are looking for and discover unforeseen relationships between topics and tags. Thus, using this framework, it is possible to scan the Social Web for a name, product, brand, or combination thereof and determine query-related topic classes with related terms and thus identify hidden sources. This chapter also briefly describes the youReputation prototype (www.youreputation.org), a free web-based application for reputation analysis. In the course of this, a small example will explain the benefits of the prototype.

Prometheus Framework for Fuzzy Information Retrieval in Semantic Spaces

This paper introduces a novel vision for further enhanced Internet of Things services. Based on a variety of data (such as location data, ontology-backed search queries, in- and outdoor conditions) the Prometheus framework is intended to support users with helpful recommendations and information preceding a search for context-aware data. Adapted from artificial intelligence concepts, Prometheus proposes user-readjusted answers on umpteen conditions. A number of potential Prometheus framework applications are illustrated. Added value and possible future studies are discussed in the conclusion.

Prometheus – Fuzzy Information Retrieval for Semantic Homes and Environments

This paper introduces a novel vision for further enhanced Internet of Things services. Based on a variety of data – such as location data, ontology-backed search queries, in- and outdoor conditions – the Prometheus framework is intended to support users with helpful recommendations and information preceding a search for context-aware data. Adapted from artificial intelligence concepts, Prometheus proposes user-readjusted answers on umpteen conditions. A number of potential Prometheus framework applications are illustrated. Added value and possible future studies are discussed in the conclusion.

Evaluating the disparity of female breast cancer mortality among racial groups - a spatiotemporal analysis

Background The literature suggests that the distribution of female breast cancer mortality demonstrates spatial concentration. There remains a lack of studies on how the mortality burden may impact racial groups across space and over time. The present study evaluated the geographic variations in breast cancer mortality in Texas females according to three predominant racial groups (non-Hispanic White, Black, and Hispanic females) over a twelve-year period. It sought to clarify whether the spatiotemporal trend might place an uneven burden on particular racial groups, and whether the excess trend has persisted into the current decade. Methods The Spatial Scan Statistic was employed to examine the geographic excess of breast cancer mortality by race in Texas counties between 1990 and 2001. The statistic was conducted with a scan window of a maximum of 90% of the study period and a spatial cluster size of 50% of the population at risk. The next scan was conducted with a purely spatial option to verify whether the excess mortality persisted further. Spatial queries were performed to locate the regions of excess mortality affecting multiple racial groups. Results The first scan identified 4 regions with breast cancer mortality excess in both non-Hispanic White and Hispanic female populations. The most likely excess mortality with a relative risk of 1.12 (p = 0.001) occurred between 1990 and 1996 for non-Hispanic Whites, including 42 Texas counties along Gulf Coast and Central Texas. For Hispanics, West Texas with a relative risk of 1.18 was the most probable region of excess mortality (p = 0.001). Results of the second scan were identical to the first. This suggested that the excess mortality might not persist to the present decade. Spatial queries found that 3 counties in Southeast and 9 counties in Central Texas had excess mortality involving multiple racial groups. Conclusion Spatiotemporal variations in breast cancer mortality affected racial groups at varying levels. There was neither evidence of hot-spot clusters nor persistent spatiotemporal trends of excess mortality into the present decade. Non-Hispanic Whites in the Gulf Coast and Hispanics in West Texas carried the highest burden of mortality, as evidenced by spatial concentration and temporal persistence.

A day in the life of PubMed: analysis of a typical day's query log.

OBJECTIVE: To characterize PubMed usage over a typical day and compare it to previous studies of user behavior on Web search engines. DESIGN: We performed a lexical and semantic analysis of 2,689,166 queries issued on PubMed over 24 consecutive hours on a typical day. MEASUREMENTS: We measured the number of queries, number of distinct users, queries per user, terms per query, common terms, Boolean operator use, common phrases, result set size, MeSH categories, used semantic measurements to group queries into sessions, and studied the addition and removal of terms from consecutive queries to gauge search strategies. RESULTS: The size of the result sets from a sample of queries showed a bimodal distribution, with peaks at approximately 3 and 100 results, suggesting that a large group of queries was tightly focused and another was broad. Like Web search engine sessions, most PubMed sessions consisted of a single query. However, PubMed queries contained more terms. CONCLUSION: PubMed's usage profile should be considered when educating users, building user interfaces, and developing future biomedical information retrieval systems.