UAVNet: A Mobile Wireless Mesh Network Using Unmanned Aerial Vehicles

We developed UAVNet, a framework for the autonomous deployment of a flying Wireless Mesh Network using small quadrocopter-based Unmanned Aerial Vehicles (UAVs). The flying wireless mesh nodes are automatically interconnected to each other and building an IEEE 802.11s wireless mesh network. The implemented UAVNet prototype is able to autonomously interconnect two end systems by setting up an airborne relay, consisting of one or several flying wireless mesh nodes. The developed software includes basic functionality to control the UAVs and to setup, deploy, manage, and monitor a wireless mesh network. Our evaluations have shown that UAVNet can significantly improve network performance.

Outcomes and patterns of failure in solitary plasmacytoma: a multicenter Rare Cancer Network study of 258 patients

PURPOSE: To assess the outcomes and patterns of failure in solitary plasmacytoma (SP). METHODS AND MATERIALS: The data from 258 patients with bone (n = 206) or extramedullary (n = 52) SP without evidence of multiple myeloma (MM) were collected. A histopathologic diagnosis was obtained for all patients. Most (n = 214) of the patients received radiotherapy (RT) alone; 34 received chemotherapy and RT, and 8 surgery alone. The median radiation dose was 40 Gy. The median follow-up was 56 months (range 7-245). RESULTS: The median time to MM development was 21 months (range 2-135), with a 5-year probability of 45%. The 5-year overall survival, disease-free survival, and local control rate was 74%, 50%, and 86%, respectively. On multivariate analyses, the favorable factors were younger age and tumor size <4 cm for survival; younger age, extramedullary localization, and RT for disease-free survival; and small tumor and RT for local control. Bone localization was the only predictor of MM development. No dose-response relationship was found for doses >30 Gy, even for larger tumors. CONCLUSION: Progression to MM remains the main problem. Patients with extramedullary SP had the best outcomes, especially when treated with moderate-dose RT. Chemotherapy and/or novel therapies should be investigated for bone or bulky extramedullary SP.

INTERACTING WITH LOCAL AND REMOTE DATA RESPOSITORIES USING THE stashR PACKAGE

The stashR package (a Set of Tools for Administering SHared Repositories) for R implements a simple key-value style database where character string keys are associated with data values. The key-value databases can be either stored locally on the user's computer or accessed remotely via the Internet. Methods specific to the stashR package allow users to share data repositories or access previously created remote data repositories. In particular, methods are available for the S4 classes localDB and remoteDB to insert, retrieve, or delete data from the database as well as to synchronize local copies of the data to the remote version of the database. Users efficiently access information from a remote database by retrieving only the data files indexed by user-specified keys and caching this data in a local copy of the remote database. The local and remote counterparts of the stashR package offer the potential to enhance reproducible research by allowing users of Sweave to cache their R computations for a research paper in a localDB database. This database can then be stored on the Internet as a remoteDB database. When readers of the research paper wish to reproduce the computations involved in creating a specific figure or calculating a specific numeric value, they can access the remoteDB database and obtain the R objects involved in the computation.

Body sensor network for in-home personal healthcare

A body sensor network solution for personal healthcare under an indoor environment is developed. The system is capable of logging the physiological signals of human beings, tracking the orientations of human body, and monitoring the environmental attributes, which covers all necessary information for the personal healthcare in an indoor environment. The major three chapters of this dissertation contain three subsystems in this work, each corresponding to one subsystem: BioLogger, PAMS and CosNet. Each chapter covers the background and motivation of the subsystem, the related theory, the hardware/software design, and the evaluation of the prototype’s performance.

Tracking a non-cooperative target using a Doppler radar wireless sensor network

Tracking or target localization is used in a wide range of important tasks from knowing when your flight will arrive to ensuring your mail is received on time. Tracking provides the location of resources enabling solutions to complex logistical problems. Wireless Sensor Networks (WSN) create new opportunities when applied to tracking, such as more flexible deployment and real-time information. When radar is used as the sensing element in a tracking WSN better results can be obtained; because radar has a comparatively larger range both in distance and angle to other sensors commonly used in WSNs. This allows for less nodes deployed covering larger areas, saving money. In this report I implement a tracking WSN platform similar to what was developed by Lim, Wang, and Terzis. This consists of several sensor nodes each with a radar, a sink node connected to a host PC, and a Matlab© program to fuse sensor data. I have re-implemented their experiment with my WSN platform for tracking a non-cooperative target to verify their results and also run simulations to compare. The results of these tests are discussed and some future improvements are proposed.

Automated design of self-stabilization

Self-stabilization is a property of a distributed system such that, regardless of the legitimacy of its current state, the system behavior shall eventually reach a legitimate state and shall remain legitimate thereafter. The elegance of self-stabilization stems from the fact that it distinguishes distributed systems by a strong fault tolerance property against arbitrary state perturbations. The difficulty of designing and reasoning about self-stabilization has been witnessed by many researchers; most of the existing techniques for the verification and design of self-stabilization are either brute-force, or adopt manual approaches non-amenable to automation. In this dissertation, we first investigate the possibility of automatically designing self-stabilization through global state space exploration. In particular, we develop a set of heuristics for automating the addition of recovery actions to distributed protocols on various network topologies. Our heuristics equally exploit the computational power of a single workstation and the available parallelism on computer clusters. We obtain existing and new stabilizing solutions for classical protocols like maximal matching, ring coloring, mutual exclusion, leader election and agreement. Second, we consider a foundation for local reasoning about self-stabilization; i.e., study the global behavior of the distributed system by exploring the state space of just one of its components. It turns out that local reasoning about deadlocks and livelocks is possible for an interesting class of protocols whose proof of stabilization is otherwise complex. In particular, we provide necessary and sufficient conditions – verifiable in the local state space of every process – for global deadlock- and livelock-freedom of protocols on ring topologies. Local reasoning potentially circumvents two fundamental problems that complicate the automated design and verification of distributed protocols: (1) state explosion and (2) partial state information. Moreover, local proofs of convergence are independent of the number of processes in the network, thereby enabling our assertions about deadlocks and livelocks to apply on rings of arbitrary sizes without worrying about state explosion.

Systemic analysis of microarray data sets towards identifying genes regulating root development

Nitrogen and water are essential for plant growth and development. In this study, we designed experiments to produce gene expression data of poplar roots under nitrogen starvation and water deprivation conditions. We found low concentration of nitrogen led first to increased root elongation followed by lateral root proliferation and eventually increased root biomass. To identify genes regulating root growth and development under nitrogen starvation and water deprivation, we designed a series of data analysis procedures, through which, we have successfully identified biologically important genes. Differentially Expressed Genes (DEGs) analysis identified the genes that are differentially expressed under nitrogen starvation or drought. Protein domain enrichment analysis identified enriched themes (in same domains) that are highly interactive during the treatment. Gene Ontology (GO) enrichment analysis allowed us to identify biological process changed during nitrogen starvation. Based on the above analyses, we examined the local Gene Regulatory Network (GRN) and identified a number of transcription factors. After testing, one of them is a high hierarchically ranked transcription factor that affects root growth under nitrogen starvation. It is very tedious and time-consuming to analyze gene expression data. To avoid doing analysis manually, we attempt to automate a computational pipeline that now can be used for identification of DEGs and protein domain analysis in a single run. It is implemented in scripts of Perl and R.

Optimal game theoretic distributed control methodologies in small scale power systems

This dissertation presents the competitive control methodologies for small-scale power system (SSPS). A SSPS is a collection of sources and loads that shares a common network which can be isolated during terrestrial disturbances. Micro-grids, naval ship electric power systems (NSEPS), aircraft power systems and telecommunication system power systems are typical examples of SSPS. The analysis and development of control systems for small-scale power systems (SSPS) lacks a defined slack bus. In addition, a change of a load or source will influence the real time system parameters of the system. Therefore, the control system should provide the required flexibility, to ensure operation as a single aggregated system. In most of the cases of a SSPS the sources and loads must be equipped with power electronic interfaces which can be modeled as a dynamic controllable quantity. The mathematical formulation of the micro-grid is carried out with the help of game theory, optimal control and fundamental theory of electrical power systems. Then the micro-grid can be viewed as a dynamical multi-objective optimization problem with nonlinear objectives and variables. Basically detailed analysis was done with optimal solutions with regards to start up transient modeling, bus selection modeling and level of communication within the micro-grids. In each approach a detail mathematical model is formed to observe the system response. The differential game theoretic approach was also used for modeling and optimization of startup transients. The startup transient controller was implemented with open loop, PI and feedback control methodologies. Then the hardware implementation was carried out to validate the theoretical results. The proposed game theoretic controller shows higher performances over traditional the PI controller during startup. In addition, the optimal transient surface is necessary while implementing the feedback controller for startup transient. Further, the experimental results are in agreement with the theoretical simulation. The bus selection and team communication was modeled with discrete and continuous game theory models. Although players have multiple choices, this controller is capable of choosing the optimum bus. Next the team communication structures are able to optimize the players’ Nash equilibrium point. All mathematical models are based on the local information of the load or source. As a result, these models are the keys to developing accurate distributed controllers.

DISTRIBUTED APPROACH FOR SOLVING OPTIMAL POWER FLOW PROBLEMS IN THREE-PHASE UNBALANCED DISTRIBUTION NETWORK

The objective of this report is to study distributed (decentralized) three phase optimal power flow (OPF) problem in unbalanced power distribution networks. A full three phase representation of the distribution networks is considered to account for the highly unbalance state of the distribution networks. All distribution network’s series/shunt components, and load types/combinations had been modeled on commercial version of General Algebraic Modeling System (GAMS), the high-level modeling system for mathematical programming and optimization. The OPF problem has been successfully implemented and solved in a centralized approach and distributed approach, where the objective is to minimize the active power losses in the entire system. The study was implemented on the IEEE-37 Node Test Feeder. A detailed discussion of all problem sides and aspects starting from the basics has been provided in this study. Full simulation results have been provided at the end of the report.

LOCAL DIGITAL CONTROL OF POWER ELECTRONIC CONVERTERS IN A DC MICROGRID BASED ON A-PRIORI DERIVATION OF SWITCHING SURFACES

In power electronic basedmicrogrids, the computational requirements needed to implement an optimized online control strategy can be prohibitive. The work presented in this dissertation proposes a generalized method of derivation of geometric manifolds in a dc microgrid that is based on the a-priori computation of the optimal reactions and trajectories for classes of events in a dc microgrid. The proposed states are the stored energies in all the energy storage elements of the dc microgrid and power flowing into them. It is anticipated that calculating a large enough set of dissimilar transient scenarios will also span many scenarios not specifically used to develop the surface. These geometric manifolds will then be used as reference surfaces in any type of controller, such as a sliding mode hysteretic controller. The presence of switched power converters in microgrids involve different control actions for different system events. The control of the switch states of the converters is essential for steady state and transient operations. A digital memory look-up based controller that uses a hysteretic sliding mode control strategy is an effective technique to generate the proper switch states for the converters. An example dcmicrogrid with three dc-dc boost converters and resistive loads is considered for this work. The geometric manifolds are successfully generated for transient events, such as step changes in the loads and the sources. The surfaces corresponding to a specific case of step change in the loads are then used as reference surfaces in an EEPROM for experimentally validating the control strategy. The required switch states corresponding to this specific transient scenario are programmed in the EEPROM as a memory table. This controls the switching of the dc-dc boost converters and drives the system states to the reference manifold. In this work, it is shown that this strategy effectively controls the system for a transient condition such as step changes in the loads for the example case.

Local Resources for Learning/Teaching CS for Pre-College Students/Teachers

Presentation by Dr. Frank Ackerman. Additional information can be found on Montana Tech's Department of Computer Sciences website.

Cellular and network mechanisms of rhythm generation in spinal cord circuits

The generation of rhythmic electrical activity is a prominent feature of spinal cord circuits that is used for locomotion and also for circuit refinement during development. The mechanisms involved in rhythm generation in spinal cord networks are not fully understood. It is for example not known whether spinal cord rhythms are driven by pacemaker neurons and if yes, which neurons are involved in this function. We studied the mechanisms involved in rhythm generation in slice cultures from fetal rats that were grown on multielectrode arrays (MEAs). We combined multisite extracellular recordings from the MEA electrodes with intracellular patch clamp recordings from single neurons. We found that spatially restricted oscillations of activity appeared in most of the cultures spontaneously. Such activity was based on intrinsic activity in a percentage of the neurons that could activate the spinal networks through recurrent excitation. The local oscillator networks critically involved NMDA, AMPA and GABA / glycine receptors at subsequent phases of the oscillation cycle. Intrinsic spiking in individual neurons (in the absence of functional synaptic coupling) was based on persistent sodium currents. Intrinsic firing as well as persistent sodium currents were increased by 5-HT through 5-HT2 receptors. Comparing neuronal activity to muscle activity in co-cultures of spinal cord slices with muscle fibers we found that a percentage of the intrinsically spiking neurons were motoneurons. These motoneurons were electrically coupled among each other and they could drive the spinal networks through cholinergic recurrent excitation. These findings open the possibility that during development rhythmic activity in motoneurons is not only involved in circuit refinement downstream at the neuromuscular endplates but also upstream at the level of spinal cord circuits.

The results of surgery, with or without radiotherapy, for primary spinal myxopapillary ependymoma: a retrospective study from the rare cancer network

PURPOSE: The aim of this study was to assess the outcome of patients with primary spinal myxopapillary ependymoma (MPE). MATERIALS AND METHODS: Data from a series of 85 (35 females, 50 males) patients with spinal MPE were collected in this retrospective multicenter study. Thirty-eight (45%) underwent surgery only and 47 (55%) received postoperative radiotherapy (RT). Median administered radiation dose was 50.4 Gy (range, 22.2-59.4). Median follow-up of the surviving patients was 60.0 months (range, 0.2-316.6). RESULTS: The 5-year progression-free survival (PFS) was 50.4% and 74.8% for surgery only and surgery with postoperative low- (<50.4 Gy) or high-dose (>or=50.4 Gy) RT, respectively. Treatment failure was observed in 24 (28%) patients. Fifteen patients presented treatment failure at the primary site only, whereas 2 and 1 patients presented with brain and distant spinal failure only. Three and 2 patients with local failure presented with concomitant spinal distant seeding and brain failure, respectively. One patient failed simultaneously in the brain and spine. Age greater than 36 years (p = 0.01), absence of neurologic symptoms at diagnosis (p = 0.01), tumor size >or=25 mm (p = 0.04), and postoperative high-dose RT (p = 0.05) were variables predictive of improved PFS on univariate analysis. In multivariate analysis, only postoperative high-dose RT was independent predictors of PFS (p = 0.04). CONCLUSIONS: The observed pattern of failure was mainly local, but one fifth of the patients presented with a concomitant spinal or brain component. Postoperative high-dose RT appears to significantly reduce the rate of tumor progression.