Optimal Sleep-Wake Policies for an Energy Harvesting Sensor Node

We study a sensor node with an energy harvesting source. In any slot,the sensor node is in one of two modes: Wake or Sleep. The generated energy is stored in a buffer. The sensor node senses a random field and generates a packet when it is awake. These packets are stored in a queue and transmitted in the wake mode using the energy available in the energy buffer. We obtain energy management policies which minimize a linear combination of the mean queue length and the mean data loss rate. Then, we obtain two easily implementable suboptimal policies and compare their performance to that of the optimal policy. Next, we extend the Throughput Optimal policy developed in our previous work to sensors with two modes. Via this policy, we can increase the through put substantially and stabilize the data queue by allowing the node to sleep in some slots and to drop some generated packets. This policy requires minimal statistical knowledge of the system. We also modify this policy to decrease the switching costs.

Rapid localization of damage using a circular sensor array and Lamb wave based triangulation

A damage detection and imaging methodology based on symmetry of neighborhood sensor path and similarity of signal patterns with respect to radial paths in a circular array of sensors has been developed It uses information regarding Limb wave propagation along with a triangulation scheme to rapidly locate and quantify the severity of damage without using all of the sensor data. In a plate like structure, such a scheme can be effectively employed besides full field imaging of wave scattering pattern from the damage, if present in the plate. This new scheme is validated experimentally. Hole and corrosion type damages have been detected and quantified using the proposed scheme successfully. A wavelet based cumulative damage index has been studied which shows monotonic sensitivity against the severity of the damage. which is most desired in a Structural Health Monitoring system. (C) 2010 Elsevier Ltd. All rights reserved.

Joint Power Control, Scheduling and Routing for Multihop Energy Harvesting Sensor Networks

We study wireless multihop energy harvesting sensor networks employed for random field estimation. The sensors sense the random field and generate data that is to be sent to a fusion node for estimation. Each sensor has an energy harvesting source and can operate in two modes: Wake and Sleep. We consider the problem of obtaining jointly optimal power control, routing and scheduling policies that ensure a fair utilization of network resources. This problem has a high computational complexity. Therefore, we develop a computationally efficient suboptimal approach to obtain good solutions to this problem. We study the optimal solution and performance of the suboptimal approach through some numerical examples.

Use of the Nasicon/Na2SO4 couple in a solid state sensor for SOx (x=2,3)

The e.m.f. of a concentration cell for SO x (x=2,3)-O2 incorporating Nasicon as the main solid electrolyte has been measured in the temperature range 720 to 1080 K. The cell arrangement can be represented as,$$Pt, O'_2 + SO'_2 + SO'_3 \left| {Na_2 SO_4 \left\| {\left. {Nasicon} \right\|} \right.} \right.\left. {Na_2 SO_4 } \right|SO''_3 + SO''_2 + O''_2 , Pt$$ The Na2SO4 acts both as an auxiliary electrode, converting chemical potentials of SO x and O2 to equivalent sodium potentials, and as an electrolyte. The presence of Na2SO4 provides partial protection of Nasicon from chemical reaction with gas mixtures containing SO x . The open circuit e.m.f. of the cell is in close agreement with values given by the Nernst equation. For certain fixed inlet gas compositions of SO2+O2, the e.m.f. varies non-linearly with temperature. The intrinsic response time of the cell to step changes in gas composition is estimated to vary from sim2.0 ksec at 723K to sim 0.2 ksec at 1077K. The cell functions well for large differences in partial pressures of SO3(pPrimeSO 3/pprimeSO 3ap104) at the electrodes.

An SOx (x = 2, 3) sensor using ?-alumina/Na2SO4 couple

A solid-state sensor for SOx (x = 2, 3) species has been designed using ?-alumina as the solid electrolyte and Na2SO4 as the auxiliary electrode. The measured e.m.f. of the cell Pt, O?2 + SO?2 + SO?3|Na2SO4short parallel?-aluminashort parallelNa2SO4|SO?3 + SO?2 + O?2, PT in the temperature range 700 K to 1150 K agrees well with values calculated using the Nernst equation. The sodium sulphate acts both as a protective covering, preventing direct access of the gaseous SOx species to the ?-alumina electrolyte, and as an auxiliary electrode, converting chemical potentials of SOx species and O2 into an equivalent sodium potential. The open-circuit e.m.f. varies non-linearly with temperature for fixed composition of inlet gas mixtures containing SO2, O2 and Ar. The response time (t0.99) of the cell varies between 1.9 ks at 750 K and 0.06 ks at 1100 K. The e.m.f. response is faster when the partial pressure of SOx at the electrode is increased than when it is decreased.

Classification of Protein Kinases on the Basis of Both Kinase and Non-Kinase Regions

Background: Protein phosphorylation is a generic way to regulate signal transduction pathways in all kingdoms of life. In many organisms, it is achieved by the large family of Ser/Thr/Tyr protein kinases which are traditionally classified into groups and subfamilies on the basis of the amino acid sequence of their catalytic domains. Many protein kinases are multidomain in nature but the diversity of the accessory domains and their organization are usually not taken into account while classifying kinases into groups or subfamilies. Methodology: Here, we present an approach which considers amino acid sequences of complete gene products, in order to suggest refinements in sets of pre-classified sequences. The strategy is based on alignment-free similarity scores and iterative Area Under the Curve (AUC) computation. Similarity scores are computed by detecting common patterns between two sequences and scoring them using a substitution matrix, with a consistent normalization scheme. This allows us to handle full-length sequences, and implicitly takes into account domain diversity and domain shuffling. We quantitatively validate our approach on a subset of 212 human protein kinases. We then employ it on the complete repertoire of human protein kinases and suggest few qualitative refinements in the subfamily assignment stored in the KinG database, which is based on catalytic domains only. Based on our new measure, we delineate 37 cases of potential hybrid kinases: sequences for which classical classification based entirely on catalytic domains is inconsistent with the full-length similarity scores computed here, which implicitly consider multi-domain nature and regions outside the catalytic kinase domain. We also provide some examples of hybrid kinases of the protozoan parasite Entamoeba histolytica. Conclusions: The implicit consideration of multi-domain architectures is a valuable inclusion to complement other classification schemes. The proposed algorithm may also be employed to classify other families of enzymes with multidomain architecture.

Microprocessor-based temperature indicator using platinum resistance as the sensor

A novel microprocessor-based platinum resistance temperature indicator has been developed and described. This indicator provides a linear performance over a wide dynamic temperature range of - 183.0°C to +200°C with an accuracy of better than ±0.05°C. To sasily carry out the linearization of platinum thermometer through software, the modified Callendar-Van Dusen equation is used. Test results are given to support the theory.

A wide‐range superconductor thermal sensor for low‐temperature measurement

This paper aims at describing a low‐temperature thermal sensor based on superconductor films which can be designed to have required variation of resistance with temperature through an appropriate geometry. Further, it has been shown that the temperature range can be varied to some extent by controlling the bias current.

A Low-Complexity Algorithm for Intrusion Detection in a PIR-Based Wireless Sensor Network

We present a low-complexity algorithm for intrusion detection in the presence of clutter arising from wind-blown vegetation, using Passive Infra-Red (PIR) sensors in a Wireless Sensor Network (WSN). The algorithm is based on a combination of Haar Transform (HT) and Support-Vector-Machine (SVM) based training and was field tested in a network setting comprising of 15-20 sensing nodes. Also contained in this paper is a closed-form expression for the signal generated by an intruder moving at a constant velocity. It is shown how this expression can be exploited to determine the direction of motion information and the velocity of the intruder from the signals of three well-positioned sensors.

Semi-Supervised Classification Using Sparse Gaussian Process Regression

Gaussian Processes (GPs) are promising Bayesian methods for classification and regression problems. They have also been used for semi-supervised learning tasks. In this paper, we propose a new algorithm for solving semi-supervised binary classification problem using sparse GP regression (GPR) models. It is closely related to semi-supervised learning based on support vector regression (SVR) and maximum margin clustering. The proposed algorithm is simple and easy to implement. It gives a sparse solution directly unlike the SVR based algorithm. Also, the hyperparameters are estimated easily without resorting to expensive cross-validation technique. Use of sparse GPR model helps in making the proposed algorithm scalable. Preliminary results on synthetic and real-world data sets demonstrate the efficacy of the new algorithm.

A New Liquid Level Sensor for Process-Control Applications

Many process-control systems are air-operated. In such an environment, it would be desirable and economical to use pneumatic sensors. Bubble-back pressure sensors perform quite satisfactorily, but in case of viscous inflammable and slurry-like liquids with a tendency to froth, this level sensor is inadequate. The method suggested in this paper utilizes a pneumatic capacitor, one boundary of which is formed by the liquid level, to modulate a fluid amplifier feedback oscillator. The absence of moving parts and economy obtained makes this method attractive for process-control applications. The system has been mathematically modeled and simulated on an IBM 360/44 digital computer. Experimental values compare fairly well with the theoretical results. For the range tested, the sensor is found to have a linear frequency variation with the liquid level Extended running in the laboratory shows that the system is very reliable. This system has been found insensitive to temperature variations of up to 15ðC.

Optimisation problems in wireless sensor networks

This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating–dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating–dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs – these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating–dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.

A new classification and linear sequence of extant gymnosperms

A new classification and linear sequence of the gymnosperms based on previous molecular and morphological phylogenetic and other studies is presented. Currently accepted genera are listed for each family and arranged according to their (probable) phylogenetic position. A full synonymy is provided, and types are listed for accepted genera. An index to genera assists in easy access to synonymy and family placement of genera.

Functional outcome and health-related quality of life after traumatic brain injury in the framework of the International Classification of Functioning, Disability and Health (ICF)

Traumatic brain injury (TBI) affects people of all ages and is a cause of long-term disability. In recent years, the epidemiological patterns of TBI have been changing. TBI is a heterogeneous disorder with different forms of presentation and highly individual outcome regarding functioning and health-related quality of life (HRQoL). The meaning of disability differs from person to person based on the individual s personality, value system, past experience, and the purpose he or she sees in life. Understanding of all these viewpoints is needed in comprehensive rehabilitation. This study examines the epidemiology of TBI in Finland as well as functioning and HRQoL after TBI, and compares the subjective and objective assessments of outcome. The frame of reference is the International Classification of Functioning, Disability and Health (ICF). The subjects of Study I represent the population of Finnish TBI patients who experienced their first TBI between 1991 and 2005. The 55 Finnish subjects of Studies II and IV participated in the first wave of the international Quality of life after brain injury (QOLIBRI) validation study. The 795 subjects from six language areas of Study III formed the second wave of the QOLIBRI validation study. The average annual incidence of Finnish hospitalised TBI patients during the years 1991-2005 was 101:100 000 in patients who had TBI as the primary diagnosis and did not have a previous TBI in their medical history. Males (59.2%) were at considerably higher risk of getting a TBI than females. The most common external cause of the injury was falls in all age groups. The number of TBI patients ≥ 70 years of age increased by 59.4% while the number of inhabitants older than 70 years increased by 30.3% in the population of Finland during the same time period. The functioning of a sample of 55 persons with TBI was assessed by extracting information from the patients medical documents using the ICF checklist. The most common problems were found in the ICF components of Body Functions (b) and Activities and Participation (d). HRQoL was assessed with the QOLIBRI which showed the highest level of satisfaction on the Emotions, Physical Problems and Daily Life and Autonomy scales. The highest scores were obtained by the youngest participants and participants living independently without the help of other people, and by people who were working. The relationship between the functional outcome and HRQoL was not straightforward. The procedure of linking the QOLIBRI and the GOSE to the ICF showed that these two outcome measures cover the relevant domains of TBI patients functioning. The QOLIBRI provides the patients subjective view, while the GOSE summarises the objective elements of functioning. Our study indicates that there are certain domains of functioning that are not traditionally sufficiently documented but are important for the HRQoL of persons with TBI. This was the finding especially in the domains of interpersonal relationships, social and leisure activities, self, and the environment. Rehabilitation aims to optimize functioning and to minimize the experience of disability among people with health conditions, and it needs to be based on a comprehensive understanding of human functioning. As an integrative model, the ICF may serve as a frame of reference in achieving such an understanding.