817 resultados para Vector sensor


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In wireless sensor networks, the routing algorithms currently available assume that the sensor nodes are stationary. Therefore when mobility modulation is applied to the wireless sensor networks, most of the current routing algorithms suffer from performance degradation. The path breaks in mobile wireless networks are due to the movement of mobile nodes, node failure, channel fading and shadowing. It is desirable to deal with dynamic topology changes with optimal effort in terms of resource and channel utilization. As the nodes in wireless sensor medium make use of wireless broadcast to communicate, it is possible to make use of neighboring node information to recover from path failure. Cooperation among the neighboring nodes plays an important role in the context of routing among the mobile nodes. This paper proposes an enhancement to an existing protocol for accommodating node mobility through neighboring node information while keeping the utilization of resources to a minimum.

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One of the major applications of underwater acoustic sensor networks (UWASN) is ocean environment monitoring. Employing data mules is an energy efficient way of data collection from the underwater sensor nodes in such a network. A data mule node such as an autonomous underwater vehicle (AUV) periodically visits the stationary nodes to download data. By conserving the power required for data transmission over long distances to a remote data sink, this approach extends the network life time. In this paper we propose a new MAC protocol to support a single mobile data mule node to collect the data sensed by the sensor nodes in periodic runs through the network. In this approach, the nodes need to perform only short distance, single hop transmission to the data mule. The protocol design discussed in this paper is motivated to support such an application. The proposed protocol is a hybrid protocol, which employs a combination of schedule based access among the stationary nodes along with handshake based access to support mobile data mules. The new protocol, RMAC-M is developed as an extension to the energy efficient MAC protocol R-MAC by extending the slot time of R-MAC to include a contention part for a hand shake based data transfer. The mobile node makes use of a beacon to signal its presence to all the nearby nodes, which can then hand-shake with the mobile node for data transfer. Simulation results show that the new protocol provides efficient support for a mobile data mule node while preserving the advantages of R-MAC such as energy efficiency and fairness.

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Sensor networks are one of the fastest growing areas in broad of a packet is in transit at any one time. In GBR, each node in the network can look at itsneighbors wireless ad hoc networking (? Eld. A sensor node, typically'hop count (depth) and use this to decide which node to forward contains signal-processing circuits, micro-controllers and a the packet on to. If the nodes' power level drops below a wireless transmitter/receiver antenna. Energy saving is one certain level it will increase the depth to discourage trafiE of the critical issue forfor sensor networks since most sensors are equipped with non-rechargeable batteries that have limited lifetime.

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Page 1. The World of Sensor Networks G Santhosh Kumar, CUSAT Kumar, CUSAT Page 2. Are you as quick as Messi or Bale? WSN adidas innovation (source: http://www.wsnblog. com/) Page 3. Fukushima nuclear disaster • Fukushima Rescue Workers Facing Depression and Death • How to measure the levels of radiation of the affected zones without compromising the life of the workers? • Radiation measurements in real-time Page 4. Fukushima nuclear disaster Page 5. Fukushima nuclear disaster Page 6. Goals .

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Clustering combined with multihop communication is a promising solution to cope with the energy requirements of large scale Wireless Sensor Networks. In this work, a new cluster based routing protocol referred to as Energy Aware Cluster-based Multihop (EACM) Routing Protocol is introduced, with multihop communication between cluster heads for transmitting messages to the base station and direct communication within clusters. We propose EACM with both static and dynamic clustering. The network is partitioned into near optimal load balanced clusters by using a voting technique, which ensures that the suitability of a node to become a cluster head is determined by all its neighbors. Results show that the new protocol performs better than LEACH on network lifetime and energy dissipation

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In wireless sensor networks, the routing algorithms currently available assume that the sensor nodes are stationary. Therefore when mobility modulation is applied to the wireless sensor networks, most of the current routing algorithms suffer from performance degradation. The path breaks in mobile wireless networks are due to the movement of mobile nodes, node failure, channel fading and shadowing. It is desirable to deal with dynamic topology changes with optimal effort in terms of resource and channel utilization. As the nodes in wireless sensor medium make use of wireless broadcast to communicate, it is possible to make use of neighboring node information to recover from path failure. Cooperation among the neighboring nodes plays an important role in the context of routing among the mobile nodes. This paper proposes an enhancement to an existing protocol for accommodating node mobility through neighboring node information while keeping the utilization of resources to a minimum.

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Wireless sensor networks monitor their surrounding environment for the occurrence of some anticipated phenomenon. Most of the research related to sensor networks considers the static deployment of sensor nodes. Mobility of sensor node can be considered as an extra dimension of complexity, which poses interesting and challenging problems. Node mobility is a very important aspect in the design of effective routing algorithm for mobile wireless networks. In this work we intent to present the impact of different mobility models on the performance of the wireless sensor networks. Routing characteristics of various routing protocols for ad-hoc network were studied considering different mobility models. Performance metrics such as end-to-end delay, throughput and routing load were considered and their variations in the case of mobility models like Freeway, RPGM were studied. This work will be useful to figure out the characteristics of routing protocols depending on the mobility patterns of sensors

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Sensor networks are one of the fastest growing areas in broadwireless ad hoc networking (?Eld. A sensor node, typically'contains signal-processing circuits, micro-controllers and awireless transmitter/receiver antenna. Energy saving is oneof the critical issue for sensor networks since most sensorsare equipped with non-rechargeable batteries that have limited lifetime.In thiswork, four routing protocols for wireless sensor networks vizFlooding, Gossiping, GBR and LEACH have been simulated using Tiny OS and their power consumption is studied usingcaorwreiredTOoSuStIuMs.ingAMirceaal2izMaotitoens.of these protocols has been carried out using mica 2 motes

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This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is based on Haar wavelet transform and a classification stage that uses support vector machine classifier. Experimental results show that the proposed method is effective

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In our study we use a kernel based classification technique, Support Vector Machine Regression for predicting the Melting Point of Drug – like compounds in terms of Topological Descriptors, Topological Charge Indices, Connectivity Indices and 2D Auto Correlations. The Machine Learning model was designed, trained and tested using a dataset of 100 compounds and it was found that an SVMReg model with RBF Kernel could predict the Melting Point with a mean absolute error 15.5854 and Root Mean Squared Error 19.7576

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A differential pulse voltammetric sensor for the determination of tamsulosin hydrochloride (TAM) using multiwalled carbon nanotubes (MWNTs)–Nafion-modified glassy carbon electrode (GCE) has been developed. MWNTs were dispersed in water with the help of Nafion and were used to modify the surface of GCE via solvent evaporation. At MWNT-modified electrode, TAM gave a well-defined oxidation peak at a potential of 1084 mV in 0.1 M acetate buffer solution of pH 5. Compared to the bare electrode, the peak current of TAM showed a marked increase and the peak potential showed a negative deviation. The determination conditions, such as the amount of MWNT–Nafion suspension, pH of the supporting electrolyte and scan rate, were optimised. Under optimum conditions, the oxidation peak current was proportional to the concentration of TAM in the range 1 × 1023 M–3 × 1027 M with a detection limit of 9.8 × 1028 M. The developed sensor showed good stability, selectivity and was successfully used for the determination of TAM in pharmaceutical formulations and urine samples

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At present, a fraction of 0.1 - 0.2% of the patients undergoing surgery become aware during the process. The situation is referred to as anesthesia awareness and is obviously very traumatic for the person experiencing it. The reason for its occurrence is mostly an insufficient dosage of the narcotic Propofol combined with the incapability of the technology monitoring the depth of the patient’s anesthetic state to notice the patient becoming aware. A solution can be a highly sensitive and selective real time monitoring device for Propofol based on optical absorption spectroscopy. Its working principle has been postulated by Prof. Dr. habil. H. Hillmer and formulated in DE10 2004 037 519 B4, filed on Aug 30th, 2004. It consists of the exploitation of Intra Cavity Absorption effects in a two mode laser system. In this Dissertation, a two mode external cavity semiconductor laser, which has been developed previously to this work is enhanced and optimized to a functional sensor. Enhancements include the implementation of variable couplers into the system and the implementation of a collimator arrangement into which samples can be introduced. A sample holder and cells are developed and characterized with a focus on compatibility with the measurement approach. Further optimization concerns the overall performance of the system: scattering sources are reduced by re-splicing all fiber-to-fiber connections, parasitic cavities are eliminated by suppressing the Fresnel reflexes of all one fiber ends by means of optical isolators and wavelength stability of the system is improved by the implementation of thermal insulation to the Fiber Bragg Gratings (FBG). The final laser sensor is characterized in detail thermally and optically. Two separate modes are obtained at 1542.0 and 1542.5 nm, tunable in a range of 1nm each. Mode Full Width at Half Maximum (FWHM) is 0.06nm and Signal to Noise Ratio (SNR) is as high as 55 dB. Independent of tuning the two modes of the system can always be equalized in intensity, which is important as the delicacy of the intensity equilibrium is one of the main sensitivity enhancing effects formulated in DE10 2004 037 519 B4. For the proof of concept (POC) measurements the target substance Propofol is diluted in the solvents Acetone and DiChloroMethane (DCM), which have been investigated for compatibility with Propofol beforehand. Eight measurement series (two solvents, two cell lengths and two different mode spacings) are taken, which draw a uniform picture: mode intensity ratio responds linearly to an increase of Propofol in all cases. The slope of the linear response indicates the sensitivity of the system. The eight series are split up into two groups: measurements taken in long cells and measurements taken in short cells.

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This thesis concerns with the main aspects of medical trace molecules detection by means of intracavity laser absorption spectroscopy (ICLAS), namely with the equirements for highly sensitive, highly selective, low price, and compact size sensor. A novel two modes semiconductor laser sensor is demonstrated. Its operation principle is based on the competition between these two modes. The sensor sensitivity is improved when the sample is placed inside the two modes laser cavity, and the competition between the two modes exists. The effects of the mode competition in ICLAS are discussed theoretically and experimentally. The sensor selectivity is enhanced using external cavity diode laser (ECDL) configuration, where the tuning range only depends on the external cavity configuration. In order to considerably reduce the sensor cost, relative intensity noise (RIN) is chosen for monitoring the intensity ratio of the two modes. RIN is found to be an excellent indicator for the two modes intensity ratio variations which strongly supports the sensor methodology. On the other hand, it has been found that, wavelength tuning has no effect on the RIN spectrum which is very beneficial for the proposed detection principle. In order to use the sensor for medical applications, the absorption line of an anesthetic sample, propofol, is measured. Propofol has been dissolved in various solvents. RIN has been chosen to monitor the sensor response. From the measured spectra, the sensor sensitivity enhancement factor is found to be of the order of 10^(3) times of the conventional laser spectroscopy.

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ZUSAMMENFASSUNG: Proteinkinasen übernehmen zentrale Aufgaben in der Signaltransduktion höherer Zellen. Dabei ist die cAMP-abhängige Proteinkinase (PKA) bezüglich ihrer Struktur und Funktion eine der am besten charakterisierten Proteinkinasen. Trotzdem ist wenig über direkte Interaktionspartner der katalytischen Untereinheiten (PKA-C) bekannt. In einem Split-Ubiquitin basiertem Yeast Two Hybrid- (Y2H-)System wurden potenzielle Interaktionspartner der PKA-C identifiziert. Als Bait wurden sowohl die humane Hauptisoform Cα (hCα) als auch die Proteinkinase X (PrKX) eingesetzt. Nach der Bestätigung der Funktionalität der PKA-C-Baitproteine, dem Nachweis der Expression und der Interaktion mit dem bekannten Interaktionspartner PKI wurde ein Y2H-Screen gegen eine Mausembryo-cDNA-Expressionsbibliothek durchgeführt. Von 2*10^6 Klonen wurden 76 Kolonien isoliert, die ein mit PrKX interagierendes Preyprotein exprimierten. Über die Sequenzierung der enthaltenen Prey-Vektoren wurden 25 unterschiedliche, potenzielle Interaktionspartner identifiziert. Für hCα wurden über 2*10^6 S. cerevisiae-Kolonien untersucht, von denen 1.959 positiv waren (1.663 unter erhöhter Stringenz). Über die Sequenzierung von ca. 10% der Klone (168) konnten Sequenzen für 67 verschiedene, potenzielle Interaktionspartner der hCα identifiziert werden. 15 der Preyproteine wurden in beiden Screens identifiziert. Die PKA-C-spezifische Wechselwirkung der insgesamt 77 Preyproteine wurde im Bait Dependency Test gegen largeT, ein Protein ohne Bezug zum PKA-System, untersucht. Aus den PKA-C-spezifischen Bindern wurden die löslichen Preyproteine AMY-1, Bax72-192, Fabp3, Gng11, MiF, Nm23-M1, Nm23-M2, Sssca1 und VASP256-375 für die weitere in vitro-Validierung ausgewählt. Die Interaktion von FLAG-Strep-Strep-hCα (FSS-hCα) mit den über Strep-Tactin aus der rekombinanten Expression in E. coli gereinigten One-STrEP-HA-Proteinen (SSHA-Proteine) wurde über Koimmunpräzipitation für SSHA-Fabp3, -Nm23-M1, -Nm23-M2, -Sssca1 und -VASP256-375 bestätigt. In SPR-Untersuchungen, für die hCα kovalent an die Oberfläche eines CM5-Sensorchips gekoppelt wurde, wurden die ATP/Mg2+-Abhängigkeit der Bindungen sowie differentielle Effekte der ATP-kompetitiven Inhibitoren H89 und HA-1077 untersucht. Freie hCα, die vor der Injektion zu den SSHA-Proteinen gegeben wurde, kompetierte im Gegensatz zu FSS-PrKX die Bindung an die hCα-Oberfläche. Erste kinetische Analysen lieferten Gleichgewichtsdissoziationskonstanten im µM- (SSHA-Fabp3, -Sssca1), nM- (SSHA-Nm23-M1, –M2) bzw. pM- (SSHA-VASP256-375) Bereich. In funktionellen Analysen konnte eine Phosphorylierung von SSHA-Sssca1 und VASP256-375 durch hCα und FSS-PrKX im Autoradiogramm nachgewiesen werden. SSHA-VASP256-375 zeigte zudem eine starke Inhibition von hCα im Mobility Shift-Assay. Dieser inhibitorische Effekt sowie die hohe Affinität konnten jedoch auf eine Kombination aus der Linkersequenz des Vektors und dem N-Terminus von VASP256-375 zurückgeführt werden. Über die Wechselwirkungen der hier identifizierten Interaktionspartner Fabp3, Nm23-M1 und Nm23-M2 mit hCα können in Folgeuntersuchungen neue PKA-Funktionen insbesondere im Herzen sowie während der Zellmigration aufgedeckt werden. Sssca1 stellt dagegen ein neues, näher zu charakterisierendes PKA-Substrat dar.

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Die thermische Verarbeitung von Lebensmitteln beeinflusst deren Qualität und ernährungsphysiologischen Eigenschaften. Im Haushalt ist die Überwachung der Temperatur innerhalb des Lebensmittels sehr schwierig. Zudem ist das Wissen über optimale Temperatur- und Zeitparameter für die verschiedenen Speisen oft unzureichend. Die optimale Steuerung der thermischen Zubereitung ist maßgeblich abhängig von der Art des Lebensmittels und der äußeren und inneren Temperatureinwirkung während des Garvorgangs. Das Ziel der Arbeiten war die Entwicklung eines automatischen Backofens, der in der Lage ist, die Art des Lebensmittels zu erkennen und die Temperatur im Inneren des Lebensmittels während des Backens zu errechnen. Die für die Temperaturberechnung benötigten Daten wurden mit mehreren Sensoren erfasst. Hierzu kam ein Infrarotthermometer, ein Infrarotabstandssensor, eine Kamera, ein Temperatursensor und ein Lambdasonde innerhalb des Ofens zum Einsatz. Ferner wurden eine Wägezelle, ein Strom- sowie Spannungs-Sensor und ein Temperatursensor außerhalb des Ofens genutzt. Die während der Aufheizphase aufgenommen Datensätze ermöglichten das Training mehrerer künstlicher neuronaler Netze, die die verschiedenen Lebensmittel in die entsprechenden Kategorien einordnen konnten, um so das optimale Backprogram auszuwählen. Zur Abschätzung der thermische Diffusivität der Nahrung, die von der Zusammensetzung (Kohlenhydrate, Fett, Protein, Wasser) abhängt, wurden mehrere künstliche neuronale Netze trainiert. Mit Ausnahme des Fettanteils der Lebensmittel konnten alle Komponenten durch verschiedene KNNs mit einem Maximum von 8 versteckten Neuronen ausreichend genau abgeschätzt werden um auf deren Grundlage die Temperatur im inneren des Lebensmittels zu berechnen. Die durchgeführte Arbeit zeigt, dass mit Hilfe verschiedenster Sensoren zur direkten beziehungsweise indirekten Messung der äußeren Eigenschaften der Lebensmittel sowie KNNs für die Kategorisierung und Abschätzung der Lebensmittelzusammensetzung die automatische Erkennung und Berechnung der inneren Temperatur von verschiedensten Lebensmitteln möglich ist.