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In Wireless sensor networks (WSNs), clustering is an important and effective technique for raising the life span of the network, which directly led to an improved routing method. This technique includes combination of sensor nodes (SNs) to clusters and selecting the suitable CHs for every cluster. Actually, CHs accumulates the data from related SNs in the cluster and after that, it transmits those combined data to BS. The drawbacks of the collection of suitable cluster head (CH). Yet, a lot of analysis is still going on for resolving these issues depending upon specific parameters. Here this paper establishes a novel cluster based routing model via choosing the optimal CH. For optimal CHS, this work exploits a novel approach called Lion Mutated WOA (LM-WOA) that combined the theories of WOA and LA.Here, an innovative multi-objective function is described based upon diverse constraints like: Distance, Delay, Energy, Cluster Density, Traffic rate, Throughput and QoS. After electing the optimum CH, the data is transmitted along the chosen optimal path that is selected via LM-WOA model. The effectiveness of the newly implemented approach is ultimately reflected through analysis. [ABSTRACT FROM AUTHOR]

Wireless Sensor Nodes (WSNs) cover almost everywhere, and they carry a tremendous amount of computation. As their resources are still limited, they are still struggling to meet the demands of computeintensive tasks. Offloading sensor nodes' tasks using wireless networks to the cloud (edge cloud/far cloud) becomes an essential means to improve sensor nodes' performance. By analyzing the sensor nodes' offloading process, we found numerous three granular phenomena. A collection of sensor tasks on each device can perform its tasks locally, at the edge node, and in the far cloud, respectively. There is mutual gaming between the devices due to shared bandwidth and other factors. This paper proposes an offloading model for sensor tasks, drawing on three-way game theory ideas. First, we define the cost of offloading mobile devices. Second, through a three-way game, the model divides the mobile senor tasks into different locations rationally and efficiently. The game determines the places where tasks are offloaded, i.e., the set of tasks is divided into three parts by a pair of thresholds, which are offloaded to three locations, i.e., local, edge nodes, and cloud servers. Different devices will have different thresholds for partitioning, and we repeat iterations of adjusting both thresholds to find the optimal range of threshold partitioning based on the cost function. The simulation experiments results show that the strategy and the corresponding algorithm are beneficial and can optimize the energy consumption well under the premise of meeting the quality of service. [ABSTRACT FROM AUTHOR]

Sensor-IoT (Internet of Things) networks allow users, cloud, or edge servers to query and collect data from sensor-IoT devices. It is important to enable the resilience of failures in data query and collection. This paper studies the issue of functional structure to enable the mutual support among sensor-IoT devices in discovery and recovery of query losses with low cost. We especially address the problem of how to configure the sensor-IoT network with a sufficient but small number of detector-role nodes that perform the monitoring role for nearby nodes. We propose two schemes. One is random selection of detectors at each sensor-IoT node. Another scheme allows each IoT-sensor node to choose the its detectors in an order of node IDs. The evaluation results show the effectiveness in the construction of detector sets with a small number of sensors by using the proposed schemes. Moreover, we verify that the ID-sequence based scheme is more effective in detector selection to reach the target of easy construction of detector set using a small number of detectors. [ABSTRACT FROM AUTHOR]

The influence of the internet of things (IoT) has been dramatically increasing on various applications. In the recent trend, wireless sensor networks (WSN) will become an important technology of IoT. Clustering methods are a common way to improve the performance of these networks, and IEEE 802.15.4 becomes a more popular technology for WSNs. In this paper, a discrete-time Markov model is proposed for a sensor node in a cluster based on the non-acknowledge non-beaconenabled IEEE 802.15.4. This paper calculates the probability of the busy channel using a proposed recursive method and conditional probabilities. Moreover, the cumulative distribution function of the packet delivery delay, packet delivery ratio, and energy consumption per bit are obtained by proposing an absorbing Markov model. The model is investigated for various network conditions, and the results are verified in different cases using the Monte Carlo algorithm, which points to the accuracy and precision of the model. [ABSTRACT FROM AUTHOR]

Recently, target coverage and node connectivity have been playing a significant role in various wireless sensor network applications. Various target coverage algorithms are widely used to monitor the target point by dividing sensor nodes into a set of cover groups where, each sensor cover group contains the target points. Optimal sensor node placement imposes a critical task when the number of sensors is limited. The quality of maximum target coverage and node connectivity can be improved by deploying sensors in the optimal location. In this paper, a novel genetic algorithm with 2-D discrete Daubechies 4 (db4) lifting wavelet transform is proposed for identifying the optimal position of each sensor. Initially, the genetic algorithm identifies the population-based sensor location and 2-D discrete db4 lifting adjusts the sensor location into an optimal position where each sensor can cover a maximum number of targets that are connected to another sensor. The potential position of the sensor is examined while the sensor covers the target points, and the node can communicate to another node. To further prove that the proposed model is better than the existing algorithm, a set of experiments are carried out with different scenarios by achieving maximum target points covers, node connectivity, and network lifetime with a limited number of sensor nodes. [ABSTRACT FROM AUTHOR]

By combining the complementary strengths of sensor networks and grid computing, sensor grids can provide various services that require realtime information from the physical environment and vast amount of computational and storage resources. Different sensor services may be owed by different organizations, so it is quite reasonable to address the selfish problems among several sensor service providers. The paper is targeted to solve this problem. This paper studies sensors cooperation in sensor grid. We formalize sensors cooperation using optimization based approach, which can be distributed by sensor service application QoS optimization and sensor service provider optimization. The paper presents the market based sensors cooperation algorithm in the sensor grid. The paper discusses implementation issues of sensor service cooperation negotiation. A camera sharing application scenario is presented to illustrate how to exploit services of sensor service provider for supporting the sensor grid user requirement. The simulations are conducted to compare the proposed algorithm with other resource allocation algorithms for sensor grid. [ABSTRACT FROM AUTHOR]

Spectrogram analysis is used to characterize electrical spiking behavior of Pleurotus citrinopileatus and its relation to fungal signalling. The setup explores the effects of heat, water, and music on the electrical response of fungi with the additional context of ambient room temperature, substrate moisture level, ambient sound level, and ambient air humidity. Summarily, distinct frequency and intensity spiking behavior is identified in response to various external stimuli, which may provide discerning information to further decode fungal signals. [ABSTRACT FROM AUTHOR]

Recent years have witnessed the rapid development of camera sensor applications. Sensors and cameras are deployed everywhere. However, there are several problems in traditional camera sensor surveillance applications. First, the positions of the camera sensors are fixed so that the surveillance range is limited. Second, there is a potential security issue since criminal suspects can make an on-the-spot investigation in advance and then circumvent the surveillance area while committing criminal activities. To solve these problems, we introduced a mobile video surveillance method in this paper, which can not only extend the monitoring range, but also improve the security. We firstly design a Stadia Ant Colony Algorithm (SACA) to improve the surveillance efficiency. Based on this algorithm, a Chaotic Path Planning Algorithm (CPPA) is designed to make the moving paths of camera sensors unpredictable, which ensures the security of surveillance. Moreover, a prototype system with mobile cameras is implemented. Extensive simulation experiments validate the effectiveness of the proposed method which is an improvement of existed fixed surveillance systems. [ABSTRACT FROM AUTHOR]

Urban traffic congestion has become a very common phenomenon. In order to solve this problem, it is necessary to obtain the traffic data effectively. In this paper, we propose an adaptive vehicle detection algorithm based on magnetic sensors in intelligent transportation systems. The magnetic sensors used to detect the vehicles are deployed on the sides of roads to reduce the interference of sensors to the traffic other than the traditional methods in which sensors are often deployed on the traffic roads, and hence interfere with the normal traffic. In order to reduce the interference and improve the detecting accuracy rate, some kinds of effective algorithms to detect small signals are required. First of all, the deviation factor of the geomagnetic field signal is constructed to extract characteristics of the magnetic signals. Based on the definition, the y-axis of the magnetic signal is obtained and is proven to be the most obvious amplitude of variation. Based on this discovery, an adaptive vehicle detection algorithm is proposed. The proposed algorithm is tested on single lane and real and complicated urban road environments. Experimental results show that the proposed algorithm can achieve high detection accuracy. [ABSTRACT FROM AUTHOR]

Human activity is a key element for context-awareness and health monitoring. However, it is difficult to infer human activities from uncertain mobile sensor data, due to sensor noise and various phone positions. Activities like standing, sitting, walking, running have been investigated widely, while research on identifying fine-grained walking modes without prior knowledge of phone positions is still in its infancy. This paper proposes a two-layer algorithm to recognize different types of walking (static, slow walking, medium walking, fast walking and running) and different ways of going upstairs and downstairs (by elevator, by escalator and by stairs) using only phone sensors without prior knowledge of phone positions. Horizontal walking, upstairs and downstairs are distinguished on the first layer using only barometer data. Different types of horizontal walking are distinguished on the second layer using the features extracted from 3-axis acceleration sequences through wavelet transform and singular value decomposition. Recognition of different ways of going upstairs and downstairs is performed with altitude sequences and 3-axis acceleration sequences. Three classification algorithms of Support Vector Machine, Bayesian Network and Decision Tree are applied separately to fulfill the classification tasks. Evaluations show that the three algorithms achieve comparable recognition results and Decision Tree achieves the best with the mean recognition accuracy of horizontal walking modes as 95% and vertical walking modes as 97.7%, independent of phone positions. [ABSTRACT FROM AUTHOR]

This paper presents an optical sensor system to observe early changes in the surface properties due to the microbic corrosion of metals. The experiment uses natural lake water at pH 8.3, and bulk water at pH 4.0 and pH 9.2 as test solutions and mild steel as test coupon. The optical micrographs as well as optical scattered light intensities have been taken simultaneously within 15 minutes at regular intervals. Both experimental observation systems provide the real time adherence information about the corrosion products on metal surfaces. The optical results and micrographs found to be dissimilar on different test solution. Microbial corrosion is well established fact but it is solely experimentally illustrated in this study. [ABSTRACT FROM AUTHOR]

This paper analyzes the physical relation between the power consumption and the link utilization of wireless video sensor networks. It then proposes a method of multi-channel allocation and routing for multi-hop wireless sensor networks where each node is a battery-powered video camera sensor. Battery powered video camera sensors are often used in a form of a wireless mesh network to cover a large area. We analyze the power consumption model for a wireless link in terms of the distance and its utilization ratio. We present a formula of routing and channel allocation using only active sensor nodes in a way that minimizes the overall power consumption while ensuring transmission of the target video data. We developed a fast heuristic algorithm, and implemented it in a wireless video sensor network simulator. It introduces a notion of aggressor and victims of shared channels to calculate utilization incrementally as the routing algorithm proceeds. Extensive simulation results are provided with wireless video sensor networks of various sizes, which show the performance advantage of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The article discusses various reports published within the issue, including one by Maia Judith Fraser on face routing, one by Beat Gfeller and Elias Vicari on growth-bounded graphs, and one by Gagan Gupta and Parmesh Ramanathan on algorithmic solutions.

A new method for measuring fat concentration in milk based on a He-Ne laser sensor at room temperature (25°C) is presented. The measurement system consists of signal acquisition module and signal processing module. The signal acquisition module consists of a light source, photodetector, temperature control module and a lifting platform. The signal processing module mainly consists of signal amplification module, signal conversion module and microprocessor module. According to the characteristic of fat in milk, the corresponding laser light source and photodetector are selected. Milk samples with different fat concentration have different levels of reflectance. Based on this, the model of fat concentration and diffuse reflection light intensity in milk is established. The research shows that the fat concentration can be measured accurately by the laser sensor system, and the feasibility of the method is also verified. Meanwhile, the method proposed in this paper can measure the fat concentration in milk in real time, which provides a new way for detecting main component concentration in foods. [ABSTRACT FROM AUTHOR]

A well-known dangerous attacks against Wireless Sensor Networks (WSNs) is Sybil attack in which a malicious node propagates multiple fake identities. This attack affects routing protocols and many usual operations of WSNs including voting and data aggregation. In this paper, a novel algorithm has been proposed for detecting this attack in static WSNs. There are several mobile observer nodes in the proposed algorithm, which walk in the network's environment continuously. They first detect areas suspicious to Sybil attack and then record information about these areas in their memories. Using stored information, they will be able to detect Sybil nodes. The proposed algorithm is implemented using JSIM simulator and its efficiency has been compared to other existing algorithms in terms of true detection and false detection rates. The results show that the proposed algorithm can detect 99% of Sybil nodes on average, while the false detection rate is about 5%. [ABSTRACT FROM AUTHOR]

The objective of this work was to demonstrate how joining surface plasmon resonance (SPR) with interferometry provides a high sensitivity molecular sensor, especially for low molecular weight gases. This paper reports how various parameters influence the performance of the twochannel surface plasmon resonance interferometer (SPRI) laboratory system. Much of the effort was to achieve good reproducibility and to reduce the sources of noise and drift. This SPRI design uses a Mach-Zehnder interferometer (MZI) that allows for measurements with a single detector or with a digital camera. Results both in detector and camera modes using the optimize system are reported. In the absence of functionalization of the gold film, it is assummed that sensing was primarily due to the nearfield photonic gradient forces generated by the evanescent electric fields at the gold film that forms a dielectric layer over the gold. The calibration of recent experimental studies in detector mode of dry N2 flow showed that the SPRI technique has a sensitivity of about 1 part in 107 RIU (RIU = refractive index units). The sensitivity to milliliters/min of anhydrous NH3 mixed in 1.5 liters/min of dry N2 flow is estimated to be <1 part in 108 RIU. [ABSTRACT FROM AUTHOR]

Underwater Wireless Sensor Networks (UWSNs) have become a hot field in wireless sensor networks. In UWSNs, nodes are distributed in a harsh 3 dimensional (3D) environment, which are easy tofail due to the limited amount of energy and it is much more difficult to replace or recharge in underwater circumstances. Dynamic changes of network topology due to node failure or poor link quality will significantly affect the acoustic communication and decrease the network performance. To solve those problems, this paper proposes a topology control algorithm that comprehensively considers link quality and balance of node energy consumption based on the optimally rigid graph in 3D underwater sensor networks. By dynamically optimizing network topology based on link quality and energy consumption, the proposed algorithm can significantly improve network performance. Extensive mathematical analysis and simulation results demonstrate that the proposed algorithm can not only improve network robustness, but also effectively balance nodes energy and load, as well as prolonging network lifetime compared with other existing algorithms. [ABSTRACT FROM AUTHOR]

With the technology development, more and more transactions or activities are conducted via networks. Along with electronic technology penetrating every where in the world, networks need face the new problem which was not predicted when networks were firstly designed, the malicious attack. The existing malicious activity or malicious person forces to redesign a much safer network. The security problem in multi hop wireless networks is more severe than that in wired networks since its transmission media is the unprotected air, which makes wireless network easier to be attacked. In this paper, we show how to increase the effective throughput via carefully choosing the multi-path routing for given source and destination nodes under attack. We model the problem as a two-player game and theoretically prove that the corresponding routing protocols can achieve an effective network throughput (with packets which are not attacked) within a constant factor of the optimum in the worst case. Our theoretic results are confirmed by extensive simulations studies. [ABSTRACT FROM AUTHOR]

Considering the potential interference of ultra-wide band (UWB) system to OFDM based narrowband wireless communication system, such as IEEE 802.11n system, this paper investigates the optimal power allocation scheme for Impulse Radio UWB (IR-UWB) user in order to maximize the total transmission rate of UWB within the coexisting frequency range shared with IEEE 802.11n, with the constraints that its interference to IEEE 802.11n user is below a certain acceptable threshold. Therefore, UWB user could reach its best performance regarding to transmission rate, while the coexisting IEEE 802.11n user tends to work normally with permissible interference from UWB user. Simulation results show that the optimal power allocation scheme significantly increases the capacity of UWB user compared with equal power allocation scheme. [ABSTRACT FROM AUTHOR]

The expected lifetime of any wireless sensor network is a critical issue since sensor nodes are powered by small batteries. The propagation of redundant highly correlated data is costly in terms of system performance, and results in energy depletion, network overloading, and congestion. Data aggregation is regarded as an effective technique to reduce energy consumption and prevent congestion. This paper objective is to identify near duplicate nodes that generate similar sets of collected data in periodic applications. We propose a new prefix filtering approach that avoids computing similarity values for all possible pairs of sets.We define a new filtering technique based on the quality of information. To the best of our knowledge, the proposed algorithm is a pioneer in using "sets similarity functions" for data aggregation in sensor networks. To evaluate the performance of the proposed method, experiments on real and synthetic sensor data have been conducted. The analysis and the results show the effectiveness of our method dedicated to sensor networks. [ABSTRACT FROM AUTHOR]

Recently, social-based approaches, which attempt to exploit the social behavior of mobile nodes to guide routing decisions, have attracted lots of attention in routing design of opportunistic networks. This paper presents a survey of the social characteristics shown in opportunistic mobile networks and emphasizes how to measure the social characteristics in time vary contact graph. It discusses the typical social-based routing protocols and investigates the relationship among the routing performance, the mobility scenarios and routing protocols. This paper is concluded by discussing open questions and challenges in the design of social-based routing protocol between mobile devices. [ABSTRACT FROM AUTHOR]

Ocean observations are difficult and expensive to obtain. Optimal placement of oceanographic sensors can reduce the number of sensors used while improving observational accuracy. This paper presents a new technique for optimal placement of a set of oceanographic sensors in a highly variable environment. The study initially demonstrates how an objective analysis method, which incorporates an inverse distance weighting function, can be used to estimate salinity maps from a small number of sensors. Next, the effectiveness of a particular choice of sensor locations in terms of the expected errors is addressed. Subsequently it is shown how numerical, nonlinear optimization techniques can iteratively modify a set of sensor positions until the optimal choice of sensor placements is achieved by minimizing the expected error. The technique is first evaluated with a series of ground truth simulations using historical data. The paper concludes by presenting the results of a field trial, in which a small number of optimally placed sensor locations are used to develop accurate salinity maps for a complex region of the lower Hudson River with root mean square errors of approximately 1 psu or less for several comparison points. [ABSTRACT FROM AUTHOR]

Although very developed in many sectors (databases, filesystems), access control schemes are still somewhat elusive when it comes to wireless sensor networks. However, it is clear that many WSN systems - such as healthcare and automotive ones - need a controlled access to data that sensor nodes produce, given its high sensitivity. Enforcing access control in wireless sensor networks is a particularly difficult task due to the limited computational capacity of wireless sensor nodes. In this paper we present a full-fledged access control scheme for wireless sensor data. We enforce access control through data encryption, thus embedding access control in sensor data units. We also propose a lightweight key generation mechanism, based on cryptographic hash functions, that allows for hierarchical key derivation. The suggested protocol only relies on simple operations, does not require interactions between nodes and data consumers and has minimal storage requirements. [ABSTRACT FROM AUTHOR]

During machining, high temperatures are generated in the region of the tool cutting edge. These temperatures have a controlling influence on the wear rate of the cutting tool and on the friction between the chip and the tool. However, direct measurement of temperature using contact type sensors at the tool-work interface is difficult to implement due to the movement of the workpiece and the presence of the chip. Conventional methods such as infrared pyrometer, embedded thermocouple and tool-work thermocouple usually present problems. The use of inverse heat conduction techniques represents a good alternative since these methods uses temperatures measured in accessible positions. This paper proposes a comparison of the inverse techniques Golden Section, Function Specification, Simulated Annealing and Dynamics Observers Based on Green's Function. They are used in an experimental methodology to determine the thermal fields and heat generated at the chip-tool interface during machining. A numerical 3-D transient thermal model was developed to consider both tool and tool holder assembly. The results are validated by controlled experiments and qualitative analysis. Some of the cited procedures are in the computational code INV3D that contain a series of functions for the experimental data acquisition, the three-dimensional mesh generation and the graphical environment analysis. [ABSTRACT FROM AUTHOR]

The signal returns from radar targets are usually buried in thermal noise and clutter. Target detection is commonly performed by comparing radar returns to an adaptive threshold such that a constant false alarm rate (CFAR) is maintained. The threshold in a CFAR detector is set on a cell by cell basis according to the estimated noise/clutter power, which is determined by processing a group of reference cells surrounding the cell under investigation. In this paper, a configurable Field Programmable GateArray (FPGA)-based hardware architecture forTrimmed Mean (TM)-CFAR processor for radar target detection is presented. The proposed processor is designed, implemented, and tested using Stratix FPGA chip (EP2S60F1020C4 device). The system has the advantages of being simple, fast, and flexible with low development cost. For a reference window of length 16 cells, the experimental results carried out using Altera development kit showed that the proposed processor works properly with a processing speed up to 100 MHz. [ABSTRACT FROM AUTHOR]

This paper presents a FPGA based architecture for Sobel edge detection operator. Typical use of Edge detection is in the artificial intelligence system. It has found application in forensic science and also in digital multimedia for creating image dazzling effect. Currently the image processing algorithms has been limited to software implementation which is slower due to the limited processor speed. So a dedicated processor for edge detection has been required which was not possible until advancement in VLSI technology. Now more complex system can be integrated on a single chip providing a platform to process real time algorithms on hardware. Sobel operator is chosen due to its property of less deterioration in high levels of noise. [ABSTRACT FROM AUTHOR]

This paper presents an optoelectronic system to estimate the degree of corrosion of mild steels. The and detector fibres are held at different angles to probe the changes in surface texture due to atmospheric corrosion. The fibre optic sensor system consists of laser light as a source and a pair of photo diodes as detectors. This work is based on the theory of scattering of light by objects. The degree of corrosion of metals is estimated as the ratio between scattered and reflected intensities in a relative scale from zero to one hundred. The results obtained show a consistent relationship between the optical measurements and the level of corrosion. This work suggests the possibility of using the surface roughness factor to measure the degree of corrosion of metals. [ABSTRACT FROM AUTHOR]

Optimizing energy consumption in wireless sensor networks is of paramount importance. There is a recent trend to deal with this problem by introducing mobile elements (sensors or sink nodes) in the network. The majority of these approaches assume time-driven scenarios and/or single-hop communication between participating nodes. However, there are several real-life applications for which an event-based and multi-hop operation is more appropriate. In this paper we propose to adaptively move the sink node inside the covered region, according to the evolution of current events, so as to minimize the energy consumption incurred by the multi-hop transmission of the event-related data. Both analytical and simulation results are given for two optimization strategies: minimizing the overall energy consumption, and minimizing the maximum load on a specific sensor respectively. We show that by adaptively moving the sink, significant power saving can be achieved, prolonging the lifetime of the network. [ABSTRACT FROM AUTHOR]

In this paper, we analyze performance of the 802.15.4 cluster in beacon enabled mode under the presence of key exchange protocol. We assume that all nodes are applying power management technique based on the constant event sensing reliability required by the coordinator. Power management generates random sleep times by every node which in average fairly distributes the sensing load among the nodes. Key exchange is initiated by cluster coordinator after some given number of sensing packets have been received by the coordinator. We develop analytical model of key exchange integrated into the cluster's sensing function and evaluate the impact of frequency of key exchange on the cluster's energy consumption. [ABSTRACT FROM AUTHOR]

This paper presents a 3-dimensional algorithm for determining the node locations in ad-hoc wireless local area sensor networks capable of internodal distance measurement (ranging). In accordance with common classification of localisation strategies, the paper proposes a geometric centralised optionally anchor free algorithm that is based on clusterisation, multilateration and geodetic network adjustment. The method avoids fold- ambiguities by statistical tests on the robustness of the minimally stable structure in 3D. Such a rigid cluster is expanded by a novel robust approach for multilateration. The algorithm developed is capable of obtaining the least-squares solution reliably even in the presence of measurement noise levels of up to 7% of the ranges. Simulations with randomly deployed networks show that it is possible to reach the best achievable mean position deviation (i.e. the Cramer Rao bound). [ABSTRACT FROM AUTHOR]

Data gathering is a common but critical operation in many applications of wireless sensor networks. Innovative techniques that improve energy efficiency to prolong the network lifetime are highly required. Clustering is an effective topology control approach in wireless sensor networks, which can increase network scalability and lifetime. In this paper, we propose a novel energy efficient clustering scheme (EECS) for single-hop wireless sensor networks, which better suits the periodical data gathering applications. Our approach elects cluster heads with more residual energy in an autonomous manner through local radio communication with no iteration while achieving good cluster head distribution; further more, it introduces a novel distance-based method to balance the load among the cluster heads. Simulation results show that EECS prolongs the network lifetime significantly against the other clustering protocols such as LEACH and HEED. [ABSTRACT FROM AUTHOR]

Angle-of-arrival(AOA) based passive localization is an important enabling technology in tracking systems. Previous work mainly focus on locating the target by making a coordinates estimation, while only a few provide ambiguous area estimation. The latter ones, however, are more applicable in military scenarios, e.g. warship tracking, since ambiguous area contains much more information than coordinates. This paper proposes a novel approach for ambiguous area estimation in AOA based localization. Comparing to existing work, confidence ellipse is used for area estimation instead of rectangle and circle. Theoretic model and parameter setting in practical uses are discussed. We conduct extensive simulations in different settings. Simulation results show that our approach provides a good tradeoff between the accuracy and the confidence for localization. It performs better than the previous work under the same localization condition based on a good performance of the tradeoff between the confidence and accuracy. [ABSTRACT FROM AUTHOR]

In wireless sensor networks (WSNs), congestion introduces not only buffer overflow, but also transmission delay for message forwarding from the source node to the sink. In this paper, we propose a novel congestion-aware routing (CAW) scheme to reduce the packet end-toend transmission delay while increasing network throughput. The proposed routing protocol is based on the geographic routing scheme. The relay node selection is determined by the sensor node location and the congestion condition in MAC layer of the local area. The proposed routing scheme utilizes the local area traffic information to select the next hop node so that the likelihood for traffic congestion and transmission delay can be minimized in the subsequent routing. The OPNET simulation results demonstrate that the proposed routing scheme can reduce the end-to-end packets transmission delay by 50% while increasing the network throughput for more than 2 times in our settings. [ABSTRACT FROM AUTHOR]

The present work presents a hardware architecture design for real- time edge detection based on Interval Type-2 fuzzy systems. The proposed architecture is designed in order to be implemented on FPGAs, taking advantage of the parallelism, pipelining and fixed-point notation strategies. The proposed approach of hardware implementation is put forward because one of the main obstacles of Interval Type-2 fuzzy systems in applications is that they require a high processing rate and this kind of systems demands a high computational cost. The proposed approach is evaluated in three aspects, the first aspect is the processing rate, the proposed architecture must be able to realize at least 24 frames per second of edge detection, that corresponds to a real-time edge detection, the second aspect is their noise robustness, and the third aspect is the error with respect to the software implementation, and this is relevant because the proposed architecture handles the data at a binary level and there exist an inherent error in the hardware implementation. [ABSTRACT FROM AUTHOR]

With the increasing stress and unhealthy lifestyles in people's daily life, mental health problems are becoming a global concern. In particular, mood related mental health problems, such as mood disorders, depressions, and elation, arc seriously impacting people's quality of life. However, due to the complexity and unstableness of personal mood, assessing and analyzing daily mood arc both difficult and inconvenient, presenting a major challenge in mental health care. In this paper, we propose a novel framework called MoodMiner for assessing and analyzing mood in daily life. MoodMiner uses mobile phone data--mobile phone sensor data and communication data (including acceleration, light, ambient sound, location, call log, etc. )--to extract human behavior pattern and assess daily mood. A factor-graph based model called SFFG is proposed, combining temporal and social information together with mobile phone sensing data for daily mood assessment. Our approach overcomes the problems of subjectivity and inconsistency of traditional mood assessment methods, and achieves a fairly good accuracy (around 70%) with minimal user intervention. We have built a system with clients on Android platform and an assessment model based on factor graph. We have also carried out experiments to evaluate our design in effectiveness and efficiency. [ABSTRACT FROM AUTHOR]

Every time an exceptional situation takes place on the road, dangerous situations occur and they need the drivers' skills in order to cope with them. These special situations can occur due to many reasons such as a non-expected object on the road, or an incoming emergency vehicle. Current proposals consider that vehicles are equipped with sensors and communication devices that collect and communicate sensor data to a central point to take further decisions. In this paper, those exceptional situations are handled in a different way: we propose to integrate an ontology inside each vehicle to provide them with distributed reasoning capabilities. Our system benefits traffic management in emergency situations with immediate and coherent suggestions to drivers where each vehicle is a decision point, reacts considering its neighboring vehicles, and collaborates with them to reach consensus in real time. A complete analysis of the system is given, from the behavior of the wireless link channel to the application level, giving an integral description of the designed solution. The system operates continuously adapting itself to driver reactions. A common ontology provides, during the reasoning process, a suggestion to each driver, maintaining the coherence of the whole set of suggestions (avoiding conflicting situations). [ABSTRACT FROM AUTHOR]

Supporting multi-hop communication in Mobile ad Hoc Networks (MANET) is a challenging research area because it requires cooperation between different protocol layers Physical (Phy), medium access control (MAC), routing...). In particular, MAC and routing protocols could be considered mutually cooperative protocol layers. When a route is established, the exposed and hidden terminal problems at MAC layer may decrease the end-to-end performance proportionally with the length of each route. The topology of the network may change rapidly and unpredictability due to node mobility causing unstable links with multiple discontinuities. All these problems will increase especially in a shadowing environment qualified as an environment with important variations in the received signal power. In this paper, we proposed cross-layer designs among physical, MAC and network layers, using Received Signal Strength (RSS) as a cross-layer interaction parameter to provide reliable route discovery, stable links with a strong connectivity, and energy conservation in transmitting data in a shadowing environment. [ABSTRACT FROM AUTHOR]

Recently, Huang proposed a new access control scheme based on elliptic curve cryptosystem which prevents malicious nodes from joining the sensor network. This scheme uses the expiration time of nodes so that the nodes can only authenticate with its neighbor nodes within that time. In this paper, we first show that though this scheme is efficient, but it has a fatal weakness such as it is vulnerable to an active attack known as man-in-the-middle attack. In order to remedy that weakness we propose a more efficient and secure access control scheme as compared with Huang's scheme. Further, our scheme is significantly better in terms of performance and security compared with other related access control schemes. In fact, our scheme requires significantly less communication costs as compared to other related schemes. Moreover, we simulate our scheme for formal security analysis using the AVISPA (Automated Validation of Internet Security Protocols and Applications) tool and show that our scheme is secure. [ABSTRACT FROM AUTHOR]

Increasing the lifetime of a wireless sensor network (WSN) while maintaining good coverage is a well studied research problem. A cellular automaton is a biologically inspired model that has been widely used to model different physical systems including wireless sensor networks. In this paper, we use cellular automaton algorithms to optimize the coverage and the lifetime of a WSN. An advantage of the cellular automaton model is that its algorithms rely only on limited local information that can easily be stored in individual nodes. We consider a radius 2 neighborhood instead of a radius 1 neighborhood and consider different energy levels for different operations of the network. We compare different rules of this model with the rules of the existing model (radius 1 neighborhood) and we devise a probabilistic technique to solve the sudden falls of the coverage in these models. We develop cellular automaton based algorithms also for the object detection problem and present simulation results. [ABSTRACT FROM AUTHOR]

The Nd:YAG laser is a solid state laser that has many applications in the industry, science and medicine. We in this paper use a continuous wave (CW) Nd:YAG laser emitting light at 1064 nm to generate random numbers. We first give a recipe of an experimental setup that is capable of measuring and recording the vacuum fluctuations with the help of our cw Nd:YAG laser. The basic scheme simply involves the Nd:YAG laser, detectors and some radio frequency electronic components. The laser source used in the demonstration provides us with a quantum noise limited CW at a radio frequency sideband of 14 MHz. The final data obtained after appropriate electronic signal processing are digitized voltage fluctuations that correspond to the vacuum fluctuations in the optical domain. The data randomly lies above or below zero due to its quantum mechanical probabilistic nature. We assign a '1' to the data that is positive and a '0' to the data that is negative, hence we are able to generate a random bit sequence by using a cw Nd:YAG laser. This result adds yet another interesting application to the many number of broad applications of the Nd:YAG laser system. [ABSTRACT FROM AUTHOR]

Spatially distributed excitable chemical media can work as information processing devices where information is coded in propagating pulses of excitation. In this paper we discuss two strategies of sensing and two possible realizations of sensors. The functionality of proposed devices has been studied in numerical simulations and the results have been confirmed by experiments performed with ruthenium catalyzed, photosensitive Belousov-Zhabotinsky reaction. [ABSTRACT FROM AUTHOR]

In Photon Correlation Spectroscopy (PCS), it is important to keep the detector area smaller than the coherence area. However, only a little research has been devoted to ascertaining how small the detector aperture should be. This paper focuses on determining the optimum aperture for the first time in the following ways. The signal in the PCS experiment is produced using spatial coherence and the quantum noise is developed by photon statistics. By calculating the signal-to-noise power ratio (S²/N²) of the Photon Multiplier Tube, the optimum detector aperture is calculated as the best S²/N². Furthermore, the best signal to noise power ratio can also be obtained by adjusting the distance between the pin holes. [ABSTRACT FROM AUTHOR]

A surveillance application requires sufficient coverage of the protected region while minimizing the energy consumption and extending the lifetime of sensor networks. This can be achieved by putting redundant sensor nodes to sleep. In this paper,we propose a precise and energy-aware coverage control protocol, named Area-based Collaborative Sleeping (ACOS). The ACOS protocol, based on the net sensing area of a sensor, controls the mode of sensors to maximize the coverage, minimize the energy consumption, and to extend the lifetime of the sensor network. The simulation shows that our protocol has better coverage of the surveillance area while waking fewer sensors than other state-of-the-art sleeping protocols. It extends the lifetime of sensor networks significantly. [ABSTRACT FROM AUTHOR]

Wireless sensor networks, consisting of sensors equipped with energy-limited batteries, have been receiving significant attention and are increasingly being deployed for environmental monitoring and surveillance. Data generated by the sensors usually needs to be extracted and aggregated for a wide variety of purposes. Due to the serious energy constraint imposed on such a network, it is a great challenge to perform aggregate queries efficiently. In this paper, we consider the aggregate query evaluation problem in wireless sensor networks with an objective to prolong the network lifetime. To do so, we first introduce a node capability concept, which balances the residual energy and the consumed energy at each node, and propose a heuristic algorithm based on this concept. We then present an improved algorithm by incorporating group aggregation and conditional clauses into consideration. We finally evaluate the performance of the proposed algorithms against the existing algorithms through experimental simulations. The experimental results show that the proposed algorithms significantly outperform the existing ones in terms of network lifetime. [ABSTRACT FROM AUTHOR]

Laser-Doppler profile sensor was developed for highly spatially resolved velocity-profile measurement of shear flows. The profile sensor utilizes two optical fringe systems in the measurement volume. The sensor resolves both the position and the velocity of individual tracer particle inside the measurement volume. Hence the spatially high resolved velocity profile is obtained without traversing the sensor. In this paper, the sensor systems based on two different techniques are reported. The sensors were designed to measure flow velocity close to zero, which is encountered in boundary layer flows. The spatial resolution and relative accuracy were estimated to be about 5 micrometers and 0.2 %, respectively. The dimensions of the measurement volume were approximately 0.1 x 0.1 x 1 mm. The sensors were tested in laminar boundary layers and they successfully resolved the Blasius velocity profile close to the wall. Furthermore, the turbulent boundary layer in a two-dimensional channel flow was analyzed. The feasibility of the sensors was demonstrated through the experiments. [ABSTRACT FROM AUTHOR]

We present a model of Quantum Finite State Machines (QFSM) based on the quantum circuit representation. In this model, properties of quan-tum bits are exploited in order to implement Quantum Finite State Machines without an explicit external memory. We show that because of the the natural ability of quantum systems to retain the quantum state, quantum circuits can be directly used to implement some classes of the quantum finite state machines. In particular, the circuit model allows to remove the logic-memory distinction as it is used in the classically established model of finite state machines. Rather, the quantum register implementing the QFSM as a circuit is alternatively used as memory and as logic. In order to allow such behavior the quantum circuit (pro-cessor) is controlled by a classical circuit that provides the necessary timing of the quantum operations as well as the interface between the quantum and the classical world. Moreover, additional mechanism for preserving unknown quantum qubit state is used and a novel computa-tional protocol allowing the implementation of the QFSM is proposed. This framework is is called the Classically Controlled Quantum Com-puter (CCQC). The CCQC thus combines a quantum processor with a classical controller in such manner that computation is carried from the classical inputs, through quantum processing to classical outputs. We discuss a high level synthesis approach to quantum sequence detection based on the synthesis of quantum sequential circuits. Such machines can find many applications for instance in robotics; for exam-ple a robot is required to recognize certain sequences of input sensor values. [ABSTRACT FROM AUTHOR]

A wireless sensor network for automatic meter reading needs to satisfy two contradicting requirements, i.e. long lifetime and prompt detection and notification of emergency. We propose a sensor network protocol for this purpose, in which sensor nodes operate on a low duty cycle while the latency of transmission is guaranteed to be less than a certain bound. In this protocol, each node is assigned a time slot in which it receives messages from other nodes. To accomplish slot assignment where nodes further from a BS are assigned earlier time slots for a packet to be transmitted to the BS in one cycle, we propose a slot assignment function with which a node can determine its own slot in a distributed way. We explore several slot assignment functions to find one which gives low and homogeneous contention over a grid network. The simulation results show that our protocol performs well close to the optimal case. [ABSTRACT FROM AUTHOR]

A wireless sensor network (WSN) is composed of wireless sensors with limited energy resources, which limits the network lifetime. How to maximize the network lifetime, is critical in the design of WSNs. We establish a relationship between the node deployment and the network lifetime in a periodical data delivery scenario of WSNs. On the basis of our theoretical analysis, we propose a new nonuniform deployment approach in which sensor nodes are spread on the WSN according to variation in the node energy consumption, thereby effectively increasing the network lifetime. Both theoretical analysis and simulation results show that our approach outperforms existing uniform deployment method in terms of the network lifetime. In addition, we also tested our deployment strategy on a WSN testbed. [ABSTRACT FROM AUTHOR]

We consider a sensor network involving sensors that are placed in specific locations. A point phenomenon is being detected and tracked by activated sensors. The latter collect data characterizing parameters of the phenomenon, possibly compress it and transport the compressed data to a central node. The latter processes the received data to derive an estimate of the phenomenon's parameters. The corruption level of the sensed data is assumed to be dependent on the distance between the sensor and the point phenomenon. We also account for location dependent correlations between observation noise components. We develop computationally efficient algorithms for determining the specific set of sensors to be activated, and the level of compression to be applied by each selected sensor, under energy and communications capacity constraints. The aim is to achieve a sufficiently low reproduction distortion level. We demonstrate the performance behavior of our algorithms. We show that the activation of sensors that belong to a critical set of sensors tends to provide a distinct reduction in the distortion measure. In turn, the activation of additional sensors that are not members of this set may not lead to further distinct improvement. [ABSTRACT FROM AUTHOR]