Search results for: sensor pattern noise

Authors: Heruanda Alviana Giska Barabah, Hilda Rasnia Hapsari

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Acoustic phenomena create an acoustic interpretation condition that describes the characteristics of the environment. In urban areas, the tendency of heterogeneous and simultaneous human activity form a soundscape that is different from other regions, one of the characteristics of urban areas that developing the soundscape is the presence of vertical model houses or residential building. Activities both within the building and surrounding environment are able to make the soundscape with certain characteristics. The acoustics comfort of residential building becomes an important aspect, those demand lead the building features become more diverse. Initial steps in mapping acoustic conditions in a soundscape are important, this is the method to determine uncomfortable condition. Noise generated by road traffic, railway, and plane is an important consideration, especially for urban people, therefore the proper design of the building becomes very important as an effort to bring appropriate acoustics comfort. In this paper the authors developed noise mapping on the location of the residential building. Mapping done by taking some point referring to the noise source. The mapping result become the basis for modeling the acoustics wave interacted with the building model. Material selection is done based on literature study and modeling simulation using Insul by considering the absorption coefficient and Sound Transmission Class. The analysis of acoustics rays is ray tracing method using Comsol simulator software that can show the movement of acoustics rays and their interaction with a boundary. The result of this study can be used to consider boundary material in residential building as well as consideration for improving the acoustic quality in the acoustics zones that are formed.

Keywords: residential building, noise, absorption coefficient, sound transmission class, ray tracing

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Authors: Jigg Pelayo, Ricardo Villar

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Leaning on the development of aerial laser scanning in the Philippine geospatial industry, researches about remote sensing and machine vision technology became a trend. Object detection via template matching is one of its application which characterized to be fast and in real time. The paper purposely attempts to provide application for robust pattern matching algorithm based on the normalized cross correlation (NCC) criterion function subjected in Object-based image analysis (OBIA) utilizing high-resolution aerial imagery and low density LiDAR data. The height information from laser scanning provides effective partitioning order, thus improving the hierarchal class feature pattern which allows to skip unnecessary calculation. Since detection is executed in the object-oriented platform, mathematical morphology and multi-level filter algorithms were established to effectively avoid the influence of noise, small distortion and fluctuating image saturation that affect the rate of recognition of features. Furthermore, the scheme is evaluated to recognized the performance in different situations and inspect the computational complexities of the algorithms. Its effectiveness is demonstrated in areas of Misamis Oriental province, achieving an overall accuracy of 91% above. Also, the garnered results portray the potential and efficiency of the implemented algorithm under different lighting conditions.

Keywords: algorithm, LiDAR, object recognition, OBIA

Procedia PDF Downloads 242

Authors: Hiesik Kim, Yong-Beom Kim, Jaheon Gu

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Internet of Things (IoT) applications are widely serviced and spread worldwide. Local wireless data transmission technique must be developed to rate up with some technique. Bluetooth wireless data communication is wireless technique is technique made by Special Inter Group (SIG) using the frequency range 2.4 GHz, and it is exploiting Frequency Hopping to avoid collision with a different device. To implement experiment, equipment for experiment transmitting measured data is made by using Arduino as open source hardware, gas sensor, and Bluetooth module and algorithm controlling transmission rate is demonstrated. Experiment controlling transmission rate also is progressed by developing Android application receiving measured data, and controlling this rate is available at the experiment result. It is important that in the future, improvement for communication algorithm be needed because a few error occurs when data is transferred or received.

Keywords: Arduino, Bluetooth, gas sensor, IoT, transmission

Procedia PDF Downloads 274

Authors: Ayadi Aya, Ghorbel Oussama, M. Obeid Abdulfattah, Abid Mohamed

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Nowadays, many wireless sensor networks have been distributed in the real world to collect valuable raw sensed data. The challenge is to extract high-level knowledge from this huge amount of data. However, the identification of outliers can lead to the discovery of useful and meaningful knowledge. In the field of wireless sensor networks, an outlier is defined as a measurement that deviates from the normal behavior of sensed data. Many detection techniques of outliers in WSNs have been extensively studied in the past decade and have focused on classic based algorithms. These techniques identify outlier in the real transaction dataset. This survey aims at providing a structured and comprehensive overview of the existing researches on classification based outlier detection techniques as applicable to WSNs. Thus, we have identified key hypotheses, which are used by these approaches to differentiate between normal and outlier behavior. In addition, this paper tries to provide an easier and a succinct understanding of the classification based techniques. Furthermore, we identified the advantages and disadvantages of different classification based techniques and we presented a comparative guide with useful paradigms for promoting outliers detection research in various WSN applications and suggested further opportunities for future research.

Keywords: bayesian networks, classification-based approaches, KPCA, neural networks, one-class SVM, outlier detection, wireless sensor networks

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Authors: Esther Van Andel, Stefanie C. Lange, Maarten M. J. Smulders, Han Zuilhof

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False outcomes of diagnostic tests are a major concern in medical health care. To improve the reliability of surface-based diagnostic tests, it is of crucial importance to diminish background signals that arise from the non-specific binding of biomolecules, a process called fouling. The aim is to create surfaces that repel all biomolecules except the molecule of interest. This can be achieved by incorporating antifouling protein repellent coatings in between the sensor surface and it’s recognition elements (e.g. antibodies, sugars, aptamers). Zwitterionic polymer brushes are considered excellent antifouling materials, however, to be able to bind the molecule of interest, the polymer brushes have to be functionalized and so far this was only achieved at the expense of either antifouling or binding capacity. To overcome this limitation, we combined both features into one single monomer: a zwitterionic sulfobetaine, ensuring antifouling capabilities, equipped with a clickable azide moiety which allows for further functionalization. By copolymerizing this monomer together with a standard sulfobetaine, the number of azides (and with that the number of recognition elements) can be tuned depending on the application. First, the clickable azido-monomer was synthesized and characterized, followed by copolymerizing this monomer to yield functionalizable antifouling brushes. The brushes were fully characterized using surface characterization techniques like XPS, contact angle measurements, G-ATR-FTIR and XRR. As a proof of principle, the brushes were subsequently functionalized with biotin via strain-promoted alkyne azide click reactions, which yielded a fully zwitterionic biotin-containing 3D-functionalized coating. The sensing capacity was evaluated by reflectometry using avidin and fibrinogen containing protein solutions. The surfaces showed excellent antifouling properties as illustrated by the complete absence of non-specific fibrinogen binding, while at the same time clear responses were seen for the specific binding of avidin. A great increase in signal-to-noise ratio was observed, even when the amount of functional groups was lowered to 1%, compared to traditional modification of sulfobetaine brushes that rely on a 2D-approach in which only the top-layer can be functionalized. This study was performed on stoichiometric silicon nitride surfaces for future microring resonator based assays, however, this methodology can be transferred to other biosensor platforms which are currently being investigated. The approach presented herein enables a highly efficient strategy for selective binding with retained antifouling properties for improved signal-to-noise ratios in binding assays. The number of recognition units can be adjusted to a specific need, e.g. depending on the size of the analyte to be bound, widening the scope of these functionalizable surface coatings.

Keywords: antifouling, signal-to-noise ratio, surface functionalization, zwitterionic polymer brushes

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Authors: M. Pramila Devi, N. V. N. Indra Kiran

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Control charts, predominantly in the form of X-bar chart, are important tools in statistical process control (SPC). They are useful in determining whether a process is behaving as intended or there are some unnatural causes of variation. A process is out of control if a point falls outside the control limits or a series of point’s exhibit an unnatural pattern. In this paper, a study is carried out on four training algorithms for CCPs recognition. For those algorithms optimal structure is identified and then they are studied for type I and type II errors for generalization without early stopping and with early stopping and the best one is proposed.

Keywords: control chart pattern recognition, neural network, backpropagation, generalization, early stopping

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Authors: Luo Jiaoyang, Yu Hongyang

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In this paper, we explore a method that can be used in the working scene of intelligent industrial robots to confirm the identity information of operators to ensure that the robot executes instructions in a sufficiently safe environment. This approach uses three information modalities, namely visible light, depth, and sound. We explored a variety of fusion modes for the three modalities and finally used the joint feature learning method to improve the performance of the model in the case of noise compared with the single-modal case, making the maximum noise in the experiment. It can also maintain an accuracy rate of more than 90%.

Keywords: multimodal, kinect, machine learning, distance image

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Authors: M. Shoukath Ali, Rajendra Prasad Singh

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Game Theory approaches and their application in improving the performance of Wireless Sensor Networks (WSNs) are discussed in this paper. The mathematical modeling and analysis of WSNs may have low success rate due to the complexity of topology, modeling, link quality, etc. However, Game Theory is a field, which can efficiently use to analyze the WSNs. Game Theory is related to applied mathematics that describes and analyzes interactive decision situations. Game theory has the ability to model independent, individual decision makers whose actions affect the surrounding decision makers. The outcome of complex interactions among rational entities can be predicted by a set of analytical tools. However, the rationality demands a stringent observance to a strategy based on measured of perceived results. Researchers are adopting game theory approaches to model and analyze leading wireless communication networking issues, which includes QoS, power control, resource sharing, etc.

Keywords: wireless sensor network, game theory, cooperative game theory, non-cooperative game theory

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Authors: A. Khan, H. Mahmood

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In Underwater Wireless Sensor Networks (UWSNs), sensor nodes close to water surface (final destination) are often preferred for selection as forwarders. However, their frequent selection makes them depleted of their limited battery power. In consequence, these nodes die during early stage of network operation and create energy holes where forwarders are not available for packets forwarding. These holes severely affect network throughput. As a result, system performance significantly degrades. In this paper, a routing protocol is proposed to avoid energy holes during packets forwarding. The proposed protocol does not require the conventional position information (localization) of holes to avoid them. Localization is cumbersome; energy is inefficient and difficult to achieve in underwater environment where sensor nodes change their positions with water currents. Forwarders with the lowest water pressure level and the maximum number of neighbors are preferred to forward packets. These two parameters together minimize packet drop by following the paths where maximum forwarders are available. To avoid interference along the paths with the maximum forwarders, a packet holding time is defined for each forwarder. Simulation results reveal superior performance of the proposed scheme than the counterpart technique.

Keywords: energy holes, interference, routing, underwater

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Authors: Muhammad Zikril Hakim Md. Azizi, Norhafizan Ahmad, Raja Ariffin Raja Ghazilla

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Postural stability, attention level of the archer and particularly the vibrations of the bow itself plays a prominent role in determining the athletes performance. Many techniques and systems had been developing to monitor the parameters of the archers during training. In Malaysia, archery coaches tend to use non-scientific ways that they are familiar with, to evaluate archer performance. An approach that provides more affordable yet accurate systems to the masses and relatively easy system deployment procedure need to be proposed. Hence, this project will address to fulfil the needs. Three area of the archer parameter were included for data monitoring sensors. Attention level can be measured using EEG sensor, centre of mass linked to the postural stability can be measured by foot pressure sensor, and the bow vibrations in three axis will be relayed by the vibrations sensors placed directly on the bow using wireless sensors. Arduino based microcontroller used to relay all the data back to the interfacing systems. Interface systems will be using Python language and C++ framework for user interface and hardware interfacing systems. All sensor data can be observed in real time using the in-house applications, and each sessions can be saved to common files so that coach and the team can have a further discussion and comparisons.

Keywords: archery, graphical user interface, microcontroller, wireless sensor, monitoring system

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Authors: Saleh Gorji, Sahil Gulati, Ana Pakzad

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Continuous electron diffraction tomography, also known as microcrystal electron diffraction (MicroED) or three-dimensional electron diffraction (3DED), is a powerful technique, which in combination with cryo-electron microscopy (cryo-ED), can provide atomic-scale 3D information about the crystal structure and composition of different classes of crystalline materials such as proteins, peptides, and small molecules. Unlike the well-established X-ray crystallography method, 3DED does not require large single crystals and can collect accurate electron diffraction data from crystals as small as 50 – 100 nm. This is a critical advantage as growing larger crystals, as required by X-ray crystallography methods, is often very difficult, time-consuming, and expensive. In most cases, specimens studied via 3DED method are electron beam sensitive, which means there is a limitation on the maximum amount of electron dose one can use to collect the required data for a high-resolution structure determination. Therefore, collecting data using a conventional scintillator-based fiber coupled camera brings additional challenges. This is because of the inherent noise introduced during the electron-to-photon conversion in the scintillator and transfer of light via the fibers to the sensor, which results in a poor signal-to-noise ratio and requires a relatively higher and commonly specimen-damaging electron dose rates, especially for protein crystals. As in other cryo-EM techniques, damage to the specimen can be mitigated if a direct detection camera is used which provides a high signal-to-noise ratio at low electron doses. In this work, we have used two classes of such detectors from Gatan, namely the K3® camera (a monolithic active pixel sensor) and Stela™ (that utilizes DECTRIS hybrid-pixel technology), to address this problem. The K3 is an electron counting detector optimized for low-dose applications (like structural biology cryo-EM), and Stela is also a counting electron detector but optimized for diffraction applications with high speed and high dynamic range. Lastly, data collection workflows, including crystal screening, microscope optics setup (for imaging and diffraction), stage height adjustment at each crystal position, and tomogram acquisition, can be one of the other challenges of the 3DED technique. Traditionally this has been all done manually or in a partly automated fashion using open-source software and scripting, requiring long hours on the microscope (extra cost) and extensive user interaction with the system. We have recently introduced Latitude® D in DigitalMicrograph® software, which is compatible with all pre- and post-energy-filter Gatan cameras and enables 3DED data acquisition in an automated and optimized fashion. Higher quality 3DED data enables structure determination with higher confidence, while automated workflows allow these to be completed considerably faster than before. Using multiple examples, this work will demonstrate how to direct detection electron counting cameras enhance 3DED results (3 to better than 1 Angstrom) for protein and small molecule structure determination. We will also show how Latitude D software facilitates collecting such data in an integrated and fully automated user interface.

Keywords: continuous electron diffraction tomography, direct detection, diffraction, Latitude D, Digitalmicrograph, proteins, small molecules

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Authors: Yulong Wang, Yuan Yan Tang, Cuiming Zou, Lina Yang

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This paper presents a novel sparse representation method for robust pattern classification. Generalized orthogonal matching pursuit (GOMP) is a recently proposed efficient sparse representation technique. However, GOMP adopts the mean square error (MSE) criterion and assign the same weights to all measurements, including both severely and slightly corrupted ones. To reduce the limitation, we propose an information-theoretic GOMP (ITGOMP) method by exploiting the correntropy induced metric. The results show that ITGOMP can adaptively assign small weights on severely contaminated measurements and large weights on clean ones, respectively. An ITGOMP based classifier is further developed for robust pattern classification. The experiments on public real datasets demonstrate the efficacy of the proposed approach.

Keywords: correntropy induced metric, matching pursuit, pattern classification, sparse representation

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Authors: Adeniyi Onasanya, Maher Elshakankiri

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In recent years, the Internet of Things (IoT) has constituted a driving force of modern technological advancement, and it has become increasingly common as its impacts are seen in a variety of application domains, including healthcare. IoT is characterized by the interconnectivity of smart sensors, objects, devices, data, and applications. With the unprecedented use of IoT in industrial, commercial and domestic, it becomes very imperative to harness the benefits and functionalities associated with the IoT technology in (re)assessing the provision and positioning of healthcare to ensure efficient and improved healthcare delivery. In this research, we are focusing on two important services in healthcare systems, which are cancer care services and business analytics/cloud services. These services incorporate the implementation of an IoT that provides solution and framework for analyzing health data gathered from IoT through various sensor networks and other smart devices in order to improve healthcare delivery and to help health care providers in their decision-making process for enhanced and efficient cancer treatment. In addition, we discuss the wireless sensor network (WSN), WSN routing and data transmission in the healthcare environment. Finally, some operational challenges and security issues with IoT-based healthcare system are discussed.

Keywords: IoT, smart health care system, business analytics, (wireless) sensor network, cancer care services, cloud services

Procedia PDF Downloads 173

Authors: Joo-Hack Lee, Jin-Seung Choi, Dong-Won Kang, Jeong-Woo Seo, Ju-Young Kim, Dae-Hyeok Kim, Seung-Tae Yang, Gye-Rae Tack

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For cycling, the analysis of the pedal force is one of the important factors in the study of exercise ability assessment and overuse injuries. In past studies, a two-axis measurement sensor was used at the sagittal plane to measure the force only in the anterior, posterior, and vertical directions and to analyze the loss of force and the injury on the frontal plane due to the forces in the right and left directions. In this study, which is a basic study on diverse analyses of the pedal force that consider the forces on the sagittal plane and the frontal plane, a three-axis pedal force measurement sensor was developed to measure the anterior-posterior (Fx), medio-lateral (Fz), and vertical (Fy) forces. The sensor was fabricated with a size and shape similar to those of the general flat pedal, and had a 550g weight that allowed smooth pedaling. Its measurement range was ±1000 N for Fx and Fz and ±2000 N for Fy, and its non-linearity, hysteresis, and repeatability were approximately 0.5%. The data were sampled at 1000 Hz using a signal collector. To use the developed sensor, the pedaling efficiency (index of efficiency, IE) and the range of left and right (medio-lateral, ML) forces were measured with two seat heights (low and high). The results of the measurement showed that the IE was higher and the force range in the ML direction was lower with the high position than with the low position. The developed measurement sensor and its application results will be useful in understanding and explaining the complicated pedaling technique, and will enable diverse kinematic analyses of the pedal force on the sagittal plane and the frontal plane.

Keywords: cycling, pedal force, index of effectiveness, measuring

Procedia PDF Downloads 656

Authors: Hiesik Kim, YongBeum Kim

Abstract:

Internet of Things (IoT) applications are widely serviced and spread worldwide. Local wireless data transmission technique must be developed to speed up with some technique. Bluetooth wireless data communication is wireless technique is technique made by Special Inter Group(SIG) using the frequency range 2.4 GHz, and it is exploiting Frequency Hopping to avoid collision with different device. To implement experiment, equipment for experiment transmitting measured data is made by using Arduino as Open source hardware, Gas sensor, and Bluetooth Module and algorithm controlling transmission speed is demonstrated. Experiment controlling transmission speed also is progressed by developing Android Application receiving measured data, and controlling this speed is available at the experiment result. it is important that in the future, improvement for communication algorithm be needed because few error occurs when data is transferred or received.

Keywords: Arduino, Bluetooth, gas sensor, internet of things, transmission Speed

Procedia PDF Downloads 480

Authors: Mattias Bergstrom

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Significance of the Study: This research will provide new insights into the risks with digital embedded infrastructure. Through this research, we will analyze each risk and its potential negation strategies, especially for AI and autonomous automation. Moreover, the analysis that is presented in this paper will convey valuable information for future research that can create more stable, secure, and efficient autonomous systems. To learn and understand the risks, a large IoT system was envisioned, and risks with hardware, tampering, and cyberattacks were collected, researched, and evaluated to create a comprehensive understanding of the potential risks. Potential solutions have then been evaluated on an open source IoT hardware setup. This list shows the identified passive and active risks evaluated in the research. Passive Risks: (1) Hardware failures- Critical Systems relying on high rate data and data quality are growing; SCADA systems for infrastructure are good examples of such systems. (2) Hardware delivers erroneous data- Sensors break, and when they do so, they don’t always go silent; they can keep going, just that the data they deliver is garbage, and if that data is not filtered out, it becomes disruptive noise in the system. (3) Bad Hardware injection- Erroneous generated sensor data can be pumped into a system by malicious actors with the intent to create disruptive noise in critical systems. (4) Data gravity- The weight of the data collected will affect Data-Mobility. (5) Cost inhibitors- Running services that need huge centralized computing is cost inhibiting. Large complex AI can be extremely expensive to run. Active Risks: Denial of Service- It is one of the most simple attacks, where an attacker just overloads the system with bogus requests so that valid requests disappear in the noise. Malware- Malware can be anything from simple viruses to complex botnets created with specific goals, where the creator is stealing computer power and bandwidth from you to attack someone else. Ransomware- It is a kind of malware, but it is so different in its implementation that it is worth its own mention. The goal with these pieces of software is to encrypt your system so that it can only be unlocked with a key that is held for ransom. DNS spoofing- By spoofing DNS calls, valid requests and data dumps can be sent to bad destinations, where the data can be extracted for extortion or to corrupt and re-inject into a running system creating a data echo noise loop. After testing multiple potential solutions. We found that the most prominent solution to these risks was to use a Peer 2 Peer consensus algorithm over a blockchain to validate the data and behavior of the devices (sensors, storage, and computing) in the system. By the devices autonomously policing themselves for deviant behavior, all risks listed above can be negated. In conclusion, an Internet middleware that provides these features would be an easy and secure solution to any future autonomous IoT deployments. As it provides separation from the open Internet, at the same time, it is accessible over the blockchain keys.

Keywords: IoT, security, infrastructure, SCADA, blockchain, AI

Procedia PDF Downloads 103

Authors: Neha Bhattacharyya, Soumendra Singh, Amrita Banerjee, Ria Ghosh, Oindrila Sinha, Nairit Das, Rajkumar Gayen, Somya Subhra Pal, Sahely Ganguly, Tanmoy Dasgupta, Tanusree Dasgupta, Pulak Mondal, Aniruddha Adhikari, Sharmila Sarkar, Debasish Bhattacharyya, Asim Kumar Mallick, Om Prakash Singh, Samir Kumar Pal

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Background: We aim to develop an integrated device comprised of single-probe EEG and CCD-based motion sensors for a more objective measure of Attention-deficit Hyperactivity Disorder (ADHD). While the integrated device (MAHD) relies on the EEG signal (spectral density of beta wave) for the assessment of attention during a given structured task (painting three segments of a circle using three different colors, namely red, green and blue), the CCD sensor depicts movement pattern of the subjects engaged in a continuous performance task (CPT). A statistical analysis of the attention and movement patterns was performed, and the accuracy of the completed tasks was analysed using indigenously developed software. The device with the embedded software, called MAHD, is intended to improve certainty with criterion E (i.e. whether symptoms are better explained by another condition). Methods: We have used the EEG signal from a single-channel dry sensor placed on the frontal lobe of the head of the subjects (3-5 years old pre-schoolers). During the painting of three segments of a circle using three distinct colors (red, green, and blue), absolute power for delta and beta EEG waves from the subjects are found to be correlated with relaxation and attention/cognitive load conditions. While the relaxation condition of the subject hints at hyperactivity, a more direct CCD-based motion sensor is used to track the physical movement of the subject engaged in a continuous performance task (CPT) i.e., separation of the various colored balls from one table to another. We have used our indigenously developed software for the statistical analysis to derive a scale for the objective assessment of ADHD. We have also compared our scale with clinical ADHD evaluation. Results: In a limited clinical trial with preliminary statistical analysis, we have found a significant correlation between the objective assessment of the ADHD subjects with that of the clinician’s conventional evaluation. Conclusion: MAHD, the integrated device, is supposed to be an auxiliary tool to improve the accuracy of ADHD diagnosis by supporting greater criterion E certainty.

Keywords: ADHD, CPT, EEG signal, motion sensor, psychometric test

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Authors: El Korchi Ayoub, Cherif Raef

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Interior noise in vehicles is an essential factor affecting occupant comfort. Over recent decades, much work has been done to develop simulation tools for vehicle NVH. At the medium high-frequency range, the statistical energy analysis method (SEA) shows significant effectiveness in predicting noise and vibration responses of mechanical systems. In this paper, the evaluation of the sound pressure level (SPL) inside an automobile cabin has been performed numerically using the statistical energy analysis (SEA) method. A test car cabin was performed using a monopole source as a sound source. The decay rate method was employed to obtain the damping loss factor (DLF) of each subsystem of the developed SEA model. These parameters were then used to predict the sound pressure level in the interior cabin. The results show satisfactory agreement with the directly measured SPL. The developed SEA vehicle model can be used in early design phases and allows the engineer to identify sources contributing to the total noise and transmission paths.

Keywords: SEA, SPL, DLF, NVH

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Authors: Lei Qi, Rongxin Yan, Lichen Sun

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With the increasing of human space activities, the number of space debris has increased dramatically, and the possibility that spacecrafts on orbit are impacted by space debris is growing. A method is of the vital significance to real-time detect and assess spacecraft damage, determine of gas leak accurately, guarantee the life safety of the astronaut effectively. In this paper, acoustic sensor array is used to detect the acoustic signal which emits from the damage of the spacecraft on orbit. Then, we apply the time difference of arrival and beam forming algorithm to locate the damage and leakage. Finally, the extent of the spacecraft damage is evaluated according to the nonlinear ultrasonic method. The result shows that this method can detect the debris impact and the structural damage, locate the damage position, and identify the damage degree effectively. This method can meet the needs of structural damage detection for the spacecraft in-orbit.

Keywords: acoustic sensor array, spacecraft, damage assessment, leakage location

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Authors: Le Zhao, Alain Nogaret

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We have built universal Central Pattern Generator (CPG) hardware by interconnecting Hodgkin-Huxley neurons with reciprocally inhibitory synapses. We investigate the dynamics of neuron oscillations as a function of the time delay between current steps applied to individual neurons. We demonstrate stimulus dependent switching between spiking polyrhythms and map the phase portraits of the neuron oscillations to reveal the basins of attraction of the system. We experimentally study the dependence of the attraction basins on the network parameters: the neuron response time and the strength of inhibitory connections.

Keywords: central pattern generator, winnerless competition principle, artificial neural networks, synapses

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Authors: C. D. Papanikolaou, V. A. Giouvanis, E. A. Karatasiou, D. S. Dimakas, M. A. Sakellariou-Makrantonaki

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Irrigation is one of the most important cultivation practices for each crop, especially in areas where rainfall is enough to cover the crop water needs. In such areas, the farmers must irrigate in order to achieve high economical results. The precise irrigation scheduling contributes to irrigation water saving and thus a valuable natural resource is protected. Under this point of view, in the experimental field of the Laboratory of Agricultural Hydraulics of the University of Thessaly, a research was conducted during the growing season of 2012 in order to evaluate the growth, seed and oil production of sunflower as well as the water saving, by applying different methods of irrigation scheduling. Three treatments in four replications were organized. These were: a) surface drip irrigation where the irrigation scheduling based on the Penman-Monteith (PM) method (control); b) surface drip irrigation where the irrigation scheduling based on a soil moisture sensor (SMS); and c) surface drip irrigation, where the irrigation scheduling based on a soil potential sensor (WM).

Keywords: irrigation, energy production, soil moisture sensor, sunflower, water saving

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Authors: Nicholas V. Scott, Jack McCarthy

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Military, law enforcement, and counter terrorism organizations are often tasked with target detection and image characterization of scenes containing explosive materials in various types of environments where light scattering intensity is high. Mitigation of this photonic noise using classical digital filtration and signal processing can be difficult. This is partially due to the lack of robust image processing methods for photonic noise removal, which strongly influence high resolution target detection and machine learning-based pattern recognition. Such analysis is crucial to the delivery of reliable intelligence. Polarization filters are a possible method for ambient glare reduction by allowing only certain modes of the electromagnetic field to be captured, providing strong scene contrast. An experiment was carried out utilizing a polarization lens attached to a hyperspectral imagery camera for the purpose of exploring the degree to which an imaged polarized scene of potassium, phosphorus, and nitrogen mixture allows for improved target detection and image segmentation. Preliminary imagery results based on the application of machine learning algorithms, including competitive leaky learning and distance metric analysis, to polarized hyperspectral imagery, suggest that polarization filters provide a slight advantage in image segmentation. The results of this work have implications for understanding the presence of explosive material in dry, desert areas where reflective glare is a significant impediment to scene characterization.

Keywords: explosive material, hyperspectral imagery, image segmentation, machine learning, polarization

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

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Authors: P. Sam Vimal Rajkumar, K. Priyanga

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Acoustics is the scientific study of sound which includes the effect of reflection, refraction, absorption, diffraction and interference. Sound can be considered as a wave phenomenon. A sound wave is a longitudinal wave where particles of the medium are temporarily displaced in a direction parallel to energy transport and then return to their original position. The vibration in a medium produces alternating waves of relatively dense and sparse particles –compression and rarefaction respectively. The resultant variation to normal ambient pressure is translated by the ear and perceived as sound. Today much importance is given to the acoustical environment. The noise sources are increased day by day and annoying level is strongly violated in different locations by traffic, sound systems, and industries. There is simple evidence showing that the high noise levels cause sleep disturbance, hearing loss, decrease in productivity, learning disability, lower scholastic performance and increase in stress related hormones and blood pressure. Therefore, achieving a pleasing and noise free environment is one of the endeavours of many a research groups. This can be obtained by using various techniques. One such technique is by using suitable materials with good sound absorbing properties. The conventionally used materials that possess sound absorbing properties are rock wool or glass wool. In this work, an attempt is made to use synthetic material in both fibrous and sheet form and use it for manufacturing of non-woven for sound absorption.

Keywords: acoustics, fibre, non-woven, noise, sound absorption properties, sound absorption coefficient

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Authors: Carlos H. Cuadra, Nobuhiro Shimoi

Abstract:

Application of piezoelectric sensors to detect structural damage due to seismic action on building structures is investigated. Plate-type piezoelectric sensor was developed and proposed for this task. A film-type piezoelectric sheet was attached on a steel plate and covered by a layer of glass. A special glue is used to fix the glass. This glue is a silicone that requires the application of ultraviolet rays for its hardening. Then, the steel plate was set up at a steel column-beam joint of a test specimen that was subjected to bending moment when test specimen is subjected to monotonic load and cyclic load. The structural behavior of test specimen during cyclic loading was verified using a finite element model, and it was found good agreement between both results on load-displacement characteristics. The cross section of steel elements (beam and column) is a box section of 100 mm×100 mm with a thin of 6 mm. This steel section is specified by the Japanese Industrial Standards as carbon steel square tube for general structure (STKR400). The column and beam elements are jointed perpendicularly using a fillet welding. The resulting test specimen has a T shape. When large deformation occurs the glass plate of the sensor device cracks and at that instant, the piezoelectric material emits a voltage signal which would be the indicator of a certain level of deformation or damage. Applicability of this piezoelectric sensor to detect structural damages was verified; however, additional analysis and experimental tests are required to establish standard parameters of the sensor system.

Keywords: piezoelectric sensor, static cyclic test, steel structure, seismic damages

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Authors: Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, José Anderson Rodrigues de Souza, Jeronimo Silva Rocha

Abstract:

Propagation in radio frequency is a constant concern in the application of Wireless Sensor Networks (WSN), the behavior of an environment determines how good the quality of signal reception. The objective of this paper is to analyze the behavior of a WSN in an environment for agriculture where environmental variables are present and correlate the capture of values received signal strength (RSSI) with a propagation model.

Keywords: propagation, WSN, agriculture, quality

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Authors: Bashiru Olayinka Adisa, Najeem Lateef

Abstract:

The integrated knowledge in the application of mechanical engineering, microprocessor and electronic sensor technologies is becoming the basic skill of a modern engineer in machinery based processes. To meet this objective, we have developed a cross-disciplinary industrial training to teach essential hard technical and soft project skills to the mechanical engineering students in mid-curriculum. Ten groups of students were selected to participate in a 150 hour program. The students were required to design and build a robot with ability to follow tracks and pick/place target blocks in specific locations. The students were trained to integrate the knowledge of computer aid design, electronics, sensor theories and motor technology to fabricate a workable robot as a major outcome of this course. On completion of the project, students competed for top robot honors by demonstrating their robots' movements and performance in pick/place to a panel of judges.

Keywords: electronics, sensor theories and motor, robot, technology

Procedia PDF Downloads 276

Authors: Jae-Neung Lee, Myung-Won Lee, Jung-Su Han, Keun-Chang Kwak

Abstract:

The paper established DB on the basis of five sailing essentials in the real yachting environment. It obtained the yacht condition (tilt, speed and course), surrounding circumstances (wind direction and speed) and user motion. Gopro camera for image processing was used to recognize the user motion and tilt sensor was employed to see the yacht balance. In addition, GPS for course, wind speed and direction sensor and marked suit were employed.

Keywords: DB consturuction, yacht, five essentials of sailing, marker, Gps

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Authors: Ahmad Akrad, Rabia Sehab, Fadi Alyoussef

Abstract:

Nowadays, induction machines are widely used in industry thankful to their advantages comparing to other technologies. Indeed, there is a big demand because of their reliability, robustness and cost. The objective of this paper is to deal with diagnosis, detection and isolation of faults in a three-phase induction machine. Among the faults, Inter-turn short-circuit fault (ITSC), current sensors fault and single-phase open circuit fault are selected to deal with. However, a fault detection method is suggested using residual errors generated by the root mean square (RMS) of phase currents. The application of this method is based on an asymmetric nonlinear model of Induction Machine considering the winding fault of the three axes frame state space. In addition, current sensor redundancy and sensor fault detection and isolation (FDI) are adopted to ensure safety operation of induction machine drive. Finally, a validation is carried out by simulation in healthy and faulty operation modes to show the benefit of the proposed method to detect and to locate with, a high reliability, the three types of faults.

Keywords: induction machine, asymmetric nonlinear model, fault diagnosis, inter-turn short-circuit fault, root mean square, current sensor fault, fault detection and isolation

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Authors: Nipin Kohli, Ravi Chand Singh

Abstract:

Diabetes mellitus is a serious illness and can be life-threatening if left untreated. Acetone present in the exhaled breath of a diabetic person is a biomarker of patients suffering from diabetes mellitus and is higher than its usual concentration present in the breath of healthy people. In the present work, a portable gas sensor system based on chromium oxide (Cr₂O₃) nanoparticles has been developed that can analyze diabetic patient’s breath. Undoped and indium (In) doped Cr₂O₃ nanoparticles were synthesized by a chemical route and characterized by X-ray diffraction, scanning electron microscopy, Raman spectroscopy, UV-visible spectroscopy, and photoluminescence spectroscopy for their structural, morphological and optical properties. Thick film gas sensors were fabricated out of synthesized samples. To diagnose diabetes, the sensors’ response to low concentrations of acetone was measured, and it was found that the addition of indium dramatically enhances the acetone gas sensing response. Moreover, the fabricated sensors were highly stable, reproducible and resistant to humidity. Enhancement of sensor response of doped sensors towards acetone can be ascribed to increase in defects due to addition of a dopant, and it was found that in-doped Cr₂O₃ sensors are more useful for analysis of breath of diabetic patients.

Keywords: Diabetes mellitus, nanoparticles, raman spectroscopy, sensor

Procedia PDF Downloads 139