Search results for: network devices

Authors: Parisa Mansour

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Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

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Authors: Hiba Hamdi, Thomas Corpetti, Laure Roupioz, Xavier Briottet

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Air temperatures are generally higher in cities than in their rural surroundings. The overheating of cities is a direct consequence of increasing urbanization, characterized by the artificial filling of soils, the release of anthropogenic heat, and the complexity of urban geometry. This phenomenon, referred to as urban heat island (UHI), is more prevalent during heat waves, which have increased in frequency and intensity in recent years. In the context of global warming and urban population growth, helping urban planners implement UHI mitigation and adaptation strategies is critical. In practice, the study of UHI requires air temperature information at the street canyon level, which is difficult to obtain. Many urban air temperature simulation models have been proposed (mostly based on physics or statistics), all of which require a variety of input parameters related to urban morphology, land use, material properties, or meteorological conditions. In this paper, we build and evaluate a neural network model based on Urban Weather Generator (UWG) model simulations and data from meteorological stations that simulate air temperature over Toulouse, France, on days favourable to UHI.

Keywords: air temperature, neural network model, urban heat island, urban weather generator

Procedia PDF Downloads 91

Authors: Weeradej Cheewapattananuwong, Keeree Srivichian, Godchamon Somchai, Wasin Phusanong, Nontawat Yoddamnern

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Natural rubber used for traffic devices in Thailand has been developed and researched for several years. When compared with Dry Rubber Content (DRC), the quality of Rib Smoked Sheet (RSS) is better. However, the cost of admixtures, especially CaCO₃ and sulphur, is higher than the cost of RSS itself. In this research, Flexible Guideposts and Rubber Fender Barriers (RFB) are taken into consideration. In case of flexible guideposts, the materials used are both RSS and DRC60%, but for RFB, only RSS is used due to the controlled performance tests. The objective of flexible guideposts and RFB is to decrease a number of accidents, fatal rates, and serious injuries. Functions of both devices are to save road users and vehicles as well as to absorb impact forces from vehicles so as to decrease of serious road accidents. This leads to the mitigation methods to remedy the injury of motorists, form severity to moderate one. The solution is to find the best practice of traffic devices using natural rubber under the engineering concepts. In addition, the performances of materials, such as tensile strength and durability, are calculated for the modulus of elasticity and properties. In the laboratory, the simulation of crashes, finite element of materials, LRFD, and concrete technology methods are taken into account. After calculation, the trials' compositions of materials are mixed and tested in the laboratory. The tensile test, compressive test, and weathering or durability test are followed and based on ASTM. Furthermore, the Cycle-Repetition Test of Flexible Guideposts will be taken into consideration. The final decision is to fabricate all materials and have a real test section in the field. In RFB test, there will be 13 crash tests, 7 Pickup Truck tests, and 6 Motorcycle Tests. The test of vehicular crashes happens for the first time in Thailand, applying the trial and error methods; for example, the road crash test under the standard of NCHRP-TL3 (100 kph) is changed to the MASH 2016. This is owing to the fact that MASH 2016 is better than NCHRP in terms of speed, types, and weight of vehicles and the angle of crash. In the processes of MASH, Test Level 6 (TL-6), which is composed of 2,270 kg Pickup Truck, 100 kph, and 25 degree of crash-angle is selected. The final test for real crash will be done, and the whole system will be evaluated again in Korea. The researchers hope that the number of road accidents will decrease, and Thailand will be no more in the top tenth ranking of road accidents in the world.

Keywords: LRFD, load and resistance factor design, ASTM, american society for testing and materials, NCHRP, national cooperation highway research program, MASH, manual for assessing safety hardware

Procedia PDF Downloads 128

Authors: Chryssa Thermolia, Ekaterini S. Bei, Stelios Sotiriadis, Kostas Stravoskoufos, Euripides G. M. Petrakis

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Moving into a new era of healthcare, new tools and devices are developed to extend and improve health services, such as remote patient monitoring and risk prevention. In this concept, Internet of Things (IoT) and Cloud Computing present great advantages by providing remote and efficient services, as well as cooperation between patients, clinicians, researchers and other health professionals. This paper focuses on patients suffering from bipolar disorder, a brain disorder that belongs to a group of conditions called effective disorders, which is characterized by great mood swings.We exploit the advantages of Semantic Web and Cloud Technologies to develop a patient monitoring system to support clinicians. Based on intelligently filtering of evidence-knowledge and individual-specific information we aim to provide treatment notifications and recommended function tests at appropriate times or concluding into alerts for serious mood changes and patient’s non-response to treatment. We propose an architecture, as the back-end part of a cloud platform for IoT, intertwining intelligence devices with patients’ daily routine and clinicians’ support.

Keywords: bipolar disorder, intelligent systems patient monitoring, semantic web technologies, healthcare

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Authors: Yichao Ma, Chengsiong Chin, Wailok Woo

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Since the last decade, there has been a rapid growth in digital multimedia, such as high-resolution media files and three-dimentional movies. Hence, there is a need for large digital storage such as Hard Disk Drive (HDD). As such, users expect to have a quieter HDD in their laptop. In this paper, a jury test has been conducted on a group of 34 people where 17 of them are students who is the potential consumer, and the remaining are engineers who know the HDD. A total 13 HDD sound samples have been selected from over hundred HDD noise recordings. These samples are selected based on an agreed subjective feeling. The samples are played to the participants using head acoustic playback system which enabled them to experience as similar as possible the same environment as have been recorded. Analysis has been conducted and the obtained results have indicated different group has different perception over the noises. Two neural network-based acoustic annoyance models are established based on back propagation neural network. Four psychoacoustic metrics, loudness, sharpness, roughness and fluctuation strength, are used as the input of the model, and the subjective evaluation results are taken as the output. The developed models are reasonably accurate in simulating both training and test samples.

Keywords: hdd noise, jury test, neural network model, psychoacoustic annoyance

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Authors: A. Shebani, C. Pislaru

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Wear of materials is an everyday experience and has been observed and studied for long time. The prediction of wear is a fundamental problem in the industrial field, mainly correlated to the planning of maintenance interventions and economy. Pin-on-disc test is the most common test which is used to study the wear behaviour. In this paper, the pin-on-disc (AEROTECH UNIDEX 11) is used for the investigation of the effects of normal load and hardness of material on the wear under dry and sliding conditions. In the pin-on-disc rig, two specimens were used; one, a pin which is made of steel with a tip, is positioned perpendicular to the disc, where the disc is made of aluminium. The pin wear and disc wear were measured by using the following instruments: The Talysurf instrument, a digital microscope, and the alicona instrument; where the Talysurf profilometer was used to measure the pin/disc wear scar depth, and the alicona was used to measure the volume loss for pin and disc. After that, the Archard model, American Society for Testing and Materials model (ASTM), and neural network model were used for pin/disc wear modelling and the simulation results are implemented by using the Matlab program. This paper focuses on how the alicona can be considered as a powerful tool for wear measurements and how the neural network is an effective algorithm for wear estimation.

Keywords: wear modelling, Archard Model, ASTM Model, Neural Networks Model, Pin-on-disc Test, Talysurf, digital microscope, Alicona

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Authors: Wafa' Slaibi Alsharafat

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Cloud computing is a modern approach in network environment. According to increased number of network users and online systems, there is a need to help these systems to be away from unauthorized resource access and detect any attempts for privacy contravention. For that purpose, Intrusion Detection System is an effective security mechanism to detect any attempts of attacks for cloud resources and their information. In this paper, Cloud Intrusion Detection System has been proposed in term of reducing or eliminating any attacks. This model concerns about achieving high detection rate after conducting a set of experiments using benchmarks dataset called KDD'99.

Keywords: IDS, cloud computing, anticipating classifier system, intrusion detection

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Authors: Hyeon Su Kim, Sungjin Park, Hae Ryung Chang, Hae Rim Jung, Young Zoo Ahn, Yon Hui Kim, Seungyoon Nam

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Ependymoma, one of the most common parenchymal spinal cord tumor, represents 3-6% of all CNS tumor. Especially intracranial ependymomas, which are more frequent in childhood, have a more poor prognosis and more malignant than spinal ependymomas. Although there are growing needs to understand pathogenesis, detailed molecular understanding of pathogenesis remains to be explored. A cancer cell is composed of complex signaling pathway networks, and identifying interaction between genes and/or proteins are crucial for understanding these pathways. Therefore, we explored each ependymoma in terms of differential expressed genes and signaling networks. We used Microsoft Excel™ to manipulate microarray data gathered from NCBI’s GEO Database. To analyze and visualize signaling network, we used web-based PATHOME algorithm and Cytoscape. We show HOX family and NEFL are down-regulated but SCL family is up-regulated in cerebrum and posterior fossa cancers over a spinal cancer, and JAK/STAT signaling pathway and Chemokine signaling pathway are significantly different in the both intracranial ependymoma comparing to spinal ependymoma. We are considering there may be an age-dependent mechanism under different histological pathogenesis. We annotated mutation data of each gene subsequently in order to find potential target genes.

Keywords: systems biology, ependymoma, deg, network analysis

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Authors: Bashir Abdu Muzakkari, Mohamad Afendee Mohamad, Mohd Fadzil Abdul Kadir

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Wireless Sensor Networks (WSNs) is an aggregation of several tiny, low-cost sensor nodes, spatially distributed to monitor physical or environmental status. WSN is constantly changing because of the rapid technological advancements in sensor elements such as radio, battery and operating systems. The Medium Access Control (MAC) protocols remain very vital in the WSN because of its role in coordinating communication amongst the sensors. Other than battery consumption, packet collision, network lifetime and latency are factors that largely depend on WSN MAC protocol and these factors have been widely treated in recent days. In this paper, we survey some latest proposed WSN Contention-based, Scheduling-based and Hybrid MAC protocols while presenting an examination, correlation of advantages and limitations of each protocol. Concentration is directed towards investigating the treatment of Quality of Service (QoS) performance metrics within these particular protocols. The result shows that majority of the protocols leaned towards energy conservation. We, therefore, believe that other performance metrics of guaranteed QoS such as latency, throughput, packet loss, network and bandwidth availability may play a critical role in the design of future MAC protocols for WSNs.

Keywords: WSN, QoS, energy consumption, MAC protocol

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Authors: Feng Wang, Shencheng Ni, Shuying Han, Shanhong You

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With the development of optical communication, optical performance monitoring (OPM) has received more and more attentions. Since optical signal-to-noise ratio (OSNR) is directly related to bit error rate (BER), it is one of the important parameters in optical networks. Recently, artificial neural network (ANN) has been greatly developed. ANN has strong learning and generalization ability. In this paper, a method of OSNR monitoring based on delay-tap sampling (DTS) and ANN has been proposed. DTS technique is used to extract the eigenvalues of the signal. Then, the eigenvalues are input into the ANN to realize the OSNR monitoring. The experiments of 10 Gb/s non-return-to-zero (NRZ) on–off keying (OOK), 20 Gb/s pulse amplitude modulation (PAM4) and 20 Gb/s return-to-zero (RZ) differential phase-shift keying (DPSK) systems are demonstrated for the OSNR monitoring based on the proposed method. The experimental results show that the range of OSNR monitoring is from 15 to 30 dB and the root-mean-square errors (RMSEs) for 10 Gb/s NRZ-OOK, 20 Gb/s PAM4 and 20 Gb/s RZ-DPSK systems are 0.36 dB, 0.45 dB and 0.48 dB respectively. The impact of chromatic dispersion (CD) on the accuracy of OSNR monitoring is also investigated in the three experimental systems mentioned above.

Keywords: artificial neural network (ANN), chromatic dispersion (CD), delay-tap sampling (DTS), optical signal-to-noise ratio (OSNR)

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Authors: Mehrnaz Aminifar

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The relation between textural parameters and casein network on release of aromatic compounds was investigated over 90-days of ripening. Low DE maltodextrin and WPI were used to modify the textural properties of low fat brined cheese. Hardness, brittleness and compaction of casein network were affected by addition of maltodextrin and WPI. Textural properties and aroma release from cheese texture were affected by interaction of WPI protein-cheese protein and maltodexterin-cheese protein.

Keywords: aroma release, brined cheese, maltodexterin, WPI

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Authors: Guezouli Larbi, Belkacem Soundes

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The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.

Keywords: text detection, CNN, PZM, deep learning

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Authors: Shunsuke Saito, Kazuho Yoshimoto, Shunichi Ohmori, Sirawadee Arunyanart

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In this paper, we suggest a mechanism of assessment that rater and Ratee (or employees) to convince. There are many problems exist in the personnel assessment. In particular, we were focusing on the three. (1) Raters are not sufficiently recognized assessment point. (2) Ratee are not convinced by the mechanism of assessment. (3) Raters (or Evaluators) and ratees have empathy. We suggest 1: Setting of "understanding of the assessment points." 2: Setting of "relative assessment ability." 3: Proposal of two-way assessment mechanism to solve these problems. As a prerequisite, it is assumed that there are multiple raters. This is because has been a growing importance of multi-faceted assessment. In this model, it determines the weight of each assessment point evaluators by the degree of understanding and assessment ability of raters and ratee. We used the ANP (Analytic Network Process) is a theory that an extension of the decision-making technique AHP (Analytic Hierarchy Process). ANP can be to address the problem of forming a network and assessment of Two-Way is possible. We apply this technique personnel assessment, the weights of rater of each point can be reasonably determined. We suggest absolute assessment for Two-Way assessment by ANP. We have verified that the consent of the two approaches is higher than conventional mechanism. Also, human resources consultant we got a comment about the application of the practice.

Keywords: personnel evaluation, pairwise comparison, analytic network process (ANP), two-ways

Procedia PDF Downloads 382

Authors: Chia-Chi Chang, Chuan-Bi Lin, Chia-Min Chan

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Most ZigBee sensor networks to date make use of nodes with limited processing, communication, and energy capabilities. Energy consumption is of great importance in wireless sensor applications as their nodes are commonly battery-driven. Once ZigBee nodes are deployed outdoors, limited power may make a sensor network useless before its purpose is complete. At present, there are two strategies for long node and network lifetime. The first strategy is saving energy as much as possible. The energy consumption will be minimized through switching the node from active mode to sleep mode and routing protocol with ultra-low energy consumption. The second strategy is to evaluate the energy consumption of sensor applications as accurately as possible. Erroneous energy model may render a ZigBee sensor network useless before changing batteries. In this paper, we present a ZigBee wireless sensor node with four key modules: a processing and radio unit, an energy harvesting unit, an energy storage unit, and a sensor unit. The processing unit uses CC2530 for controlling the sensor, carrying out routing protocol, and performing wireless communication with other nodes. The harvesting unit uses a 2W solar panel to provide lasting energy for the node. The storage unit consists of a rechargeable 1200 mAh Li-ion battery and a battery charger using a constant-current/constant-voltage algorithm. Our solution to extend node lifetime is implemented. Finally, a long-term sensor network test is used to exhibit the functionality of the solar powered system.

Keywords: ZigBee, Li-ion battery, solar panel, CC2530

Procedia PDF Downloads 374

Authors: Danladi Ali, Onah Festus Iloabuchi

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In this paper, GSM signal strength was measured in order to detect the type of the signal fading phenomenon using one-dimensional multilevel wavelet residual method and neural network clustering to determine the average GSM signal strength received in the study area. The wavelet residual method predicted that the GSM signal experienced slow fading and attenuated with MSE of 3.875dB. The neural network clustering revealed that mostly -75dB, -85dB and -95dB were received. This means that the signal strength received in the study is a weak signal.

Keywords: one-dimensional multilevel wavelets, path loss, GSM signal strength, propagation, urban environment

Procedia PDF Downloads 338

Authors: Rajan Vohra, Ravinder Singh Sawhney, Kunwar Partap Singh

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Electrical charge transport through two basic strands thymine and adenine of DNA have been investigated and analyzed using the jellium model approach. The FFT-2D computations have been performed for semi-empirical Extended Huckel Theory using atomistic tool kit to contemplate the charge transport metrics like current and conductance. The envisaged data is further evaluated in terms of transmission spectrum, HOMO-LUMO Gap and number of electrons. We have scrutinized the behavior of the devices in the range of -2V to 2V for a step size of 0.2V. We observe that both thymine and adenine can act as molecular devices when sandwiched between two gold probes. A prominent observation is a drop in HLGs of adenine and thymine when working as a device as compared to their intrinsic values and this is comparative more visible in case of adenine. The current in the thymine based device exhibit linear increase with voltage in spite of having low conductance. Further, the broader transmission peaks represent the strong coupling of electrodes to the scattering molecule (thymine). Moreover, the observed current in case of thymine is almost 3-4 times than that of observed for adenine. The NDR effect has been perceived in case of adenine based device for higher bias voltages and can be utilized in various future electronics applications.

Keywords: adenine, DNA, extended Huckel, thymine, transmission spectra

Procedia PDF Downloads 155

Authors: P. G. Kaviya, B. Muthupandian, R. Ganesan

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On-chip routers typically have buffers are used input or output ports for temporarily storing packets. The buffers are consuming some router area and power. The multiple queues in parallel as in VC router. While running a traffic trace, not all input ports have incoming packets needed to be transferred. Therefore large numbers of queues are empty and others are busy in the network. So the time consumption should be high for the high traffic. Therefore using a RoShaQ, minimize the buffer area and time The RoShaQ architecture was send the input packets are travel through the shared queues at low traffic. At high load traffic the input packets are bypasses the shared queues. So the power and area consumption was reduced. A parallel cross bar architecture is proposed in this project in order to reduce the power consumption. Also a new adaptive weighted routing algorithm for 8-port router architecture is proposed in order to decrease the delay of the network on chip router. The proposed system is simulated using Modelsim and synthesized using Xilinx Project Navigator.

Keywords: buffer, RoShaQ architecture, shared queue, VC router, weighted routing algorithm

Procedia PDF Downloads 542

Authors: Yasin Tadayonrad

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Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading /unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is loading/unloading capacity in each source/ destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming

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Authors: Virgil-Florin Duma, Dorin Demian

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Optical choppers are among the most common optomechatronic devices, utilized in numerous applications, from radiometry to telescopes and biomedical imaging. The classical configuration has a rotational disk with windows with linear margins. This research points out the laser signals that can be obtained with these classical choppers, as well as with another, novel, patented configuration, of eclipse choppers (i.e., with rotational disks with windows with non-linear margins, oriented outwards or inwards). Approximately triangular laser signals can be obtained with eclipse choppers, in contrast to the approximately sinusoidal – with classical devices. The main topic of this work refers to another, novel device, of choppers with shafts of different shapes and with slits of various profiles (patent pending). A significant improvement which can be obtained (with regard to disk choppers) refers to the chop frequencies of the laser signals. Thus, while 1 kHz is their typical limit for disk choppers, with choppers with shafts, a more than 20 times increase in the chop frequency can be obtained with choppers with shafts. Their transmission functions are also discussed, for different types of laser beams. Acknowledgments: This research is supported by the Romanian National Authority for Scientific Research, through the project PN-III-P2-2.1-BG-2016-0297.

Keywords: laser signals, laser systems, optical choppers, optomechatronics, transfer functions, eclipse choppers, choppers with shafts

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Authors: Mohammad Reza Rahimi Khoygani, Reza Ghasemi

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In this paper, designing direct adaptive neural controller is applied for a class of a nonlinear pendulum dynamic system. The radial basis function (RBF) is used for the Neural network (NN). The adaptive neural controller is robust in presence of external and internal uncertainties. Both the effectiveness of the controller and robustness against disturbances are the merits of this paper. The promising performance of the proposed controllers investigates in simulation results.

Keywords: adaptive control, pendulum dynamical system, nonlinear control, adaptive neural controller, nonlinear dynamical, neural network, RBF, driven pendulum, position control

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Authors: Maxime Moreau, Silvère Baron, Jean-Marc Lobaccaro, Karine Charlet, Sébastien Menecier, Frédéric Perisse

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Cold Atmospheric Plasma (CAP) is an ionized gas generated at atmospheric pressure with the temperature of heavy particles (molecules, ions, atoms) close to the room temperature. Recent studies have shown that both in-vitro and in-vivo plasma exposition to many cancer cell lines are efficient to induce the apoptotic way of cell death. In some other works, normal cell lines seem to be less impacted by plasma than cancer cell lines. This is called selectivity of plasma. It is highly likely that the generated RNOS (Reactive Nitrogen Oxygen Species) in the plasma jet, but also in the medium, play a key-role in this selectivity. In this study, two CAP devices will be compared to electrical power, chemical species composition and their efficiency to kill cancer cells. A particular focus on the action of hydrogen peroxide will be made. The experiments will take place as described next for both devices: electrical and spectroscopic characterization for different voltages, plasma treatment of normal and cancer cells to compare the CAP efficiency between cell lines and to show that death is induced by an oxidative stress. To enlighten the importance of hydrogen peroxide, an inhibitor of H2O2 will be added in cell culture medium before treatment and a comparison will be made between the results of cell viability in this case and those from a simple plasma exposition. Besides, H2O2 production will be measured by only treating medium with plasma. Cell lines will also be exposed to different concentrations of hydrogen peroxide in order to characterize the cytotoxic threshold for cells and to make a comparison with the quantity of H2O2 produced by CAP devices. Finally, the activity of catalase for different cell lines will be quantified. This enzyme is an important antioxidant agent against hydrogen peroxide. A correlation between cells response to plasma exposition and this activity could be a strong argument in favor of the predominant role of H2O2 to explain the selectivity of plasma cancer treatment by cold atmospheric plasma.

Keywords: cold atmospheric plasma, hydrogen peroxide, prostate cancer, selectivity

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Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

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Authors: Bingquan Shen

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Convolutional Neural Networks (CNN) have demonstrated their effectiveness in synthesizing 3D views of object instances at various viewpoints. Given the problem where one have limited viewpoints of a particular object for classification, we present a pose normalization architecture to transform the object to existing viewpoints in the training dataset before classification to yield better classification performance. We have demonstrated that this Pose Normalization Network (PNN) can capture the style of the target object and is able to re-render it to a desired viewpoint. Moreover, we have shown that the PNN improves the classification result for the 3D chairs dataset and ShapeNet airplanes dataset when given only images at limited viewpoint, as compared to a CNN baseline.

Keywords: convolutional neural networks, object classification, pose normalization, viewpoint invariant

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Authors: Barry D. Kyle, Jessica Boyd, Robin Pickersgill, Nicole Squires, Cynthia Balion

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Background-Aim: Fentanyl is a highly-potent synthetic μ-opioid receptor agonist used for exceptional pain management. Its main metabolite, norfentanyl, is typically present in urine at significantly high concentrations (i.e. ~20%) representing an effective targeting molecule for immunoassay detection. Here, we evaluated the NCS^TM One Step Fentanyl Test Device© and the BTNX Rapid Response^TM Single Drug Test Strip© point of care (POC) test strips targeting norfentanyl (20 ng/ml) and fentanyl (100 ng/ml) molecules for potential risperidone interference. Methods: POC tests calibrated against norfentanyl (20 ng/ml) used [immunochromatographic] lateral flow devices to provide qualitative results within five minutes of urine sample contact. Results were recorded as negative if lines appeared in the test and control regions according to manufacturer’s instructions. Positive results were recorded if no line appeared in the test region (i.e., control line only visible). Pooled patient urine (n=20), that screened negative for drugs of abuse (using NCS One Step Multi-Line Screen) and fentanyl (using BTNX Rapid Response Strip) was used for spiking studies. Urine was spiked with risperidone alone and with combinations of fentanyl, norfentanyl and/or risperidone to evaluate cross-reactivity in each test device. Results: A positive screen result was obtained when 8,000 ng/mL of risperidone was spiked into drug free urine using the NCS test device. Positive screen results were also obtained in spiked urine samples containing fentanyl and norfentanyl combinations below the cut-off concentrations when 4000 ng/mL risperidone was present using the NCS testing device. There were no screen positive test results using the BTNX test strip with up to 8,000 ng/mL alone or in combination with concentrations of fentanyl and norfentanyl below the cut-off. Both devices screened positive when either fentanyl or norfentanyl exceeded the cut-off threshold in the absence and presence of risperidone. Conclusion: We report that urine samples containing risperidone may give a false positive result using the NCS One Step Fentanyl Test Device.

Keywords: fentanyl, interferences, point of care test, Risperidone

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Authors: Hala Zaghloul, Taymoor Nazmy

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One of the great challenges of the 21st century is to build a robot that can perceive and act within its environment and communicate with people, while also exhibiting the cognitive capabilities that lead to performance like that of people. The Pulse Coupled Neural Network, PCNN, is a relative new ANN model that derived from a neural mammal model with a great potential in the area of image processing as well as target recognition, feature extraction, speech recognition, combinatorial optimization, compressed encoding. PCNN has unique feature among other types of neural network, which make it a candid to be an important approach for perceiving in cognitive systems. This work show and emphasis on the potentials of PCNN to perform different tasks related to image processing. The main drawback or the obstacle that prevent the direct implementation of such technique, is the need to find away to control the PCNN parameters toward perform a specific task. This paper will evaluate the performance of PCNN standard model for processing images with different properties, and select the important parameters that give a significant result, also, the approaches towards find a way for the adaptation of the PCNN parameters to perform a specific task.

Keywords: cognitive system, image processing, segmentation, PCNN kernels

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Authors: KumarShashvat, ArshpreetKaur, RajeshKumar, Raman Chadha

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Wireless sensor networks have principal characteristic of having restricted energy and with limitation that energy of the nodes cannot be replenished. To increase the lifetime in this scenario WSN route for data transmission is opted such that utilization of energy along the selected route is negligible. For this energy efficient network, dandy infrastructure is needed because it impinges the network lifespan. Clustering is a technique in which nodes are grouped into disjoints and non–overlapping sets. In this technique data is collected at the cluster head. In this paper, Adaptive-PSO algorithm is proposed which forms energy aware clusters by minimizing the cost of locating the cluster head. The main concern is of the suitability of the swarms by adjusting the learning parameters of PSO. Particle Swarm Optimization converges quickly at the beginning stage of the search but during the course of time, it becomes stable and may be trapped in local optima. In suggested network model swarms are given the intelligence of the spiders which makes them capable enough to avoid earlier convergence and also help them to escape from the local optima. Comparison analysis with traditional PSO shows that new algorithm considerably enhances the performance where multi-dimensional functions are taken into consideration.

Keywords: Particle Swarm Optimization, adaptive – PSO, comparison between PSO and A-PSO, energy efficient clustering

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Authors: Samia Dardouri, Ridha Bouallegue

Abstract:

Scheduling is the process of dynamically allocating physical resources to User Equipment (UE) based on scheduling algorithms implemented at the LTE base station. Various algorithms have been proposed by network researchers as the implementation of scheduling algorithm which represents an open issue in Long Term Evolution (LTE) standard. This paper makes an attempt to study and compare the performance of PF, MLWDF and EXP/PF scheduling algorithms. The evaluation is considered for a single cell with interference scenario for different flows such as Best effort, Video and VoIP in a pedestrian and vehicular environment using the LTE-Sim network simulator. The comparative study is conducted in terms of system throughput, fairness index, delay, packet loss ratio (PLR) and total cell spectral efficiency.

Keywords: LTE, multimedia flows, scheduling algorithms, mobile computing

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Authors: Taehoon Kwon, Hyeongrae Cho, Dirk Henkensmeier, Youngjong Kang, Chong Min Koo

Abstract:

Ionic polymer actuators have been of interest in the bio-inspired artificial muscle devices. However, the relatively slow response and low power density were the obstacles for practical applications. In this study, ionic polymer actuators are fabricated with ionic polymer composite membranes based on sulfonated poly(arylene ether sulfone) (SPAES) and copper(II) phthalocyanine tetrasulfonic acid (CuPCSA). CuPCSA is an organic filler with very high ion exchange capacity (IEC, 4.5 mmol H+/g) that can be homogeneously dispersed on the molecular scale into the SPAES membrane. SPAES/CuPCSA actuators show larger ionic conductivity, mechanical properties, bending deformation, exceptional faster response to electrical stimuli, and larger mechanical power density (3028 W m–3) than Nafion actuators. This outstanding actuation performance of SPAES/CuPCSA composite membrane actuators makes them attractive for next generation transducers with high power density, which are currently developed biomimetic devices such as endoscopic surgery.

Keywords: actuation performance, composite membranes, ionic polymer actuators, organic filler

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Authors: Chothmal

Abstract:

In this paper, we present a route discovery process which uses the signal strength on a link as a parameter of its inclusion in the route discovery method. The proposed signal-to-interference and noise ratio (SINR) based multipath reactive routing protocol is named as SINR-MP protocol. The proposed SINR-MP routing protocols has two following two features: a) SINR-MP protocol selects routes based on the SINR of the links during the route discovery process therefore it select the routes which has long lifetime and low frame error rate for data transmission, and b) SINR-MP protocols route discovery process is multipath which discovers more than one SINR based route between a given source destination pair. The multiple routes selected by our SINR-MP protocol are node-disjoint in nature which increases their robustness against link failures, as failure of one route will not affect the other route. The secondary route is very useful in situations where the primary route is broken because we can now use the secondary route without causing a new route discovery process. Due to this, the network overhead caused by a route discovery process is avoided. This increases the network performance greatly. The proposed SINR-MP routing protocol is implemented in the trail version of network simulator called Qualnet.

Keywords: ad hoc networks, quality of service, video streaming, H.264/SVC, multiple routes, video traces

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Authors: Senay Yitmen

Abstract:

This research investigated individual’s support and helping intentions towards Syrian refugees in Turkey. This is examined in relation to perceived threat and negative emotions, and also to the perceptions of whether one’s intimate social network (family and friends) considers Syrians a threat (descriptive network norm) and whether this network morally supports Syrian refugees (injunctive norms). A questionnaire study was conducted among Turkish participants (n= 565) and the results showed that perception of threat was associated with negative emotions which, in turn, were related to less support of Syrian refugees. Additionally, descriptive norms moderated the relationship between perceived threat and negative emotions towards Syrian refugees. Furthermore, injunctive norms moderated the relationship between negative emotions and support to Syrian refugees. Specifically, the findings indicate that perceived threat is associated with less support of Syrian refugees through negative emotions when descriptive norms are weak and injunctive norms are strong. Injunctive norms appear to trigger a dilemma over the decision to conform or not to conform: when one has negative emotions as a result of perceived threat, it becomes more difficult to conform to the moral obligation of injunctive norms which is associated with less support of Syrian refugees. Hence, these findings demonstrate that both descriptive and injunctive norms are important and play different roles in individual’s support of Syrian refugees.

Keywords: descriptive norms, emotions, injunctive norms, the perception of threat

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