Search results for: passive optical networks (PONs)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5052

Search results for: passive optical networks (PONs)

3492 Nonlinear Aerodynamic Parameter Estimation of a Supersonic Air to Air Missile by Using Artificial Neural Networks

Authors: Tugba Bayoglu

Abstract:

Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

Procedia PDF Downloads 270
3491 Embedded Hw-Sw Reconfigurable Techniques For Wireless Sensor Network Applications

Authors: B. Kirubakaran, C. Rajasekaran

Abstract:

Reconfigurable techniques are used in many engineering and industrial applications for the efficient data transmissions through the wireless sensor networks. Nowadays most of the industrial applications are work for try to minimize the size and cost. During runtime the reconfigurable technique avoid the unwanted hang and delay in the system performance. In recent world Field Programmable Gate Array (FPGA) as one of the most efficient reconfigurable device and widely used for most of the hardware and software reconfiguration applications. In this paper, the work deals with whatever going to make changes in the hardware and software during runtime it’s should not affect the current running process that’s the main objective of the paper our changes be done in a parallel manner at the same time concentrating the cost and power transmission problems during data trans-receiving. Analog sensor (Temperature) as an input for the controller (PIC) through that control the FPGA digital sensors in generalized manner.

Keywords: field programmable gate array, peripheral interrupt controller, runtime reconfigurable techniques, wireless sensor networks

Procedia PDF Downloads 401
3490 Comparative Analysis of Data Gathering Protocols with Multiple Mobile Elements for Wireless Sensor Network

Authors: Bhat Geetalaxmi Jairam, D. V. Ashoka

Abstract:

Wireless Sensor Networks are used in many applications to collect sensed data from different sources. Sensed data has to be delivered through sensors wireless interface using multi-hop communication towards the sink. The data collection in wireless sensor networks consumes energy. Energy consumption is the major constraints in WSN .Reducing the energy consumption while increasing the amount of generated data is a great challenge. In this paper, we have implemented two data gathering protocols with multiple mobile sinks/elements to collect data from sensor nodes. First, is Energy-Efficient Data Gathering with Tour Length-Constrained Mobile Elements in Wireless Sensor Networks (EEDG), in which mobile sinks uses vehicle routing protocol to collect data. Second is An Intelligent Agent-based Routing Structure for Mobile Sinks in WSNs (IAR), in which mobile sinks uses prim’s algorithm to collect data. Authors have implemented concepts which are common to both protocols like deployment of mobile sinks, generating visiting schedule, collecting data from the cluster member. Authors have compared the performance of both protocols by taking statistics based on performance parameters like Delay, Packet Drop, Packet Delivery Ratio, Energy Available, Control Overhead. Authors have concluded this paper by proving EEDG is more efficient than IAR protocol but with few limitations which include unaddressed issues likes Redundancy removal, Idle listening, Mobile Sink’s pause/wait state at the node. In future work, we plan to concentrate more on these limitations to avail a new energy efficient protocol which will help in improving the life time of the WSN.

Keywords: aggregation, consumption, data gathering, efficiency

Procedia PDF Downloads 487
3489 Mobile Network Users Amidst Ultra-Dense Networks in 5G Using an Improved Coordinated Multipoint (CoMP) Technology

Authors: Johnson O. Adeogo, Ayodele S. Oluwole, O. Akinsanmi, Olawale J. Olaluyi

Abstract:

In this 5G network, very high traffic density in densely populated areas, most especially in densely populated areas, is one of the key requirements. Radiation reduction becomes one of the major concerns to secure the future life of mobile network users in ultra-dense network areas using an improved coordinated multipoint technology. Coordinated Multi-Point (CoMP) is based on transmission and/or reception at multiple separated points with improved coordination among them to actively manage the interference for the users. Small cells have two major objectives: one, they provide good coverage and/or performance. Network users can maintain a good quality signal network by directly connecting to the cell. Two is using CoMP, which involves the use of multiple base stations (MBS) to cooperate by transmitting and/or receiving at the same time in order to reduce the possibility of electromagnetic radiation increase. Therefore, the influence of the screen guard with rubber condom on the mobile transceivers as one major piece of equipment radiating electromagnetic radiation was investigated by mobile network users amidst ultra-dense networks in 5g. The results were compared with the same mobile transceivers without screen guards and rubber condoms under the same network conditions. The 5 cm distance from the mobile transceivers was measured with the help of a ruler, and the intensity of Radio Frequency (RF) radiation was measured using an RF meter. The results show that the intensity of radiation from various mobile transceivers without screen guides and condoms was higher than the mobile transceivers with screen guides and condoms when call conversation was on at both ends.

Keywords: ultra-dense networks, mobile network users, 5g, coordinated multi-point.

Procedia PDF Downloads 91
3488 Identifying Temporary Housing Main Vertexes through Assessing Post-Disaster Recovery Programs

Authors: S. M. Amin Hosseini, Oriol Pons, Carmen Mendoza Arroyo, Albert de la Fuente

Abstract:

In the aftermath of a natural disaster, the major challenge most cities and societies face, regardless of their diverse level of prosperity, is to provide temporary housing (TH) for the displaced population (DP). However, the features of TH, which have been applied in previous recovery programs, greatly varied from case to case. This situation demonstrates that providing temporary accommodation for DP in a short period time and usually in great numbers is complicated in terms of satisfying all the beneficiaries’ needs, regardless of the societies’ welfare levels. Furthermore, when previously used strategies are applied to different areas, the chosen strategies are most likely destined to fail, unless the strategies are context and culturally based. Therefore, as the population of disaster-prone cities are increasing, decision-makers need a platform to help to determine all the factors, which caused the outcomes of the prior programs. To this end, this paper aims to assess the problems, requirements, limitations, potential responses, chosen strategies, and their outcomes, in order to determine the main elements that have influenced the TH process. In this regard, and in order to determine a customizable strategy, this study analyses the TH programs of five different cases as: Marmara earthquake, 1999; Bam earthquake, 2003; Aceh earthquake and tsunami, 2004; Hurricane Katrina, 2005; and, L’Aquila earthquake, 2009. The research results demonstrate that the main vertexes of TH are: (1) local characteristics, including local potential and affected population features, (2) TH properties, which needs to be considered in four phases: planning, provision/construction, operation, and second life, and (3) natural hazards impacts, which embraces intensity and type. Accordingly, this study offers decision-makers the opportunity to discover the main vertexes, their subsets, interactions, and the relation between strategies and outcomes based on the local conditions of each case. Consequently, authorities may acquire the capability to design a customizable method in the face of complicated post-disaster housing in the wake of future natural disasters.

Keywords: post-disaster temporary accommodation, urban resilience, natural disaster, local characteristic

Procedia PDF Downloads 236
3487 Cytotoxic and Biocompatible Evaluation of Silica Coated Silver Nanoparticle Against Nih-3t3 Cells

Authors: Chen-En Lin, Lih-Rou Rau, Jiunn-Woei Liaw, Shiao-Wen Tsai

Abstract:

The unique optical properties of plasmon resonance metallic particles have attracted considerable applications in the fields of physics, chemistry and biology. Metal-Enhanced Fluorescence (MEF) effect is one of the useful applications. MEF effect stated that fluorescence intensity can be quenched or be enhanced depending on the distance between fluorophores and the metal nanoparticles. Silver nanoparticles have used widely in antibacterial studies. However, the major limitation for silver nanoparticles (AgNPs) in biomedical application is well-known cytotoxicity on cells. There were numerous literatures have been devoted to overcome the disadvantage. The aim of the study is to evaluate the cytotoxicity and biocompatibility of silica coated AgNPs against NIH-3T3 cells. The results were shown that NIH-3T3 cells started to detach, shrink, become rounded and finally be irregular in shape after 24 h of exposure at 10 µg/ml AgNPs. Besides, compared with untreated cells, the cell viability significantly decreased to 60% and 40% which were exposed to 10 µg/ml and 20 µg/ml AgNPs respectively. The result was consistent with previously reported findings that AgNPs induced cytotoxicity was concentration dependent. However, the morphology and cell viability of cells appeared similar to the control group when exposed to 20 µg/ml of silica coated AgNPs. We further utilized the dark-field hyperspectral imaging system to analysis the optical properties of the intracellular nanoparticles. The image displayed that the red shift of the surface plasmonic resonances band of the enclosed AgNPs further confirms the agglomerate of the AgNPs rather than their distribution in cytoplasm. In conclusion, the study demonstrated the silica coated of AgNPs showed well biocompatibility and significant lower cytotoxicity compared with bare AgNPs.

Keywords: silver nanoparticles, silica, cell viability, morphology

Procedia PDF Downloads 388
3486 Instant Fire Risk Assessment Using Artifical Neural Networks

Authors: Tolga Barisik, Ali Fuat Guneri, K. Dastan

Abstract:

Major industrial facilities have a high potential for fire risk. In particular, the indices used for the detection of hidden fire are used very effectively in order to prevent the fire from becoming dangerous in the initial stage. These indices provide the opportunity to prevent or intervene early by determining the stage of the fire, the potential for hazard, and the type of the combustion agent with the percentage values of the ambient air components. In this system, artificial neural network will be modeled with the input data determined using the Levenberg-Marquardt algorithm, which is a multi-layer sensor (CAA) (teacher-learning) type, before modeling the modeling methods in the literature. The actual values produced by the indices will be compared with the outputs produced by the network. Using the neural network and the curves to be created from the resulting values, the feasibility of performance determination will be investigated.

Keywords: artifical neural networks, fire, Graham Index, levenberg-marquardt algoritm, oxygen decrease percentage index, risk assessment, Trickett Index

Procedia PDF Downloads 132
3485 Optical Properties of Nanocrystalline Europium-Yttrium Titanate EuYTi2O7

Authors: J. Mrazek, R. Skala, S. Bysakh, Ivan Kasik

Abstract:

Lanthanide-doped yttrium titanium oxides, which crystallize in a pyrochlore structure with general formula (RExY1-x)2Ti2O7 (RE=rare earth element), have been extensively investigated in recent years for their interesting physical and chemical properties. Despite that the pure pyrochlore structure does not present luminescence ability, the presence of yttrium ions in the pyrochlore structure significantly improves the luminescence properties of the RE. Moreover, the luminescence properties of pyrochlores strongly depend on the size of formed nanocrystals. In this contribution, we present a versatile sol-gel synthesis of nanocrystalline EuYTi2O7pyrochlore. The nanocrystalline powders and thin films were prepared by the condensation of titanium(IV)butoxide with europium(III) chloride followed by the calcination. The introduced method leads to the formation of the highly-homogenous nanocrystalline EuYTi2O7 with tailored grain size ranging from 20 nm to 200 nm. The morphology and the structure of the formed nanocrystals are linked to the luminescence properties of Eu3+ ions incorporated into the pyrochlore lattice. The results of XRD and HRTEM analysis show that the Eu3+ and Y3+ ions are regularly distributed inside the lattice. The lifetime of Eu3+ ions in calcinated powders is regularly decreasing from 140 us to 68 us and the refractive index of prepared thin films regularly increases from 2.0 to 2.45 according to the calcination temperature. The shape of the luminescence spectra and the decrease of the lifetime correspond with the crystallinity of prepared powders. The results present fundamental information about the effect of the size of the nanocrystals to their luminescence properties. The promising application of prepared nanocrystals in the field of lasers and planar optical amplifiers is widely discussed in the contribution.

Keywords: europium, luminescence, nanocrystals, sol-gel

Procedia PDF Downloads 253
3484 Incidence of Orphans Neonatal Puppies Attend in Veterinary Hospital – Causes, Consequences and Mortality

Authors: Maria L. G. Lourenço, Keylla H. N. P. Pereira, Viviane Y. Hibaru, Fabiana F. Souza, João C. P. Ferreira, Simone B. Chiacchio, Luiz H. A. Machado

Abstract:

Orphaned is a risk factor for mortality in newborns since it is a condition with total or partial absence of maternal care that is essential for neonatal survival, including nursing (nutrition, the transference of passive immunity and hydration), warmth, urination, and defecation stimuli, and protection. The most common causes of mortality in orphans are related to lack of assistance, handling mistakes and infections. This study aims to describe the orphans rates in neonatal puppies, the main causes, and the mortality rates. The study included 735 neonates admitted to the Sao Paulo State University (UNESP) Veterinary Hospital, Botucatu, Sao Paulo, Brazil, between January 2018 and November 2019. The orphans rate was 43.4% (319/735) of all neonates included, and the main causes for orphaned were related to maternal agalactia/hypogalactia (23.5%, 75/319); numerous litter (15.7%, 50/319), toxic milk syndrome due to maternal mastitis (14.4%, 46/319), absence of suction/weak neonate (12.2%, 39/319), maternal disease (9.4%, 30/319), cleft palate/lip (6.3%, 20/319), maternal death (5.9%, 19/319), prematurity (5.3%, 17/319), rejection/failure in maternal instinct (3.8%, 12/319) and abandonment by the owner/separation of mother and neonate (3.5%, 11/319). The main consequences of orphaned observed in the admitted neonates were hypoglycemia, hypothermia, dehydration, aspiration pneumonia, wasting syndrome, failure in the transference of passive immunity, infections and sepsis, which happened due to failure of identifying the problem early, lack of adequate assistance, negligence and handling mistakes by the owner. The total neonatal mortality rate was 8% (59/735) and the neonatal mortality rate among orphans was 18.5% (59/319). The orphaned and mortality rates were considered high, but even higher rates may be observed in locations without adequate neonatal assistance and owner orientation. The survival of these patients is related to constant monitoring of the litter, early diagnosis and assistance, and the implementation of effective handling for orphans. Understanding the correct handling for neonates and instructing the owners regarding proper handling are essential to minimize the consequences of orphaned and the mortality rates.

Keywords: orphans, neonatal care, puppies, newborn dogs

Procedia PDF Downloads 249
3483 Effectiveness of New Digital Tools on Implementing Quality Management System: An Exploratory Study of French Companies

Authors: Takwa Belwakess

Abstract:

With the wave of the digitization that invades the modern world, communication tools took their place in the world of business. As for organizations, being part of the digital era necessarily involves an evolution of the management style, mainly in processes management, knowing also as quality management system (QMS). For more than 50 years quality management standards have been adopted by organizations to prove their operational and financial performances. We believe that achieving a high-level of communication can lead to better quality management and greater customer satisfaction, which is essential to make sure long-term competitiveness. In this paper, a questionnaire survey was developed to investigate the use of collaboration tools such as Content Management System and Social Networks. Data from more than 100 companies based in France was analyzed, the results show that adopting new digital communication tools while applying quality management practices over a reasonable period, contributed to delivering a better implementation of the QMS for a better business performance.

Keywords: communication tools, content management system, digital, effectiveness, French companies, quality management system, quality management practices, social networks

Procedia PDF Downloads 260
3482 Opto-Electronic Properties and Structural Phase Transition of Filled-Tetrahedral NaZnAs

Authors: R. Khenata, T. Djied, R. Ahmed, H. Baltache, S. Bin-Omran, A. Bouhemadou

Abstract:

We predict structural, phase transition as well as opto-electronic properties of the filled-tetrahedral (Nowotny-Juza) NaZnAs compound in this study. Calculations are carried out by employing the full potential (FP) linearized augmented plane wave (LAPW) plus local orbitals (lo) scheme developed within the structure of density functional theory (DFT). Exchange-correlation energy/potential (EXC/VXC) functional is treated using Perdew-Burke and Ernzerhof (PBE) parameterization for generalized gradient approximation (GGA). In addition to Trans-Blaha (TB) modified Becke-Johnson (mBJ) potential is incorporated to get better precision for optoelectronic properties. Geometry optimization is carried out to obtain the reliable results of the total energy as well as other structural parameters for each phase of NaZnAs compound. Order of the structural transitions as a function of pressure is found as: Cu2Sb type → β → α phase in our study. Our calculated electronic energy band structures for all structural phases at the level of PBE-GGA as well as mBJ potential point out; NaZnAs compound is a direct (Γ–Γ) band gap semiconductor material. However, as compared to PBE-GGA, mBJ potential approximation reproduces higher values of fundamental band gap. Regarding the optical properties, calculations of real and imaginary parts of the dielectric function, refractive index, reflectivity coefficient, absorption coefficient and energy loss-function spectra are performed over a photon energy ranging from 0.0 to 30.0 eV by polarizing incident radiation in parallel to both [100] and [001] crystalline directions.

Keywords: NaZnAs, FP-LAPW+lo, structural properties, phase transition, electronic band-structure, optical properties

Procedia PDF Downloads 426
3481 Chemical Fabrication of Gold Nanorings: Controlled Reduction and Optical Tuning for Nanomedicine Applications

Authors: Mehrnaz Mostafavi, Jalaledin Ghanavi

Abstract:

This research investigates the production of nanoring structures through a chemical reduction approach, exploring gradual reduction processes assisted by reductant agents, leading to the formation of these specialized nanorings. The study focuses on the controlled reduction of metal atoms within these agents, crucial for shaping these nanoring structures over time. The paper commences by highlighting the wide-ranging applications of metal nanostructures across fields like Nanomedicine, Nanobiotechnology, and advanced spectroscopy methods such as Surface Enhanced Raman Spectroscopy (SERS) and Surface Enhanced Infrared Absorption Spectroscopy (SEIRA). Particularly, gold nanoparticles, especially in the nanoring configuration, have gained significant attention due to their distinctive properties, offering accessible spaces suitable for sensing and spectroscopic applications. The methodology involves utilizing human serum albumin as a reducing agent to create gold nanoparticles through a chemical reduction process. This process involves the transfer of electrons from albumin's carboxylic groups, converting them into carbonyl, while AuCl4− acquires electrons to form gold nanoparticles. Various characterization techniques like Ultraviolet–visible spectroscopy (UV-Vis), Atomic-force microscopy (AFM), and Transmission electron microscopy (TEM) were employed to examine and validate the creation and properties of the gold nanoparticles and nanorings. The findings suggest that precise and gradual reduction processes, in conjunction with optimal pH conditions, play a pivotal role in generating nanoring structures. Experiments manipulating optical properties revealed distinct responses in the visible and infrared spectrums, demonstrating the tunability of these nanorings. Detailed examinations of the morphology confirmed the formation of gold nanorings, elucidating their size, distribution, and structural characteristics. These nanorings, characterized by an empty volume enclosed by uniform walls, exhibit promising potential in the realms of Nanomedicine and Nanobiotechnology. In summary, this study presents a chemical synthesis approach using organic reducing agents to produce gold nanorings. The results underscore the significance of controlled and gradual reduction processes in crafting nanoring structures with unique optical traits, offering considerable value across diverse nanotechnological applications.

Keywords: nanoring structures, chemical reduction approach, gold nanoparticles, spectroscopy methods, nano medicine applications

Procedia PDF Downloads 113
3480 NFResNet: Multi-Scale and U-Shaped Networks for Deblurring

Authors: Tanish Mittal, Preyansh Agrawal, Esha Pahwa, Aarya Makwana

Abstract:

Multi-Scale and U-shaped Networks are widely used in various image restoration problems, including deblurring. Keeping in mind the wide range of applications, we present a comparison of these architectures and their effects on image deblurring. We also introduce a new block called as NFResblock. It consists of a Fast Fourier Transformation layer and a series of modified Non-Linear Activation Free Blocks. Based on these architectures and additions, we introduce NFResnet and NFResnet+, which are modified multi-scale and U-Net architectures, respectively. We also use three differ-ent loss functions to train these architectures: Charbonnier Loss, Edge Loss, and Frequency Reconstruction Loss. Extensive experiments on the Deep Video Deblurring dataset, along with ablation studies for each component, have been presented in this paper. The proposed architectures achieve a considerable increase in Peak Signal to Noise (PSNR) ratio and Structural Similarity Index (SSIM) value.

Keywords: multi-scale, Unet, deblurring, FFT, resblock, NAF-block, nfresnet, charbonnier, edge, frequency reconstruction

Procedia PDF Downloads 127
3479 Three-Dimensional Vibration Characteristics of Piezoelectric Semi-Spherical Shell

Authors: Yu-Hsi Huang, Ying-Der Tsai

Abstract:

Piezoelectric circular plates can provide out-of-plane vibrational displacements on low frequency and in-plane vibrational displacements on high frequency. Piezoelectric semi-spherical shell, which is double-curvature structure, can induce three-dimensional vibrational displacements over a large frequency range. In this study, three-dimensional vibrational characteristics of piezoelectric semi-spherical shells with free boundary conditions are investigated using three experimental methods and finite element numerical modeling. For the experimental measurements, amplitude-fluctuation electronic speckle pattern interferometry (AF-ESPI) is used to obtain resonant frequencies and radial and azimuthal mode shapes. This optical technique utilizes a full-field and non-contact optical system that measures both the natural frequency and corresponding vibration mode shape simultaneously in real time. The second experimental technique used, laser displacement meter is a point-wise displacement measurement method that determines the resonant frequencies of the piezoelectric shell. An impedance analyzer is used to determine the in-plane resonant frequencies of the piezoelectric semi-spherical shell. The experimental results of the resonant frequencies and mode shapes for the piezoelectric shell are verified with the result from finite element analysis. Excellent agreement between the experimental measurements and numerical calculation is presented on the three-dimensional vibrational characteristics of the piezoelectric semi-spherical shell.

Keywords: piezoelectric semi-spherical shell, mode shape, resonant frequency, electronic speckle pattern interferometry, radial vibration, azimuthal vibration

Procedia PDF Downloads 225
3478 Nanocomposites Based Micro/Nano Electro-Mechanical Systems for Energy Harvesters and Photodetectors

Authors: Radhamanohar Aepuru, R. V. Mangalaraja

Abstract:

Flexible electronic devices have drawn potential interest and provide significant new insights to develop energy conversion and storage devices such as photodetectors and nanogenerators. Recently, self-powered electronic systems have captivated huge attention for next generation MEMS/NEMS devices that can operate independently by generating built-in field without any need of external bias voltage and have wide variety of applications in telecommunication, imaging, environmental and defence sectors. The basic physical process involved in these devices are charge generation, separation, and charge flow across the electrodes. Many inorganic nanostructures have been exploring to fabricate various optoelectronic and electromechanical devices. However, the interaction of nanostructures and their excited charge carrier dynamics, photoinduced charge separation, and fast carrier mobility are yet to be studied. The proposed research is to address one such area and to realize the self-powered electronic devices. In the present work, nanocomposites of inorganic nanostructures based on ZnO, metal halide perovskites; and polyvinylidene fluoride (PVDF) based nanocomposites are realized for photodetectors and nanogenerators. The characterization of the inorganic nanostructures is carried out through steady state optical absorption and luminescence spectroscopies as well as X-ray diffraction and high-resolution transmission electron microscopy (TEM) studies. The detailed carrier dynamics is investigated using various spectroscopic techniques. The developed composite nanostructures exhibit significant optical and electrical properties, which have wide potential applications in various MEMS/NEMS devices such as photodetectors and nanogenerators.

Keywords: dielectrics, nanocomposites, nanogenerators, photodetectors

Procedia PDF Downloads 126
3477 Adaptive Energy-Aware Routing (AEAR) for Optimized Performance in Resource-Constrained Wireless Sensor Networks

Authors: Innocent Uzougbo Onwuegbuzie

Abstract:

Wireless Sensor Networks (WSNs) are crucial for numerous applications, yet they face significant challenges due to resource constraints such as limited power and memory. Traditional routing algorithms like Dijkstra, Ad hoc On-Demand Distance Vector (AODV), and Bellman-Ford, while effective in path establishment and discovery, are not optimized for the unique demands of WSNs due to their large memory footprint and power consumption. This paper introduces the Adaptive Energy-Aware Routing (AEAR) model, a solution designed to address these limitations. AEAR integrates reactive route discovery, localized decision-making using geographic information, energy-aware metrics, and dynamic adaptation to provide a robust and efficient routing strategy. We present a detailed comparative analysis using a dataset of 50 sensor nodes, evaluating power consumption, memory footprint, and path cost across AEAR, Dijkstra, AODV, and Bellman-Ford algorithms. Our results demonstrate that AEAR significantly reduces power consumption and memory usage while optimizing path weight. This improvement is achieved through adaptive mechanisms that balance energy efficiency and link quality, ensuring prolonged network lifespan and reliable communication. The AEAR model's superior performance underlines its potential as a viable routing solution for energy-constrained WSN environments, paving the way for more sustainable and resilient sensor network deployments.

Keywords: wireless sensor networks (WSNs), adaptive energy-aware routing (AEAR), routing algorithms, energy, efficiency, network lifespan

Procedia PDF Downloads 28
3476 Creation of Ultrafast Ultra-Broadband High Energy Laser Pulses

Authors: Walid Tawfik

Abstract:

The interaction of high intensity ultrashort laser pulses with plasma generates many significant applications, including soft x-ray lasers, time-resolved laser induced plasma spectroscopy LIPS, and laser-driven accelerators. The development in producing of femtosecond down to ten femtosecond optical pulses has facilitates scientists with a vital tool in a variety of ultrashort phenomena, such as high field physics, femtochemistry and high harmonic generation HHG. In this research, we generate a two-octave-wide ultrashort supercontinuum pulses with an optical spectrum extending from 3.5 eV (ultraviolet) to 1.3 eV (near-infrared) using a capillary fiber filled with neon gas. These pulses are formed according to nonlinear self-phase modulation in the neon gas as a nonlinear medium. The investigations of the created pulses were made using spectral phase interferometry for direct electric-field reconstruction (SPIDER). A complete description of the output pulses was considered. The observed characterization of the produced pulses includes the beam profile, the pulse width, and the spectral bandwidth. After reaching optimization conditions, the intensity of the reconstructed pulse autocorrelation function was applied for the shorts pulse duration to achieve transform limited ultrashort pulses with durations below 6-fs energies up to 600μJ. Moreover, the effect of neon pressure variation on the pulse width was examined. The nonlinear self-phase modulation realized to be increased with the pressure of the neon gas. The observed results may lead to an advanced method to control and monitor ultrashort transit interaction in femtochemistry.

Keywords: supercontinuum, ultrafast, SPIDER, ultra-broadband

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3475 Requirement Engineering for Intrusion Detection Systems in Wireless Sensor Networks

Authors: Afnan Al-Romi, Iman Al-Momani

Abstract:

The urge of applying the Software Engineering (SE) processes is both of vital importance and a key feature in critical, complex large-scale systems, for example, safety systems, security service systems, and network systems. Inevitably, associated with this are risks, such as system vulnerabilities and security threats. The probability of those risks increases in unsecured environments, such as wireless networks in general and in Wireless Sensor Networks (WSNs) in particular. WSN is a self-organizing network of sensor nodes connected by wireless links. WSNs consist of hundreds to thousands of low-power, low-cost, multi-function sensor nodes that are small in size and communicate over short-ranges. The distribution of sensor nodes in an open environment that could be unattended in addition to the resource constraints in terms of processing, storage and power, make such networks in stringent limitations such as lifetime (i.e. period of operation) and security. The importance of WSN applications that could be found in many militaries and civilian aspects has drawn the attention of many researchers to consider its security. To address this important issue and overcome one of the main challenges of WSNs, security solution systems have been developed by researchers. Those solutions are software-based network Intrusion Detection Systems (IDSs). However, it has been witnessed, that those developed IDSs are neither secure enough nor accurate to detect all malicious behaviours of attacks. Thus, the problem is the lack of coverage of all malicious behaviours in proposed IDSs, leading to unpleasant results, such as delays in the detection process, low detection accuracy, or even worse, leading to detection failure, as illustrated in the previous studies. Also, another problem is energy consumption in WSNs caused by IDS. So, in other words, not all requirements are implemented then traced. Moreover, neither all requirements are identified nor satisfied, as for some requirements have been compromised. The drawbacks in the current IDS are due to not following structured software development processes by researches and developers when developing IDS. Consequently, they resulted in inadequate requirement management, process, validation, and verification of requirements quality. Unfortunately, WSN and SE research communities have been mostly impermeable to each other. Integrating SE and WSNs is a real subject that will be expanded as technology evolves and spreads in industrial applications. Therefore, this paper will study the importance of Requirement Engineering when developing IDSs. Also, it will study a set of existed IDSs and illustrate the absence of Requirement Engineering and its effect. Then conclusions are drawn in regard of applying requirement engineering to systems to deliver the required functionalities, with respect to operational constraints, within an acceptable level of performance, accuracy and reliability.

Keywords: software engineering, requirement engineering, Intrusion Detection System, IDS, Wireless Sensor Networks, WSN

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3474 Adversarial Attacks and Defenses on Deep Neural Networks

Authors: Jonathan Sohn

Abstract:

Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

Procedia PDF Downloads 189
3473 Analyze of Nanoscale Materials and Devices for Future Communication and Telecom Networks in the Gas Refinery

Authors: Mohamad Bagher Heidari, Hefzollah Mohammadian

Abstract:

New discoveries in materials on the nanometer-length scale are expected to play an important role in addressing ongoing and future challenges in the field of communication. Devices and systems for ultra-high speed short and long range communication links, portable and power efficient computing devices, high-density memory and logics, ultra-fast interconnects, and autonomous and robust energy scavenging devices for accessing ambient intelligence and needed information will critically depend on the success of next-generation emerging nonmaterials and devices. This article presents some exciting recent developments in nonmaterials that have the potential to play a critical role in the development and transformation of future intelligent communication and telecom networks in the gas refinery. The industry is benefiting from nanotechnology advances with numerous applications including those in smarter sensors, logic elements, computer chips, memory storage devices, optoelectronics.

Keywords: nonmaterial, intelligent communication, nanoscale, nanophotonic, telecom

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3472 In situ Polymerization and Properties of Biobased Polyurethane/Epoxy Interpenetrating Network Nanocomposites

Authors: Aiswarea Mathew, Smita Mohanty, Jr., S. K. Nayak

Abstract:

Polyurethane networks based on castor oil (CO) as a renewable resource polyol were synthesized. Polyurethane/epoxy resin interpenetrating network nanocomposites containing modified montmorillonite organoclay (C30B-PU/EP nanocomposites) were prepared by an in situ intercalation method. The conventional spectroscopic characterization of the synthesized samples using FT-IR confirms the existence of the proposed castor oil based PU structure and also showed that strong interactions existed between C30B and EP/PU matrix. The dispersion degree of C30B in EP/PU matrix was characterized by X-Ray diffraction (XRD) method. Scanning electronic microscopy analysis showed that the interpenetrating process of PU and EP increases the exfoliation degree of C30B, and it improves the compatibility and the phase structure of polyurethane/epoxy resin interpenetrating polymer networks (PU/EP IPNs). The thermal stability improves compared to the polyurethane when the PU/EP IPN is formed. Mechanical properties including the Young’s modulus and tensile strength reflected marked improvement with addition of C30B.

Keywords: castor oil, epoxy, montmorillonite, polyurethane

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3471 Frequency Distribution and Assertive Object Theory: An Exploration of the Late Bronze Age Italian Ceramic Landscape

Authors: Sara Fioretti

Abstract:

In the 2nd millennium BCE, maritime networks became essential to the Mediterranean lifestyle, creating an interconnected world. This phenomenon of interconnected cultures has often been misinterpreted as an “effect” of the Mycenaean “influence” without considering the complexity and role of regional and cross-cultural exchanges. This paper explores the socio-economic relationships, in both cross-cultural and potentially inter-regional settings, present within the archaeological repertoire of the southern Italian Late Bronze Age (LBA 1600 -1140 BCE). The emergence of economic relations within the connectivity of the regional settlements is explored through ceramic contexts found in the case studies Punta di Zambrone, Broglio di Trebisacce, and Nuraghe Antigori. This work-in-progress research is situated in the shifting theoretical views of the last ten years that discuss the Late Bronze Age’s connectivity through Social Networks, Entanglement, and Assertive Objects combined with a comparative statistical study of ceramic frequency distribution. Applying these theoretical frameworks with a quantitative approach demonstrates the specific regional economic relationships that shaped the cultural interactions of the Late Bronze Age. Through this intersection of theory and statistical analysis, the case studies establish a small percentage of pottery as imported, whilst assertive productions have a relatively higher quantity. Overall, the majority still adheres to regional Italian traditions. Therefore, we can dissect the rhizomatic relationships cultivated by the Italian coasts and Mycenaeans and their roles within their networks through the intersection of theoretical and statistical analysis. This research offers a new perspective on the connectivity of the Late Bronze Age relational structures.

Keywords: late bronze age, mediterranean archaeology, exchanges and trade, frequency distribution of ceramic assemblages

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3470 Experimental Investigation on Noise from Rod-Airfoil with Leading Edge Serrations

Authors: Siti Ruhliah Lizarose Samion, Mohamed Sukri Mat Ali, Con Doolan

Abstract:

The present work is an experimental investigation of adapting a passive treatment leading edge serrations over a rod-airfoil flow-induced noise generation. The leading edge serrations are bio-inspired from a barn-owl silent flight. The rod-airfoil configuration is a benchmark configuration taken to investigate airfoil-turbulence interaction noise (ATIN). Location of serrations placed and the wideness of serrations are the two parameters taken in this study. The ATIN is reduced up to 3.5 dB for a wide leading serrations case. A correlation is found between the wideness of serrations and the noise reduction mechanism of the airfoil.

Keywords: aerodynamic noise, leading edge serrations, rod-airfoil, experiment

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3469 Neural Network Approach For Clustering Host Community: Based on Perceptions Toward Tourism, Their Satisfaction Level and Demographic Attributes in Iran (Lahijan)

Authors: Nasibeh Mohammadpour, Ali Rajabzadeh, Adel Azar, Hamid Zargham Borujeni,

Abstract:

Generally, various industries development depends on their stakeholders and beneficiaries supports. One of the most important stakeholders in tourism industry ( which has become one of the most important lucrative and employment-generating activities at the international level these days) are host communities in tourist destination which are affected and effect on this industry development. Recognizing host community and its segmentations can be important to get their support for future decisions and policy making. In order to identify these segments, in this study, clustering of the residents has been done by using some tools that are designed to encounter human complexities and have ability to model and generalize complex systems without any needs for the initial clusters’ seeds like classic methods. Neural networks can help to meet these expectations. The research have been planned to design neural networks-based mathematical model for clustering the host community effectively according to multi criteria, and identifies differences among segments. In order to achieve this goal, the residents’ segmentation has been done by demographic characteristics, their attitude towards the tourism development, the level of satisfaction and the type of their support in this field. The applied method is self-organized neural networks and the results have compared with K-means. As the results show, the use of Self- Organized Map (SOM) method provides much better results by considering the Cophenetic correlation and between clusters variance coefficients. Based on these criteria, the host community is divided into five sections with unique and distinctive features, which are in the best condition (in comparison other modes) according to Cophenetic correlation coefficient of 0.8769 and between clusters variance of 0.1412.

Keywords: Artificial Nural Network, Clustering , Resident, SOM, Tourism

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3468 High-Capacity Image Steganography using Wavelet-based Fusion on Deep Convolutional Neural Networks

Authors: Amal Khalifa, Nicolas Vana Santos

Abstract:

Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

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3467 Design an Intelligent Fire Detection System Based on Neural Network and Particle Swarm Optimization

Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

Abstract:

In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

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3466 Functional Connectivity Signatures of Polygenic Depression Risk in Youth

Authors: Louise Moles, Steve Riley, Sarah D. Lichenstein, Marzieh Babaeianjelodar, Robert Kohler, Annie Cheng, Corey Horien Abigail Greene, Wenjing Luo, Jonathan Ahern, Bohan Xu, Yize Zhao, Chun Chieh Fan, R. Todd Constable, Sarah W. Yip

Abstract:

Background: Risks for depression are myriad and include both genetic and brain-based factors. However, relationships between these systems are poorly understood, limiting understanding of disease etiology, particularly at the developmental level. Methods: We use a data-driven machine learning approach connectome-based predictive modeling (CPM) to identify functional connectivity signatures associated with polygenic risk scores for depression (DEP-PRS) among youth from the Adolescent Brain and Cognitive Development (ABCD) study across diverse brain states, i.e., during resting state, during affective working memory, during response inhibition, during reward processing. Results: Using 10-fold cross-validation with 100 iterations and permutation testing, CPM identified connectivity signatures of DEP-PRS across all examined brain states (rho’s=0.20-0.27, p’s<.001). Across brain states, DEP-PRS was positively predicted by increased connectivity between frontoparietal and salience networks, increased motor-sensory network connectivity, decreased salience to subcortical connectivity, and decreased subcortical to motor-sensory connectivity. Subsampling analyses demonstrated that model accuracies were robust across random subsamples of N’s=1,000, N’s=500, and N’s=250 but became unstable at N’s=100. Conclusions: These data, for the first time, identify neural networks of polygenic depression risk in a large sample of youth before the onset of significant clinical impairment. Identified networks may be considered potential treatment targets or vulnerability markers for depression risk.

Keywords: genetics, functional connectivity, pre-adolescents, depression

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3465 An Assessment of the Digital Transformation of Radio

Authors: Fatih Sogut

Abstract:

Developments in information technologies have caused significant changes in terms of radio and television broadcasting. With these changes in terms of production format, transmission techniques and service delivery, the distinction between traditional media and New Media has emerged. The viewer/listener, who was in a passive position before, is now in an active position and has a say in many matters, including content production. Visual and auditory data transfer has diversified and become easier thanks to the convergence phenomenon. These transformations and developments also affected one of the oldest electronic communication tools, radio. In this study, in order to adapt to the new era that emerged with the digital age, the change in radio broadcasting and the factors that led to this change were tried to be explained.

Keywords: Internet, radio broadcasting, digital transformation, Internet broadcasting

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3464 Unity in Diversity: Exploring the Psychological Processes and Mechanisms of the Sense of Community for the Chinese Nation in Ethnic Inter-embedded Communities

Authors: Jiamin Chen, Liping Yang

Abstract:

In 2007, sociologist Putnam proposed a pessimistic forecast in the United States' "Social Capital Community Benchmark Survey," suggesting that "ethnic diversity would challenge social unity and undermine social cohesion." If this pessimistic assumption were proven true, it would indicate a risk of division in diverse societies. China, with 56 ethnic groups, is a multi-ethnic country. On May 26, 2014, General Secretary Xi Jinping proposed "building ethnically inter-embedded communities to promote deeper development in interactions, exchanges, and integration among ethnic groups." Researchers unanimously agree that ethnic inter-embedded communities can serve as practical arenas and pathways for solidifying the sense of the Chinese national community However, there is no research providing evidence that ethnic inter-embedded communities can foster the sense of the Chinese national community, and the influencing factors remain unclear. This study adopts a constructivist grounded theory research approach. Convenience sampling and snowball sampling were used in the study. Data were collected in three communities in Kunming City. Twelve individuals were eventually interviewed, and the transcribed interviews totaled 187,000 words. The research has obtained ethical approval from the Ethics Committee of Nanjing Normal University (NNU202310030). The research analyzed the data and constructed theories, employing strategies such as coding, constant comparison, and theoretical sampling. The study found that: firstly, ethnic inter-embedded communities exhibit characteristics of diversity, including ethnic diversity, cultural diversity, and linguistic diversity. Diversity has positive functions, including increased opportunities for contact, promoting self-expansion, and increasing happiness; negative functions of diversity include highlighting ethnic differences, causing ethnic conflicts, and reminding of ethnic boundaries. Secondly, individuals typically engage in interactions within the community using active embedding and passive embedding strategies. Active embedding strategies include maintaining openness, focusing on similarities, and pro-diversity beliefs, which can increase external group identification, intergroup relational identity, and promote ethnic integration. Individuals using passive embedding strategies tend to focus on ethnic stereotypes, perceive stigmatization of their own ethnic group, and adopt an authoritarian-oriented approach to interactions, leading to a perception of more identity threats and ultimately rejecting ethnic integration. Thirdly, the commonality of the Chinese nation is reflected in the 56 ethnic groups as an "identity community" and "interest community," and both active and passive embedding paths affect individual understanding of the commonality of the Chinese nation. Finally, community work and environment can influence the embedding process. The research constructed a social psychological process and mechanism model for solidifying sense of the Chinese national community in ethnic inter-embedded communities. Based on this theoretical model, future research can conduct more micro-level psychological mechanism tests and intervention studies to enhance Chinese national cohesion.

Keywords: diversity, sense of the chinese national community, ethnic inter-embedded communities, ethnic group

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3463 A Survey on Traditional Mac Layer Protocols in Cognitive Wireless Mesh Networks

Authors: Anusha M., V. Srikanth

Abstract:

Maximizing spectrum usage and numerous applications of the wireless communication networks have forced to a high interest of available spectrum. Cognitive Radio control its receiver and transmitter features exactly so that they can utilize the vacant approved spectrum without impacting the functionality of the principal licensed users. The Use of various channels assists to address interferences thereby improves the whole network efficiency. The MAC protocol in cognitive radio network explains the spectrum usage by interacting with multiple channels among the users. In this paper we studied about the architecture of cognitive wireless mesh network and traditional TDMA dependent MAC method to allocate channels dynamically. The majority of the MAC protocols suggested in the research are operated on Common-Control-Channel (CCC) to handle the services between Cognitive Radio secondary users. In this paper, an extensive study of Multi-Channel Multi-Radios or frequency range channel allotment and continually synchronized TDMA scheduling are shown in summarized way.

Keywords: TDMA, MAC, multi-channel, multi-radio, WMN’S, cognitive radios

Procedia PDF Downloads 551