Search results for: graph signals

Authors: Ali Mustafa Elshawesh, Mohamed Abdulali

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The paper presents an approach to dimension circuit switched networks and find the relationship between the parameters of the circuit switched networks on the condition of specific probability of call blocking. Our work is creating a Simulation code based on Erlang (B) formula to draw graphs which show two curves for each graph; one of simulation and the other of calculated. These curves represent the relationships between average number of calls and average call duration with the probability of call blocking. This simulation code facilitates to select the appropriate parameters for circuit switched networks.

Keywords: Erlang B formula, call blocking, telephone system dimension, Markov model, link capacity

Procedia PDF Downloads 596

Authors: Sarah Pasala, Elizabeth Zacharias

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Vital sign monitoring is crucial for both everyday health and medical diagnosis. A significant factor in assessing a human's health is their vital signs, which include heart rate, breathing rate, blood pressure, and electrocardiogram (ECG) readings. Vital sign monitoring has been the focus of many system and method innovations recently. Piezoelectrics are materials that convert mechanical energy into electrical energy and can be used for vital sign monitoring. Piezoelectric energy harvesters that are stretchable and flexible can detect very low frequencies like airflow, heartbeat, etc. Current advancements in piezoelectric materials and flexible sensors have made it possible to create wearable and implantable medical devices that can continuously monitor physiological signals in humans. But because of their non-biocompatible nature, they also produce a large amount of e-waste and require another surgery to remove the implant. This paper presents a biocompatible and flexible piezoelectric composite material for wearable and implantable devices that offers a high-performance platform for seamless and continuous monitoring of human physiological signals and tactile stimuli. It also addresses the issue of e-waste and secondary surgery. A Lead-free piezoelectric, SrBi4Ti4O15, is found to be suitable for this application because the properties can be tailored by suitable substitutions and also by varying the synthesis temperature protocols. In the present work, SrBi4Ti4O15 modified by rare-earth has been synthesized and studied. Coupling factors are calculated from resonant (fr) and anti-resonant frequencies (fa). It is observed that Samarium substitution in SBT has increased the Curie temperature, dielectric and piezoelectric properties. From impedance spectroscopy studies, relaxation, and non-Debye type behaviour are observed. The composite of bioresorbable poly(l-lactide) and Lead-free rare earth modified Bismuth Layered Ferroelectrics leads to a flexible piezoelectric device for non-invasive measurement of vital signs, such as heart rate, breathing rate, blood pressure, and electrocardiogram (ECG) readings and also artery pulse signals in near-surface arteries. These composites are suitable to detect slight movement of the muscles and joints. This Lead-free rare earth modified Bismuth Layered Ferroelectrics – polymer composite is synthesized using a ball mill and the solid-state double sintering method. XRD studies indicated the two phases in the composite. SEM studies revealed the grain size to be uniform and in the range of 100 nm. The electromechanical coupling factor is improved. The elastic constants are calculated and the mechanical flexibility is found to be improved as compared to the single-phase rare earth modified Bismuth Latered piezoelectric. The results indicate that this composite is suitable for the non-invasive detection of multiple vital signs of humans.

Keywords: composites, flexible, non-invasive, piezoelectric

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Authors: Adelia Desi Agnesita

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The advent of a new disease called covid-19 made many major changes in the world, one of which is the process of learning and teaching. Learning formerly offline but now is done online, which makes students need adaptation to the learning process. The covid-19 pandemic that occurs almost worldwide causes activities that involve many people to be avoided, one of which is learning to teach. In Indonesia, since March 2020, the process of college learning is turning into online/ long-distance learning. It's to prevent the spread of the covid-19. Student online learning presents some of the obstacles to poor signals, many of the tasks, lack of focus, difficulty sleeping, and resulting stress.

Keywords: learning, online, covid-19, pandemic

Procedia PDF Downloads 202

Authors: Jasbir Singh Gill, Baljit Singh

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Scheduling and mapping the application task graph on multiprocessor parallel systems is considered as the most crucial and critical NP-complete problem. Many genetic algorithms have been proposed to solve such problems. In this paper, two genetic approach based algorithms have been designed and developed with or without task duplication. The proposed algorithms work on two fitness functions. The first fitness i.e. task fitness is used to minimize the total finish time of the schedule (schedule length) while the second fitness function i.e. process fitness is concerned with allocating the tasks to the available highly efficient processor from the list of available processors (load balance). Proposed genetic-based algorithms have been experimentally implemented and evaluated with other state-of-art popular and widely used algorithms.

Keywords: parallel computing, task scheduling, task duplication, genetic algorithm

Procedia PDF Downloads 333

Authors: Sara Alshehri, Bayan Alenzi, Atheer Alshehri, Samia Chelloug, Zainab Almry, Hussah Albugmai

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This paper concerns body area networks sensor that collect signals around a human body. The black hole attacks are the main security challenging problem because the data traffic can be dropped at any node. The focus of our proposed solution is to efficiently route data packets while detecting black hole nodes.

Keywords: body sensor networks, security, black hole, routing, broadcasting, OMNeT++

Procedia PDF Downloads 629

Authors: Larissa Bolliger, Junoš Lukan, Mitja Lustrek, Dirk De Bacquer, Els Clays

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Introduction and Aim: Chronic workplace stress and its health-related consequences like mental and cardiovascular diseases have been widely investigated. This project focuses on the sources and context of psychosocial daily workplace stress in a real-world setting. The main objective is to analyze and model real-time relationships between (1) psychosocial stress experiences within the natural work environment, (2) micro-level work activities and events, and (3) physiological signals and behaviors in office workers. Methods: An Ecological Momentary Assessment (EMA) protocol has been developed, partly building on machine learning techniques. Empatica® wristbands will be used for real-life detection of stress from physiological signals; micro-level activities and events at work will be based on smartphone registrations, further processed according to an automated computer algorithm. A field study including 100 office-based workers with high-level problem-solving tasks like managers and researchers will be implemented in Slovenia and Belgium (50 in each country). Data mining and state-of-the-art statistical methods – mainly multilevel statistical modelling for repeated data – will be used. Expected Results and Impact: The project findings will provide novel contributions to the field of occupational health research. While traditional assessments provide information about global perceived state of chronic stress exposure, the EMA approach is expected to bring new insights about daily fluctuating work stress experiences, especially micro-level events and activities at work that induce acute physiological stress responses. The project is therefore likely to generate further evidence on relevant stressors in a real-time working environment and hence make it possible to advise on workplace procedures and policies for reducing stress.

Keywords: ecological momentary assessment, real-time, stress, work

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Authors: Bulcha Belay Etana

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Electromyography is used to measure the electrical activity of muscles for various health monitoring applications using surface electrodes or needle electrodes. Recent developments in electromyogram signal acquisition using textile electrodes open the door for wearable health monitoring which enables patients to monitor and control their health issues outside of traditional healthcare facilities. The aim of this research is therefore to develop and analyze wearable textile electrodes for the acquisition of electromyography signals for Parkinson’s patients and apply an appropriate thermal stimulus to relieve muscle cramping. In order to achieve this, textile electrodes are sewn with a silver-coated thread in an overlapping zigzag pattern into an inextensible fabric, and stainless steel knitted textile electrodes attached to a sleeve were prepared and its electrical characteristics including signal to noise ratio were compared with traditional electrodes. To relieve muscle cramping, a heating element using stainless steel conductive yarn Sewn onto a cotton fabric, coupled with a vibration system were developed. The system was integrated using a microcontroller and a Myoware muscle sensor so that when muscle cramping occurs, measured by the system activates the heating elements and vibration motors. The optimum temperature considered for treatment was 35.50c, so a Temperature measurement system was incorporated to deactivate the heating system when the temperature reaches this threshold, and the signals indicating muscle cramping have subsided. The textile electrode exhibited a signal to noise ratio of 6.38dB while the signal to noise ratio of the traditional electrode was 7.05dB. The rise time of the developed heating element was about 6 minutes to reach the optimum temperature using a 9volt power supply. The treatment of muscle cramping in Parkinson's patients using heat and muscle vibration simultaneously with a wearable electromyography signal acquisition system will improve patients’ livelihoods and enable better chronic pain management.

Keywords: electromyography, heating textile, vibration therapy, parkinson’s disease, wearable electronic textile

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Authors: A. Zanj, F. He

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In the current paper, a domain independent conduction model compatible for multi-physical system dynamic investigations is suggested. By means of a port-based approach, a classical nonlinear conduction model containing physical states is first represented. A compatible discrete configuration of the thermal domain in line with the elastic domain is then generated through the enhancement of the configuration of the conventional thermal element. The presented simulation results of a sample structure indicate that the suggested conductive model can cover a wide range of dynamic behavior of the thermal domain.

Keywords: multi-physical domain, conduction model, port based modeling, dynamic interaction, physical modeling

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Authors: Olalekan Lawrence Ojo

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Designing microwave terrestrial propagation networks requires a thorough evaluation of the severity of multipath fading, especially at frequencies below 10 GHz. In nations like Nigeria, without a large enough databases to support the existing empirical models, the mistakes in the prediction technique intended for the evaluation may be severe. The need for higher bandwidth for various satellite applications makes the investigation of the effects of radio refractivity, fading due to multipath, and Geoclimatic factors on satellite propagation links more important. One of the key elements to take into account for the best functioning of microwave frequencies is the clear air effects. This work has taken into account the geographical distribution of radio refractivity and fades depth over a number of stations in Nigeria. Data from five locations in Nigeria—Akure, Enugu, Jos, Minna, and Sokoto—based on five-year (2017–2021) measurement methods of atmospheric pressure, relative, and humidity temperature—at two levels (ground surface and 100 m heights)—are studied to deduced their effects on signals propagated through a µwave communication links. The assessments included considerations for µwave communication systems as well as the impacts of the dry and wet components of radio refractivity, the effects of the fade depth at various frequencies, and a 20 km link distance. The results demonstrate that the percentage occurrence of the dry terms dominated the radio refractivity constituent at the surface level, contributing a minimum of about 78% and a maximum of about 92%, while at heights of 100 meters, the percentage occurrence of the dry terms dominated the radio refractivity constituent, contributing a minimum of about 79% and a maximum of about 92%. The spatial distribution reveals that, regardless of height, the country's tropical rainforest (TRF) and freshwater swampy mangrove (FWSM) regions reported the greatest values of radio refractivity. The statistical estimate shows that fading values can differ by as much as 1.5 dB, especially near the TRF and FWSM coastlines, even during clear air conditions. The current findings will be helpful for budgeting Earth-space microwave links, particularly for the rollout of Nigeria's 5G and 6G projected microcellular networks.

Keywords: fade depth, geoclimatic factor, refractivity, refractivity gradient

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Authors: Rai Sachindra Prasad

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Thought is physical force. This has been well recognized but hardly translated visually or otherwise in the sense of its transfer from one individual to another. In the present world of chaos and disorder with yawning gaps between right and wrong thinking individuals, if it is possible to transfer the right thoughts to replace the wrong ones it would indeed be a great achievement in the present situation of the world which is torn with violence with dangerous thoughts of individuals. Moreover, such a possibility would completely remove the barrier of language between two persons, which at times proves to be a great obstacle in realizing a desired purpose. If a proper instrumentation scheme containing appropriate transducers and electronics is designed and implemented to realize this thought ransfer phenomenon, this would prove to be extremely useful when properly used. Considering the advancements already made in recording the nerve impulses in the brain, which are electrical events of very short durations that move along the axon, it is conceivable that this may be used to good effect in implementing the scheme. In such a proposition one shoud consider the roles played by pineal body, pituitary gland and ‘association’ areas. Pioneer students of brain have thought that associations or connections between sensory input and motor output were made in these areas. It is currently believed that rather than being regions of simple sensory-motor connections, the association areas process and integrate sensory information relayed to them from the primary sensory areas of the cortex and from the thalamus, after the information has been processed, it may be sent to motor areas to be acted upon. Again, even though the role played by pineal body is not known fully to neurologists its interconnection with pituitary gland is a matter of great significance to the ‘Rishis’ and; Seers’ s described in Vedas and Puranas- the ancient Holy books of Hindus. If the pineal body is activated through meditation it would control the pituitary gland thereby the individual’s thoughts and acts. Thus, if thoughts can be picked up by special transducers, these can be connected to suitable electronics circuitry to amplify the signals. These signals in the form of electromagnetic waves can then be transmitted using modems for long distance transmission and eventually received by or passed on to a subject of interest through another set of electronics circuit and devices.

Keywords: modems, pituitary gland, pineal body, thought transfer

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Authors: Rohit Shrivastava, Stefan Luding

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A mechanical wave is propagation of vibration with transfer of energy and momentum. Studying the energy as well as spectral energy characteristics of a propagating wave through disordered granular media can assist in understanding the overall properties of wave propagation through inhomogeneous materials like soil. The study of these properties is aimed at modeling wave propagation for oil, mineral or gas exploration (seismic prospecting) or non-destructive testing for the study of internal structure of solids. The study of Energy content (Kinetic, Potential and Total Energy) of a pulse propagating through an idealized one-dimensional discrete particle system like a mass disordered granular chain can assist in understanding the energy attenuation due to disorder as a function of propagation distance. The spectral analysis of the energy signal can assist in understanding dispersion as well as attenuation due to scattering in different frequencies (scattering attenuation). The selection of one-dimensional granular chain also helps in studying only the P-wave attributes of the wave and removing the influence of shear or rotational waves. Granular chains with different mass distributions have been studied, by randomly selecting masses from normal, binary and uniform distributions and the standard deviation of the distribution is considered as the disorder parameter, higher standard deviation means higher disorder and lower standard deviation means lower disorder. For obtaining macroscopic/continuum properties, ensemble averaging has been used. Interpreting information from a Total Energy signal turned out to be much easier in comparison to displacement, velocity or acceleration signals of the wave, hence, indicating a better analysis method for wave propagation through granular materials. Increasing disorder leads to faster attenuation of the signal and decreases the Energy of higher frequency signals transmitted, but at the same time the energy of spatially localized high frequencies also increases. An ordered granular chain exhibits ballistic propagation of energy whereas, a disordered granular chain exhibits diffusive like propagation, which eventually becomes localized at long periods of time.

Keywords: discrete elements, energy attenuation, mass disorder, granular chain, spectral energy, wave propagation

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Authors: L. Benbaouche, H. E. , F. Krim

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In this paper we propose real-time control of grid-connected single phase inverter, which is flexible and efficient. The first step is devoted to the study and design of the controller through simulation, conducted by the LabVIEW software on the computer 'host'. The second step is running the application from PXI 'target'. LabVIEW software, combined with NI-DAQmx, gives the tools to easily build applications using the digital to analog converter to generate the PWM control signals. Experimental results show that the effectiveness of LabVIEW software applied to power electronics.

Keywords: real-time control, labview, inverter, PWM

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Authors: Rania A. Aboalela, Javed I. Khan

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This research presents a learning assessment theory of Cognitive Skill in Concept Space (CS2) to measure the assessed knowledge in terms of cognitive skill levels of the concepts. The cognitive skill levels refer to levels such as if a student has acquired the state at the level of understanding, or applying, or analyzing, etc. The theory is comprised of three constructions: Graph paradigm of a semantic/ ontological scheme, the concept states of the theory and the assessment analytics which is the process to estimate the sets of concept state at a certain skill level. Concept state means if a student has already learned, or is ready to learn, or is not ready to learn a certain skill level. The experiment is conducted to prove the validation of the theory CS2.

Keywords: cognitive skill levels, concept states, concept space, knowledge assessment theory

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Authors: Adrian Millea

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In hierarchical reinforcement learning, one of the main issues encountered is the discovery of subgoal states or options (which are policies reaching subgoal states) by partitioning the environment in a meaningful way. This partitioning usually requires an expensive global clustering operation or eigendecomposition of the Laplacian of the states graph. We propose a local solution to this issue, much more efficient than algorithms using global information, which successfully discovers subgoal states by computing a simple function, which we call heterogeneity for each state as a function of its neighbors. Moreover, we construct a value function using the difference in heterogeneity from one step to the next, as reward, such that we are able to explore the state space much more efficiently than say epsilon-greedy. The same principle can then be applied to higher level of the hierarchy, where now states are subgoals discovered at the level below.

Keywords: exploration, hierarchical reinforcement learning, locality, options, value functions

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Authors: Evan Lowhorn, Rocio Alba-Flores

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The purpose of this work is to develop a method for classifying hand signals and using the output in a drone control algorithm. To achieve this, methods based on Convolutional Neural Networks (CNN) were applied. CNN's are a subset of deep learning, which allows grid-like inputs to be processed and passed through a neural network to be trained for classification. This type of neural network allows for classification via imaging, which is less intrusive than previous methods using biosensors, such as EMG sensors. Classification CNN's operate purely from the pixel values in an image; therefore they can be used without additional exteroceptive sensors. A development bench was constructed using a desktop computer connected to a high-definition webcam mounted on a scissor arm. This allowed the camera to be pointed downwards at the desk to provide a constant solid background for the dataset and a clear detection area for the user. A MATLAB script was created to automate dataset image capture at the development bench and save the images to the desktop. This allowed the user to create their own dataset of 12,000 images within three hours. These images were evenly distributed among seven classes. The defined classes include forward, backward, left, right, idle, and land. The drone has a popular flip function which was also included as an additional class. To simplify control, the corresponding hand signals chosen were the numerical hand signs for one through five for movements, a fist for land, and the universal “ok” sign for the flip command. Transfer learning with PyTorch (Python) was performed using a pre-trained 18-layer residual learning network (ResNet-18) to retrain the network for custom classification. An algorithm was created to interpret the classification and send encoded messages to a Ryze Tello drone over its 2.4 GHz Wi-Fi connection. The drone’s movements were performed in half-meter distance increments at a constant speed. When combined with the drone control algorithm, the classification performed as desired with negligible latency when compared to the delay in the drone’s movement commands.

Keywords: classification, computer vision, convolutional neural networks, drone control

Procedia PDF Downloads 195

Authors: Shankha Sanyal, Archi Banerjee, Sayan Biswas, Sourya Sengupta, Sayan Nag, Ranjan Sengupta, Dipak Ghosh

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The term ‘gestalt’ has been widely used in the field of psychology which defined the perception of human mind to group any object not in part but as a 'unified' whole. Music, in general, is polyphonic - i.e. a combination of a number of pure tones (frequencies) mixed together in a manner that sounds harmonious. The study of human brain response due to different frequency groups of the acoustic signal can give us an excellent insight regarding the neural and functional architecture of brain functions. Hence, the study of music cognition using neuro-biosensors is becoming a rapidly emerging field of research. In this work, we have tried to analyze the effect of different frequency bands of music on the various frequency rhythms of human brain obtained from EEG data. Four widely popular Rabindrasangeet clips were subjected to Wavelet Transform method for extracting five resonant frequency bands from the original music signal. These frequency bands were initially analyzed with Detrended/Adaptive Fractal analysis (DFA/AFA) methods. A listening test was conducted on a pool of 100 respondents to assess the frequency band in which the music becomes non-recognizable. Next, these resonant frequency bands were presented to 20 subjects as auditory stimulus and EEG signals recorded simultaneously in 19 different locations of the brain. The recorded EEG signals were noise cleaned and subjected again to DFA/AFA technique on the alpha, theta and gamma frequency range. Thus, we obtained the scaling exponents from the two methods in alpha, theta and gamma EEG rhythms corresponding to different frequency bands of music. From the analysis of music signal, it is seen that loss of recognition is proportional to the loss of long range correlation in the signal. From the EEG signal analysis, we obtain frequency specific arousal based response in different lobes of brain as well as in specific EEG bands corresponding to musical stimuli. In this way, we look to identify a specific frequency band beyond which the music becomes non-recognizable and below which in spite of the absence of other bands the music is perceivable to the audience. This revelation can be of immense importance when it comes to the field of cognitive music therapy and researchers of creativity.

Keywords: AFA, DFA, EEG, gestalt in music, Hurst exponent

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Authors: Haluk Altay, Bilal Yücel, Berkcan Ulcay, Yücel Aydın

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In this study, the design, integration, and testing of measurement systems required for performance tests of jet engines used in small-scale unmanned aerial vehicles are described. Performance tests are carried out as thrust and fuel consumption. For thrust tests, measurements are made using a load cell. Amplifier and filter designs have been made for the load cell to measure accurately to meet the desired sensitivity. It was calibrated by making multiple measurements at different thrust levels. As a result of these processes, the cycle thrust graph was obtained. For fuel consumption tests, tests are carried out using a flow meter. Performance graphics were obtained by finding the fuel consumption for different RPM levels of the engine.

Keywords: jet engine, UAV, experimental test, loadcell, thrust, fuel consumption

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Authors: Chayma Bahar, Chokri Baccouch, Hedi Sakli, Nizar Sakli

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Harvesting and transport of optical and radiofrequency signals are a topical subject with multiple challenges. In this paper, we present a Optical RECTENNA system. We propose here a hybrid system solar cell antenna for 5G mobile communications networks. Thus, we propose rectifying circuit. A parametric study is done to follow the influence of load resistance and input power on Optical RECTENNA system performance. Thus, we propose a solar cell antenna structure in the frequency band of future 5G standard in 2.45 GHz bands.

Keywords: antenna, IoT, optical rectenna, solar cell

Procedia PDF Downloads 168

Authors: Chi-Chang Lin, Jian-Rong Wu, Jiun-Yan Chiu

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Myopia, ubiquitous symptom that is necessary to correct the eyesight by optical lens struggles many people for their daily life. Recent years, younger people raise interesting on using contact lens because of its convenience and aesthetics. In clinical, the risk of eye infections increases owing to the behavior of incorrectly using contact lens unsupervised cleaning which raising the infection risk of cornea, named ocular keratitis. In order to overcome the identification needs, new detection or analysis method with rapid and more accurate identification for clinical microorganism is importantly needed. In our study, we take advantage of Raman spectroscopy having unique fingerprint for different functional groups as the distinct and fast examination tool on microorganism. As we know, Raman scatting signals are normally too weak for the detection, especially in biological field. Here, we applied special SERS enhancement substrates to generate higher Raman signals. SERS filter we designed in this article that prepared by deposition of silver nanoparticles directly onto cellulose filter surface and suspension nanoparticles - gold nanostars (AuNSs) also be introduced together to achieve better enhancement for lower concentration analyte (i.e., various bacteria). Research targets also focusing on studying the shape effect of synthetic AuNSs, needle-like surface morphology may possible creates more hot-spot for getting higher SERS enhance ability. We utilized new designed SERS technology to distinguish the bacteria from ocular keratitis under strain level, and specific Raman and SERS fingerprint were grouped under pattern recognition process. We reported a new method combined different SERS substrates can be applied for clinical microorganism detection under strain level with simple, rapid preparation and low cost. Our presenting SERS technology not only shows the great potential for clinical bacteria detection but also can be used for environmental pollution and food safety analysis.

Keywords: bacteria, gold nanostars, Raman spectroscopy surface-enhanced Raman scattering filter

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Authors: Liudmyla Koliechkina, Olena Dvirna

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The statement of the multi-objective optimization problem on combinatorial configurations is formulated, and the approach to its solution is proposed. The problem is of interest as a combinatorial optimization one with many criteria, which is a model of many applied tasks. The approach to solving the multi-objective optimization problem on combinatorial configurations consists of two stages; the first is the reduction of the multi-objective problem to the single criterion based on existing multi-objective optimization methods, the second stage solves the directly replaced single criterion combinatorial optimization problem by the horizontal combinatorial method. This approach provides the optimal solution to the multi-objective optimization problem on combinatorial configurations, taking into account additional restrictions for a finite number of steps.

Keywords: discrete set, linear combinatorial optimization, multi-objective optimization, Pareto solutions, partial permutation set, structural graph

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Authors: Juliana A. B. Silva, Caio H. T. L. Albuquerque, Leonardo L. dos Santos, Cristiane K. Oliveira, Ivani Malvestiti, Fernando Hallwass, Ricardo L. Longo

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Complexes with lanthanide ions have been extensively studied due to their applications as luminescent, magnetic and catalytic materials as molecular or extended crystals, thin films, glasses, polymeric matrices, ionic liquids, and in solution. NMR chemical shift data in solution have been reported and suggest fluxional structures in a wide range of coordination compounds with rare earth ions. However, the fluxional mechanisms for these compounds are still not established. This structural fluxionality may affect the photophysical, catalytic and magnetic properties in solution. Thus, understanding the structural interconversion mechanisms may aid the design of coordination compounds with, for instance, improved (electro)luminescence, catalytic and magnetic behaviors. The [Eu(btfa)₃bipy] complex, where btfa= 4,4,4-trifluoro-1-phenyl-1,3-butanedionate and bipy= 2,2’-bipiridyl, has a well-defined X-ray crystallographic structure and preliminary 1H NMR data suggested a structural fluxionality. Thus, we have investigated a series of coordination compounds with lanthanide ions [Ln(btfa)₃L], where Ln = La, Eu, Gd or Yb and L= bipy or phen (phen=1,10-phenanthroline) using a combined theoretical-experimental approach. These complexes were synthesized and fully characterized, and detailed NMR measurements were obtained. They were also studied by quantum chemical computational methods (DFT-PBE0). The aim was to determine the relevant factors in the structure of these compounds that favor or not the fluxional behavior. Measurements of the 1H NMR signals at variable temperature in CD₂Cl₂ of the [Eu(btfa)₃L] complexes suggest that these compounds have a fluxional structure, because the crystal structure has non-equivalent btfa ligands that should lead to non-equivalent hydrogen atoms and thus to more signals in the NMR spectra than those obtained at room temperature, where all hydrogen atoms of the btfa ligands are equivalent, and phen ligand has an effective vertical symmetry plane. For the [Eu(btfa)₃bipy] complex, the broadening of the signals at –70°C provides a lower bound for the coalescence temperature, which indicates the energy barriers involved in the structural interconversion mechanisms are quite small. These barriers and, consequently, the coalescence temperature are dependent upon the radii of the lanthanide ion as well as to their paramagnetic effects. The PBE0 calculated structures are in very good agreement with the crystallographic data and, for the [Eu(btfa)₃bipy] complex, this method provided several distinct structures with almost the same energy. However, the energy barrier for structural interconversion via dissociative pathways were found to be quite high and could not explain the experimental observations. Whereas the pseudo-rotation pathways, involving the btfa and bipy ligands, have very small activation barriers, in excellent agreement with the NMR data. The results also showed an increase in the activation barrier along the lanthanide series due to the decrease of the ionic radii and consequent increase of the steric effects. TD-DFT calculations showed a dependence of the ligand donor state energy with different structures of the complex [Eu(btfa)₃phen], which can affect the energy transfer rates and the luminescence. The energy required to promote the structural fluxionality may also enhance the luminescence quenching in solution. These results can aid in the design of more luminescent compounds and more efficient devices.

Keywords: computational chemistry, lanthanide-based compounds, NMR, structural fluxionality

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Authors: Chanon Promsakon, Sayan Panma

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Let S be a finite semigroup, A a subset of S and f an endomorphism on S. The endo-Cayley digraph of a semigroup S corresponding to a connecting set A and an endomorphism f, denoted by endo − Cayf (S, A) is a digraph whose vertex set is S and a vertex u is adjacent to a vertex v if and only if v = f(u)a for some a ∈ A. A digraph D is called undirected if any edge uv in D, there exists an edge vu in D. We consider the undirectedness of an endo-Cayley of a cyclic group of order prime, Zp. In this work, we investigate conditions for connecting sets and endomorphisms to make endo-Cayley digraphs of cyclic groups of order primes be undirected. Moreover, we give some conditions for an undirected endo-Cayley of cycle group of any order.

Keywords: endo-Cayley graph, undirected digraphs, cyclic groups, endomorphism

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Authors: Krongthong Khairiree

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The purpose of this research study is to explore mathematics project-based learning approach and the use of technology in the context of school mathematics in Thailand. Data of the study were collected from 6 sample secondary schools and the students were 6-14 years old. Research findings show that through mathematics project-based learning approach and the use of GSP, students were able to make mathematics learning fun and challenging. Based on the students’ interviews they revealed that, with GSP, they were able to visualize and create graphical representations, which will enable them to develop their mathematical thinking skills, concepts and understanding. The students had fun in creating variety of graphs of functions which they can not do by drawing on graph paper. In addition, there are evidences to show the students’ abilities in connecting mathematics to real life outside the classroom and commercial products, such as weaving, patterning of broomstick, and ceramics design.

Keywords: mathematics, project-based learning, Geometer’s Sketchpad (GSP), commercial products

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Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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The increase in the demand for precision optics, coupled with the absence of much research output in the ultra high precision grinding of precision optics as compared to the ultrahigh precision diamond turning of optical metals has fostered the need for more research in the ultra high precision grinding of an optical lens. Furthermore, the increase in the stringent demands for nanometric surface finishes through lapping, polishing and grinding processes necessary for the use of borosilicate-crown glass in the automotive and optics industries has created the demand to effectively monitor the surface roughness during the production process. Acoustic emission phenomenon has been proven as useful monitoring technique in several manufacturing processes ranging from monitoring of bearing production to tool wear estimation. This paper introduces a rare and unique approach with the application of acoustic emission technique to monitor the surface roughness of borosilicate-crown glass during an ultra high precision grinding process. This research was carried out on a 4-axes Nanoform 250 ultrahigh precision lathe machine using an ultra high precision grinding spindle to machine the flat surface of the borosilicate-crown glass with the tip of the grinding wheel. A careful selection of parameters and design of experiment was implemented using Box-Behnken method to vary the wheel speed, feed rate and depth of cut at three levels with a 3-center point design. Furthermore, the average surface roughness was measured using Taylor Hobson PGI Dimension XL optical profilometer, and an acoustic emission data acquisition device from National Instruments was utilized to acquire the signals while the data acquisition codes were designed with National Instrument LabVIEW software for acquisition at a sampling rate of 2 million samples per second. The results show that the raw and root mean square amplitude values of the acoustic signals increased with a corresponding increase in the measured average surface roughness values for the different parameter combinations. Therefore, this research concludes that acoustic emission monitoring technique is a potential technique for monitoring the surface roughness in the ultra high precision grinding of borosilicate-crown glass.

Keywords: acoustic emission, borosilicate-crown glass, surface roughness, ultra high precision grinding

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Authors: Mohamed Mounir Tellache, Hiroyuki Kambara, Yasuharu Koike, Makoto Miyakoshi, Natsue Yoshimura

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This study explores the practicality of using electroencephalographic (EEG) independent components to predict eight-direction finger movements in pseudo-real-time. Six healthy participants with individual-head MRI images performed finger movements in eight directions with two different arm configurations. The analysis was performed in two stages. The first stage consisted of using independent component analysis (ICA) to separate the signals representing brain activity from non-brain activity signals and to obtain the unmixing matrix. The resulting independent components (ICs) were checked, and those reflecting brain-activity were selected. Finally, the time series of the selected ICs were used to predict eight finger-movement directions using Sparse Logistic Regression (SLR). The second stage consisted of using the previously obtained unmixing matrix, the selected ICs, and the model obtained by applying SLR to classify a different EEG dataset. This method was applied to two different settings, namely the single-participant level and the group-level. For the single-participant level, the EEG dataset used in the first stage and the EEG dataset used in the second stage originated from the same participant. For the group-level, the EEG datasets used in the first stage were constructed by temporally concatenating each combination without repetition of the EEG datasets of five participants out of six, whereas the EEG dataset used in the second stage originated from the remaining participants. The average test classification results across datasets (mean ± S.D.) were 38.62 ± 8.36% for the single-participant, which was significantly higher than the chance level (12.50 ± 0.01%), and 27.26 ± 4.39% for the group-level which was also significantly higher than the chance level (12.49% ± 0.01%). The classification accuracy within [–45°, 45°] of the true direction is 70.03 ± 8.14% for single-participant and 62.63 ± 6.07% for group-level which may be promising for some real-life applications. Clustering and contribution analyses further revealed the brain regions involved in finger movement and the temporal aspect of their contribution to the classification. These results showed the possibility of using the ICA-based method in combination with other methods to build a real-time system to control prostheses.

Keywords: brain-computer interface, electroencephalography, finger motion decoding, independent component analysis, pseudo real-time motion decoding

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Authors: Samaniego Campoverde José Enrique, Rosero Muñoz Jorge Enrique, Luzcando Narea Lorena Elizabeth

Abstract:

This paper presents a practical and theoretical model for the operation of the Tesla coil using digital signal processing. The research is based on the analysis of ten scientific papers exploring the development and operation of the Tesla coil. Starting from the Testa coil, several modifications were carried out on the Tesla coil, with the aim of amplifying the digital signal by making use of digital signal processing. To achieve this, an amplifier with a transistor and digital filters provided by MATLAB software were used, which were chosen according to the characteristics of the signals in question.

Keywords: tesla coil, digital signal process, equalizer, graphical environment

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Authors: Metuku Shyamsunder, Kakarla Subbarao, P. Prasanna

Abstract:

In radars, an electromagnetic waveform is sent, and an echo of the same signal is received by the receiver. From this received signal, by extracting various parameters such as round trip delay, Doppler frequency it is possible to find distance, speed, altitude, etc. However, nowadays as the technology increases, intruders are intercepting transmitted signal as it reaches them, and they will be extracting the characteristics and trying to modify them. So there is a need to develop a system whose signal cannot be identified by no cooperative intercept receivers. That is why LPI radars came into existence. In this paper, a brief discussion on LPI radar and its modulation (polytime code (PT1)), detection (cyclostationary (DFSM & FAM) techniques such as DFSM, FAM are presented and compared with respect to computational complexity.

Keywords: LPI radar, polytime codes, cyclostationary DFSM, FAM

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Authors: Marzieh Ahmadi, Ruhullah Alikhan Gorgani

Abstract:

The usual methods of measuring regional inequalities can not reflect the internal changes of the country in terms of their displacement in different development groups, and the indicators of inequalities are not effective in demonstrating the dynamics of the distribution of inequality. For this purpose, this paper examines the dynamics of the urban inertial transport in the country during the period of 2006-2016 using the CIRD multidimensional index and stochastic kernel density method. it firstly selects 25 indicators in five dimensions including macroeconomic conditions, science and innovation, environmental sustainability, human capital and public facilities, and two-stage Principal Component Analysis methodology are developed to create a composite index of inequality. Then, in the second stage, using a nonparametric analytical approach to internal distribution dynamics and a stochastic kernel density method, the convergence hypothesis of the CIRD index of the Iranian provinces center is tested, and then, based on the ergodic density, long-run equilibrium is shown. Also, at this stage, for the purpose of adopting accurate regional policies, the distribution dynamics and process of convergence or divergence of the Iranian provinces for each of the five. According to the results of the first Stage, in 2006 & 2016, the highest level of development is related to Tehran and zahedan is at the lowest level of development. The results show that the central cities of the country are at the highest level of development due to the effects of Tehran's knowledge spillover and the country's lower cities are at the lowest level of development. The main reason for this may be the lack of access to markets in the border provinces. Based on the results of the second stage, which examines the dynamics of regional inequality transmission in the country during 2006-2016, the first year (2006) is not multifaceted and according to the kernel density graph, the CIRD index of about 70% of the cities. The value is between -1.1 and -0.1. The rest of the sequence on the right is distributed at a level higher than -0.1. In the kernel distribution, a convergence process is observed and the graph points to a single peak. Tends to be a small peak at about 3 but the main peak at about-0.6. According to the chart in the final year (2016), the multidimensional pattern remains and there is no mobility in the lower level groups, but at the higher level, the CIRD index accounts for about 45% of the provinces at about -0.4 Take it. That this year clearly faces the twin density pattern, which indicates that the cities tend to be closely related to each other in terms of development, so that the cities are low in terms of development. Also, according to the distribution dynamics results, the provinces of Iran follow the single-density density pattern in 2006 and the double-peak density pattern in 2016 at low and moderate inequality index levels and also in the development index. The country diverges during the years 2006 to 2016.

Keywords: Urban Disparity, CIRD Index, Convergence, Distribution Dynamics, Random Kernel Density

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Authors: Autumn Rooms Cypres, Barbara Driver

Abstract:

The purpose of this study is to extend discussions about innovations and career politics. Research questions that grounded this effort were: How does an academic learn the unspoken rules of the academy? What happens politically to an academic’s career when their research speaks against the grain of society? Do professors perceive signals that it is time to move on to another institution or even to another career? Epistemology and Methods: This qualitative investigation was focused on examining perceptions of academics. Therefore an open-ended field study, based on Grounded Theory, was used. This naturalistic paradigm (Lincoln & Guba,1985) was selected because it tends to understand information in terms of whole, of patterns, and in relations to the context of the environment. The technique for gathering data was the process of semi-structured, in-depth interviewing. Twenty five academics across the United States were interviewed relative to their career trajectories and the politics and opportunities they have encountered in relation to their research efforts. Findings: The analysis of interviews revealed four themes: Academics are beholden to 2 specific networks of power that influence their sense of job security; the local network based on their employing university and the national network of scholars who share the same field of research. The fights over what counts as research can and does drift from the intellectual to the political, and personal. Academic were able to identify specific instances of shunning and or punishment from their colleagues related directly to the dissemination of research that spoke against the grain of the local or national networks. Academics identified specific signals from both of these networks indicating that their career was flourishing or withering. Implications: This research examined insights from those who persevered when the fights over what and who counts drifted from the intellectual to the political, and the personal. Considerations of why such drifts happen were offered in the form of a socio-political construct called Fit, which included thoughts on hegemony, discourse, and identity. This effort reveals the importance of understanding what professional capital is relative to job security. It also reveals that fear is an enmeshed and often unspoken part of the culture of Academia. Further research to triangulate these findings would be helpful within international contexts.

Keywords: politics, academia, job security, context

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Authors: Brouri Adil, Giri Fouad

Abstract:

The problem of identifying Wiener-Hammerstein systems is addressed in the presence of two linear subsystems of structure totally unknown. Presently, the nonlinear element is allowed to be noninvertible. The system identification problem is dealt by developing a two-stage frequency identification method such a set of points of the nonlinearity are estimated first. Then, the frequency gains of the two linear subsystems are determined at a number of frequencies. The method involves Fourier series decomposition and only requires periodic excitation signals. All involved estimators are shown to be consistent.

Keywords: Wiener-Hammerstein systems, Fourier series expansions, frequency identification, automation science

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