Search results for: wearable patch
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 351

Search results for: wearable patch

111 Quantifying Spatiotemporal Patterns of Past and Future Urbanization Trends in El Paso, Texas and Their Impact on Electricity Consumption

Authors: Joanne Moyer

Abstract:

El Paso, Texas is a southwest border city that has experienced continuous growth within the last 15-years. Understanding the urban growth trends and patterns using data from the National Land Cover Database (NLCD) and landscape metrics, provides a quantitative description of growth. Past urban growth provided a basis to predict 2031 future land-use for El Paso using the CA-Markov model. As a consequence of growth, an increase in demand of resources follows. Using panel data analysis, an understanding of the relation between landscape metrics and electricity consumption is further analyzed. The studies’ findings indicate that past growth focused within three districts within the City of El Paso. The landscape metrics suggest as the city has grown, fragmentation has decreased. Alternatively, the landscape metrics for the projected 2031 land-use indicates possible fragmentation within one of these districts. Panel data suggests electricity consumption and mean patch area landscape metric are positively correlated. The study provides local decision makers to make informed decisions for policies and urban planning to ensure a future sustainable community.

Keywords: landscape metrics, CA-Markov, El Paso, Texas, panel data

Procedia PDF Downloads 105
110 Towards Reliable Mobile Cloud Computing

Authors: Khaled Darwish, Islam El Madahh, Hoda Mohamed, Hadia El Hennawy

Abstract:

Cloud computing has been one of the fastest growing parts in IT industry mainly in the context of the future of the web where computing, communication, and storage services are main services provided for Internet users. Mobile Cloud Computing (MCC) is gaining stream which can be used to extend cloud computing functions, services and results to the world of future mobile applications and enables delivery of a large variety of cloud application to billions of smartphones and wearable devices. This paper describes reliability for MCC by determining the ability of a system or component to function correctly under stated conditions for a specified period of time to be able to deal with the estimation and management of high levels of lifetime engineering uncertainty and risks of failure. The assessment procedures consists of determine Mean Time between Failures (MTBF), Mean Time to Failure (MTTF), and availability percentages for main components in both cloud computing and MCC structures applied on single node OpenStack installation to analyze its performance with different settings governing the behavior of participants. Additionally, we presented several factors have a significant impact on rates of change overall cloud system reliability should be taken into account in order to deliver highly available cloud computing services for mobile consumers.

Keywords: cloud computing, mobile cloud computing, reliability, availability, OpenStack

Procedia PDF Downloads 372
109 Automatic Verification Technology of Virtual Machine Software Patch on IaaS Cloud

Authors: Yoji Yamato

Abstract:

In this paper, we propose an automatic verification technology of software patches for user virtual environments on IaaS Cloud to decrease verification costs of patches. In these days, IaaS services have been spread and many users can customize virtual machines on IaaS Cloud like their own private servers. Regarding to software patches of OS or middleware installed on virtual machines, users need to adopt and verify these patches by themselves. This task increases operation costs of users. Our proposed method replicates user virtual environments, extracts verification test cases for user virtual environments from test case DB, distributes patches to virtual machines on replicated environments and conducts those test cases automatically on replicated environments. We have implemented the proposed method on OpenStack using Jenkins and confirmed the feasibility. Using the implementation, we confirmed the effectiveness of test case creation efforts by our proposed idea of 2-tier abstraction of software functions and test cases. We also evaluated the automatic verification performance of environment replications, test cases extractions and test cases conductions.

Keywords: OpenStack, cloud computing, automatic verification, jenkins

Procedia PDF Downloads 456
108 A Portable Cognitive Tool for Engagement Level and Activity Identification

Authors: Terry Teo, Sun Woh Lye, Yufei Li, Zainuddin Zakaria

Abstract:

Wearable devices such as Electroencephalography (EEG) hold immense potential in the monitoring and assessment of a person’s task engagement. This is especially so in remote or online sites. Research into its use in measuring an individual's cognitive state while performing task activities is therefore expected to increase. Despite the growing number of EEG research into brain functioning activities of a person, key challenges remain in adopting EEG for real-time operations. These include limited portability, long preparation time, high number of channel dimensionality, intrusiveness, as well as level of accuracy in acquiring neurological data. This paper proposes an approach using a 4-6 EEG channels to determine the cognitive states of a subject when undertaking a set of passive and active monitoring tasks of a subject. Air traffic controller (ATC) dynamic-tasks are used as a proxy. The work found that when using the channel reduction and identifier algorithm, good trend adherence of 89.1% can be obtained between a commercially available BCI 14 channel Emotiv EPOC+ EEG headset and that of a carefully selected set of reduced 4-6 channels. The approach can also identify different levels of engagement activities ranging from general monitoring ad hoc and repeated active monitoring activities involving information search, extraction, and memory activities.

Keywords: assessment, neurophysiology, monitoring, EEG

Procedia PDF Downloads 46
107 Image Inpainting Model with Small-Sample Size Based on Generative Adversary Network and Genetic Algorithm

Authors: Jiawen Wang, Qijun Chen

Abstract:

The performance of most machine-learning methods for image inpainting depends on the quantity and quality of the training samples. However, it is very expensive or even impossible to obtain a great number of training samples in many scenarios. In this paper, an image inpainting model based on a generative adversary network (GAN) is constructed for the cases when the number of training samples is small. Firstly, a feature extraction network (F-net) is incorporated into the GAN network to utilize the available information of the inpainting image. The weighted sum of the extracted feature and the random noise acts as the input to the generative network (G-net). The proposed network can be trained well even when the sample size is very small. Secondly, in the phase of the completion for each damaged image, a genetic algorithm is designed to search an optimized noise input for G-net; based on this optimized input, the parameters of the G-net and F-net are further learned (Once the completion for a certain damaged image ends, the parameters restore to its original values obtained in the training phase) to generate an image patch that not only can fill the missing part of the damaged image smoothly but also has visual semantics.

Keywords: image inpainting, generative adversary nets, genetic algorithm, small-sample size

Procedia PDF Downloads 102
106 Mobile Systems: History, Technology, and Future

Authors: Shivendra Pratap Singh, Rishabh Sharma

Abstract:

The widespread adoption of mobile technology in recent years has revolutionized the way we communicate and access information. The evolution of mobile systems has been rapid and impactful, shaping our lives and changing the way we live and work. However, despite its significant influence, the history and development of mobile technology are not well understood by the general public. This research paper aims to examine the history, technology and future of mobile systems, exploring their evolution from early mobile phones to the latest smartphones and beyond. The study will analyze the technological advancements and innovations that have shaped the mobile industry, from the introduction of mobile internet and multimedia capabilities to the integration of artificial intelligence and 5G networks. Additionally, the paper will also address the challenges and opportunities facing the future of mobile technology, such as privacy concerns, battery life, and the increasing demand for high-speed internet. Finally, the paper will also provide insights into potential future developments and innovations in the mobile sector, such as foldable phones, wearable technology, and the Internet of Things (IoT). The purpose of this research paper is to provide a comprehensive overview of the history, technology, and future of mobile systems, shedding light on their impact on society and the challenges and opportunities that lie ahead.

Keywords: mobile technology, artificial intelligence, networking, iot, technological advancements, smartphones

Procedia PDF Downloads 54
105 Lightweight Hybrid Convolutional and Recurrent Neural Networks for Wearable Sensor Based Human Activity Recognition

Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

Abstract:

Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

Procedia PDF Downloads 117
104 Influence of the 3D Printing Parameters on the Dynamic Characteristics of Composite Structures

Authors: Ali Raza, Rūta Rimašauskienė

Abstract:

In the current work, the fused deposition modelling (FDM) technique is used to manufacture PLA reinforced with carbon fibre composite structures with two unique layer patterns, 0°\0° and 0°\90°. The purpose of the study is to investigate the dynamic characteristics of each fabricated composite structure. The Macro Fiber Composite (MFC) is embedded with 0°/0° and 0°/90° structures to investigate the effect of an MFC (M8507-P2 type) patch on vibration amplitude suppression under dynamic loading circumstances. First, modal analysis testing was performed using a Polytec 3D laser vibrometer to identify bending mode shapes, natural frequencies, and vibration amplitudes at the corresponding natural frequencies. To determine the stiffness of each structure, several loads were applied at the free end of the structure, and the deformation was recorded using a laser displacement sensor. The findings confirm that a structure with 0°\0° layers pattern was found to have more stiffness compared to a 0°\90° structure. The maximum amplitude suppression in each structure was measured using a laser displacement sensor at the first resonant frequency when the control voltage signal with optimal phase was applied to the MFC. The results confirm that the 0°/0° pattern's structure exhibits a higher displacement reduction than the 0°/90° pattern. Moreover, stiffer structures have been found to perform amplitude suppression more effectively.

Keywords: carbon fibre composite, MFC, modal analysis stiffness, stiffness

Procedia PDF Downloads 27
103 Smart Material for Bacterial Detection Based on Polydiacetylene/Polyvinyl Butyrate Fiber Composites

Authors: Pablo Vidal, Misael Martinez, Carlos Hernandez, Ananta R. Adhikari, Luis Materon, Yuanbing Mao, Karen Lozano

Abstract:

Conjugated polymers are smart materials that show tremendous practical applications in diverse subjects. Polydiacetylenes are conjugated polymers with special optical properties. In response to the environmental changes such as pH and molecular binding, it changes its color. Such an interesting chromic and emissive behavior of polydiacetylenes make them a highly popular polymer in wide areas, including biomedicine such as a biosensor. In this research, we used polyvinyl butyrate as a matrix to fibrillate polydiacetylenes. We initially prepared polyvinyl butyrate/diacetylene matrix using forcespinning technique. They were then polymerized to form polyvinyl butyrate/polydiacetylene (PVB/PDA). These matrices then studied for their bio-sensing response to gram-positive and gram-negative bacteria. The sensing ability of the PVB/PDA biosensor was observed as early as 30 min in the presence of bacteria at 37°C. Now our effort is to decrease this effective temperature to room temperature to make this device applicable in the general daily life. These chromic biosensors will find extensive application not only alert the infection but also find other promising applications such as wearable sensors and diagnostic systems.

Keywords: smart material, conjugated polymers, biosensor, polyvinyl butyrate/polydiacetylene

Procedia PDF Downloads 100
102 Developing Artificial Neural Networks (ANN) for Falls Detection

Authors: Nantakrit Yodpijit, Teppakorn Sittiwanchai

Abstract:

The number of older adults is rising rapidly. The world’s population becomes aging. Falls is one of common and major health problems in the elderly. Falls may lead to acute and chronic injuries and deaths. The fall-prone individuals are at greater risk for decreased quality of life, lowered productivity and poverty, social problems, and additional health problems. A number of studies on falls prevention using fall detection system have been conducted. Many available technologies for fall detection system are laboratory-based and can incur substantial costs for falls prevention. The utilization of alternative technologies can potentially reduce costs. This paper presents the new design and development of a wearable-based fall detection system using an Accelerometer and Gyroscope as motion sensors for the detection of body orientation and movement. Algorithms are developed to differentiate between Activities of Daily Living (ADL) and falls by comparing Threshold-based values with Artificial Neural Networks (ANN). Results indicate the possibility of using the new threshold-based method with neural network algorithm to reduce the number of false positive (false alarm) and improve the accuracy of fall detection system.

Keywords: aging, algorithm, artificial neural networks (ANN), fall detection system, motion sensorsthreshold

Procedia PDF Downloads 468
101 Lamb Waves Propagation in Elastic-Viscoelastic Three-Layer Adhesive Joints

Authors: Pezhman Taghipour Birgani, Mehdi Shekarzadeh

Abstract:

In this paper, the propagation of lamb waves in three-layer joints is investigated using global matrix method. Theoretical boundary value problem in three-layer adhesive joints with perfect bond and traction free boundary conditions on their outer surfaces is solved to find a combination of frequencies and modes with the lowest attenuation. The characteristic equation is derived by applying continuity and boundary conditions in three-layer joints using global matrix method. Attenuation and phase velocity dispersion curves are obtained with numerical solution of this equation by a computer code for a three-layer joint, including an aluminum repair patch bonded to the aircraft aluminum skin by a layer of viscoelastic epoxy adhesive. To validate the numerical solution results of the characteristic equation, wave structure curves are plotted for a special mode in two different frequencies in the adhesive joint. The purpose of present paper is to find a combination of frequencies and modes with minimum attenuation in high and low frequencies. These frequencies and modes are recognizable by transducers in inspections with Lamb waves because of low attenuation level.

Keywords: three-layer adhesive joints, viscoelastic, lamb waves, global matrix method

Procedia PDF Downloads 366
100 Field-Programmable Gate Arrays Based High-Efficiency Oriented Fast and Rotated Binary Robust Independent Elementary Feature Extraction Method Using Feature Zone Strategy

Authors: Huang Bai-Cheng

Abstract:

When deploying the Oriented Fast and Rotated Binary Robust Independent Elementary Feature (BRIEF) (ORB) extraction algorithm on field-programmable gate arrays (FPGA), the access of global storage for 31×31 pixel patches of the features has become the bottleneck of the system efficiency. Therefore, a feature zone strategy has been proposed. Zones are searched as features are detected. Pixels around the feature zones are extracted from global memory and distributed into patches corresponding to feature coordinates. The proposed FPGA structure is targeted on a Xilinx FPGA development board of Zynq UltraScale+ series, and multiple datasets are tested. Compared with the streaming pixel patch extraction method, the proposed architecture obtains at least two times acceleration consuming extra 3.82% Flip-Flops (FFs) and 7.78% Look-Up Tables (LUTs). Compared with the non-streaming one, the proposed architecture saves 22.3% LUT and 1.82% FF, causing a latency of only 0.2ms and a drop in frame rate for 1. Compared with the related works, the proposed strategy and hardware architecture have the superiority of keeping a balance between FPGA resources and performance.

Keywords: feature extraction, real-time, ORB, FPGA implementation

Procedia PDF Downloads 89
99 Dynamic Analysis and Design of Lower Extremity Power-Assisted Exoskeleton

Authors: Song Shengli, Tan Zhitao, Li Qing, Fang Husheng, Ye Qing, Zhang Xinglong

Abstract:

Lower extremity power-assisted exoskeleton (LEPEX) is a kind of wearable electromechanical integration intelligent system, walking in synchronization with the wearer, which can assist the wearer walk by means of the driver mounted in the exoskeleton on each joint. In this paper, dynamic analysis and design of the LEPEX are performed. First of all, human walking process is divided into single leg support phase, double legs support phase and ground collision model. The three kinds of dynamics modeling is established using the Lagrange method. Then, the flat walking and climbing stairs dynamic information such as torque and power of lower extremity joints is derived for loading 75kg according to scholar Stansfield measured data of flat walking and scholars R. Riener measured data of climbing stair respectively. On this basis, the joint drive way in the sagittal plane is determined, and the structure of LEPEX is designed. Finally, the designed LEPEX is simulated under ADAMS by using a person’s joint sports information acquired under flat walking and climbing stairs. The simulation result effectively verified the correctness of the structure.

Keywords: kinematics, lower extremity exoskeleton, simulation, structure

Procedia PDF Downloads 400
98 Altered L-Type Calcium Channel Activity in Atrioventricular Nodal Myocytes from Rats with Streptozotocin-Induced Type I Diabetes Mellitus

Authors: Kathryn H. Yull, Lina T. Al Kury, Frank Christopher Howarth

Abstract:

Cardiovascular diseases are frequently reported in patients with Type-1 Diabetes mellitus (DM). In addition to changes in cardiac muscle inotropy, electrical abnormalities are also commonly observed in these patients. In the present study, using streptozotocin (STZ) rat model of Type-1 DM, we have characterized the changes in L-type calcium channel activity in single atrioventricular nodal (AVN) myocytes. Ionic currents were recorded from AVN myocytes isolated from the hearts of control rats and from those with STZ-induced diabetes. Patch-clamp recordings were used to assess changes in cellular electrical activity in individual myocytes. Type-1 DM significantly altered the cellular characteristics of L-type calcium current (ICaL). A reduction in peak ICaL density was observed, with no corresponding changes in the activation parameters of the current. ICaL also exhibited faster time-dependent inactivation in AVN myocytes from diabetic rats. A negative shift in the voltage dependence of inactivation was also evident. These findings demonstrate that experimentally–induced type-1 DM significantly alters AVN L-type calcium channel cellular electrophysiology. The changes in ion channel activity may underlie the abnormalities in the cardiac electrical function that contribute to the high mortality levels in patients with DM.

Keywords: cardiac, ion-channel, diabetes, atrioventricular node, calcium channel

Procedia PDF Downloads 311
97 Hand Gesture Interpretation Using Sensing Glove Integrated with Machine Learning Algorithms

Authors: Aqsa Ali, Aleem Mushtaq, Attaullah Memon, Monna

Abstract:

In this paper, we present a low cost design for a smart glove that can perform sign language recognition to assist the speech impaired people. Specifically, we have designed and developed an Assistive Hand Gesture Interpreter that recognizes hand movements relevant to the American Sign Language (ASL) and translates them into text for display on a Thin-Film-Transistor Liquid Crystal Display (TFT LCD) screen as well as synthetic speech. Linear Bayes Classifiers and Multilayer Neural Networks have been used to classify 11 feature vectors obtained from the sensors on the glove into one of the 27 ASL alphabets and a predefined gesture for space. Three types of features are used; bending using six bend sensors, orientation in three dimensions using accelerometers and contacts at vital points using contact sensors. To gauge the performance of the presented design, the training database was prepared using five volunteers. The accuracy of the current version on the prepared dataset was found to be up to 99.3% for target user. The solution combines electronics, e-textile technology, sensor technology, embedded system and machine learning techniques to build a low cost wearable glove that is scrupulous, elegant and portable.

Keywords: American sign language, assistive hand gesture interpreter, human-machine interface, machine learning, sensing glove

Procedia PDF Downloads 261
96 Enhancing Urban Sustainability through Integrated Green Spaces: A Focus on Tehran

Authors: Azadeh Mohajer Milani

Abstract:

Urbanization constitutes an irreversible global trend, presenting myriad challenges such as heightened energy consumption, pollution, congestion, and the depletion of natural resources. Today's urban landscapes have emerged as focal points for economic, social, and environmental challenges, underscoring the pressing need for sustainable development. This article delves into the realm of sustainable urban development, concentrating on the pivotal role played by integrated green spaces as an optimal solution to address environmental concerns within cities. The study utilizes Tehran as a case study. Our findings underscore the imperative of preserving and expanding green spaces in urban areas, coupled with the establishment of well-designed ecological networks, to enhance environmental quality and elevate the sustainability of cities. Notably, Tehran's urban green spaces exhibit a disjointed design, lacking a cohesive network to connect various patches and corridors, resulting in significant environmental impacts. The results emphasize the necessity of a balanced and proportional distribution of urban green spaces and the creation of a cohesive patch-corridor-matrix network tailored to the ecological and social needs of residents. This approach is crucial for fostering a more sustainable and livable urban environment for all species, with a specific focus on humans.

Keywords: ecology, sustainable urban development, sustainable landscape, urban green space network

Procedia PDF Downloads 35
95 Optimal Sliding Mode Controller for Knee Flexion during Walking

Authors: Gabriel Sitler, Yousef Sardahi, Asad Salem

Abstract:

This paper presents an optimal and robust sliding mode controller (SMC) to regulate the position of the knee joint angle for patients suffering from knee injuries. The controller imitates the role of active orthoses that produce the joint torques required to overcome gravity and loading forces and regain natural human movements. To this end, a mathematical model of the shank, the lower part of the leg, is derived first and then used for the control system design and computer simulations. The design of the controller is carried out in optimal and multi-objective settings. Four objectives are considered: minimization of the control effort and tracking error; and maximization of the control signal smoothness and closed-loop system’s speed of response. Optimal solutions in terms of the Pareto set and its image, the Pareto front, are obtained. The results show that there are trade-offs among the design objectives and many optimal solutions from which the decision-maker can choose to implement. Also, computer simulations conducted at different points from the Pareto set and assuming knee squat movement demonstrate competing relationships among the design goals. In addition, the proposed control algorithm shows robustness in tracking a standard gait signal when accounting for uncertainty in the shank’s parameters.

Keywords: optimal control, multi-objective optimization, sliding mode control, wearable knee exoskeletons

Procedia PDF Downloads 47
94 The Impact of Artificial Intelligence in the Development of Textile and Fashion Industry

Authors: Basem Kamal Abasakhiroun Farag

Abstract:

Fashion, like many other areas of design, has undergone numerous developments over the centuries. The aim of the article is to recognize and evaluate the importance of advanced technologies in fashion design and to examine how they are transforming the role of contemporary fashion designers by transforming the creative process. It also discusses how contemporary culture is involved in such developments and how it influences fashion design in terms of conceptualization and production. The methodology used is based on examining various examples of the use of technology in fashion design and drawing parallels between what was feasible then and what is feasible today. Comparison of case studies, examples of existing fashion designs and experiences with craft methods; We therefore observe patterns that help us predict the direction of future developments in this area. Discussing the technological elements in fashion design helps us understand the driving force behind the trend. The research presented in the article shows that there is a trend towards significantly increasing interest and progress in the field of fashion technology, leading to the emergence of hybrid artisanal methods. In summary, as fashion technologies advance, their role in clothing production is becoming increasingly important, extending far beyond the humble sewing machine.

Keywords: fashion, identity, such, textiles ambient intelligence, proximity sensors, shape memory materials, sound sensing garments, wearable technology bio textiles, fashion trends, nano textiles, new materials, smart textiles, techno textiles fashion design, functional aesthetics, 3D printing.

Procedia PDF Downloads 22
93 Gradient Index Metalens for WLAN Applications

Authors: Akram Boubakri, Fethi Choubeni, Tan Hoa Vuong, Jacques David

Abstract:

The control of electromagnetic waves is a key aim of several researches over the past decade. In this regard, Metamaterials have shown a strong ability to manipulate the electromagnetic waves on a subwavelength scales thanks to its unconventional properties that are not available in natural materials such as negative refraction index, super imaging and invisibility cloaking. Metalenses were used to avoid some drawbacks presented by conventional lenses since focusing with conventional lenses suffered from the limited resolution because they were only able to focus the propagating wave component. Nevertheless, Metalenses were able to go beyond the diffraction limit and enhance the resolution not only by collecting the propagating waves but also by restoring the amplitude of evanescent waves that decay rapidly when going far from the source and that contains the finest details of the image. Metasurfaces have many mechanical advantages over three-dimensional metamaterial structures especially the ease of fabrication and a smaller required volume. Those structures have been widely used for antenna performance improvement and to build flat metalenses. In this work, we showed that a well-designed metasurface lens operating at the frequency of 5.9GHz, has efficiently enhanced the radiation characteristics of a patch antenna and can be used for WLAN applications (IEEE 802.11 a). The proposed metasurface lens is built with a geometrically modified unit cells which lead to a change in the response of the lens at different position and allow the control of the wavefront beam of the incident wave thanks to the gradient refractive index.

Keywords: focusing, gradient index, metasurface, metalens, WLAN Applications

Procedia PDF Downloads 227
92 Determining the Effects of Wind-Aided Midge Movement on the Probability of Coexistence of Multiple Bluetongue Virus Serotypes in Patchy Environments

Authors: Francis Mugabi, Kevin Duffy, Joseph J. Y. T Mugisha, Obiora Collins

Abstract:

Bluetongue virus (BTV) has 27 serotypes, with some of them coexisting in patchy (different) environments, which make its control difficult. Wind-aided midge movement is a known mechanism in the spread of BTV. However, its effects on the probability of coexistence of multiple BTV serotypes are not clear. Deterministic and stochastic models for r BTV serotypes in n discrete patches connected by midge and/or cattle movement are formulated and analyzed. For the deterministic model without midge and cattle movement, using the comparison principle, it is shown that if the patch reproduction number R0 < 1, i=1,2,...,n, j=1,2,...,r, all serotypes go extinct. If R^j_i0>1, competitive exclusion takes place. Using numerical simulations, it is shown that when the n patches are connected by midge movement, coexistence takes place. To account for demographic and movement variability, the deterministic model is transformed into a continuous-time Markov chain stochastic model. Utilizing a multitype branching process, it is shown that the midge movement can have a large effect on the probability of coexistence of multiple BTV serotypes. The probability of coexistence can be brought to zero when the control interventions that directly kill the adult midges are applied. These results indicate the significance of wind-aided midge movement and vector control interventions on the coexistence and control of multiple BTV serotypes in patchy environments.

Keywords: bluetongue virus, coexistence, multiple serotypes, midge movement, branching process

Procedia PDF Downloads 118
91 Hierarchical Optimization of Composite Deployable Bridge Treadway Using Particle Swarm Optimization

Authors: Ashraf Osman

Abstract:

Effective deployable bridges that are characterized by an increased capacity to weight ratio are recently needed for post-disaster rapid mobility and military operations. In deployable bridging, replacing metals as the fabricating material with advanced composite laminates as lighter alternatives with higher strength is highly advantageous. This article presents a hierarchical optimization strategy of a composite bridge treadway considering maximum strength design and bridge weight minimization. Shape optimization of a generic deployable bridge beam cross-section is performed to achieve better stress distribution over the bridge treadway hull. The developed cross-section weight is minimized up to reserving the margins of safety of the deployable bridging code provisions. Hence, the strength of composite bridge plates is maximized through varying the plies orientation. Different loading cases are considered of a tracked vehicle patch load. The orthotropic plate properties of a composite sandwich core are used to simulate the bridge deck structural behavior. Whereas, the failure analysis is conducted using Tsai-Wu failure criterion. The naturally inspired particle swarm optimization technique is used in this study. The proposed technique efficiently reduced the weight to capacity ratio of the developed bridge beam.

Keywords: CFRP deployable bridges, disaster relief, military bridging, optimization of composites, particle swarm optimization

Procedia PDF Downloads 113
90 Impact of Integrated Signals for Doing Human Activity Recognition Using Deep Learning Models

Authors: Milagros Jaén-Vargas, Javier García Martínez, Karla Miriam Reyes Leiva, María Fernanda Trujillo-Guerrero, Francisco Fernandes, Sérgio Barroso Gonçalves, Miguel Tavares Silva, Daniel Simões Lopes, José Javier Serrano Olmedo

Abstract:

Human Activity Recognition (HAR) is having a growing impact in creating new applications and is responsible for emerging new technologies. Also, the use of wearable sensors is an important key to exploring the human body's behavior when performing activities. Hence, the use of these dispositive is less invasive and the person is more comfortable. In this study, a database that includes three activities is used. The activities were acquired from inertial measurement unit sensors (IMU) and motion capture systems (MOCAP). The main objective is differentiating the performance from four Deep Learning (DL) models: Deep Neural Network (DNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and hybrid model Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), when considering acceleration, velocity and position and evaluate if integrating the IMU acceleration to obtain velocity and position represent an increment in performance when it works as input to the DL models. Moreover, compared with the same type of data provided by the MOCAP system. Despite the acceleration data is cleaned when integrating, results show a minimal increase in accuracy for the integrated signals.

Keywords: HAR, IMU, MOCAP, acceleration, velocity, position, feature maps

Procedia PDF Downloads 54
89 Improved Embroidery Based Textile Electrodes for Sustainability of Impedance Measurement Characteristics

Authors: Bulcha Belay Etana

Abstract:

Research shows that several challenges are to be resolved for textile sensors and wearable smart textiles systems to make it accurate and reproducible minimizing variability issues when tested. To achieve this, we developed stimulating embroidery electrode with three different filling textiles such as 3Dknit, microfiber, and nonwoven fabric, and tested with FTT for high recoverability on compression. Hence The impedance characteristics of wetted electrodes were caried out after 1hr of wetting under normal environmental conditions. The wetted 3D knit (W-3D knit), Wetted nonwoven (W-nonwoven), and wetted microfiber (W-microfiber) developed using Satin stitch performed better than a dry standard stitch or dry Satin stitch electrodes. Its performance was almost the same as that of the gel electrode (Ag/AgCl) as shown by the impedance result in figure 2 .The impedance characteristics of Dry and wetted 3D knit based Embroidered electrodes are better than that of the microfiber, and nonwoven filling textile. This is due to the fact that 3D knit fabric has high recoverability on compression to retain electrolyte gel than microfiber, and nonwoven. However,The non-woven fabric held the electrolyte for longer time without releasing it to the skin when needed, thus making its impedance characteristics poor as observed from the results. Whereas the dry Satin stitch performs better than the standard stitch based developed electrode. The inter electrode distance of all types of the electrode was 25mm, with the area of the electrode being 20mm by 20mm. Detail evaluation and further analysis is in progress for EMG monitoring application

Keywords: impedance, moisture retention, 3D knit fabric, microfiber, nonwoven

Procedia PDF Downloads 102
88 Performance Comparison of Resource Allocation without Feedback in Wireless Body Area Networks by Various Pseudo Orthogonal Sequences

Authors: Ojin Kwon, Yong-Jin Yoon, Liu Xin, Zhang Hongbao

Abstract:

Wireless Body Area Network (WBAN) is a short-range wireless communication around human body for various applications such as wearable devices, entertainment, military, and especially medical devices. WBAN attracts the attention of continuous health monitoring system including diagnostic procedure, early detection of abnormal conditions, and prevention of emergency situations. Compared to cellular network, WBAN system is more difficult to control inter- and inner-cell interference due to the limited power, limited calculation capability, mobility of patient, and non-cooperation among WBANs. In this paper, we compare the performance of resource allocation scheme based on several Pseudo Orthogonal Codewords (POCs) to mitigate inter-WBAN interference. Previously, the POCs are widely exploited for a protocol sequence and optical orthogonal code. Each POCs have different properties of auto- and cross-correlation and spectral efficiency according to its construction of POCs. To identify different WBANs, several different pseudo orthogonal patterns based on POCs exploits for resource allocation of WBANs. By simulating these pseudo orthogonal resource allocations of WBANs on MATLAB, we obtain the performance of WBANs according to different POCs and can analyze and evaluate the suitability of POCs for the resource allocation in the WBANs system.

Keywords: wireless body area network, body sensor network, resource allocation without feedback, interference mitigation, pseudo orthogonal pattern

Procedia PDF Downloads 322
87 Optimization of a Flexible Thermoelectric Generator for Energy Harvesting from Human Skin to Power Wearable Electronics

Authors: Dessalegn Abera Waktole, Boru Jia, Zhengxing Zuo, Wei Wang, Nianling Kuang

Abstract:

A flexible thermoelectric generator is one method for recycling waste heat. This research provides the optimum performance of a flexible thermoelectric generator with optimal geometric parameters and a detailed structural design. In this research, a numerical simulation and experiment were carried out to develop an efficient, flexible thermoelectric generator for energy harvesting from human skin. Heteromorphic electrodes and a polyimide substrate with a copper-printed circuit board were introduced into the structural design of a flexible thermoelectric generator. The heteromorphic electrode was used as a heat sink and component of a flexible thermoelectric generator to enhance the temperature difference within the thermoelectric legs. Both N-type and P-type thermoelectric legs were made of bismuth selenium telluride (Bi1.7Te3.7Se0.3) and bismuth antimony telluride (Bi0.4Sb1.6Te3). The output power of the flexible thermoelectric generator was analyzed under different heat source temperatures and heat dissipation conditions. The COMSOL Multiphysics 5.6 software was used to conduct the simulation, which was validated by experiment. It is recorded that the maximum power output of 232.064μW was obtained by considering different wind speed conditions, the ambient temperature of 20℃, and the heat source temperature of 36℃ under various load resistance conditions, which range from 0.24Ω to 0. 91Ω. According to this finding, heteromorphic electrodes have a significant impact on the performance of the device.

Keywords: flexible thermoelectric generator, optimization, performance, temperature gradient, waste heat recovery

Procedia PDF Downloads 90
86 Study of 'Rolled in Scale' and 'Rolled in Scum' in Automotive Grade Cold-Rolled Annealed Steel Sheet

Authors: Soumendu Monia, Vaibhav Jain, Hrishikesh Jugade, Manashi Adhikary, Goutam Mukhopadhyay

Abstract:

'Rolled in scale' (RIS) and 'Rolled in Scum' (RISc) are two superficial surface defects on cold rolled and annealed steel sheets which affect the aesthetics of surface and thereby that of the end-product. Both the defects are believed to be originating from distinctly different sources having different mechanisms of formation. However, due to their similar physical appearance, RIS and RISc are generally confused with each other and hence attaining the exact root cause for elimination of the defect becomes difficult. RIS appears irregular in shape, sometimes scattered, and always oriented in rolling direction. RISc is generally oval shaped, having identifiable pointed edges and mostly oriented in rolling direction. Visually, RIS appears to be greyish in colour whereas RISc is whitish in colour. Both the defects have quite random occurrence and do not leave any imprints on the reverse-side of the sheet. In the current study, an attempt has been made to differentiate these two similar looking surface defects using various metallographic and characterization techniques. Systematic experiments have been carried out to identify possible mechanisms of formation of these defects. Detailed characterization revealed basic differences between RIS and RISc with respect to their surface morphology. To summarize, RIS was observed as a residue of an otherwise under-pickled scale patch on surface, after it has been subjected to cold rolling and annealing in a batch/continuous furnace. Whereas RISc was found to be a localized rubbing of the surface, at the time of cold rolling itself, resulting in a rough surface texture.

Keywords: annealing, rolled in scale, rolled in scum, skin panel

Procedia PDF Downloads 146
85 Electrospun Alginate Nanofibers Containing Spirulina Extract Double-Layered with Polycaprolactone Nanofibers

Authors: Seon Yeong Byeon, Hwa Sung Shin

Abstract:

Nanofibrous sheets are of interest in the beauty industries due to the properties of moisturizing, adhesion to skin and delivery of nutrient materials. The benefit and function of the cosmetic products should not be considered without safety thus a non-toxic manufacturing process is ideal when fabricating the products. In this study, we have developed cosmetic patches consisting of alginate and Spirulina extract, a marine resource which has antibacterial and antioxidant effects, without addition of harmful cross-linkers. The patches obtained their structural stabilities by layer-upon-layer electrospinning of an alginate layer on a formerly spread polycaprolactone (PCL) layer instead of crosslinking method. The morphological characteristics, release of Spirulina extract, water absorption, skin adhesiveness and cytotoxicity of the double-layered patches were assessed. The image of scanning electron microscopy (SEM) showed that the addition of Spirulina extract has made the fiber diameter of alginate layers thinner. Impregnation of Spirulina extract increased their hydrophilicity, moisture absorption ability and skin adhesive ability. In addition, wetting the pre-dried patches resulted in releasing the Spirulina extract within 30 min. The patches were detected to have no cytotoxicity in the human keratinocyte cell-based MTT assay, but rather showed increased cell viability. All the results indicate the bioactive and hydro-adhesive double-layered patches have an excellent applicability to bioproducts for personal skin care in the trend of ‘A mask pack a day’.

Keywords: alginate, cosmetic patch, electrospun nanofiber, polycaprolactone, Spirulina extract

Procedia PDF Downloads 318
84 Enabling Oral Communication and Accelerating Recovery: The Creation of a Novel Low-Cost Electroencephalography-Based Brain-Computer Interface for the Differently Abled

Authors: Rishabh Ambavanekar

Abstract:

Expressive Aphasia (EA) is an oral disability, common among stroke victims, in which the Broca’s area of the brain is damaged, interfering with verbal communication abilities. EA currently has no technological solutions and its only current viable solutions are inefficient or only available to the affluent. This prompts the need for an affordable, innovative solution to facilitate recovery and assist in speech generation. This project proposes a novel concept: using a wearable low-cost electroencephalography (EEG) device-based brain-computer interface (BCI) to translate a user’s inner dialogue into words. A low-cost EEG device was developed and found to be 10 to 100 times less expensive than any current EEG device on the market. As part of the BCI, a machine learning (ML) model was developed and trained using the EEG data. Two stages of testing were conducted to analyze the effectiveness of the device: a proof-of-concept and a final solution test. The proof-of-concept test demonstrated an average accuracy of above 90% and the final solution test demonstrated an average accuracy of above 75%. These two successful tests were used as a basis to demonstrate the viability of BCI research in developing lower-cost verbal communication devices. Additionally, the device proved to not only enable users to verbally communicate but has the potential to also assist in accelerated recovery from the disorder.

Keywords: neurotechnology, brain-computer interface, neuroscience, human-machine interface, BCI, HMI, aphasia, verbal disability, stroke, low-cost, machine learning, ML, image recognition, EEG, signal analysis

Procedia PDF Downloads 94
83 A Literature Review on Emotion Recognition Using Wireless Body Area Network

Authors: Christodoulou Christos, Politis Anastasios

Abstract:

The utilization of Wireless Body Area Network (WBAN) is experiencing a notable surge in popularity as a result of its widespread implementation in the field of smart health. WBANs utilize small sensors implanted within the human body to monitor and record physiological indicators. These sensors transmit the collected data to hospitals and healthcare facilities through designated access points. Bio-sensors exhibit a diverse array of shapes and sizes, and their deployment can be tailored to the condition of the individual. Multiple sensors may be strategically placed within, on, or around the human body to effectively observe, record, and transmit essential physiological indicators. These measurements serve as a basis for subsequent analysis, evaluation, and therapeutic interventions. In conjunction with physical health concerns, numerous smartwatches are engineered to employ artificial intelligence techniques for the purpose of detecting mental health conditions such as depression and anxiety. The utilization of smartwatches serves as a secure and cost-effective solution for monitoring mental health. Physiological signals are widely regarded as a highly dependable method for the recognition of emotions due to the inherent inability of individuals to deliberately influence them over extended periods of time. The techniques that WBANs employ to recognize emotions are thoroughly examined in this article.

Keywords: emotion recognition, wireless body area network, WBAN, ERC, wearable devices, psychological signals, emotion, smart-watch, prediction

Procedia PDF Downloads 21
82 Near-Infrared Optogenetic Manipulation of a Channelrhodopsin via Upconverting Nanoparticles

Authors: Kanchan Yadav, Ai-Chuan Chou, Rajesh Kumar Ulaganathan, Hua-De Gao, Hsien-Ming Lee, Chien-Yuan Pan, Yit-Tsong Chen

Abstract:

Optogenetics is an innovative technology now widely adopted by researchers in different fields of the biological sciences. However, due to the weak tissue penetration capability of the short wavelengths used to activate light-sensitive proteins, an invasive light guide has been used in animal studies for photoexcitation of target tissues. Upconverting nanoparticles (UCNPs), which transform near-infrared (NIR) light to short-wavelength emissions, can help address this issue. To improve optogenetic performance, we enhance the target selectivity for optogenetic controls by specifically conjugating the UCNPs with light-sensitive proteins at a molecular level, which shortens the distance as well as enhances the efficiency of energy transfer. We tagged V5 and Lumio epitopes to the extracellular N-terminal of channelrhodopsin-2 with an mCherry conjugated at the intracellular C-terminal (VL-ChR2m) and then bound NeutrAvidin-functionalized UCNPs (NAv-UCNPs) to the VL-ChR2m via a biotinylated antibody against V5 (bV5-Ab). We observed an apparent energy transfer from the excited UCNP (donor) to the bound VL-ChR2m (receptor) by measuring emission-intensity changes at the donor-receptor complex. The successful patch-clamp electrophysiological test and an intracellular Ca2+ elevation observed in the designed UCNP-ChR2 system under optogenetic manipulation confirmed the practical employment of UCNP-assisted NIR-optogenetic functionality. This work represents a significant step toward improving therapeutic optogenetics.

Keywords: Channelrhodopsin-2, near infrared, optogenetics, upconverting nanoparticles

Procedia PDF Downloads 252