Search results for: location quotients model

Authors: Visith Siriphuwanun, Yodying Punjasawadwong, Suwinai Saengyo, Kittipan Rerkasem

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Objective: To determine incidences and factors associated with perioperative cardiac arrest in trauma patients who received anesthesia for emergency surgery. Design and setting: Retrospective cohort study in trauma patients during anesthesia for emergency surgery at a university hospital in northern Thailand country. Patients and methods: This study was permitted by the medical ethical committee, Faculty of Medicine at Maharaj Nakorn Chiang Mai Hospital, Thailand. We clarified data of 19,683 trauma patients receiving anesthesia within a decade between January 2007 to March 2016. The data analyzed patient characteristics, traumas surgery procedures, anesthesia information such as ASA physical status classification, anesthesia techniques, anesthetic drugs, location of anesthesia performed, and cardiac arrest outcomes. This study excluded the data of trauma patients who had received local anesthesia by surgeons or monitoring anesthesia care (MAC) and the patient which missing more information. The factor associated with perioperative cardiac arrest was identified with univariate analyses. Multiple regressions model for risk ratio (RR) and 95% confidence intervals (CI) were used to conduct factors correlated with perioperative cardiac arrest. The multicollinearity of all variables was examined by bivariate correlation matrix. A stepwise algorithm was chosen at a p-value less than 0.02 was selected to further multivariate analysis. A P-value of less than 0.05 was concluded as statistically significant. Measurements and results: The occurrence of perioperative cardiac arrest in trauma patients receiving anesthesia for emergency surgery was 170.04 per 10,000 cases. Factors associated with perioperative cardiac arrest in trauma patients were age being more than 65 years (RR=1.41, CI=1.02–1.96, p=0.039), ASA physical status 3 or higher (RR=4.19–21.58, p < 0.001), sites of surgery (intracranial, intrathoracic, upper intra-abdominal, and major vascular, each p < 0.001), cardiopulmonary comorbidities (RR=1.55, CI=1.10–2.17, p < 0.012), hemodynamic instability with shock prior to receiving anesthesia (RR=1.60, CI=1.21–2.11, p < 0.001) , special techniques for surgery such as cardiopulmonary bypass (CPB) and hypotensive techniques (RR=5.55, CI=2.01–15.36, p=0.001; RR=6.24, CI=2.21–17.58, p=0.001, respectively), and patients who had a history of being alcoholic (RR=5.27, CI=4.09–6.79, p < 0.001). Conclusion: Incidence of perioperative cardiac arrest in trauma patients receiving anesthesia for emergency surgery was very high and correlated with many factors, especially age of patient and cardiopulmonary comorbidities, patient having a history of alcoholic addiction, increasing ASA physical status, preoperative shock, special techniques for surgery, and sites of surgery including brain, thorax, abdomen, and major vascular region. Anesthesiologists and multidisciplinary teams in pre- and perioperative periods should remain alert for warning signs of pre-cardiac arrest and be quick to manage the high-risk group of surgical trauma patients. Furthermore, a healthcare policy should be promoted for protecting against accidents in high-risk groups of the population as well.

Keywords: perioperative cardiac arrest, trauma patients, emergency surgery, anesthesia, factors risk, incidence

Procedia PDF Downloads 172

Authors: Rita Chattopadhyay, Vivek Anand Thoutam

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Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

Procedia PDF Downloads 83

Authors: Nurul Jamilah Binti Rosly

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The typology of motion must be understood as a change from one location to another. But from a conceptual point of view, motion can also occur in non-spatial contexts associated with human and social factors. Therefore, from the conceptual point of view, the concept of non-spatial motion involves the movement of time, ownership, identity, state, and existence. Accordingly, this study will focus on the lexical as shared, accept, be, store, and exist as the study material. The data in this study were extracted from the Database of Languages and Literature Corpus Database, Malaysia, which was analyzed using semantics and syntax concepts using Conceptual Structure Theory - Ray Jackendoff (2002). Semantic representations are represented in the form of conceptual structures in argument functions that include functions [events], [situations], [objects], [paths] and [places]. The findings show that the mapping of these arguments comprises three main stages, namely mapping the argument structure, mapping the tree, and mapping the role of thematic items. Accordingly, this study will show the representation of non- spatial Malay language areas.

Keywords: arguments, concepts, constituencies, events, situations, thematics

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Authors: Zina Saheb, Ezz El-Masry

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As CMOS technology scaling down, Silicon oxide thickness (SiO2) become very thin (few Nano meters). When SiO2 is less than 3nm, gate direct tunneling (DT) leakage current becomes a dormant problem that impacts the transistor performance. Floating gate MOSFET (FGMOSFET) has been used in many low-voltage and low-power applications. Most of the available simulation models of FGMOSFET for analog circuit design does not account for gate DT current and there is no accurate analysis for the gate DT. It is a crucial to use an accurate mode in order to get a realistic simulation result that account for that DT impact on FGMOSFET performance effectively.

Keywords: CMOS transistor, direct-tunneling current, floating-gate, gate-leakage current, simulation model

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Authors: Thanaphat Suwanaklang, Supaporn Suwannarongsri

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Presently, there are many industries in Thailand producing various products for both domestic distribution and export to foreign countries. Warehouse is one of the most important areas of business needing to store their products. Such businesses need to have a suitable warehouse management system for reducing the storage time and using the space as much as possible. This paper proposes the development of a web application for a warehouse management system. One of the ceramics factories in Thailand is conducted as a case study. By applying the ABC analysis, fixed location, commodity system, ECRS, and 7-waste theories and principles, the web application for the warehouse management system of the selected ceramics factory is developed to design the optimal storage area for groups of products and design the optimal routes of forklifts. From experimental results, it was found that the warehouse management system developed via the web application can reduce the travel distance of forklifts and the time of searching for storage area by 100% once compared with the conventional method. In addition, the entire storage area can be on-line and real-time monitored.

Keywords: warehouse management system, warehouse design method, logistics system, web application

Procedia PDF Downloads 140

Authors: Kwang Chun, John Kemeny

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Light detection and ranging (LiDAR) has been a prevalent remote-sensing technology applied in the geological fields due to its high precision and ease of use. One of the major applications is to use the detailed geometrical information of underground structures as a basis for the generation of a three-dimensional numerical model that can be used in a geotechnical stability analysis such as FEM or DEM. To date, however, straightforward techniques in reconstructing the numerical model from the scanned data of the underground structures have not been well established or tested. In this paper, we propose a comprehensive approach integrating all the various processes, from LiDAR scanning to finite element numerical analysis. The study focuses on converting LiDAR 3D point clouds of geologic structures containing complex surface geometries into a finite element model. This methodology has been applied to Kartchner Caverns in Arizona, where detailed underground and surface point clouds can be used for the analysis of underground stability. Numerical simulations were performed using the finite element code Abaqus and presented by 3D computing visualization solution, ParaView. The results are useful in studying the stability of all types of underground excavations including underground mining and tunneling.

Keywords: finite element analysis, LiDAR, remote-sensing, scientific visualization, underground stability

Procedia PDF Downloads 181

Authors: Keisuke Akiyama, Takashi Sakai, Junichiro Koyanagi, Hideki Yoshikawa, Kazuomi Sugamoto

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The geometry of acetabular cartilage surface plays an important role in hip joint biomechanics. The aim of this study was to analyze the morphology of acetabular articular cartilage surface in elderly subjects using a 3D-digitizer. Twenty hemipelves from 12 subjects (mean ages 85 years) were scanned with 3D-digitizer. Each acetabular surface model was divided into four regions: anterosuperior (AS), anteroinferior (AI), posterosuperior (PS), and posteroinferior (PI). In the global acetabulum and each region, the acetabular sphere radius and the standard deviation (SD) of the distance from the acetabular sphere center to the acetabular cartilage surface were calculated. In the global acetabulum, the distance between the acetabular surface model and the maximum sphere which did not penetrate over the acetabular surface model was calculated as the inferred femoral head, and then the distribution was mapped at intervals of 0.5 mm. The SD in AS was significantly larger than that in AI (p = 0.006) and PI (p = 0.001). The SD in PS was significantly larger than that in PI (p = 0.005). The closest region (0-0.5 mm) tended to be distributed at anterior or posterosuperior acetabular edge. The contact between the femoral head and acetabulum might start at the periphery of the lunate surface, especially in the anterior or posterosuperior region. From viewpoint of acetabular morphology, the acetabular articular cartilage in the anterior or posterosuperior edge could be more vulnerable due to direct contact mechanism.

Keywords: acetabulum, cartilage, morphology, 3D-digitizer

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Authors: Weiwei Shan, Wenjing Ding, Juan Ning, Chao He, Zijuan Wang

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Gravity circulation loop for the cryopumps of the space simulator is introduced, and two phase mathematic model of flow heat transfer is analyzed as well. Based on this model, the liquid nitrogen (LN₂) gravity circulation loop including its equipment and layout is designed and has served as LN₂ feeding system for cryopumps in one large space simulator. With the help of control software and human machine interface, this system can be operated flexibly, simply, and automatically under four conditions. When running this system, the results show that the cryopumps can be cooled down and maintained under the required temperature, 120 K.

Keywords: cryopumps, gravity circulation loop, liquid nitrogen, two-phase

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Authors: Xiaohua Zou, Yongxin Su

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The reasonable operation of heating, ventilation, and air conditioning (HVAC) is of great significance in improving the security, stability, and economy of power system operation. However, the uncertainty of the operating environment, thermal comfort varies by users and rapid decision-making pose challenges for HVAC demand response optimization. In this regard, this paper proposes a reinforcement learning-based method for HVAC demand response optimization considering few-shot personalized thermal comfort (PTC). First, an HVAC DR optimization framework based on few-shot PTC model and DRL is designed, in which the output of few-shot PTC model is regarded as the input of DRL. Then, a few-shot PTC model that distinguishes between awake and asleep states is established, which has excellent engineering usability. Next, based on soft actor criticism, an HVAC DR optimization algorithm considering the user’s PTC is designed to deal with uncertainty and make decisions rapidly. Experiment results show that the proposed method can efficiently obtain use’s PTC temperature, reduce energy cost while ensuring user’s PTC, and achieve rapid decision-making under uncertainty.

Keywords: HVAC, few-shot personalized thermal comfort, deep reinforcement learning, demand response

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Authors: Divya Agarwal, Pushpendra S. Bharti

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Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc.

Keywords: path planning, obstacle avoidance, autonomous mobile robots, algorithms

Procedia PDF Downloads 239

Authors: Ceren Vardar Acar, Mine Caglar

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In finance, the price of a volatile asset can be modeled using fractional Brownian motion (fBm) with Hurst parameter H>1/2. The Black-Scholes model for the values of returns of an asset using fBm is given as, 〖Y_t=Y_0 e^((r+μ)t+σB)〗_t^H, 0≤t≤T where Y_0 is the initial value, r is constant interest rate, μ is constant drift and σ is constant diffusion coefficient of fBm, which is denoted by B_t^H where t≥0. Black-Scholes model can be constructed with some Markov processes such as Brownian motion. The advantage of modeling with fBm to Markov processes is its capability of exposing the dependence between returns. The real life data for a volatile asset display long-range dependence property. For this reason, using fBm is a more realistic model compared to Markov processes. Investors would be interested in any kind of information on the risk in order to manage it or hedge it. The maximum possible loss is one way to measure highest possible risk. Therefore, it is an important variable for investors. In our study, we give some theoretical bounds on the distribution of maximum possible loss of fBm. We provide both asymptotical and strong estimates for the tail probability of maximum loss of standard fBm and fBm with drift and diffusion coefficients. In the investment point of view, these results explain, how large values of possible loss behave and its bounds.

Keywords: maximum drawdown, maximum loss, fractional brownian motion, large deviation, Gaussian process

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Authors: Gian Bhushan, Vinkel Arora, M. L. Aggarwal

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The objective of the present study is to determine better eye end design of a mono leaf spring used in light motor vehicle. A conventional 65Si7 spring steel leaf spring model with standard eye, casted and riveted eye end are considered. The CAD model of the leaf springs is prepared in CATIA and analyzed using ANSYS. The standard eye, casted, and riveted eye leaf springs are subjected to similar loading conditions. The CAE analysis of the leaf spring is performed for various parameters like deflection and Von-Mises stress. Mass reduction of 62.9% is achieved in case of riveted eye mono leaf spring as compared to standard eye mono leaf spring for the same loading conditions.

Keywords: CAE, leaf spring, standard, casted, riveted eye

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Authors: Sun Shi, Sun Cheng

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The pedestrian corridor is the most crowded area in the public space. The crowded severity has been focused on the field of evacuation strategies of the entrance in large public spaces. The aim of this paper is to analyze the walking efficiency in different spaces of pedestrian corridor with the variation of spatial parameters. The congestion condition caused by the variation of walking efficiency is modeled as well. This study established the space model of the walking corridor by setting the width, slope, turning form and turning angle of the pedestrian corridor. The pedestrian preference of walking mode varied with the difference of the crowded severity, walking speed, field of vision, sight direction and the expected destination, which is influenced by the characters of physical space form. Swarm software is applied to build Agent model. According to the output of the Agent model, the relationship between the pedestrian corridor width, ground slope, turning forms, turning angle and the walking efficiency, crowded severity is acquired. The results of the simulation can be applied to pedestrian corridor design in order to reduce the crowded severity and the potential safety risks caused by crowded people.

Keywords: crowded severity, multi-agent, pedestrian preference, urban space design

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Authors: Haoyang Liang, Dandong Ge

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With the rapid development of Chinese cities, traffic congestion has become more and more serious. At the same time, there are many closed old residential area in Chinese cities, which seriously affect the connectivity of urban roads and reduce the density of urban road networks. After reopening the restricted old residential area, the internal roads in the original residential area were transformed into urban roads, which was of great help to alleviate traffic congestion. This paper uses the spatial syntactic theory to analyze the urban road network and compares the roads with the integration and connectivity degree to evaluate whether the opening of the roads in the residential areas can improve the urban traffic. Based on the road network system within the first loop road in Kunming, the Space Syntax evaluation model is established for status analysis. And comparative analysis method will be used to compare the change of the model before and after the road openness of the old urban residential district within the first-ring road in Kunming. Then it will pick out the areas which indicate a significant difference for the small dimensions model analysis. According to the analyzed results and traffic situation, the evaluation of road openness in the old urban residential district will be proposed to improve the urban residential districts.

Keywords: Space Syntax, Kunming, urban renovation, traffic jam

Procedia PDF Downloads 167

Authors: Farhad Asadi, Mohammad Javad Mollakazemi

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In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: time series, fluctuation in statistical characteristics, optimal learning, change-point algorithm

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Authors: Basma Khelfa, Antoine Tordeux, Ibrahima Ba

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We present a descriptive analysis data of lane-changing events in multi-lane roads. The data are provided from The Highway Drone Dataset (HighD), which are microscopic trajectories in highway. This paper describes and analyses the role of the different parameters and their significance. Thanks to HighD data, we aim to find the most frequent reasons that motivate drivers to change lanes. We used the programming language R for the processing of these data. We analyze the involvement and relationship of different variables of each parameter of the ego vehicle and the four vehicles surrounding it, i.e., distance, speed difference, time gap, and acceleration. This was studied according to the class of the vehicle (car or truck), and according to the maneuver it undertook (overtaking or falling back).

Keywords: autonomous driving, physical traffic model, prediction model, statistical learning process

Procedia PDF Downloads 265

Authors: Gionata Carmignani, Mario G. C. A. Cimino, Franco Failli

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Business Processes (BPs) are the key instrument to understand how companies operate at an organizational level, taking an as-is view of the workflow, and how to address their issues by identifying a to-be model. In last year’s, the BP Model and Notation (BPMN) has become a de-facto standard for modeling processes. However, this standard does not incorporate explicitly the Problem-Solving (PS) knowledge in the Process Modeling (PM) results. Thus, such knowledge cannot be shared or reused. To narrow this gap is today a challenging research area. In this paper we present a framework able to capture the PS knowledge and to improve a workflow. This framework extends the BPMN specification by incorporating new general-purpose elements. A pilot scenario is also presented and discussed.

Keywords: business process management, BPMN, problem solving, process mapping

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Authors: M. Harir, A. Bendiabdellah, A. Chaouch, N. Benouzza

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This paper deals with the modelling and simulation of the squirrel cage induction motor by taking into account all space harmonic components, as well as the introduction of the bars skew, in the calculation of the linear evolution of the magnetomotive force (MMF) between the slots extremities. The model used is based on multiple coupled circuits and the modified winding function approach (MWFA). The effect of skewing is included in the calculation of motors inductances with an axial asymmetry in the rotor. The simulation results in both time and spectral domains show the effectiveness and merits of the model and the error that may be caused if the skew of the bars is neglected.

Keywords: modeling, MWFA, skew effect, squirrel cage induction motor, spectral domain

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Authors: Shende Suraj Balu, A. B. Deoghare, K. M. Pandey

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The human middle ear (ME) is a delicate and vital organ. It has a complex structure that performs various functions such as receiving sound pressure and producing vibrations of eardrum and propagating it to inner ear. It consists of Tympanic Membrane (TM), three auditory ossicles, various ligament structures and muscles. Incidents such as traumata, infections, ossification of ossicular structures and other pathologies may damage the ME organs. The conditions can be surgically treated by employing prosthesis. However, the suitability of the prosthesis needs to be examined in advance prior to the surgery. Few decades ago, this issue was addressed and analyzed by developing an equivalent representation either in the form of spring mass system, electrical system using R-L-C circuit or developing an approximated CAD model. But, nowadays a three-dimensional ME model can be constructed using micro X-Ray Computed Tomography (μCT) scan data. Moreover, the concern about patient specific integrity pertaining to the disease can be examined well in advance. The current research work emphasizes to develop the ME model from the stacks of μCT images which are used as input file to MIMICS Research 19.0 (Materialise Interactive Medical Image Control System) software. A stack of CT images is converted into geometrical surface model to build accurate morphology of ME. The work is further extended to understand the dynamic behaviour of Harmonic response of the stapes footplate and umbo for different sound pressure levels applied at lateral side of eardrum using finite element approach. The pathological condition Cholesteatoma of ME is investigated to obtain peak to peak displacement of stapes footplate and umbo. Apart from this condition, other pathologies, mainly, changes in the stiffness of stapedial ligament, TM thickness and ossicular chain separation and fixation are also explored. The developed model of ME for pathologies is validated by comparing the results available in the literatures and also with the results of a normal ME to calculate the percentage loss in hearing capability.

Keywords: computed tomography (μCT), human middle ear (ME), harmonic response, pathologies, tympanic membrane (TM)

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Authors: Soulayma Smirani, Mourad Aidi, Taoufik Aguili

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Energy harvesting has arisen as a prominent research area for low power delivery to RF devices. Rectennas have become a key element in this technology. In this paper, electromagnetic modeling of a rectenna system is presented. In our approach, a hybrid technique was demonstrated to associate both the method of auxiliary sources (MAS) and MoM-GEC (the method of moments combined with the generalized equivalent circuit technique). Auxiliary sources were used in order to substitute specific electronic devices. Therefore, a simple and controllable model is obtained. Also, it can easily be interconnected to form different topologies of rectenna arrays for more energy harvesting. At last, simulation results show the feasibility and simplicity of the proposed rectenna model with high precision and computation efficiency.

Keywords: computational electromagnetics, MoM-GEC method, rectennas, RF energy harvesting

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Authors: Angelis P. Barlampas

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An 89 years old woman came to the emergency department complaining of long-lasting headaches and nausea. A CT examination was performed, and a homogeneous midline anterior cranial fossa lesion was revealed, which was situated near the base and measured 2,4 cm in diameter. The patient was allergic, and an i.v.c injection could not be done on the spot, and neither could an MRI exam because of metallic implants. How could someone narrow down the differential diagnosis? The interhemispheric meningioma is usually a silent midline lesion with no edema, and most often presents as a homogeneous, solid type, isodense, or slightly hyperdense mass ( usually the smallest lesions as this one ). Of them, 20-30% have some calcifications. Hyperostosis is typical for meningiomas that abut the base of the skull but is absent in the current case, presumably of a more cephalad location that is borderline away from the bone. Because further investigation could not be done, as the patient was allergic to the contrast media, some other differential options should be considered. Regarding the site of the lesion, the most common other entities to keep in mind are the following: Metastasis, tumor of skull base, abscess, primary brain tumors, meningioma, giant aneurysm of the anterior cerebral artery, olfactory neuroblastoma, interhemispheric meningioma, giant aneurysm of the anterior cerebral artery, midline lesion. Appearance will depend on whether the aneurysm is non-thrombosed, or partially, or completely thrombosed. Non-contrast: slightly hyperdense, well-defined round extra-axial mass, may demonstrate a peripheral calcified rim, olfactory neuroblastoma, midline lesion. The mass is of soft tissue attenuation and is relatively homogeneous. Focal calcifications are occasionally present. When an intracranial extension is present, peritumoral cysts between it and the overlying brain are often present. Final diagnosis interhemispheric meningioma (Known from the previous patient’s history). Meningiomas come from the meningocytes or the arachnoid cells of the meninges. They are usually found incidentally, have an indolent course, and their most common location is extra-axial, parasagittal, and supratentorial. Other locations include the sphenoid ridge, olfactory groove, juxtasellar, infratentorial, intraventricular, pineal gland area, and optic nerve meningioma. They are clinically silent entities, except for large ones, which can present with headaches, changes in personality status, paresis, or symptomatology according to their specific site and may cause edema of the surrounding brain tissue. Imaging findings include the presence of calcifications, the CSF cleft sign, hyperostosis of adjacent bone, dural tail, and white matter buckling sign. After i.v.c. injection, they enhance brightly and homogenously, except for large ones, which may exhibit necrotic areas or may be heavily calcified. Malignant or cystic variants demonstrate more heterogeneity and less intense enhancement. Sometimes, it is inevitable that the needed CT protocol cannot be performed, especially in the emergency department. In these cases, the radiologist must focus on the characteristic imaging features of the unenhanced lesion, as well as in previous examinations or a known lesion history, in order to come to the right report conclusion.

Keywords: computed tomography, emergency radiology, metastasis, tumor of skull base, abscess, primary brain tumors, meningioma, giant aneurysm of the anterior cerebral artery, olfactory neuroblastoma, interhemispheric meningioma

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Authors: Pavol Tanuska, Pavel Vazan, Michal Kebisek, Dominika Jurovata

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The paper gives the results of the project that was oriented on the usage of knowledge discoveries from production systems for needs of the hierarchical process control. One of the main project goals was the proposal of knowledge discovery model for process control. Specifics data mining methods and techniques was used for defined problems of the process control. The gained knowledge was used on the real production system, thus, the proposed solution has been verified. The paper documents how it is possible to apply new discovery knowledge to be used in the real hierarchical process control. There are specified the opportunities for application of the proposed knowledge discovery model for hierarchical process control.

Keywords: hierarchical process control, knowledge discovery from databases, neural network, process control

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Authors: Jasman Tuyon, Zamri Ahmad

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Behavioral asset pricing research has been gaining momentum since in 1990s. However, it is still incomplete and has been criticized for some philosophical, theoretical and model specification limitations. Due to these drawbacks, investors’ behaviors as a source of risk in behavioral asset pricing modeling still remains disputable. This paper aims to address these issues with an alternative perspective based on behavioral finance paradigm. Specifically, this paper proposes a theoretical linkages of both fundamental and behavioral risks on stock prices formation and an extension of the multifactor stock pricing model by combining multi-factor fundamentals and behavioral risks factors.

Keywords: behavioral finance, multifactor asset pricing, behavioral risks, fundamental risks

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Authors: Ali Abdul Kadhim, Fue Lien

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Solid particle distribution on an impingement surface has been simulated utilizing a graphical processing unit (GPU). In-house computational fluid dynamics (CFD) code has been developed to investigate a 3D turbulent impinging jet using the lattice Boltzmann method (LBM) in conjunction with large eddy simulation (LES) and the multiple relaxation time (MRT) models. This paper proposed an improvement in the LBM-cellular automata (LBM-CA) probabilistic method. In the current model, the fluid flow utilizes the D3Q19 lattice, while the particle model employs the D3Q27 lattice. The particle numbers are defined at the same regular LBM nodes, and transport of particles from one node to its neighboring nodes are determined in accordance with the particle bulk density and velocity by considering all the external forces. The previous models distribute particles at each time step without considering the local velocity and the number of particles at each node. The present model overcomes the deficiencies of the previous LBM-CA models and, therefore, can better capture the dynamic interaction between particles and the surrounding turbulent flow field. Despite the increasing popularity of LBM-MRT-CA model in simulating complex multiphase fluid flows, this approach is still expensive in term of memory size and computational time required to perform 3D simulations. To improve the throughput of each simulation, a single GeForce GTX TITAN X GPU is used in the present work. The CUDA parallel programming platform and the CuRAND library are utilized to form an efficient LBM-CA algorithm. The methodology was first validated against a benchmark test case involving particle deposition on a square cylinder confined in a duct. The flow was unsteady and laminar at Re=200 (Re is the Reynolds number), and simulations were conducted for different Stokes numbers. The present LBM solutions agree well with other results available in the open literature. The GPU code was then used to simulate the particle transport and deposition in a turbulent impinging jet at Re=10,000. The simulations were conducted for L/D=2,4 and 6, where L is the nozzle-to-surface distance and D is the jet diameter. The effect of changing the Stokes number on the particle deposition profile was studied at different L/D ratios. For comparative studies, another in-house serial CPU code was also developed, coupling LBM with the classical Lagrangian particle dispersion model. Agreement between results obtained with LBM-CA and LBM-Lagrangian models and the experimental data is generally good. The present GPU approach achieves a speedup ratio of about 350 against the serial code running on a single CPU.

Keywords: CUDA, GPU parallel programming, LES, lattice Boltzmann method, MRT, multi-phase flow, probabilistic model

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Authors: Jirawan Jitthavech, Vichit Lorchirachoonkul

Abstract:

A statistical procedure using multiple comparisons test for proportions is proposed for variable selection in a data envelopment analysis (DEA) model. The test statistic in the multiple comparisons is the proportion of efficient decision making units (DMUs) in a DEA model. Three methods of multiple comparisons test for proportions: multiple Z tests with Bonferroni correction, multiple tests in 2Xc crosstabulation and the Marascuilo procedure, are used in the proposed statistical procedure of iteratively eliminating the variables in a backward manner. Two simulation populations of moderately and lowly correlated variables are used to compare the results of the statistical procedure using three methods of multiple comparisons test for proportions with the hypothesis testing of the efficiency contribution measure. From the simulation results, it can be concluded that the proposed statistical procedure using multiple Z tests for proportions with Bonferroni correction clearly outperforms the proposed statistical procedure using the remaining two methods of multiple comparisons and the hypothesis testing of the efficiency contribution measure.

Keywords: Bonferroni correction, efficient DMUs, Marascuilo procedure, Pastor et al. method, 2xc crosstabulation

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Authors: Waheeda Jabbar, Ali Gul, Rida Noor, Sania Kurd, Saba Gulzar

Abstract:

Hundreds of miners die from mining accidents each year due to poisonous gases found underground mining areas. This paper proposed an idea to protect the precious lives of mining workers. A supervising system is designed which is based on ZigBee wireless technique along with the smart protective helmets to detect real-time surveillance and it gives early warnings on presence of different poisonous gases in order to save mineworkers from any danger caused by these poisonous gases. A wireless sensor network is established using ZigBee wireless technique by integrating sensors on the helmet, apart from this helmet have embedded heartbeat sensor to detect the pulse rate and be aware of the physical or mental strength of a mineworker to increase the potential safety. Radio frequency identification (RFID) technology is used to find the location of workers. A ZigBee based base station is set-upped to control the communication. The idea is implemented and results are verified through experiment.

Keywords: Arduino, gas sensor (MQ7), RFID, wireless ZigBee

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Authors: Samira Cherid, Samir Bentata, F. Zahira Meghoufel, Sabria Terkhi, Yamina Sefir, Fatima Bendahma, Bouabdellah Bouadjemi, Ali Z. Itouni

Abstract:

In this work, we examined the propagation of light in one-dimensional systems is examined by means of the random dimer model. The introduction of defect elements, randomly in the studied system, breaks down the Anderson localization and provides a set of propagating delocalized modes at the corresponding conventional dimer resonances. However, tuning suitably the defect dimer resonance on the host ones (or vice versa), the transmission magnitudes can be enhanced providing the optimized ballistic transmission regime as an average response. Hence, ballistic optical filters can be conceived at desired wavelengths.

Keywords: photonic crystals, random dimer model, ballistic resonance, localization and transmission

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Authors: Julio Aguirre, Yohnny Campana, Elmer Guerrero, Daniel De La Torre Ugarte

Abstract:

A well-developed transportation network is a necessary condition for a country to derive full benefits from good trade and macroeconomic policies. Road infrastructure plays a key role in the economic development of rural areas of developing countries; where agriculture is the main economic activity. The ability to move agricultural production from the place of production to the market, and then to the place of consumption, greatly influence the economic value of farming activities, and of the resources involved in the production process, i.e., labor and land. Consequently, investment in transportation networks contributes to enhance or overcome the natural advantages or disadvantages that topography and location have imposed over the agricultural sector. This is of particular importance when dealing with countries, like Peru, with a great topographic diversity. The objective of this research is to estimate the impacts of road infrastructure on the performance of the agricultural sector. Specific variables of interest are changes in travel time, shifts of production for self-consumption to production for the market, changes in farmers income, and impacts on the diversification of the agricultural sector. In the study, a cross-section model with instrumental variables is the central methodological instrument. The data is obtained from agricultural and transport geo-referenced databases, and the instrumental variable specification utilized is based on the Kruskal algorithm. The results show that the expansion of road connectivity reduced farmers' travel time by an average of 3.1 hours and the proportion of output sold in the market increases by up to 40 percentage points. The increase in connectivity has an unexpected increase in the districts index of diversification of agricultural production. The results are robust to the inclusion of year and region fixed-effects, and to control for geography (i.e., slope and altitude), population variables, and mining activity. Other results are also very eloquent. For example, a clear positive impact can be seen in access to local markets, but this does not necessarily correlate with an increase in the production of the sector. This can be explained by the fact that agricultural development not only requires provision of roads but additional complementary infrastructure and investments intended to provide the necessary conditions so that producers can offer quality products (improved management practices, timely maintenance of irrigation infrastructure, transparent management of water rights, among other factors). Therefore, complementary public goods are needed to enhance the effects of roads on the welfare of the population, beyond enabling them to increase their access to markets.

Keywords: agriculture devolepment, market access, road connectivity, regional development

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Authors: P. R. Prabhu, S. M. Kulkarni, S. S. Sharma, K. Jagannath, Achutha Kini U.

Abstract:

In the present study, response surface methodology has been used to optimize turn-assisted deep cold rolling process of AISI 4140 steel. A regression model is developed to predict surface hardness and surface roughness using response surface methodology and central composite design. In the development of predictive model, deep cold rolling force, ball diameter, initial roughness of the workpiece, and number of tool passes are considered as model variables. The rolling force and the ball diameter are the significant factors on the surface hardness and ball diameter and numbers of tool passes are found to be significant for surface roughness. The predicted surface hardness and surface roughness values and the subsequent verification experiments under the optimal operating conditions confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface hardness and surface roughness is calculated as 0.16% and 1.58% respectively. Using the optimal processing parameters, the hardness is improved from 225 to 306 HV, which resulted in an increase in the near surface hardness by about 36% and the surface roughness is improved from 4.84µm to 0.252 µm, which resulted in decrease in the surface roughness by about 95%. The depth of compression is found to be more than 300µm from the microstructure analysis and this is in correlation with the results obtained from the microhardness measurements. Taylor Hobson Talysurf tester, micro Vickers hardness tester, optical microscopy and X-ray diffractometer are used to characterize the modified surface layer.

Keywords: hardness, response surface methodology, microstructure, central composite design, deep cold rolling, surface roughness

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Authors: Vishnu A., Ashesh Saha

Abstract:

The operation of high-speed rotating machinery in industries is accompanied by rotor vibrations due to many factors. One of the primary instability mechanisms in a rotor system is the centrifugal force induced due to the eccentricity of the center of mass away from the center of rotation. These unwanted vibrations may lead to catastrophic fatigue failure. So, there is a need to control these rotor vibrations. In this work, control of rotor vibrations by using a 4-pole Radial Active Magnetic Bearing (RAMB) as an actuator is analysed. A continuous rotor system model is considered for the analysis. Several important factors, like the gyroscopic effect and rotary inertia of the shaft and disc, are incorporated into this model. The large deflection of the shaft and the restriction to axial motion of the shaft at the bearings result in nonlinearities in the system governing equation. The rotor system is modeled in such a way that the system dynamics can be related to the geometric and material properties of the shaft and disc. The mathematical model of the rotor system is developed by incorporating the control forces generated by the RAMB. A simple PD controller is used for the attenuation of system vibrations. An analytical expression for the amplitude and phase equations is derived using the Method of Multiple Scales (MMS). Analytical results are verified with the numerical results obtained using an ‘ode’ solver in-built into MATLAB Software. The control force is found to be effective in attenuating the system vibrations. The multi-valued solutions leading to the jump phenomenon are also eliminated with a proper choice of control gains. Most interestingly, the shape of the backbone curves can also be altered for certain values of control parameters.

Keywords: rotor dynamics, continuous rotor system model, active magnetic bearing, PD controller, method of multiple scales, backbone curve

Procedia PDF Downloads 84