Search results for: trading signals generation

Authors: Perla Elizabeth Jimarez Rocha, Carolina Daniela Tejeda Franco, Arturo Minor Martínez, Annel Gomez Coello

Abstract:

One of the biggest problems in developing new therapies for the management and treatment of voice disorders is the difficulty of objectively evaluating the results of each treatment. A system was proposed that captures and records voice signals, in addition to analyzing the vocal quality (fundamental frequency, zero crossings, energy, and amplitude spectrum), as well as the subglottic pressure (cm H2O) during the sustained phonation of the vowel / a /; a recording system is implemented, as well as an interactive system that records information on subglottic pressure. In Mexico City, a control group of 31 patients with phoniatric pathology is proposed; non-invasive tests were performed for these most common vocal pathologies (Nodules, Polyps, Irritative Laryngitis, Ventricular Dysphonia, Laryngeal Cancer, Dysphonia, and Dysphagia). The most common pathology was irritative laryngitis (32%), followed by vocal fold paralysis (unilateral and bilateral,19.4 %). We take into consideration men and women in the pathological groups due to the physiological difference. They were separated in gender by the difference in the morphology of the respiratory tract.

Keywords: amplitude spectrum, energy, fundamental frequency, subglottic pressure, zero crossings

Procedia PDF Downloads 120

Authors: Prateek Chharia, Biswa Bhusan Ghosh

Abstract:

Graph coloring is one of the prominent concepts in graph coloring. It can be defined as a coloring of the various regions of the graph such that all the constraints are fulfilled. In this paper various graphs coloring approaches like greedy coloring, Heuristic search for maximum independent set and graph coloring using edge table is described. Graph coloring can be used in various real time applications like student time tabling generation, Sudoku as a graph coloring problem, GSM phone network.

Keywords: graph coloring, greedy coloring, heuristic search, edge table, sudoku as a graph coloring problem

Procedia PDF Downloads 539

Authors: M. J. Kang, Y. N. Jo, H. H. Yoo

Abstract:

Pendulum tests were used to identify a stretch reflex and diagnose spasticity. Some researches tried to make a mathematical model to simulate the motions. Thighs are subject to compressive forces due to gravity during a pendulum test. Therefore, it affects knee trajectories. However, the most studies on the pendulum tests did not consider that conditions. We used Kelvin-Voight model as compression model of skin and muscles. In this study, we investigated viscoelastic behaviors of skin and muscles using gelatin blocks from experiments of the vibration of the compliantly supported beam. Then we calculated a dynamic stiffness and loss factors from the experiment and estimated a damping coefficient of the model. We also did pendulum tests of human lower limbs to validate the stiffness and damping coefficient of a skin model. To simulate the pendulum motion, we derive equations of motion. We used stretch reflex activation model to estimate muscle forces induced by the stretch reflex. To validate the results, we compared the activation with electromyography signals during experiments. The compression behavior of skin and muscles in this study can be applied to analyze sitting posture as wee as developing surgical techniques.

Keywords: Kelvin-Voight model, pendulum test, skin and muscles under compression, stretch reflex

Procedia PDF Downloads 445

Authors: Md. Jisan Ahmed, M. A. Taher

Abstract:

One of the cities in Bangladesh that is developing the fastest is Narayanganj City Corporation. In 2011, the municipality of Narayanganj was transformed into a city corporation, with 27 wards combining Kadamrasul Municipality, Siddhirganj Municipality, and Narayanganj Town. It is also one of Bangladesh's most important industrial centers in Bangladesh. Narayanganj City Corporation (NCC), which has had high development growth, is also generating more solid waste on a high per-capita basis. Because of the increasing rate of population expansion, business activity, industrial development, and fast urbanization, NCC is today creating more waste than ever before. The enormous amount of solid garbage produced in NCC is currently causing air pollution, soil contamination, water pollution, drainage system blockages, and an unpleasant urban environment. The study aimed to find out the amount of solid waste produced per day in NCC by exploring the waste composition and potentiality of resource recovery from the produced solid waste. This study considered household surveys, polythene bag surveys, questionnaire surveys in commercial and industrial sectors, KIIs, FGDs, and lab tests to identify the total amount of waste generated in NCC with waste composition and potentiality for energy recovery from the generated waste. This study has explored that NCC is producing about 922 tons of solid waste per day from households, commercial activities, and industrial sectors where the existing waste collection rate by NCC authority is only about 50% of total generated waste. This study has also explored that about 75% of daily-produced solid waste is perishable with comparatively high moisture content whereas 18 % and 7% are non-perishable and hazardous. It is also explored that there is no resource recovery plant for solid waste management in NCC. On the other hand, this study has explored that the calorific value of the produced solid waste favors resource recovery like waste to electricity. The generated solid waste composition is also in favor of waste-to-biogas, and waste-to-compost fertilizer production. This study has advocated that initiatives need to develop a solid waste management plant in NCC for resource recovery from solid waste. This research may provide a quick overview of the rate of solid waste generation, its composition, and the potential for resource recovery from solid waste in Bangladesh's metropolitan regions. It can also provide information and knowledge to other trash departments in different cities and municipalities in Bangladesh.

Keywords: solid waste, waste composition, waste management, resource recovery from solid waste

Procedia PDF Downloads 20

Authors: A. Achour L. Chekour, A. Mekroud

Abstract:

Tribology, the science of lubrication, friction and wear, plays an important role in science "crossroads" initiated by the recent developments in the industry. Its multidisciplinary nature reinforces its scientific interest. It covers all the sciences that deal with the contact between two solids loaded and relative motion. It is thus one of the many intersections more clearly established disciplines such as solid mechanics and the fluids, rheological, thermal, materials science and chemistry. As for his experimental approach, it is based on the physical and processing signals and images. The optimization of operating conditions by cutting tool must contribute significantly to the development and productivity of advanced automation of machining techniques because their implementation requires sufficient knowledge of how the process and in particular the evolution of tool wear. In addition, technological advances have developed the use of very hard materials, refractory difficult machinability, requiring highly resistant materials tools. In this study, we present the behavior wear a machining tool during the roughing operation according to the cutting parameters. The interpretation of the experimental results is based mainly on observations and analyzes of sharp edges e tool using the latest techniques: scanning electron microscopy (SEM) and optical rugosimetry laser beam.

Keywords: friction, wear, tool, cutting

Procedia PDF Downloads 331

Authors: Ramzi Rihane, Yassine Benayed

Abstract:

Epilepsy is a chronic neurological disorder characterized by recurrent, unprovoked seizures resulting from abnormal electrical activity in the brain. Timely and accurate detection of these seizures is essential for improving patient care. In this study, we leverage the UK Bonn University open-source EEG dataset and employ advanced deep-learning techniques to automate the detection of epileptic seizures. By extracting key features from both time and frequency domains, as well as Spectrogram features, we enhance the performance of various deep learning models. Our investigation includes architectures such as Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), 1D Convolutional Neural Networks (1D-CNN), and hybrid CNN-LSTM and CNN-BiLSTM models. The models achieved impressive accuracies: LSTM (98.52%), Bi-LSTM (98.61%), CNN-LSTM (98.91%), CNN-BiLSTM (98.83%), and CNN (98.73%). Additionally, we utilized a data augmentation technique called SMOTE, which yielded the following results: CNN (97.36%), LSTM (97.01%), Bi-LSTM (97.23%), CNN-LSTM (97.45%), and CNN-BiLSTM (97.34%). These findings demonstrate the effectiveness of deep learning in capturing complex patterns in EEG signals, providing a reliable and scalable solution for real-time seizure detection in clinical environments.

Keywords: electroencephalogram, epileptic seizure, deep learning, LSTM, CNN, BI-LSTM, seizure detection

Procedia PDF Downloads 13

Authors: Tawfik Thelaidjia, Salah Chenikher

Abstract:

Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach

Keywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement

Procedia PDF Downloads 437

Authors: Alhulw H. Alshammari, Ahmed Iraqi, S. A. Saad, T. A. Taha

Abstract:

In this work, we present for the first time the study of Raman spectra and dielectric relaxation of polyester polymer-CoFe₂O₄ (5.0, 10.0, 15.0, and 20.0 wt%) nanocomposites. Raman spectroscopy was applied as a sensitive structural identification technique to characterize the polyester-CoFe₂O₄ nanocomposites. The images of AFM confirmed the uniform distribution of CoFe₂O₄ inside the polymer matrix. Dielectric relaxation was employed as an important analytical technique to obtain information about the ability of the polymer nanocomposites to store and filter electrical signals. The dielectric relaxation analyses were carried out on the polyester-CoFe₂O₄ nanocomposites at different temperatures. An increase in dielectric constant ε₁ was observed for all samples with increasing temperatures due to the alignment of the electric dipoles with the applied electric field. In contrast, ε₁ decreased with increasing frequency. This is attributed to the difficulty for the electric dipoles to follow the electric field. The α relaxation peak that appeared at a high frequency shifted to higher frequencies when increasing the temperature. The activation energies for Maxwell-Wagner Sillar (MWS) changed from 0.84 to 1.01 eV, while the activation energies for α relaxations were 0.54 – 0.94 eV. The conduction mechanism for the polyester- CoFe₂O₄ nanocomposites followed the correlated barrier hopping (CBH) model.

Keywords: AC conductivity, activation energy, dielectric permittivity, polyester nanocomposites

Procedia PDF Downloads 114

Authors: Paul V. Thomas, Mostafa S. A. Elsayed, Denis Walch

Abstract:

Airframe structural optimization at different design stages results in new mass and stiffness distributions which modify the critical design loads envelop. Determination of aircraft critical loads is an extensive analysis procedure which involves simulating the aircraft at thousands of load cases as defined in the certification requirements. It is computationally prohibitive to use a Global Finite Element Model (GFEM) for the load analysis, hence reduced order structural models are required which closely represent the dynamic characteristics of the GFEM. This paper presents the implementation of Component Mode Synthesis (CMS) method for the generation of high fidelity Reduced Order Model (ROM) of complex airframes. Here, sub-structuring technique is used to divide the complex higher order airframe dynamical system into a set of subsystems. Each subsystem is reduced to fewer degrees of freedom using matrix projection onto a carefully chosen reduced order basis subspace. The reduced structural matrices are assembled for all the subsystems through interface coupling and the dynamic response of the total system is solved. The CMS method is employed to develop the ROM of a Bombardier Aerospace business jet which is coupled with an aerodynamic model for dynamic aeroelasticity loads analysis under gust turbulence. Another set of dynamic aeroelastic loads is also generated employing a stick model of the same aircraft. Stick model is the reduced order modelling methodology commonly used in the aerospace industry based on stiffness generation by unitary loading application. The extracted aeroelastic loads from both models are compared against those generated employing the GFEM. Critical loads Modal participation factors and modal characteristics of the different ROMs are investigated and compared against those of the GFEM. Results obtained show that the ROM generated using Craig Bampton CMS reduction process has a superior dynamic characteristics compared to the stick model.

Keywords: component mode synthesis, craig bampton reduction method, dynamic aeroelasticity analysis, model order reduction

Procedia PDF Downloads 209

Authors: Dávid Kovács, Bálint Csanády, Dániel Boros, Iván Ivkovic, Lóránt Nagy, Dalma Tóth-Lakits, László Márkus, András Lukács

Abstract:

The modeling practice of financial instruments has seen significant change over the last decade due to the recognition of time-dependent and stochastically changing correlations among the market prices or the prices and market characteristics. To represent this phenomenon, the Stochastic Correlation Process (SCP) has come to the fore in the joint modeling of prices, offering a more nuanced description of their interdependence. This approach has allowed for the attainment of realistic tail dependencies, highlighting that prices tend to synchronize more during intense or volatile trading periods, resulting in stronger correlations. Evidence in statistical literature suggests that, similarly to the volatility, the SCP of certain stock prices follows rough paths, which can be described using fractional differential equations. However, estimating parameters for these equations often involves complex and computation-intensive algorithms, creating a necessity for alternative solutions. In this regard, the Fractional Ornstein-Uhlenbeck (fOU) process from the family of fractional processes offers a promising path. We can effectively describe the rough SCP by utilizing certain transformations of the fOU. We employed neural networks to understand the behavior of these processes. We had to develop a fast algorithm to generate a valid and suitably large sample from the appropriate process to train the network. With an extensive training set, the neural network can estimate the process parameters accurately and efficiently. Although the initial focus was the fOU, the resulting model displayed broader applicability, thus paving the way for further investigation of other processes in the realm of financial mathematics. The utility of SCP extends beyond its immediate application. It also serves as a springboard for a deeper exploration of fractional processes and for extending existing models that use ordinary Wiener processes to fractional scenarios. In essence, deploying both SCP and fractional processes in financial models provides new, more accurate ways to depict market dynamics.

Keywords: fractional Ornstein-Uhlenbeck process, fractional stochastic processes, Heston model, neural networks, stochastic correlation, stochastic differential equations, stochastic volatility

Procedia PDF Downloads 118

Authors: S. K. M. Nzaba, H. H. Nyoni, B. Ntsendwana, B. B. Mamba, A. T. Kuvarega

Abstract:

Azo dye effluents, released into water bodies are not only toxic to the ecosystem but also pose a serious impact on human health due to the carcinogenic and mutagenic effects of the compounds present in the dye discharge. Conventional water treatment methods such as adsorption, flocculation/coagulation and biological processes are not effective in completely removing most of the dyes and their natural degradation by-products. Advanced oxidation processes (AOPs) have proven to be effective technologies for complete mineralization of these recalcitrant pollutants. Therefore, there is a need for new technology that can solve the problem. Thus, this study examined the photocatalytic degradation of an azo dye brilliant black (BB) using non-metal/metal codoped TiO₂. N, Pt co-doped TiO₂ photocatalysts were prepared by a modified sol-gel method using amine-terminated polyamidoamine dendrimer generation 0 (PAMAM G0), amine-terminated polyamidoamine dendrimer generation 1 ( PAMAM G1) and hyperbranched polyethyleneimine (HPEI) as templates and source of nitrogen. Structural, morphological, and textural properties were evaluated using scanning electron microscopy coupled to energy dispersive X-ray spectroscopy (SEM/EDX), high-resolution transmission electron microscopy (HRTEM), X-ray diffraction spectroscopy (XRD), X-ray photoelectron spectroscopy (XPS), thermal gravimetric analysis (TGA), Fourier- transform infrared (FTIR), Raman spectroscopy (RS), photoluminescence (PL) and ultra-violet /visible spectroscopy (UV-Vis). The synthesized photocatalysts exhibited lower band gap energies as compared to the Degussa P-25 revealing a red shift in band gap towards the visible light absorption region. Photocatalytic activity of N, Pt co-doped TiO₂ was measured by the reaction of photocatalytic degradation of brilliant black (BB) dye. The N, metal codoped TiO₂ containing 0.5 wt. % of the metal consisted mainly of the anatase phase as confirmed by XRD results of all three samples, with a particle size range of 13–30 nm. The particles were largely spherical and shifted the absorption edge well into the visible region. Band gap reduction was more pronounced for the N, Pt HPEI (Pt 0.5 wt. %) codoped TiO₂ compared to PAMAM G0 and PAMAM G1. Consequently, codoping led to an enhancement in the photocatalytic activity of the materials for the degradation of brilliant black (BB).

Keywords: codoped TiO₂, dendrimer, photodegradation, wastewater

Procedia PDF Downloads 173

Authors: Anupama Sekhar, Preeti Saryan, Vinita Gowda

Abstract:

Plants, due to their sedentary lifestyle, have evolved mechanisms to synthesize a huge diversity of complex, specialized chemical metabolites, a majority of them being volatile organic compounds (VOCs). These VOCs are heavily involved in their biotic and abiotic interactions. Since chemical composition could be under the same selection processes as other morphological characters, we test if VOCs can be used to taxonomically distinguish species in the well-studied, fragrant ginger genus -Hedychium (Zingiberaceae). We propose that variations in the volatile profiles are suggestive of adaptation to divergent environments, and their presence could be explained by either phylogenetic conservatism or ecological factors. In this study, we investigate the volatile chemistry within Hedychium, which is endemic to Asian palaeotropics. We used an unsupervised clustering approach which clearly distinguished most taxa, and we used ancestral state reconstruction to estimate phylogenetic signals and chemical trait evolution in the genus. We propose that taxonomically, the chemical composition could aid in species identification, especially in species complexes where taxa are not morphologically distinguishable, and extensive, targeted chemical libraries will help in this effort.

Keywords: chemotaxonomy, dynamic headspace sampling, floral fragrance, floral volatile evolution, gingers, Hedychium

Procedia PDF Downloads 95

Authors: Mohammad Hadi Khorashadi Zadeh ‎

Abstract:

An entrepreneur is a manager or the owner of the commercial company that creates resources and money by risking and initiative. The Netpreneur is the capability to run an online business. It needs only the Connectivity. An Entrepreneur, as long as he has a service which the market demands can set up a feasible and viable trade with his Intellectual Capital as the principle input and the Connectivity Infrastructure as the only physical input. The internet is possibly the most significant revolution in science and technology that our generation could fantasize or imagine. It has introduced in various benefits to the society, culture, economics and politics. The entrepreneur is a premium member in the community. She/he provides services to the society and community including employment.

Keywords: entrepreneur, Netpreneur, intellectual capital, infrastructure

Procedia PDF Downloads 327

Authors: Markus Meyer, Bastian Maucher, Rolf Witzmann

Abstract:

The ever increasing amount of distributed generation in low voltage distribution grids (mainly PV and micro-CHP) can lead to reverse load flows from low to medium/high voltage levels at times of high feed-in. Reverse load flow leads to rising voltages that may even exceed the limits specified in the grid codes. Furthermore, the share of electrical loads connected to low voltage distribution grids via switched power supplies continuously increases. In combination with inverter-based feed-in, this results in high harmonic levels reducing overall power quality. Especially high levels of third-order harmonic currents can lead to neutral conductor overload, which is even more critical if lines with reduced neutral conductor section areas are used. This paper illustrates a possible concept for smart grids in order to increase the feed-in capacity, improve power quality and to ensure safe operation of low voltage distribution grids at all times. The key feature of the concept is a hierarchically structured control strategy that is run on a superordinated controller, which is connected to several distributed grid analyzers and inverters via broad band powerline (BPL). The strategy is devised to ensure both quick response time as well as the technically and economically reasonable use of the available inverters in the grid (PV-inverters, batteries, stepless line voltage regulators). These inverters are provided with standard features for voltage control, e.g. voltage dependent reactive power control. In addition they can receive reactive power set points transmitted by the superordinated controller. To further improve power quality, the inverters are capable of active harmonic filtering, as well as voltage balancing, whereas the latter is primarily done by the stepless line voltage regulators. By additionally connecting the superordinated controller to the control center of the grid operator, supervisory control and data acquisition capabilities for the low voltage distribution grid are enabled, which allows easy monitoring and manual input. Such a low voltage distribution grid can also be used as a virtual power plant.

Keywords: distributed generation, distribution grid, power quality, smart grid, virtual power plant, voltage control

Procedia PDF Downloads 267

Authors: Aliyu Mohammed Lawal

Abstract:

The problems placed on the environment as a result of energy generation and usage in Nigeria is: potential damage to the environment health by CO, CO2, SOx, and NOx, effluent gas emissions and global warming. For instance in the year 2004 in Nigeria energy consumption was 58% oil and 34% natural gas but about 94 million metric tons of CO2 was emitted out of which 64% came from fossil fuels while about 35% came from fuel wood. The findings from this research on how to alleviate these problems are that long term sustainable development solutions should be enhanced globally; energy should be used more rationally renewable energy resources should be exploited and the existing emissions should be controlled to tolerate limits because the increase in energy demand in Nigeria places enormous strain on current energy facilities.

Keywords: effluent gas, emissions, NOx, SOx

Procedia PDF Downloads 381

Authors: D. Artamonov, A. Tsibulnikova, I. Samusev, V. Bryukhanov, A. Kozhevnikov

Abstract:

The synthesis and luminescent properties of Yb₂O₃, Nd₂O₃@Bi₂O₃ complex with upconversion generation are discussed in this work. The obtained samples were measured in the visible region of the spectrum under excitation with a wavelength of 980 nm. The studies showed that the obtained complexes have a high degree of stability and intense luminescence in the wavelength range of 400-750 nm. Consideration of the time dependence of the intensity of the upconversion luminescence allowed us to conclude that the enhancement of the intensity occurs in the time interval from 5 to 30 min, followed by the appearance of a stationary mode.

Keywords: lasers, luminescence, upconversion photonics, rare earth metals

Procedia PDF Downloads 82

Authors: Krishan Kumar, Mohit Mittal, Pramod Kumar

Abstract:

Wireless sensor network is one of the most promising communication networks for monitoring remote environmental areas. In this network, all the sensor nodes are communicated with each other via radio signals. The sensor nodes have capability of sensing, data storage and processing. The sensor nodes collect the information through neighboring nodes to particular node. The data collection and processing is done by data aggregation techniques. For the data aggregation in sensor network, clustering technique is implemented in the sensor network by implementing self-organizing feature map (SOFM) neural network. Some of the sensor nodes are selected as cluster head nodes. The information aggregated to cluster head nodes from non-cluster head nodes and then this information is transferred to base station (or sink nodes). The aim of this paper is to manage the huge amount of data with the help of SOM neural network. Clustered data is selected to transfer to base station instead of whole information aggregated at cluster head nodes. This reduces the battery consumption over the huge data management. The network lifetime is enhanced at a greater extent.

Keywords: artificial neural network, data clustering, self organization feature map, wireless sensor network

Procedia PDF Downloads 517

Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas

Abstract:

This paper presents a comparative evaluation of features extraction algorithm for a real-time isolated word recognition system based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were implemented in hardware/software design. The proposed system was investigated in the speaker-dependent mode for 100 different Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signals to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients give best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose, the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfies the real-time requirements and is suitable for applications in embedded systems.

Keywords: isolated word recognition, features extraction, MFCC, LFCC, LPCC, LPC, FPGA, DTW

Procedia PDF Downloads 495

Authors: Negar Riazifar, Nigel G. Stocks

Abstract:

This paper proposes strategies in level crossing (LC) sampling and reconstruction that provide high fidelity signal reconstruction for speech signals; these strategies circumvent the problem of exponentially increasing number of samples as the bit-depth is increased and hence are highly efficient. Specifically, the results indicate that the distribution of the intervals between samples is one of the key factors in the quality of signal reconstruction; including samples with short intervals do not improve the accuracy of the signal reconstruction, whilst samples with large intervals lead to numerical instability. The proposed sampling method, termed reduced conventional level crossing (RCLC) sampling, exploits redundancy between samples to improve the efficiency of the sampling without compromising performance. A reconstruction technique is also proposed that enhances the numerical stability through linear interpolation of samples separated by large intervals. Interpolation is demonstrated to improve the accuracy of the signal reconstruction in addition to the numerical stability. We further demonstrate that the RCLC and interpolation methods can give useful levels of signal recovery even if the average sampling rate is less than the Nyquist rate.

Keywords: level crossing sampling, numerical stability, speech processing, trigonometric polynomial

Procedia PDF Downloads 146

Authors: Arash Sepehri Bonab

Abstract:

Techniques to switch cells between development and differentiation, which tend to be commonly exclusive, are utilized in arrange to supply an expansive cell mass that can perform particular separated capacities required for the tissue to develop. Approaches to tissue engineering center on the have to give signals to cell populaces to advance cell multiplication and separation. Current tissue regenerative procedures depend primarily on tissue repair by transplantation of synthetic/natural inserts. In any case, restrictions on the existing procedures have expanded the request for tissue designing approaches. Tissue engineering innovation and stem cell investigation based on tissue building have made awesome advances in overcoming the issues of tissue and organ damage, useful loss, and surgical complications. Bone tissue has the capability to recover itself; in any case, surrenders of a basic estimate anticipate the bone from recovering and require extra support. The advancement of bone tissue building has been utilized to form useful options to recover the bone. This paper primarily portrays current advances in tissue engineering in different fields of bone and talks about the long-term trend of tissue designing innovation in the treatment of complex diseases.

Keywords: tissue engineering, bone, technologies, treatment

Procedia PDF Downloads 95

Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee

Abstract:

A purpose of this study is to develop efficient detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive estimation. Due to dependence of radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. Thus, to utilize GNSS for aerospace or ground vehicles requiring high level of safety, unhealthy measurements should be considered seriously. For the reason, this paper proposes adaptive fault detection method to deal with unhealthy measurements in various harsh environments. By the proposed method, the test statistics for fault detection is generated by estimated measurement noise. Pseudorange and carrier-phase measurement noise are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. Performance of the proposed method was evaluated by field-collected GNSS measurements. To evaluate the fault detection capability, intentional faults were added to measurements. The experimental result shows that the proposed detection method is efficient in detecting unhealthy measurements and improves the accuracy of GNSS positioning under fault occurrence.

Keywords: adaptive estimation, fault detection, GNSS, residual

Procedia PDF Downloads 575

Authors: Priyanka Sharma, Manoj Jais, Poonam Gupta, Suraiya K. Ansari, Ravinder Kaur

Abstract:

Introduction: As much as the Health Care is necessary for the population, so is the management of the Biomedical waste produced. Biomedical waste is a wide terminology used for the waste material produced during the diagnosis, treatment or immunization of human beings and animals, in research or in the production or testing of biological products. Biomedical waste management is a chain of processes from the point of generation of Biomedical waste to its final disposal in the correct and proper way, assigned for that particular type of waste. Any deviation from the said processes leads to improper disposal of Biomedical waste which itself is a major health hazard. Proper segregation of Biomedical waste is the key for Biomedical Waste management. Improper disposal of BMW can cause sharp injuries which may lead to HIV, Hepatitis-B virus, Hepatitis-C virus infections. Therefore, proper disposal of BMW is of upmost importance. Health care establishments segregate the Biomedical waste and dispose it as per the Biomedical waste management rules in India. Objectives: This study was done to observe the current trends of Biomedical waste generated in a tertiary care Hospital in Delhi. Methodology: Biomedical waste management rounds were conducted in the hospital wards. Relevant details were collected and analysed and sites with maximum Biomedical waste generation were identified. All the data was cross checked with the commons collection site. Results: The total amount of waste generated in the hospital during January 2014 till December 2014 was 6,39,547 kg, of which 70.5% was General (non-hazardous) waste and the rest 29.5% was BMW which consisted highly infectious waste (12.2%), disposable plastic waste (16.3%) and sharps (1%). The maximum quantity of Biomedical waste producing sites were Obstetrics and Gynaecology wards with a total Biomedical waste production of 45.8%, followed by Paediatrics, Surgery and Medicine wards with 21.2 %, 4.6% and 4.3% respectively. The maximum average Biomedical waste generated was by Obstetrics and Gynaecology ward with 0.7 kg/bed/day, followed by Paediatrics, Surgery and Medicine wards with 0.29, 0.28 and 0.18 kg/bed/day respectively. Conclusions: Hospitals should pay attention to the sites which produce a large amount of BMW to avoid improper segregation of Biomedical waste. Also, induction and refresher training Program of Biomedical waste management should be conducted to avoid improper management of Biomedical waste. Healthcare workers should be made aware of risks of poor Biomedical waste management.

Keywords: biomedical waste, biomedical waste management, hospital-tertiary care, New Delhi

Procedia PDF Downloads 245

Authors: Rashmi Gupta

Abstract:

It is unclear whether arousal or valence modulates the response inhibition process. It has been suggested that irrelevant positive emotional information (e.g., happy faces) and negative emotional information (e.g., angry faces) interact with attention differently. In the present study, we used arousal-matched irrelevant happy and angry faces. These faces were used as stop-signals in the stop-signal paradigm. There were two kinds of trials: go-trials and stop-trials. Participants were required to discriminate between the letter X or O by pressing the corresponding keys on go-trials. However, a stop signal was occasionally presented on stop trials, where participants were required to withhold their motor response. A significant main effect of emotion on response inhibition was observed. It indicated that the valence of a stop signal modulates inhibitory control. We found that stop-signal reaction time was faster in response to irrelevant angry faces than happy faces, indicating that irrelevant angry faces facilitate the response inhibition process compared to happy faces. These results shed light on the interaction of emotion with cognitive control functions.

Keywords: attention, emotion, response inhibition, inhibitory control

Procedia PDF Downloads 104

Authors: Mahabub Alam, Mohammad Mahmudul Hassan, M. Hasanuzzaman, M. Ahasanul Hoque

Abstract:

Animals are transported from one place to another for different purposes in Bangladesh. However, the potential effect of long-distance transport on cattle health has not frequently been studied. Therefore, this study was conducted to assess health conditions of cattle transported from a long distance to Chittagong in Bangladesh. A total of 100 adult cattle, regardless of breed and sex, were selected at Benapole live cattle market in Jessore between August and September 2015 for the study. Blood samples were taken from 50 randomly selected cattle at 0 hours before transportation, just after transportation, at 12-16 hours post-conclusion of transportation, and 24 hours after transportation. The external health conditions and injuries of the cattle were assessed by close inspection, and the trader was interviewed using the structured questionnaire. Images of cattle injuries were taken with a camera. The basic internal health of the cattle was evaluated using standard hemato-biochemical tests. Animals were fasted and remained standing within a small space allocation (8-10 sq feet/animal) in the vehicle during transportation. Animals were provided only with paddy straw and water prior to selling at the destination market. The overall frequency of cattle injuries varied significantly (26% before vs. 47% after transportation; p < 0.001). The frequency of different cattle injuries also significantly varied by types such as abrasion (11% vs. 21%; p < 0.05) and barbed wire injury (9% vs. 18%; p < 0.05). Single cattle injury differed significantly (21% vs. 36%; p < 0.001). Cattle health conditions varied significantly (nasal discharge: 15% vs. 28%; p < 0.05; diarrhea: 15% vs. 23%; p < 0.05 and severe dehydration: 8% vs. 20%; p < 0.001). The values of hemoglobin (Hb), total erythrocyte count (TEC), total leukocyte count (TLC), lymphocyte (L), neutrophil (N) and eosinophil (E) varied significantly (p ≤ 0.01) (Hb: 11.1mg/dl vs. 12.3mg/dl; TEC: 4.7 million/ml vs. 5.7million/ml; TLC: 6.2 thousand/ml vs. 7.3 thousand/ml; L: 61.7% vs. 58.1%; N: 29.7% vs. 32.8%; E: 3.8% vs. 4.7%). The values of serum total protein (TP), creatine kinase (CK), triglyceride (TG), calcium (Ca), phosphorus (P) and alkaline phosphatase (ALP) significantly differed (p ≤ 0.05) (TP: 6.8g/dl vs. 8.2g/dl; CK:574.9u/l vs. 1288u/l; TG: 104.7mg/dl vs. 127.7mg/dl; Ca: 11.3mg/dl vs. 13mg/dl; P: 7.3mg/dl vs. 7.6mg/dl; ALP: 303u/l vs. 363u/l). The identified status of external and internal health conditions of the cattle for trading purpose due to long-distance transportation in the present study indicates a high degree of transport stress and poor animal welfare.

Keywords: animal welfare, cattle, external and internal health conditions, transportation

Procedia PDF Downloads 181

Authors: Yiquan Liao, Quanhong Jiang

Abstract:

Since terahertz was observed by German scientists, we have obtained terahertz through different generation technologies of broadband and narrowband. Then, with the development of semiconductor and other technologies, the imaging technology of terahertz has become increasingly perfect. From the earliest application of nondestructive testing in aviation to the present application of information transmission and human safety detection, the role of terahertz will shine in various fields. The weapons produced by terahertz were epoch-making, which is a crushing deterrent against technologically backward countries. At the same time, terahertz technology in the fields of imaging, medical and livelihood, communication and communication are for the well-being of the country and the people.

Keywords: terahertz, imaging, communication, medical treatment

Procedia PDF Downloads 99

Authors: Muhammad Saleem Ullah Khan Sumbal, Eric Tsui, Ricky Cheong, Eric See To

Abstract:

Organizations are posed to a threat of valuable knowledge loss when employees leave either due to retirement, resignation, job change or because of disabilities e.g. death, etc. Due to changing economic conditions, globalization, and aging workforce, organizations are facing challenges regarding retention of valuable knowledge. On the one hand, large number of employees are going to retire in the organizations whereas on the other hand, younger generation does not want to work in a company for a long time and there is an increasing trend of frequent job change among the new generation. Because of these factors, organizations need to make sure that they capture the knowledge of employee before (s)he walks out of the door. The first step in this process is to know what type of knowledge employee possesses and whether this knowledge is important for the organization. Researchers reveal in the literature that despite the serious consequences of knowledge loss in terms of organizational productivity and competitive advantage, there has not been much work done in the area of knowledge loss assessment of departing employees. An important step in the knowledge retention process is to determine the critical ‘at risk’ knowledge. Thus, knowledge loss risk assessment is a process by which organizations can gauge the importance of knowledge of the departing employee. The purpose of this study is to explore this topic of knowledge loss risk assessment by conducting a qualitative study in oil and gas sector. By engaging in dialogues with managers and executives of the organizations through in-depth interviews and adopting a grounded methodology approach, the research will explore; i) Are there any measures adopted by organizations to assess the risk of knowledge loss from departing employees? ii) Which factors are crucial for knowledge loss assessment in the organizations? iii) How can we prioritize the employees for knowledge retention according to their criticality? Grounded theory approach is used when there is not much knowledge available in the area under research and thus new knowledge is generated about the topic through an in-depth exploration of the topic by using methods such as interviews and using a systematic approach to analyze the data. The outcome of the study will generate a model for the risk of knowledge loss through factors such as the likelihood of knowledge loss, the consequence/impact of knowledge loss and quality of the knowledge loss of departing employees. Initial results show that knowledge loss assessment is quite crucial for the organizations and it helps in determining what types of knowledge employees possess e.g. organizations knowledge, subject matter expertise or relationships knowledge. Based on that, it can be assessed which employee is more important for the organizations and how to prioritize the knowledge retention process for departing employees.

Keywords: knowledge loss, risk assessment, departing employees, Hong Kong organizations

Procedia PDF Downloads 408

Authors: Leili Esmaeilani, Jafar Ghaisari, Mohsen Ahmadian

Abstract:

Hammerstein–Wiener model is a block-oriented model where a linear dynamic system is surrounded by two static nonlinearities at its input and output and could be used to model various processes. This paper contains an optimization approach method for analysing the problem of Hammerstein–Wiener systems identification. The method relies on reformulate the identification problem; solve it as constraint quadratic problem and analysing its solutions. During the formulation of the problem, effects of adding noise to both input and output signals of nonlinear blocks and disturbance to linear block, in the emerged equations are discussed. Additionally, the possible parametric form of matrix operations to reduce the equation size is presented. To analyse the possible solutions to the mentioned system of equations, a method to reduce the difference between the number of equations and number of unknown variables by formulate and importing existing knowledge about nonlinear functions is presented. Obtained equations are applied to an instance H–W system to validate the results and illustrate the proposed method.

Keywords: identification, Hammerstein-Wiener, optimization, quantization

Procedia PDF Downloads 257

Authors: Meena Agrawal, Chaitanya P. Agrawal

Abstract:

The power systems are transforming and becoming smarter with innovations in technologies to enable embark simultaneously upon the sustainable energy needs, rising environmental concerns, economic benefits and quality requirements. The advantages provided by inter-connection of renewable energy resources are becoming more viable and dependable with the smart controlling technologies. The limitation of most renewable resources have their diversity and intermittency causing problems in power quality, grid stability, reliability, security etc. is being cured by these efforts. A necessitate of optimal energy management by intelligent Micro-Grids at the distribution end of the power system has been accredited to accommodate sustainable renewable Distributed Energy Resources on large scale across the power grid. All over the world Smart Grids are emerging now as foremost concern infrastructure upgrade programs. The hardware setup includes NI cRIO 9022, Compact Reconfigurable Input Output microcontroller board connected to the PC on a LAN router with three hardware modules. The Real-Time Embedded Controller is reconfigurable controller device consisting of an embedded real-time processor controller for communication and processing, a reconfigurable chassis housing the user-programmable FPGA, Eight hot-swappable I/O modules, and graphical LabVIEW system design software. It has been employed for signal analysis, controls and acquisition and logging of the renewable sources with the LabVIEW Real-Time applications. The employed cRIO chassis controls the timing for the module and handles communication with the PC over the USB, Ethernet, or 802.11 Wi-Fi buses. It combines modular I/O, real-time processing, and NI LabVIEW programmable. In the presented setup, the Analog Input Module NI 9205 five channels have been used for input analog voltage signals from renewable energy sources and NI 9227 four channels have been used for input analog current signals of the renewable sources. For switching actions based on the programming logic developed in software, a module having Electromechanical Relays (single-pole single throw) with 4-Channels, electrically isolated and LED indicating the state of that channel have been used for isolating the renewable Sources on fault occurrence, which is decided by the logic in the program. The module for Ethernet based Data Acquisition Interface ENET 9163 Ethernet Carrier, which is connected on the LAN Router for data acquisition from a remote source over Ethernet also has the module NI 9229 installed. The LabVIEW platform has been employed for efficient data acquisition, monitoring and control. Control logic utilized in program for operation of the hardware switching Related to Fault Relays has been portrayed as a flowchart. A communication system has been successfully developed amongst the sources and loads connected on different computers using Hypertext transfer protocol, HTTP or Ethernet Local Stacked area Network TCP/IP protocol. There are two main I/O interfacing clients controlling the operation of the switching control of the renewable energy sources over internet or intranet. The paper presents experimental results of the briefed setup for intelligent control of the micro-grid for renewable energy sources, besides the control of Micro-Grid with data acquisition and control hardware based on a microcontroller with visual program developed in LabVIEW.

Keywords: data acquisition and control, LabVIEW, microcontroller cRIO, Smart Micro-Grid

Procedia PDF Downloads 333

Authors: Xiaoyu Shen, Fang Fang, Chujun Qiu

Abstract:

Herewith we present a Fourier method for credit risk quantification and allocation in the factor-copula model framework. The key insight is that, compared to directly computing the cumulative distribution function of the portfolio loss via Monte Carlo simulation, it is, in fact, more efficient to calculate the transformation of the distribution function in the Fourier domain instead and inverting back to the real domain can be done in just one step and semi-analytically, thanks to the popular COS method (with some adjustments). We also show that the Euler risk allocation problem can be solved in the same way since it can be transformed into the problem of evaluating a conditional cumulative distribution function. Once the conditional or unconditional cumulative distribution function is known, one can easily calculate various risk metrics. The proposed method not only fills the niche in literature, to the best of our knowledge, of accurate numerical methods for risk allocation but may also serve as a much faster alternative to the Monte Carlo simulation method for risk quantification in general. It can cope with various factor-copula model choices, which we demonstrate via examples of a two-factor Gaussian copula and a two-factor Gaussian-t hybrid copula. The fast error convergence is proved mathematically and then verified by numerical experiments, in which Value-at-Risk, Expected Shortfall, and conditional Expected Shortfall are taken as examples of commonly used risk metrics. The calculation speed and accuracy are tested to be significantly superior to the MC simulation for real-sized portfolios. The computational complexity is, by design, primarily driven by the number of factors instead of the number of obligors, as in the case of Monte Carlo simulation. The limitation of this method lies in the "curse of dimension" that is intrinsic to multi-dimensional numerical integration, which, however, can be relaxed with the help of dimension reduction techniques and/or parallel computing, as we will demonstrate in a separate paper. The potential application of this method has a wide range: from credit derivatives pricing to economic capital calculation of the banking book, default risk charge and incremental risk charge computation of the trading book, and even to other risk types than credit risk.

Keywords: credit portfolio, risk allocation, factor copula model, the COS method, Fourier method

Procedia PDF Downloads 167

Authors: Huey-Kuo Chen

Abstract:

Travel demand forecasting including four travel choices, i.e., trip generation, trip distribution, modal split and traffic assignment constructs the core of transportation planning. In its current application, travel demand forecasting has associated with three important issues, i.e., interface inconsistencies among four travel choices, inefficiency of commonly used solution algorithms, and undesirable multiple path solutions. In this paper, each of the three issues is extensively elaborated. An ideal unified framework for the combined model consisting of the four travel choices and variable demand functions is also suggested. Then, a few remarks are provided in the end of the paper.

Keywords: travel choices, B algorithm, entropy maximization, dynamic traffic assignment

Procedia PDF Downloads 458